Special Issue on Multidisciplinary Sciences and Engineering 2018

Smoking has been proven to negatively affect health in a multitude of ways. As of 2009, smoking has been considered the leading cause of preventable morbidity and mortality in the United States, continuing to plague the country’s overall health. This study aims to investigate the viability and effectiveness of some machine learning algorithms for predicting the smoking status of patients based on their blood tests and vital readings results. The analysis of this study is divided into two parts: In part 1, we use One-way ANOVA analysis with SAS tool to show the statistically significant difference in blood test readings between smokers and non-smokers. The results show that the difference in INR, which measures the effectiveness of anticoagulants, was significant in favor of non-smokers which further confirms the health risks associated with smoking. In part 2, we use five machine learning algorithms: Naïve Bayes, MLP, Logistic regression classifier, J48 and Decision Table to predict the smoking status of patients. To compare the effectiveness of these algorithms we use: Precision, Recall, F-measure and Accuracy measures. The results show that the Logistic algorithm outperformed the four other algorithms with Precision, Recall, F-Measure, and Accuracy of 83%, 83.4%, 83.2%, 83.44%, respectively.

Read more…

Data centers’ mission critical nature, significant power consumption, and increasing reliance on them for digital information, have created an urgent need to monitor and adequately manage these facilities. Metrics are a key part of this effort as their indicators raise flags that lead to optimization of resource utilization. A thorough review of existing data center metrics presented in this paper shows that while existing metrics are valuable, they overlook important aspects. New metrics should enable a holistic understanding of the data center behavior. This paper proposes a novel framework using a multidimensional approach for a new family of data center metrics. Performance is examined across four different sub-dimensions: productivity, efficiency, sustainability, and operations. Risk associated with each of those sub-dimensions is contemplated. External risks are introduced, namely site risk, as another dimension of the metrics, and makes reference to a methodology that explains how it is calculated. Results from metrics across all sub-dimensions can be normalized to the same scale and incorporated in one graph, which simplifies visualization and reporting. The new family of data center metrics can help to standardize a process that evolves into a best practice to help evaluate data centers, to compare them to each other, and to improve the decision-making process.

Read more…

This paper surveys on Cloud Based Automated Testing Software that is able to perform Black-box testing, White-box testing, as well as Unit and Integration Testing as a whole. In this paper, we discuss few of the available automated software testing frameworks on the cloud. These frameworks are found to be more efficient and cost effective because they execute test suites over a distributed cloud infrastructure. One of the framework effectiveness was attributed to having a module that accepts manual test cases from users and it prioritize them accordingly. Software testing, in general, accounts for as much as 50% of the total efforts of the software development project. To lessen the efforts, one the frameworks discussed in this paper used swarm intelligence algorithms. It uses the Ant Colony Algorithm for complete path coverage to minimize time and the Bee Colony Optimization (BCO) for regression testing to ensure backward compatibility.

Read more…

E-Money mobile payments, also called digital money, are electronic payments, payment transactions using an Internet network integrated with NFC-enabled smartphones and prepaid cards. In Indonesia not only banks that issue e-money products, telecom operators from Telkomsel also issued an e-money product called T-cash. T-cash is a new innovation of electronic money presented by Telkomsel. The purpose of this study was to check the effect of responsiveness, smartness, perceived ease of use, perceived usefulness, social influence, and security against the intention to use T-cash. The data used in this study include primary and secondary data. Respondents in this study are users of T-cash products in Yogyakarta as many as 115 respondents. While the data were collected by using the questionnaire to then be analyzed using the amos analysis technique 22.0. The results of the analysis prove that two characteristics of technology, responsiveness and smartness have a significant effect on perceived usefulness. Ease of use has a significant effect on perceived usefulness. Ease of use, usefulness and security have a significant effect on intention to use. The higher the level of responsiveness, smartness, ease of use, perceived usefulness and security will also increase the use of T-cash social influence factors have no effect on intention to use.

Read more…

In this paper, we introduce and describe a novel approach to adaptive image steganography which is combined with One-Time Pad encryption and demonstrate the software which implements this methodology. Testing using the state-of-the-art steganalysis software tool StegExpose concludes the image hiding is reliably secure and undetectable using reasonably-sized message payloads (?25% message bits per image pixel; bpp). Payload image file format outputs from the software include PNG, BMP, JP2, JXR, J2K, TIFF, and WEBP. A variety of file output formats is empirically important as most steganalysis programs will only accept PNG, BMP, and possibly JPG, as the file inputs. In this extended reprint, we introduce additional application and discussion regarding cold storage of crypto-currency account and password information, as well as applications for secure transfer in hostile or insecure network circumstances.

Read more…

The objective of this paper is to investigate three different approaches of modeling, design and discrete-time implementation of PI closed-loop control strategies in SIMULINK simulation environment, applied to a centrifugal chiller system. Centrifugal chillers are widely used in large building HVAC systems. The system consists of an evaporator, a condenser, a centrifugal compressor and an expansion valve. The overall system is an interconnection of two main control loops, namely the chilled water temperature inside the evaporator, and the refrigerant liquid level control in condenser. The centrifugal chiller dynamics model in a discrete-time state-space representation is of high complexity in terms of dimension and encountered nonlinearities. For simulation purpose the centrifugal chiller model is simplified by using different approaches, especially the development of linear polynomials ARMAX and ARX models. The aim to build linear ARMAX models for centrifugal chiller is to simplify considerable the control design strategies that are investigated in this research paper. The novelty of this research is a new controller design approach, more precisely an improved version of proportional – integral control, the so called Proportional-Integral-Plus control for systems with time delay, based on linear ARMAX models. It is conceived within the context of non-minimum state space control system that “seems to be the natural description of a discrete-time transfer function, since its dimension is dictated by the complete structure of the model”. The effectiveness of this new controller design, its implementation simplicity, convergence speed and robustness are proved in the last section of the paper.

Read more…

This study applies systemic functional linguistics (SFL) as complementary framework of analysis of technology acceptance models (TAMs). The purpose is to bridge research methodology language in international business (IB) studies and engineering management science. Currently TAMs and its consolidated version, the Unified Theory of Acceptance and Use of Technology (UTAUT) provides for a typology of one user in one context scenario. The need for the UTAUT model to account for multiple users in multiple work contexts in a single framework of analysis was foregrounded in the study of the workflow processes of a remote services business model of a European founded multinational business enterprise (MBE) with regards to its (i) intra-firm improvements in managing remote services cases, and its (ii) extra-firm selling of life cycle management remote services contracts. The Enterprise has global operations in over 100 countries, of which this study focused on its European operations of improving the quality of remote services for the marine industry. Through an application of SFL unto UTAUT, this study illustrates how multiple users in multiple contexts can be analysed simultaneously, and whose behaviours can be accounted for in a single framework of analysis. The combined SFL UTAUT model addresses the initial statisticity of the UTAUT model, whilst at the same time, expands upon current theoretical perspectives of technology use and acceptance that can be applied in practice.

Read more…

We consider the problem of aligning two very long biological sequences. The score for the best alignment may be found using the Smith-Waterman scoring algorithm while the best alignment itself may be determined using Myers and Miller’s alignment algorithm. Neither of these algorithms takes advantage of computer caches to obtain high efficiency. We propose cache-efficient algorithms to determine the score of the best alignment as well as the best alignment itself. All algorithms were implemented using C and OpenMP, and benchmarked using real data sets from the National Center for Biotechnology Information (NCBI) database. The test computational platforms were Xeon E5 2603, I7-x980 and Xeon E5 2695. Our best single-core cacheefficient scoring algorithm reduces the running time by as much as 19.7% relative to the Smith-Waterman scoring algorithm and our best cache-efficient alignment algorithm reduces the running time by as much as 17.1% relative to the Myers and Miller alignment algorithm. Multicore versions of our cache-efficient algorithms scale quite well up to the 24 cores we tested; achieving a speedup of 22 with 24 cores. Our multi-core scoring and alignment algorithms reduce the running time by as much as 61.4% and 47.3% relative to multi-core versions of the Smith-Waterman scoring algorithm and Myers and Miller’s alignment algorithm, respectively.

Read more…

This paper presents a numerical and experimental study of Radar Cross Section (RCS) of radar targets using Gaussian Beam Summation (GBS) method. The purpose GBS method has several advantages over ray method, mainly on the caustic problem. To evaluate the performance of the chosen method, we started the analysis of the RCS using Gaussian Beam Summation (GBS) and Gaussian Beam Launching (GBL), the asymptotic models Physical Optic (PO), Geometrical Theory of Diffraction (GTD) and the rigorous Method of Moment (MoM). Then, we showed the experimental validation of the numerical results using experimental measurements which have been executed in the anechoic chamber of Lab-STICC at ENSTA Bretagne. The numerical and experimental results of the RCS are studied and given as a function of various parameters: polarization type, target size, Gaussian beams number and Gaussian beams width.

Read more…

Memory based ternary physical unclonable functions contain cells with fuzzy states that are exploited to create multiple sources of physical randomness, and design true random numbers generators. A XOR compiler enhances the randomness of the binary data streams generated with such components, while a modulo-3 addition enhances the randomness of the native ternary data streams, also generated with the same method. Deviations from perfect randomness of these random numbers, in terms of probability to be non-random, was reported as low as 10-10 in the experimental section of this paper, which is considered as extremely random based on NIST criteria.

Read more…

The pitch angle controller maintains the aerodynamic captured power at rated level when the wind speed is above the rated speed. Besides, it can also improve the transient stability occurring in the wind energy system (WES). This paper, therefore, proposes an effective pitch angle control strategy that can deliver the conditioned output power in windy condition and increase the transient stability capability in grid faults. A fuzzy logic method has employed to design the proposed control strategy, Moreover, in this paper some major factors that affect the transient stability have been investigated by deriving steady-state equivalent model of the wind energy system. The simulated results show that the proposed fuzzy logic based pitch angle controller is effective at conditioning the output power and complying with fault ride through requirements for WES in the power system.

Read more…

Analysis of magnetic resonant wireless power transfer systems aims to achieve maximum efficiency of the power transfer. From the analysis we wish to derive the maximum power and the frequency at which this occurs. This paper presents a method to estimate these two required values and to achieve this requires the solution of the input impedance equation numerically. The frequency of the maximum efficiency is found when the imaginary of the input impedance is close to zero, and it could be different to the natural resonant frequency. We estimate the efficiency value which depends on the real value part of the input impedance. The proposed method has been applied to one of the four types of possible connections; a series-parallel (SP) connection although similar approaches could be applied to the others. In some cases the maximum efficiency shifts away from the resonant frequency. Therefore, this paper shows how to use the same equations to achieve maximum efficiency at resonance and suggests a design method to achieve this practically.

Read more…

During sudden anti-terrorist drives conducted by the law enforcement agencies, a localized cyber security system happens to be a special tactic to avert the unprecedented massacre and gruesome fatalities against the residents of that area by disconnecting the affected territory from the rest of the world; so that the militants and their outside accomplices cannot communicate with each other and also the terrorists cannot go through the ongoing apprehensive operation via wireless communications. This paper presents a novel framework of an unmanned aerial vehicular networking signal jammer which is oriented to block incoming and outgoing signals of all frequencies transmitted from a specifically marginalized territory scanned and explored by the aerial vehicle. During such a cyber-vigilance operation, the aerial vehicle is equipped with a transmitter and an auto-tuning band-pass filter module with automatic regulation of center frequencies according to the surrounding networking signals, which are considered to be the suppressing noise parameters. In order to restrict the signal blocking operation within the militant hub, the aerial vehicle with the network terminator is controlled to navigate within a particular boundary of a residential area and its navigation is continuously mapped and stored for effective evacuation process directed to save the innocent stranded people. A very low frequency (VLF) metal detector has been designed to trace the explosives and buried landmines inside the exploration arena. An algorithm for 3-D mapping of the metal traces detected by the aerial navigator has been presented in this paper. Signal blocking, metal tracing and stable confined movements have been tested where the testbed is provided with signals of different frequencies along with variation in dimensions of the testing region to evaluate the reliability of the proposed framework.

Read more…

During microwave heating of materials, the efficiency of microwave heating depends on the materials’ dielectric property, shapes and sizes of the material, materials’ position inside the applicator, operating frequency, level of input power, specific heat capacity, number and position of waveguide over the applicator, size and geometry of applicator etc. This paper examines the effects of dielectric properties of the clay sample placed in the multimode applicator on the performance of microwave heating. The simulated and experimentally obtained results show that the variation in clay samples dielectric value creates variation in system efficiency inside the microwave applicator. Also placing another dielectric slab over the material to be heated affects the electric field distribution and system efficiency. Placing KESTAMID dielectric slab over the material improved the heating efficiency by 22%. COMSOL Multiphysics software was used to simulate and estimate the electric field distribution over the surface of the clay sample and inside the multimode applicator for different dielectric property clay samples. The simulated and experimentally obtained results are almost matched.

Read more…

The rapid evolution of Collaborative e-Learning Systems migrates to the use of new technologies such the artificial intelligence (AI). In this context, the role of AI in increasing the quality of learning and making it more productive, persistent and efficient. In addition, it can accomplish repetitive and complex tasks in record time and unmatched accuracy. These advantages offer the ability to interact with learners in an almost human way. This interaction could be made on the base of adaptive hypermedia techniques, Multi-agent Systems technology and a cognitive learner model.
In this paper, we present and analyze some existing intelligent collaborative e-Learning systems on the basis of their various features such as collaboration features, intelligent actors’ interaction, adaptability measurement, cognitive student modeling, and security measurement. Our analysis aims to provide important information to researchers, educators and software developers of educational environments concerning strengths and weaknesses of those e-Learning systems. According to this study, we found that some collaborative e-Learning environments, even the use of the mentioned technologies, still poor in terms of the structure of human cognitive architecture aspects and the capacity to assess the help provided to learners. For these reasons, we present, in the end, some prospects in order to determine how we can improve these systems to stop the reasons of abandoning courses.

Read more…

The development of agent-based systems is negatively impacted by the lack of process standardization across the major development phases, such as the requirements analysis phase. This issue creates a key barrier for agent technology stockholders regarding comprehending and analyzing complexity associated with these systems specifications. Instead, such fundamental low-level infrastructure is loosely attended to in an ad-hoc fashion, and important aspects of requirements analysis are often neglected altogether. The IEEE Std 830 model is a recommended practice aimed at describing how to write better quality requirement specifications of conventional software. Knowing that agent-based computing is a natural and logical evolution of the conventional approaches to software development, we believe that the requirements phase in agent-based systems can benefit from applying the IEEE Std 830 model which results in high-quality and more accepted artifacts. This article provides a criteriabased evaluation that is derived from the software engineering body of knowledge guide to assessing the adoption degree of agent-oriented methodologies to software requirements standards. Then, it proposes a model-driven approach to restructuring and extending the IEEE Std 830- 2009 standard model to specify requirements of agent-based systems. To evaluate the applicability and usefulness of the updated model, we design a research study that allows practicing the model with simple real-world problem scenarios and conducting a summative survey to solicit feedback on the model usages.

Read more…

Multitenancy isolation is a way of ensuring that the performance, stored data volume and access privileges required by one tenant and/or component does not affect other tenants and/or components. One of the conditions that can influence the varying degrees of isolation is when locking is enabled for a process or component that is being shared. Although the concept of locking has been extensively studied in database management, there is little or no research on how locking affects multitenancy isolation and its implications for optimizing the deployment of components of a cloud-hosted service in response to workload changes. This paper applies COMITRE (Component-based approach to Multitenancy Isolation through Request Re-routing) to evaluate the impact of enabling locking for a shared process or component of a cloud-hosted application. Results show that locking has a significant effect on the performance and resource consumption of tenants especially for operations that interact directly with the local file system of the platform used on the cloud infrastructure. We also present recommendations for achieving the required degree of multitenancy isolation when locking is enabled for three software processes: continuous integration, version control, and bug tracking.

Read more…

Adaptive education systems (AES) are considered one of the most interesting research topics in technology-based learning strategies. Since students have different abilities, needs and learning styles, we should fit the curriculum and teaching activities to these different learning styles. This study investigates the impact of using LAES (Libyan Adaptive Education System) on the performance of students. An ALSI (Arabic Learning Style Instrument) was integrated into the LAES system to investigate learning preferences of students. The student models are constructed according to the results obtained using this instrument (ALSI). Three experimental studies were then conducted to investigate the impact of the LAES system on the performance of students. The results reveal the students who have learnt using the LAES system were more successful than others who learnt without, in terms of the knowledge gained.The objective was to review and add literature whether green tea is helpful for weight reduction. Reviewing the randomized, double-blind, placebo-controlled trials to compare green tea extracts for weight loss from various online sources including Ovid MEDLINE, PubMed, and Cochrane databases studies published in 2006, 2007 and 2008 in English language were considered. In each of the three studies, baseline measurements were taken and analyzed of the research participants. Measurements of total body weight, BMI with reference to age, hip and waist circumference were measured at the interval of 4 weeks i.e. 0 week (0 month), 4th week (1 month), 8th week (2 month), 12th week (3 month) were taken. All the research work analyzed and reviewed showed that a part of some minor changes no major changes were observed to prove the significance of green tea as a single agent for reducing weight. An increase in body energy expenditure was observed which leads to increase in appetite by the subjects but no adverse effects were noted. After detail review and analysis, the results showed that green tea have no significant effect on the weight reduction as a single agent.

Read more…

Face recognition is one of the most well-known biometric methods. It is a technique used for identifying individual from his face. The recognition process takes the face and compares it with the one stored in the database for recognizing it. Many methods were proposed to achieve that. In this paper, a new technique is proposed by using meta-heuristic algorithm. The algorithm is used to search for the best point in the image to be selected as a pivot, generate a vector of extracted features that are not necessary for the recognition and may reduce accuracy of it and evaluate the weight value for each area in the face image areas. A dataset with 371 images was used for evaluation. The results were conducted and compared with the original face recognition technique. That results show that proposed idea could enhance recognition by increasing accuracy up to 20% over original face recognition technique.

Read more…

Multiprocessing can be considered the most characteristic common property of complex digital systems. Due to the more and more complex tasks to be solved for fulfilling often conflicting requirements (cost, speed, energy and communication efficiency, pipelining, parallelism, the number of component processors, etc.), different types of component processors may be required by forming a so called Heterogeneous Multiprocessing Architecture (HMPA). The component processors of such systems may be not only general purpose CPUs or cores, but also DSPs, GPUs, FPGAs and other custom hardware components as well. Nevertheless, the system-level design process should be capable to handle the different types of component processors the same generic way. The hierarchy of the component processors and the data transfer organization between them are strongly determined by the task to be solved and by the priority order of the requirements to be fulfilled. For each component processor, a subtask must be defined based on the requirements and their desired priority orders. The definition of the subtasks, i.e. the decomposition of the task influences strongly the cost and performance of the whole system. Therefore, systematically comparing and evaluating the effects of different decompositions into subtasks may help the designer to approach optimal decisions in the system-level synthesis phase. For this purpose, the paper presents a novel method called DECHLS based on combining the decomposition and the modified high level synthesis algorithms. The application of the method is illustrated by redesigning and evaluating in some versions of two existing high performance practical embedded multiprocessing systems.

Read more…

This paper is an extension of work originally presented in conference name” Study Performance of Speed Tracking Control with Frequency and Amplitude Dependence”. Though many PMSMs (Permanent Magnet Synchronous Motor) control approach have already been published, little endeavors have been invested in the study of speed tacking control with frequency or amplitude dependence. The use of NDI (Nonlinear Dynamic Inversion) tracking control in versus amplitude and frequency dependence is the major focus of this paper. The proposed tracking control demonstrates that NDI control presents the ability to track the desired output with high precision. PMSM outputs are characterized at different amplitude and frequency. The speed and the direct current versus amplitude and frequency are successfully extracted. A mathematical (d-q) of the permanent magnet synchronous motor model is also presented. A comparative study between desired data and simulation results is conducted. Important to note, the proposed model and the simulation results reflect a successful agreement as far as a amplitude and frequency dependence is concerned. A new validity approach, namely “Validity Abacus” is proposed and discussed.

Read more…

Residential schools can be a great place for students to learn and develop a different set of skills if the right environment is given to the child. Constant communication with parents can help the child to stay motivated and feel comfortable away from home, hence schools tend to provide various solutions to allow the student to communicate with their parents. The most common ways are using a coin booth or a common telephone. This process is very hectic as hundreds of student’s use this facility and these hundreds of calls have to be monitored individually so that no student would be getting into bad influence. In order to counter this problem, the entire process is automated in this paper. The proposed work also countered every small problem, such as unauthorized access, making calls to unauthorized numbers or exceeding the duration of call time allotted. In this paper, the digital lines are used to allow multiple calls and control these with the help of a Primary Rate Interface (PRI) card and an Electronic Private Automatic Branch Exchange (EPABX) system.

Read more…

A selective harmonic elimination system using fuzzy logic for the elimination of high magnitude harmonics with frequencies close to fundamental in the output voltage of single phase inverters is presented. The system does not require look up tables for storage of the data as in traditional harmonic elimination methods. The input of the fuzzy system is the modulation index values. The output of the fuzzy system provides the switching angles which are further used to construct the switching signal for the switches in the inverter. With this fuzzy logic based selective harmonic elimination system, predetermined dominant low rank harmonics are successfully eliminated. Simulations are made with Matlab/Simulink and the results are presented which show the effectiveness of the presented harmonic elimination system.

Read more…

Moderate exercise has been implemented in spaceflight programs to prevent muscle and joint damage under extreme circumstances such as microgravity. Although the physical effects of exercise have been investigated experimentally, advanced modeling and simulation techniques are powerful tools that could provide insight into the physical limitations, optimal conditions, and mechanisms that might lead to muscle and joint damage. Ergometers are safe for patients and elderly individuals because exercise intensity can be easily regulated. Moreover, ergometer exercise that removes the load imposed by body weight on leg joints would better reflect training conditions in locations such as the International Space Station or on the surfaces of the Moon and Mars, where the force of gravity is lower than that on the Earth. A hybrid training system (HTS) that combines the electrical stimulation of antagonist muscles and volitional contraction of agonist muscles is an effective training method. Co-contractile motions in the HTS can counteract the reduced effect of gravitational force on leg joints during ergometer exercise. The present study aimed to validate the ability of an ergometer exercise model to measure oxygen uptake and joint reaction forces by comparison with experimental results and create strategies for electrically stimulating leg joint muscles for modulation under altered gravity. The simulation results suggested that the HTS could easily control the magnitude of oxygen uptake and joint reaction forces. Optimal cycling conditions to achieve desirable values for oxygen uptake and joint reaction forces would help to maintain the health of astronauts and appropriate exercise programs could be implemented in constrained space facilities.

Read more…

The torch relay for the 2017 Taipei Summer Universiade started June. The innovative torch design was altered and tested, follow-up production successfully. For preventing weather effect, the head of the torch embedded with a unique airflow structure that allowed the sacred flame to pass the wind and rain tests. The safety lantern displays a 3D spiral flash. Safety lantern uses biofuel so that the mother flame can transport by air. The scientific principles are Stack effect, Coanda effect, Bernoulli’s principle, and Capillary phenomenon. Product design refers to principles and a series of work from the specifications to determine the product structure. Cross-discipline collaboration is needed to increase the integrity.

Read more…

Stream cipher can be used in constrained environments to provide information security and reduce energy expense at data transmission. In this paper, it is shown that Reed-Solomon (RS) code can be used to implement stream cipher, which is widely used for error corrections of data in transmission and storages. The proposed stream cipher combines the keys with the messages and conceals the cipher within the erroneous RS code. Then at the receiving part the cipher can be checked out by RS decoding, leaving the information unchanged. There are several advantages with this scheme: First, compared with the usual stream cipher including wo engines, only one engine is required, making the synchronization of the stream cipher and messages easily. In the situation, the stream cipher and the messages are held as a whole while the alignment of stream cipher is not needed. Thus, the usual power consumptions for synchronization and key generation at the receiving part can be saved. Second, the stream cipher increases the security level by adding the difficulty of decoding a random linear RS code, which stores the key streams like public key cryptography. Since the RS encoding and decoding modules are already included in many computer systems or devices, the new scheme may be implemented by reconfiguration rather than extra hardware units. Compared with generalized RS code for code-based public-key cryptography like McEliece system, it uses systematic encoding instead of nonsystematic encoding, which decreases the power overhead. Unlike the encryption by public keys and decryption by private keys of McEliece system, it encrypts messages by private keys from stream cipher and decrypts texts by public keys implemented in the RS decoder.

Read more…

Doubly fed asynchronous machines have an outstanding property: they can be operated up to twice rated speed delivering full rated torque. This paper presents, for the first time in the literature, a control system for multiphase asynchronous machines fed by Voltage Source Inverters (VSIs) both in stator and rotor that incorporates the harmonic torques. The system has three main and distinctive features: the independent control of the fundamental and harmonic torques, a very fast dynamic response for each one of these torques and a powerful method for selecting the best suited inverter state to achieve the evolution of the fundamental and harmonics flux linkage space phasors prescribed by the external control loops. The first feature is achieved through the decoupling of the multiphase machine provided by the Space Phasor Theory (SPhTh). The second one comes from the application of the General Approach for a very Fast TOrque Control (GAFTOC) principle. The third feature relies on using for multi-phase VSIs a simple but powerful switching-table based mode of operation that overcomes the limitations of the switching-table based modes of operation developed up to now, that only enable for the inverter to feed machines with no harmonic torques contribution.

Read more…

The object of this paper is to identify the unknown electrical parameters of solar photovoltaic generators in real time, through the application of a novel suggested hybrid method. The identification process is discussed with details, about the four steps of identification. In this issue, the first step describes the experimental data acquisition work done to obtain data from a real photovoltaic system. For the second step, a model of a cell’s corresponding electrical circuit is selected. In the third step, the estimation of the parameters ‘values is done using two combined optimization approaches, such as Levenberg-Marquardt combined with Particle Swarm Optimization. The fourth step describes the validation of the selected model. The benefit of this work compared to those before, is in the use of real data, in the use of smart optimization technics and the hybridization between two methods, which provides best results.

Read more…

The following work introduces the use of the available Redundant switching states introduced by the double star four level converter topology, for its application in a medium voltage variable speed drive under a wide range of operation loads. Redundant switching states are obtained using multi-carrier phase-shifted pulse width modulation (PWM) strategy. The converter performance is evaluated in terms of the dc-voltage drift and the torque ripple on the load side, when compared with a classical level-shifted PWM modulation.

Read more…

This paper presents a resource-friendly dynamic digital beamformer for a portable ultrasound imaging system based on a single field-programmable gate array (FPGA). The core of the ultrasound imaging system is a 128- channel receive beamformer with fully dynamic focusing embedded in a single FPGA chip, which operates at a frequency of 40 MHz. The Rx beamformer is composed of a midend processing module, a backend processing module, and a control block. The midend processing module is established using the implementation of the delay summation through coarse delays and fine delays, with which delays could vary continuously to support dynamic beamforming. In order to enhance spatial and contrast resolution, the Rx beamformer is further accommodated by employing a polyphase filter, which improves the effective beamforming frequency to 240 MHz. The control block generates control signals based on a memory management block, which doubles the data transfer rate. The processed data is wirelessly sent to a commercial Android device. The low cost ultrasound imaging system supports real-time images with a frame rate of 40 fps, due to the limitation imposed by the wireless backhaul process. To reduce power consumption, a dynamic power management technique is used, with which the power consumption is reduced by 25%. This paper demonstrates the feasibility of the implementation of a high performance power-efficient dynamic beamformer in a single FPGA-based portable ultrasound system.

Read more…

Virtual Reality (VR) technology has become one of the most advanced techniques that is used currently in many fields. The role of education is extremely important in every society; therefore, it should always be updated to be in line with new technologies and lifestyles. Applying technology in education enhances the way of teaching and learning. This paper clarifies a virtual reality application for educational resolutions. The application demonstrates a virtual educational environment that is seen through a Virtual Reality headset, and it is controlled by a motion controller. It allows the user to perform scientific experiments, attend online live 360° lectures, watch pre-recorded lectures, have a campus tour, and visit informative labs virtually. The application helps to overcome many educational issues including hazardous experiments, lack of equipment, and limited mobility of students with special needs.

Read more…

Reverse logistics activities are widely used application to preserve the environment in many developed countries from e-waste problem. Due to lack of public awareness in many emerging countries, implementation of reverse logistics program must be initiated by government. Besides that, reverse logistics practices often fail to balance among profit target achievement, the environmental conservation, and social harmony. Moreover, in the recent years, triple bottom line is not enough since many parties are only focused on their reputation due to they are afraid to be blame as the source of problems. Therefore, this research aims to build sustainable reverse logistics theory for emerging countries through quattro bottom line approach from government perspectives. Theory building process consists of systematic literature review, triangulation of data collection, major part of theory description, conceptualization and operationalization of theory. The result indicates a number of obligation that must be regulated by government for all parties that was divided into four categories, i.e. infrastructures and facilities provision, human resource commitment, regulation establishment, and managerial orientation. This theory can be adopted to measure performance of SRL Implementation.

Read more…

Game-based learning has been introduced as an interactive tool to facilitate learning and training processes in various fields, including supply chain management (SCM). Most of these games are specifically designed to focus on certain scenarios and concepts. For example, the original beer distribution game focuses on a single product supply chain without considering capacity and process reliability into account. This creates challenges for extending the games to cover other concepts in SCM. To tackle this problem, we propose a board game, titled ThinkLog, as a face-to-face extendable framework to facilitate learning in SCM. It can be extended to generate different scenarios for various concepts in SCM without changing the basic game structure. Using this principle, we have extended the basic version of ThinkLog to two other scenarios, namely: humanitarian logistics and urban logistics, by simply modifying the rule of the game. Each scenario would have different learning objectives embedded in the gameplay. The game is also complemented with a computer-based application (digital application) to enhance the overall learning experience and collect relevant data (data gathering) during a game session. These three scenarios have been evaluated on four-interactive sessions with government officials and policy- makers in Indonesia. Each session has been consistent in its acceptance of the game as a tool to facilitate learning in SCM, regardless of the scenarios that we played. Our learning objective evaluation also shows that the game is effective in deepening the players’ understanding of SCM concepts.

Read more…

Noise defined as ‘a sensation of unwanted intensity of a wave’, is perception of a pollutant and a type of environmental stressor. The unwanted intensity of a wave is a propagation of noise due to transmission of waves (viz. physical agents) such as light, sound, heat, electricity, fluid and fire. The characterization of noise interference, due to power difference of two intensities in a wave is presented. Noise interference characterization in a wave is obtained depending on type of wave. Standard definitions of noise sources, their measurement equations, their units and their origins under limiting reference conditions are derived. All types of wave form one positive power cycle and one negative power cycle. The positive and negative noise scales and their units are devised depending on speed of noise interference in a wave. A numerical and experimental study was conducted for supporting the noise characterization theory via ascertainment of energy conversion characteristics of a pair of photovoltaic (PV) modules integrated with solar wall of an outdoor test-room. A pre-fabricated outdoor room was setup for conducting outdoor experiments on a PV solar wall with ventilation through the outdoor room. Acoustic signal processing is supported with some experimental and numerical results of a parallel plate PV solar wall device installed in an outdoor test-room to authenticate the noise interference equations. Detailed discussions on noise characterization theory along with some examples of noise filter systems as per noise sources are also presented. The noise characterization theory is also exemplified with some noise unit calculations using presented noise measurement equations.

Read more…

The number of smart devices inside the living environments grows more and more every day, and with it the need to interface them in order to share data and activate functions. Each day, new scenarios and new applications emerge to make our lives easier in many different contexts. The AAL SOCIALIZE project aims to create a new reference platform for active ageing by applying technological solutions to care for the health of the elderly, facilitate their daily activities, simplify their access to dedicated services.
The work presented herein describes the “Elderly Monitoring service” ? an IoT module of the SOCIALIZE platform, whose aim is to monitor elderly people’s activities and physiological parameters and to combine smart device functions. This modeling process can actively contribute to anticipating, and thereby preventing, emergency situations, increasing elderly autonomy and making them feel “protected” and “safe”.
In this regard, the system implements a practicable, scalable solution that allows heterogeneous devices belonging to different domotic systems using diverse protocols to interact with each other, share data and services and bind together through ‘friendship’, thereby creating an infrastructure suitable for the creation of a true Social IoT (SIoT).

Read more…

The abilities of human brain to discover solutions for many problems is a great gift that motivate the scientists to develop the revolution of the artificial intelligence and using it in many areas. This paper proposed an intelligent chessboard which works in a way that similar to the human brain that predicts the next positions for any piece of the chess. MATLAB is used in the training of the artificial neural networks of the chessboard and implemented on FPGA as a hardware part; the proposed system has many advantages such as the low cost of production with a high efficiency in the prediction of the position of any piece on the chessboard and the similarities to the human brain.

Read more…

Four different soundscapes with different loudness and spectral distributions were recorded in Zagreb (capital of Croatia) and reproduced to two groups of listeners while they were performing a concentration demanding task – a simplified variation of the memory game. These two groups of test subjects listened to the same soundscapes but with different loudness distribution. The game results versus time were recorded, analyzed and compared to questionnaire answers, along with loudness and property changes of each soundscape. The goal was to determine which of the sound events causes the largest distraction and to establish a connection between these results and the annoyance level of each soundscape. As expected, the loudest soundscape resulted in the lowest score and caused the largest annoyance. However, other factors proved to cause listeners’ distraction, mainly unexpected sounds that differ from the main sound print. In that sense, this paper also deals with a concept of creating enjoyable sound environment in urban places.

Read more…

A dual-band 90-degree SiGe HBT active phase shifter based on band-pass and band-stop designs using dual-band resonators is presented in this paper. The active phase shifter employs differential configuration and has band-pass and band-stop filters in the load circuit. By switching two output ports of the differential amplifier, 90-degree phase shifting has been realized at dual bands. The implemented dual-band active phase shifter using 0.35 micron SiGe HBT has achieved a gain of 9.3 dB and a phase shift of 95 degrees at 0.74 GHz as well as a gain of 8.9 dB and a phase shift of 98 degrees at 0.88 GHz. This is the first paper to present a dual-band active phase shifter based on band-pass and band-stop designs using dual-band resonators.

Read more…

This paper refers to a novel mixed-mode universal biquad employing plus current output differential voltage current conveyors with grounded passive components. The circuit performs mixed-mode operation with the selection of the input and output terminals, and it enables low-pass, band-pass, high-pass, band-stop and all-pass responses choosing suitable input signals. The circuit needs no component matching constraints for obtaining five basic circuit responses above, and can adjust orthogonally the characteristic parameters by the circuit component. Additionally, the circuit has extremely low sensitivities with respect to the circuit components. A circuit design is performed with PSPICE simulation in order to verify the workability of the circuit.

Read more…

Requirement for pole-changing motors emerged at the very early times of asynchronous motor design. Different solutions have been elaborated and some of them are generally used. One of these solutions in use is the so called pole phase modulation method. The so called 3 Y / 3 Y pole-changing winding being subject of this paper belongs to this group. This paper presents a new approach to this method. A new, complete and comprehensive study is introduced, including features and, moreover, detailed design guidelines. The method is applicable for any pole combination for the so called close ratio without any further particular consideration. As the target of the paper is to provide solution for high power application, it does not deal with balancing methods, but as a novelty, calculates the effect of those disadvantageous phenomena (asymmetries, even harmonics) in order to enable the designer for evaluation and decision. The study also reveals as a novelty that the same method is suitable for wide ratio as well, moreover, a new solution for theoretically infinite ratio expressed in 1:N, with supply voltage system of N phase is proposed. Using this motor, a new and complete drive system has been proposed with subject pole changing motor as core element as the most appropriate arrangement of high power main marine propulsion drive.

Read more…

The Industrial Internet of Things (IIoT), a typical use case of the Internet of Things, has been a great prospect for development in the near future. In the developing fifth generation mobile communications, the IIoT is an extremely important application case. In this paper, the channel propagation properties are researched and modeled based on the measurement data in an automobile welding factory. The results of the path loss exponent values are around 2.5 and 3.3 in line of sight propagation (LOS) and obstructed line of sight (OLOS) propagation scenarios, respectively. In LOS and OLOS propagation scenarios, K factor values are around 5 dB and 4 dB, respectively. Meanwhile, in these two propagation environment, the amount of multipath components (MPCs) and the root mean squared (RMS) delay are extracted and compared. Particularly, a special case is considered that the sensor/actuator is placed inside the metallic body of a machine, which affects the path loss exponent values and K factor values. These measurement results are of great significance to the development of IIoT.

Read more…

In this article, a new method to extract the RLC parameters from the structure of a Rotating Traveling Wave Oscillator (RTWO) is described. The use of a 3D simulator (EMPRO) allow us to develop a precise analysis of the impact of the topology, the geometrical discontinuities, and the dimensions of the transmission lines, on the performance parameters of the RTWO, i.e. frequency of oscillation and power consumption. The results show that a right angle discontinuity compensation can reduce the power consumption up to 3.34% and, for RTWOs with a frequency range between 11.4 GHz and 11.5 GHZ, narrow transmission lines (as the technology is able) can reduce the power consumption up to 98%. Additionally, it was observed that the topology used affects the performance parameters, as there are more folds and overlaps between metal levels in the RTWO structure, and the frequency increases by 2.9% while the power consumption increases by 10.52%.

Read more…

In this study, the authors propose a modified design of sequential card activities to recollect experience for the elderly with Dementia. The cards and App were designed to complement each other for Nostalgia-based support. Image and text are utilized to trigger memories that bring out shared experience from the patient. By using suitable trigger elements, group sharing, and physical objects, one can enhance the memory recall. The procedure of rice dumpling preparation and making were listed in a sequential step and printed on cards. Cards are shuffled, and the elderly are asked to sort these cards to right sequence with the help of QR scanner. In multiple theme scenarios, different groups of object making steps were mixed, and the player needs to select cards that related to a specific group. Using actual items and activities, the triggered of elder’s experience was confirmed. The qualitative testing results showed that the elderly enjoyed the activities. Those events verified the effectiveness of the proposed method.

Read more…

This paper presents analytical methods for optimum allocation of distribution generators in a radial distribution network. The aim is to increase power efficiency and reduce loss of power. The ideal size of each distribution generator unit at the identified locations has been carefully selected by making adjustments to loss saving equations and the voltage on a radial feeder. The experimental system is located in the governorate of Bethlehem specifically within the district served by the Jerusalem Distribution Electricity Company (JDECO). The NEPLAN simulator has been utilized in the verification process of the aforementioned experimental system. It entails of several nodes and 400 V-buses that feed up to five household loads. The size and location of each has been carefully chosen. Consequently, significant loss saving, and voltage profile improvement have been reported.
Hence, the use of Renewable Distribution Generators (DGs) systems is highly desirable for various reasons including increased system reliability, decreased loss of power, and enhanced voltage profile. Notably, cutting back on the use of conventional fuel will in turn reduce the negative environmental impacts.

Read more…

This paper is an extension of work originally presented at the Convention of Central America and Panama XXX VII- The Institute of Electrical and Electronic Engineers -2017. We have extended our previous work by presenting the initial results of how social technologies in particular wikis has the potential for Information Technology support of a cooperative community knowledge generation.
This paper outlines an experience in the implementation of a multidisciplinary research project – AGILe busIness PrOcess (AGILIPO), applied to an important organization in Nicaragua. In addition, it focused on improving key process by describing through collaborative tools which foster end user collaboration and organization knowledge.
We gathered evidence that blogs and podcasts couldn’t afford to allow users on collaborative tasks of AGILIPO. The principal contributions of this work are the lessons learned from the experience of applying AGILIPO to an organization in Nicaragua, the key elements in achieving success in the application, the conditions that were brought together in order to use AGILIPO, the drawbacks during the experience and the relevant limitations of AGILIPO and how we can improve process by agile Business Process Management.

Read more…

Currently, synchronous digital circuits (SDC) may require certain design conditions, such as power consumption, robustness, performance, etc. These design conditions are more difficult to satisfy when SDC are implemented in VLSI (Very Large Scale Integration) technology and in the deep-sub-micron MOS (DSM-MOS) technology. The asynchronous design style has properties that serve as an alternative to design DSM-MOS technology circuits and it can satisfy these design conditions. Quasi Delay-Insensitive (QDI) circuits is a class of asynchronous circuits, they have properties where the DSM-MOS technology design is applied, because they are robust to noise, temperature and voltage variations, as well as low electromagnetic emissions, and they are tolerant to certain faults. An interesting style of QDI combinational circuits are NCL (NULL Convention Logic) circuits, because they accept conventional Boolean functions and it can achieve a better optimization. This paper presents an approach and an architecture based in basic gates for the synthesis of NCL gates, therefore its implementation uses only standard libraries and Field Programmable Gate Array (FPGA). The proposed QDI combinational circuits are implemented in the approach that uses only NCL gates.

Read more…

The aim of the present work is to guarantee the trajectory tracking of a nonlinear biological process and compare two control approaches. The main objective of this work is to elaborate a fuzzy model and build a fuzzy controllers for a biological process by using the fuzzy Takagi-Sugeno. Two controllers are synthesized, the parallel distributed compensation control and optimal fuzzy linear quadratic integral control. In both cases, the physical constraints on the manipulated inputs are respected. In addition, the case with and without the observer is presented, where a fuzzy observer based control is used with unmeasurable premise variables. Finally, the performances and the effectiveness of both the modeling and the control are demonstrated via simulations.

Read more…

In this research we address the problem of routing information across dynamic temporal sensor networks. The goal is to determine which information, generated by sensors on resources at various times, is able to be routed to other resources, consumer resources, within the given information time window, while being constrained by temporally dynamic bandwidth limitations across the sensor network, and storage limitations on the resources. A mathematical model of the problem is derived, and used to find solutions to the problem. In addition, a heuristic is developed to efficiently find good quality solutions. Monte-Carlo simulations are performed comparing solutions found by commercial software with the heuristic.

Read more…

MARWIN is a mobile autonomous robot platform designed to carry out maintenance and inspection tasks in the European XFEL. The XFEL is an accelerator plant which is operated in Hamburg, Germany. The robot system consists of an four-wheel drive chassis and a scissor lift for easy inspection and maintenance tasks. Through this manipulator and the chassis, the robot system acquires three degrees of freedom. MARWIN is intended for autonomous radiation measurements along the XFEL research facility and thus needs accurate localization. The facility describes a straight tunnel and consists partly of irregular structures and also of sections with almost no obstacles. In the 1000 meter long sections in which MARWIN operates, the robot must approach the facilities to a few centimeters, but must not touch them. For this purpose, di fferent localization methods were tested and checked for accuracy. Furthermore, the influence of radiation on the localization is investigated.

Read more…

Automatic speech emotion recognition (SER) techniques based on acoustic analysis show high confusion between certain emotional categories. This study used an indirect approach to provide insights into the amplitude-frequency characteristics of different emotions in order to support the development of future, more efficiently differentiating SER methods. The analysis was carried out by transforming short 1-second blocks of speech into RGB or grey-scale images of spectrograms. The images were used to fine-tune a pre-trained image classification network to recognize emotions. Spectrogram representation on four different frequency scales – linear, melodic, equivalent rectangular bandwidth (ERB), and logarithmic – allowed observation of the effects of high, mid-high, mid-low and low frequency characteristics of speech, respectively. Whereas the use of either red (R), green (G) or blue (B) components of RGB images showed the importance of speech components with high, mid and low amplitude levels, respectively. Experiments conducted on the Berlin emotional speech (EMO-DB) data revealed the relative positions of seven emotional categories (anger, boredom, disgust, fear, joy, neutral and sadness) on the amplitude-frequency plane.

Read more…

Advanced sensing technologies are providing for greater capabilities to discern and classify details of objects as they appear in actual environments as experienced by nonprofessional drivers. Distinctive geometric configurations of new sensory devices including but not limited to infrared (abbreviated as IR) and LIDAR sensory units are appearing as cost effective data acquisition systems for environment sensing and presenting. Here, we describe a novel IR sensory-based autonomous vehicle guidance and its associated convoy unit. The underlying systems is first presented in a general system model and the experimental test results have been elaborated to demonstrate the usefulness of the presented prototype in futuristic auto industries and its supporting branches, respectively.

Read more…

Finding similarity of textual data is very important task in natural language processing. In this article we present approach to finding similarity of words, paragraphs, sentences and documents. Semantic similarity is one of the central tasks in many applications, including text summarization, Intelligent Tutoring Systems (ITS) etc. In ITS sentence similarity is used to compare the student’s response with the correct answer. The result is used to gain information about student’s level of knowledge. We propose three different methods that measure text to text semantic relatedness. There are multiple approaches to finding the right measure to determine the similarity of the sentences. Some measure the alignment of characters, and other measure semantic similarity between sentences. In this work we present and evaluate methods for finding not just similarity of sentences but even also similarity of whole paragraphs and documents. We have evaluated these methods using the data from the Yahoo Question and Answer of the Non-Factual Data Set.

Read more…

As the contribution from renewable energy sources increase, the power quality degradation has become a challenge for the power system operator. There are major two factors causing power quality deterioration. First is the current harmonic generation by the power electronic converters used in renewable energy sources, and second is the magnification of harmonic voltage due to harmonic resonance condition educed by power factor correction capacitors. The motivation behind this work is power quality related problems, observed recently in the field. To analyze the problem a comprehensive approach is adopted. A practical wind farm configuration is considered for study. Using an eigenvalue analysis method, critical resonance modes are determined for different value of capacitor connected to different buses. To check the effect of change in network parameter on eigenvalue, the sensitivity analysis is carried out and how resonant point is varied with the capacitor value and connection point is discussed by simulating different cases. The results are useful in determining the filter value and location for maximizing its effectiveness in curbing the harmonic problems.

Read more…

This paper first simplifies the GA-optimized filter structure developed by us. Then the filter structure is modified by introducing slot and conductor stubs, based on electric fields and magnetic currents at resonant and transmission zero points. As a result, return losses in two passband regions are suppressed more than 28 dB, and also insertion loss in stopband dividing two passbands is suppressed more than 20 dB. Finally, two kinds of the proposed filters are fabricated, and effectiveness of them is confirmed from comparison between the measured and the numerical results.

Read more…

This work introduces the design and prototype development of a novel optical-based fingertip force sensor, which is integrated in a bio-mimetic finger for robotic and prosthetic manipulation. Given the optical nature of the sensor, the proposed device is free of any electrical and metal components. Accordingly, the design improves manipulation of objects with high electromagnetic compatibility performance, reducing sensor’s susceptibility in the presence of these disturbances. The sensor has inherently high SNR and low-power consumption. The concept of using simplified and low cost optical based fingertip force sensor for bio-mimetic anthropomorphic fingers has not been widely implemented so far. The sensor is based on a cantilever design combined with a couple of fiber optics and a reflective surface, it is integrated on the distal phalange of a novel bio-mimetic and anthropomorphic robotic finger. Sensor design was performed and optimized throughout a 3D printing process and Finite Element Analysis. The sensor’s sensitivity (0.098V/N), resolution (0.01N), accuracy (3% of full scale output (FS)) and hysteresis (9.24% of FS) were characterized through a calibration processes. Various applications like surgical manipulation or handling in harsh environment (i.e. high voltage, high temperature and explosive environments) will benefit from the proposed sensor’s performance, reliability, simplicity and bio-compatibility.

Read more…

In this work, we discuss how the insertion of a LaSiOx layer in between an in-house IL passivation layer and the high-k has moved the III-V gate stack into the target window for future technology nodes. The insertion of this LaSiOx layer in the gate stack has reduced the Dit and Nbt below the target level of 5×1011 /eV.cm2 and 3×1010 /cm2 (target at 10 years operation: ?Vfb<30mV at 125°C) respectively. From physical analysis, it was found that LaSiOx can stabilize the interaction of the IL layer with the InGaAs substrate. An implant free In0.53Ga0.47As n-MOSFET was fabricated with this gate stack and for the first time, a III-V gate stack meets the reliability target for advanced technology nodes with a max operating Vov of 0.6 V. In addition, an excellent electron mobility (µeff,peak=3531 cm2/V-s), low SSlin=71 mV/dec and an EOT of 1.15 nm were obtained. We also report the scaling potential of this stack to 1 nm EOT without any loss in performance, reliability and further reduction of the sub-threshold swing (SSlin=68 mV/dec).

Read more…

This paper presents a novel parametric co-variance assignment strategy for multi-variable stochastic uncertain systems. Based upon the explicit parametric design and reduced-order closed-form co-variance model, the variances and co-variances of the system outputs can be assigned artificially using output feedback while the effect of the system uncertainties can be minimized by optimizing the free parameters. In addition, the stability of the closed-loop system has been analyzed and an illustrative numerical example is given to demonstrate the effectiveness of the presented strategy. As a summary, the contributions of this paper include the reduced-order co-variance model, the co-variance error based performance criterion and the parametric control design with stability analysis.

Read more…

A lot of research reported that the active learning, especially the flipped classroom learning has higher performance than the lecture-based learning called the traditional learning. Therefore, this research is experimented on the object-oriented analysis and design course. The objectives are to try the flipped classroom learning with the workshop activity in order to analyze learners’ behavior and to evaluate the effectiveness of the learning system. The aim of the research is to determine the suitability of the flipped classroom learning on the object-oriented analysis and design course, and to find the advantages and limitations of such learning method. The scope of this research is to test on the object-oriented analysis and design course, Faculty of Science, Chulalongkorn University. CourseVille developed by Chulalongkorn University is used as the learning management system. Moreover, the learning materials are Thai lecture videos, and English documents, such as English PowerPoint slides. Furthermore, the examples of activities in the classroom are Thai discussion and group activities, including the learner presentation. The research mythology is to collect data from learners composed of the behavior of the learners, learners’ test scores, the result of the workshop activity and the output of term project. In addition, the collected data from the questionnaires about learner opinions with the classroom observation result are used for analyzing the learner attitude of the flipped classroom learning, and the learners’ scores in the flipped classroom learning are compared to those in the traditional learning. In conclusion, the research results show that the 90 percentage of learners agree that the flipped classroom learning is suitable for the object-oriented analysis and design course, and it has higher performance that the traditional lecture-based learning system.

Read more…

A low-complexity dual-band chirp FSK, direct conversion receiver is described in this paper. The receiver is dedicated to be used in the transceiver unit of a medical implantable wireless sensor. The system uses the RF band between 402 and 405 MHz. Two sub-bands frequencies employing chirped pulses are assigned for both binary information. The novelty of this work is the use of a Binary FSK LFM modulator, a direct conversion receiver and a simple and low power non-coherent BFSK envelope detection demodulator. Receiver performances are evaluated for all the input power dynamic range. Receiver front-end parameters are optimized using harmonic balance simulation. In order to improve receiver sensitivity, a low pass filter with controllable bandwidth between 40 and 300 KHz is used to avoid in-band interference. The receiver is able to achieve a noise figure of 5.5 dB, a receiver sensitivity of -93 dBm and a maximum data rate of 100Kbps. The simulated IIP3 and P-1dB are 12.6 dBm and 22.1 dBm respectively. A simple non coherent binary dual band FSK demodulator was used which is based on an envelope detector, integrate & dump, a sampling & hold and a liming circuit. The receiver was co-simulated with the dual band non coherent demodulator. The proposed receiver has a sensitivity of -93 dBm and a BER less than 10-3.

Read more…

There are more than 7billion people in the world where there are around 500 million people in the world who are denied from normal lifestyle due to physical and mental issue. It is completely fair to say that every person deserves to enjoy a normal lifestyle. While physically and mentally challenged people find suitable way to surpass their limits, thus become able in other ways, researchers always try to find solutions better than the existing one. A complete remedial of such issue is included in advanced medical science, and the amelioration of such issue to a better extent is the challenge for the engineers.
In this work we have focused on hand gestures. Hand gestures are created using the movement of hand and arm, using fingers to create different shapes, using fingers and palm to create different angles. Single or both hands can be used to create different expressions. The main objective of this work is to generate an algorithm that can recognize different patterns of hand gestures with notable accuracy. American Sign Language is one possible reference model that can be used. Images of different hand signs are taken as inputs using a webcam, followed by segmentation of the images using polygon approximation and approximate convex decomposition. Feature extraction is done by recording the unique feature among the various convex segments of the hand. The resultant singularities are then used as extracted feature vectors. This involves training with the obtained features which are approximately unique for different hand gestures. Hence, we will be able to identify sign languages and successively make disabled individuals socially acceptable. This work is an extension of the work entitled “A Machine Learning Framework Using Distinctive Feature Extraction for Hand Gesture Recognition” in 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (IEEE-CCWC).

Read more…

The Internet of Things (IoT) is a new concept that has a great appeal for researchers, businesses and the ordinary tech user. It presents new possibilities of connection between devices and people and it stimulates our need and desire to interact, to exchange ideas and to communicate with the surrounding environment. This paper briefly explores aspects of the IoT that may be important for future developments and focuses on the impact of creative methodologies, such as user centered design (UCD) in a smart parking, IoT-based system prototype. It aspires to provide an alternative perspective for an improved user experience (UX) and aims to contribute to the discussion about the challenges, findings and perspectives when merging science and creativity to maintain continuous progress in the IoT domain.

Read more…

The latest design approach for Data Centers (DCs) follows the direction of exploiting optical switching to connect Top-of-Rack (ToR) switches that serve thousands of data storing and computing devices. A ToR’s usual function is the Virtual Output Queues (VOQs), which is the prevalent solution for the head-of-line blocking problem of the DC switches. An effective VOQs architecture improves the DC’s performance by reducing the frames communication latency and it is efficient with respect to the implementation cost. The current paper introduces a VOQs architecture for the ToRs of DCs that function with Time Division Multiple Access (TDMA). The proposed VOQ architecture contains a bounded number of queues at each input port supporting the active destinations and forwarding the input Ethernet frames to a shared memory. An efficient mechanism of low latency grants each queue to an active destination. The VOQs constitutes a module of a ToR development, which is based on a commercially available Ethernet switch and two FPGA Xilinx boards, the Virtex VC707 and the Xilinx NetFPGA. The VOQs architecture’s implementation and validation took place on the NetFPGA board.

Read more…

This paper introduces an electroencephalogram (EEG) analysis method to detect preferences for particular sounds. Our study aims to create novel brain–computer interfaces (BMIs) to control human mental (NBMICM), which are used to detect human mental conditions i.e., preferences, thinking, and consciousness, choose stimuli to control these mental conditions, and evaluate these choices. It is important to detect the preferences on stimuli. If the stimuli related to the preference can be detected, the NBCIMC can provide stimuli to the user based on their emotions by detecting their favorite stimuli. The proposed method adopted EEG recording technique, extraction techniques of EEG features and detection methods of preferences. EEG recording employs a simple electroencephalograph, for which the measurement position is the left frontal lobe (Fp1) of the brain. We assume that the differences of the EEG activities on the patterns of preference are expressed in the association between the changes of the power spectra on each frequency band of the EEG. To calculate the association, we employ the gray theory model. The EEG feature is extracted by calculating the gray association degree, then, the preferences are detect using a support vector machine (SVM). Experiments are conducted to test the effectiveness of this method, which is validated by a mean accuracy rate >88% on the favorite sound detection. These results suggest that the detection of subject’s favorite sounds becomes easy when the EEG signals are analyzed while the gray associate degrees are used as the EEG feature and the SVM is used as the classifier.

Read more…

In this work, we investigate the effects of variation of processing parameters on the quality of dispersion of polycarbonate compound. In order to achieve appropriate pigments dispersion, we performed compounding process parameters optimizations, by investigating three processing parameters, temperature, screw speed, and feed rate. We utilized experimental design for the optimization of process parameters based upon three levels full factorial response surface methodology was utilized. The experimental designs, statistical and numerical optimization were performed using design expert software. Statistical equation was developed to understand individual parameters interactions on the values of color. The model was established as statistically significant based on diagnostic tests performed. Our analysis of variance (ANOVA) illustrates that the parameters of color (dL*, da* and db*) are affected by the three investigated parameters. The process parameters required to attain color values in a minimum desirable deviation dE* of 0.8 were found through optimization to be equal to 245.26 oC, 741.27 rpm, and 24.72 kg/hr. Furthermore, we also demonstrate variations of the processing variables while other parameters remained constant (General Trends). Both strategies generated process parameters that were statistically significant. SVM is used as the classifier.

Read more…

This work presents new pipeline-parallel, generic and configurable parallel hardware architectures for the Direct/Inverse Wavelet Packet Transform (DWPT/IDWPT) independent of any specific family of wavelets, implemented in FPGA technology using a parallel architecture of direct FIR filter. We propose in the following paper, new P-parallel structures for the DWPT and IDWPT transforms based on the Mallat binary tree algorithm. Therewith, we developed a P-parallel/modified direct FIR filter architecture using pipeline-parallelize and hardware resource sharing, which provides not only ultra-high speed data processing but also a limited amount of hardware as resources are shared between filters and the bidirectional wavelet packet transformation. This model follows two important strategies: I) a powerful structure pipeline/P-parallel using strict data management and interleaving, II) sharing hardware at different levels in the transformation and between the two DWPT/IDWPT transformations. These architectures are modeled in VHDL at RTL modeling level. They are generic and fully configurable: at synthesis and post-synthesis.
The simulation results show an acceleration of data processing to an approximate value of P-Parallel multiplied by frequency with lower used resources. Furthermore, the impact of tree depth and filters order on throughput is very light due to the linearize architecture of our model. The synthesis was achieved using the Intel Quartus Prime Lite Edition software and targeting the Intel Altera Cyclone FPGA technology.

Read more…

Industrial estate firms have important roles in national development through the industrial development. In the course of their life, industrial estate firms ought to follow the firm life cycle pattern. The common pattern shows that the period, in which the firm experiences profit increase, will be directly followed by consistent profit and profit decrease. Should the strategy realization are not precisely implemented during each stage, especially the decreases period, it will be difficult for the firm to survive.
A strategy that can be implemented by industrial estate firms in order to be sustained is to manage Product-Service System (PSS). It is a well-known concept in creating opportunities for a new business model in which firms can offer bundles of products and services to their customers instead of merely tangible products. PSS can be distinguished into three types of categorization consist of different compositions of products and services and different business activities. Each type of PSS and business activities can be applied at the stages of the firm life cycle in accordance with its condition to maintain the company’s sustainability at every stage of its life cycle. In this article, we construct a conceptual framework to help Indonesian industrial estate firm to be alert on the need to focuses on providing services instead of only selling products. This article also shows that different PSS management would be needed in particular stages of firm life cycle. Applying suitable PSS and business activities based on PSS in each stage of the firm life cycle can lead to gaining a competitive advantage and sustainable industrial estate firms. This article’s novelty is to combine the PSS concept concerning each stage of firm life cycle at industrial estate firms.

Read more…

With the increasing need for effective storage management due to ever-growing content-generation over the Internet, Distributed Storage Systems (DSS) has arisen as a valuable tool. Although DSS has considerably improved in the past years, it still leverages legacy techniques in its networking. To cope with the demanding requirements, Software Defined Networking (SDN) has revolutionized the way we manage networks and can significantly help in improving DSS network management. In this paper, we propose an SDN-based network control method that is capable of handling DSS network management and improving its performance. This paper presents the design, implementation, and evaluation using an emulated environment of a typical Data Center Network (DCN) deployment. The experiment results show that by applying the proposed method, DSS can increase the performance and service resilience compared to existing solutions.

Read more…

Fifth generation of mobile networks (5G) comes to cope with the context of the new mobile telecommunications era. Edge computing is a new collaborative technology under standardization utilizing end-user devices or near-end-user edge devices to operate processing, communication, or control operations. The achievement of efficient error control is a very critical aspect in the successful development of 5G Next Generation Mobile Networks (NGMN). Especially utilizing Forward Error Correction (FEC) codes on the application level is an efficient approach on improving error control on NGMN since it is adopted in several mobile multicast standards. FEC is a feedback free error control technique where redundant data are introduced with the source data to enable the recipient recovering from packet losses with an interesting approach on applying AL-FEC error protection introduces deterministic or randomized online algorithms. Based on this we present a novel online scheme on applying AL-FEC application on the context of the AL-FEC policy online problem. In this work we present an online algorithm based on feedback received from mobile end-users which adapts the introduced protection based on this. Another aspect of this work is the utilization of AL-FEC protection on the edge level based on RaptorQ FEC codes.

Read more…

Robot contests are suitable for bachelor courses to gather hands-on experience in engineering diciplines such as mechanics, electronics and embedded software. After summarizing a concept of a robot contest for distance education (robot sumo) as presented in earlier publications this paper describes the implementation and first results of this concept. The contest is seperated into different tasks such as line detection and opponent location. As an example for transferring theoretical knowledge into a working prototype a simple sensor design for robot sumo is described and tested. Additionally a first student concept of a self designed robot is presented.

Read more…

In this study, torrefaction pretreatment on palm kernel shell (PKS) was investigated using fixed bed reactor. The PKS was torrefied at the temperatures of 210, 230, 250, 270 and 290 °C. The characteristics between untreated and torrefied PKS were compared. The results showed that, the mass and energy yield lessened, while the calorific value augmented with the increasing torrefaction temperature. Furthermore, with the rise of temperature, the oxygen composition, O/C ratio, oxygenated compounds and volatile matter of torrefied PKS decreased, but, the carbon and fixed carbon content increased. The composition of carbon in torrefied PKS was toward coal where equivalent calorific values was achieved. The gasification of torrefied PKS enhanced the product yield which produced higher gas, lower tar and char yield than the gasification of untreated PKS. Gasification of torrefied PKS increased the gas yield by 16.9 % than the untreated PKS. The tar and char yield of torrefied PKS decreased by 19.4 % and 25.9 %, respectively than the untreated PKS. Therefore, the torrefied PKS, by which their physical and chemical properties have been improved through torrefaction pretreatment is more suitable to be used in gasification and co-gasification as their influences are significant than the untreated PKS.

Read more…

Digitalization changes the way people work to a considerable extent. It alters business models and process organizations of whole industries. The ensuing market dynamics and faster innovation cycles cause an increase in complexity. In this article, the interconnection of digitalization and complexity in work systems is analyzed. For this purpose, a framework for comparing relevant complexity definitions is developed. Moreover, complexity drivers in digitalized labor systems in six different organizational dimensions (process organization, organizational structure, technology, working conditions, product and personnel) are explored. 23 experts from the academic and industrial sector were interviewed using semi-structured interviews. The results of a qualitative content analysis show that the consideration of complexity and digitalization has extensive impact what becomes evident in interdependent relations amongst the organizational dimensions. Furthermore, complexity drivers in digitalized work systems are determined as a result of the analysis procedure. Finally, the implications of the expert interviews for cooperative forms of work are discussed. The concept of a “task complexity mountain range” is presented to explain the effect of task complexity on performance and motivation in the context of work groups.

Read more…

Network motif analysis has several applications in many different fields such as biological study and social network modeling, yet motif detection tools are still limited by the intensive computation. Currently, there are two categories for network motif detection method: network-centric and motif-centric approach. While most network-centric algorithms excel in enumerating all potential motifs of a given size, the runtime is infeasible for larger size of motifs. Researchers who are interested in larger motifs and have established a set of potential motif patterns could utilize motif-centric tools to check whether such patterns are truly network motifs by mapping them to the target network and counting their frequency. In the paper, we present NemoMap (Network Motif Mapping algorithm) which is an improvement of the motif-centric algorithm, GK (by Grochow and Kellis) and MODA (Motif Detection Algorithm). Experimental results on three different protein-protein interaction networks show that NemoMap is more efficient in mapping complex motif patterns, while GK and MODA is much faster in analyzing simpler patterns with fewer edges. We also compare the performance of NemoMap and ParaMODA (introduced previously to improve MODA), and the result shows that NemoMap yields better runtime due to the implementation of Grochow-Kellis’ symmetry-breaking technique and the better node selection process.

Read more…

An experimental investigation of reconfigurable ultra-wideband (UWB) modified octagonal microstrip monopole patch antenna with switchable and tunable band-notched characteristic is presented in this paper. Notched-bands are obtained by connecting or disconnecting the open shunt stubs. The switching is achieved by using PIN diodes. Additionally, more notch-bands are created by adding additional stubs to the original design and tuning is achieved by employing a varactor diode in the circuit. The proposed antenna has more freedom to suppress the interfering bands because of tuning nature. The proposed designs are simulated, fabricated and then tested. The proposed structures are simple in geometry and useful to operate in the rich electromagnetic scattering environment.

Read more…

Recently, several studies focus on a GaN material system that exhibits a significant probability of use in power devices including wide-gap semiconductors. However, the GaN-HEMT is also a structure that easily leads to crystal defects in AlGaN and i-GaN heterojunction. The aim of the study involved investigating the cause of the current collapse in GaN-HEMT after device construction. A GaN-HEMT with a field plate structure was subject to an environmental temperature change from 300 K to 400 K. A pulse voltage was applied to the gate electrode, and the transient response characteristic of the drain current was analyzed. Given the application of the pulse voltage on the gate electrode, charging and discharging of 2 DEG carriers was repeated with respect to crystal defects near the gate electrode. The charge / discharge reduction was observed via a sampling oscilloscope as a transient response. The transient response exhibited an evident dependence on temperature change. The dependence indicated a time constant change, and thus it was possible to calculate the activation energy of crystal defects trapping carriers. The results suggested that the crystal defect evaluation of GaN-HEMT was possible via transient response analysis of 2DEG carrier by using the proposed method.

Read more…

In this research paper, the development and evaluating of a smart controller for electrical powered wheelchairs are presented. The controller aimed to assist quadriplegic, paralyzed, and handicap patients who cannot use their hands to drive an electrical wheelchair by using a joystick controller. Two sub control units have been combined in one hybrid system to create the current version which are voice, and head tilt controllers. They are activated and operated in parallel at the same time to allow the wheelchair user to choose the preferred control method. The voice controller is activated by the user’s voice command to control the wheelchair instead of a joystick. The head tilt controller uses the user’s head motions to create control commands instead of the joystick controller. The head tilt controller design is based on using two embedded MEMS orientation detection modules as input measurement units. The system uses a modern low power consumption microcontroller to analyze the received information and data from inputs and creating the prompt control commands and send it to the wheelchair motors driver as an output unit.

Read more…

At present, the wireless charging and data transmission systems developed by major car manufacturers rely heavily on additional transmission equipment. This paper presents a newly developed wireless power and bidirectional data transmission scheme without adding any radio frequency (RF) devices. The battery charge status and vehicle related information can be transmitted bidirectionally in the wireless manner by the compensation capacitor between two isolated units. Based on the function, this system can quickly inform the user when an emergency event occurs during power transmission. An inverter is used on the primary side of the system, and the generated AC power is transmitted to the load at the secondary side through mutual inductance; the secondary side of the system adjusts the load current to transmit data back. The primary side uses the zero voltage switching (ZVS) method to receive data, and the trimming of the current curve to transmit commands; the secondary side of the system receives commands and uses carrier cycles for decoding. Experimental verification shows applicability of the proposed system.

Read more…

Cloud Computing is considered nowadays an attractive solution to serve the Big Data storage, processing, and analytics needs. Given the high complexity of Big Data workflows and their contingent requirements, a single cloud provider might not be able alone to satisfy these needs. A multitude of cloud providers that offer myriad of cloud services and resources can be selected. However, such selection is not straightforward since it has to deal with the scaling of Big Data requirements, and the dynamic cloud resources fluctuation. This work proposes a novel cloud service selection approach which evaluates Big Data requirements, matches them in real time to most suitable cloud services, after which suggests the best matching services satisfying various Big Data processing requests. Our proposed selection scheme is performed throughout three phases: 1) capture Big Data workflow requirements using a Big Data task profile and map these to a set of QoS attributes, and prioritize cloud service providers (CSPs) that best fulfil these requirements, 2) rely on the pool of selected providers by phase 1 to then choose the suitable cloud services from a single provider to satisfy the Big Data task requirements, and 3) implement multiple providers selection to better satisfy requirements of Big Data workflow composed of multiples tasks. To cope with the multi-criteria selection problem, we extended the Analytic Hierarchy Process (AHP) to better provide more accurate rankings. We develop a set of experimental scenarios to evaluate our 3-phase selection schemes while verifying key properties such as scalability and selection accuracy. We also compared our selection approach to well-known selection schemes in the literature. The obtained results demonstrate that our approach perform very well compared to the other approaches and efficiently select the most suitable cloud services that guarantee Big Data tasks and workflow QoS requirements.

Read more…

The monitoring of environmental parameters is a critical topic in occupational medicine. With advances in technology, during the recent years, the wearable sensors are widely used to evaluate the ambient parameters. In this paper a compact, small, light-weighted, and configurable sensor node in three physical layers for prolonged chemical ambient monitoring is described. The device is designed and demonstrated by using MLMS (Multi-Layer Multi-Sensor) concept. The device application is not only limited to hazardous gas (CO & NO2) monitoring but physical ambient elements (air pressure, air humidity and temperature) and motion tracking are tracked, too. The device consist of integrated (ambient physical and motion tracking) and add-on sensors (hazardous gases) and enables centralized data processing. The integrated sensors are distributed on the middle physical layer on both sides (host platform). The host platform also includes micro controller and antenna for data transmission to the smartphone. The gas sensor along with the gas sensor driver board form the gas sensor node which for easy gas exposure is located at the top of the device and stuck at the top of host platform. The gas sensor driver is designed universally to be compatible with 3-lead gas sensors with low power consumption. This layer is replaceable and can be substituted with one more target gas (e.g. NO2 instead of CO). The sensor configuration and initialization is performed via sending commands from the smartphone to the device by the wearer. In addition, the device is equipped with the notification system (beeper and vibrating motor) for early user warning in an abnormal detected. The notification driver layer is located at the bottom of the proposed device. All physical layers are stuck on top of each other appropriately through a board to board connector. The collected data from integrated and add-on sensors are transmitted in various time interval to the smartphone for screening and logging. Filter design and calibration process are also briefly described in this work.

Read more…

This paper is an extension of work originally presented in the 19th International Conference on Computer Supported Education and Information Technology. This paper identifies motivational factors that ensure the initiation and effective implementation of mathematical activity. These factors are in subordination to each other, forming a hierarchical dependence. At the heart of this hierarchy is the practical need for solving problems from real-life practice. In order to actualize this need, a number of approaches are proposed, each of which manifests itself differently at various stages of teaching mathematics at school. At the first stage, the task material is intended, in the main, only to stimulate the consideration of certain mathematical problems. It also initiates to some extent the activity procedures inherent in reality through observation and experiment. At the same time, the emphasis in teaching is on solving problems of calculation, measurement, tracing, construction, cutting, etc. At the next stage, the main emphasis is on the possibility of using a mathematical tools in the study of related disciplines. It introduces elements of mathematical modelling of real-life states and processes, which can be carried out on the basis of solving various textual problems. At the final stage, the dominant focus the vocational guidance function of practice, the mathematical knowledge for successful implementation of future professional activity. Such awareness can be provided, in particular, with the help of pseudo-real applications from the relevant professional field. In this paper the authors also provides examples supporting each stage.

Read more…

Data deduplication technology is used to improve the spatial efficiency of cloud storage. This technology is used for storing data on a cloud and omitting data uploading if the data are already present. However, various security threats may occur during the deduplication process. These security threats include poison attacks and user identity exposure through ownership. In addition, in an environment in which ownership changes in real time, there is a problem in renewing ownership information that has already been issued. Therefore, various studies have been conducted to solve these problems. In this study, a poison attack, real-time ownership management, and ownership anonymization are provided through MLE and dynamic ownership management.

Read more…

The contents of this article consist of an extension original work presented at the 4th International Conference on Control, Automation and Robotics (ICCAR 2018) and aims to develop the systematic model of an effective triggering system of production Kanban size towards Just-In-Time (JIT) production system. The developed model was introduced based on the philosophy of continuous improvement program by selection of case study industry in automotive manufacturing floor and it has been carried out through the development of an effective material Kanban size model using triggering system towards achieving a JIT production system. This developed model was analysed and verified by implementing through three phases which are the investigation of the Kanban size, analysis the production idling time and analysis of the time management for material replenishment process. The implementation was carried out to ensure the main objectives of the developed model in minimizing the waste of waiting through effective Kanban size for production system will be achieved by focusing on the communication between material incoming warehouse and production floor. The significant results were obtained during the verification process where the dual material feeders were identified for every process in the production floor to ensure the effectiveness of the production system. Throughout the implementation of the developed model, the production losses time caused by miscommunication between the production floor and warehouse had been identified and it was successfully minimized and the waiting time was reduced by 36.64%.

Read more…

The effect of rotation and translation of an electromagnetic (EM) scatterer upon the scattered field is studied for the case of TM polarization. The Franklin and Lorenz transformations are used to analyze the phase and the magnitude of the backscattered field during the movement of the scatterer. Also, a new model is presented that simulates rotation and translation using static data. This stationary data is generated using FEKO. These simulation results of the exact analytical solution are compared with the results of the proposed model using static data. Finally, a comparison between the phase and magnitude of the backscattered field of a scatterer undergoing both translation and rotation for the two different modes (TM and TE) is presented.

Read more…

Nowadays, many companies and organizations use various encryption techniques to secure their private data before send it through the unsecure network. However, many attackers try to store private data by using various attacks. Most of the organizations use password based encryption algorithm (PBE) to protect their private data. However, the existing PBE methods are vulnerable in brute-force attacks because of user-generated weak or repeated passwords. The problem of weak password based encryption algorithm prompted us to introduce honey encryption (HE). Honey encryption and honeywords help to minimize this vulnerability of password based encryption algorithm and they can prevent the text based messages from brute face attacks in order to make messaging communication more secure and efficient. However, the conventional HE has message space limitation in Distribution Transforming Encoder (DTE) process and storage overhead problem in honeywords generation process. Therefore, our proposed honey encryption algorithm uses discrete distribution function in DTE process to solve message space limitation instead of using cumulative distribution function. Storage overhead and typo safety problem can overcome by using our proposed honeywords generation method in honey encryption algorithm. Furthermore, we also propose hashing and salting algorithm for securing password and key expansion. In this paper, we describe the case studies as a calculation of DTE and hashing and salting algorithm. And then, we design and implement the improved honey encryption mechanisms and honeywords generation algorithm in message transmission process. Finally, we show the comparison results using mathematical model in DTE process and security analysis of our system.

Read more…

The proposed solution is intended for virtual universities wishing to improve their distance learning platforms. These enhancements include the instructional content model, how to deliver courses to students, and how to evaluate students’ knowledge. With this solution that improves the functionality of Moodle, virtual classes now include new features such as the transfer of heavy files, control of remote screens, video, audio, chat without degradation of the quality of service. The solution will be particularly useful for language teachers who have difficulty in assessing the speaking skills of their students. Indeed, the platform with its audio / video features, integrates a tool to assess the knowledge and improve the speaking skills of students. Teachers of technical subjects such as programming or computer networks will also be able to use this solution to improve the way they deliver courses, including making it easier for students to do practical work.
On the technical side, the solution is based on the MSRP-RELAY, MSRP and Websocket protocols. It is therefore compatible with smartphones, tablets and computers. Tests were conducted with teachers of languages and STEM subjects to evaluate their students in direct synchronous encounters without necessarily going through multiple choice questions.

Read more…

Intelligent Transportation Systems (ITS) applications can take big advantage of Context Awareness approaches. Parameters such as user mobility, passengers comfort reaction and pollution emission levels (CO2) can enrich such applications during the decision making phase. Moreover, the expanding in ITS services offers great opportunities for travelers to find the best route to reach their destinations with the lowest or fair costs. It can offer a selecting methodology for optimal route that adapted with some processing parameters like CO2 level, ticket cost, waiting or connection times and the overall traveling time plus the comfortability reaction for each means of transportation) in real time environment using Machine Learning (ML) tools like Q-Learning or SVM: Support Vector Machines. This paper aims at conducting a comparison study for green ITS routes (i.e. the lowest CO2 levels). The study compares between Q-Learning and SVM techniques for identifying different variety of routes between two stops as ranked routes from best to lowest based on some traces gathered from some known transportation traces. Reinforcement Q-Learning is applied to validate the first phase in our approach to recommend the best means and SVM is used to validate the prediction phase about the best route among different routes built based on three means of transportation (metro, train and bus).

Read more…

This survey paper deals with the structural health monitoring systems on the basis of methodologies involving intelligent techniques. The intelligent techniques are the most popular tools for damage identification in terms of high accuracy, reliable nature and the involvement of low cost. In this critical survey, a thorough analysis of various intelligent techniques is carried out considering the cases involved in civil structures. The importance and utilization of various intelligent tools to be mention as the concept of fuzzy logic, the technique of genetic algorithm, the methodology of neural network techniques, as well as the approaches of hybrid methods for the monitoring of the structural health of civil structures are illustrated in a sequential manner.

Read more…

A sequential pre-treatment of demineralization and torrefaction, was carried out on palm empty fruit bunches (EFB). EFB and demineralized EFB (DEFB) were torrefied in a vertical tubular reactor in the temperature range of 200 to 280 °C for 30 mins under nitrogen (flow rate:100 mL/min. The pretreated samples were characterized using proximate and ultimate analyses, fuel properties, and Fourier-transform infrared (FTIR) spectroscopy techniques. The thermal and kinetic study on the torrefied samples were carried out using thermogravimetric analysis. The results showed that sequential pre-treatment enhances the properties of solid EFB by increasing the carbon content and reducing the oxygen content with increasing the calorific value. Fuel properties of torrefied samples showed the mass and energy yield decreased, with an increase in energy density. In addition, the FTIR spectra showed the decomposition of hemicellulose occurring for torrefied samples as evidenced by the disappearance of the vibrational features belonging to hydroxyl and carbonyl groups. The kinetic study carried out using Coats-Redfern method on torrefied samples suggested that the activation energy can be transferred by the sequential pre-treatment, indicating that the abundant energy it has can be converted into bio oil of high quality. Apparently, torrefied samples bear high potential to be used as biofuel feedstock when exposed to further thermal decomposition and pyrolysis processes.

Read more…

The physically-based environmental model is a crucial tool used in many scientific inquiries. With physical modeling, different models are used to simulate real world phenomena and most environmental scientists use their own devices to execute the models. A complex simulation can be time-consuming with limited computing power. Also, sharing a scientific model with other researchers can difficult, which means the same model is rebuilt multiple times for similar problems. A web-service-based framework to expose models as services is proposed in this paper to address these problems. The main functions of the framework include model executions in cloud environments, NetCDF file format transmission, model resource management with various web services. As proof of concept, a prototype is introduced,implemented and compared against existing similar software packages. Through a feature comparison with equivalent software, we demonstrate that the Virtual Watershed System (VWS) provides superior customization through its APIs. We also indicate that the VWS uniquely provides friendly, usable UIs enabling researchers to execute models.

Read more…

A design of elliptical printed dipole antenna based on neural network approach is presented in this paper for recent WiMAX, Bluetooth, WLAN, LTE, and future 5G applications. The dipole patch is printed on top of substrate which has relative permittivity of 2.2 and 0.787mm of thickness. The elliptical dipole antenna is single band and the operational frequency is controlled by the major and minor axes of the ellipse. Neural network composed of one input layer, one hidden layer, and one output layer is implemented using simulated dataset of 24 samples collected using the electromagnetic simulator CST Microwave Studio. The neural network is trained using Levenberg-Marquardt algorithm and we divided the data set into 90% for training, 5% for testing, and 5% for validation. The error, described by the difference between the target data and expected output, is less than 0.005. The neural network model is a promising candidate to implement the design of elliptical dipole antenna to eliminate the simulation time taken by the EM simulator and reduce the cost of using large computing cluster.

Read more…

Nd:YAG laser has shown some potential to be used in dental practice replacing the conventional method. In particular, it can be used to modify the tooth surface by the ablation process. The laser provides an ability to accurately deliver a significant amount of energy into a confined region. Thus, alteration of the sample surface and composition may occur during the process. Additionally, the use of a laser in ablation procedure is also associated with heat generation and potential thermal injury that may be experienced by a patient. The wet condition of the samples is expected to reduce the thermal effect. In this paper, the changes of enamel surface and elemental composition following laser irradiation of Nd:YAG laser are discussed. The teeth samples were irradiated at 1.5 Hz of pulse rate, 100 ms of pulse width, and range of fluences of 80-120 J/cm2. Field Emission Scanning Microscopy (FESEM) and Energy Dispersive X-ray (EDX) were used to analyze the morphology and composition of the teeth samples. Samples were compared before and after laser irradiation. The percentages of carbon increased after laser irradiation, while oxygen decreased for most of the samples. The morphologies of the samples were varied with a more pronounced effect on the sample surface at higher fluence. In addition, the effect of wet sample condition is also investigated and discussed. It is demonstrated that the ablation in wet condition produced less damage to the enamel surface compared to dry sample. However, no remarkable difference between the elemental composition of wet and dry samples.

Read more…

Transport planners and engineers frequently face the challenge to determine the best design for a specific junction. Many road design manuals provide guidelines for the design and evaluation of different junction alternatives, however these mostly refer to specialized software in which the performances of design alternatives can be modelled. In the first stage of the design process, such assessments of many alternatives are undesirable due to time and budget constraints. There is a need for quick design rules which need limited input data. Although some of these rules exist, their usability is limited due to inconsistencies in rules and non-transparency in combination with objectives. In this paper, we present an approach by which consistent and transparent junction design rules can be determined. The resulting rules can be used to predict a set of viable junction design alternatives for the first stage of the junction design assessment process. The predicted set is in fact the Pareto optimal set of solutions for multiple objectives, e.g. regarding operational, safety and/or environmental impact. The Pareto optimal set of solutions always contains the best solution, whatever set of weights is used for different objectives in a later stage of the assessment process, thus handling multiple objectives in a straightforward manner. The rules are derived from a dataset by using decision tree data mining techniques. For this, a large dataset is first generated, using performance models, with Pareto optimal sets of junction design alternatives for a large amount of, randomly generated, traffic volumes. The approach is applied and evaluated on cases for two different countries. Results show that for over 90% of the situations the Pareto optimal set can be predicted by the new rules, whereas existing rules hardly reach 33%. The new rules provide junction design alternatives with a better performance.

Read more…

In most industrial high-power applications, the brushless DC (BLDC) motor is connected to multi-level inverters specially the three-level NPC inverters (B12). Torque ripple is a critical issue in BLDC motor drives. Accordingly, minimizing the ripple produced in the torque is necessary to enhance the BLDC motor drive performances. This paper aims to develop two direct torque control (DTC) schemes. To evaluate the proposed strategies performances, three DTC schemes, namely DTC- 1, DTC- 2, and DTC-3, are treated. The DTC-1 scheme is inspired from the Takahashi’s strategy proposed in induction motor drives. This scheme is penalized by the high torque dips. In view of that, the DTC-2 is proposed to address the DTC-1 limitations. Simulation evaluation proves that difference between the slopes of the incoming and outgoing phases currents procreates commutation torque dips penalizing the DTC-2 scheme. This difference is more serious at high speed. To overcome the DTC-2 strategy drawbacks, a DTC-3 scheme, based on the compensation of this difference, is proposed. Taking into account the increase of this difference with the increase of the rotation speed, the vector selection table design of this strategy is synthesized to minimize the torque ripple as far as possible.

Read more…

Usually, after properly biasing an analog circuit we need to linearize its transistors in order to linearize the entire circuit for performance analysis and design. This linearization is done through modeling of devices, which is becoming more and more complicated as the electronic technology advances. This is not of course a major issue for circuit simulators that use the latest device models and fast computers to deal with them. However, it makes it difficult when manual computation and understanding of the circuit behavior is in question. This is particularly important in teaching and training electrical engineering students.
What the proposed method offers is to simplify the case in two steps. First, adopt a most recent model with nominal parameter values for the transistors and run the circuit. Second, compare the circuit responses with those obtained through simulators with the most advanced device models. Next, with the help of one or more nullors try to modify the manually selected model parameters so that the two responses become close enough together. Several examples demonstrate the way the technique works and how close we can get to the simulated responses.

Read more…

This research is part of a study concerned with building an integrated framework for development of sustainable urban planning in Iraqi provinces. Seven Iraqi middle provinces are covered in this study. The aim of the study is to determine, measure and evaluate economic and social sustainability in the Iraqi middle provinces.
The stages to achieve this research were based on establishing a two levels hierarchy framework (a level for categories and a level for indicators). In this study, the Economic dimension comprised of 6 categories and 18 indicators and the Social dimension comprised of 8 categories and 41 indicators. Through using the Multi Criteria Analysis method and the Analytic Hierarchy Process, the Sustainability Index has been determined and used to measure and evaluate the economic and social sustainability in the Iraqi middle provinces

Read more…

Flow measurements are important for numerous industries as it directly relates to proper equipment functioning and product quality. This work demonstrates a novel thermal energy based compact flow measuring sensor. The sensor injects thermal energy into the core which is then extracted by the moving flow through the center of the core. Temperature changes produced by thermal energy exchange is evaluated over time and then used to calibrate and measure flows. The sensor can detect extremely low energy changes therefore measure relatively low flow rates as well. Being minimally intrusive, it does not disturb the flow eliminating any additional resistance commonly introduced by intrusive type sensors. It is made from inexpensive components and is easy to assemble therefore making it affordable. The simple geometry allows for it to be easily incorporated into compact systems and can be used in miniature devices to measure low flows. We declare this minimally intrusive only due to breaking the flow path with the sensor element otherwise it is non-intrusive.

Read more…

Plastic is highly polluting nowadays and is found in many disposable elements used for people. Plastic materials are disposed inadequately and large quantities of them become pollution in the ground, water, and air, affecting plants and animals. Most of the plastic is Polyethylene Terephthalate (PET) which is used in many activities. Resistance, support capacity, and flexibility are some characteristics that make PET useful in road engineering. This research shows a numerical simulation of three kinds of structures for pavements in PET. The simulation uses 3D models that were analyzed in the software SAP2000. The material characteristics of the recycling PET were taken from industries and analyzed in the laboratory. The model used in the simulation was composed of vertical loads for traffic type A. Loads were applied in the border, 0.75 meters and 1.5 meters from the border. Three types of structures were analyzed with three, four and five supports respectively. Structure type 2 with four supports displayed the best results regarding vertical displacements in all the elements. Structure type 2 was simulated with six different thicknesses (0.06, 0.08, 0.10, 0.12, 0.14 and 0.16 meters). Optimization of this material and the resistance of the structure showed the 0.10 meters thickness as the best due to its admissible vertical displacements and required the lowest quantity of material for producing it.

Read more…

Identity and Access Management (IAM) and Single Sign on (SSO) are two security concepts that are related to each other. IAM governs the user access in an organization whereas SSO facilitates the user by authenticating to one centralized application and not having to re-authenticate when trying to access other applications. This paper addresses the different benefits that an IAM and SSO tool can provide to reduce the security risk within an organization. Since, authentication and authorization are one of the major concerns in the cyber security; this paper analyzes common problems that are faced during authentication and authorization. We have also analyzed prior researches that have been done in the IAM and SSO space along with conducting a survey to understand the different issues and benefits of IAM and SSO. From the survey that has been conducted, we have addressed different issues when implementing IAM and SSO solutions along with understanding the architecture, in which these solutions have been deployed into. The surveys conducted have been compared with prior researches done in IAM and SSO space to understand the benefits that the solution provides. The results from the survey have been analyzed to provide the best practices when implementing IAM and SSO solutions along with the benefits provided by the solution.

Read more…

Predicting the impact of suicide on incidental witnesses at an early stage helps to avert the possible side effect. When suicide is committed in public, incidental observers are left to grapple with it. In many cases, these incidental witnesses tend to experience the emotional side effect with time. In this study, we employed a Machine learning algorithms to predict the impact of suicide and suicidal attempt on incidental witnesses. This prediction was based on the accounts of suicide given by selected participants who have witnessed the act. The accounts, which was pre-processed into a corpus, were manually annotated with predefined emotion categories. While sadness emerged as the most salient emotional impact on the witnesses, fear was found as the lowest of the emotional impact on the witnesses. However, the machine learning prediction yielded highest in predicting depression with insignificant variations in the other emotional categories. This nonetheless shows that people who have witnessed suicide or suicidal attempts are inherently affected by some form of emotions that may require urgent attention to alleviate. By evaluating the performance of the Machine learning algorithms, the Support Vector Machine was superior, in terms its prediction, then the Multinomial Naïve Bayes algorithm. The outcome of the study contributes to the pool of research that sought to advocate the use of Machine Learning for predicting social phenomenon.Identity and Access Management (IAM) and Single Sign on (SSO) are two security concepts that are related to each other. IAM governs the user access in an organization whereas SSO facilitates the user by authenticating to one centralized application and not having to re-authenticate when trying to access other applications. This paper addresses the different benefits that an IAM and SSO tool can provide to reduce the security risk within an organization. Since, authentication and authorization are one of the major concerns in the cyber security; this paper analyzes common problems that are faced during authentication and authorization. We have also analyzed prior researches that have been done in the IAM and SSO space along with conducting a survey to understand the different issues and benefits of IAM and SSO. From the survey that has been conducted, we have addressed different issues when implementing IAM and SSO solutions along with understanding the architecture, in which these solutions have been deployed into. The surveys conducted have been compared with prior researches done in IAM and SSO space to understand the benefits that the solution provides. The results from the survey have been analyzed to provide the best practices when implementing IAM and SSO solutions along with the benefits provided by the solution.

Read more…

Metaheuristic hybridization has recently been widely studied and discussed in many research works as it allows benefiting from the strengths of metaheuristics by combining adequately the different algorithms. MMACS is a new hybrid ant colony optimization algorithm based on the foraging behavior of ants. This algorithm presents two hybridization levels. The first hybridization consists in integrating the Ant Colony System selection rule in MAX-MIN Ant System. The second level of hybridization is to combine the hybridized ACO and an algorithm based on a local search heuristic, then both algorithms are operating sequentially. The optimal performance of MMACS algorithm depends mainly on the identification of suitable values for the parameters. Therefore, a comparative study of the solution quality and the execution time for MMACS algorithm is presented. The aim of this study is to provide insights towards a better understanding of the behavior of the MMACS algorithm with various parameter settings and to develop parametric guidelines for the application of MMACS to the Strongly Correlated Knapsack Problems. Results are compared with well-known Ant Colony Algorithms and recent methods in the literature.

Read more…

Advances in technology have enabled the installation of an increasing number of sensors in various mechanical systems allowing for more detailed equipment health monitoring capabilities. It is hoped the sensor data will enable development of predictive tools to prevent system failures. This work describes continued analysis of sensor data surrounding a seizure of a turbocharger within a propulsion system. The objective of the analysis was to characterize and distinguish healthy and failed states of the turbocharger. The analysis approach included mapping of multi-dimensional sensor data to a low-dimensional space using various linear and nonlinear techniques in order to highlight and visualize the underlying structure of the information. To provide some physical insight into the structure of the low-dimensional representation, the transformation plots were analyzed from the perspective of several engine signals. By overlaying operating ranges of individual sensor signals, certain regions of the mappings could be associated with distinct operational states of the engine, and several anomalies could be related to various points in the turbocharger seizure. Although the failed points did not map to an obvious outlier location in the transformations, incorporating expert domain knowledge with the data mining tools significantly enhanced the insight derived from the sensor data.

Read more…

Our research deals with the single-vehicle routing problem (VRP) with multi-shift and fuzzy uncertainty. In such a problem, a company constantly uses one vehicle to serve demand over a scheduling period of different work shifts. Our issue relies on a routing problem in maintenance jobs, where a crew executes jobs in different sites. The crew runs during several work shifts but repeatedly returns to the depot before the shift ends. The goal is executing all the activities minimizing the makespan. We examine the impact of uncertainty in driving and maintenance processing time on system performance. We realize an Artificial Immune Heuristic to find optimal solutions considering both makespan and overtime avoidance. First, we introduce a framework to assess the uncertainty impact. Then, we produce a numerical company case study to examine the problem. Outcomes present significant improvements are obtained with the proposed approach.

Read more…

This article discusses IoT security in situations whereby devices do not share the same security domains, which raises security, privacy and safety concerns. It then presents an Access Control and Privacy infrastructure for addressing these concerns in the context of distributed environments. IoT deployments allow billions of connected physical devices to collect, process and share data; collaborate and cooperate in automating tasks in an unrivaled fashion. However, security and safety are still top major fears that demand holistic approach, particularly when devices do not share the same digital trust. This is not a surprise, as a revolutionary system, IoT comes with inherent vulnerabilities, threats and risks like most other computing and data processing systems. Conversely, when security breaches or compromises occur, it is most likely to have a far-reaching and upsetting consequences that extends traditional concerns. The fact that IoT can be deployed in plethora of application scenarios; means that end-to-end security should be treated contextually and in a dynamic manner. Consequently, these concerns; trust, confidentiality, and privacy at the IoT application stack need to be addressed robustly. Thus, in this article, a novel distributed access control infrastructure based on configurable policy constructs is presented. The infrastructure provides a mechanism for gradual negotiated release of provable attributes to dynamically build trust before protected resources are made available. In this configuration, IoT transaction parties can express their Capabilities (competences, features, etc.) and Requirements (rules and provable attributes required to access the capabilities) as the basis for sharing data or collaboration in solving business problems.

Read more…

There are high expectations for commercial cloud services as an economical computation resource when executing scientific computing workflows, for which the computation is increasing on a daily basis. However, no method has been developed for determining whether a scientific computing workflow can be executed at a low usage cost, and thus scientists have difficulty in selecting from the diverse range of computational resources. The aim of this study is to provide clear criteria for selecting a computational resource while executing a scientific computing workflow. This study focuses on the performance of application execution for one such commercial cloud service, Amazon EC2, and proposes a method for selecting the optimal resource showing high similarity to a target application in execution time and usage cost. The novelty of this study is its approach of employing application similarity in resource selection, which enables us to apply our method to unknown applications. The contributions of this work include (1) formularizing performance values of computational resources, as well as similarity values of applications, and (2) demonstrating the effectiveness of using these values for resource selection.

Read more…

This study presented a prototype augmented reality (AR) application that helps visualize the affordances of everyday objects for infants in their home environments to prevent accidents and promote development. To detect and visualize affordances, we observed 16 infants regarding how they perceive and handle common objects from 4 to 12 months of age in their homes in Tokyo, Japan and in Lisbon, Portugal. Based on the longitudinal observation data, we developed an AR application for handheld devices (iPhone and iPad) and tested two types of vision-based markers. Ten types of basic objects were selected from the results of the observation and embedded into the AR markers. AR contents illustrated infants’ actions toward objects based on actual video data recorded for security purposes. To confirm the prototype’s advantages and improvements, informal user interviews and user tests were conducted. The results demonstrated that the prototype reveals the relationship between infants and their home environments, what kinds of objects they have, how they perceive objects, and how they interact with these objects. Our study demonstrates the potential of this application’s AR contents to enable adults to better understand infants’ behavior towards objects by considering the affordances of everyday objects. Specifically, our app assists in improving the perspective of adults who live with infants and promotes the creation of more flexible and safer environments.

Read more…

Climate change, increasing fuel oil prices and new international regulation on ship emissions lead to more focus on shipping fuel consumption and energy efficiency. There are various solutions for improving the ship energy efficiency. In this manuscript, we aim to present a real case of energy saving by adopting the central cooling system with box cooler on the ship instead of conventional system. The electric energy power necessary for operating the machinery cooling system of the ship is calculated for conventional cooling system and compared to the cooling system using box coolers in term of fuel oil consumption and CO2 emissions. This study quantified the fuel saving potential that could be achieved with use of keel coolers. Adopting central cooling with box coolers may contribute in reduction of fuel oil consumption and improving the ship energy efficiency. systems. should not contain citations.

Read more…

Exploring the ocean underneath has always been an area of great scientific and environmental concern. However, the study of underwater environment was very difficult due to the extreme conditions. Undersea descriptions undergo severe distortion attributed to absorptive as well as scattering properties. Absorption substantially removes illumination, whereas a ray of light redirected in several path when it interacts by substance. Because of these, undersea descriptions encompass blur as well as color loss. In this paper we suggested an effective technique namely, a turbidity removal method for deblurring the image. If the deblurred image has a lighting problem, we make use of a color-correction method to find the clear image. Our substantial qualitative and quantitative assessment expose that the proposed algorithm progress the excellence as well as lessen color distortion loyally, also improves the state-of-the-art undersea technique.

Read more…

Proportional navigation (PN) is a widely-used guidance law for missiletarget engagement. The goal of the missile intercept problem is to reduce the closest distance between the missile and target by diminishing the line-of-sight rate (LOS rate). In general, PN guidance law necessitates information of the LOS rate and missile velocity. The closing velocity (relative approaching speed to the target) instead of the missile velocity is an additional option for effective guidance. However, there are cases where a sensing device for measuring target motions that can be mounted on a missile is limited. In this paper, we propose a novel guidance law on the basis of proportional navigation (PN) using only line-of-sight (LOS) rate information. In this paper, an uncertainty and disturbance estimator (UDE) is applied to estimate such target motions including velocity change or unpredictable movement etc. The UDE works also for compensating uncertain modeled dynamics such as a missile’s bearing uncertainty and velocity changes. The proposed guidance law is referred to as uncertainty and disturbance-compensated intercept guidance. Numerical simulations with some engagement scenarios are presented taking account of the velocity changes of the missile to demonstrate the potential of the proposed guidance law.

Read more…

To gather information rapidly in disaster sites, a lot of search/rescue robots have been developed. It is difficult to correspond to the complicated environment composed of fields requiring various locomotion strategies, because most of these robots have only one type of locomotion device. To increase the available search routes under such conditions with the aim of gathering information more efficiently, we have previously proposed a legged aerial vehicle. The vehicle has tandem rotors to fly in the air and four legs to walk on the ground. The particular feature of this robot is that it has fewer actuators than the sum of those required for controlling a quadrupedal robot and a tandem-rotor helicopter individually. This paper presents modeling of the robot and development of an attitude control system that uses the leg motions. The behavior of the vehicle with the proposed attitude control is simulated using Multibody Dynamics (MBD) simulation software.

Read more…

Almost every cells in human’s body contain the same number of genes so what makes them different is which genes are expressed at any time. Measuring gene expression can be done by measuring the amount of mRNA molecules. However, it is a very expensive and time consuming task. Using computational methods can help biologists to perform gene expression measurements more efficiently by providing prediction techniques based on partial measurements. In this paper we describe how we can recover a gene expression dataset by employing Euclidean distance, Pearson correlation coefficient, Cosine similarity and Robust PCA. To do this, we can assume that the gene expression data is a matrix that has missing values. In that case the rows of the matrix are different genes and columns are different subjects. In order to find missing values, we assume that the data matrix is low rank. We then used different correlation metrics to find similar genes. In another approach, we employed RPCA method to differentiate the underlying low rank matrix from the sparse noise. We used existing implementations of state-of-the-art algorithms to compare their accuracy. We describe that RPCA approach outperforms the other approaches with reaching improvement factors beyond 4.8 in mean squared error.

Read more…

This article presents the design and realization of decoder mobile for distress beacon 406 MHz. The use of the sparse Fourier transforms in the processing of distress beacon signals. The characteristics of these decoders are mobility, able to decode all the frequencies of the beacons. It locates with great precision the location of the emitting emergency beacon, which is equipped with GPS, indicates the actual distance from which the alerts emanate. This compressed detection can give us a more detailed form of signals, so new results are given in the detection, the performance of the results is presented through experience.

Read more…

In this research work, we are implementing a student performance evaluation model using Mamdani Fuzzy Inference System (FIS) and Neuro Fuzzy system and comparing the results with classical averaging method for Network Analysis (NA) course studied by third semester Electronics and Communication Engineering students. This work explains the designing of scoring rubrics using Bloom’s levels as the criteria of assessment for NA course. Also at initial stages of learning how students’ strengths and weaknesses can be identified using rubrics and develop critical thinking skills. The five inputs identify, understand, apply, analyze and design/create are five levels of learning as per Bloom’s Taxonomy. Fuzzy rules are applied and the evaluated results are expressed in both crisp and linguistic variables and compared with classical aggregate scores.

Read more…

Combinatorial optimization problems are often NP-hard and too complex to be solved within a reasonable time frame by exact methods. Heuristic methods which do not offer a convergence guarantee could obtain some satisfactory resolution for combinatorial optimization problems. However, it is not only very time consuming for Central Processing Units (CPU) but also very difficult to obtain an optimized solution when solving large problem instances. So, parallelism can be a good technique for reducing the time complexity, as well as improving the solution quality. Nowadays Graphics Processing Units (GPUs) have evolved supporting general purpose computing. GPUs have become many core processors, multithreaded, highly parallel with high bandwidth memory and tremendous computational power due to the market demand for high definition and real time 3D graphics. Our proposed work aims to design an efficient GPU framework for parallelizing optimization heuristics by focusing on the followings: distribution of data processing efficiently between GPU and CPU, efficient memory management, efficient parallelism control. Our proposed GPU accelerated parallel models can be very efficient to parallelize heuristic methods for solving large scale combinatorial optimization problems. We have made a series of experiments with our proposed GPU framework to parallelize some heuristic methods such as simulated annealing, hill climbing, and genetic algorithm for solving combinatorial optimization problems like Graph Bisection problem, Travelling Salesman Problem (TSP). For performance evaluation, we’ve compared our experiment results with CPU based sequential solutions and all of our experimental evaluations show that parallelizing combinatorial optimization heuristics with our GPU framework provides with higher quality solutions within a reasonable time.

Read more…

This article is devoted to the issues of ensuring the security of a group of mobile robots in the implementation of attacks aimed at the property of accessibility of information and the availability of network nodes. The article presents a method for detecting an abnormal behavior of a network node based on the analysis by the group members of the parameters: residual energy and network load. Analysis of the behavior of individual robots relative to general behavior using probabilistic methods avoids the problem of creating a reference distribution for describing the behavior of a node, as well as creating a signature database for detecting anomalies. The developed method demonstrates high detection rate of denial of service attack and distributed denial of service attack with the number of malicious nodes not exceeding or slightly exceeding the number of trusted nodes. It also provides detection of the Sybil attack.

Read more…

This paper reports on an empirical study (an extension of a pilot study) that analyses the design of icons in a German 3-D virtual art gallery interface. It evaluates the extent to which a sample of typical computer users from a range of ages, educational attainments and employments can interpret the meaning of icons from the virtual interface taken ‘out of context’ and ‘in context’. The study assessed a sample of 21 icons representing the ‘action’, ‘information’ and ‘navigation’ functions of the virtual interface using a new Icon Recognition Testing method (IRT) developed by the researchers from existing usability test methods. The Icon Recognition Rate (IRR) of the icons was calculated and they were classified as ‘identifiable’, ‘mediocre’ or ‘vague’ in a novel and useful classification system. The IRT results show that the IRR of almost a quarter of the icons was below the ‘identifiable’ standard, which could seriously compromise the usability of a virtual interface. A comparison is made, using textual and thematic analysis, between the participants’ understanding of the icons’ meaning in and out of context and of the effect of positioning icons in relation to their virtual surroundings and of grouping them in tool bars. From the findings of the study, conclusions are drawn, and recommendations are made for economical icon redesign and replacement. It is suggested in the conclusions that further research is needed into how designers’ conceptual models can be better matched to users’ mental models in the design of virtual interfaces by bringing user profiles into the study.

Read more…

Facility location problem is a problem that many organizations still face today because of its increasing constraints and objectives. Decision makers want this problem solved in order to maximize profit and as such, it became a field of interest to many computer scientists over the years. The solution tool used by these scientists; a function of technological advancement, has evolved from the use of classical mathematical approaches to the use of metaheuristics. Some of the metaheuristics used include particle swarm optimization metaheuristics, genetic algorithm metaheuristics and tabu search. The problem considered in this research evolves the study of waste management in Lagos state. How the location of waste evacuation centers could be allocated in order to minimize resources such as transportation cost, facility cost, distance and the capacity of each centers. A mathematical model was developed that serves as a template for the algorithm used to solve the problem. Then particle swarm optimization metaheuristics was used to find the optimal solution in terms of capacity to the problem. Particle swarm optimization minimizes the use of memory and still gives a satisfactory solution. With the result obtained, respective agencies could make good decision as to the best location to build a new facility.

Read more…

Voice problems are routinely assessed in hospital voice clinics by speech and language therapists (SLTs) who are highly skilled in making audio-perceptual evaluations of voice quality. The evaluations are often presented numerically in the form of five-dimensional ‘GRBAS’ scores. Computerised voice quality assessment may be carried out using digital signal processing (DSP) techniques which process recorded segments of a patient’s voice to measure certain acoustic features such as periodicity, jitter and shimmer. However, these acoustic features are often not obviously related to GRBAS scores that are widely recognised and understood by clinicians. This paper investigates the use of machine learning (ML) for mapping acoustic feature measurements to more familiar GRBAS scores. The training of the ML algorithms requires accurate and reliable GRBAS assessments of a representative set of voice recordings, together with corresponding acoustic feature measurements. Such ‘reference’ GRBAS assessments were obtained in this work by engaging a number of highly trained SLTs as raters to independently score each voice recording. Clearly, the consistency of the scoring is of interest, and it is possible to measure this consistency and take it into account when computing the reference scores, thus increasing their accuracy and reliability. The properties of well known techniques for the measurement of consistency, such as intra-class correlation (ICC) and the Cohen and Fleiss Kappas, are studied and compared for the purposes of this paper. Two basic ML techniques, i.e. K-nearest neighbour regression and multiple linear regression were evaluated for producing the required GRBAS scores by computer. Both were found to produce reasonable accuracy according to a repeated cross-validation test.

Read more…

Brain tumor is the abnormal growth of cancerous cells in Brain. The development of automated methods for segmenting brain tumors remains one of the most difficult tasks in medical data processing. Accurate segmentation can improve diagnosis, such as evaluating tumor volume. However, manual segmentation in magnetic resonance data is a laborious task. The main problem to detect brain tumors is less precise to determine the area of the tumor and determine the segmentation accuracy of the tumor. The system proposed the fusion based results binding for MRI image enhancement and combination of adaptive K-means clustering and morphological operation for tumor segmentation. BRATS multimodal images of brain tumor Segmentation Benchmark dataset was used in experiment testing.

Read more…

Rescue operations require technology to assist the rescue process. The robotic technology in these missions is becoming very important. The important aspects investigated in this study are the integration of a mechatronic system that will allow for a robotic platform with a vision system.
The research collaboration between Argentina and South Africa is discussed, with the correlating research areas that each country investigated. The study permitted the development and advancement of a search and rescue system for different robots (wayfarer and drones) with different vision capabilities. A novel and innovative vision approach is presented.

Read more…

The paper presents design and implementation of a mobile robot, located in an accommodation. As opposed to other known solutions, the presented one is entirely based on standard, cheap and accessible devices and tools. An algorithm for transformation of the 2D coordinates of the robot into 3D coordinates is described. The design and implementation of the system are presented. Finally, experimental results with different devices are shown.

Read more…

Health services are under increasing pressure to reduce large waiting times for appointments. The delayed diagnosis of a human illnesses could have profound consequences for the patient. The large waiting times may be attributed to lack of data, the accuracy of the data or the timeliness of the availability of the data. In addition to this people often priorities their busy lives over their health. Other factors that affect delayed diagnosis of patients could be attributed to ill-health and the difficulty in the patient visiting the health-care practitioner, this is more evident in elderly patients that may have suffered a deterioration of their health. To overcome these obstacles eHealth systems could be put in place to facilitate the transmission of real-time and accurate data regarding a patient’s health directly to secure database that can be accessed by authorized practitioners. This paper outlines the use of eHealth (electronic health) to improve health care services which makes use of a wearable set of secure sensors and a secure database that is accessible using a web application. The proposed wearable system records and stores encrypted data which is related to the body’s physical parameters. Then, the encrypted data are transmitted using wireless technologies from the wearable device to a secure relational multi-user database using a protected protocol. The data can be accessed by the patient and professionals, such as general practitioners, using a web interface once authentication has taken place. This secure wearable architecture alleviates the problems of the lack of data, the inaccuracy of data and the timeliness of data by recording vital body parameters throughout the day and by sending real-time live data to a system that can be immediately accessed by the practitioner. The system also allows for the automatic analysis of data and presentation of the data using graphs which could aid the practitioner in determining patterns in the patients’ health statistics.

Read more…

The decision support systems regarding the Supply Chains (SCs) management services can be significantly improved if an effective viable method is utilised. This paper presents a robust simulation optimisation approach (SOA) for the design and analysis of a granularity controlled and complex system known as Consumer Supply Network (CSN) incorporating uncertain demand and capacity. Minimising the total cost of running the network, calculating optimum values of orders and optimum capacity of the inventory associated with each product family are the objectives pursued in this study. A mixed integer non-linear programming (MINLP) model was formulated, mathematically described, simulated and optimised using Genetic Algorithms (GA). Also, the influence of the problem’s attributes (e.g. product classes, consumers, various planning horizons), and controllable parameters of the search algorithm (e.g. size of the population, crossover rate, and mutation rate) as well as the mutual interaction of various dependencies on the quality of the solution was scrutinised using Taguchi method along with regression. The robustness of the proposed SOA was demonstrated by a series of representative case studies.

Read more…

Space debris removal is currently a critical issue for space development. It has been reported that five pieces of debris should be removed each year to avoid further increase in the amount of debris in orbit. One approach for the removal of multiple pieces of debris is to launch multiple satellites that can each remove one target debris from orbit. The benefit of this approach is that the target debris can be removed without orbit transition, and thus, the satellite can be developed considering simple satellite mechanics. However, to realize this concept, multiple satellites need to be launched. Another approach is to use one satellite to remove multiple pieces of space debris. This approach can reduce the launch costs and achieve efficient removal of space debris. However, the satellite must change its orbit after the removal of each debris piece, and a technique for optimizing the orbit transition is required. In this study, the latter strategy and developed a satellite trajectory optimization method for efficient space debris removal were focused on. The similarity between the problem of multiple space debris removal and the travelling serviceman problem (TSP) were considered, and the TSP solution involving an evolutionary algorithm (EA) was applied. To improve the efficiency of multiple debris removal, the total radar cross-section (RCS), which indicates the amount of space debris, and the total thrust of the satellite was minimized. The TSP solution method was extended to multiple objectives by coupling it with a satellite trajectory simulation. To evaluate the developed method, a set of 100 pieces of space debris was selected from a database. The results indicated a trade-off between the total RCS and total thrust.

Read more…

Driven by today’s market demand, semiconductor is pushing towards the zero-defect direction. The improvement demanded in semiconductor manufacturing is becoming increasingly challenging. In this paper, common molding defects comprise of voids, incomplete fills, and piping holes are studied systematically, focusing on three key areas: 1) Potential mold flow weakness; 2) Molding temperature stability; as well as 3) Defined pressure effects. The in-depth understanding of mold flow in the LF design is achieved via mold flow numerical tool. The numerical model prediction is verified by short shots and end-of-line auto vision data. Advance Process Control (APC) is adopted to measure the stability of key molding parameters like temperature, transfer profile and pressure. The mechanism of transferring the compound in relation to pressure is also analyzed and its effect to molding quality is also assessed. A methodical approach is utilized to understand the process and equipment built-in capabilities from two different equipment manufacturers. The real time transfer profile monitoring is activated for diagnosis of the system issue which leads to the finding of design error of a critical component. The dual temperature controller on one of the systems is analyzed to stabilize temperature for improved compound flow-viscosity control. The process limitations are assessed and transfer profiles are optimized to modify the melt front. By shifting the molding defects to non-critical location, the formation of void at the 500um diameter bonded wire loop peak will be avoided. The verification of potential negative impacts resulted from changes to improve voids, incomplete fills and piping holes are also included in this study. Up-front analysis by adopting numerical tool as a means of understanding the existing design and identifying improvement approach are proven to be useful.

Read more…

The frequency dependent grid impedance at the terminals of an electrical supply grid is an essential parameter for power quality and grid feedback analysis. In this contribution the identification of the grid impedance is achieved using spectral excitation currents at the corresponding grid connection point, which generate measureable changes in the grid voltage spectra. Different measurement systems based on this method have been successfully realized for the low- and medium-voltage level. A measurement system for the high-voltage level is currently being realized. The application of the measurement systems are facing quite different external framework conditions leading to specific system designs for each measurement device. The spectral grid impedance identification on these voltage levels is done through fast switching of an ohmic load with power electronic. The requirements and setup of the grid impedance measurement systems are outlined and measurement results on the low- and medium-voltage level are presented and discussed. The systems can be used to evaluate grid connection points and to verify other active or passive grid impedance identification methods on different voltage levels.Driven by today’s market demand, semiconductor is pushing towards the zero-defect direction. The improvement demanded in semiconductor manufacturing is becoming increasingly challenging. In this paper, common molding defects comprise of voids, incomplete fills, and piping holes are studied systematically, focusing on three key areas: 1) Potential mold flow weakness; 2) Molding temperature stability; as well as 3) Defined pressure effects. The in-depth understanding of mold flow in the LF design is achieved via mold flow numerical tool. The numerical model prediction is verified by short shots and end-of-line auto vision data. Advance Process Control (APC) is adopted to measure the stability of key molding parameters like temperature, transfer profile and pressure. The mechanism of transferring the compound in relation to pressure is also analyzed and its effect to molding quality is also assessed. A methodical approach is utilized to understand the process and equipment built-in capabilities from two different equipment manufacturers. The real time transfer profile monitoring is activated for diagnosis of the system issue which leads to the finding of design error of a critical component. The dual temperature controller on one of the systems is analyzed to stabilize temperature for improved compound flow-viscosity control. The process limitations are assessed and transfer profiles are optimized to modify the melt front. By shifting the molding defects to non-critical location, the formation of void at the 500um diameter bonded wire loop peak will be avoided. The verification of potential negative impacts resulted from changes to improve voids, incomplete fills and piping holes are also included in this study. Up-front analysis by adopting numerical tool as a means of understanding the existing design and identifying improvement approach are proven to be useful.

Read more…

Our work demonstrates how to use contemporary software tools on older or “legacy” robots while keeping compatibility with the original control, tools, and calibration procedures. This is done by implementing a lightweight middle-ware called MDS-Ach connected directly to the hardware communications layer of the robot’s control system. The MDS-Ach middle-ware, which relies on the x-Ach methodology, was specifically designed for Xitome Mobile Dexterous Social (MDS) Robot which was released in 2008. The MDS Robot is actively used in multiple research facilities including the United States Naval Research Laboratory. This middle-ware gives the MDS Robot the bleeding edge software capabilities of today’s robot by implementing the x-Ach real-time processes based computer control architecture. MDS-Ach controls the robot over its low level hardware communications interface (CAN-Bus). This communication controlled and implemented by a real-time daemon process. Controllers communicate with the real-time daemon via a ring buffer shared memory with network capabilities. The ring buffer shared memory is a “first-in-last-out” and is non-head-of-line blocking. All of the latter ensure non-blocking reading and writing of the latest data even while newer data is being added to the buffer. The UDP and TCP protocols can be implemented depending on reliability and timing requirements. Secure communication between networked controllers is implemented via tunneling over SSH if needed. The MDS-Ach middle-ware is designed to allow for simple and easy development with modern robotic tools while adding accessibility and usability to our non-hardware-focused partners. We present an implementation of real-time collision avoidance and a robust inverse kinematics solution within the MDS-Ach system. We include detailed examples of collision avoidance, inverse kinematics implementation, and the software architecture and tools.

Read more…

High Performance Computing (HPC) systems offer excellent metrics for speed and efficiency when using bare metal hardware, a high speed interconnects, and massively parallel applications. However, this leaves out a significant portion of scientific computational tasks, namely high throughput computing tasks that can be trivially parallelized and scientific workflows that require their own well-defined software environments. Cloud computing provides such management and implementation flexibility at the expense of a tolerable fraction of performance. We show two approaches to make HPC resources available in a dynamically reconfigurable hybrid HPC/Cloud architecture. Both can be achieved with few modifications to existing HPC/Cloud environments. The first approach, from the University of Melbourne, generates a consistent compute node operating system image with variation in the virtual hardware specification. The second approach, from the University of Freiburg, deploys a cloud-client on the HPC compute nodes, so the HPC hardware can run Cloud-Workloads using the scheduling and accounting facilities of the HPC system. Extensive use of these production systems provides evidence of the validity of either approach.

Read more…