Volume 2, Issue 3, Special issue on Recent Advances in Engineering Systems (Published Papers)

Articles

Transmit / Received Beamforming for Frequency Diverse Array with Symmetrical frequency offsets

Shaddrack Yaw Nusenu

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1-6 (2017);

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Frequency diverse array (FDA) employs a small frequency increment across its array elements to provide range, angle and time dependent beampattern. In most radar systems, FDA with linear frequency offsets have been employed. But, its transmit beampattern is coupled in range and angle dimensions, which may degrade the output signal-to-interference-plus-noise ratio performance. Note that nonlinear offset is also beneficial in FDA radar. In this paper, symmetrical frequency offsets based FDA is investigated which removes the inherent periodicity of FDA beampattern to achieve a single maxima in the target area. In doing so, the signal information at the receiver is improved significantly. Transmit/received beampatterns, signal-to-interference-plus-noise ratio (SINR) and detection probability of the proposed method are compared with the conventional FDA. Computer simulations are used to verify the effectiveness of the proposed method.

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Detailed Analysis of Amplitude and Slope Diffraction Coefficients for knife-edge structure in S-UTD-CH Model

Eray Arik, Mehmet Baris Tabakcioglu

Adv. Sci. Technol. Eng. Syst. J. 2(3), 7-11 (2017);

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In urban, rural and indoor applications, diffraction mechanism is very important to predict the field strength and calculate the coverage accurately. The diffraction mechanism takes place on NLOS (non-line-of-sight) cases like rooftop, vertex, corner, edge and sharp surfaces. S-UTD-CH model computes three type of electromagnetic wave incidence such as direct, reflected and diffracted waves, respectively. As obstacles in diffraction geometry are in the same or closer height, contribution of the diffraction mechanism is dominant. To predict the diffracted fields accurately, amplitude and slope diffraction coefficients and the derivative of these coefficients have to be taken correctly. In this paper, all the derivations about diffraction coefficients are made for knife edge type structures and extensive simulations are performed in order to analyze the amplitude and diffraction coefficients. In plane angle diffraction, contributions of amplitude and slope diffraction coefficient are maxima.

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Applications of Case Based Organizational Memory Supported by the PAbMM Architecture

Martín, María de los Ángeles, Diván, Mario José

Adv. Sci. Technol. Eng. Syst. J. 2(3), 12-23 (2017);

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In the aim to manage and retrieve the organizational knowledge, in the last years numerous proposals of models and tools for knowledge management and knowledge representation have arisen. However, most of them store knowledge in a non-structured or semi-structured way, hindering the semantic and automatic processing of this knowledge. In this paper we present a more detailed case-based organizational memory ontology, which aims at contributing to the design of an organizational memory based on cases, so that it can be used to learn, reasoning, solve problems, and as support to better decision making as well.

The objective of this Organizational Memory is to serve as base for the organizational knowledge exchange in a processing architecture specialized in the measurement and evaluation. In this way, our processing architecture is based on the C-INCAMI framework (Context-Information Need, Concept model, Attribute, Metric and Indicator) for defining the measurement projects. Additionally, the proposal architecture uses a big data repository to make available the data for consumption and to manage the Organizational Memory, which allows a feedback mechanism in relation with online processing. In order to illustrate its utility, two practical cases are explained: A pasture predictor system, using the data of the weather radar (WR) of the Experimental Agricultural Station (EAS) INTA Anguil (La Pampa State, Argentina) and an outpatient monitoring scenario. Future trends and concluding remarks are extended.

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Low Probability of Interception Beampattern Using Frequency Diverse Array Antenna

Shaddrack Yaw Nusenu

Adv. Sci. Technol. Eng. Syst. J. 2(3), 24-29 (2017);

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Frequency diverse array (FDA) antenna employs a small frequency increment, as compared with the carrier frequency, across antenna array elements. The use of a frequency increment generates an array factor that is dependent on angle, time, and the range and this yields a range and angle dependent beampattern. In this paper, a transmit array beamforming FDA employing costa sequence frequency increments is proposed that offers low probability of interception (LPI) for radar systems. Because active radars are highly visible to intercept receivers, FDA beam with uniform linear array and non-linearly increasing frequency offsets to reduce the system visibility is replaced by the conventional high gain phased-array antenna beam. The proposed method produce random-like peak distribution without obvious peaks making it difficult to be detected by unfriendly detector or intercept receivers without known of the specified coding sequence for the frequency increments. Numerical simulation results verify the proposed method.

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Zero Trust Cloud Networks using Transport Access Control and High Availability Optical Bypass Switching

Casimer DeCusatis, Piradon Liengtiraphan, Anthony Sager

Adv. Sci. Technol. Eng. Syst. J. 2(3), 30-35 (2017);

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Cyberinfrastructure is undergoing a radical transformation as traditional enterprise and cloud computing environments hosting dynamic, mobile workloads replace telecommunication data centers. Traditional data center security best practices involving network segmentation are not well suited to these new environments. We discuss a novel network architecture, which enables an explicit zero trust approach, based on a steganographic overlay, which embeds authentication tokens in the TCP packet request, and first-packet authentication. Experimental demonstration of this approach is provided in both an enterprise-class server and cloud computing data center environment.

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A Derived Metrics as a Measurement to Support Efficient Requirements Analysis and Release Management

Indranil Nath

Adv. Sci. Technol. Eng. Syst. J. 2(3), 36-40 (2017);

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This paper presents a Release Management model to support requirements management. Requirements development and management can be integrated with a release-planning approach to achieve lesser Requirements spillover problems which is an innovative way to capture, control and evolve the user requirements based on integer linear programming.

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Feedback device of temperature sensation for a myoelectric prosthetic hand

Yuki Ueda, Chiharu Ishii

Adv. Sci. Technol. Eng. Syst. J. 2(3), 41-40 (2017);

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In this study, a control system of a feedback device of temperature sensation for myoelectric prosthetic hand users was improved. The device is mounted on a user’s upper arm in contact with the skin, and transfers the temperature sensation in the upper arm corresponding to the temperature detected by the temperature sensor at the fingertip to the user. However, since the feedback device developed in the previous study was controlled in an open loop system, it was difficult to maintain the temperature for a long period. To solve this problem, a closed loop control system was constructed for the feedback device by using a PID controller. In addition, in order to verify the performance of the feedback device controlled in the closed loop control system, performance evaluation experiments were performed. As a result, the sufficient capability of the feedback device controlled in the closed loop control system was indicated. Finally, temperature identification experiments were performed based on psychophysical method to verify an effectiveness of the feedback device. As a result, the difference threshold of the feedback device of temperature sensation, 0.62°C was obtained.

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Deep venous thrombus characterization: ultrasonography, elastography and scattering operator

Thibaud Berthomier, Ali Mansour, Luc Bressollette, Frédéric Le Roy, Dominique Mottier

Adv. Sci. Technol. Eng. Syst. J. 2(3), 48-59 (2017);

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A thrombus or a blood clot is the result of blood coagulation which is a natural process to prevent bleeding. An inappropriate formation of a thrombus in a deep vein is known as Deep Venous Thrombosis (DVT). The main complication of a DVT is a Pulmonary Embolism (PE) which occurs when a thrombus breaks loose and travels to the lungs. DVT, PE, or both are also known as Venous thromboembolism (VTE). It affects an estimated 300,000–600,000 Individuals just in the United States per year and can cause considerable morbidity and mortality. This multifactorial disease related to advanced age, immobility, surgery or obesity is an important public health issue. Our project is looking to link the VTE epidemiology (risk factors, patient history, PE) to the thrombus structure. To reach our goals, we are collecting ultrasonography (echogenicity) and elastography (stiffness) of human thrombus. This manuscript describes our approach to create and preprocess a database using Toshiba Aplio 500. Our approaches to characterize the thrombus structure with ultrasound images are also described. The feature extraction is made with the scattering operator. Obtained features are then reduced using Principal Component Analysis and are analyzed to evaluate our approach.

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Improving customs’ border control by creating a reference database of cargo inspection X-ray images

Selina Kolokytha, Alexander Flisch, Thomas Lüthi, Mathieu Plamondon, Adrian Schwaninger, Wicher Vasser, Diana Hardmeier, Marius Costin, Caroline Vienne, Frank Sukowski, Ulf Hassler, Irène Dorion, Najib Gadi, Serge Maitrejean, Abraham Marciano, Andrea Canonica, Eric Rochat, Ger Koomen, Micha Slegt

Adv. Sci. Technol. Eng. Syst. J. 2(3), 60-66 (2017);

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Countries’ effective and efficient border security is becoming increasingly important in today’s global world of economy and trade. To ensure these, customs organisations are responsible for the prevention of illicit goods’ transportation across borders, particularly upon entry. The predicament of the customs administrations will soon be aggravated by both the increase of global trade and the trend towards 100% screening. It is therefore a goal to advance inspection methods to enable successful cargo handling, a scope towards which this research was aimed at. This work was carried out as part of the project ACXIS “Automated Comparison of X-ray Images for cargo Scanning” a European research project within the seventh framework programme answering the call SEC-2012.3.4-1: « Research on Automated Comparison of X-ray Images for cargo Scanning », to improve the process with the largest impact to trade flow: the procedures of freight X-ray scanning. As such, this project was focused on to implementing a manufacturer independent reference database for X-ray images of illicit and non-illicit cargo, developing procedures and algorithms in order to uniform X-ray images of different cargo scanners, and developing a training simulator for inspection officers and a toolbox enclosing several assisted and automated identification techniques for potentially illicit cargo.

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Aviation Navigation with Use of Polarimetric Technologies

Arsen Klochan, Ali Al-Ammouri, Viktor Romanenko, Vladimir Tronko

Adv. Sci. Technol. Eng. Syst. J. 2(3), 67-72 (2017);

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The article deals with the problem of increasing the accuracy of determination of aircraft’s navigation flight parameters. Increasing the accuracy and sensitivity of navigation parameters determination will improve the efficiency of air conveyance by optimizing the flight trajectories and reducing the flight time and simultaneously will ensure the sufficient level of air conveyance safety. The main purpose of this article is to develop a polarimetric navigation method for determining the aircraft’s coordinates during flight. This method can potentially increase the accuracy and sensitivity of navigation parameters determination. The article gives a detailed analysis of the existing methods and systems for determination of aircraft’s navigation parameters, their advantages and the sphere of application. Also the polarimetric navigation method and the system for implementing this method are proposed. The system envisages the use of two measurement channels and consists of two main blocks: the radiation unit and the measurement unit. The practical implementation of the proposed navigation method and system includes the development, creation and use of the polarimetric navigation system. The results of system’s mathematical modeling are given and the optimum parameters of the optical channel elements of the proposed system are determined based on these results. Further research in this area envisages the development and creation of the polarimetric navigation system as well as experimental verifications of the concept. Using a high-precision measuring method, such as polarimetric measurement method, to determine the aircraft’s navigation flight parameters will significantly improve the safety and efficiency of the airlines industry.

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Optimization of Multi-standard Transmitter Architecture Using Single-Double Conversion Technique Used for Rescue Operations

Riadh Essaadali, Said Aliouane, Chokri Jebali and Ammar Kouki

Adv. Sci. Technol. Eng. Syst. J. 2(3), 73-81 (2017);

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A new architecture of multi-standard transmitter that combines single and double frequency conversion is presented. The transmitter is able to generate waveforms of different cellular standards (GSM, UMTS, Wimax), LAN standards (Bluetooth, Zigbee, IEEE802.11 b/g) and Radio navigation standards (GPS, Galileo) as well. Depending on the selected standard and frequency, the transmitter routes the intermediate frequency signal, into direct or double conversion path. Optimization design techniques are introduced to manage multiple standards and efficiently enable them while reducing cost, size and weight of the resulting transmitter. Such a transmitter is aimed to be used as a backup solution for a broken network to reestablish and insure communication links for rescue operations.

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Singular Integral Equations in Electromagnetic Waves Reflection Modeling

A. S. Ilinskiy, T. N. Galishnikova

Adv. Sci. Technol. Eng. Syst. J. 2(3), 82-87 (2017);

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The processes of reflection of three-dimensional electromagnetic waves by locally irregular media interfaces are investigated. The problem under study is mathematically reduced to the solution of a boundary value problem for the Maxwell equations in an infinite space with an irregular boundary. In order to develop a numerical algorithm, the potential theory and a special Green’s function are applied to reduce the addressed boundary problem to an equivalent system of two hypersingular integral equations. This system is solved with the use of the approximation and collocation method. Special attention is focused on calculation of the kernels of these equations. Results of simulation of the currents induced on the irregularity and reflected field patterns in the resonance frequency range are presented.

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Methodology for Management of Information Security in Industrial Control Systems: A Proof of Concept aligned with Enterprise Objectives

Fabian Bustamante, Walter Fuertes, Paul Diaz, Theofilos Toulqueridis

Adv. Sci. Technol. Eng. Syst. J. 2(3), 88-99 (2017);

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This article is an extended version of the study presented at the IEEE Ecuador Technical Chapters Meeting (ETCM)-2016. At that time, a methodological proposal was designed, implemented, and applied in a group of industrial plants for the management of the information security of the Industrial control systems (ICS). The present study displays an adaptation and improvement of such methodology with the purpose of aligning the proposal for the effective management of information security with the strategic objectives. The development of this study has been divided into three distinctive phases. Firstly, we induced the articulation of PMI-PMBOK v5 and ITIL v3 both for the management of the project and for the verification of risks in the IT services. Second, we applied a set of risk mitigation strategies based on international standards as NIST 800-82 and 800-30. Thirdly, we assembled the two mentioned phases in a Guide for standards-based instructions and security policies, which previously have been encouraged on NIST 800-82, 800-53 and 800-12. Hereby, we observed the reduction of incidents of information security, the correct delimitation of the functions of the direct responsible of the ICS and the improvement of the communication between the operative and technical areas of the involved companies. The results demonstrate the functionality of these improvements, especially in the context of the availability and integrity of information, which generates an added value to the enterprise.

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Dependence-Based Segmentation Approach for Detecting Morpheme Boundaries

Ahmed Khorsi, Abeer Alsheddi

Adv. Sci. Technol. Eng. Syst. J. 2(3), 100-110 (2017);

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The unsupervised morphology processing in the emerging mutant languages has the advantage over the human/supervised processing of being more agiler. The main drawback is, however, their accuracy. This article describes an unsupervised morphemes identification approach based on an intuitive and formal definition of event dependence. The input is no more than a plain text of the targeted language. Although the original objective of this work was classical Arabic, the test was conducted on an English set as well. Tests on these two languages show a very acceptable precision and recall. A deeper refinement of the output allowed 89% precision and 78% recall on Arabic.

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Paper Improving Rule Based Stemmers to Solve Some Special Cases of Arabic Language

Soufiane Farrah, Hanane El Manssouri, Ziyati Elhoussaine, Mohamed Ouzzif

Adv. Sci. Technol. Eng. Syst. J. 2(3), 111-115 (2017);

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Analysis of Arabic language has become a necessity because of its big evolution; we propose in this paper a rule based extraction method of Arabic text to solve some weaknesses founded on previous research works. Our approach is divided on preprocessing phase, on which we proceed to the tokenization of the text, and formatting it by removing any punctuation, diacritics and non-letter characters. Treatment phase based on the elimination of several sets of affixes (diacritics, prefixes, and suffixes), and on the application of several patterns. A check phase that verifies if the root extracted is correct, by searching the result in root dictionaries.

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Medical imbalanced data classification

Sara Belarouci, Mohammed Amine Chikh

Adv. Sci. Technol. Eng. Syst. J. 2(3), 116-124 (2017);

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In general, the imbalanced dataset is a problem often found in health applications. In medical data classification, we often face the imbalanced number of data samples where at least one of the classes constitutes only a very small minority of the data. In the same time, it represent a difficult problem in most of machine learning algorithms. There have been many works dealing with classification of imbalanced dataset. In this paper, we proposed a learning method based on a cost sensitive extension of Least Mean Square (LMS) algorithm that penalizes errors of different samples with different weights and some rules of thumb to determine those weights. After the balancing phase, we apply the different techniques (Support Vector Machine [SVM], K- Nearest Neighbor [K-NN] and Multilayer perceptron [MLP]) for the balanced datasets. We have also compared the obtained results before and after balancing method. We have obtained best results compared to literature with a classification accuracy of 100%.

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ADOxx Modelling Method Conceptualization Environment

Nesat Efendioglu, Robert Woitsch, Wilfrid Utz, Damiano Falcioni

Adv. Sci. Technol. Eng. Syst. J. 2(3), 125-136 (2017);

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The importance of Modelling Methods Engineering is equally rising with the importance of domain specific languages (DSL) and individual modelling approaches. In order to capture the relevant semantic primitives for a particular domain, it is necessary to involve both, (a) domain experts, who identify relevant concepts as well as (b) method engineers who compose a valid and applicable modelling approach. This process consists of a conceptual design of formal or semi-formal of modelling method as well as a reliable, migratable, maintainable and user friendly software development of the resulting modelling tool. Modelling Method Engineering cycle is often under-estimated as both the conceptual architecture requires formal verification and the tool implementation requires practical usability, hence we propose a guideline and corresponding tools to support actors with different background along this complex engineering process. Based on practical experience in business, more than twenty research projects within the EU frame programmes and a number of bilateral research initiatives, this paper introduces the phases, corresponding a toolbox and lessons learned with the aim to support the engineering of a modelling method. ”The proposed approach is illustrated and validated within use cases from three different EU-funded research projects in the fields of (1) Industry 4.0, (2) e-learning and (3) cloud computing. The paper discusses the approach, the evaluation results and derived outlooks.

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GPSR+Predict: An Enhancement for GPSR to Make Smart Routing Decision by Anticipating Movement of Vehicles in VANETs

Zineb Squalli Houssaini, Imane Zaimi, Mohammed Oumsis, Saïd El Alaoui Ouatik

Adv. Sci. Technol. Eng. Syst. J. 2(3), 137-146 (2017);

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Vehicular ad-hoc networks (VANETs) are still more challenging to overcome even if they have been widely studied during the last decades. The routing mechanism is the essentially relevant issue in this field. Indeed, it must strictly to be adapted to specific and unique characteristics such as the high mobility of the vehicles, the dynamic nature of network topology as well as the high link breakage probability. In this paper, our objective is to improve the greedy perimeter stateless routing protocol (GPSR) as being the most promising position-based mechanism. However, according to the impact of position information on routing decision, our proposed approach defined by GPSR+PRedict protocol ensures that each vehicle estimates its own position for the near future. Afterwards, through extensive experiments, we show the ability of the GPSR+PRedict to overcome the observed problems and to enhance the overall performance of the traditional GPSR approach. The simulations are carried out on both highway and urban scenarios by using NS-2 and VanetMobiSim simulators.

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Optimal Synthesis of Universal Space Vector Digital Algorithm for Matrix Converters

Adrian Popovici, Mircea Băbăiţă, Petru Papazian

Adv. Sci. Technol. Eng. Syst. J. 2(3), 147-152 (2017);

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This paper presents the synthesis of a dynamic space vector modulation for power matrix converters so that it is possible to implement a universal modulator that provides a control algorithm dynamically optimized according to the requirements for the matrix converter.

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Control design for axial flux permanent magnet synchronous motor which operates above the nominal speed

Xuan Minh Tran, Nhu Hien Nguyen, Quoc Tuan Duong

Adv. Sci. Technol. Eng. Syst. J. 2(3), 153-159 (2017);

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The axial flux permanent magnet synchronous motor (AFPM motor) using magnet bearings instead of ball-bearings at both two shaft ends could allow rotational speed of shaft much greater than nominal speed. One of the solutions to increase motor speed higher than its nameplate speed is reducing rotor’s pole magnetic flux of rotor (Yp). This paper proposes a method to boost the speed of AFPM motor above nominal speed by adding a reversed current isd of (Yp).

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A synchronizing second order sliding mode control applied to decentralized time delayed multi−agent robotic systems: Stability Proof

Marwa Fathallah, Fatma Abdelhedi, Nabil Derbel

Adv. Sci. Technol. Eng. Syst. J. 2(3), 160-170 (2017);

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This study investigates the synchronization issue of multiple robot manipulators in the presence of time delay. Since several previous works based on synchronization task neglect the communication delay, in this paper we develop a finite time stability based on a Lyaponov functional for synchronization of a networked robotic system where time delay exists during the communication between robots. To this effect, we consider a second order sliding mode control (SMC) combined with the cross coupling concept in order to ensure the position synchronization of networked robot manipulators. Furthermore, the stability of the proposed controller with communication’s delay has been proved. Simulation results illustrate satisfactory performances which prove the efficiency of the proposed approach.

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Fault Diagnosis and Tolerant Control Using Observer Banks Applied to Continuous Stirred Tank Reactor

Martin F. Pico, Eduardo J. Adam

Adv. Sci. Technol. Eng. Syst. J. 2(3), 171-181 (2017);

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This paper focuses on studying the problem of fault tolerant control (FTC), including a detailed fault detection and diagnosis (FDD) module using observer banks which consists of output and unknown input observers applied to a continuous stirred tank reactor (CSTR). The main objective of this paper is to use a FDD module here proposed to estimate the fault in order to apply this result in a FTC system (FTCS), to prevent a lost of of the control system performance. The benefits of the observer bank and fault adaptation here studied are illustrated by numerical simulations which assumes faults in manipulated and measuring elements of the CSTR.

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Development and Validation of a Heat Pump System Model Using Artificial Neural Network

Nabil Nassif, Jordan Gooden

Adv. Sci. Technol. Eng. Syst. J. 2(3), 182-185 (2017);

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Modeling of direct expansion (DX) air conditioning and heat pump systems can be necessary in developing energy saving methods required to reduce energy consumption in buildings. The artificial neural networks (ANN) can be simple and reliable as compared to traditional methods. A properly trained artificial neural network can provide accurate results, while being relatively straightforward and easy in development. This paper discusses the implementation and validation of an artificial neural network modeling technique to predict the performance of a DX air conditioning and heat pump. The model predicts the compressor power as a function of airflow rate, humidity ratio, ambient and mixed air temperatures. Three different leaning algorithms were compared and validated versus the actual data using statistical indexes to determine the most accurate model structures. Experiments were conducted on a 3-ton DX split-system heat pump fully implemented. The heat pump ran over the course of several months to obtain a wide range of measurements. The results showed that artificial neural network can provide very accurate predictions and this ANN model technique can effectively be used for many energy-efficiency heat pump applications.

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Assessment of the usefulness and appeal of stigma-stop by psychology students: a serious game designed to reduce the stigma of mental illness

Adolfo J. Cangas, Noelia Navarro, Juan J. Ojeda, Diego Cangas, Jose A. Piedra, José Gallego

Adv. Sci. Technol. Eng. Syst. J. 2(3), 186-190 (2017);

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The present work describes the first serious game designed to reduce the stigma among students towards mental health problems. The game is called Stigma-Stop, and it features characters who suffer from various mental disorders. Players are provided with information about different mental illnesses, and they are presented with several options on how to act when they encounter characters with these problems. In addition, the game questions the participants as to whether they have ever felt like the individuals portrayed in the game, with the goal of fostering empathy for those that suffer from these types of disorders. Stigma-Stop was applied to a sample of second-year university Psychology students to evaluate the game’s usefulness and appeal. The results demonstrate the importance of this game and that these students consider it to be highly useful. The most notable characteristics are described in depth in the present paper.

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Kinect-Based Moving Human Tracking System with Obstacle Avoidance

Abdel Mehsen Ahmad, Zouhair Bazzal, Hiba Al Youssef

Adv. Sci. Technol. Eng. Syst. J. 2(3), 191-197 (2017);

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This paper is an extension of work originally presented and published in IEEE International Multidisciplinary Conference on Engineering Technology (IMCET). This work presents a design and implementation of a moving human tracking system with obstacle avoidance. The system scans the environment by using Kinect, a 3D sensor, and tracks the center of mass of a specific user by using Processing, an open source computer programming language. An Arduino microcontroller is used to drive motors enabling it to move towards the tracked user and avoid obstacles hampering the trajectory. The implemented system is tested under different lighting conditions and the performance is analyzed using several generated depth images.

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A security approach based on honeypots: Protecting Online Social network from malicious profiles

Fatna Elmendili, Nisrine Maqran, Younes El Bouzekri El Idrissi, Habiba Chaoui

Adv. Sci. Technol. Eng. Syst. J. 2(3), 198-204 (2017);

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In the recent years, the fast development and the exponential utilization of social networks have prompted an expansion of social Computing. In social networks users are interconnected by edges or links, where Facebook, twitter, LinkedIn are most popular social networks websites. Due to the growing popularity of these sites they serve as a target for cyber criminality and attacks. It is mostly based on how users are using these sites like Twitter and others. Attackers can easily access and gather personal and sensitive user’s information. Users are less aware and least concerned about the security setting. And they easily become victim of identity breach. To detect malicious users or fake profiles different techniques have been proposed like our approach which is based on the use of social honeypots to discover malicious profiles in it. Inspired by security researchers who used honeypots to observe and analyze malicious activity in the networks, this method uses social honeypots to trap malicious users. The two key elements of the approach are: (1) The deployment of social honeypots for harvesting information of malicious profiles. (2) Analysis of the characteristics of these malicious profiles and those of deployed honeypots for creating classifiers that allow to filter the existing profiles and monitor the new profiles.

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Pulse Generator for Ultrasonic Piezoelectric Transducer Arrays Based on a Programmable System-on-Chip (PSoC)

Pedro Acevedo, Martín Fuentes, Joel Durán, Mónica Vázquez, Carlos Díaz

Adv. Sci. Technol. Eng. Syst. J. 2(3), 205-209 (2017);

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This paper describes the design of a pulse generator to excite PZT and PVDF ultrasonic transducer arrays, based on the Programmable System-on-Chip (PSoC) module. In this module, using programmable logic different pulses were implemented; these pulses are required in ultrasonic applications for multiple channels to excite PZT and PVDF transducer arrays. To excite multiple elements, bursts are required which can be generated simultaneously or out of phase, generating dynamic wave fronts. For medical applications where bidirectional blood flow is detected burst and quadrature pulses are used. These pulses can be generated independently or in combinations, as simultaneous pulses, shift pulses or burst.  This module can operate with programmable frequencies from 3-74 MHz; its programming may be versatile covering a wide range of ultrasonic applications.

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Enabling Toy Vehicles Interaction With Visible Light Communication (VLC)

M. A. Ilyas, M. B. Othman, S. M. Shah, Mas Fawzi

Adv. Sci. Technol. Eng. Syst. J. 2(3), 210-216 (2017);

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An effective communication among the road users is crucial for safety precautions. Nowadays, a light emitting diode (LED) are commonly installed on a motor vehicle as the lighting system. The LED lights are more reliable and flexible in terms of the design and power adjustments. To further utilize the LED applications in a vehicular system, a simple data transmission system based on LED lights for short distance is developed. Toy vehicles are used to demonstrate the functionality of the system. This paper explains the components used and the communication protocols of A and B that have been developed and tested. The implementations of a software-based modulation and communication protocols by using a microcontroller can be considered as the initial approach that can be further enhanced for future development. In this paper, the prototype of the system as well as the experimental results are presented. The prototypes are able to send short messages by using the LED and photodetector (PD) which could reach up to 2-meter distance.  In addition, it is also believed that this project can be implemented on the real motor vehicles subject to a few improvements.

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Analysis of Fractional-Order 2xn RLC Networks by Transmission Matrices

Mahmut Ün, Manolya Ün

Adv. Sci. Technol. Eng. Syst. J. 2(3), 217-220 (2017);

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In this study, a new method is devised and presented for the dynamic analysis of a 2xn RLC circuit network modeled with the fractional-order circuit elements. The analysis method is based on the principles of dynamic analysis with transfer function approximation. Firstly, the fractional-order 2xn RLC circuit network of interest which is divided into n equal cells connected in cascaded form, then related transmission matrices are individually calculated for each cell correspondingly, Secondly. the transmission matrix of the whole circuit network is calculated based on the properties of the cascaded connection. By means of this transmission matrix and the two-part connection, diagram circuit functions, such as transfer function and the equivalent input impedance of the whole circuit network, are obtained depending on the number of cells (n) and the fractional-order values. Finally, essential dynamic system analysis, such as frequency, step and pulse responses, and the impedance characteristics of the network, are simulated using necessary MATLAB programs depending on cell number n and the fractional-order values.

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Fire extinguishing system in large underground garages

Ivan Antonov, Rositsa Velichkova, Svetlin Antonov, Kamen Grozdanov, Milka Uzunova, Ikram El Abbassi

Adv. Sci. Technol. Eng. Syst. J. 2(3), 221-226 (2017);

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In the work is considered an acceptable constructive scheme from a practical point of view at fire extinguishing in underground garages. The garage space is divided into quadrants which covering, for example, 2 cars. In case of ignition on one of them, a sprinkler nozzle system is triggered by the effect of the vertical convective jet. A protective curtain preventing the spread of fire to adjacent vehicles is realized. The solution is based on an integrated method which allows the calculation from hydrodynamic point of view on extinguishing time of the fire extinguishing system.

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Directional Antenna Modulation Technique using A Two-Element Frequency Diverse Array

Shaddrack Yaw Nusenu

Adv. Sci. Technol. Eng. Syst. J. 2(3), 227-232 (2017);

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Direction dependent antenna modulation (DAM), as a potential physical-layer security technique, is able to enhance the security of wireless communication systems by virtue of the capability of its direction-dependent signal modulation format transmission. In this paper, DAM using frequency diverse array (FDA) to produce the modulation is presented. By phase shifting each element, the desired amplitude and phase of each symbol can be produced during a particular transmission in a given range and angle position determined by the switching speed of the phase shifters. Accordingly, the proposed method offers a robust security for wireless transmission, as the transmitted signal can be purposely distorted in undesired positions, while preserving a clear constellation along prespecified position(s). Numerical examples are given to illustrate the effectiveness of the proposed method.

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Classifying region of interests from mammograms with breast cancer into BIRADS using Artificial Neural Networks

Estefanía D. Avalos-Rivera, Alberto de J. Pastrana-Palma

Adv. Sci. Technol. Eng. Syst. J. 2(3), 233-240 (2017);

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Breast cancer is one of the most common cancers among female diseases all over the world. Early diagnosis and treatment is particularly important in reducing the mortality rate. This research is focused on the prevention of breast cancer, therefore it is important to detect micro-calcifications (MCs) which are a sign of early stage breast cancer. Micro-calcifications are tiny deposits of calcium which are visible on mammograms as they present as tiny white spots. A computer-aided diagnosis system (CAD) is created with the development of computer technology that way radiologists are aided improving their diagnostics while using CAD as a second reader. We are aiming to classify into BIRADS 2, 3 and 4 which are the stages when the cancer can be prevented and a fourth category called No lesion which are veins and tissue that our high pass Gaussian filter detects. This research focuses on classification using ANN (Artificial Neural Network). Experimenting with the categories to classify into using ANN, the results were the following: into the four mentioned before an overall accuracy of 71% was obtained, then joining categories BIRADS 2 and 3 into one and classifying into 3 categories gave an 80% of accuracy. Joining this two categories was the result of analizing the ROC curve and observation of the ROI images of the MCs as the regions measured are very alike in this two categories and variation is that MCs are more present in BIRADS 3 than in BIRADS 2.  Data matrix was reduced using PCA (Principal Component Analysis) but it did not gave better results so it was discarded as the ANN accuracy to classify was reduced to a 69.8%.

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Magnetically Levitated and Guided Systems

Florian Puci, Miroslav Husak

Adv. Sci. Technol. Eng. Syst. J. 2(3), 241-244 (2017);

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The paper describes the fundamentals of magnetic levitation technology. A general background of the magnetic levitation is given in this article, including applications of this technology, several comparisons with other types of technologies, the real stage of its development, etc. Further in the paper, the two main types of magnetically levitated systems are compared within their subgroups, on characteristics and specifications basis. A comparison between the AC and DC power supplies for these systems, including the pros and cons of each type, is also provided in the paper.

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Energy-Efficient Mobile Sensing in Distributed Multi-Agent Sensor Networks

Minh T. Nguyen

Adv. Sci. Technol. Eng. Syst. J. 2(3), 245-253 (2017);

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In this paper, we exploit an integration between Compressive sensing (CS) and the random mobility of sensors in distributed mobile sensor networks (MSNs). A small number of distributed mobile sensors are deployed randomly in a sensing area to observe a large number of positions. The distributed mobile sensors sparsely sample the sensing area for data collection. At each sampling time, the sensors collect data at their random positions and exchange their readings to the others through their neighbors within the sensor transmission range to form one CS measurement at each sensor. After a certain number of rounds for moving, sensing and sharing data, each mobile sensor creates a sufficient CS measurements to be able to reconstruct all readings from all positions that need to be observed. Network performance is analyzed considering the number of sensors deployed in the networks, the convergence time and the sensor transmission range. Expressions for transmission power consumption are formulated and optimal low power cases are identified.

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Validity and efficiency of conformal anomaly detection on big distributed data

Ilia Nouretdinov

Adv. Sci. Technol. Eng. Syst. J. 2(3), 254-267 (2017);

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Conformal Prediction is a recently developed framework for reliable confident predictions. In this work we discuss its possible application to big data coming from different, possibly heterogeneous data sources. On example of anomaly detection problem, we study the question of saving validity of Conformal Prediction in this case. We show that the straight forward averaging approach is invalid, while its easy alternative of maximizing is not very efficient because of its conservativeness. We propose the third compromised approach that is valid, but much less conservative. It is supported by both theoretical justification and experimental results in the area of energy engineering.

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S-Parameters Optimization in both Segmented and Unsegmented Insulated TSV upto 40GHz Frequency

Juma Mary Atieno, Xuliang Zhang, HE Song Bai

Adv. Sci. Technol. Eng. Syst. J. 2(3), 268-276 (2017);

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Segmented and unsegmented 3D insulated copper through silicon vias (TSVs) of diameter 10 micro-meter, height 100 micro-meter and silicon of sizes 100 micro-meter by 100 micro-meter by 100 micro-meter are modeled using analysis system (ANSYS), equivalent circuit using advanced design system (ADS) at frequency ranges between 100MHz and 40GHz and 10MHz step size. The segmented via is divided into three parts. Each part modeled separately. Scattering parameters are found. The outputs are optimized to give accurate results. The results show that the outputs reflect the transmission characteristics of an ideal TSV.

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Synthesis of Important Design Criteria for Future Vehicle Electric System

Lisa Braun, Eric Sax

Adv. Sci. Technol. Eng. Syst. J. 2(3), 277-283 (2017);

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In this article, we give a brief overview of future trends and corresponding stakeholder requests regarding the design of automotive electric and electronic (e/e)-architectures. While today’s optimization is mainly based on the static design criteria of unit costs and weight, three dynamic design criteria are considered decisive factors in the future: voltage stability, vehicle energy consumption and total cost of ownership. It is shown, how quantitative values for each criterion can be derived, on basis of which different designs of a potential future power supply system could be evaluated. Subsequently, their potential influences on the future system design is discussed.

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Gestural Interaction for Virtual Reality Environments through Data Gloves

G. Rodriguez, N. Jofre, Y. Alvarado, J. Fernández, R. Guerrero

Adv. Sci. Technol. Eng. Syst. J. 2(3), 284-290 (2017);

View Description

In virtual environments, virtual hand interactions play a key role in interactivity and realism allowing to perform fine motions. Data glove is widely used in Virtual Reality (VR) and through simulating a human hands natural anatomy (Avatar’s hands) in its appearance and motion is possible to interact with the environment and virtual objects. Recently, hand gestures are considered as one of the most meaningful and expressive signals. As consequence, this paper explores the use of hand gestures as a mean of Human-Computer Interaction (HCI) for VR applications through data gloves. Using a hand gesture recognition and tracking method, accurate and real-time interactive performance can be obtained. To verify the effectiveness and usability of the system, an experiment of ease learning based on execution’s time was performed. The experimental results demonstrate that this interaction’s approach does not present problems for people more experienced in the use of computer applications. While people with basic knowledge has some problems the system becomes easy to use with practice.

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Solving the Capacitated Network Design Problem in Two Steps

Meriem Khelifi, Mohand Yazid Saidi, Saadi Boudjit

Adv. Sci. Technol. Eng. Syst. J. 2(3), 291-301 (2017);

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In this paper, we propose a two steps-based algorithm to solve the modular link version of the Capacitated Network Design Problem (CNDP) which consists to determine the optimal network that guarantees the routing of a set of commodities. In our proposition, CNDP is divided into two sub-problems: Network Design problem (NDP) and Network Loading Problem (NLP). In the first step, we solved NDP by using the genetic algorithms which select sets of network topologies. In the second step, NLP is solved with the use of Linear programming to evaluate and validate the best network topologies. Simulation results on three real network instances (Atlanta, France and Germany) show that the proposed algorithm is better and more efficient than the Iterative Local Search algorithm.

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A Computationally Intelligent Approach to the Detection of Wormhole Attacks in Wireless Sensor Networks

Mohammad Nurul Afsar Shaon, Ken Ferens

Adv. Sci. Technol. Eng. Syst. J. 2(3), 302-320 (2017);

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A wormhole attack is one of the most critical and challenging security threats for wireless sensor networks because of its nature and ability to perform concealed malicious activities. This paper proposes an innovative wormhole detection scheme to detect wormhole attacks using computational intelligence and an artificial neural network (ANN). Most wormhole detection schemes reported in the literature assume the sensors are uniformly distributed in a network, and, furthermore, they use statistical and topological information and special hardware for their detection. However, these schemes may perform poorly in non-uniformly distributed networks, and, moreover, they may fail to defend against “out of band” and “in band” wormhole attacks. The aim of the proposed research is to develop a detection scheme that is able to detect all kinds of wormhole attacks in both uniformly and non-uniformly distributed sensor networks. Furthermore, the proposed research does not require any special hardware and causes no significant network overhead throughout the network. Most importantly, the probable location of the malicious nodes can be identified by the proposed ANN based detection scheme. We evaluate the efficacy of the proposed detection scheme in terms of detection accuracy, false positive rate, and false negative rate. The performance of the proposed algorithm is also compared with other machine learning techniques (i.e. SVM and regularized nonlinear logistic regression (LR) based detection models). The simulation results show that proposed ANN based algorithm outperforms the SVM or LR based detection schemes in terms of detection accuracy, false positive rate, and false negative rates.

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Real Time Advanced Clustering System

Giuseppe Spampinato, Arcangelo Ranieri Bruna, Salvatore Curti, Viviana D’Alto

Adv. Sci. Technol. Eng. Syst. J. 2(3), 321-326 (2017);

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This paper describes a system to gather information from a stationary camera to identify moving objects. The proposed solution makes only use of motion vectors between adjacent frames, obtained from any algorithm. Starting from them, the system is able to retrieve clusters of moving objects in a scene acquired by an image sensor device. Since all the system is only based on optical flow, it is really simple and fast, to be easily integrated directly in low cost cameras. The experimental results show fast and robust performance of our method.  The ANSI-C code has been tested on the ARM Cortex A15 CPU @2.32GHz, obtaining an impressive fps, about 3000 fps, excluding optical flow computation and I/O. Moreover, the system has been tested for different applications, cross traffic alert and video surveillance, in different conditions, indoor and outdoor, and with different lenses.

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Indoor Mobile Robot Navigation in Unknown Environment Using Fuzzy Logic Based Behaviors

Khalid Al-Mutib, Foudil Abdessemed

Adv. Sci. Technol. Eng. Syst. J. 2(3), 327-337 (2017);

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This paper presents the development and design of a methodology based on fuzzy logic to control an indoor mobile robot for a complete navigation in an unknown environment. The methodology incorporates two basic behaviors, namely: reaching the goal and avoiding obstacles. The obstacle avoidance behavior is treated using wall-following scheme based on an Interval Type-2 Fuzzy Inference technique. .This helps in handling data uncertainties to produce a better performance. The mobile robot control mechanism uses some sort of knowledge base arranged in a set of fuzzy-rule-base to implement the wanted behavior that makes the mobile robot follow the boundary of an obstacle or a wall. A constant distance to the obstacle/wall is maintained while the robot tries successfully to get around this difficulty. Once the path is clear, the obstacle avoidance behavior is inhibited and reaching the goal behavior is activated using a secondary fuzzy controller. This methodology was successfully tested on a real mobile robot for different sort of scenarios. In order to provide better insight into the work’s objective, a comparison work with another method, which uses a Partial Swarm Optimization-Fuzzy method, is carried out based on some defined criteria. The experiment shows a better improvement in the results of the proposed method.

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Validity of Mind Monitoring System as a Mental Health Indicator using Voice

Naoki Hagiwara, Yasuhiro Omiya, Shuji Shinohara, Mitsuteru Nakamura, Masakazu Higuchi, Shunji Mitsuyoshi, Hideo Yasunaga, Shinichi Tokuno

Adv. Sci. Technol. Eng. Syst. J. 2(3), 338-344 (2017);

View Description

We have been developing a method of evaluating the mental health condition of a person based on the sound of their voice. Currently, we have applied this technology to create a smartphone application that shows the vitality and the mental activity as mental health condition indices. Using voice to measure one’s mental health condition is a non-invasive method. Moreover, this application can be used continually through a smartphone call. Unlike a periodic checkup every year, it could be used for monitoring on a daily basis. The purpose of this study is to compare the vitality index to the widely used Beck depression inventory (BDI) and to evaluate its validity. This experiment was conducted at the Center of Innovation Program of the University of Tokyo with 50 employees of one corporation as participants between early December 2015 and early February 2016. Each participant was given a smartphone with our application that recorded his/her voice automatically during calls. In addition, the participants had to read and record a fixed phrase daily. The BDI test was conducted at the beginning of the experimental period. The vitality index was calculated based on the voice data collected during the first two weeks of the experiment and was considered as the vitality index at the time when the BDI test was conducted. When the vitality and the mental activity indicators were compared to BDI score, we found that there was a negative correlation between the BDI score and these indices. Additionally, these indices were a useful method to discriminate a participant of high risk of disease with a high BDI score. And the mental activity index shows a higher performance than the vitality index.

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The Model of Adaptive Learning Objects for virtual environments instanced by the competencies

Carlos Guevara, Jose Aguilar, Alexandra González-Eras

Adv. Sci. Technol. Eng. Syst. J. 2(3), 345-355 (2017);

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This article presents the instantiation of the Model of Adaptation of Learning Objects (MALO) developed in previous works, using the competencies to be developed in a given educational context. MALO has been developed for virtual environments based on an extension of the LOM standard. The model specifies modularly and independently two categories of rules, of adaptation and conversion, giving it versatility and flexibility to perform different types of adaptation to the learning objects, incorporating or removing rules in each category. In this work, we instance these rules of MALO using the competencies considered in a given educational context.

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An Overview of Traceability: Towards a general multi-domain model

Kamal Souali, Othmane Rahmaoui, Mohammed Ouzzif

Adv. Sci. Technol. Eng. Syst. J. 2(3), 356-361 (2017);

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Traceability for some people, is merely a tool to keep a history over something important that happened in the past. For others, is has no added value to their actual processes or products. In fact, it is becoming more and more valued. Traceability is still a vast area of research and an undiscovered field that if it is well used and managed, can provide a set of critical information or lead to something bigger. Many researches are still working to enhance its use and its integration by providing solutions to help users better manage and control their different elements (products, source code, documents, requirements, specifications, etc.). Nowadays, it is used in almost all domains as it can provide reliable information and helps improve efficiency and productivity. In this paper, we first present the state of the art on traceability and its use, through several examples. Then we provide a list of major techniques used in this field and propose our own traceability definition models.

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L-Band SiGe HBT Active Differential Equalizers with Variable, Positive or Negative Gain Slopes Using Dual-Resonant RLC Circuits

Yasushi Itoh, Hiroaki Takagi

Adv. Sci. Technol. Eng. Syst. J. 2(3), 362-368 (2017);

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L-band SiGe HBT active differential equalizers with variable,  positive or negative gain slopes have been designed and fabricated for frequency and temperature compensation of microwave and optical systems. The active equalizer employs dual-resonant RLC circuits in the series feedback path of the differential amplifier for positive gain slopes or in the load for negative gain slopes. The implemented active equalizers have achieved positive gain slopes of +54 to +87dB/GHz across 0.2 to 0.6GHz as well as negative gain slopes of -50 to -100dB/GHz over 0.6 to 1.2GHz. The active differential equalizers presented in this paper have an outstanding feature of providing variable, positive or negative gain slopes, which can be easily adjusted to meet with various stringent requirements for frequency and temperature compensation in microwave and optical systems.

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Moving Towards Reliability-Centred Management of Energy, Power and Transportation Assets

Kang Seng Seow, Loc K. Nguyen, Kelvin Tan, Kees-Jan Van Oeveren

Adv. Sci. Technol. Eng. Syst. J. 2(3), 369-375 (2017);

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Infrastructure Asset Management was first adopted in 1980s for challenges faced by the utilities, road and rail transport systems, mining, process and manufacturing industries in asset life cycle value optimization. International standards ISO 55000 and PAS 55 were subsequently developed to provide a basis for a structured methodology in the development of Asset Management System. This methodology with the basic framework is considered inadequate in addressing the changing and challenging environment faced by the Energy, Power and Transportation sectors. This paper introduces the concept of Reliability-Centred Management System that could leverage on the advancement in Information and Communication Technologies and the entry of the ‘Big Data’ and ‘Smarter Grid’ era.

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Secure Path Selection under Random Fading

Furqan Jameel, Faisal, M Asif Ali Haider, Amir Aziz Butt

Adv. Sci. Technol. Eng. Syst. J. 2(3), 376-383 (2017);

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Application-oriented Wireless Sensor Networks (WSNs) promises to be one of the most useful technologies of this century. However, secure communication between nodes in WSNs is still an unresolved issue. In this context, we propose two protocols (i.e. Optimal Secure Path (OSP) and Sub-optimal Secure Path (SSP)) to minimize the outage probability of secrecy capacity in the presence of multiple eavesdroppers. We consider dissimilar fading at the main and wiretap link and provide detailed evaluation of the impact of Nakagami-m and Rician-K factors on the secrecy performance of WSNs. Extensive simulations are performed to validate our findings. Although the optimal scheme ensures more security, yet the sub-optimal scheme proves to be a more practical approach to secure wireless links.

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Security in SWIPT with Power Splitting Eavesdropper

Furqan Jameel, Faisal, M Asif Ali Haider, Amir Aziz Butt

Adv. Sci. Technol. Eng. Syst. J. 2(3), 384-388 (2017);

View Description

ASimultaneous wireless information and power transfer (SWIPT) has drawn significant research interest in recent years. In this paper, we investigate the information theoretic secrecy of a SWIPT system under Weibull fading channel. To be specific, we analyze the information security in the presence of an energy harvesting and information decoding eavesdropper. All links are subjected to Weibull fading which is more complex than traditional Rayleigh fading. Moreover, we derive closed-form expressions for the probability of strictly positive secrecy capacity and the ergodic secrecy capacity. We evaluate the effect of Weibull shape parameter and power splitting factor on the secrecy performance of SWIPT system. Numerical and simulation results are provided to demonstrate that our findings are instantly applicable on the design of wireless power networks.

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Performance Analysis of Phased Array and Frequency Diverse Array Radar Ambiguity Functions

Shaddrack Yaw Nusenu

Adv. Sci. Technol. Eng. Syst. J. 2(3), 389-394 (2017);

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Radar ambiguity function is widely employed to analyze a radar system’s time delay (range) resolution, Doppler frequency (range rate) resolution, mainlobe width and sidelobes in both range and Doppler. In this paper, ambiguity functions of frequency diverse array (FDA) which offers range-angle dependent transmit beampattern and Phased array which yields angle transmit beampattern is investigated. The FDA and Phased array radar ambiguity function is derived and evaluate its performance characteristics in terms of time-delay and Doppler frequency resolutions. Performance analysis has also been done in terms of empirical cumulative distribution function (ECDF). Simulation and results have verified the effectiveness of both radar systems by comparing their performance characteristics.

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Adaptive Discrete-time Fuzzy Sliding Mode Control For a Class of Chaotic Systems

Hanene Medhaffar, Moez Feki, Nabil Derbel

Adv. Sci. Technol. Eng. Syst. J. 2(3), 395-400 (2017);

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In this paper, we propose an adaptive discrete-time fuzzy sliding mode control for a class of chaotic systems. For this aim, a discrete sliding mode controller and a fuzzy system are combined to achieve an adequate control. The Laypunov stability theorem is used to testify the asymptotic stability of the whole system and the consequence parameters of the adaptive fuzzy system are tuned on-line by adaptive laws. The simulation example of the 3D Henon chaotic model is giving to confirm the effectiveness and the robustness of the proposed method.

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Fault Tolerant Inverter Topology for the Sustainable Drive of an Electrical Helicopter

Igor Bolvashenkov, Jörg Kammermann, Taha Lahlou, Hans-Georg Herzog

Adv. Sci. Technol. Eng. Syst. J. 2(3), 401-411 (2017);

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The paper describes the results of the system analysis of various options of electric inverter topologies for the use in the traction drive of an electrical helicopter. The paper explains the optimal choice, in terms of the design requirements and future operational conditions, and the type and topology of the electric inverter to supply the traction permanent magnet synchronous motor with the batteries. The main focus has been set on the study of the overload capacity, thermal behavior, and the fault tolerance of the multilevel electric inverter. In order to estimate these parameters, the Markov models of the multi-state system’s reliability evaluation were used.

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Computational Intelligence Methods for Identifying Voltage Sag in Smart Grid

Turgay Yalcin, Muammer Ozdemir

Adv. Sci. Technol. Eng. Syst. J. 2(3), 412-419 (2017);

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In recent years pattern recognition of power quality (PQ) disturbances in smart grids has developed into crucial topic for system equipments and end-users. Undoubtedly analyzing the PQ disturbances develop and maintain smart grids effectiveness. Voltage sags are the most common events that affect power quality. These faults are also the most costly. This paper represents performance comparisons of different computer intelligence methods for voltage sag identification. PQube Analyzer which is installed in Ondokuz Mayis University Computer Laboratory for collecting real time disturbances data for each three phases in order to test for proposed algorithms. Firstly, we used Hilbert Huang Transform to genarate Instantaneous Amplitude (IA) feature signal. Then Characteristic features are attained from IA. The 4 features, mean, standard deviation, skewness, kurtosis of IA are calculated. Support Vector Machines (SVMs) and C4.5 Decision Tree methods are conducted for classification of the disturbance. Secondly we used Fishers Discriminant Ratio for selecting statistical features such as mean, standard deviation, skewness and kurtosis of the normal and voltage sag signals for this part K Means Clustering Method were performed for classification of the disturbance. Consecuently, SVMs, C4.5 Decision Tree and K Means Clustering Methods were performed also their achievements were matched for error rates and CPU timing

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A Highly-Secured Arithmetic Hiding cum Look-Up Table (AHLUT) based S-Box for AES-128 Implementation

Ali Akbar Pammu, Kwen-Siong Chong, Bah-Hwee Gwee

Adv. Sci. Technol. Eng. Syst. J. 2(3), 420-426 (2017);

View Description

Side-Channel Attack (SCA) is an effective method in extracting the secret key of cryptographic algorithms by correlating the physical leakage information with the processed data. In this paper, we propose an arithmetic hiding cum Look-up Table (AHLUT) based Substitution-Box (S-Box) in AES-128 cryptographic algorithm implementation to countermeasure against SCA. There are three key features in our proposed AHLUT S-Box. First, the arithmetic hiding performs four types of arithmetic operations such that their total physical leakage information sufficiently overshadows the correlated physical leakage information of the S-Box operation. This is to reduce the correlation of the AES-128 physical leakage information with the processed data. Second, the AHLUT S-Box pre-stores all the 256 bytes of possible output values based on the conventional S-Box and selects a corresponding output value with respect to the input accordingly. In this context, it dissipates significantly lower power when compared to the conventional S-Box which performs multiplication inversion and affine transformation. Third, we propose a methodology to determine a minimum number of the arithmetic operations to sufficiently overshadow the physical leakage information of the S-Box operation. Based on the measurement results of performing AES-128 algorithm on Sakura-X FPGA encryption-board and in term of power dissipation, our proposed AHLUT S-Box dissipates 1.6mW and features 11.56× lower power dissipation than the conventional S-Box. In term of security which is based on Correlation Power Analysis attack, it requires 73× more power traces to reveal the secret key for our proposed AHLUT S-Box than the conventional S-Box. As for the non-invasive Correlation Electromagnetic Analysis attack, it requires 25× more electromagnetic traces for our proposed AHLUT S-Box than the conventional S-Box.

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Service Productivity and Complexity in Medical Rescue Services

Markus Harlacher, Andreas Petz, Philipp Przybysz, Olivia Chaillié, Susanne Mütze-Niewöhner

Adv. Sci. Technol. Eng. Syst. J. 2(3), 427-434 (2017);

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The increasing impact of services on economic wealth and income in high wage countries calls for a detailed examination of service productivity and complexity in current research projects. This paper describes the development of a measurement model of service productivity and complexity within the domain of medical service provision. While the measurement model of service productivity is partly literature-based, a novel construct is developed for service complexity. The reliability and validity of these constructs have been analyzed by a survey with 454 employees of German medical rescue service providers. Reliability of the construct is estimated by analyzing Cronbach’s alpha, average variance extracted, variance inflation factors and the significance, weights and loadings of the items. Furthermore, the relationship between the partial productivities (capacity, internal and external) as well as complexity and service performance is analyzed by using the structural equation modeling approach with partial least square method (PLS-SEM). The results indicate that the developed constructs have sufficient reliability, although the examination of validity highlights difficulties in quantifying service productivity and complexity. While a significant and substantial effect of internal and external efficiency on service performance could be proved, complexity influences performance only marginally and positively while capacity efficiency has no effect at all. Thus, further research is needed in order to foster the measurement model and to investigate possible nonlinear relationships between the constructs in more detail.

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Principal Component Analysis Application on Flavonoids Characterization

Che Hafizah Che Noh, Nor Fadhillah Mohamed Azmin, Azura Amid

Adv. Sci. Technol. Eng. Syst. J. 2(3), 435-440 (2017);

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Flavonoid is one of the bioactive compounds that are currently used in pharmaceutical and medicinal industries due to their health benefit. The focus of current research is mainly on the extraction and isolation of bioactive compounds; however non to date has explored on the identification of flavonoids classes under the Fourier Transform Infrared spectroscopy (FTIR). This gap presents an opportunity for the application of statistical analysis which can identify the distinct wavenumbers range of flavone, flavanone and flavonol for their characterization in the FTIR spectrum. Development of algorithm based on principal component analysis (PCA) for the analysis and identification of flavonoids classes based on FTIR spectrum was introduced. Based on the results, five wavenumbers ranges have been identified as the distinct characteristics of flavonol, flavone and flavanone hence used for their identification.

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A Reconfigurable Metal-Plasma Yagi-Yuda Antenna for Microwave Applications

Giulia Mansutti, Davide Melazzi, Antonio-Daniele Capobianco

Adv. Sci. Technol. Eng. Syst. J. 2(3), 441-448 (2017);

View Description

This paper is an extension of the work originally presented at the European Microwave Conference (EuMC) about a reconfigurable hybrid metal-plasma Yagi-Uda antenna operating at 1.55 GHz: this antenna consists of metallic reflector and active element and two plasma directors. The conference work showed through full-wave numerical simulations (CST Microwave Studio) how it is possible to achieve reconfigurability with respect to the gain by turning on/off the plasma discharges. However the model that was used to represent the plasma discharges was quite ideal, so one comment that was provided questioned the actual possibility of achieving reconfigurability in a real system.
Consequently we performed extensive measurements of different plasma discharges and thanks to the collected data, we noticed some important differences between the full-wave numerical model of the plasma that we used in the conference paper and the actual plasma discharges that were generated in the experimental setup: the dielectric vessel and the metallic electrodes used respectively to confine and generate the plasma have an influence on the radiation pattern of the antenna and so they must be included in the design procedure; the cylindrical plasma discharge is much easier to realize when the cylinder diameter is at least 3mm; and finally the collision frequency of the plasma in realistic cases is pretty higher than the one adopted in our previous work.
Therefore this work presents a feasibility study of a more detailed and realistic model of our antenna with respect to the plasma discharges. We will show that reconfigurability can still be achieved through a proper design of the overall antenna, thus paving the way to an actual realization of the proposed reconfigurable Yagi-Uda.

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Verifying the Detection Results of Impersonation Attacks in Service Clouds

Sarra Alqahtani, Rose Gamble

Adv. Sci. Technol. Eng. Syst. J. 2(3), 449-459 (2017);

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A web service impersonation is a class of attacks in which an attacker poses as or assumes the identity of a legitimate service to maliciously utilize that service’s privileges. Providing security for interacting cloud services requires more than user authentication with passwords or digital certificates and confidentiality in data transmission. In this paper, we focus on the service cloud model, which facilitates the composition and communication among web services owned by different cloud vendors. We develop a distributed mechanism to detect and mitigate impersonation attacks against web services in the cloud. The detection approach monitors the behavior of each service and identifies anomalies as a potential impersonation attack if it deviates significantly from the expected behavior. To verify the impersonation attack, we deploy a cloud-based verification technique, misleading suspicious services with useless responses. The experimental results show that modeling request behavior reliably detects a significant number of impersonation attempts, with a performance degradation that is a reasonable trade-off.

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Image Segmentation Using Fuzzy Inference System on YCbCr Color Model

Alvaro Anzueto-Rios, Jose Antonio Moreno-Cadenas, Felipe Gómez-Castañeda, Sergio Garduza-Gonzalez

Adv. Sci. Technol. Eng. Syst. J. 2(3), 460-468 (2017);

View Description

This paper This paper presents a reliable method for image segmentation using a fuzzy inference system. The Fuzzy Membership function is applied on the YCbCr color space. Triangular membership functions are used in the input of the fuzzy system, Mamdani type fuzzy inference system is applied and for the output universe, singleton-type functions are used; to get the accurate output value, the Weighted Average Method (WAM) is applied. The YCbCr color space is used as feature space. One of the reasons being that it is standardized for the transmission and reception of digital video, (ITU-R Recommendation BT.601-5), and implemented by most of the sensors used in the acquisition of video. The fuzzy membership functions characterize the different membership levels between hue and Chroma from the YCbCr color model. The fuzzy inference system classifies data and generates regions of pixels with a homogeneous color level in the output images. The proposed method was also compared with another system segmentation using Euclidean distance applied to the RGB color space. The best results were obtained in the YCbCr color space. In such model, the changes of hue in presence of illumination variations are considered so that it has a better performance in the segmentation task. In addition, the processing time was lower in this color space.

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Segmented and Detailed Visualization of Anatomical Structures based on Augmented Reality for Health Education and Knowledge Discovery

Isabel Cristina Siqueira da Silva, Gerson Klein, Denise Munchen Brandão

Adv. Sci. Technol. Eng. Syst. J. 2(3), 469-478 (2017);

View Description

The evolution of technology has changed the face of education, especially when combined with appropriate pedagogical bases. This combination has created innovation opportunities in order to add quality to teaching through new perspectives for traditional methods applied in the classroom. In the Health field, particularly, augmented reality and interaction design techniques can assist the teacher in the exposition of theoretical concepts and/or concepts that need of training at specific medical procedures. Besides, visualization and interaction with Health data, from different sources and in different formats, helps to identify hidden patterns or anomalies, increases the flexibility in the search for certain values, allows the comparison of different units to obtain relative difference in quantities, provides human interaction in real time, etc. At this point, it is noted that the use of interactive visualization techniques such as augmented reality and virtual can collaborate with the process of knowledge discovery in medical and biomedical databases. This work discuss aspects related to the use of augmented reality and interaction design as a tool for teaching anatomy and knowledge discovery, with the proposition of an case study based on mobile application that can display targeted anatomical parts in high resolution and with detail of its parts.

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Intrusion detection in cloud computing based attack patterns and risk assessment

Ben Charhi Youssef, Mannane Nada, Bendriss Elmehdi, Regragui Boubker

Adv. Sci. Technol. Eng. Syst. J. 2(3), 479-484 (2017);

View Description

This paper is an extension of work originally presented in SYSCO CONF.We extend our previous work by presenting the initial results of the implementation of intrusion detection based on risk assessment on cloud computing. The idea focuses on a novel approach for detecting cyber-attacks on the cloud environment by analyzing attacks pattern using risk assessment methodologies. The aim of our solution is to combine evidences obtained from Intrusion Detection Systems (IDS) deployed in a cloud with risk assessment related to each attack pattern. Our approach presents a new qualitative solution for analyzing each symptom, indicator and vulnerability analyzing impact and likelihood of distributed and multi-steps attacks directed to cloud environments. The implementation of this approach will reduce the number of false alerts and will improve the performance of the IDS.

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Optimal Sizing and Control Strategy of renewable hybrid systems PV-Diesel Generator-Battery: application to the case of Djanet city of Algeria

Adel Yahiaoui, Khelifa Benmansour, Mohamed Tadjine

Adv. Sci. Technol. Eng. Syst. J. 2(3), 485-491 (2017);

View Description

A method for optimal sizing of hybrid system consisting of a Photovoltaic (PV) panel, diesel generator, Battery banks and load is considered in this paper. To this end a novel approach is proposed. More precisely a methodology for the design and simulation of the behavior of Hybrid system PV-Diesel-Battery banks to electrify an isolated rural site in southern Algeria Illizi (Djanet). This methodology is based on the concept of the loss power supply probability. Sizing and simulation are performed using MATLAB. The technique developed in this study is to determine the number of photovoltaic panels, diesel generators and batteries needed to cover the energy deficit and respond to the growing rural resident energy demand. The obtained results demonstrate the superior capabilities of this proposed method.

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RFID Antenna Near-field Characterization Using a New 3D Magnetic Field Probe

Kassem Jomaa, Fabien Ndagijimana, Hussam Ayad, Majida Fadlallah, Jalal Jomaah

Adv. Sci. Technol. Eng. Syst. J. 2(3), 492-497 (2017);

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In this paper the design of a new 3D magnetic field (H-field) probe with a near-field scanning system is presented, then the near electromagnetic fields radiated by a Library RFID system is characterized. The proposed system is developed in order to determine the magnetic near-field emitted by electronic devices. The designed isotropic H-field probe consists of three orthogonal and identical loops each of diameter of 6 mm having 3 turns. The antenna factor of the designed probe is presented for a frequency range from 10 MHz to 1 GHz. The designed probe is tested and validated using a standard passive circuit as a device under test. An RFID reader antenna is also designed and simulated on HFSS (high frequency structural simulator) and the radiated magnetic field, obtained by simulations, is then compared to the real measured one above the fabricated circuit. The obtained levels are checked if they satisfy the European and ICNIRP Electromagnetic Fields Guidelines.

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Design, Fabrication and Testing of a Dual-Range XY Micro-Motion Stage Driven by Voice Coil Actuators

Xavier Herpe, Matthew Dunnigan, Xianwen Kong

Adv. Sci. Technol. Eng. Syst. J. 2(3), 498-504 (2017);

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Nowadays, compliant micro-motion stages offer high positioning accuracy and repeatability. When assembled with conventional stages, the resulting dual-range positioning systems allow for nanometer scale accuracy within a centimeter scale working area. However, such systems invoke a high cost and large footprint. This paper presents a low-cost, compact compliant XY micro-motion stage where dual-range manipulation has been implemented in an effort to maintain the workspace area and increase the positioning accuracy. The method presented in this work employs the use of a large range/low resolution linear encoder to measure the position of the stage (coarse positioning), before using short range/high resolution capacitive sensors to correct the positioning error (fine positioning). This solution achieves a positioning accuracy close to 1μm within a workspace of ±2.2mm 2.2mm. The compliant stage has been machined from Aluminum 7075-T6 using Wire Electric Discharge Machining (WEDM). This material is well known for its large reversible strain and its suitability for compliant mechanisms.

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Self-Organizing Map based Feature Learning in Bio-Signal Processing

Marwa Farouk Ibrahim Ibrahim, Adel Ali Al-Jumaily

Adv. Sci. Technol. Eng. Syst. J. 2(3), 505-512 (2017);

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Feature extraction is playing a significant role in bio-signal processing. Feature identification and selection has two approaches. The standard method is engineering handcraft which is based on user experience and application area. While the other approach is feature learning that based on making the system identify and select the best features suit the application. The idea behind feature learning is to avoid dealing with any feature extraction or reduction algorithms and to train the suggested model on learning features from input bio-signal by itself. In this paper, Self-Organizing Map (SOM) will be implemented as a feature learning technique to learn the model extract the features from the input data. Deep learning approach will be proposed by deploying SOM to learn features. In the proposed model, the raw data will be read then represented by using different signal representation as Spectrogram, Wavelet and Wavelet Packet.
The newly represented data will be fed to self-organizing map layer to generate features, and finally, the performance of the suggested scheme will be evaluated by applying different classifiers such as Support Vector Machine, Extreme Learning Machine, Evolutionally Extreme Learning Machine and Discriminate Analysis Classification. Analysis of Variance (ANOVA) and confidence interval for different classifiers will be calculated. As an improving step for the results, classifier fusion layer will be implemented to select the most accurate result for both training and testing set. Classifier fusion layer led to a promising training and testing accuracies.

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A delay-dependent distributed SMC for stabilization of a networked robotic system exposed to external disturbances

Fatma Abdelhedi, Nabil Derbel

Adv. Sci. Technol. Eng. Syst. J. 2(3), 513-519 (2017);

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In this paper, a delay-dependent controller based on the sliding mode concept is proposed to stabilize a networked robotic system in a decentralized synchronization scheme. In addition to being affected by communication time-delays between agents, and seen that external disturbances obviously affect any physical and dynamic system, an unsettling action resulting from measurement errors affects the position and the velocity state vectors of agents. Then, it has been proved that the synchronizing algorithm enables cooperative agents, acting in a disturbed environment, to efficiently accomplish a shared task and to compensate delayed communication data. The proposed controller has been implemented in a cooperative robotic system, where the controller proves its robustness face to disturbances.

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Modelization of cognition, activity and motivation as indicators for Interactive Learning Environment

Asmaa Darouich, Faddoul Khoukhi, Khadija Douzi

Adv. Sci. Technol. Eng. Syst. J. 2(3), 520-531 (2017);

View Description

In Interactive Learning Environment (ILE), the cognitive activity and behavior of learners are the center of the researchers’ concerns. The improvement of learning through combining these axes as a structure of indicators for well-designed learning environment, encloses the measurement of the educational activity as a part of the learning process. In this paper, we propose a mathematical modeling approach based on learners actions to estimate the cognitive activity, learning behavior and motivation, in accordance with a proposed course content structure. This Cognitive indicator includes the study of knowledge, memory and reasoning. While, activity indicator aims to study effort, resistance and intensity. The results recovered on a sample of students with different levels of education, assume that the proposed approach presents a relation among all these indicators which is relatively reliable in the term of cognitive system.

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Homemade array of surface coils implementation for small animal magnetic resonance imaging

Fernando Yepes-Calderon, Olivier Beuf

Adv. Sci. Technol. Eng. Syst. J. 2(3), 532-539 (2017);

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Small animal modeling is an exciting research field where human pathogenic frameworks can be replicated in a controlled environment. Accurate Imaging is in high demand when modeling abnormalities and, magnetic resonance imaging plays a vital role due to its demonstrated lowest intrusion when compared with other imaging methods. However, the required high-resolution yields low-quality images and often, critical events are masked. In this manuscript, we improve the images in small animal frameworks by modifying the reception coils to parallelize the readings and by dealing with the mutual induction produced at the dimensions required for the studied subjects.

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An Encryption Key for Secure Authentication: The Dynamic Solution

Zubayr Khalid, Pritam Paul, Khabbab Zakaria, Himadri Nath Saha

Adv. Sci. Technol. Eng. Syst. J. 2(3), 540-544 (2017);

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In modern day technology, the Information Society is at risk. Passwords are a multi-user computer systems usual first line of defence against intrusion. A password may be textual with any combination of alphanumeric characters or biometric or 3-D. But no authentication protocol is fully secured against todays hackers as all of them are Static in type. Dynamic authentication protocol is still a theoretical concept. In this paper, we are focusing on a concept of authentication technique which is actually dynamic in genre, i.e. the password here will change in t time (where t is as small as possible). This technique comprises of both hardware and software part. In this paper, we have covered the idea of generating an efficient algorithm that can work as the final in the Dynamic Password Authentication system. We have used standard deviation within statistics to generalize the possible password which is further secured by Feistel Block Cipher and Advanced Encryption Standard technique (AES), leading and following the said mathematics respectively. In order to allow the system to create variable password in the least time interval possible, we must make sure our process is not much complex.

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Multi-Domain Virtual Network Embedding with Coordinated Link Mapping

Shuopeng Li, Mohand Yazid Saidi, Ken Chen

Adv. Sci. Technol. Eng. Syst. J. 2(3), 545-552 (2017);

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Network Virtualization, which allows the co-existence of various logical networks on shared physical infrastructure, has become popular in recent years. The optimal mapping of virtual resource to physical resource is a major issue in network virtualization. This problem, called virtual network embedding (VNE), has been well explored in the context of one physical domain, which is in practice operated by a single infrastructure provider (InP). However, the needs of virtual network (VN) is rapidly growing, and quite a number of VNs have to be established across multi-domain. For multi-domain VNE, infrastructure providers can no longer just solve their own single domain VNE problem, but have to cooperate to build the whole VN. Therefore, new challenge arises for the multi-domain VNE, compared to traditional single domain VNE. The existing investigations on this problem mainly focus on decomposing a VN to sub VN for each domain, but little attention has been paid to the joint relation between intra-domain and inter-domain (peering) links. In this paper, we propose a multi-domain link mapping method which combines the intra and peering link mapping so as to optimize the overall resource utilization. Our approach is easy to be deployed since it is based on current Internet architecture. Evaluation shows that our approach brings improvements related to existing methods.

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Semantic-less Breach Detection of Polymorphic Malware in Federated Cloud

Yahav Biran, George Collins, Borky John M, Joel Dubow

Adv. Sci. Technol. Eng. Syst. J. 2(3), 553-561 (2017);

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Cloud computing is one of the largest emerging utility services that is expected to grow enormously over the next decade. Many organizations are moving into hybrid cloud/hosted computing models. Single cloud service provider introduces cost and environmental challenges. Also, multi-cloud solution implemented by the Cloud tenant is suboptimal as it requires expensive adaptation costs. Cloud Federation is a useful structure for aggregating cloud based services under a single umbrella to share resources and responsibilities for the benefit of the member cloud service providers. An efficient security model is crucial for successful cloud business. However, with the advent of large scale and multi-tenant environments, the traditional perimeter boundaries along with traditional security practices are changing. Defining and securing asset and enclave boundaries is more challenging, and system perimeter boundaries are more susceptible to breach. This paper to describe security best practices for Cloud Federation. The paper also describes a tool and technique for detecting anomalous behavior in resource usage across the federation participants. This is a particularly serious issue because of the possibility of an attacker potentially gaining access to more than one CSP federation member. Specifically, this technique is developed for Cloud Federations since they have to deal with heterogeneous multi-platform environments with a diverse mixture of data and security log schema, and it has to do this in real time. A Semantic-less Breach detection system that implements a self-learning system was prototyped and resulted in up to 87% True-Positive rate with 93% True-Negative.

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Impact of PSS and SVC on the Power System Transient Stability

Mohammed Omar Benaissa, Samir Hadjeri, Sid Ahmed Zidi

Adv. Sci. Technol. Eng. Syst. J. 2(3), 562-568 (2017);

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The Static Var Compensator (SVC) is used to improve the stability of the power system because of its role in injecting or absorbing the reactive power in the electrical transmission lines. The Power System Stabilizer (PSS) is also a control device which ensures maximum power transfer and thus the stability of the power system enhancement. The PSS has been widely used to damp electromechanical oscillations occur in power systems. If no adequate damping is available, the oscillations will increase leading to instability. The present work is an original contribution to the problem of transient stability in the electrical power system, the authors have made some efforts to illustrate the flexibility and the importance of inserting the SVC alone or with the PSS the fact that maintain the characteristics of the system within acceptable limits in a very short time. The results show that the system has been developed successfully in terms of transient stability in a bi-machine transmission system only with the presence of PSS when a single-phase fault has been occurred, while the presence of SVC is more than essential when a three-phase fault is occurred.

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The Search for a Convergent Option to Deploy Smart Grids on IoT Scenario

Hamilton da Gama Schroder Filho, José Pissolato Filho, Vinicius Luciano Moreli

Adv. Sci. Technol. Eng. Syst. J. 2(3), 569-577 (2017);

View Description

Smart city projects are quickly evolving in several countries as a feasible solution to the urban organization to provide sustainable socioeconomic growth and solve problems that arise as the populations of these cities grow. In this sense, technology application plays an important role in enabling automation of processes, improving the citizen’s quality of life and reducing the costs of public services for municipalities and enterprises. However, automation initiatives of services such as electricity, water, and gas which materialize by the so-called smart grids, have emerged earlier than smart city projects, and are consolidating in several countries. Although smart grid initiatives have arisen earlier to projects of smart cities it represents a subset of the great scenario of IoT that is the vision in which the smart city projects are based. The time difference from developments between these two initiatives made the alternatives of communication technologies for infrastructures construction of communication followed different paths. However, in view of the great scenery of IoT is desirable to determine technologies that provide convergence of a single urban communication infrastructure capable of supporting all applications, whether they are typically IoT or traditional smart grid applications. This work is a review which presents and discusses the two main technologies which are currently best positioned to play this role of convergence that is RF Mesh and LoRaWAN. The strengths and weaknesses of each one of them are also presented and propose that in actuality LoRaWAN is a promising option to offer the required conditions to take on this convergent position.

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Optimizing the Decoding Complexity of PEG-Based Methods with an Improved Hybrid Iterative/Gaussian Elimination Decoding Algorithm

Reem Alkanhel, Marcel Adrian Ambroze

Adv. Sci. Technol. Eng. Syst. J. 2(3), 578-586 (2017);

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This paper focuses on optimizing the decoding complexity of the progressive-edge-growth-based (PEG-based) method for the extended grouping of radio frequency identification (RFID) tags using a hybrid iterative/Gaussian elimination decoding algorithm. To further reduce the decoding time, the hybrid decoding is improved by including an early stopping criterion to avoid unnecessary iterations of iterative decoding for undecodable blocks. Various simulations have been carried out to analyse and assess the performance achieved with the PEG-based method under the improved hybrid decoding, both in terms of missing recovery capabilities and decoding complexities. Simulation results are presented, demonstrating that the improved hybrid decoding achieves the optimal missing recovery capabilities of full Gaussian elimination decoding at a lower complexity, as some of the missing tag identifiers are recovered iteratively.

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FAG – a management support tool with BI techniques to assist teachers in the virtual learning environment Moodle

Luciana Silva Zapparolli, Itana Stiubiener

Adv. Sci. Technol. Eng. Syst. J. 2(3), 587-597 (2017);

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One of the great challenges in distance-learning is to follow the actions of the teachers/tutors and also the actions of students during the process of teaching and learning. This article presents the FAG Tool integrated with the LMS Moodle was developed to help managers of the Distance Education environment to monitor the actions of teachers/tutors and also teachers/tutors in the follow-up of student actions. Through the techniques of Business Intelligence (BI) and Learning Analytics (LA), the tool generates analytical reports and dashboards, presenting a holistic and transversal view, being this vision the differential of this tool. The use of FAG allows teachers/tutors to monitor the participation of all their students in all virtual rooms under their responsibility and thus take corrective measures in the teaching and learning process, such as reducing the risk of avoidance. For the managers, it can be considered as a support tool for decision making regarding the faculty, maintaining or not the teacher/tutor in the process of teaching and learning or even be a base to enlarge or reduce their classes depending on their performance in the virtual environment. Through the use of the FAG, this decision-making can happen during the teaching and learning process and not only after the end, as is usual, because the reports are easy to understand and present accurate information in time to ensure the success of the teaching and learning process.

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A comparative between CRISP-DM and SEMMA through the construction of a MODIS repository for studies of land use and cover change

Herman Jair Gómez Palacios, Robinson Andrés Jiménez Toledo, Giovanni Albeiro Hernández Pantoja, Álvaro Alexander Martínez Navarro

Adv. Sci. Technol. Eng. Syst. J. 2(3), 598-604 (2017);

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Among the most popular methodologies for development of data mining projects are CRISP-DM and SEMMA, This research paper explains the reason why it was decided to compare them from a specific case study. Therefore, this document describes in detail each phase, task and activity proposed by each methodology, applying it in the construction of a MODIS repository for studies of land use and cover change. In addition to the obvious differences between the methodologies, there were found other differences in the activities proposed by each model that are crucial in non-typical studies of data mining. At the same time, this research determines safely the advantages and disadvantages of each model for this type of case studies. When the MODIS product repository construction process was completed, it was found that the additional time used by CRISP-DM in the first phase was composed in the following phases, since the planning, definition of mining goals, and generation of contingency plans, allow developing the proposed phases without inconvenience. It was also demonstrated that CRISP-DM is presented as a true methodology in comparison with SEMMA, because it describes in detail each phase and task through its official documentation and concrete examples of its application.

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Power requirements and battery life measurement for wireless transmission between two nodes in different mediums

Radouane Karli, Abdellatif Bouchalkha, Khalid Alhammadi

Adv. Sci. Technol. Eng. Syst. J. 2(3), 605-611 (2017);

View Description

One of the most important roles of the wireless sensor networks (WSN) is to avoid wiring costs, be self-sustainable and be able to function for several years. However, due to the slow progress in battery technology, power continues to be a limited resource in wireless sensor communication and electric energy storage remains to be an important issue. On the other hand, if batteries must be replaced often, many remote sensing applications may become impractical. Therefore, batteries with long life on the order of several years are needed. This paper is an extension of work originally presented in The 5th International Conference on Electronic Devices, Systems and Applications[1] to investigate further the power requirements for wireless data transfer between two nodes using batteries with different capacities (55 mAh, 550 mAh and 5500 mAh). In particular, the effect of a propagation medium such as air, distilled water and engine oil on the wireless communication inside a one meter long metallic pipe was investigated. Our first result shows a successful transmission of wireless signal through air, distilled water and oil medium with very low transmission losses. The second result shows that an increase in the battery capacity will increase the two-node wireless sensor operation time even in different propagation medium. This result can be used to determine the required battery capacity for extending the WSN operation time.

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A Novel Dual-Band Rectenna for Ambient RF Energy Harvesting at GSM 900 MHz and 1800 MHz

Dinh Khanh Ho, Van-Duc Ngo, Ines Kharrat, Tan Phu Vuong, Quoc Cuong Nguyen, Minh Thuy Le

Adv. Sci. Technol. Eng. Syst. J. 2(3), 612-616 (2017);

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This paper presents a novel dual-band rectenna for RF energy harvesting system. This rectenna is created from a dual-band antenna and a dual-band rectifier which operates at GSM bands (900 MHz and 1800 MHz). The printed monopole antenna is miniaturized by two meander-lines. The received signal from the receiving antenna is rectified by a voltage double using Schottky diode SMS-7630. The rectifier is optimized for low input power level of -20dBm using harmonic balance. Prototype is designed and fabricated. The simulation is validated by measurement with power conversion efficiency of 20% and 40.8% (in measurement) at the input power level of -20dBm. The proposed rectenna has output voltage from 183-415 mV. From the measured results, this rectenna provides the possibility to harvest the ambient electromagnetic energy for powering low-power electronic devices.

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Optimisation of Software-Defined Networks Performance Using a Hybrid Intelligent System

Ann Sabih, Yousif Al-Dunainawi, H. S. Al-Raweshidy, Maysam F. Abbod

Adv. Sci. Technol. Eng. Syst. J. 2(3), 617-622 (2017);

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This paper proposes a novel intelligent technique that has been designed to optimise the performance of Software Defined Networks (SDN). The proposed hybrid intelligent system has employed integration of intelligence-based optimisation approaches with the artificial neural network. These heuristic optimisation methods include Genetic Algorithms (GA) and Particle Swarm Optimisation (PSO). These methods were utilised separately in order to select the best inputs to maximise SDN performance. In order to identify SDN behaviour, the neural network model is trained and applied. The maximal optimisation approach has been identified using an analytical approach that considered SDN performance and the computational time as objective functions. Initially, the general model of the neural network was tested with unseen data before implementing the model using GA and PSO to determine the optimal performance of SDN. The results showed that the SDN represented by Artificial Neural Network ANN, and optmised by PSO, generated a better configuration with regards to computational efficiency and performance index.

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Data Error Detection and Recovery in Embedded Systems: a Literature Review

Venu Babu Thati, Jens Vankeirsbilck, Jeroen Boydens, Davy Pissoort

Adv. Sci. Technol. Eng. Syst. J. 2(3), 623-633 (2017);

View Description

This paper presents a literature review on data flow error detection and recovery techniques in embedded systems. In recent years, embedded systems are being used more and more in an enormous number of applications from small mobile device to big medical devices. At the same time, it is becoming important for embedded developers to make embedded systems fault-tolerant. To make embedded systems fault-tolerant, error detection and recovery mechanisms are effective techniques to take into consideration. Fault tolerance can be achieved by using both hardware and software techniques. This literature review focuses on software-based techniques since hardware-based techniques need extra hardware and are an extra investment in cost per product. Whereas, software-based techniques needed no or limited hardware. A review on various existing data flow error detection and error recovery techniques is given along with their strengths and weaknesses. Such an information is useful to identify the better techniques among the others.

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Augmented Reality Prototype HUD for Passenger Infotainment in a Vehicular Environment

Shu Wang, Vassilis Charissis, David K. Harisson

Adv. Sci. Technol. Eng. Syst. J. 2(3), 634-641 (2017);

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The paper presents a prototype Head Up Display interface which acts as an interactive infotainment system for rear seat younger passengers, aiming to minimize driver distraction. The interface employs an Augmented Reality medium that utilizes the external scenery as a background for two platform games explicitly designed for this system. Additionally, the system provides AR embedded information on major en route landmarks, navigational data, and local news amongst other infotainment options. The proposed design is applied in the peripheral windscreens with the use of a novel Head-Up Display system. The system evaluation by twenty users offered promising results discussed in the paper.

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Incorporating Spatial Information for Microaneurysm Detection in Retinal Images

Mohamed M. Habib, Roshan A. Welikala, Andreas Hoppe, Christopher G. Owen, Alicja R. Rudnicka, Adnan Tufail, Catherine Egan, Sarah A. Barman

Adv. Sci. Technol. Eng. Syst. J. 2(3), 642-649 (2017);

View Description

The presence of microaneurysms(MAs) in retinal images is a pathognomonic sign of Diabetic Retinopathy (DR). This is one of the leading causes of blindness in the working population worldwide. This paper introduces a novel algorithm that combines information from spatial views of the retina for the purpose of MA detection. Most published research in the literature has addressed the problem of detecting MAs from single retinal images. This work proposes the incorporation of information from two spatial views during the detection process. The algorithm is evaluated using 160 images from 40 patients seen as part of a UK diabetic eye screening programme which contained 207 MAs. An improvement in performance compared to detection from an algorithm that relies on a single image is shown as an increase of 2% ROC score, hence demonstrating the potential of this method.

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Human Robot Interaction for Hybrid Collision Avoidance System for Indoor Mobile Robots

Mazen Ghandour, Hui Liu, Norbert Stoll, Kerstin Thurow

Adv. Sci. Technol. Eng. Syst. J. 2(3), 650-657 (2017);

View Description

In this paper, a novel approach for collision avoidance for indoor mobile robots based on human-robot interaction is realized. The main contribution of this work is a new technique for collision avoidance by engaging the human and the robot in generating new collision-free paths. In mobile robotics, collision avoidance is critical for the success of the robots in implementing their tasks, especially when the robots navigate in crowded and dynamic environments, which include humans. Traditional collision avoidance methods deal with the human as a dynamic obstacle, without taking into consideration that the human will also try to avoid the robot, and this causes the people and the robot to get confused, especially in crowded social places such as restaurants, hospitals, and laboratories. To avoid such scenarios, a reactive-supervised collision avoidance system for mobile robots based on human-robot interaction is implemented. In this method, both the robot and the human will collaborate in generating the collision avoidance via interaction. The person will notify the robot about the avoidance direction via interaction, and the robot will search for the optimal collision-free path on the selected direction. In case that no people interacted with the robot, it will select the navigation path autonomously and select the path that is closest to the goal location. The humans will interact with the robot using gesture recognition and Kinect sensor. To build the gesture recognition system, two models were used to classify these gestures, the first model is Back-Propagation Neural Network (BPNN), and the second model is Support Vector Machine (SVM). Furthermore, a novel collision avoidance system for avoiding the obstacles is implemented and integrated with the HRI system. The system is tested on H20 robot from DrRobot Company (Canada) and a set of experiments were implemented to report the performance of the system in interacting with the human and avoiding collisions.

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Multi Level Integrity Management in LTE/LTE-A Networks

Ouafae Kasmi, Amine Baina, Mostafa Bellafkih

Adv. Sci. Technol. Eng. Syst. J. 2(3), 658-668 (2017);

View Description

The sector of telecommunications is experiencing a large growth and rapid change in developing applications due to the variety of technologies, to increase the number of users and to arrival services varied from the high demand of the service quality such as streaming, web navigation. In this regard, the 3rd Generation Partnership Project (3GPP) organization has greatly motivated to develop Next Generation Network (NGN). Indeed, telecom operators are forced to make a portfolio of available services more efficient to ensure customer loyalty. This article aims to propose an incorporation a layer above the quality of service (QoS) controller based on Fuzzy Logic to determine the guaranteed levels of QoS and levels of criticality. It describes a new approach of multi criticality in order to ensure the integrity in IP Multimedia Subsystem (IMS) networks. This approach is based on the recent model of integrity Totel. The proposed approach is tested and evaluated using Fuzzy Inference System to simulate levels of criticality for determining an adequate QoS level that ensures the customer’s needs. The simulation results describe the comparison between three membership function Triangle, Trapezoidal, Gaussian also describes the comparison between the methods of defuzzification to find whose gives better results and has more efficient in the aspect of chance value for levels of QoS and levels of criticality.

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Development of an automated vehicle stop system for cardiac emergencies

Tung T. Nguyen, Issey Takahashi, Takahiro Tanaka, Eijiro Takeuchi, Shinpei Kato, Tatsuya Suzuki, Hitoshi Kanamori, Yoshiki Ninomiya, Hirofumi Aoki

Adv. Sci. Technol. Eng. Syst. J. 2(3), 669-673 (2017);

View Description

This paper describes the concept and configuration of a novel automated safety vehicle stop system, and a future prospect of the study. Intrinsic sudden death may cause traffic accident since such accidents sometimes involve not only the driver but also other traffic users such as passengers and pedestrians. Cardiovascular disease (CVD) is considered as a serious driving risk factor. The pain and others effects of cardiac events degrade driver’s performance, and CVD causes ischemia brought by the CVD induces incapacity of driving. In the automated safety vehicle stop system, which our research group has developed, steer-sensors collects bio-signals and a camera captures the driver’s posture to monitor driver’s incapability. When the driver loses his or her driving capability, the system takes over the maneuver of the vehicle and automatically drives to a safety spot by observing the traffic environment. An emergency scenario was used to demonstrate the system verifying its potential.

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Computer Aided Classification using Support Vector Machines in Detecting Cysts of Jaws

Veena Divya K, Anand Jatti, Revan Joshi P, Sabah Meharaj

Adv. Sci. Technol. Eng. Syst. J. 2(3), 674-677 (2017);

View Description

Jaw cyst is one of the most common pathology observed in the field of dentistry. Early detection of the cystic lesion will help the surgeons to take appropriate therapeutic measures after a thorough diagnostic procedure. One of the challenging task for surgeons is to differentiate the cysts from the other pathologies. The appearance of these pathologies on a radiograph is a complex and confusing task due to the close similarity between the cysts and tumors which is a difficult to differentiate just by its appearance. Hence to resolve this problem, a computer aided classification algorithm is needed for accurate classification of cysts. The work presents a new approach for the determination of the presence or severity of the jaw bone disease aiding the diagnosis and radiotherapy planning. This paper presents texture characterization for the dental panoramic images. The transposed images are analyzed using Gray level co-occurrence matrix(GLCM). The textural properties such as entropy, contrast, correlation, energy and homogeneity are determined for both cyst and non-cystic images. The results obtained are fed to the classification model to classify the given image into normal or abnormal images containing cyst. Support vector machines are chosen for image classification. Image dataset of 30 were used in training and validation. The image set consists of 20 abnormal images and 10 normal images used in image classification.

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Spatiotemporal Traffic State Prediction Based on Discriminatively Pre-trained Deep Neural Networks

Mohammed Elhenawy, Hesham Rakha

Adv. Sci. Technol. Eng. Syst. J. 2(3), 678-686 (2017);

View Description

The availability of traffic data and computational advances now make it possible to build data-driven models that capture the evolution of the state of traffic along modeled stretches of road. These models are used for short-time prediction so that transportation facilities can be operated in an efficient way that guarantees a high level of service. In this paper, we adopted a state-of-the-art machine learning deep neural network and the divide-and-conquer approach to model large road stretches. The proposed approach is expected to be a tool used in daily routines to enhance proactive decision support systems. The proposed approach maintains spatiotemporal correlations between contiguous road segments and is suitable for practical applications because it divides the large prediction problem into a set of smaller overlapping problems. These smaller problems can be solved in a reasonable time using a medium configuration PC. The proposed approach was used to model 21.1- and 30.7-mile stretches of highway along I-15 and I-66, respectively. The resulting predictions were better than predictions obtained using partial least squares regression.

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Low-cost Hybrid Wheelchair Controller for Quadriplegias and Paralysis Patients

Mohammed Faeik Ruzaij Al-Okby, Sebastian Neubert, Norbert Stoll, Kerstin Thurow

Adv. Sci. Technol. Eng. Syst. J. 2(3), 687-694 (2017);

View Description

Wheelchair controller design is very important for handicapped users such as quadriplegia, amputee, paralyzed and elderly. The safe use, easiness, and comfort are an important factor that can directly affect the user’s social efficiency and quality of life. In this paper, the design, implementation, and test of a new low-cost hybrid wheelchair controller for quadriplegics and paralysis patient have been proposed. Two sub-controllers are combined together to build the hybrid controller which are the voice controller and the head tilt controller. The voice controller consists of two voice recognition (VR) modules. The first module uses the dynamic time warping (DTW) and the second used both the hidden Markov model (HMM) and the DTW to process the user’s voice and recognize the required commands. This controller has been tested with three global languages English, German, and Chinese at two different noise levels 42 and 72 dB. The voice controllers can be used for motion commands as well as for controlling other parameters like lights, light signals, sound alarm, etc. The second sub-controller is the head tilt controller. It consists of two sophisticated orientation detection modules BNO055 to detect and track the user’s head and the wheelchair-robot orientation. The controller has an auto-calibrated algorithm to calibrate the user head orientation with reference wheelchair orientation to adjust the control commands and the speed of the system motors in case of ascending or descending a hill or when passing non-straight roads. The head tilt controller was tested successfully for indoor and outdoor applications.

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Preparation of Ni-C Ultrafine Composite from Waste Material

Mahmoud A. Rabah, S.M. Abdelbasir

Adv. Sci. Technol. Eng. Syst. J. 2(3), 695-701 (2017);

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This work depicts the preparation of Ni-C ultrafine composite from used engine oil. The used oil was emulsified with detergent loaded with Ni (OH)2. The loaded emulsion was sprayed on electric plasma generated between two C electrodes to a DC main 28 V and 70-80 A. The purged Ni-doped carbon fume was trapped on a polymer film moistened with synthetic adhesive to fix the trapped smoke. Characterization of the deposit was made using SEM. XRD examined the crystal morphology. Carbon density in the cloud was calculated. The average size and thickness of the deposited composite is 120-160 nm. Aliphatic hydrocarbons readily decompose to gaseous products. Solid carbon smoke originates from aromatic compounds. Plasma heat blasts the oil in short time to decompose in one step.

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Schizophrenia Prediction Using Integrated Imaging Genomic Networks

Su-Ping Deng, Wenxing Hu, Vince D. Calhoun, Yu-Ping Wang

Adv. Sci. Technol. Eng. Syst. J. 2(3), 702-710 (2017);

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In order to increase the diagnosis accuracy of schizophrenia (SCZ) disease, it is essential to comprehensively employ complementary information from multiple types of data. It is well known that a network is a general method for analyzing relationships between patients, with its nodes representing patients and its edges showing relationships between them. In this study, we constructed a fused network using three types of data including genetic, epigenetic and neuroimaging data from a study of schizophrenia patients. We developed a network-based prediction approach taking advantage of the whole network of patients rather than just individual clusters in the network. The majority neighborhood of a node in the network was exploited as a feature for discriminating SCZ from healthy controls. Compared with other 9 graph-based label prediction methods, our network-fusion based label prediction method shows the best performance according to the prediction accuracy. The prediction power of our proposed method was also tested under different parameters settings and an optimal parameter was found for achieving the best performance. The method is also computationally efficient and can be extended to identify other clinical outcomes.

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IGS: The Novel Fast IC Power Ground Network Optimization Flow Based on Improved Gauss-Seidel Method

Qinghao Ye, Xiaoxiao Wang, Jiansong Gong, Songhao Ru, Donglin Su

Adv. Sci. Technol. Eng. Syst. J. 2(3), 711-721 (2017);

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With silicon technology further scaling, the switching activities together with GHz operation frequency greatly affects the power integrity by generating large IR-drop noises. Excessive IR-drop causes functional failures such as timing failure, abnormal reset and SRAM flipping. The PGN needs to be optimized to reduce IR-drop. The traditional EDA optimization routine repeats the steps such as generating layout, extracting parameter and simulation, which greatly increases the cost of integrated circuit design. This paper proposes a novel fast optimization flow optimizing the PGN based on the improved Gauss-Seidel method (IGS), which calculates the accurate IR-drop distribution according to the initial voltage distribution and the 3-D parasitic resistance distribution of PGN. The proposed optimization flow compares the calculated IR-drop distribution with the IR-drop distribution constraints, and changes the parameters of power straps until the performance of PGN meets the requirement of constraints without full chip simulation, which reduces the time cost of PGN optimization. This paper also provides the comparison between the IGS-based optimization flow and traditional EDA optimization routine. The difference of IR-drop distributions calculated by the proposed optimization flow and traditional EDA optimization routine is less than 4.7%. And the PGN optimization time has been reduced by 96.2% on average for ITC99 benchmark s9234, s13207, s35932 and b19. According to the results and analysis, the IGS-based optimization flow is reliable to improve the performance of PGNs.

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GNSS Positioning in Non-line-of-Sight Context—a Survey for Technological Innovation

Julia Breßler, Marcus Obst

Adv. Sci. Technol. Eng. Syst. J. 2(3), 722-731 (2017);

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Reliable, available and accurate localization of people and vehicles is one crucial requirement for intelligent transportation systems (ITSs). This has led to a variety of technical approaches in recent years. Towards an exact positioning via Global Navigation Satellite Systems (GNSSs) the visibility of satellites is an important factor. In this paper, we review the literature regarding the positioning under non-line-of-sight conditions and analyze a range of topics from explicit modeling to empirical data collection. The variety of research indicates a growing interest in robust localization in urban areas. Furthermore, we develop a taxonomy of the technical design for GNSS applications dealing with non-line-of-sight and a typology of the measuring instruments. Both is based on an extensive analysis and review of the state-of-the-art. In doing so, we characterize the current research road map. Thus, the goal of this work is to provide a starting point in terms of the state-of-the-art for further research activities in robust GNSS positioning and the opportunity for technological innovations to ITS.

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Collision avoidance between a wheelchair front wheels and a step wall during step climbing using a care robot

Hidetoshi Ikeda, Kazuki Hashimoto, Daisuke Murayama, Rikuto Yamazaki, Eiji Nakano

Adv. Sci. Technol. Eng. Syst. J. 2(3), 732-740 (2017);

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This paper discusses a step climbing strategy using a wheelchair and a teleoperated care robot that avoids collisions between the wheelchair’s front wheels and the step wall. In our method, the two vehicles are connected and use the velocity difference between them to climb steps. Since the wheelchair’s front wheels, or another part of the wheelchair, tend to collide with the step being mounted while the wheelchair front wheels are in the lifted position, we investigated a system that permits switching between teleoperation and autonomous control to avoid this problem. In our proposed system, the wheelchair step climbing process is performed under autonomous control, while the robot step climbing process is performed under teleoperation control by a remote caregiver. Theoretical analysis and accompanying calculations were performed to clarify the most suitable lifting position for wheelchair front wheels when climbing, and our experimental results show the overall effectiveness of this system.

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Adapting Model Predictive Control for a PV Station and Evaluating two different MPPT Algorithms P&O and FLC

Imad Elzein, Yury Petrenko

Adv. Sci. Technol. Eng. Syst. J. 2(3), 741-748 (2017);

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In this paper first discussion approach will stress out the integration of model predictive control in maximum power point tracking MPPT and as progressing a second approach identified as fuzzy logic controller FLC and perturb & Observe P&O algorithms are analyzed. All are interrelated to MPPT model for a photovoltaic module, PVM, to search for and generate the maximum power; in this case what’s called Pmax. As per the first technique the focus is on the optimal duty ratio, D, for a series of multi diverse types of converters and load matching. The design of the MPPT for a stand-alone photovoltaic power generation system is applied where the system will consist of a solar array with nonlinear time varying characteristics, and a converter with appropriate filters. The integration of model predictive control will be addressed first in this paper. The second fold will implement an MPPT system that use the FLC and compare it with a P&O) algorithm through the utilization of Simulink.

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Human Sit Down Position Detection Using Data Classification and Dimensionality Reduction

Paul Rosero-Montalvo, Daniel Jaramillo, Stefany Flores, Diego Peluffo, Vanessa Alvear, Milton Lopez

Adv. Sci. Technol. Eng. Syst. J. 2(3), 749-754 (2017);

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The analysis of human sit down position is a research area allows for preventing health physical problems in the back. Many works have proposed systems that detect the sitting position, some open issues are still to be dealt with, such as: Cost, computational load, accuracy, portability, and among others. In this work, we present an alternative approach based on an embedded system to acquire the position-related variables and machine learning techniques, namely dimensionality reduction (DR) and classification. Since the information acquired by sensors is high-dimensional and therefore it might not be saved into embedded system memory, for this reason the system has a DR stage based on principal component analysis (PCA) is performed. Subsequently, the posed detection is carried out by the k-nearest neighbors (KNN) classifier between the matrix stored in the system and new data acquired by pressure and distance sensors. Thus, regarding using the whole data set, the computational cost is decreased by 33 % as well as the data reading is reduced by 10 ms. Then, sitting-pose detection task takes 26 ms, and reaches 75% of accuracy in a 4-trial experiment.

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Designing a Smart Car Parking System (PoC) Prototype Utilizing CCTV Nodes: A vision of an IoT parking system via UCD process

Muftah Fraifer, Mikael Fernström

Adv. Sci. Technol. Eng. Syst. J. 2(3), 755-764 (2017);

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Using smart parking systems has become very important, and particularly so for metropolitan areas, because of the benefits for drivers in many aspects, such as time, frustration, stress, and anger, in addition to the increased consumption of fuel while searching for a vacant parking space. This paper proposes a review of recent advances in sensing and communication technology concerning smart parking systems. It includes a brief study of the selected topics and provides an implementation process of those selected systems. Moreover, this work proposes a design approach for a smart car parking system prototype based on utilizing CCTVs (nodes), it is also illustrates the algorithms used for computer vision detection through simulation and real environments, as the system has been deployed in both these environments. Furthermore, the system has been tested and evaluated by stakeholders via a user-centred design process by applying a qualitative research; the promising results demonstrate the effectiveness of our prototype. Finally, this paper discusses the benefits of engaging the stakeholders to develop the prototype.

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Multilingual evaluation of voice disability index using pitch rate

Shuji Shinohara, Yasuhiro Omiya, Mitsuteru Nakamura, Naoki Hagiwara, Masakazu Higuchi, Shunji Mitsuyoshi, Shinichi Tokuno

Adv. Sci. Technol. Eng. Syst. J. 2(3), 765-772 (2017);

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We propose the use of the pitch rate of free-form speech recorded by smartphones as an index of voice disability. This research compares the effectiveness of pitch rate, jitter, shimmer, and harmonic-to-noise ratio (HNR) as indices of voice disability in English, German, and Japanese. Normally, the evaluation of these indices is performed using long-vowel sounds; however, this study included the recitation of a set passage, which is more similar to free-form speech. The results showed that for English, the jitter, shimmer, and HNR were very effective indices for long-vowel sounds, but the shimmer and HNR for read speech were considerably worse. Although the effectiveness of jitter as an index was maintained for read speech, the pitch rate was better in distinguishing between healthy individuals and patients with illnesses affecting their voice. The read speech results in German, Japanese, and English were similar, and the pitch rate showed the greatest efficiency for identification. Nevertheless, compared to English, the identification efficiency for the other two languages was lower.

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Efficacy of multiple anticancer therapies may depend on host immune response

Kritika Karri, Dhundy R Bastola

Adv. Sci. Technol. Eng. Syst. J. 2(3), 773-787 (2017);

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The host immune system is a key player in anticancer therapy response and resistance. Although the impact of host immune response in the ‘war against cancer’ has been studied and it has been the basis for immunotherapy, understanding of its role in attenuating the action of conventional anticancer therapies is an area that has not been fully explored. In spite of advances in systemic therapy, the 5-year survival rate for adenocarcinoma is still a mere 13% and the primary reason for treatment failure is believed to be due to acquired resistance to therapy. Hence, there is a need for identifying reliable biomarkers for guided treatment of lung and colon adenocarcinoma and to better predict the outcomes of specific anticancer therapies. In this work, gene expression data were analyzed using public resources and this study shows how host immune competence underscores the efficacy of various anticancer therapies. Additionally, the result provides insight on the regulation of certain biochemical pathways relating to the immune system, and suggests that smart chemotherapeutic intervention strategies could be based on a patient’s immune profile.

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Interdisciplinarity to Integrate Knowledge in Engineering

Stella Abreu, Amélia Caldeira, Alexandra R. Costa, Tiago Gomes, Luís A. C. Roque

Adv. Sci. Technol. Eng. Syst. J. 2(3), 788-795 (2017);

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This paper is an extension of work originally presented at the 2nd International Conference of the Portuguese Society for Engineering Education and aims to describe an interdisciplinarity teaching experiment involving three subjects of the scientific area of Mathematics and a fourth one in the area of Management. Using only one project, the students developed skills, in an integrated way, in the fields of the subjects involved. The structure of the project is described in detail. It is shown how the knowledge obtained in the different subjects is needed and how it connects together to answer the proposed challenges. We report the progress of the students’ work, the main difficulties and the skills developed during this process. We conclude with a reflection on the main problems and gains that may arise in similar projects.

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Treadmill and Vision System for Human Gait Acquisition and Analysis

Paulo A. Ferreira, João P. Ferreira, Manuel Crisóstomo, A. Paulo Coimbra

Adv. Sci. Technol. Eng. Syst. J. 2(3), 796-804 (2017);

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This paper presents a developed low cost system for human gait analysis. Two web cameras placed in opposite sides of a treadmill are used to acquire images of a person walking at different speeds on a treadmill, carrying a set of passive marks located at strategic places of its body. The treadmill also has passive marks with the color chosen to contrast with the ambient dominant color. The body joint angle trajectories and 3D crossed angles are obtained by image processing of the two opposite side videos. The maximum absolute error for the different joint angles acquired by the system was found to be between 0.4 to 3.5 degrees. With this low cost measurement system the analysis and reconstruction of the human gait can be done with relatively good accuracy, becoming a good alternative to more expensive systems to be used in human gait characterization.

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Assessment of the heat sinking effect of a human hand that holds a flexible phototherapy device for use in Kangaroo Mother Care

Luis Jimenez, Luis Vilcahuaman, Jorge Galdos

Adv. Sci. Technol. Eng. Syst. J. 2(3), 805-811 (2017);

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The heat transfer process from a 6.4 Watt blue light flexible phototherapy mattress to a human hand has been studied. The intended use of the mattress is the provision of neonatal jaundice phototherapy during Kangaroo Mother Care (KMC) or skin-to-skin care. The heat transfer process has been studied with temperature and heat flow sensors inside an expanded- polystyrene spheroid 25mm of thickness where the phototherapy mattress’s non emitting surface is in contact and folded around the hand while the light radiates outwards, to the polystyrene spheroid. The effective thermal capacitance of the phototherapy mattress was calculated as 3.4 J/oK, the mattress-to-hand thermal conductance was found to be 0.25 W/oC, the maximum temperature gradient between the mattress and the palm of the hand was 10oC and the maximum power absorbed by the hand, 2.5W. The palm of the hand skin-to-core temperature gradient was 0.5oC. It is expected that when used in KMC only one half of the hand skin surface would be in contact with the phototherapy mattress so that the effective thermal conductance to the hand in this conditions would be 0.125 W/oC. Further study is suggested to include sweating effect of the hand.

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Network Intrusion Detection System using Apache Storm

Muhammad Asif Manzoor, Yasser Morgan

Adv. Sci. Technol. Eng. Syst. J. 2(3), 812-818 (2017);

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Network security implements various strategies for the identification and prevention of security breaches. Network intrusion detection is a critical component of network management for security, quality of service and other purposes. These systems allow early detection of network intrusion and malicious activities; so that the Network Security infrastructure can react to mitigate these threats. Various systems are proposed to enhance the network security. We are proposing to use anomaly based network intrusion detection system in this work. Anomaly based intrusion detection system can identify the new network threats. We also propose to use Real-time Big Data Stream Processing Framework, Apache Storm, for the implementation of network intrusion detection system. Apache Storm can help to manage the network traffic which is generated at enormous speed and size and the network traffic speed and size is constantly increasing. We have used Support Vector Machine in this work. We use Knowledge Discovery and Data Mining 1999 (KDD’99) dataset to test and evaluate our proposed solution.

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Towards Optimality in Online Learning – The OLeCenT Approach

Carl Beckford, Ezra K. Mugisa

Adv. Sci. Technol. Eng. Syst. J. 2(3), 819-838 (2017);

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Higher Education Institutions (HEIs) employ Learning Management Systems (LMSs) primarily for greater efficiency, profitability, technological advancement or survival. The predominantly used LMSs, Moodle and Blackboard account for in excess of 60% usage by the top HEIs. However, the individual international regions do not necessarily bear the percentages of the overall total. Gaps are identified in optimality in course delivery within online learning when one studies LMSs and their functionalities. Advanced Distributed Learning (ADL) Initiative which was established to standardize and modernize training and education management and delivery, developed and recommended usage of Sharable Content Object Reference Model (SCORM) 2004 and later versions. SCORM 2004 which provides for flexibility in sequencing and navigation for learner-centric course delivery is not supported in any version of the more prevalently used LMSs. It is believed that most people have a preferred way in processing information. We propose codifying one or more Learning Style Instruments (LSIs), diagnosing the preferred teaching approach(es) and dominant/existing learning styles within a batch of learners, then providing course delivery as a best-fit per learner. As a proof of concept, OLeCenT allows the input of one or more course learning paths with real-time learning and automatic reconfiguration of the course path where a new trend or pattern is identified. OLeCenT identified disparity in teaching-learning and provided a mechanism towards improving online learner-centric course delivery. OLeCenT also identified comparative levels of similarities among learners and instructors even where they are deemed to be of different teaching-learning styles/mechanisms.

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An efficient model to improve the performance of platelet inventory of the blood banks

Annista Wijayanayake, Manisha Dandunna

Adv. Sci. Technol. Eng. Syst. J. 2(3), 839-844 (2017);

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Platelet transfusions are vital for the prevention of fatal hemorrhage. Therefore, a stable inventory of platelets is required for an efficient and effective delivery of services in all the hospitals and medical centers. However, over the past decades, the requirement for platelets seems to be continuously increasing, while the number of potential donors is decreasing. Moreover, due to its very short life span of just five days, a large volume of platelets expires while they are on the shelves, resulting unnecessary shortages of platelets. Furthermore, it is very costly and difficult to get platelets from another blood bank in a short notice. Hence, these unexpected shortages put the life of patients at risk.

This study is focused on addressing the issues discussed, by developing an efficient blood inventory management model to reduce the platelet shortages, and wastages, while reducing the related inventory costs. Currently, the blood banks are managing platelet inventory according to their own instincts, which result to shortages and wastages. As a solution, we propose a model to manage the daily supply of platelets by forecasting the daily demand. Three different algorithms were developed using lower bound, average and upper bound values and tested to find the optimal solution that best fits to manage platelet inventory. These models were tested using data for 60 days obtained from two different levels of blood banks in Sri Lanka, namely a General Hospital blood bank and a Base Hospital blood bank. In General hospitals, the demand for blood components including platelets is very high when compared to the Base hospitals.

The study was able to come up with two different inventory management models for the two different types of blood banks. The model that best fits the General Hospital blood bank where the demand is high and was able to reduce the shortages by 46.74%, wastage by 89.82% and total inventory level by 39.10% and, the model that best fits the Base Hospital blood bank was able to reduce the shortages by 100%, wastage by 81.48% and total inventory level by 37.95%. It can be concluded that the same models can be adopted by other blood banks with similar characteristics to manage their blood inventory efficiently.

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Performance Evaluation of Associative Classifiers in Perspective of Discretization Methods

Zulfiqar Ali, Waseem Shahzad

Adv. Sci. Technol. Eng. Syst. J. 2(3), 845-854 (2017);

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Discretization is the process of converting numerical values into categorical values. Contemporary literature study reveals that there are many techniques available for numerical data discretization. The performance of classification method is dependent on the exploitation of the data discretizing method. In this article, we investigate the effect of discretization methods on the performance of associative classifiers. Most of the classification approaches work on the discretized databases. There are various approaches exploited for the discretization of the database to compare the performance of the classifiers. The selection of the discretization method greatly influences the classification performance of the classification method. We compare the performance of associative classifiers namely CBA and CBA2 on the selective discretizing methods i.e. 1R Discretizer (1R-D), Ameva Discretizer (Ameva-D), Bayesian Discretizer (Bayesian-D), Discretization algorithm based on Class-Attribute Contingency Coefficient (CACC-D), Class-Attribute Dependent Discretizer (CADD-D), Distribution-Index-Based Discretizer (DIBD-D), Cluster Analysis (ClusterAnalysis-D), Chi-Merge Discretizer (ChiMerge-D) and Chi2 Discretizer (Chi2-D) in terms of accuracy. The main object of this study is to investigate the impact of discretizing method on the performance of the Associative Classifier by keeping constant other experimental parameters. Our experimental results show that the performance of the Associative Classifier significantly varies with the change of data discretization method. So the accuracy rate of the classifier is highly dependent on the selection of the discretization method. For this comparative performance study, we use the implementation of these methods in KEEL data mining tool on public datasets.

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A novel model for Time-Series Data Clustering Based on piecewise SVD and BIRCH for Stock Data Analysis on Hadoop Platform

Ibgtc Bowala, Mgnas Fernando

Adv. Sci. Technol. Eng. Syst. J. 2(3), 855-864 (2017);

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With the rapid growth of financial markets, analyzers are paying more attention on predictions. Stock data are time series data, with huge amounts. Feasible solution for handling the increasing amount of data is to use a cluster for parallel processing, and Hadoop parallel computing platform is a typical representative. There are various statistical models for forecasting time series data, but accurate clusters are a pre-requirement. Clustering analysis for time series data is one of the main methods for mining time series data for many other analysis processes. However, general clustering algorithms cannot perform clustering for time series data because series data has a special structure and a high dimensionality has highly co-related values due to high noise level. A novel model for time series clustering is presented using BIRCH, based on piecewise SVD, leading to a novel dimension reduction approach. Highly co-related features are handled using SVD with a novel approach for dimensionality reduction in order to keep co-related behavior optimal and then use BIRCH for clustering. The algorithm is a novel model that can handle massive time series data. Finally, this new model is successfully applied to real stock time series data of Yahoo finance with satisfactory results.

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Analysis of Wireless Traffic Data through Machine Learning

Muhammad Ahsan Latif, Muhammad Adnan

Adv. Sci. Technol. Eng. Syst. J. 2(3), 865-871 (2017);

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The paper presents an analytical study on a wireless traffic dataset carried out under the different approaches of machine learning including the backpropagation feedforward neural network, the time-series NARX network, the self-organizing map and the principal component analyses. These approaches are well-known for their usefulness in the modeling and in transforming a high dimensional data into a more convenient form to make the understanding and the analysis of the trends, the patterns within the data easy. We witness to an exponential rise in the volume of the wireless traffic data in the recent decade and it is increasingly becoming a problem for the service providers to ensure the QoS for the end-users given the limited resources as the demand for a larger bandwidth almost always exist. The inception of the next generation wireless networks (3G/4G) somehow provide such services to meet the amplified capacity, higher data rates, seamless mobile connectivity as well as the dynamic ability of reconfiguration and the self-organization. Nevertheless, having an intelligent base-station able to perceive the demand well before the actual need may assist in the management of the traffic data. The outcome of the analysis conducted in this paper may be considered in designing an efficient and an intelligent base-station for better resource management for wireless network traffic.

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Video-frame Quality Improvement before Shot boundary Detection by using Logarithm, Wavelet and Contoulet Transform

Songpon Nakharacruangsak

Adv. Sci. Technol. Eng. Syst. J. 2(3), 872-877 (2017);

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Video shot boundary detection is important step for the research in the content analysis and retrieval fields. In this paper, firstly we presented an efficient method for Video-frame quality improvement to suppress flash occurred within video frame using logarithm, wavelet and contourlet transform. In addition, wavelet and contourlet transform also performed denoising. Secondly, for shot boundary detection, we used gray-scale histogram differences with edge change ratio. Furthermore, the adaptive threshold algorithm for shot transition detection was proposed. The experiment results showed that using logarithm with contourlet transform gain the precision and recall higher than using logarithm with wavelet transform.

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Electromagnetic Field and Lumped Circuit Analysis of Planar Transformer at Medium Frequency for Converter Application

Chengjian Lian, Daming Zhang

Adv. Sci. Technol. Eng. Syst. J. 2(3), 878-883 (2017);

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High frequency planar transformer is a new type of transformer that operates at high frequency. Its significance is proved through its miniaturised features, high power density and other performances. The design of planar transformer needs to consider several fundamental factors, including core material, dimension of layers and winding pattern. As the volume decreases, extra attentions need to be paid in power losses and safety requirements. Different converter topologies, with planar transformer integrated, are also investigated and simulated for maximising the overall efficiency of conversion. Overall, the use of planar transformer in converters can bring several benefits, and, hence, there is a strong interest of comprehending its structure and high frequency behaviours.

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Indoor monitoring in Public Buildings: workplace wellbeing and energy consumptions. An example of IoT for smart cities application

Stefania Nanni, Elisa Benetti, Gianluca Mazzini

Adv. Sci. Technol. Eng. Syst. J. 2(3), 884-890 (2017);

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In the recent years LepidaSpa created Sensornet platform for the control of the Emilia-Romagna territory managing heterogeneous environmental sensor networks distributed all over the region. LepidaSpa decided to integrate into Sensornet a brand-new family of sensors measuring indoor environmental parameters inside public buildings, in order to monitor energy consumption on one hand and workers’ wellbeing on the other. The innovative aspects of the adopted solution (the extreme simplicity of the sensor network architecture, its ease of installation, the real time detection of parameters directly related to power consumption and the availability of environmental parameters measurements (temperature, humidity and light) simultaneously providing context information on the power consumption and correlation to working conditions) made it a perfect candidate for a seamless integration within the platform and for an intensive monitoring campaign. This paper is presenting the results of such monitoring activity, where an IoT infrastructure acts as an enabler of a Smart City solution, focused on a sustainable wellbeing of the working places.

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EEG Mind Controlled Smart Prosthetic Arm – A Comprehensive Study

Taha Beyrouthy, Samer Al Kork, Joe Akl Korbane, Mohamed Abouelela

Adv. Sci. Technol. Eng. Syst. J. 2(3), 891-899 (2017);

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Recently, the field of prosthetics has seen many accomplishments especially with the integration of technological advancements. In this paper, different arm types (robotic, surgical, bionic, prosthetic and static) are analyzed in terms of resistance, usage, flexibility, cost and potential. Most of these techniques have some problems; they are extremely expensive, hard to install and maintain and may require surgery. Therefore, our work introduces the initial design of an EEG mind controlled smart prosthetic arm. The arm is controlled by the brain commands, obtained from an electroencephalography (EEG) headset, and equipped with a network of smart sensors and actuators that give the patient intelligent feedback about the surrounding environment and the object in contact. This network provides the arm with normal hand functionality, smart reflexes and smooth movements. Various types of sensors are used including temperature, pressure, ultrasonic proximity sensors, accelerometers, potentiometers, strain gauges and gyroscopes. The arm is completely 3D printed built from various lightweight and high strength materials that can handle high impacts and fragile elements as well. Our project requires the use of nine servomotors installed at different places in the arm. Therefore, the static and dynamic modes of servomotors are analyzed. The total cost of the project is estimated to be relatively cheap compared to other previously built arms. Many scenarios are analyzed corresponding to the actions that the prosthetic arm can perform, and an algorithm is created to match these scenarios. Experimental results show that the proposed EEG Mind-controlled Arm is a promising alternative for current solutions that require invasive and expensive surgical procedures.

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Features based approach for indexation and representation of unstructured Arabic documents

Mohamed Salim El Bazzi, Driss Mammass, Abdelatif Ennaji, Taher Zaki

Adv. Sci. Technol. Eng. Syst. J. 2(3), 900-905 (2017);

View Description

The increase of textual information published in Arabic language on the internet, public libraries and administrations requires implementing effective techniques for the extraction of relevant information contained in large corpus of texts. The purpose of indexing is to create a document representation that easily find and identify the relevant information in a set of documents. However, mining textual data is becoming a complicated task, especially when taking semantic into consideration. In this paper, we will present an indexation system based on contextual representation that will take the advantage of semantic links given in a document. Our approach is based on the extraction of keyphrases. Then, each document is represented by its relevant keyphrases instead of its simple keywords. The experimental results confirms the effectiveness of our approach.

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The Analysis and Comparison of Multiport Converter used for Renewable Energy Sources

Sarab Al-Chlaihawi, Ammar Al-Gizi, Aurelian Craciunescu

Adv. Sci. Technol. Eng. Syst. J. 2(3), 906-912 (2017);

View Description

The concept of renewable energy is increasing day by day because the electrical applications are moving towards utilization of renewable sources and due to this factor electric power is also gaining ground and new type of converters are modelled in order to get high utilization of renewable sources. In this paper, two types of multiport converters are presented which includes a DC-DC converter with a transformer attached and a DC-DC converter without a transformer. The converter with transformer is further subdivided into a full bridge and a half bridge DC-DC converter. The simulation results for all converters are presented and in the end, a case is taken for comparison which involves fixed resistance. The converters are compared with a constant load resistance of 70 ohms in terms of cost, area, complexity, control, isolation, weight and efficiency etc.

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Structural Optimization of Wavy FinFET for Leakage Reduction and Performance Enhancement

Anju Chakkikavil, Nisha Kuruvilla, Ayoob Khan, Shahul Hameed

Adv. Sci. Technol. Eng. Syst. J. 2(3), 913-917 (2017);

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Wavy FinFET is a hybrid device that integrates FinFET and Ultrathin Body FET technologies on SOI platform to provide high density and drivability without causing area penalty. The problem associated with this device is higher leakage and lower threshold voltage. This problem can be solved by structural modification of the device. This work analyses the performance of Wavy FinFET under various optimization methods such as device/channel engineering, work function engineering, spacer engineering and variation of isolation oxide thickness. The obtained results indicate that optimized Wavy FinFET can act as a solution for low power, highly reliable device topology. Leakage power is found to be reduced by 40.39%, 30.39% and 43.75% with channel engineering techniques such as substrate doping., halo doping and retrograde doping, respectively. Leakage power is lowered by 35.48% and 32.25% with increase in gate work function and isolation oxide thickness respectively. By using high k spacer material 54.77% reduction in leakage is further obtained without compromising drive current. In ADSE(Asymmetric Drain Side Extention) wavy FinFET,leakage is reduced by 61.35%. Whereas in symmetric and asymmetric Dual k wavy FinFET, leakage reduction is found to be 44.19% and 28.25% respectively.

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Program with Ixquic

Carmen Ramos, Tania Patiño

Adv. Sci. Technol. Eng. Syst. J. 2(3), 918-921 (2017);

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The goal of this paper is to explain the story telling, game design, game play and how is the interaction with the game Program with Ixquic. Here is the description about the new approach to this video game I called Program with Ixquic. Initially focused on an educational video game but now is a hybrid, now has more levels and provides moments of great fun, where each player can have some much fun in each different level and environments of interaction.

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A Design of SDN Based IP Mobility Management Considering Inter-Domain Handovers and Its Evaluation

Misumi Hata, Mustafa Soylu, Satoru Izumi, Toru Abe, Takuo Suganuma

Adv. Sci. Technol. Eng. Syst. J. 2(3), 922-931 (2017);

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To use IP services continually while users are moving with their mobile devices, IP mobility management that enables them to keep IP communication is necessary. Although Mobile IP is a popular method to manage IP mobility, Mobile IP has a problem that there is a possibility of a mobile node (MN) communicating over a redundant route. Then, Software Defined Network (SDN) based IP mobility management has emerged to solve this problem. Most of these solutions focus on intra-domain handovers and routing. However, since wireless network environment has spread, mobile devices move across domains during communication. To deal with this, we need to look upon inter-domain handovers and routing. In this paper, we propose a SDN based IP mobility management scheme considering situation of mobile devices moving across domains. This proposed scheme focuses on inter-domain handovers and introduces efficient functions of management information sharing and inter-domain routing. Experimental results show the desired effects of the proposed scheme: optimizing communication route and keeping the management information exchange traffic low.

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Computer Tomography from Micro-Electronics to Assembled Products

Keith Bryant, Ragnar Vaga

Adv. Sci. Technol. Eng. Syst. J. 2(3), 932-936 (2017);

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Traditional CT in our industry has been limited to Business card sized samples, due to the Cone Beam x-ray systems used by Electronics manufacturing companies. Inclined or Partial CT provides a slightly different solution showing layers or slices in 2D very well, but due to the partial nature of the scans does not produce very accurate 3D reconstructions. This seminar will look at more sophisticated x-ray systems, including dual tube units, which can image at sub-micron level and have the ability to build an accurate and detailed 3D image of a tablet or smart phone without any stitching or joining of images. With high quality reconstruction software, these images can easily be manipulated to allow key features or failure sites to be easily seen. These systems are being used in Failure Analysis but also in NPI and in the design and development process as CAD data can be overlaid and metrology is also possible with some systems.

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Mathematical Modeling and Digital Control of A Hybrid Switching Buck Converter

Muhammad Umar Abbasi

Adv. Sci. Technol. Eng. Syst. J. 2(3), 937-945 (2017);

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The aim of this paper is to describe mathematical modeling and digital control of a hybrid switching buck converter. This converter belongs to a class of so called hybrid switching converters and contains a resonant capacitor, resonant inductor and a diode in addition to original buck converter components. The dc gain of this converter is shown to be independent of resonant branch parameters. Moreover the dc conversion ratio is derived for both ideal case and including main inductor dc resistance. Small signal model of the converter is derived and is shown to be similar to conventional buck converter. Simulation results in SIMPLIS Software as well as experimental results of digital control using an 8 bit STM microcontroller are presented. The potential advantages and applications of this converter are discussed.

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For human comfort and convenience, appropriate temperature values may not be sufficient enough for the environment that they live in. The moisture content of the air has an important place in this regard. 30% to 65% humidity is desireable for a relaxed and comfortable life. Humidity in the environment is fundamental for the human health, convenience and comfort. Humidity is also valid for therapeutics. The drugs that are used in medicine for diagnosis and therapy must be inhaled with cold or hot water vapor in case drug effectiveness is desired to be increased. For such achievments, cold vaporization method is being preferred to reach the alveoli of the patients, thus, the drug can be used in a more efficient manner without damaging the respiratory tract. In this project, effect of ambient temperaure in ultrasonic nebulizers is investigated. It is proved that as the temperature increases 5°C, the speed of cold vapor increases 10% which refers a decrease in particle diameter. The variations in particle dimension may severely effect the efficiency of therapeutics. Therefore, in this study, it is presented that ultrasonic nebulizers should be designed considering ambient temperature. A design rationale is proposed in this study.

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Graphics on demand: the automatic data visualization on the WEB

Ramzi Guetari, Maha Mallek

Adv. Sci. Technol. Eng. Syst. J. 2(3), 951-957 (2017);

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Data visualization is an effective tool for communicating the results of opinion surveys, epidemiological studies, statistics on consumer habits, etc. The graphical representation of data usually assists human information processing by reducing demands on attention, working memory, and long-term memory. It allows, among other things, a faster reading of the information (by acting on the forms, directions, colors…), the independence of the language (or culture), a better capture the attention of the audience, etc.
Data that could be graphically represented may be structured or unstructured. The unstructured data, whose volume grows exponentially, often hide important and even vital information for society and companies. It, therefore, takes a lot of work to extract valuable information from unstructured data. If it is easier to understand a message through structured data, such as a table, than through a long narrative text, it is even easier to convey a message through a graphic than a table. In our opinion, it is often very useful to synthesize the unstructured data in the form of graphical representations.
In this paper, we present an approach for processing unstructured data containing statistics in order to represent them graphically. This approach allows transforming the unstructured data into structured one which globally conveys the same countable information. The graphical representation of such a structured data is then obvious. This approach deals with both quantitative and qualitative data. It is based on Natural Language Processing Techniques and Text Mining. An application that implements this process is also presented in this paper.

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Spectral Reflectance Estimation and Color Reproduction Based on Sparse Neugebauer Model

Kohei Inoue, Kenji Hara, Kiichi Urahama

Adv. Sci. Technol. Eng. Syst. J. 2(3), 958-966 (2017);

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This paper proposes a method for estimating the spectral reflectance of Neugebauer primaries or eight basic colors when the spectral reflectance data of several colors are given. The proposed method is based on Neugebauer model, which expresses an arbitrary color as a weighted average of Neugebauer primaries, and its sparse version called sparse Neugebauer model. We also reproduce the colors from the estimated reflectance spectra, and show experimental results of spectral reflectance estimation and color reproduction from the estimated spectral data. It is experimentally demonstrated that the sparse Neugebauer model outperforms the conventional Neugebauer model in both spectral reflectance estimation and color reproduction.

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3D Senor-based Library Navigation System

Abdel-Mehsen Ahmad, Zouhair Bazzal, Roba Al Majzoub, Ola Charanek

Adv. Sci. Technol. Eng. Syst. J. 2(3), 967-973 (2017);

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The discussed system in this paper uses the Kinect’s 3D input (acquired through IR projector and Camera) to detect gestures and then based on these gestures perform certain tasks, and display certain results on an output screen. The programming language used here is the Processing open source software and a database was implemented to manage the data required within the system. The deigned system was created for a library but the system’s design is broad enough to allow its utilization in many more domains. Implementation, system screenshots, simulation and results are discussed along with testing the system in different condition of light and distance. Some simple additions have been added to this version of the program to facilitate the interaction between the user and the system further.

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Deterministic Approach to Detect Heart Sound Irregularities

Richard Mengko, Amy Hamidah, Ricky Saputra

Adv. Sci. Technol. Eng. Syst. J. 2(3), 974-980 (2017);

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A new method to detect heart sound that does not require machine learning is proposed. The heart sound is a time series event which is generated by the heart mechanical system. From the analysis of heart sound S-transform and the understanding of how heart works, it can be deducted that each heart sound component has unique properties in terms of timing, frequency, and amplitude. Based on these facts, a deterministic method can be designed to identify each heart sound components. The recorded heart sound then can be printed with each component correctly labeled. This greatly help the physician to diagnose the heart problem. The result shows that most known heart sounds were successfully detected. There are some murmur cases where the detection failed. This can be improved by adding more heuristics including setting some initial parameters such as noise threshold accurately, taking into account the recording equipment and also the environmental condition. It is expected that this method can be integrated into an electronic stethoscope biomedical system.

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Spatial Modulation Technique For Filtered-OFDM Based Wireless Transmission

Shaddrack Yaw Nusenu

Adv. Sci. Technol. Eng. Syst. J. 2(3), 981-986 (2017);

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In this paper, a spatial modulation (SM) which provides no synchronization between the transmitting antennas and avoids inter-channel interference (ICI) at the receiver input while maintaining high spectral efficiency is applied to filtered-orthogonal frequency division multiplexing (F-OFDM) transmission. The SM technique maps a block of information bits into two information carrying units, namely, a symbol chosen from a signal constellation diagram and a unique antenna number selected from the set of transmit antennas. Therefore, for F-OFDM wireless transmission, each subcarrier within the subband is mapped to one of the transmitting antennas. During wireless data transmission, there is only one active antenna transmitting power on that subcarrier at an instant of time and the rest of the antennas remains silent (zero power). At the receiver, a maximum-likelihood (ML) detector recovers the transmitted block of information bits by estimating the transmitted signal and the respective transmit antenna number. The effectiveness of the proposed method is verified using numerical results.

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Template-like Tensor Domain Operations to Enhancing Diffusion Datasets Quality

Fernando Yepes-Calderon, Flor M. Medina

Adv. Sci. Technol. Eng. Syst. J. 2(3), 987-995 (2017);

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Diffusion MRI-based tractography, which is built by connecting the principal components of the estimated water diffusion pattern, is used to elucidate neuronal connectivity. However, the anatomical accuracy of the method is affected by factors such as noise and imaging misalignments. In this manuscript, we present a method to clean diffusion datasets by rotating the diffusion patterns according to a transformation matrix, that is in turn obtained in the fractional anisotropy domain. We demonstrated the accuracy and feasibility of our method by improving brain images of a mouse and also by creating a diffusion template in a neonates framework.

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Ensemble of Neural Network Conditional Random Fields for Self-Paced Brain Computer Interfaces

Hossein Bashashati, Rabab Kreidieh Ward

Adv. Sci. Technol. Eng. Syst. J. 2(3), 996-1005 (2017);

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Classification of EEG signals in self-paced Brain Computer Interfaces (BCI) is an extremely challenging task. The main difficulty stems from the fact that start time of a control task is not defined. Therefore it is imperative to exploit the characteristics of the EEG data to the extent possible. In sensory motor self-paced BCIs, while performing the mental task, the user’s brain goes through several well-defined internal state changes. Applying appropriate classifiers that can capture these state changes and exploit the temporal correlation in EEG data can enhance the performance of the BCI. In this paper, we propose an ensemble learning approach for self-paced BCIs. We use Bayesian optimization to train several different classifiers on different parts of the BCI hyper- parameter space. We call each of these classifiers Neural Network Conditional Random Field (NNCRF). NNCRF is a combination of a neural network and conditional random field (CRF). As in the standard CRF, NNCRF is able to model the correlation between adjacent EEG samples. However, NNCRF can also model the nonlinear dependencies between the input and the output, which makes it more powerful than the standard CRF. We compare the performance of our algorithm to those of three popular sequence labeling algorithms (Hidden Markov Models, Hidden Markov Support Vector Machines and CRF), and to two classical classifiers (Logistic Regression and Support Vector Machines). The classifiers are compared for the two cases: when the ensemble learning approach is not used and when it is. The data used in our studies are those from the BCI competition IV and the SM2 dataset. We show that our algorithm is considerably superior to the other approaches in terms of the Area Under the Curve (AUC) of the BCI system.

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Optimal Plant Growth in Smart Farm Hydroponics System using the Integration of Wireless Sensor Networks into Internet of Things

Nathaphon Boonnam, Jumras Pitakphongmetha, Siriwan Kajornkasirat, Teerayut Horanont, Deeprom Somkiadcharoen, Jiranuwat Prapakornpilai

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1006-1012 (2017);

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Greenhouse cultivation is easy to keep up and control important factors such as light, temperature, and humidity. Using of sensors and actuators in the greenhouse to capture different values allows for the control of the equipment, it can also be optimized for growth at optimal temperature and humidity of various crops planted. We use wireless sensor networks’ system by sending results to the cloud service, monitoring values, and devices’s controlling via smart phone. The results of this study are useful for growing crops not only in technical parts, but also in physical part; it was evaluated by questionnaire using technology acceptance model.

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Skeletonization in Natural Image using Delaunay Triangulation

Vicky Sintunata, Terumasa Aoki

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1013-1018 (2017);

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In this paper a novel approach to extract 2D skeleton information (skeletonization) from natural image is proposed. The work presented here is the extension of our previous paper presented at the International Sympsosium on Multimedia 2016. In the past work, a threshold based method is utilized. Here the algorithm is further improved by using a better edge points detection and skeleton extraction. Furthermore the proposed method is compared with the Skeleton Strength Map (SSM) and shows better result visually and numerically (F-measure comparison).

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A High Efficiency 0.13μm CMOS Full Wave Active Rectifier with Comparators for Implanted Medical Devices

João Ricardo de Castilho Louzada, Leonardo Breseghello Zoccal, Robson Luiz Moreno, Tales Cleber Pimenta

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1019-1025 (2017);

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This paper presents a full wave active rectifier for biomedical implanted devices using a new comparator in order to reduce the rectifier transistors reverse current. The rectifier was designed in 0.13μm CMOS process and it can deliver 1.2Vdc for a minimum signal of 1.3Vac. It achieves a power conversion efficiency of 92% at the 13.56MHz Scientific and Medical (ISM) band.

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Multiclass Myoelectric Identification of Five Fingers Motion using Artificial Neural Network and Support Vector Machine

Jawad Ahmad, Ammar Mohsin Butt, Muhammad Tanveer Riaz, Shoaib Bhutta, Muhammad Zeeshan Khan, Inam-Ul-Haq

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1026-1033 (2017);

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The research in Neuro-Prosthetics is gaining more significance and popularity as the advancement in prosthetics control allows amputees to perform even more tasks. Indeed, the improvement of classification accuracy is a challenge in prosthetics control. In this research, a system is developed in order to improve the multiclass classification rate. Two classifiers namely Artificial Neural Network(ANN) and Support Vector Machine(SVM) are trained to recognize five different myoelectric motions of hand fingers. The Electromyography(EMG) signals are acquired using surface electrodes placed on the forearm at specific nodes. The signal conditioning is performed using two stage filtering and amplification followed by digitization process. The final version of EMG signals is correlated in joint time and frequency domain for best feature vectors done via Discrete Wavelet Transform (DWT). The feature vectors are used to train the ANN and SVM. The classification results show an exceptional performance of ANN with classification accuracy of 98.7%. over the SVM, which is 96.7%.

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Group of UAVs Moving on Smooth Control Law with Fixed Obstacles

Dmytro Pavlovich Kucherov, Andrei Nikolayevich Kozub, Oleg Nikolayevich Kostyna

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1034-1041 (2017);

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In this paper considered the movement of multi-agent system that consists of several UAVs that carry out monitoring ground surface. The multi-agent system includes a lead agent and several agents-members of the group. The motion of this system occurs along a trajectory, which is determined by the initial conditions, its mathematical model and obstacles on the route. Only the leader of the group knows the ultimate goal of the movement. The motion of this structure is considered in the potential field, which determined the forces of attraction and repulsion and created control signals by measuring the distances to the nearest neighbors. This allows the UAV group to consider an aggregate that has some size and to describe its motion the system of differential equations of second-order. As UAV selected Quadrotor. In this investigation, the stability conditions of such motion are considered, and simulation of approach is proposed.

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A company’s ability to find the most profitable technology is based on a precise forecast of achievement potential. Technology Management (TM) uses forecasting models to analyse future potentials, e.g. the Gartner Hype Cycle, Arthur D. Little’s technology lifecycle or McKinsey’s S-curve model. All these methods are useful for qualitative analysis in the planning of strategic research and development (R&D) expenses. In a new approach, exponential and logistic growth functions are used to identify and quantify characteristic stages of technology development. Innovations from electrical, mechanical and computer engineering are observed and projected until the year 2025. Datasets from different industry sectors are analysed, as the number of active Facebook users worldwide, the tensile yield point of flat bar steel, the number of transistors per unit area on integrated circuits, the fuel efficiency per dimension of passenger cars, and the energy density of Lithium-Ion cells. Results show the period of performance doubling and the forecast for the end of the technological achievement potential. The methodology can help to answer key entrepreneurial questions such as the search for alternatives to applied technologies, as well as identifying the risk of substitution technology.

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Improving the Performance of Fair Scheduler in Hadoop

Shou-Chih Lo, Ya-Wen Cheng

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1050-1058 (2017);

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Cloud computing is a power platform to deal with big data. Among several software frameworks used for the construction of cloud computing systems, Apache Hadoop, which is an open-source software, becomes a popular one. Hadoop supports for distributed data storage and the process of large data sets on computer clusters based on a MapReduce parallel processing framework. The performance of Hadoop in parallel data processing is depended on the efficiency of a job scheduling algorithm underworking. In this paper, we improve the performance of the well-known fair scheduling algorithm adopted in Hadoop by introducing several mechanisms. The modified scheduling algorithm can dynamically adjust resource allocation to user jobs and the precedence of user jobs to be executed. Our approach can properly adapt to the runtime environment’s condition with the objective of achieving job fairness and reducing job turnaround time. Performance evaluations verify the superiority of the proposed scheduler over the original fair scheduler. The average turnaround time of jobs can be largely reduced in our experiments.

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Ranking of Two Multi Criteria Decision Making Cases with Evidential Reasoning under Uncertainty

Farzaneh Ahmadzadeh

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1059-1063 (2017);

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Many decision problems have more than one objective that need to be dealt with simultaneously. Moreover, because of the qualitative nature of the most of real world problem it is an inevitable activity and very important to interpret and present the uncertain information for making effective decision. The Evidential Reasoning (ER) approach which is one of the latest development within multi criteria decision making (MCDM) seems to be the best fit to synthesize both qualitative and quantitative data under uncertainty. To support this claim, two case studies were tested to illustrate the application of ER for prioritization and ranking of decision alternative to support decision process even with uncertain information. The overall goal of the first case study is to identify and prioritize factors that can be considered maintenance-related waste within the automotive manufacturing industry. The result after applying ER shows “inadequate resources” and “weather /indoor climate,” respectively, are the highest and lowest average scores for creating maintenance-related waste. This prioritization methodology can be used as a tool to create awareness for managers seeking to reduce or eliminate maintenance-related waste. The aim of the second case study is to look at the possibility of having a new approach for sustainable design. So through a literature review six design strategies were taken into consideration in order to develop a new approach based on all advantages (sustainable factors) of the six approaches. For ranking and finding out about the most important factors the evidential reasoning (ER) approach is used. Based on ER all the important factors, apart from the one collected from interviews are a part of eco-design. So it means among all strategies eco-design is the most dominant strategy in term of environment. However two of the important factors are not found in any strategy but in interviews. These factors can be used as the building blocks for a new approach. The importance of having a better structured decision process is essential for the success of any organization, so it can be applied widely in most of real world problem dealing with making effective decision.

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Applied Horizontal and Vertical Geothermal Heat Exchanger with Heat Pump System to Provide Air Conditioning for an Academic Facility in Mexico

Daniel Alcantar Martínez, Oskar Javier González Pedraza, Crisanto Mendoza Cavarrubias, J. Jesus Pacheco Ibarra, Jorge Alberto Rangel Arista

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1064-1069 (2017);

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At present in Mexico, the renewable energy has become more important due to the great dependence of the country for fossil fuels. Within the several applications of renewable energy, there are the geothermal applications for the air conditioning of spaces. This technology employs heat pumps that interexchange heat with the ground. This technology is relatively young in Mexico, leaving a large field for study and application throughout the country. In this way, to calculate the correct sizing of geothermal heat exchangers, it is necessary to calculate the thermal loads of the complex in which this technology of geothermal heat pumps using vertical heat exchangers type U will be installed, to perform the calculation of thermal loads Autodesk Revit® software was used, with which was possible to make a virtual model in detail of the botanical center that is located in Morelia, Michoacán, Mexico and belongs to the Universidad Michoacana de San Nicolás de Hidalgo (UMNSH).

This study shows the results of the analysis of the installations and determination of the thermal loads of the complex due to this type of infrastructure. By obtaining the values of the thermal loads, the dimensioning of the heat exchanger was archived, which will have to be installed to cover the thermal requirement of this system and his installation, in addition to the selection of the heat pump. This complex of 2 levels, where, on the first floor there are cubicles and laboratories and on the second floor, several common areas.

The design was developed in detail in Autodesk Revit 2015. After obtaining the thermal loads, the GLHEPro software was used for dimensioning the Vertical heat exchangers with the number and depth of the exchangers was obtained. the GLD 2014 software was used for dimensioning the Horizontal heat exchangers with the number and depth of the exchangers was obtained.

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Space Time – Track Circuits with Trellis Code Modulation

Marius Enulescu

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1070-1079 (2017);

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The track circuits are very important equipments used in the railway transportation system. Today these are used to send vital information, to the running train, in the same time with the integrity checking of the rail. The actual track circuits have a small problem due to the use of the same transmission medium by the signals containing vital information and the return traction current, the running track rails. But this small problem can produce big disturbances in the train circulation, especially in the rush hours.

To improve the data transmission to the train on-board equipment, the implementation of new track circuits using new communication technology were studied. This technology is used by the mobile and satellite communications and applies the principle of diversity encoding both time and space through the use of multiple transmission points of the track circuit signal for telegram which is sent to the train. Since this implementation does not satisfy the intended purpose, other modern communication principles such as 8PSK signals modulation and encoding using Trellis Coded Modulation were developed. This new track circuit aims to solve the problems which appeared in the current operation of track circuits and theoretically manages to transmit vital information to the train on board equipment without being affected by disturbances in electric traction transport systems.

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Support Vector Machine based Vehicle Make and Model Recognition System

Muhammad Asif Manzoor, Yasser Morgan

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1080-1085 (2017);

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Vehicle analysis is a very useful component in various real world applications. In this paper, we have developed a Vehicle Make and Model Recognition (VMMR) system using Support Vector Machine (SVM). Scale Invariant Feature Transform (SIFT) and Speed-Up Robust Transform (SURF) are used to extract local features from an image. Bag-of-Features (BoF) model is used to create visual dictionaries and convert the local image features into global image feature representation. Multiple dictionaries of different sizes are created for both features; SIFT and SURF and the dataset is coded using these dictionaries to determine the best size for the visual dictionary. NTOU-MMR is a publicly available vehicle dataset which we have used to evaluate the performance of proposed VMMR system. 92% recognition rate is achieved by using the proposed VMMR system.

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Estimation of voltage unbalance at an AC traction substation with different train operational scenarios

Thanatchai Kulworawanichpong, Nattapong Mingpruk, Tosaphol Ratniyomchai

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1086-1091 (2017);

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This paper presents the modeling and simulation of the voltage unbalance in the power supply system of an AC electrified railway. The operating voltage at the traction substation is obtained by MATLAB/SIMULINK program and the voltage unbalance is evaluated by considering the voltage unbalance factor (VUF). Suvarnabhumi Airport Rail Link (ARL), in Bangkok, Thailand, is chosen to be a case study. The ARL is supplied by two single-phase traction transformers connected as a cyclic permutation of phases. According to the extension plan of the ARL, four service scenarios with different headways, auxiliary loads and total weights of the trains were simulated to study how the different scenarios influence the VUF at the three-phase side. It can be summarized that at the same headway, the VUF was increased when the train weight and auxiliary power load were increased. In case of different headways, the longer the headway, the more voltage unbalance. The extension plan of the ARL in the near future can be achieved with the voltage unbalance level under the maximum allowable value.

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A Microwave Reflectometer Prototype for Detection of Body Through the Rubble of Collapsed Buildings

Syed Daniyal Ali Shah

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1092-1106 (2017);

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There is a growing interest in using radio frequency in imaging for problem solving in situational awareness, surveillance, search and rescue operations, and screening for security. This has been fetched from recent development in addition to innovative technologies in microwave radar imaging applications. Despite the fact that no new phenomenology is exposed in this field, the prospects to eventually realize systems that operate under adverse weather conditions, interferences and obscuration has prompted newer prospects. However, the existing systems for RF imaging are not easy to afford and are not easily available and there is a need to make affordable imaging available to support people’s lives. The effort provided an economic, compact and easy solution for human body detection applications using Radio Frequency (RF) by designing and developing a microwave transceiver that can give data in a suitable form for further signal processing and data acquisition. In this project, different types of RF imaging techniques and the most feasible techniques that may be employed for under debris search and rescue operations were studied. Link budget analysis and software simulations were conducted. Individual components along with the transmitting and receiving chains were tested on VNA. Gain and radiation pattern of antennas was determined in anechoic chamber. During this project the performance of transceiver, regarding its detection ability, range resolution, signal to noise ratio (SNR) etc., were also investigated. At the end a prototype FMCW transceiver is given that is able to detect human body under debris or behind a walls whether living or dead, which is effective at transmitting as well as receiving the reflections and giving data in an audio format for further signal processing.

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Rotary Cutting of Electrical Steel Laminations – A Contrast to Traditional Stamping

Markus Hubert, Simon Kutter, Marco Ziegler, Michael Schneider, Joerg Franke

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1107-1113 (2017);

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Rotary cutting of electrical steel laminations is a novel, promising alternative in the processing of electrical steel strip with enormous economical and technical potentials. This paper is an extension of work originally presented on the 6th International Electric Drives Production Conference (E|DPC) in Nuremberg, Germany 2016. The scope of this paper includes a theoretical description of the rotary cutting process, an explanation of the machine and tooling setup, the basics of the Toroidal Core Tests and a discussion of the theoretical and experimental results. The methodology applied is basing on the Toroidal Core Test per DIN 60404-6, which is elementary described in section 3. Toroidal core tests allow a characterization in regards of technical, process and functional aspects, what is also mainly extended in this work. Finally, a classification of the rotary cutting process into existing processing technologies of electrical steel strip is feasible with respect to its limits and possibilities.

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Design for Smaller, Lighter and Faster ICT Products: Technical Expertise, Infrastructures and Processes

Omer Aydin, Orhan Uçar

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1114-1128 (2017);

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For the design of Information and Communications Technology (ICT) related products, basic level of technical expertise and simple development tools were enough in the early 1980s. As time goes by, new generation products designed by engineers are always expected to be smaller, lighter and faster, due to the increasing global competition and the application of hardware and software in every area of our lives. In order to be able to respond to these needs, engineers have always had to produce new technologies and solutions. In this sense, hardware related technologies have been growing much faster such as System on Chips (SoC), displays, batteries and other materials used in the ICT products. Designers have been diversifying software development processes and tools remarkably for new applications and constantly developing new communication standards. In this article, all the main design phases are presented starting from the system design to the product validation and test. As can be seen from the relevant sections, in order to design an ICT product, very deep technical expertise, expensive development and verification infrastructures are needed in the relevant fields.

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A Novel Ultra High Speed and Configurable Discrete Wavelet Packet Transform Architecture

Mouhamad Chehaitly, Mohamed Tabaa, Fabrice Monteiro, Abbas Dandache

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1129-1136 (2017);

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This work is dedicated to present a new pipeline-parallel architecture of Discrete Wavelet Packet Transform (DWPT) for all wavelet family implemented in FPGA technology. The main target of our architecture is to provide an effective performance trade-off, where it significantly increases the throughput with a restricted amount of hardware. In this article, we propose two kinds of configurable architecture: first architecture with a very strict amount of hardware base of pipeline and sharing resource, and the second architecture provide an ultra-high speed by propose P-parallel DWPT and a parallel direct FIR filter under the strategy of pipeline-parallel and sharing resource. The pipeline and the clever sharing of the hardware resources are smartly connect based on low-pass and high-pass filters in the Mallat-tree algorithm. These architectures are fully configurable in synthesis according to parallel degree, the tree depth (number of tree levels), the order of the filters and the filter quantization coefficient. Consequently, the simulation results accelerated to an approximate value of P*(Frequency). Furthermore, the tree depth and filters order has little impact (only due to place and route variations) on throughput. This architecture was synthesized using Altera Quartus prime lite edition targeting an Altera Cyclone IV – (FPGA) and it was developed in VHDL at RTL level modeling.

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Cognitive Artificial Intelligence Method for Interpreting Transformer Condition Based on Maintenance Data

Karel Octavianus Bachri, Bambang Anggoro, Arwin Datumaya Wahyudi Sumari, Adang Suwandi Ahmad

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1137-1146 (2017);

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A3S(Arwin-Adang-Aciek-Sembiring) is a method of information fusion at a single observation and OMA3S(Observation Multi-time A3S) is a method of information fusion for time-series data. This paper proposes OMA3S-based Cognitive Artificial-Intelligence method for interpreting Transformer Condition, which is calculated based on maintenance data from Indonesia National Electric Company (PLN). First, the proposed method is tested using the previously published data, and then followed by implementation on maintenance data. Maintenance data are fused to obtain part condition, and part conditions are fused to obtain transformer condition. Result shows proposed method is valid for DGA fault identification with the average accuracy of 91.1%. The proposed method not only can interpret the major fault, it can also identify the minor fault occurring along with the major fault, allowing early warning feature. Result also shows part conditions can be interpreted using information fusion on maintenance data, and the transformer condition can be interpreted using information fusion on part conditions. The future works on this research is to gather more data, to elaborate more factors to be fused, and to design a cognitive processor that can be used to implement this concept of intelligent instrumentation.

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Selective Detrending using Baseline Drift Detection Index for Task-dependant fNIRS Signal

Jinung An, Gihyoun Lee, Seung Hyun Lee, Sang Hyeon Jin

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1147-1151 (2017);

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A functional near-infrared spectroscopy (fNIRS) can be employed to investigate brain activation by measuring the absorption of near-infrared light through the intact skull. The general linear model (GLM) as a standard model for fMRI analysis has been applied to functional near-infrared spectroscopic (fNIRS) imaging analysis as well. The GLM has drawback of failure in fNIRS signals, when they have drift globally. Wavelet based detrending technique is very popular to correct the baseline drift (BD) in fNIRS. However, this method globally distorted the total multi-channel signals even if just one channel’s signal was locally drifted. This paper suggests the selective detrending method using BD detection index to indicate BD as an objective index. The experiments show the performance of the proposed method as graphic results and objective evaluation index with current detrending algorithms.

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Autonomous Micro-Air-Vehicle Control Based on Visual Sensing for Odor Source Localization

Kenzo Kurotsuchi, Mitsuharu Tai, Hiromasa Takahashi

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1152-1158 (2017);

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In this paper, we propose a novel control method for autonomous-odor-source localization using visual and odor sensing by micro air vehicles (MAVs). Our method is based on biomimetics, which enable highly autonomous localization. Our method does not need any instruction signals, including even global positioning system (GPS) signals. An experimenter simply blows a whistle, and the MAV will then start to hover, to seek an odor source, and to keep hovering near the source. The GPS-signal-free control based on visual sense enables indoor/underground use. Moreover, the MAV is light-weight (85 grams) and does not cause harm to others even if it accidentally falls. Experiments conducted in the real world were successful in enabling odor source localization using the MAV with a bio-inspired searching method. The distance error of the localization was 63 cm, more accurate than the target distance of 120 cm for individual identification. Our odor source localization is the first step to a proof of concept for a danger warning system. These localization experiments were the first step to a proof of concept for a danger warning system to enable a safer and more secure society.

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EMI Shielding Performance For Varies Frequency by Metal Plating on Mold Compound

Min Fee Tai, Swee Leong Kok, Kenichiroh Mukai, Stephan Hotz, Patrick Brooks, Diego Reinoso Cocina

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1159-1164 (2017);

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Conformal metalization on mold compound offers new possibility for IC package design to improve features such as rigidization of the flexible core, heat sink capability, 3D-circuit patterning and the electromagnetic interference (EMI) shielding. With the unique processes, the fabrication technology had enabled to achieve the high reliable performance and had passed the electrical test. Following research after the reliability concern, this paper further study the shielding effectiveness of varying coating thickness with respect to laboratory simulated EMI condition, using radio frequency from 10MHz to 5.8 GHz. Different metal namely pure nickel, nickel-phosphorous and pure plated copper are studied for their effectiveness of EMI sheilding. Our first result showed over 35-40dB of shielding effectiveness is achievable on high frequency 868-5800MHz. Nevertheless on low frequency of 10MHz, the shielding effectiveness achievement is below than 25dB. To overcome the shielding need for lower frequency, we further expanded our test by choosing ferromagentic material Nicke/Ironl-alloy in combination with thick copper plating. With this new metal combination, EMI shielding effectiveness for lower frequency is improved to 40dB.

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Comparative Study of Adaptive Consensus Control of Euler-Lagrange Systems on Directed Network Graph

Yoshihiko Miyasato

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1165-1171 (2017);

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A  comparative  study  between  adaptive  consensus  control  of multi-agent systems composed of fully actuated mobile robots which are described as a class of Euler-Lagrange systems on directed network graphs based on the notion of inverse optimal H control criterion (Controller I), and the similar control strategy without H control criterion (Controller II), is given in this paper. Controller I is deduced as a solution of certain H control problem, where estimation errors of tuning parameters are considered as external disturbances to the process. Asymptotic properties, stability and robustness to unknown parameters are discussed for Controller I and Controller II.

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Future Contract Selection by Term Structure Analysis

Vasco Grossmann, Manfred Schimmler

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1172-1180 (2017);

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In futures markets, a single asset is generally represented by several contracts with different maturities. The selection of specific contracts is an inevitable task that also creates new opportunities, especially in terms of speculative trading. Evaluating immediate and upcoming trading costs for all considered contracts might lead to a significantly improved performance. Among that, even possible market inefficiencies might be taken into consideration. This research introduces and evaluates a new algorithm for the contract selection. The results are benchmarked and compared with established methods using a Monte Carlo simulation on different commodity and index futures.

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Optimal Rotor Design of Line Start Permanent Magnet Synchronous Motor by Genetic Algorithm

Bui Minh Dinh

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1181-1187 (2017);

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Line start permanent magnet synchronous motor (LSPMSM) is one of the highest efficiency motors due to no rotor copper loss at synchronous speed and self-starting. LSPMSM has torque characteristics of both induction motor IM and Permanent Magnet Synchronous Motor-PMSM. Using Genetic Algorithm (GA) for balancing magnetic cost and for copper loss minimization, the magnetic sizes and geometry parameter of stator and rotor are found and manufactured for industrial evaluation. This article is also taking account practical manufacturing factors to minimize mass production cost. In order to maximize efficiency, an optimal design method of cage-bars and magnet shape has to be considered. The geometry parameters of stator and rotor can be obtained by an analytical model method and validated by FEM simulation. This paper presents the optimal rotor design of a three-phase line-start permanent magnet motor (LSPM) considering the starting torque and efficiency. To consider nonlinear characteristics, the design process is comprised of the FEM and analytical method. During this study, permanent-magnets and cage bars were designed using the magnetic equivalent circuit method and the barriers that control all magnetic flux were designed using the FEM, and the tradeoff of starting torque and efficiency is controlled by weight function in Taguchi method simulation. Finally, some practical results have been obtained and analyzed based on a LSPMSM test bench.

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Fault-Tolerant in Embedded Systems (MPSoC): Performance Estimation and Dynamic Migration Task

Kamel Smiri, Habib Smei, Nourhen Fourati, Abderrazak Jemai

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1188-1195 (2017);

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Multiprocessor Systems-on-Chip (MPSoC) allow the implementation of heterogeneous architectures with a high integration capacity. In recent years, computational requirements MPSoC are increasing exponentially. This complexity, coupled with constantly evolving specifications, has forced designers to consider intrinsically flexible implementations. Deploying applications typical of multimedia domains is difficult, not only due to the heterogeneous parallelism in the platforms, but also due to the performance constraints that typify these systems. An application can be modeled as a set of cooperative tasks. A task can be implemented in software or in hardware depending on its complexity and the involved cost. Our proposal is a fault tolerance approach which combines the results of a performance model and a technical’s fault tolerance. We interest of the dynamic migration task to resolve the Fault-Tolerant for Multiprocessors Embedded System. We exploited an example of multimedia application (MJPEG decoder) to find optimal Fault tolerance systems. Our aim in this paper is to exploit the classic technique of fault tolerance. The solution chosen is the transformation of software processing into hardware processing. And also, exploitation of hybrid models (simulation/analytics). The goal is to have a Fault Tolerant Embedded System.

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Incremental Control Techniques for Layout Modification of Integrated Circuits

Patrik Vacula, Vlastimil Kotě, Adam Kubačák, Milan Lžíčař, Radek Zelený, Miroslav Husák, Jiří Jakovenko

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1196-1201 (2017);

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Analog layout is created in integrated circuits (IC) computer aided design (CAD) environment and during realization requires a lot of modifications of database objects. Because database objects modification is time consuming, then any improvement and simplification of modification flow in IC CAD environment can increase layout productivity. A proposed new modification concept can speed-up layout work and is very intuitive and easily put into practice. In advance, it allows to apply modern gesture tracking devices for control. By simplifying control of layout object modifications, the productivity of analog layout creation has been improved in the range of 23% to 66%.

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Effect of Cold Drawing Pass Schedule on Mechanical Properties and Microstructure of ST 52 during Cold Drawing of Seamless Tubes and its Influence on Springback

Dadabhau Baban Karanjule, Sunil Sukhdeo Bhamare, Thota Hanumant Rao

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1202-1210 (2017);

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In-elastic recovery behavior of seamless tube material has been investigated by uniaxial tensile tests. Unloading Stress–Strain curves obtained under different passes of cold drawing process shows that the percentage of in-elastic recovery to the total recovery increased with plastic deformation. This paper is an experimental study that shows Young’s Modulus decreases with plastic strain for ST 52 material. It is found that with increase in plastic strain, Young’s Modulus reduces rapidly initially then reduces more slowly and finally settles to stable value due to increase in plastic deformation and ultimately increased residual stresses. This variation of Young’s’ Modulus is related to internal stresses, residual stresses, micro cracks, dislocations during plastic deformation. Similarly, Scan Electron Microscopy (SEM) and Micro-hardness testing reveals that mechanical properties are better in the first pass sample of multiple cold drawing passes. The results of this study reveals that 10-20% degradation occurs in Young’s Modulus for 5-7% plastic strain and better mechanical properties are achieved in the first pass sample.

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IoT: Their Conveniences, Security Challenges and Possible Solutions

Davar Pishva

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1211-1217 (2017);

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The build-in internet-controlled functions of smart devices such as smart phone, smart television, home healthcare gadget, etc., have made them quite attractive to many segments of consumers. In recent years mankind has witnessed an upsurge usage of such devices for numerous purposes. In this paper, the author is going to show how previously forecasted security challenges of these devices are becoming realities in the present day life. The paper initially provides some introductory information about the topic, mostly by means of survey and citations of previous work. It then highlights the devastating effects of October 21, 2016 DDoS attack which mainly utilized IoT devices. It emphasizes the danger of recently revealed Mirai IoT botnet which serves as the basis for the DDoS-for-hire ‘booter’/ ‘stresser’ service. In terms of counter measures, after highlighting IoT security implementation challenges, numerous approaches are presented. As a long-term solution, an architecture wherein security issues are managed through universal home gateway by network operators in a product based fashion is emphasized. The author shows its technical feasibility and demonstrates its partial materialization in proprietary manners. It then explains why and how numerous stake holders are needed to get together for its wide range commercial implementation. Some immediate necessary safeguard actions and intermediate schemes which include soft infrastructures are also presented for the purpose of risk reduction.

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Recognition and Position Estimation for Multiple Labware Transportation Using Kinect V2 and Mobile Robots

Mohammed Myasar Ali, Hui Liu, Norbert Stoll, Kerstin Thurow

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1218-1226 (2017);

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Mobile robots can be used to perform transportation tasks for different objects. These tasks have to be implemented carefully. Therefore, an accurate approach for object recognition and position estimation is required. This work presents a concept for identification and position estimation of multiple labware. These labware, which contain chemical and biological components, have to be manipulated and transported in life science laboratories using H20 mobile robots. The H20 robot has dual 6-DOF arms with 2-DOF grippers. Different marks are used to be attached with the labware lid for identification process. The Kinect sensor V2 is used to recognize and localize the mark of the required labware on a wide workstation. The difference of performance between the Kinect V1 and V2 is illustrated. SURF algorithm (Speeded-Up Robust Features) is used to recognize the target according to its local features. Some preprocessing steps are applied to the RGB frame to enhance the image features. The effects of strong lighting condition are eliminated by using polarization and intensity filters which are attached to the Kinect camera. The position estimation step is performed by applying a mapping process form the color frame to the depth frame of Kinect. The communication procedure between the Kinect platform and other robot platforms is done using client-server model. An efficient performance with high success rate is obtained under different lighting conditions.

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Grasping and Placing Operation for Labware Transportation in Life Science Laboratories using Mobile Robots

Mohammed Myasar Ali, Hui Liu, Norbert Stoll, Kerstin Thurow

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1227-1237 (2017);

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In automated working environments, mobile robots can be used for different purposes such as material handling, domestic services, and objects transportation. This work presents a grasping and placing operation for multiple labware and tube racks in life science laboratories using the H20 mobile robots. The H20 robot has dual arms where each arm consists of 6 revolute joints with 6-DOF and 2-DOF grippers. The labware, which have to be manipulated and transported, contain chemical and biological components. Therefore, an accurate approach for object recognition and position estimation is required. The recognition and pose estimation of the desired objects are very essential to guide the robotic arm in the manipulation tasks. In this work, the problem statement of H20 transportation system with the proposed methodology are presented. Different strategies (visual and non-visual) of labware manipulation using mobile robots are described. The H20 robot is equipped with a Kinect V2 sensor to identify and estimate the position of the target. The local features recognition based on SURF algorithm (Speeded-Up Robust Features) is used. The recognition process is performed for the required labware and holder to perform the grasping and placing operation. A strategy is proposed to find the required holder and to check its emptiness for the placing tasks. Different styles of grippers and labware containers are used to manipulate different weights of labware and to realize a safe transportation. The parts of mobile robot transportation system are communicated with each other using Asynchronous socket Channels.

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Face Recognition and Tracking in Videos

Swapnil Vitthal Tathe, Abhilasha Sandipan Narote, Sandipan Pralhad Narote

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1238-1244 (2017);

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Advancement in computer vision technology and availability of video capturing devices such as surveillance cameras has evoked new video processing applications. The research in video face recognition is mostly biased towards law enforcement applications. Applications involves human recognition based on face and iris, human computer interaction, behavior analysis, video surveillance etc. This paper presents face tracking framework that is capable of face detection using Haar features, recognition using Gabor feature extraction, matching using correlation score and tracking using Kalman filter. The method has good recognition rate for real-life videos and robust performance to changes due to illumination, environmental factors, scale, pose and orientations.

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Efficiency of Photovoltaic Maximum Power Point Tracking Controller Based on a Fuzzy Logic

Ammar Al-Gizi, Sarab Al-Chlaihawi, Aurelian Craciunescu

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1245-1251 (2017);

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This paper examines the efficiency of a fuzzy logic control (FLC) based maximum power point tracking (MPPT) of a photovoltaic (PV) system under variable climate conditions and connected load requirements. The PV system including a PV module BP SX150S, buck-boost DC-DC converter, MPPT, and a resistive load is modeled and simulated using Matlab/Simulink package. In order to compare the performance of FLC-based MPPT controller with the conventional perturb and observe (P&O) method at different irradiation (G), temperature (T) and connected load (RL) variations – rising time (tr), recovering time, total average power and MPPT efficiency topics are calculated. The simulation results show that the FLC-based MPPT method can quickly track the maximum power point (MPP) of the PV module at the transient state and effectively eliminates the power oscillation around the MPP of the PV module at steady state, hence more average power can be extracted, in comparison with the conventional P&O method.

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Model-based Development of Safety-critical Functions and ISO 26262 Work Products using modified EAST-ADL

Bülent Sari, Hans-Christian Reuss

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1252-1259 (2017);

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Safety is becoming more and more important with the ever increasing level of safety related E/E Systems built into the cars. Increasing functionality of vehicle systems through electrification of power train, in future even more by autonomous driving, leads to complexity in designing system, software and safety architecture. ISO 26262 aims to reduce the complexity and to approve the traceability of the different safety activities. This paper presents an approach about model-based development of system, software and safety architecture using Electronics Architecture and Software Technology – Architecture Description Language (EAST-ADL), being in line with the relevant standard ISO 26262. In particular, we briefly discuss how the main safety related activities, such as hazard analysis and risk assessment, developing functional and technical safety concepts and performing safety analysis can be performed model-based and how the activities can be related with system and software development. The state-of-art is also provided and compared with the proposed approach.

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On-Chip Testing Schemes of Through-Silicon-Vias (TSVs) in 3D Stacked ICs

Shadi MS. Harb, William R. Eisenstadt

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1260-1265 (2017);

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This paper presents on-chip testing structures to characterize and detect faulty Through Silicon Vias (TSVs) in 3D ICs technology. 3D Gunning Transceiver Logic (GTL) I/O testing is proposed to characterize the performance of 3D TSVs in high speed applications. The GTL testing circuit will fire different data patterns at different frequencies to characterize the transient performance of TSVs. In addition, Different testing schemes based on an oscillation ring testing methodology are proposed to detect TSVs faults such as stuck-at, open, slope and delay degradation, and severe crosstalk TSVs coupling. A parallel ring-based oscillator test structure is proposed and simulated based on a high performance fully tunable electrical circuit pi-model where a single and coupled TSVs with ground-signal-ground (GSG) and ground-signal-signal-ground (GSSG) 3D vias configurations are used as a test vehicle for 3D interconnect characterization and test. Simulation results are presented using the Keysight/Agilent Advance Design System (ADS) and a standard 0.25 µm CMOS process.

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Stability and nonlinear controller design of Fast-Lock Phase-Locked Loop in 0.18-µm CMOS

Fatima Al-Mutairi, Reem Al-Mutairi

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1266-1271 (2017);

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This paper introduces a kind of novel backstepping phase- locked loops (PLL). The paper presents a developed theoretical model of (PLL) frequency synthesizer and provides analytical equations for calculating the desired specification such as phase margin (PM). The proposed model aims to improve the control accuracy, ensure stability and reducing the lock time. Adaptive controller algorithm has been used to design a conventional phase locked loop to operate at 2.2GHz using 0.18 μm CMOS technology. The lock time was reduced by adding nonlinear controller in addition with the low-pass filter (LPF) and the tuning variables of the adaptive control to ensure the control accuracy. The simulation results confirm that the stability of the system has been improved and increase Phase Margin (PM) from 56o to 60o. Furthermore, the simulation results indicate that the performance of adaptive PLL control has greater speed response and smaller overshoot than conventional PLL. The lock time for the conventional PLL was 2.1 μs and it is reduced to 1 μs by adding adaptive controller, showing a reduction of the lock time by 53% over the classical PLL.

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Towards Deployment Strategies for Deception Systems

Daniel Fraunholz, Marc Zimmermann, Hans Dieter Schotten

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1272-1279 (2017);

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Network security is often built on perimeter defense. Sophisticated attacks are able to penetrate the perimeter and access valuable resources in the network. A more complete defense strategy also contains mechanisms to detect and mitigate perimeter breaches. Deceptive systems are a promising technology to detect, deceive and counter infiltration. In this work we provide an insight in the basic mechanisms of deception based cyber defense and discuss in detail one of the most significant drawbacks of the technology: The deployment. We also propose a solution to enable deception systems to a broad range of users. This is achieved by a dynamic deployment strategy based on machine learning to adapt to the network context. Different methods, algorithms and combinations are evaluated to eventually build a full adaptive deployment framework. The proposed framework needs a minimal amount of configuration and maintenance.

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Classification of patient by analyzing EEG signal using DWT and least square support vector machine

Mohd Zuhair, Sonia Thomas

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1280-1289 (2017);

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Epilepsy is a neurological disorder which is most widespread in human beings after stroke. Approximately 70% of epilepsy cases can be cured if diagnosed and medicated properly. Electro-encephalogram (EEG) signals are recording of brain electrical activity that provides insight information and understanding of the mechanisms inside the brain. Since epileptic seizures occur erratically, it is essential to develop a model for automatically detecting seizure from EEG recordings. In this paper a scheme was presented to detect the epileptic seizure implementing discrete wavelet transform (DWT) on EEG signal. DWT decomposes the signal into approximation and detail coefficients, the ApEn values the coefficients were computed using pattern length (m= 2 and 3) as an input feature for the Least square support vector machine (LS-SVM). The classification is done using LS-SVM and the results were compared using RBF and linear kernels. The proposed model has used the EEG data consisting of 5 classes and compared with using the approximate and detailed coefficients combined and individually. The classification accuracy of the LS-SVM using the RBF and Linear kernel with ApEn using different cases is compared and it is found that the best accuracy percentage is 100% with RBF kernel.

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Proposal for a Visualization System of Purchase Relationship Using ID-POS Data

Ko Hashimoto, Kohei Otake, Takashi Namatame

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1290-1297 (2017);

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In recent years, big data analysis is gaining immense credence in the fields of academics and business. Businesses such as management and marketing have demonstrated a strong inclination and interest in data analytics. However, many businesses are unable to utilize data even if they have access to it. The main reason for that is the lack of familiarity with data analytics procedures. Hence, a system needs to be developed that can perform data analytics and demonstrate its benefits. In this study, we use point of sales data obtained from a supermarket chain to analyze and show the relationship between purchase goods at the same time. A supermarket is one of the ideal places to demonstrate data analysis because retail stores have many purchase records and are always conducting various marketing activities. We propose an easy-to-handle visualization system to show the goods that are inter-related. By using our system, a store manager can obtain information about the item sales easily and interactively.

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Public transportation network design: a geospatial data-driven method

Alexey Golubev, Maxim Shcherbakov

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1298-1306 (2017);

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The paper explores an issue of efficient public transportation network design as a part of the urban developing process. Having data about everyday residents travelling inside of an urban area, we can consider this data as people’s requirements for the public transport system. We propose a novel method for initial public transportation network design based on clustered geospatial data containing origin/destination point of travel patterns of residents. The core of a method is a set of four algorithms for selecting terminal clusters based on a number of centres (or focuses). The appropriate quality criteria are proposed: degree of transport demand satisfaction, the coefficient of non-straightness, and transport network density. Use cases allow evaluating a performance of proposed method and give sufficient conclusions about its application.

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A Secure Communication Framework for ECUs

Ali Shuja Siddiqui, Yutian Gui, Jim Plusquellic, Fareena Saqib

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1307-1313 (2017);

View Description

Electronic Control Units (ECUs) generate diagnostic and telemetric data that is communicated over the internal vehicular network. ECUs are resource constraint devices and have limited resources to devote for data security. In recent times, threats against vehicular networks have emerged that require attention of the research community. In this paper, we demonstrate data security threats in automobile, and present a hardware based security framework that provides real time secure communication using lightweight cryptographic primitives and propose hardware based authentication protocol. Implementation details, performance and security analysis of proposed framework are presented.

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Content Reordering Based on Mouse-tracking for Web Applications

Md. Tanjim-Al-Akib, Lutfullahil Kabir Ashik, Krishanu Chowdhury, Md. Zahid Hasan, Hosne Al Walid

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1314-1322 (2017);

View Description

Rising usage of web applications in every aspect of life has created intense need of enhancement of user experience and formation of intelligent web applications. This research work was conducted with a view to do so. This paper focuses on the reorganization of web application content based on user’s specific interests while browsing any web application by providing new algorithms and a new approach.

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Multi-attribute Reverse Auction Design Based on Fuzzy Data Envelopment Analysis Approach

Deyan Chen, Dingwei Wang

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1323-1329 (2017);

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Multi-attribute reverse auction is widely used for the procurements of enterprises or governments. To overcome the difficulty of identifying bidding attribute weight and score function of the buyer, the multi-round auction and bidding models with multiple winners are established based on fuzzy data envelopment analysis. The winner determination model of the buyer considers the integrated input-output efficiency of k winners. The bidding strategy of seller is divided into two parts: the first one estimates the weight of the ideal supplier that is thought to be the buyer’s preference; the second one is to calculate the weight of the test supplier which reflects the change trend of current weights and the seller’s weakness. The final predicted weight is the weighted sum of both. On the basis of known weight, the test supplier can improve his efficiency to increase the winning chance in the next round auction. Our models comprise crisp numbers and fuzzy numbers. Finally, a numerical example verifies the validity of the proposed models.

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A Category Based Threat Evaluation Model Using Platform Kinematics Data

Mustafa Çöçelli, Ethem Arkın

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1330-1341 (2017);

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Command and control (C2) systems direct operators to make accurate decisions in the stressful atmosphere of the battlefield at the earliest. There are powerful tools that fuse various instant piece of information and brings summary of those in front of operators. Threat evaluation is one of the important fusion method that provides these assistance to military people. However, C2 systems could be deprived of valuable data source due to the absence of capable equipment. This situation has a bad unfavorable influence on the quality of tactical picture in front of C2 operators. In this paper, we study on the threat evaluation model that take into account these deficiencies. Our method extracts threat level of various targets mostly from their kinematics in two dimensional space. In the meantime, classification of entities around battlefield is unavailable. Only, category of targets are determined as a result of sensors process, which is the information of whether entities belong to air or surface environment. Hereby, threat evaluation model is consist of three fundamental steps that runs on entities belongs to different environment separately: the extraction of threat assessment cues, threat selection based on Bayesian Inference and the calculation of threat assessment rating. We have evaluated performance of proposed model by simulating a set of synthetic scenarios.

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This paper is an extension of work originally presented in 2017 6th International Conference on Industrial Technology and Management (ICITM) [53]. This research focuses on the mobilization of human resources in the Asian electrical industry and analyzes the impact of engineers’ international mobility on the innovation of enterprises in the host countries. I examine the characteristics of engineers who moved from Japan to China and South Korea to explore which types of engineers successful firms in China and South Korea select from rival companies in Japan. In addition, this study focuses on the role of the inventors’ networks to investigate the significance of researcher mobility and knowledge spillover as mechanisms that facilitate the flow of tacit knowledge. This study reveals that during the process of innovation, informal networks play an important role in the mobility of engineers. The findings suggest that successful firms require people with analytical skills and problem-solving capacity, not “star inventors.”

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Compact wireless control network protocol with fast path switching

Yasutaka Kawamoto, Makoto Kubomi, Yuichi Kado

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1350-1357 (2017);

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Sensor network protocol stacks require the addition or adjustment of functions based on customer requirements. Sensor network protocols that require low delay and low packet error rate (PER), such as wireless control networks, often adopt time division multiple access (TDMA). However, it is difficult to add or adjust functions in protocol stacks that use TDMA methods. Therefore, to add or adjust functions easily, we propose NES-SOURCE, a compact wireless control network protocol with a fast path-switching function. NES-SOURCE is implemented using carrier sense multiple access/collision avoidance (CSMA/CA) rather than TDMA. Wireless control networks that use TDMA prevent communication failure by duplicating the communication path. If CSMA/CA networks use duplicate paths, collisions occur frequently, and communication will fail. NES-SOURCE switches paths quickly when communication fails, which reduces the effect of communication failures. Since NES-SOURCE is implemented using CSMA/CA rather than TDMA, the implementation scale is less than one-half that of existing network stacks. Furthermore, since NES-SOURCE’s code complexity is low, functions can be added or adjusted easily and quickly. Communication failures occur owing to changes in the communication environment and collisions. Experimental results demonstrate that the proposed NES-SOURCE’s path-switching function reduces the amount of communication failures when the communication environment changes owing to human movement and others. Furthermore, we clarify the relationships among the probability of a changing communication environment, the collision occurrence rate, and the PER of NES-SOURCE.

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A Meta-analysis of Content and Language Integrated Learning in English

Jong-Keol Kim, Jeong-ryeol Kim

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1358-1362 (2017);

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The purpose of this study is to investigate the effects of integrated content and English education. To fulfill this, 30 studies conducted in elementary school setting matching the meta-analysis criteria, such as being quantitative, experimental, or having affective statistical results after searching for the key words of “content-based”, “theme-based” and “integrated learning” on the accessible databases such as RISS and Google scholar were selected. The results of meta-analysis are as follows: 1) Content-based integrated English education is more effective in improving English skills than improving affective factors. 2) There is no discernable difference in effect sizes among different grades. 3) Integrating with knowledge-based subjects were more effective than integrating with all the subjects.

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Hybrid Ontology-based knowledge with multi-objective optimization model framework for Decision Support System in intercropping

Kornkanok Phoksawat, Massudi Mahmuddin

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1363-1371 (2017);

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The problem of multi-criteria or multi-objective intercropping crop planning makes it vital to consider all related factors under the constraints that will produce the highest revenue and minimum cost. Principles of intercropping elements including soil type, plant area, plant diseases, planting and harvesting time and economics factors (e.g. price, cost) are some of the factors in making decisions. Intercropping is important in the situation such as during inability to harvest main crops, co-cultivation to increase productivity, or even to increase extra revenue. Therefore, the decision-making system requires a wise decision support system, which can advise farmers on economics matters. In this article, we present the decision support system (DSS) model framework for planting rubber with intercropping by a hybrid approach using ontology-based knowledge consuming rule concepts and relationships for intercropping with integrated multi-objectives optimization to recommend the crop to be planted and the suitable proportion of planting areas or planting co-suited to the rubber plantation of farmers. This approach could be applied as a guideline for another field, such as production problems or other resource allocation issues.

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Evaluating the Effect of Mozart Music and White Noise on Electroencephalography Pattern toward Visual Memory

Syarifah Noor Syakiylla Sayed Daud, Rubita Sudirman

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1372-1380 (2017);

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Listening to auditory stimuli during study can give positive and negative influence on human cognitive processing. Thus, it has attracted researchers to conduct studies using various types of auditory stimuli. Some researchers believe that Mozart music and white noise are able to give positive influence on cognitive performance. However, most of the past studies gave more attention towards spatial task. Very little studies have been made on the effect of Mozart music and white noise towards memorizing task. Besides, the effect of these auditory stimuli on task difficulty has also not been studied deeply. Hence, the aims of this study were to investigate the effect of Mozart music and white noise on memory performance with different task difficulty levels; and to propose an effective background stimuli condition for memorization. Experiments have been conducted involving 60 healthy adults that required them to memorize the visual memory task with two difficulty levels; i.e. easy and difficult. Brain signal was recorded during memorization duration using 10-20 electrode placement system of electroencephalography (EEG) machine. EEG is a neurological test for measuring and recording the electrical activity of the brain. The effect of sound stimuli on memory performance was evaluated based on memorization test score and brain activity. The wavelet approach was used in processing the EEG data. Based on the memorizing test score result, the subjects are able to memorize better when listening to white noise compared to Mozart music at different difficulty levels. Listening to auditory stimuli can influence the electroencephalography pattern and brain activity. The level of sensory processing and attention increases when listening to white noise which cause the increase of relative gamma (easy level: p-value = 0.005; difficult level: p-value = 0.007) and beta power (easy level: p-value = 0.001; difficult level: p-value = 0.003). Thus, in this study, it is found that listening to white noise is far more effective in memorizing process compared to Mozart music.

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A Way for Measuring the Temperature Transients of Capacitors

Zoltan Sarkany, Marta Rencz

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1381-1389 (2017);

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With the increasing integration level of electronic circuits management of the generated heat became one of the most important design aspects. Beside the semiconductor components capacitors are also affected by the elevated temperature. In this paper a new thermal characterization method is proposed adopting the thermal transient measurement technique for capacitors utilizing the capacitance itself as temperature dependent parameter. The proposed switched capacitor based circuit generates a signal proportional to the capacitance of the component and hence the temperature. The measurement method is demonstrated on self and transfer resistance measurement setups and also verified using CFD simulations. It is shown that the captured thermal transient curve can even be used to fine tune the inaccurate simulation model parameters achieving a more accurate calibrated 3D simulation model.

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Radiation Hybrid Mapping: A Resampling-based Method for Building High-Resolution Maps

Raed Seetan, Jacob Bible, Michael Karavias, Wael Seitan, Sam Thangiah

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1390-1400 (2017);

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Abstract— The process of mapping large numbers of markers is computationally complex, as the increase of numbers of markers results in an exponential increase in the mapping runtime. Also, having unreliable markers in the dataset adds more complexity to the mapping process. In this research, we have addressed these two issues and proposed our solution. The proposed approach builds solid maps in two phases: Phase 1 builds an initial map following these steps: 1) Resample the original dataset to generate variant datasets, then cluster all resampled datasets into groups of markers. 2) Merge all groups of markers to filter out unreliable markers. 3) Generate a Map for each group of markers. 4) Concatenate all groups’ maps to form the final map. Phase 2, Adds more markers to the initial framework to build a high resolution map as follows: 1) Use Kmeans algorithm to filter out unreliable markers and cluster the remaining markers. 2) Insert the remaining markers in their best positions in the initial framework. To evaluate the performance of the proposed approach, we compare our constructed maps on the human genome with the physical maps. Moreover, we compare our constructed maps with a state-of-the-art tool for building maps. Experiment results show that the proposed approach has a very low computational complexity and produces solid maps with high agreement with the physical maps.

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Two-axis Gimbal with Passive Revolute Joints for Motion Isolation of a Stabilizing Mechanism

Erick Moya, Keizo Araki, Masaki Okada, Akira Mizuno, Kenjiro Tadakuma, Riichiro Tadakuma

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1401-1412 (2017);

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Energy efficiency is a salient design consideration for stabilization mechanisms when assembled on a battery-powered vehicle. In this paper we study the implementation of a two-axis gimbal with passive revolute joints for motion isolation of an inertially stabilized platform (ISP) mounted on a host vehicle. The objective is for the ISP to maintain a steady line of sight (LOS) of a payload placed in an arbitrary position on the ISP workspace by performing mass stabilization. The proposed method eliminates the need to operate gimbal motors throughout the operation of the host vehicle, stabilizing the platform LOS by relying on the gimbal passive joints acting as suspension to isolate the ISP from disturbances imparted by the host vehicle. We describe the principle of operation and a prototype of the proposed stabilizing mechanism is presented.

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Modeling and Performance Evaluation of a Top Gated Graphene MOSFET

Jith Sarker, Abu Shami Md. Zadid Shifat, Rezoan Ahmed Shuvro

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1413-1421 (2017);

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In the modernistics years, Graphene has become a promising resplendence in the horizon of fabrication technology, due to some of its unique electronic properties like zero band gap, high saturation velocity, higher electrical conductivity and so on followed by extraordinary thermal, optical and mechanical properties such as- high thermal conductivity, optical transparency, flexibility and thinness. Graphene based devices demand to be deliberated as a possible option for post Si based fabrication technology. In this paper, we have modelled a top gated graphene metal oxide semiconductor field effect transistor (MOSFET). Surface potential dependent Quantum capacitance is obtained self-consistently along with linear and square root approximation model. Gate voltage dependence of surface potential has been analyzed with graphical illustrations and required mathematics as well. Output characteristics, transfer characteristics, transconductance (as a function of gate voltage) behavior have been investigated. In the end, effect of channel length on device performance has been justified. Variation of effective mobility and minimum carrier density with respect to channel length has also been observed. Considering all of the graphical illustrations, we do like to conclude that, graphene will be a successor in post silicon era and bring revolutionary changes in the field of fabrication technology.

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CAM-Infrastructure: a novel solution for service advertisement in Cooperative Intelligent Transportation Systems

Badis Hammi, Houda Labiod, Gérard Segarra, Alain Servel, Jean Philippe Monteuuis

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1422-1431 (2017);

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Cooperative Intelligent Transportation Systems (C-ITS) are gaining ground and currently are almost part of our everyday life. A C-ITS environment can provide numerous services that soon will become essential to roads’ users. The latter resides in improvement of road safety, entertainment, and commercial services. However, in order to provide such services, the C-ITS environment needs an advertisement and dissemination service for them. Indeed, users have to be aware of the available services in order to request them if needed. Current standards of service announcement show their limits, especially regarding the interoperability between communication profiles. For this reason, in this paper, we describes our new service advertisement solution called CAM-Infrastructure. The latter is compliant with ETSI standards and is deployed in SCOOP@F, a nationwide scale project.

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Use of machine learning techniques in the prediction of credit recovery

Rogerio Gomes Lopes, Marcelo Ladeira, Rommel Novaes Carvalho

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1432-1442 (2017);

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This paper is an extended version of the paper originally presented at the International Conference on Machine Learning and Applications (ICMLA 2016), which proposes the construction of classifiers, based on the application of machine learning techniques, to identify defaulting clients with credit recovery potential. The study was carried out in 3 segments of a Bank’s operations and achieved excellent results. Generalized linear modeling algorithms (GLM), distributed random forest algorithms (DRF), deep learning (DL) and gradient expansion algorithms (GBM) implemented on the H2O.ai platform were used.

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Monocular Height Estimation Method with 3 Degree-Of-Freedom Compensation of Road Unevennesses

Alex Masuo Kaneko, Kenjiro Yamamoto

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1443-1452 (2017);

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Height estimation of objects is a valuable information for locomotion of autonomous robots and vehicles. Even though several sensors such as stereo cameras have been applied in these systems, cost and processing time have been motivating solutions with monocular cameras. This research proposes two new methods: i) height estimation of objects using only a monocular camera based on flat surface constraints and ii) 3 degree-of-freedom compensation of errors caused by roll, pitch and yaw variations of the camera when applying the Flat Surface Model. Experiments outdoors with the KITTI benchmark data (4997 frames and 436 objects) resulted in improved accuracy of the estimated heights from a maximum error of 1.51 m to 1.12 m and reduced number of estimation failures by 4 times, proving the validity and effectiveness of the proposed method.

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Scalability Dilemma and Statistic Multiplexed Computing — A Theory and Experiment

Justin Yuan Shi, Yasin Celik

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1453-1460 (2017);

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The For the last three decades, end-to-end computing paradigms, such as MPI (Message Passing Interface), RPC (Remote Procedure Call) and RMI (Remote Method Invocation), have been the de facto paradigms for distributed and parallel programming. Despite of the successes, applications built using these paradigms suffer due to the proportionality factor of crash in the application with its size. Checkpoint/restore and backup/recovery are the only means to save otherwise lost critical information. The scalability dilemma is such a practical challenge that the probability of the data losses increases as the application scales in size. The theoretical significance of this practical challenge is that it undermines the fundamental structure of the scientific discovery process and mission critical services in production today.

In 1997, the direct use of end-to-end reference model in distributed programming was recognized as a fallacy. The scalability dilemma was predicted. However, this voice was overrun by the passage of time. Today, the rapidly growing digitized data demands solving the increasingly critical scalability challenges. Computing architecture scalability, although loosely defined, is now the front and center of large-scale computing efforts.

Constrained only by the economic law of diminishing returns, this paper proposes a narrow definition of a Scalable Computing Service (SCS). Three scalability tests are also proposed in order to distinguish service architecture flaws from poor application programming. Scalable data intensive service requires additional treatments. Thus, the data storage is assumed reliable in this paper. A single-sided Statistic Multiplexed Computing (SMC) paradigm is proposed. A UVR (Unidirectional Virtual Ring) SMC architecture is examined under SCS tests. SMC was designed to circumvent the well-known impossibility of end-to-end paradigms. It relies on the proven statistic multiplexing principle to deliver reliable service using faulty components as the infrastructure expands or contracts.

To demonstrate the feasibility of such a theoretical SCS, an organized suite of experiments were conducted comparing two SMC prototypes against MPI (Message Passing Interface) using a naive dense matrix multiplication application. Consistently better SMC performance results are reported.

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Embedded C Programming Using FRDM to Enhance Engineering Students’ Learning Skill

Zulzilawati Jusoh, Mohamad Taib Miskon, Hasnorhafiza Husni, Nur Hafizah Rabi’ah Husin

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1461-1466 (2017);

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Computer programming course that utilizes languages such as C/C++ is always packed with dreary syntax details that consume most of the students’ learning time to obtain ‘grammatically’ correct source code. Consequently, it is difficult for most of the students to apply the theory they have learned in a real life context. Thus, this project proposed a hardware based learning approach for C programming curriculum and reports the effectiveness of using microcontroller board named FRDM-KL05Z to assist teaching and learning activities. The USB-powered microcontroller board is very easy to use and is programmable using C programming language. Students will have the opportunity to learn selection statement with real sensors, touse repetition statement to blink LEDs and utilizing function as well as structure to control actual input and output peripherals. In general we evaluated the students’ response in five criteria namely the students attributes, lecturer’s profile, implementation, facilities and students’ understanding. From the survey, the results in exit survey are higher compared to entrance survey for all criteria. This shows that the students are satisfied with the implementation of the module which has increased their understanding in learning C Programming.

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A Modified Patch Antenna with Square-Open Loop Resonator Slot for Improved Bandwidth Performance in WiFi Applications

Rida Gadhafi, Mihai Sanduleanu

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1467-1471 (2017);

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A novel, modified square patch antenna with square open loop resonator slot, operating at 5.5 GHz, for improved bandwidth performance is proposed in this article. A complementary square open loop resonator is introduced on the patch to enhance the bandwidth more than twice that of the conventional square patch antenna operating at the same frequency. A prototype of the antenna operating at 5.5 GHz is designed and fabricated. Results show that 2:1 VSWR bandwidth of the antenna is 7% whereas the conventional square patch antenna offers only 3% bandwidth. The proposed antenna has a compact size of 1.9 cm x 2 cm. It offers a uniform gain of 4.25 dB and a directivity of 6.1 dB at the frequency of operation.

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A comparative study for using the LBC format for compressing static medical images

Ildikó-Angelica Szöke, Vasile Stoicu-Tivadar, Diana Lungeanu

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1472-1477 (2017);

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This paper is an extension of work originally presented at conference Applied Machine Intelligence and Informatics (SAMI), 2017 IEEE 13th International Symposium. The article performs a comparative study between the image compression technique Local Binary Compressed format (LBC) proposed by the authors and the standard image compression techniques used today (BMP, JPEG, PNG and GIF). The study is carried out for large medical images that need to be stored for longer periods of time. In the study, the most common types of medical images used are: X-rays and ultrasounds images. This study aimed to determine the distribution laws parameters used to reconstruct the image as well as to determine the influence of the most used medical image formats on the compression process. The effective representation of image format LBC is proven using an image quality index type, the Structural Similarity Index (SSIM).

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Image Navigation Using A Tracking-Based Approach

Stephen Craig Stubberud, Kathleen Ann Kramer, Allen Roger Stubberud

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1478-1486 (2017);

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Navigation is often performed using the Global Positioning Satellite system. However, the system is not always reliable for use at all times in all contexts. Reliance solely on such systems could endanger a vessel or get people lost. Another approach to provide navigation is to use known landmarks and triangulate one’s position. A navigation solution can be automatically generated using image data. In this paper, a target-tracking based approach for navigation using imagery is developed. The technique is based on an extended Kalman filter that uses angle measurements only. The technique is developed to use landmarks known a priori and landmarks that are first tracked by the vessel navigating and then used as known landmarks. The issues of observability to the development are considered. Image tracking from video frame to video frame is a further element. The frame-to-frame image correlation technique, the phase-only filter, is used to provide a low uncertainty estimate of the position of elements based upon the image frame. This provides an estimate of bearing angle that can be combined with a bearing from other known landmarks to fix and track the platform to provide a navigation solution.

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Analytical and Algorithmic Approaches to Determine the Number of Sensor Nodes for Minimum Power Consumption in LWSNs

Nukhet Sazak, Ali Soner Kilinc

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1487-1490 (2017);

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A Linear Wireless Sensor Network (LWSN) is a kind of wireless sensor network where the nodes are deployed in a line. Since the sensor nodes are energy restricted, energy efficiency becomes one of the most significant design issues for LWSNs as well as wireless sensor networks. With the proper deployment, the power consumption could be minimized by adjusting the distance between the sensor nodes which is known as hop length. In this paper, analytical and algorithmic approaches are presented to determine the number of hops and sensor nodes for minimum power consumption in a linear wireless sensor network including equidistantly placed sensor nodes.

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System for the Automatic Estimation of the Tilt Angle of a Flat Solar Collector

Jorge Fonseca-Campos, Paola N. Cortez-Herrera, Israel Reyes-Ramírez

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1491-1501 (2017);

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In this work, a compact system for the automatic estimation of the tilt angle at any location of the world is presented. The system components are one computer, one GPS receiver and one Python program. The tilt angle is calculated through the maximization of the flux of direct radiation incident upon a flat solar collector. An estimation of the adjustments of this angle at different time periods are obtained. This angle is calculated in steps of six minutes during a whole year. Daily, monthly, biannually and yearly averages of this value are obtained. A comparison of the energetic gain when the tilt angle changes at the different time periods is made as well. Because, the algorithm doesn’t receive as an input the solar radiation incident upon a surface at the location of the calculation, a comparison was made between the results obtained and the results reported for the monthly tilt angle of 22 different places. The root mean square error obtained with this comparison was between 1.5 and 9.5 degrees. The monthly tilt angle estimated deviated in average for less than 6.3° with respect to the values reported for the different locations. Finally, the application of a correction factor in the monthly estimated angles is proposed, which might increase the collected energy.

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Source Code Vulnerabilities in IoT Software Systems

Saleh Mohamed Alnaeli, Melissa Sarnowski, Md Sayedul Aman, Ahmed Abdelgawad, Kumar Yelamarthi

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1502-1507 (2017);

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An empirical study that examines the usage of known vulnerable statements in software systems developed in C/C++ and used for IoT is presented. The study is conducted on 18 open source systems comprised of millions of lines of code and containing thousands of files. Static analysis methods are applied to each system to determine the number of unsafe commands (e.g., strcpy, strcmp, and strlen) that are well-known among research communities to cause potential risks and security concerns, thereby decreasing a system’s robustness and quality. These unsafe statements are banned by many companies (e.g., Microsoft). The use of these commands should be avoided from the start when writing code and should be removed from legacy code over time as recommended by new C/C++ language standards. Each system is analyzed and the distribution of the known unsafe commands is presented. Historical trends in the usage of the unsafe commands of 7 of the systems are presented to show how the studied systems evolved over time with respect to the vulnerable code. The results show that the most prevalent unsafe command used for most systems is memcpy, followed by strlen. These results can be used to help train software developers on secure coding practices so that they can write higher quality software systems.

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Lookup Tables-based mean level detection of spatially distributed targets in non Gaussian clutter

Nabila Nouar, Atef Farrouki

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1508-1514 (2017);

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In this paper, Constant False Alarm Rate (CFAR) detection of spatially distributed targets embedded in compound Gaussian clutter with Inverse Gamma texture is addressed. By taking into account the fact that clutter parameters are unknown in practical situations, we propose mean level based on Lookup Tables detectors, that operate as a two-step approach, which consists of computing threshold factors that maintain a Constant Probability of False Alarm (Pfa) using intensive Monte Carlo simulations, and storing these factors in Lookup Tables, this first step is done independently from the detection algorithm. Then, at the detection stage, the detectors structure is associated to the Maximum Likelihood (ML) estimation technique to estimate the shape and the scale parameters, and compare them to the closest integer and half integer values in the Lookup Tables, to select the suitable threshold factor. Under the High Resolution Radar (HRR) assumption, the target is spread over a number of cells according to the Multiple Dominant scattering centers (MDS) representation. The binary total binary hypothesis tests are derived using the expression of the overall target energy, which is computed as the sum of the energies reflected from each cell.

Performance analysis of the proposed detectors is carried out using Monte Carlo simulation for various couples of clutter parameters and MDS models, and are compared to those of the Cell Averaging Based on Lookup Tables detector (CA-LT). In order to assess the performances of the proposed detectors in terms of the radar resolution, their performances are compared to the case of point-like targets.

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A Machine Learning based Framework for Parameter based Multi-Objective Optimisation of Video CODECs

Maryam Al-Barwani, Eran A. Edirisinghe

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1515-1526 (2017);

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All multimedia devices now incorporate video CODECs that comply with international video coding standards such as H.264 / MPEG4-AVC and the new High Efficiency Video Coding Standard (HEVC), otherwise known as H.265. Although the standard CODECs have been designed to include algorithms with optimal efficiency, a large number of coding parameters can be used to fine-tune their operation, within known constraints of for example, available computational power, bandwidth, energy consumption, etc. With the large number of such parameters involved, determining which parameters will play a significant role in providing optimal quality of service within given constraints is a further challenge that needs to be met. We propose a framework that uses machine learning algorithms to model the performance of a video CODEC based on the significant coding parameters. We define objective functions that can be used to model the video quality as Peak Signal-to-Noise Ratio (PSNR), CPU time utilization and Bit-Rate. We show that these objective functions can be practically utilised in video Encoder designs, in particular in their performance optimisation within given constraints. A Multi-objective Optimisation framework based on Genetic Algorithms is thus proposed to optimise the performance of a video codec. The framework is designed to jointly minimize the complexity, Bit-rate and to maximize the quality of the compressed video stream.

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2-D and 3-D Visualization of Many-to-Many Relationships

SeungJin Lim

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1527-1539 (2017);

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With the unprecedented wave of Big Data, the importance of information visualization is catching greater momentum. Understanding the underlying relationships between constituent objects is becoming a common task in every branch of science, and visualization of such relationships is a critical part of data analysis. While the techniques for the visualization of binary relationships are widespread, visualization techniques for ternary or higher relationships are lacking. In this paper, we propose a 3-D visualization primitive which is suitable for such relationships. The design goals of the primitive are discussed, and the effectiveness of the proposed visual primitive with respect to information communication is demonstrated in a 3-D visualization environment.

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On the Performance of a Clustering-based Task Scheduling in a Heterogeneous System

Hidehiro Kanemitsu, Masaki Hanada, Emilia Ndilokelwa Weyulu, Moo Wan Kim

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1540-1548 (2017);

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Recent task scheduling algorithms for a generalized workflow job in heterogeneous system adopt list-based scheduling. In those algorithms, the response time cannot be effectively reduced if the given workflow job is data-intensive. If the workflow job is computationally intensive, an attempt is made to assign tasks to many processors, which can lead to resource starvation. To this end, a task scheduling algorithm that is based on clustering tasks, called CMWSL (Clustering for Minimizing the Worst Schedule Length) has been proposed. In CMWSL, the lower bound of the assignment unit size for each processor is derived in order to suppress the total number of executing processors for effective use of processors. After the lower bound is derived, the processor as a assignment target is determined and then the assignment unit as a task cluster is generated. As a final phase of CMWSL, task ordering is performed for every assigned task. In this paper, we compare several task ordering methods in CMWSL in a real environment to find the best task ordering policy.

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Modeling and Control of Collaborative Robot System using Haptic Feedback

Vivekananda Shanmuganatha, Lad Pranav Pratap, Pawar Mansi Shailendrasingh

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1549-1555 (2017);

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When two robot systems can share understanding using any agreed knowledge, within the constraints of the system’s communication protocol, the approach may lead to a common improvement. This has persuaded numerous new research inquiries in human-robot collaboration. We have built up a framework prepared to do independent following and performing table-best protest object manipulation with humans and we have actualized two different activity models to trigger robot activities. The idea here is to explore collaborative systems and to build up a plan for them to work in a collaborative environment which has many benefits to a single more complex system. In the paper, two robots that cooperate among themselves are constructed. The participation linking the two robotic arms, the torque required and parameters are analyzed. Thus the purpose of this paper is to demonstrate a modular robot system which can serve as a base on aspects of robotics in collaborative robots using haptics.

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Lifelong Learning Application: Mobile Application to Promote Lifelong Learning and Introduce Educational Institutions

Wongpanya Nuankaew, Pratya Nuankaew, Kanakarn Phanniphong

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1556-1564 (2017);

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Education is the raising of the thinking process and developing the mind in a broader perspective. However, education that is comprehensive and appropriate to the individual according to its potential, ability and skill is too hardest to describe. Thus, matching and referral institutions, including education model that suits the person’s behavior has been receiving attention. The purpose of this research is to study and develop the applications that support the development of the learner’s education process with the highest degree of achievement. The material and method are consisting of five main processes, including 1) requirement definition, 2) system and software design, 3) implementation and unit testing, 4) integration and system testing, and 5) operation and maintenance. The data collection were collected from 431 samples, which divided into 4 targets; 186 high school students at Phadungnaree School, Maha Sarakham province, 191 university students at Rajabhat Mahasarakham University, 12 head of institutions at Phadungnaree School and Rajabhat Mahasarakham University, and 42 secondary teachers and university lecturers at Phadungnaree School and Rajabhat Mahasarakham University. According to the results of research, it is indicated that the total satisfaction toward the application are highest, which is equal to 4.32, and the groups with the highest levels of satisfaction are university students, which is equal to 4.43. It can be concluded that the application is appropriate and it is advisable for students who wish to study at university.

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Planning an Availability Demonstration Test with Consideration of Confidence Level

Frank Müller, Bernd Bertsche

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1565-1576 (2017);

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The full service life of a technical product or system is usually not completed after an initial failure. With appropriate measures, the system can be returned to a functional state. Availability is an important parameter for evaluating such repairable systems: Failure and repair behaviors are required to determine this availability. These data are usually given as mean value distributions with a certain confidence level. Consequently, the availability value also needs to be expressed with a confidence level.

This paper first highlights the bootstrap Monte Carlo simulation (BMCS) for availability demonstration and inference with confidence intervals based on limited failure and repair data. The BMCS enables point-, steady-state and average availability to be determined with a confidence level based on the pure samples or mean value distributions in combination with the corresponding sample size of failure and repair behavior. Furthermore, the method enables individual sample sizes to be used. A sample calculation of a system with Weibull-distributed failure behavior and a sample of repair times is presented.

Based on the BMCS, an extended, new procedure is introduced: the “inverse bootstrap Monte Carlo simulation” (IBMCS) to be used for availability demonstration tests with consideration of confidence levels. The IBMCS provides a test plan comprising the required number of failures and repair actions that must be observed to demonstrate a certain availability value. The concept can be applied to each type of availability and can also be applied to the pure samples or distribution functions of failure and repair behavior. It does not require special types of distribution. In other words, for example, a Weibull, a lognormal or an exponential distribution can all be considered as distribution functions of failure and repair behavior.

After presenting the IBMCS, a sample calculation will be carried out and the potential of the BMCS and the IBMCS investigated.

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A Reliable, Non-Invasive Approach to Data Center Monitoring and Management

Moises Levy, Jason O. Hallstrom

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1577-1584 (2017);

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Recent standards, legislation, and best practices point to data center infrastructure management systems to control and monitor data center performance. This work presents an innovative approach to address some of the challenges that currently hinder data center management. It explains how monitoring and management systems should be envisioned and implemented. Key parameters associated with data center infrastructure and information technology equipment can be monitored in real-time across an entire facility using low-cost, low-power wireless sensors. Given the data centers’ mission critical nature, the system must be reliable and deployable through a non-invasive process. The need for the monitoring system is also presented through a feedback control systems perspective, which allows higher levels of automation. The data center monitoring and management system enables data gathering, analysis, and decision-making to improve performance, and to enhance asset utilization.

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An Ontology-Based Temporal Scheduling and Complexity Reduction Model for Timetabling Knowledge Management

Patience Usoro Usip, Enobong Moses Umoren, Udoinyang Godwin Inyang, Mfonobong Maurice Ntekop

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1585-1591 (2017);

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Technological tools such as Semantic Web and ontologies have contributed immensely to the reduction of most managerial complexities on daily basis. However, most resolved complexities are solely dependent on the emerging issues which are not general enough to accommodate some specific domain challenges. Temporal scheduling complexities occur in several domains including timetabling, but inter-departmental courses allocation on a general institutional timetable has not been considered. This poses serious managerial concerns and threats to the academic performance of any institution. This paper is aimed at formalizing an ontology model for analyzing temporal scheduling complexities in an existing schedule and giving optimal possible time scheduling resolutions showing their reduction rates for efficient and intelligent knowledge management. Protégé was used in modeling the domain ontology described in the resulted ontograf. The semantics of the formal ontology model is described based on Allen’s interval temporal relations. The use of ontologies make way for easy and intelligent reasoning with knowledge and exposes the need for such knowledge management tool to manage the influx of the numerous data.

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COTS – Harsh Condition Effects Considerations from Technology to User Level

Kirsten Weide-Zaage, Guillermo Payá-Vayá

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1592-1598 (2017);

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Radiation hardened devices are mostly extremely expensive. The continuously downscaling of microelectronic structures and the unavoidable presence of particle radiation on ground and in space leads to unwanted failures in electronic devices. Furthermore it is expected that in the next few years around 8000 new satellites will be launched around the world. Due to the enormous increasing need for Rad-Hard devices, there will be more focus on Commercial Of The Shelf (COTS) devices, which costs are lower. Also nowadays microelectronics for automotive systems are tested to withstand radiation especially SEU-single event upsets. It is clear that SEU cannot be ignored anymore especially in the application of unmanned autonomous vehicles and systems. Reliability testing is expensive and extremely time consuming. The use of COTS-Commercials of the shelf is the ultimate goal to reach. In this paper, an overview of radiation effects on different CMOS technologies used in COTS devices is given. These effects can be considered while selecting different functional equivalent COTS devices implemented with different technologies. Moreover, an overview of software techniques used in programmable commercial devices to reduce the radiation effects is also described.

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A Secure Automated Elevator Management System and Pressure Sensor based Floor Estimation for Indoor Mobile Robot Transportation

Ali Abduljalil Abdulla, Hui Liu, Norbert Stoll, Kerstin Thurow

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1599-1608 (2017);

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In this paper, a secure elevator handling system is presented to enable a flexible movement of wheeled mobile robots among laboratories distributed in different floors. The automated handling system consists mainly of an ADAM module which has the ability to call the elevator to the robot’s current floor and to request the destination floor. The LPS25HP pressure sensor attached to an STM32F411 microcontroller is utilized as a height measurement system to estimate the robot’s current floor inside the elevator. The ultrasonic sensor is used to recognize the elevator’s door status. Many challenges have to be solved to realize a stable height measurement system based on pressure sensor readings. The difference of the pressure sensor readings before and after soldering is realized by comparing the reading after soldering with an accurate barometric reading. In addition, the sensor output signal shows oscillation and wide variation of the same floor pressure sensor readings at different times. The oscillation in the output signal has been handled using a first order FIR smoothing filter. The first order filter was selected to balance between the stability and the elapsed time to receive the updated values. An auto-calibration stage is established to maintain the wide variation in the atmospheric pressure readings by calibrating the sensor readings with the robot’s current floor before entering the elevator. An error handling management system is utilized to guarantee a stable automated elevator management system performance. Many experiments to assess and verify the performance of the automated elevator management system and robot’s current floor estimation are reported. The experimental results show that the proposed methods and sub-systems developed for the mobile robot are effective and efficient in providing a transportation service in multiple-floor life sciences laboratories.

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Call Arrival Rate Prediction and Blocking Probability Estimation for Infrastructure based Mobile Cognitive Radio Personal Area Network

Neeta Nathani, Gopal Chandra Manna

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1609-1615 (2017);

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The Cognitive Radio usage has been estimated as non-emergency service with low volume traffic. Present work proposes an infrastructure based Cognitive Radio network and probability of success of CR traffic in licensed band. The Cognitive Radio nodes will form cluster. The cluster nodes will communicate on Industrial, Scientific and Medical band using IPv6 over Low-Power Wireless Personal Area Network based protocol from sensor to Gateway Cluster Head. For Cognitive Radio-Media Access Control protocol for Gateway to Cognitive Radio-Base Station communication, it will use vacant channels of licensed band. Standalone secondary users of Cognitive Radio Network shall be considered as a Gateway with one user. The Gateway will handle multi-channel multi radio for communication with Base Station. Cognitive Radio Network operators shall define various traffic data accumulation counters at Base Station for storing signal strength, Carrier-to-Interference and Noise Ratio, etc. parameters and record channel occupied/vacant status. The researches has been done so far using hour as interval is too long for parameters like holding time expressed in minutes and hence channel vacant/occupied status time is only probabilistically calculated. In the present work, an infrastructure based architecture has been proposed which polls channel status each minute in contrary to hourly polling of data. The Gateways of the Cognitive Radio Network shall monitor status of each Primary User periodically inside its working range and shall inform to Cognitive Radio- Base Station for preparation of minutewise database. For simulation, the occupancy data for all primary user channels were pulled in one minute interval from a live mobile network. Hourly traffic data and minutewise holding times has been analyzed to optimize the parameters of Seasonal Auto Regressive Integrated Moving Average prediction model. The blocking probability of an incoming Cognitive Radio call has been assessed as a function of instantaneous occupancy and the block size of trunk servers.

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Soft Handoff Evaluation and Efficient Access Network Selection in Next Generation Cellular Systems

Moses Ekpenyong, Daniel Asuquo, Samuel Robinson, Imeh Umoren, Etebong Isong

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1616-1625 (2017);

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The increased motivation (by service providers) to offer user-centric and seamless communication services – that satisfies users’ quality of experience (QoE), has manifested a myriad of challenges in the field of wireless communication; and given the increased traffic capacity and sudden explosion of cellular devices, communication systems are constantly threatened by performance related issues – including soft handoff. Although intelligent techniques have evolved to provide solutions to these issues, they are yet to flourish in the area of soft handoff. This contribution therefore proposes a framework that integrates two components: (i) machine learning methodologies: self-organizing map (SOM) and pattern classification – for robust performance evaluation of available soft handoff data; (ii) multiple attribute decision making mechanisms (MADM): the Analytical Hierarchy Process (AHP) – which result feeds the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) – for efficient access network selection.
Implementation of component one of the design revealed that SOM enabled a precise visualization of handoff features that influenced the system performance; and the error levels of training, validation and test dataset, with number and percentage of correct and incorrect classifications, were obtained from our pattern classifier.
Implementation of component two of the design for four heterogeneous (access) networks indicated that although network two (N2) was selected as best access network by TOPSIS and network three (N3) by Synthetic Extent Analysis (SEA) – a method adopted in a related paper, for a particular application; both TOPSIS and SEA selected N1 as second best alternative access network and network four (N4) as third best alternative network, despite the issue of ranking abnormality in TOPSIS. Further, AHP and TOPSIS can effectively be applied as MADM algorithms in handoff decision framework for selecting the best available network for handoff.

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Proposal of an Embedded Methodology that uses Organizational Diagnosis and Reengineering: Case of bamboo panel company

Eva Selene Hernández Gress, Antonio Oswaldo Ortega Reyes, Jaime Garnica González, José Ramón Corona Armenta

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1626-1633 (2017);

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This work is an extension of the Proceedings of the International Conference on Industrial Engineering, Management Science and Applications, which presented some of the phases of Reengineering applied to Bamboo Panel Company; the results were Strategic planning, Systemic Diagnosis and Performance Indicators through the Balanced Scorecard. Now, the main purpose of this article is to present a methodology that embedding Organizational Diagnosis and Reengineering, which emphasizes the incorporation of culture, context, management style, and knowledge as well as inner and outer actors. The results of the proposed methodology applied to the case study are included, up to the moment of the writing of this article. Future work consists on the development of strategies for Innovation as a strategy planned in the Balanced Scorecard and derived from the embedded methodology.

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Three-Dimensional EEG Signal Tracking for Reproducible Monitoring of Self-Contemplating Imagination

Qinglei Meng, Deepa Gupta, Abenezer Wudenhe, Xiaoming Du, L. Elliot Hong, Fow-Sen Choa

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1634-1646 (2017);

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Electroencephalography (EEG) can globally monitor neural activity in millisecond scale, which is critical for identifying causality of human brain functions and mechanisms. However, to obtain accurate EEG stimulation-response relationship one usually needs to repeat multiple-ten times of stimulation-response recording to average out background signals of other irreverent brain activities, making real-time monitoring difficult to be accomplished. In this study, we explored new approaches which don’t require repeats. EEG signals were recorded from subjects doing mind tasks including image formation of motor functions or emotional subjects and mathematical calculations in mind. Time stamps in EEG recording were used to mark task completion time. Signals within 300ms or 1,000ms before task completions were analyzed. Using sLoreta 3-D tracking we found that delta-wave activities were mostly located at frontal lobe or visual cortex, isolated with each other. Theta-wave activity tended to rotate around cortex with low spatial correlation. Beta-wave behaved like inquiry types of oscillations between any two regions across cortex and was consistently correlated with each other over different areas. Alpha-wave activity looked like mixture of theta and beta activities. Together with sliding window dynamic connectivity method we confirmed beta waves play key roles in linking different brain areas together for information inquiry. Theta and low Alpha are more likely playing the role of information control, integration, and image formation. With the proposed new method we demonstrated reproducible linkages of subject behaviors with 3-D tracing characteristics along the 3 categories: emotion, math calculation, and motor functions without using event repeats.

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Optimizing the front-end power solution for automotive ADAS systems

Beniamin Dragoi

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1647-1653 (2017);

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In this paper the front-end power solution for automotive ADAS electronic systems is analyzed. The increased complexity of electronic systems in ADAS automotive brings new challenges for hardware design, especially with regard to improving the efficiency of the switched-mode power supply while maintaining the overall cost reasonably low and keeping the occupied area on the PCB as small as possible. Four topologies of Non-inverting step-up/step-down converter are analyzed. A real-life case is considered and 4 DC-DC converters are designed and simulated to fulfill the requirements. Finally a comparison between the circuits is undertaken. Results are analyzed from the point of view of efficiency, area and price and a decision is reached for the most optimized converter.

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Emotional state recognition in speech signal

Krystian Kapala, Dawid Krawczyk, Stefan Brachmanski

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1654-1659 (2017);

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The matters regarding speech signal processing and analyzing in terms of emotional states recognition were presented in this paper. An experiment was conducted to perform both objective and subjective emotional states recognition tests for Polish language.

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Factors Affecting the Adsorption of Trivalent Chromium Ions by Activated Carbon Prepared from Waste Rubber Tyres

Sylvia E. Benjamin, Muhammad Ashfaq Sajjid

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1660-1664 (2017);

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Economic gains are generally the outcome of industrialization and consequently urbanization. However, positive fiscal index generates a negative impact on natural environment sources heaving pollutant burden on soil, air and water. Industries throw tones of contaminated water into soil and water bodies without proper treatment and create a potential threat for both living and non-living species. Chromium in trivalent state (Cr3+) is added in water bodies and soil through waste water from tanneries, cooling water systems, chemical and pulp and paper industries. The present research work aims at the preparation of an inexpensive activated carbon prepared from non- degradable waste scrap rubber tyres. The carbon produced from scrap rubber tyres was activated by 5% solution of BaCl2 and 0.4 N solution of HCl and verified by ethylene blue solution. The adsorption capacity of the Tyre activated carbon (TAC) was investigated for different parameters i.e., initial chromium (III) ion concentration, activated carbon dosage, contact/ stirring time and pH. The adsorption capacity of TAC depends on the initial metal ion concentration and the TAC dose. pH of the chromium solution effects the adsorption capacity of TAC due to the formation of tetra hydroxochromate(III) complexes,. The results show that TAC offers a cost effective reclamation process for the removal of Cr3+ from effluent waters.

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A prospective design of a social assistive electronic system for the elderly

Arsénio Reis, Hugo Paredes, Isabel Barroso, Maria João Monteiro, Vitor Rodrigues, Salik Ram Khanal, João Barroso

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1665-1669 (2017);

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Aging is a natural process that progressively introduces limitations in a person’s life, which can have dramatic effects on the person’s lifestyle and wellbeing and in most cases is related to the strength of the person’s social bonds with the family and friends group. Therefore, it is important to maintain these bonds in the various stages of life, especially in the later life, when the individual has health limitations and may be living in a care centre. In this work, we developed an exploratory approach to the usage of ICT systems in order to autonomy assist the elderly in maintaining their social connections and relationships with family and friends. It doesn’t substitutes the human care, but it should assist and encourage the elderly to preserve and develop their social activities and the relationships with their family and friends social group. We propose the design of a software system, capable of running in autonomous devices, such as, robots and other consumer appliances, enabling them to recognize and interact with the users, according to their state of mind and the specific current moment context. The interactions should be simple and focused on keeping the users engaged and informed about the current life events of their family and friends, and create the opportunities for the users to interact with the participants of those events by creating interaction proposals. On a technical level, the system should have knowledge about the user and be able to acquire and update context information from social media, video cameras, email, etc, regarding the user and the persons from his family and friends groups, in order to develop meaningful interactions with the user. An adaptive user interface would present and manage the interactions, acting as a mediator between the user and his family and friends group.

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Theoretical developments for interpreting kernel spectral clustering from alternative viewpoints

Diego Peluffo-Ordóñez, Paul Rosero-Montalvo, Ana Umaquinga-Criollo, Luis Suárez-Zambrano, Hernan Domínguez-Limaico, Omar Oña-Rocha, Stefany Flores-Armas, Edgar Maya-Olalla

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1670-1676 (2017);

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To perform an exploration process over complex structured data within unsupervised settings, the so-called kernel spectral clustering (KSC) is one of the most recommended and appealing approaches, given its versatility and elegant formulation. In this work, we explore the relationship between (KSC) and other well-known approaches, namely normalized cut clustering and kernel k-means. To do so, we first deduce a generic KSC model from a primal-dual formulation based on least-squares support-vector machines (LS-SVM). For experiments, KSC as well as other consider methods are assessed on image segmentation tasks to prove their usability.

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Modeling Double Subjectivity for Gaining Programmable Insights: Framing the Case of Uber

Loretta Henderson Cheeks, Ashraf Gaffar, Mable Johnson Moore

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1677-1692 (2017);

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The Internet is the premier platform that enable the emergence of new technologies. Online news is unstructured narrative text that embeds facts, frames, and amplification that can influence society attitudes about technology adoption. Online news sources are carriers of voluminous amounts of news for reaching significantly large audience and have no geographical or time boundaries. The interplay of complex and dynamical forces among authors and readers allow for progressive emergent and latent properties to exhibit. Our concept of “Double subjectivity” provides a new paradigm for exploring complementary programmable insights of deeply buried meanings in a system. The ability to understand internal embeddedness in a large collection of related articles are beyond the reach of existing computational tools, and are hence left to human readers with unscalable results. This paper uncovers the potential to utilize advanced machine learning in a new way to automate the understanding of implicit structures and their associated latent meanings to give an early human-level insight into emergent technologies, with a concrete example of “Uber”. This paper establishes the new concept of double subjectivity as an instrument for large-scale machining of unstructured text and introduces a social influence model for the discovery of distinct pathways into emerging technology, and hence an insight. The programmable insight reveals early spatial and temporal opinion shift monitoring in complex networks in a structured way for computational treatment and visualization.

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1-D Wavelet Signal Analysis of the Actuators Nonlinearities Impact on the Healthy Control Systems Performance

Nicolae Tudoroiu, Sorin Mihai Radu, Elena-Roxana Tudoroiu, Wilhelm Kecs, Nicolae Ilias, Liana Elefterie

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1693-1710 (2017);

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The objective of this paper is to investigate the use of the 1-D wavelet analysis to extract several patterns from signals data sets collected from healthy and faulty input-output signals of control systems as a preliminary step in real-time implementation of fault detection diagnosis and isolation strategies. The 1-D wavelet analysis proved that is an useful tool for signals processing, design and analysis based on wavelet transforms found in a wide range of control systems industrial applications. Based on the fact that in the real life there is a great similitude between the phenomena, we are motivated to extend the applicability of these techniques to solve similar applications from control systems field, such is done in our research work. Their efficiency will be demonstrated on a case study mainly chosen to evaluate the impact of the uncertainties and the nonlinearities of the sensors and actuators on the overall performance of the control systems. The proposed techniques are able to extract in frequency domain some pattern features (signatures) of interest directly from the signals data set collected by data acquisition equipment from the control system.

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Pluggable Controllers and Nano-Patterns in Java with Lola

Yossi Gil, Ori Marcovitch, Matteo Orru, Ori Roth

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1711-1726 (2017);

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Pluggable controllers are a different way to design control constructors such as if, while, do, switch, and operators such as short circuit con-junction (&&) and the “?.” operator of the Swift programming language. Adoption of pluggable controllers enables the final user to modify and extend the control flow constructs (if, while, etc.) of an underlying programming language, the same way they can do if they implement functions such as printf and class String in a standard library.

In modular, pluggable controller based language design, beside core control constructors, there are others, defined in standard libraries, with the purpose of augmenting and enriching the language. These pluggable controllers are extensible and replaceable. Being less intertwined in the main language, control constructor libraries can evolve independently from it, and their releases do not mandate new language releases.

We illustrate the implementation of pluggable controllers using Lola, a powerful language-independent preprocessor and macro language. We demonstrate the introduction of new pluggable controllers with two case studies. The implementation of a Java stenography based on prevalent Java idioms, called “nano-patterns” or nanos, and the introduction in Java of new code constructs inspired by the Mathematica language’s commands.

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On Modeling Affect in Audio with Non-Linear Symbolic Dynamics

Pauline Mouawad, Shlomo Dubnov

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1727-1740 (2017);

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The discovery of semantic information from complex signals is a task concerned with connecting humans’ perceptions and/or intentions with the signals content. In the case of audio signals, complex perceptions are appraised in a listener’s mind, that trigger affective responses that may be relevant for well-being and survival. In this paper we are interested in the broader question of relations between uncertainty in data as measured using various information criteria and emotions, and we propose a novel method that combines nonlinear dynamics analysis with a method of adaptive time series symbolization that finds the meaningful audio structure in terms of symbolized recurrence properties. In a first phase we obtain symbolic recurrence quantification measures from symbolic recurrence plots, without the need to reconstruct the phase space with embedding. Then we estimate symbolic dynamical invariants from symbolized time series, after embedding. The invariants are: correlation dimension, correlation entropy and Lyapunov exponent. Through their application for the logistic map, we show that our measures are in agreement with known methods from literature. We further show that one symbolic recurrence measure, namely the symbolic Shannon entropy, correlates positively with the positive Lyapunov exponents. Finally we evaluate the performance of our measures in emotion recognition through the implementation of classification tasks for different types of audio signals, and show that in some cases, they perform better than state-of-the-art methods that rely on low-level acoustic features.

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Retrieving Dialogue History in Deep Neural Networks for Spoken Language Understanding

Myoung-Wan Koo, Guanghao Xu, Hyunjung Lee, Jungyun Seo

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1741-1747 (2017);

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In this paper, we propose a revised version of the semantic decoder for multi-label classification task in the spoken language understanding (SLU) pilot task of the Dialog State Tracking Challenge 5 (DSTC5). Our model concatenates two deep neural networks – a Convolutional Neural Network (CNN) and a Recurrent Neural Networks (RNN) – for detecting semantic meaning of incoming utterance with the assistance of algorithm adaptation method. In order to evaluate the robustness of our proposed models, comparative experiments on the DSTC5 dialogue datasets are conducted. Experimental results show that the proposed models outperform most of the submitted models in the DSTC5 in terms of F1-score. Without any manually designed features or delexicalization, our model has proven its efficiency of tackling the multi-label SLU task, using only publicly available pre-trained word vectors. Our model is capable of retrieving the dialogue history, and thereby it could build the concise concept structure by employing the pragmatic intention as well as semantic meaning of utterances. The architecture of our semantic decoder has a potential to be applicable to other variety of human-to-human dialogues to achieve SLU.

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A Novel Approach to Sensor and Actuator Integrity Monitoring and Fault Magnitude Reconstruction

Weihua Li, Chiman Kwan

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1748-1757 (2017);

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This paper proposes a novel approach to sensor and actuator integrity monitoring in a dynamic system. Multiple sensor and actuator faults can be detected. Furthermore, faulty sensors and actuators are isolated by contribution analysis. Most importantly, fault magnitudes can be correctly estimated and failed sensors or actuators outputs can be reconstructed. The proposed approach is robust to disturbances, minimizes false alarms, while achieving maximized sensitivity to any faults. Numerical examples justify correctness and validity of the developed methodology.

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A Comparison of Mean Models and Clustering Techniques for Vertebra Detection and Region Separation from C-Spine X-Rays

Anum Mehmood, M. Usman Akram, Anum Tariq, Ayesha Fatima

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1758-1770 (2017);

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In Computer Aided Diagnosis (CAD) tools, vertebra localization and detection are the essential steps for the diagnosis of cervical spine injuries. The accurate localization leads to accurate treatment, which is more challenging in case of poor contrast and noisy radiographs. This paper targets c-spine radiographs for the localization of vertebra using different vertebra templates, vertebra detection at each level using two different clustering techniques and gives a comparison between them. Moreover it separates the regions for each individual c-spine. It takes the poor contrast x-ray as input, enhance the contrast and detect the edges of enhanced image. After the edge detection, manually selected Region of Interest (ROI) helps in getting the edges of area covering C3 – C7 only. These edges along with 4 different template models of vertebra are used for the localization by Generalized Hough Transform (GHT). The results obtained are analyzed visually for the best localization template. Then, on voted points obtained after pruning, two clustering techniques Fuzzy C Means and K-Means are applied separately, to form clusters and centroids for each vertebra. Another part of this paper is to separate vertebra regions. For this, intervertebral points are calculated and then along these points, centroids are rotated using Affine Transformation. It gives parallel lines to vertebrae and joining them gives region for each vertebra. The comparison and testing of proposed technique has been performed using dataset ‘NHANES II’ publicly accessible at ‘The National Library of Medicine’, total 150 cervical spine scans are used securing accuracies 93:76%, 84:21% and 83:1% for FCM, K-Means and region separation, respectively.

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Monitoring power breakers using vibro acoustic techniques

Horia Balan, Traian Varodi, Mircea I. Buzdugan

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1771-1776 (2017);

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Speaking about the commutation’s equipment, it can be said that the best solution in increasing reliability and lowering the maintenance costs is a continuous monitoring of the equipment. However, if the price/quality ratio is considered, it is obvious that, for the moment, the diagnosis can be also an acceptable solution. Nowadays the predictive maintenance for equipment’s diagnosis is currently replacing the preventive diagnosis. An efficient modality of lowering the maintenance costs is to online monitoring the power breakers, during their operation in the power systems. Consequently any connecting/disconnecting operations may be used in diagnosing a power breaker. Thus any supplementary and superfluous tests and/or maintenance maneuvers are avoided. The paper presents the operational maintenance in a power station with three high voltage active breakers, Areva type. The method of establishing the state of a breaker consists in the comparison between the signature of the acoustic signal provided by the manufacturer and the signal issued from the testing operation of the breaker’s state. The software processing procedure and the methodology of determining the faults of the monitored equipment are also developed. All the tests on the circuit breaker are made according the prescriptions of normative.

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A Cost Effective Security Technology Integrated with RFID Based Automated Toll Collection System

Rafiya Hossain, Moonmoon Ahmed, Hasan Uz Zaman

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1777-1783 (2017);

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Crime statistics and research on criminology show that under similar circumstances,crimes are more likely to occur in developing countries than in developed countries due to their lack ofsecurity measures. Transport crimes on highways and bridges are one of the most common crimes in the developing nations. Automation of various systems like the toll collection system is being introduced in the developing countries to avoid corruption in the collection of toll, decrease cost and increase operational efficiency. The goal of this research is to find an integrated solution that enhances security along with the advantage of automated toll collection. Inspired by the availability of many security systems, this research presents a system that can block a specific vehicle or a particular type of vehicles at the toll booths based on directives from the law enforcement agencies. The heart of the system is based on RFID (Radio Frequency Identification) technology. In this system, by sending a text message the law enforcement agency or the authority that controls the toll booths can prevent the barrier from being liftedeven after deduction of the toll charge if the passing vehicle has a security issue. The designed system should help the effort of reducing transport crimes on highways and bridges of developing countries.

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Investigating the Expertise Indicators of Vulnerability Discovery Professionals

Mortada Al-Banna, Boualem Benatallah, Moshe Chai Barukh

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1784-1798 (2017);

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In crowdsourcing, selecting the person with suitable expertise is very important; especially since the task requester is not always in direct contact with the worker. Recently, this has become increasingly important particularly when the crowdsourced tasks are complex and require skillful workers (e.g. software development, software testing, vulnerability discovery, and open innovation). In this paper, we investigate the expertise indicators of vulnerability discovery professionals in a crowdsourcing vulnerability discovery platform. We conduct a systematic literature review, we review online contents, conduct interviews with domain experts, and survey vulnerability discovery professionals involved in the task of vulnerability discovery. We discuss the indicators we have found, and we provide some recommendations to help improve the process of selecting vulnerability discovery professionals to perform crowd tasks related to vulnerability discovery.

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Optimization of Depth-Based Routing for Underwater Wireless Sensor Networks through Intelligent Assignment of Initial Energy

Tanveer Ahmed, Muhammad Kaleem, Khurram Saleem Alimgeer, Mustafa Shakir, Sajid Nazir

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1799-1803 (2017);

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Underwater Wireless Sensor Networks (UWSNs) are extensively used to explore the diverse marine environment. Energy efficiency is one of the main concerns regarding performance of UWSNs. In a cooperative wireless sensor network, nodes with no energy are known as coverage holes. These coverage holes are created due to non-uniform energy utilization by the sensor nodes in the network. These coverage holes degrade the performance and reduce the lifetime of UWSNs. In this paper, we present an Intelligent Depth Based Routing (IDBR) scheme which addresses this issue and contributes towards maximization of network lifetime. In our proposed scheme, we allocate initial energy to the sensor nodes according to their usage requirements. This idea is helpful to balance energy consumption amongst the nodes and keep the network functional for a longer time as evidenced by the results provided.

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Improved Hybrid Opponent System for Professional Military Training

Michael Pelosi, Michael Brown, Kinza Ahmad

Adv. Sci. Technol. Eng. Syst. J. 2(3), 1804-1814 (2017);

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Described herein is a general-purpose software engineering architecture for autonomous, computer controlled opponent implementation in modern maneuver warfare simulation and training. The implementation has been developed, refined, and tested in the user crucible for several years. The approach represents a hybrid application of various well-known AI techniques, including domain modeling, agent modeling, and object-oriented programming. Inspired by computer chess approaches, the methodology combines this theoretical foundation with a hybrid and scalable portfolio of additional techniques. The result remains simple enough to be maintainable, comprehensible for the code writers as well as the end-users, and robust enough to handle a wide spectrum of possible mission scenarios and circumstances without modification.

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