Volume 4, Issue 4

Tactile displays are widely used in the rehabilitation and education of blind persons, as it is one of the media of communication amongst them. Tactile display performance is measured in terms of accuracy in presenting pattern, accuracy in identification, recognition and reading time of presented pattern. However, it has had meager attention from researchers. This paper presents a novel 3 x 2 solenoid actuators pin array tactile display and evaluates its effectiveness in presenting alphabets to blind and normal subjects as well as compute facilitation and discrimination value. The proposed actuator requires 75 % of the current and 90 % of the power in comparison with presently available actuators. This is achieved due to the incorporation of conical spring. Two psychological experiments were conducted to evaluate system performance, also to measure perception (reading) and key pressing sense (writing) accuracy for the first time. The low-cost developed system achieved an average reading time of about 15.7 s, recognition time of 39 s and prediction accuracy to be 93 % using a confusion matrix. The developed prototype model has resulted in 94% facilitation value and 11 % discrimination index during psychological experiments for intended users.

Read more…

This study examined the performance of two proposed permutation methods for Chow test analysis and the Milek permutation method for testing structural break in linear models. The proposed permutation methods are: (1) permute object of dependent variable and (2) permute object of the predicted dependent variable. Simulation from gamma distribution and standard normal distribution were used to evaluate the performance of the methods. Also, secondary data were used to illustrate a real-life application of the methods. The findings of the study showed that method 1(permute object of dependent variable) and Method2 (permute object of the predicted dependent variable) performed better than the traditional Chow test analysis while the Chow test analysis was found to perform better than the Milek permutation for structural break. The methods were used to test whether the introduction of Nigeria Electricity Regulatory Commission (NERC) in the year 2005 has significant impact on economic growth in Nigeria. The result revealed that all the methods were able to detect presence of structural break at break point 2005. Also, the methods were used to test for structural break at January, 2015 for monthly reported cases of appendicitis in Nigeria. Result revealed that all the methods were able to detect presence of structural break at break point January, 2015.

Read more…

The paper deals with hardware emulation of bio-inspired devices and nonlinear dynamic processes of complex nature by means of mixed-mode analog-digital emulators. The discretized state model of the emulated system serves for real-time calculation of dependent quantities. In contrast to input-output emulation known in control systems, the proposed approach emulates the ports of an electrical multiport network. The paper discusses the stability of the emulation process and the possibility of partitioning the system into two parts, one being emulated digitally and the other via an analog circuitry. The procedure is illustrated on the example of emulating the Fitzhugh-Nagumo model of neuron and the model of amoeba adaptation. The paper is an extension of our paper presented at the NGCAS 2018 conference in Valletta, Malta. The extended version deals newly with the choice of the integration method and provides a deeper stability analysis and more examples of emulation of biological models.

Read more…

Students are usually unaware of their own skills. They choose to follow the trend, rather than the proper pathway. Which negatively a_ects the professional sector, and the development of the country. Orienting students, and guiding them would o_er considerable benefits. Building the appropriate student’s profiles is the golden key for an accurate orientation. To do so, relying on the simple use of the grade point average (GPA) will not be su_cient, and mislead the guidance. Instead, studying their personality and skills has to be done, in order to provide them with their reel orientation. The presented solution aims to orient students to the most suitable career, based on a mathematical model, valid for all education systems, and takes into account the trades trends and students capabilities.

Read more…

In previous study, it is difficult to estimate the biological states such as postural ones and aetas in accordance with the previous analysis of electrogastrograms (EGGs), basically the frequency resolution of healthy individuals. In addition, few studies have compared gastric myoelectrical activity in supine and sitting posture. The aim of this study is to evaluate the severity of 3D sickness in daily life. The authors herein conduct nonlinear analysis of EGGs of the healthy young and give the feasibility to discriminate the postural differences. It is suggested that the EGGs acquired in the seated position have increased wavelength irregularity and attractor complexity than those acquired in the supine position.

Read more…

Recently, the trend of mobile communication network in Korea has been dramatically increasing the number of operating equipment for managing the explosion of wireless data traffic in 4G LTE network. This phenomenon has caused an increase in the operating cost to the mobile telecommunication service provider. Especially, the study about the reduction of the operating cost through the reduction of the power consumption in the power consumption area and the efficient operation method are under study. Through these studies, we consider the method to maintain the best service quality of mobile communication subscriber while minimizing the power consumption of LTE equipment, find out PSi & PSo algorithm that can realize this and verify it in commercial network. Applying this algorithm to a commercial network will save both power consumption and service experience of mobile subscribers to the best level, and it will be more effective in the 5G era that has already begun.

Read more…

In this paper, a frequency-tunable antenna is proposed based on a previous antenna which has a ladder shape and a size of 120 x 50 mm2. It is fed using a coaxial cable and it is operational at 700 MHz which is in the UHF band with a bandwidth of 30 MHz. Varactors, having a very low resistance value and a wide range of capacitance values, are implemented on the surface of the antenna which achieves tunability in the DTV applications band used for mobile handheld devices. By using such varactors, the electromagnetic characteristics of this antenna could be changed by changing its electrical length. Multiple cases are studied; either adding a varactor on each step of the ladder antenna or adding only one varactor in a certain well justified position. The operating frequency is swept in different ranges where all of the obtained frequencies could be used for digital TV broadcasting on mobile devices.

Read more…

This paper analyzes the process of reactive power compensation using thyristors switched capacitors TSC topology based on multiterminal switch during the starting of induction motor. The paper explains the control principle of this TSC topology which depends on the multiterminal switch. To actively track the required reactive power for the dynamic load and to perfectly transit from it from one level to other, proper control system is established. MATLAB/SIMULINK is used to develop a simulation model to prove the dynamic performance of the proposed TSC during the compensation of reactive power required for induction motor during starting.

Read more…

This paper analyzes the process of reactive power compensation using thyristors switched capacitors TSC topology based on multiterminal switch during the starting of induction motor. The paper explains the control principle of this TSC topology which depends on the multiterminal switch. To actively track the required reactive power for the dynamic load and to perfectly transit from it from one level to other, proper control system is established. MATLAB/SIMULINK is used to develop a simulation model to prove the dynamic performance of the proposed TSC during the compensation of reactive power required for induction motor during starting.

Read more…

Knowledge Based Systems play a very important role, within Healthcare, with a primary goal of supporting a high quality service at an optimal cost. A widely accepted knowledge acquisition technique is through the use of Business Rules in a natural language like format. As clinical terminology is centric to HealthCare, a large percentage of these rules use industry standard codes to describe clinical concerns. Usually there is a large number of codes to denote the various clinical processes andprocedures within Healthcare. These can translate to a combinatorially explosive number of Business Rules within the HealthCare IT system. It is common practice to leverage a Rule Engine to execute these rules and produce decisions within the system. A Rule Engine accepts a collection of rules called a ruleset. Within Healthcare Insurance, these rules and rulesets embody regulatory, policy and contractual concerns. To effectively manage this huge body of rules and rulesets, it is typical for Knowledge Based Systems to reuse rules across rulesets. Further, the knowledge required to author these rules and constructing comprehensive rulesets is specialized and requires deep expertise within the domain. Further, this also requires an expertise with authoring unambiguous business rules and operating the Rule Management Systems or Knowledge Based Systems. There is a need for the continuous Governance of these rule based knowledge assets for the organization. Typically knowledge experts in this field have a decade or more of experience. An emergent challenge or trend witnessed within the industry is that the experienced knowledge workers are retiring and their positions are being replaced by people not as experienced. This paper proposes techniques to build a layer of intelligent capabilities that can transform the methods for the automation, creation and maintenance of knowledge artifacts, that can aid and support the inexperienced knowledge workers with the effective management and administration of these assets within a Healthcare system.

Read more…

The IEEE 802.11n wireless local-area network (WLAN) has been extensively deployed around the world due to the flexibility, lower cost, and the high-speed data transmission capability at 2.4 GHz ISM band. However, in the WLAN deployment, one key challenge is to optimize the channel assignment of access-points (APs) under the small number of partially overlapping channels (POCs) to reduce radio interference, particularly for the channel bonding. In POCs, the frequency spectrums of adjacent channels are partially overlapped with one another, which will result to low throughput for concurrently communicating links using them. The accurate throughput estimation of a link is critical in the optimal WLAN deployment. Previously, we studied the throughput drop estimation model using the receiving signal strength (RSS) from the interfered link for two concurrently communicating links under POCs. In this paper, based on measurement results, we have extended this model for three concurrently communicating links. The accuracy of this model extension is verified by comparing the estimated results with the measured ones.

Read more…

Information Systems are a combination of information technology and activities of people who use these technologies to support operations, management, data, and technology. Based on Indonesian Minister of Home Affairs Decree No. 17 of 2000, the Regional Office of the Ministry of Law and Human Rights of West Sulawesi implements the Employee Management Information System (SIMPEG) which functions to process data, information and employee management. Acceptance of information system users determines whether the information system is successful or failed. Thus, this study proposes an integrated model between HOT-Fit and UTAUT2 models to identify behaviours and factors that influence system user acceptance. The online survey was conducted among SIMPEG users as many as 311 respondents consisting of 69.1% men and 30.9% women with an age group dominated by 26-35 years as many as 44.1% to test hypotheses based on an integrated model using GeSCA. The results of the study prove (1) human factors with the moderation of gender and organisation have a significant influence on behavioural intention; (2) behavioural intention has a significant influence on user satisfaction; (3) human, technology and organisational factors have a relationship of compatibility with each other. Besides, the results showed that the integrated model between HOT-Fit and UTAUT2 had GFI (0.995) and SRMR (0.079) which indicated an acceptable model fit. The results of the study support the importance of human and organizational involvement to achieve success acceptance of technology adoption in the government.

Read more…

The increasing number of breast cancer in recent years has attracted numerous researchers’ attention. Several techniques of Computer Aided Diagnosis System have been proposed as alternative solutions to diagnose breast cancer. The flaw of simply using the naked eye to see the differences between normal and with cancer mammogram images makes the texture analysis play an important role in classifying breast cancer. In this study, the results of the classification were compared using various methods of texture analysis in extracting a feature of the mammogram image. Some texture analysis methods, including first order, which consist of GLCM, GLRLM, and GLDM, have successfully extracted features based on their characteristics. The statistical features of these methods are used as input for the ECOC SVM classification, which three kernel comparisons; linear, RBF, and polynomial, build the classification. The results show that the best kernel is polynomial kernels with statistical features built by GLRLM with 93.9757% accuracy value.

Read more…

From the collection of supervised machine learning technique, an ensemble procedure is used in Random Forest. In the arena of Data mining, there is an excellent claim for machine learning techniques. Random Forest has tremendous latent of becoming a widespread technique for forthcoming classifiers as its performance has been found analogous with ensemble techniques bagging and boosting. In the present work we have proposed an algorithm, Aggrandized Random Forest to detect fraud from credit card transactions/ATM transactions with high accuracy considering both balanced and imbalanced dataset, comparatively to the defined classification algorithm Random Forest in Data mining.

Read more…

An experimental transmission between two XBee modules using Radio over Fiber technique is demonstrated. Data issued from an XBee module coded on a wireless microwave carrier at 2.44GHz is transmitted through an optical link of 25.24 km. The optical transmission is based on an external modulation scheme over a dispersive channel. Frequency response of the external modulation scheme is determined by simulation and experimentally. In particular, the chromatic dispersion of the optical fiber associated to its length allow the generation of a pass-band filter whose bandwidth is used to code the RF signal. The recovered RF signal exhibits a SNR of 27dB. Obtained results allow proposing this RoF scheme as a good contender for data transmission.

Read more…

Abstract
References (33)
Cited By (0)
Metrics
Related Articles
This study introduces the implementation of fuzzy set theory to solve machine layout design issues, in order to handle vague information, using a genetic algorithm with tournament selection as the selection operator. The material handling inputs, including frequency and volume of materials that move between machines, were the parameters regarded as fuzzy numbers. The experimental results came from 2 case studies in a manufacturing system. In the first case, examining the difference in shapes of the triangular membership functions of input data, the total distances were reduced from 38.45 m to 29.72 m, a 22.71% reduction in distance. In the second case, examining the uncertainty of fuzzy data by an expert, the total distances were reduced from 103.45 m to 82.45 m, a 20.03% reduction in distance. It was found that given the uncertainty in input data, a shorter total material handling distance might not give a lower cost. The selection operator of tournament selection can compete effectively to converge to near the optimum solution. This can, therefore, be an alternative technique in managing manufacture.

Read more…

In this paper, an optimal discrete-time sliding mode control is proposed for single-input single-output nonlinear systems with input constraints. The sliding surface is designed on the basis of particle swarm optimization algorithm in order to optimize the system response characteristics while ensuring the follow-up of reference model in presence of constraints. Moreover, the controller is developed such that the elimination of chattering phenomenon, the finite-time convergence and the stability of the closed loop system are guaranteed. Performed on an inverted pendulum system, simulation results demonstrate the e_ectiveness of the proposed approach over the discrete-time sliding mode controller using the saturation function and the discrete-time second order sliding mode controller in terms of fast response.

Read more…

This article is addressed to show the results of hybrid dynamical modeling in the form of PWA (piecewise-affine) and equivalent MLD (mixed-logical dynamical) model for multi-restricted areas avoidance of an autonomous system. It is a problem of determining the optimal moving trajectory from plant’s initial position to some desired position while avoiding some restricted areas (obstacles) between them. In order to calculate the optimal input value capable of generating the optimal trajectory, the model predictive control (MPC) approach was utilized by minimizing an objective function of state/output prediction subject to the formulated hybrid dynamical model. To illustrate the formulated model and its responses, some computational simulations were performed in a three-dimensional state using two/three box-shape restricted areas. From the simulation results, the optimal trajectory was achieved, and the plant avoided the restricted area.

Read more…

Collision risk index has been studied as the required quantitative values for decision-making of collision avoidance between ships. Recently, inference methods of the collision risk were proposed on the basis of the fuzzy theory because of being possible to collect data in real time. Existing fuzzy inference system was composed of only simulation results using virtual navigation situation. In this study, we obtained the fuzzy inference rule based on ship near-collision data via the adaptive neuro fuzzy inference system. Proposed fuzzy inference rule expressed various collision risk index in order that a ship could avoid collision with an encounter ship at appropriate distance and time. It would support for navigators to make an appropriate decision for collision avoidance with encounter ships.

Read more…

The major problem in electric utility is Electrical Theft, which is harmful to electric power suppliers and causes economic loss. Detecting and controlling electrical theft is a challenging task that involves several aspects like economic, social, regional, managerial, political, infrastructural, literacy rate, etc. Numerous methods were proposed formerly for detecting electricity theft. However, the previous works considered only the one dimensional (1-D) energy consumption data which apprehended the periodicity and were found inefficient in storing and retrieving the memory that resulted in a lower accuracy rate of detection. Hence, this research study intends Convolutional Neural Network combined with Bidirectional Long Short Term Memory based Recurrent Neural Network (CNN-RNN-BiLSTM) for overcoming the aforementioned problems in the detection of electricity theft. The CNN captures the global variables of 1-D data and identifies the non-periodicity and periodicity of 2-D electricity consumption records. RNN-BiLSTM extends the memory storage capacity of the neural network with bidirectional flow of information, thereby allowing learning order dependencies. The proposed method results of the predicted values of the electricity theft show better accuracy rate with reduced time during the training phase and reduced number of epochs. The proposed model helps to discriminate the customers for preventing fraudulent activities in the usage of electric power. The validation of the proposed method is carried out by comparing the method with the existing Support Vector Machine (SVM) and multi-class SVM models. The comparative results prove that the proposed CNN-RNN-BiLSTM model of electricity theft detection works efficiently.

Read more…

This work presents a theoretical analysis of the Signal-to-Quantization Noise Ratio (SQNR) of the nonuniform Parallel Digital Ramp Pulse Position Modulator Analog-to-Digital Converter (PDR-ADC) architecture. The PDR-ADC partitions the amplitude axis into P non-overlapping partitions that sample the analog input at input signal driven instances. Samples are generated when the input signal crosses a digital ramp in a partition. The parallel digital ramps operate from a single clock. For sinusoidal signals, it is shown, for uniform partitions the SQNR can be increased be increasing the number of bits in the counter or by increasing the number of partitions. A geometric partitioning scheme is then proposed where, again for sinusoids, it is shown that this quantization rule has the e_ect of attempting to maintain the SQNR approximately constant. For geometric partitioning, it is shown that the largest SQNR is achieved when the geometric parameter, common ratio, equals two.

Read more…

The definition of equipment and components of physical plants is a necessary step towards the development of simulation, control, and supervisory applications for the petrochemical industry. Often it happens that the same plant/equipment is (re)modeled on each application, causing a waste-oftime on repetitive (re)design, besides introducing potential inconsistencies between the models. Moreover, even though each software platform normally o_ers a di_erent view of the same plant, it is desirable to have some kind of interoperability between them. This paper presents a solution for such issues named M4PIA, which consists in a Model-Driven Engineering (MDE) tool support developed mainly for petrochemical industry automation. M4PIA allows representing industrial plants by means of di_erent and interchangeable object-oriented models, providing means to perform automatic code generation from a plant specification for di_erent software platforms. Currently, our work involves using M4PIA in high-level automation manouvers and plant simulations. Evaluations studies performed with M4PIA shows that it covers most features expected from a MDE tool suite. Besides, the use of M4PIA is expected to result in less development time and costs, while it increases e_ciency, maintainability, and reliability of the developed applications.

Read more…

The authors propose a well balanced multi-value sequence (including a binary sequence). All the sequence coe_cients (except the zero) appear almost the same in number, thus, the proposed sequence is so called the well balanced sequence. This paper experimentally describes some prominent features regarding a sequence, for instance, its period, autocorrelation, and cross-correlation. The value of the autocorrelation and cross-correlation can be explicitly given by the authors formulated theorems. In addition, to ensure the usability of the proposed multi-value sequence, the authors introduce its flexibility by making it a binary sequence. Furthermore, this paper also introduces a comparison in terms of the linear complexity and distribution of bit patterns properties with their previous works. According to the comparison results, the proposed sequence holds better properties compared to our previous sequence.

Read more…

Dysphoria is a state faced when one experienced disappointment. If it is not handled properly, dysphoria may trigger acute stress, anxiety and depression. Typically, the individual who experienced dysphoria are in-denial because dysphoria is always being associated with negative connotations such as incompetency to handle pressure, weak personality and lack of will power. To date, there is no accurate instrument to measure dysphoria except using questionnaire by psychologists, such as: Depression, Anxiety and Stress Scale (DASS) and Nepean Dysphoria Scale (NDS-24). Participants may suppress or exaggerate their answers resulting in misdiagnosis. In this work, a theoretical Dysphoria Model of Affect (DMoA) is developed for dysphoria detection. Based on the hypothesis that dysphoria is related to negative emotion, the input from brain signal is captured using electroencephalogram (EEG) device to detect negative emotions. The results from analyzing the EEG signals were compared with DASS and NDS questionnaires for correlation analysis. It is observed that the proposed DMoA approach can identify negative emotions ranging from 55% to 77% accuracy. In addition, the NDS questionnaire seems to provide better distinction for dysphoria as compared to DASS and is similar to the result yielded by DMoA in detecting dysphoria. Thus, DMoA approach can be used as an alternative for early dysphoria detection to assist early intervention in identifying the patients’ mental states. Subsequently, DMoA approach can be implemented as another possible solution for early detection of dysphoria thus providing an enhancement to the present NDS instruments providing psychologists and psychiatrists with a quantitative tool for better analysis of the patients’ state.

Read more…

Currently, one of the challenges of educational institutions is drop-out student issues. Several factors have been found and determined potentially capable to stimulate dropouts. Many researchers have been applied data mining methods to analyze, predict dropout students and also optimize finding dropout variables in advance. The main objective of this study is to find the best modeling solution in identifying dropout student predictors from 17432 student data of a private university in Jakarta. We also analyze and measure the correlation between demographic indicators and academic performance to predict student dropout using three single classifiers, K-Nearest Neighbor (KNN), Naïve Bayes (NB) and Decision Tree (DT). We found indicators such as student’s attendance, homework-grade, mid-test grade, and finals-test grade, total credit, GPA, student’s area, parent’s income, parent’s education level, gender and age as student’s dropout predictors. The results only get 64.29 (NB), 64.84% (DT), and 75.27%(KNN) while we tried to combine algorithms with Ensemble Classifier Methods using Gradient Boosting as meta-classifier and gets better about 79.12%. In addition, we also get the best accuracy of about 98.82% using this method which was tested by 10-fold cross-validation.

Read more…

This work deals with the issue of understanding a user’s behaviour as this is expressed via a gamified application. The notion of ontologies and the association of concepts in relevance to decisions that have to be made is used. The current work introduces a new process-based approach, based on collected large log files and associations of underlying decisions based on them. Both of them deal with work in extracting information for intelligent use, the main difference being that the first discovers but stops on a concept relation basis, while the other based on processes, as knowledge transactions, further to the associations on a 1:1 level maybe applied on a multi associative model. The objective of the current work is to introduce the methodology into gamified environments (such as but not limited to) games, for semi-automated understanding of user behaviour and furthermore, prediction and in instances, guidance via optimal paths of decision making activities, that are useful in gamified applications in various areas like the education. Both the initial ontology based, and the extension work on it, are based on mining association rules, in one instance treated as knowledge nodes (concepts) and in the second as underlying knowledge processes, based on big log files. This may be applicable to online games, that generate big log files of user selections, that are available for study and examination for extracting user behavioural patterns. As a result, maximum length of sequential patterns and items in them, are discovered in an algorithmic based methodological approach, providing in this way a set of guidelines for designing gamified applications.

Read more…

Braille system is purposely made for visually impaired people, to support their literal communication in order to share their knowledge. Louis Braille introduced the braille system consists of series dots which are embossed to read by touching. Early days Braille papers are made manually, but at current days braille documents are made using machines. Due to lack of perceiving on braille symbols and characters, it was highly needed fact to develop Braille system to different languages. In the Sri Lankan context, we found that the mostly inconvenience are happening inside of Sri Lankan education system. Such as in Special Education centers, Colleges, and universities. Written Braille scripts are evolution by a limited number of people who are specialized in the Sinhala braille system. Also, the process of marking braille documents are not effective and efficient. The focus of this research is to address the issue of literal communication gaps between society and the blind people in Sri Lanka. Average quality single-sided composed Braille dot characters are identified with maximum accuracy by using several novel methodologies. Obtained results denote the proposed methodologies are with the highest accuracy and system performance are more efficient as promised. The research presents executable software prototype, includes proposed methods which align with optical braille recognition in order to transpose the recognize braille characters. Introduce of new binaries cell transcription method of Braille character from a Braille document and decoding them into Sinhala characters. The proposed cost-effective system can display decoded braille characters by normalizing to Sinhala text which is in a human-understandable form.

Read more…

In this paper, we propose a new Perceptually Optimized Embedded Zero Tree Image Coder EVIC and its improved version MEVIC. The coder presents a new perceptual model to weight wavelet coefficients to enhance SPIHT embedded coding. The new visual coder aims to improve the visual quality obtained by the reference SPIHT coder for a given targeted bit rate. In addition, the paper presents three-evaluation approaches (Objective, Subjective and Quantitative) based all on a quality score PS given by the objective visual quality metric named MWVDP which is an optimized version of Daly Visible Difference Predictor VDP. It incorporates the human visual system HVS properties, correlates largely well with the mean opinion score known as MOS and provides an important feature in image coding quality assessment. The visual coders EVIC/MEVIC are fully dependent to the HVS properties, from which, they include various masking effects and visual models. Based on this model, the visual coders weight the original wavelet coefficients and reshape their spectrum to optimize the perceptual quality coding for a given observation distance and bit rate. The visual weighting model processes within all wavelet sub-bands: 1) the contrast sensitivity filter CSF to mask invisible frequencies, 2) the threshold elevation to correct the luminance and elevate the contrast, 3) the Just Detectable Distortions JND to quantize visually the wavelet coefficients according to their corresponding thresholds. The visual coder EVIC and its optimized version MEVIC have the same software complexity as their reference SPIHT. However, they perform qualitatively and quantitatively excellent results experimentation and features improvement either in image coding and quality assessing.

Read more…

Clustering is one of the well-known unsupervised learning methods that groups data into homogeneous clusters, and has been successfully used in various applications. Fuzzy C-Means(FCM) is one of the representative methods in fuzzy clustering. In FCM, however, cluster centers tend leaning to high density area because the sum of Euclidean distances in FCM forces high density clusters to make more contribution to clustering result. In this paper, proposed is an enhanced clustering method that modified the FCM objective function with additional terms, which reduce clustering errors due to density difference among clusters. Introduced are two terms, one of which keeps the cluster centers as far away as possible and the other makes cluster centers to be located in high density regions. The proposed method converges more to real centers than FCM, which can be verified with experimental results.

Read more…

This paper describes an architectural approach to the development of dynamic service-oriented systems for e-Health using the service orchestration mechanism and semantic technologies. The main idea is the dynamic synthesis of the complex functionality required by user or by software agent. This idea should help to build and easily extend the applied loose-coupled systems without strict dependencies on concrete web services and their invocation details. A sample scenario of such dynamic orchestration is covered and analyzed, possible ways of further improvement of this approach are given.

Read more…

In this study, we develop the author’s approach, based on the principles of modeling of the International Flows Equilibrium Exchange Rate (IFEER). As a result, a new model is built, depending on the main macroeconomic factors in the medium term. The model presents a wide system of basic factors, but many of the intermediate factors in the modeling were eliminated. The results are discussed in the context of the previously known results of economic theory.

Read more…

With the advancement in the field of Internet-of-Things (IoT), event monitoring applications have rapidly evolved from a simple event data acquisition towards predictive event analytics involving multi-sensory data aggregation in a distributed environment. Existing event monitoring schemes are mainly relying on ine_cient centralized processing mechanism, which may lead to the common single-point of failure for the entire system. In addition, there is no proper method for verifying the event data generated by the monitoring system. In this paper, we present a distributed event monitoring scheme using a Hierarchical Graph Neuron (HGN) distributed pattern recognition algorithm. HGN is a single-cycle learning graph-based recognition scheme that is modelled for in-network deployment. In this work, event data retrieved from multi-sensory IoT devices within a distributed event monitoring network is converted into pattern. To address the event data verification problem, we integrate our proposed scheme with blockchain technology. Combining this IoT event monitoring capabilities with blockchain-based data storage and verification could leads towards a scalable event detection and monitoring model for large-scale network. The results obtained from our simulation shows that the proposed scheme o_ers high event detection accuracy and capable of minimizing the event storage requirements on blockchain network.

Read more…

Popularity and a_ordability of smart phones and other data hungry devices add exponentially to the tra_c demand of existing cellular networks. Cell densification and small cell deployment over existing macrocell has been identified as an e_ective solution to high tra_c demand predicted for future wireless networks like 5G. Small cells are deployed over existing macrocells in a Heterogeneous network to o_oad tra_c, ensure balanced load and good quality of service in the network. To achieve the purpose of HetNet, small cells are deployed in locations of high user concentration. Operators are required to be able to identify these locations for optimum small cell deployment. Presently, this decision is based on long term tra_c data which create latency in small cell deployment especially in areas of unexpected hotspots. The work presented in this paper is a new strategy that can practically help operators to promptly identify locations for small cell deployment based on user cluster. This strategy involves a monitoring system that can be easily incorporated in a mobile cellular network base transceiver station (BTS) to monitor the coverage area and periodically identify positions for prompt and optimum small-cell deployment in HetNets. The monitoring system is a two element array system that uses RSS data to resolve DoA, range, user cluster and identify positions for small cell deployment. At any point in time, the network operator can visualize cluster locations relative to the base station and is able to identify hotspots. When small cells like micro-, pico-, or femto-cells are promptly deployed in areas of higher user concentration, high data rates and good quality of service in the network are maintained at all times. The network coverage area is divided into a series of azimuthal and range sectors, and users are located into the sectors where they belong. The strategy was simulated in MATLAB environment for WiFi networks with thirty users and results indicate 100% accurate DoA estimation and MAE in range estimation of 6m for a known environment. Optimum positions for small cell deployment based on user clusters were correctly determined. Simulation was validated with experiment and result indicate close relationship between experiment and simulation with MAE di_erence in range estimation of 1m.

Read more…

Vehicles are rollover when steering at high speed, this phenomenon is limited by increasing the anti-roll moment of the suspension system. This research focuses on analyzing and establishing the dynamic model of vehicle when steering and describes the dependence of the vehicle body’s roll angle on other factors. Research has shown that when equipped a stabilizer bar it will significantly reduce the roll angle of the vehicle body. Besides, this research shows the outstanding advantages of active stabilizer bar with other stabilizer bars. Therefore, most of the vehicle should be equipped active stabilizer bar to ensure stability and safety when moving.

Read more…

Water distribution networks are infrastructural systems designed for providing potable water to consumers. In these last decades, the importance of assessing and identifying emerging leakages has become a primary issue, because of the high level of water loss characterizing such systems worldwide. In this paper, a new approach aimed at the prompt localization of leakages occurring in water distribution systems is introduced. The methodology relies on the analysis of real-time pressure measurements and on Complex Networks Theory. Starting from a collection of nodes representing the locations of pressure sensors, links of a virtual, complex network are created on the basis of the values assumed by correlation coefficients between pressure measurements: if such values are above a given threshold, relevant nodes are considered to be connected to each other. In this way, information about the structure and topology of the complex network is easily derived. In particular, the degree centrality of the nodes is a key parameter allowing to identify the position of a leakage. The paper first analyzes a well-known literature example, and then proves the high reliability of the methodology for a real water distribution system.

Read more…

The Malaysian government has recently announced to increase the share of renewable energy generation from 2% to 20% of the total electricity consumption by year 2030. However, integrating a significant level of renewable energy sources on the distribution network without proper coordination will cause adverse effects that leads to unnecessary operation costs to the stakeholders. Various solutions including energy storage system are proven to be an effective way to overcome the issues caused by the integration of renewable energy sources. However, energy storage system using batteries have limitations such as limited life cycle and environmental hazards. As such, alternative source such as fuel cell which is well known for its zero pollutant can be considered. In this paper, a distributed static synchronous compensator integrated with a hydrogen system (DSTATCOM-Fuel cell) is proposed. The hydrogen system consists of fuel cell and electrolyzer to perform power exchange within the grid for regulating the voltage magnitude at 1 p.u. Various case studies have been conducted to validate the efficacy of this proposed combination and the results have shown that the DSTATCOM-Fuel cell can effectively mitigates the voltage rise up to 12.3% while maintaining high penetration of the photovoltaic systems.

Read more…

To be able to perform a better voting system, it is important to go to ICT and its various platforms designed for electoral purposes, which are being used in several countries in Latin America. In Ecuador are being used digital mechanisms during the process, but with certain errors and he is being considered to implement electronic voting, although it remains a project. The objective of this study is to analyze the prototype of a security architecture for a system of electronic voting for the Ecuador. In this study applied a quantitative, deductive, non-experimental descriptive criteria allowing to analyze the documents of reference. It was observed that the laws governing the franchise in the country have been well designed to provide facilities to the greatest number of voters, whether people with certain physical disabilities or with deprivation of liberty; In addition gives to know how to vote and the rapid counting system. It is concluded that architecture deserves a protocol that protects information throughout the electoral process and also the use of cryptographic algorithms with special software, that allows to work quickly and provide security properties, integrity and authenticity.

Read more…

To be able to perform a better voting system, it is important to go to ICT and its various platforms designed for electoral purposes, which are being used in several countries in Latin America. In Ecuador are being used digital mechanisms during the process, but with certain errors and he is being considered to implement electronic voting, although it remains a project. The objective of this study is to analyze the prototype of a security architecture for a system of electronic voting for the Ecuador. In this study applied a quantitative, deductive, non-experimental descriptive criteria allowing to analyze the documents of reference. It was observed that the laws governing the franchise in the country have been well designed to provide facilities to the greatest number of voters, whether people with certain physical disabilities or with deprivation of liberty; In addition gives to know how to vote and the rapid counting system. It is concluded that architecture deserves a protocol that protects information throughout the electoral process and also the use of cryptographic algorithms with special software, that allows to work quickly and provide security properties, integrity and authenticity.

Read more…

This study involved three departments of teachers and students. The concept of the flow-motivated exercise implemented with a set of flow nozzles. A computer-controlled airflow with specific music introduced, and the motion responses from the participants were analyzed during the initial test and field study. During the initial examination, we adjusted the magnitude and distance setting of the flow and allowed the children to grab the air without music. Structural design, magnetic valve, and interface were implemented based on the insights from the initial test. The redesign performed in a sitting position to reduce the need for students to deviate from the location and fit for physical disabilities during exercise. Four times of visually impaired students were arranged to observe the changes in the movements of students after being guided by the airflow during the teaching process. The performance of the fourth week is better than the previous three weeks. Almost all blind children can make movements in the right position. The cross-domain cooperation experience was beneficial to the facility design.

Read more…

This study reviewed articles on information technology governance (ITG) in the Malaysian context and categorized the issues found in ITG implementation according to organizational-related and human-related issues. It further analysed the impact and role of information technology (IT) human capability in ITG implementation in developing countries like Malaysia, which is still in the infancy stage of ITG. This study found that most organizations in Malaysia are not only facing organizational-related issues but also human-related issues as well. However, there are insufficient studies on how implementation issues between organization and humans are interrelated. The roles of IT human capability in ITG implementation has been heavily underrated as most studies focused on ITG mechanisms and the impact of ITG on firm performance. Issues highlighted in past studies were summarized and used to explain the roles of IT human capability in ITG implementation. The findings revealed that the number of issues reported in the human-related category was slightly more than organizational-related issues. This study explains the role of IT human capability in ITG and reduces the ambiguity of IT human capability in ITG for future research activities.

Read more…

There is no doubt that a good knowledge of traffic demand has a direct impact on improving traffic management. Road traffic is strongly correlated with many factors such as day of week, time of day, season and holidays which make it suitable for prediction. In this paper, we develop a neural network model for hourly traffic prediction that makes full use of these temporal characteristics. The proposed algorithm is tested on a real-world case, and the experiment results is presented to evaluate its accuracy.

Read more…

The current industrial landscape is becoming increasingly aware of the need to optimize energy use and management for all domains, including telecommunications. Among others, RF Energy Harvesting is a promising technique for 5G systems as an alternative to traditional energy supply sources. This paper presents 5G landscape and ecosystem. It positions RF-Energy Harvesting in 5G context and reviews its techniques. It also considers constraints and research trends for different aspects needed to make RF energy harvesting ready for deployment along with 5G enabling technologies.

Read more…

eSign is an online electronic signature service which is recently gaining more prominence in India. eSign is based on two online services from UIDAI, viz. a viz., Aadhaar based authentication and retrieval of resident’s eKYC information after taking his/her consent. With increased adoption of Aadhaar based services, privacy of user data has become more and more important. Present method of taking boolean consent from resident through non-UIDAI entity may not be acceptable for two main reasons, first is that the consent does not include in itself a proof from resident that the consent is indeed taken from him/her and second is that the resident may wish to have better privacy and fine grained access control rules to access his/her eKYC data. Bakshi et.el have introduced a mechanism to improve amortized performance of eSign using a digital access token. In this work, the digital access token is enhanced to include Privacy Enhancing and Fine- Grained Access Control (PEaFGAC) Statements for facilitating Privacy Aware eSign. These tokens can be used by other entities to access eKYC data of the resident with better access controls enforced by the resident. This paper briefly describes the present model of eSign, the earlier proposed model of eSign followed by the proposed model of Privacy Aware eSign. The proposed model of Privacy Aware eSign is also analyzed using BAN logic assuming Dolev-Yao security environment.

Read more…

Recently, augmented reality (AR) technology has been applied to the inter- action technology between human and virtual objects. In AR interaction technology, it is necessary for users to be able to manipulate virtual objects intuitively. Thus, we focus on manipulating virtual objects directly with the user’s bare hands in this study. On the other hand, in AR technology, since the 3-dimensional (3D) model is superimposed on the image of the real space afterwards, it is always displayed on the front side than the user’s hand (occlusion problem). Thus, it becomes an unnatural scene in some cases. In this study, this system detects hand area of the user by extracting depth information, color information and using canny edge detection in the user’s hand. Thus, this system performs hidden surface removal along the area of the user’s hand by considering the object-context relations between the user’s hand and the virtual object. In the evaluation experiment, it is confirmed that the hidden surface removal in this study make it possible to distinguish between finger boundaries and to clarify and process finger contours. This work is an extension of the paper entitled “Hidden Surface Processing for Interaction of Hand and Virtual Objects Using Leap Motion Controller” published in 2018 International Conference on Informationand Communication Technology Robotics (ICT-ROBOT).

Read more…

Peer-to-peer (P2P) energy trading is a mechanism that allows people to share locally the energy they have generated from distributed renewable resources (DER), to generate profit form the unused resources and to reduce the cost for electricity for the household and in the community itself. This calls for the design of new energy markets, accompanied with the development of comprehensive exchange strategies, which reflect both the consumer?s preferences and the heterogeneity of the renewable sources. The paper presents a study of the behavior patterns of individual prosumers using bidding strategies based on the State-of-Charge of the battery and two different pricing algorithm, one with fixed prices and one based on the battery price of each standalone system as well as the effect such patterns have on a local energy market with solar panels, fuels cells and batteries. The evaluation is achieved by the use of a prototype based on the Open Energy Systems (OES), a community in Okinawa, Japan, made of 19 interconnected houses with residential storage, photovoltaic cells and AC grid connection. In order to simulate heterogeneity, a fuel cell, modeled after Ene-Farm, is added to the original configuration. Each house has a power flow management system, which uses a priority-based algorithm to maintain demand-response efficiency, capable of scheduling the operating hours of the available fuels cells. The energy market is based on Zaraba, a continuous double auction algorithm used by the Japanese Stock Exchange, in which prosumer can bid for a desired amount and price of electricity for a 30-minutes time slot in the future The preliminary numerical evaluation is based on the results from several simulations using different versions of the bidding agent.

Read more…

Although social media is used by an ever-increasing number of businesses, its benefits have not yet been fully exploited. Social media analytics tools can prove helpful in this regard, since they comprise a unique information source for business intelligence. As the social media environment rapidly evolves, various social media analytics tools are emerging. This research examines the usefulness of social media analytics tools for assessing corporate websites and Facebook pages. Two social media analytics tools, Website Grader and LikeAlyzer, are selected to evaluate the wine industry in Greece and Germany. A comparative study of the two countries is subsequently presented. The paper suggests that researchers and practitioners can easily use these analytics tools to acquire valuable quantitative data for a fast, effective and efficient assessment of corporate websites and Facebook pages and thus improve their social media usage. The results show that the two countries present similarities, but there is great potential for improvement in their use of social media.

Read more…

Recently, communication demands often change because of the various network services in companies and individuals. Software Defined Networking (SDN) has emerged as a viable control paradigm that allows flexible communication, using OpenFlow as its default standard and enabler. However, when changes happen frequently in SDN networks due to unforeseen reasons -such as a network failure or topology changes- it takes a long time to perform all the operations. For instance, to change a routing path, first new paths must be calculated, then the controller must transmit the commands to the network elements, which has to process those commands. This process can cause a delay, or even disruption, in the communication service. Therefore, this paper proposes a network control method to reduce the time to change a path using OpenFlow.

Read more…

In recent years, research has been taking an important role in Peru. There are different sources of funding for research projects, research internships, the publication of scientific articles, scholarships for postgraduate studies, among others. This importance of research has resulted in an interest in being able to measure and compare universities according to their scientific production. One of the main factors to be used to make these comparisons is the number of articles published and indexed in SCOPUS. However, this measure is not entirely fair, since it is not equitable to compare a large university with a small university since large universities have more human resources to publish scientific articles. Seeing this reality, in the present work, we present a comparison of scientific production in Peruvian universities, taking into account the size of the institutions. Among the results obtained, we can observe a change in the ranking of small universities that invest heavily in research.

Read more…

The increase of elderly population creates the need to promote healthy aging, with autonomy and independence, for preserving the functional capacity and quality of life as much as possible. To achieve this goal the recommendations include walking a certain amount of steps daily, given that the exact amount of steps changes with age, lesions, and chronic health conditions that can affect health and well-being.
Understanding how much exercise is adequate for an individual requires spe- cialized knowledge and training. It is important to avoid risks that include: (1) be too aggressive in exercising and increase injuries, create new ones, and later refrain in exercising more; or (2) be too conservative and in the long run have an activity level under each one’s potential and below what is recommended. In this article is proposed and discussed a framework that aims to support peo- ple having an adequate level of activity for its particular condition and to do it without disrupting daily routines. The framework is supported by a software system built for monitoring well-being and physical activity in the context of Smart Cities. The system is composed by: (1) smartphone applications that interact with the end-user for showing possible exercises and walk routes, and that collects some relevant data; (2) a back-office application that collects and presents data obtained from the smartphone applications. The back-office application is designed for health professionals to follow users’ progression over time, to recommend new exercises or to correct less optimal situations. The first tests with a system implementing this framework show that the solution is robust and able to be used in a large scale.

Read more…

Neurological signals are generally very weak in amplitude and strongly noisy. As a result, one of the major challenges in neuroscience is to be able to eliminate noise and thus exploit the maximum amount of information contained in neurological signals (EEG…). In this paper, we aimed at studying the N400 wave of the Event-Related Potentials (ERPs) that may reflect the effects of vowelling and semantic priming in Arabic language. To improve the quality of the recorded ERP signals, we considered a nonlinear filtering method based on 10th order Daubechies discrete wavelet transform combined to principal component analysis (PCA). Among all tested wavelets, the Daubechies one showed high values of the used signal processing metrics. Thus, it allowed a significant enhancement of the signal to noise ratio while using only 10 ERP trials. In addition, we confirm its effectiveness while comparing the filtered outputs to those obtained using the averaging technique implemented in the conventional EEGLab toolbox. In a second step, the Mexican Hat function was used to achieve continuous wavelet analysis of the filtered signals. This time-scale analysis method permitted to get an alternative representation of the ERPs and to detect the N400 wave with significantly greater accuracy.

Read more…

FM broadcast stations generate reverse intermodulation signals that cause communication problems between ATC controllers and pilots in the Air Traffic Control systems (ATC) in Thailand. In this paper proposes a balanced RF power amplifier using the improvement
3-dB quadrature hybrid couplers to reduce the reverse intermodulation of FM broadcasting systems. The mathematics analysis of the balanced RF power amplifier for two closely located FM stations shows that can reduce the reverse intermodulation products. A reverse signal from nearby FM stations travels into two amplifiers of a balanced amplifier that create intermodulation signals. The quadrature hybrid coupler in a balanced RF amplifier to provide intermodulation signals of two amplifiers have a 180? out-of-phase which cause reducing intermodulation signals. In this paper designs 3-dB quadrature hybrid couplers for a proposed RF balanced amplifier. The low-cost PCBs are used to make prototype couplers. The proposed couplers are provided experimental results of return losses that are lower than -15 dB. The directed port has a coupling coefficient -3.3 dB and the coupled port has a coupling coefficient -3.4 dB. The prototype couplers are applied to a balanced amplifier that obtains a maximum output power 210 watts with 17.20 dB gain. A proposed balanced RF amplifier is measured the reverse intermodulation products of with a situation of two closely located FM broadcast stations to compare with a single-stage class-C amplifier. The experimentation demonstrates of the transmitter using a balanced RF power amplifier that can reduce an intermodulation product 18.47 dBc.

Read more…

The entire electrical system is changing at an abrupt speed since its beginning. With the rapid advance of renewable energies (which are constantly subject to fluctuations), the electricity generation is distributed to countless locations. The traditional model of the unidirectional flow of electricity is leaning towards multidirectional flows. This situation needs significant changes in the transport infrastructure of the electrical power system and mode of operation. Technological advancements are making a smarter and more organized management system of electricity supply and demand. This development needs to incorporate modern communication, monitoring, and control capabilities, along with the intelligent transport, generation, and storage value chain. Digital substations integrate thousands of sensors by providing greater comfort, self-reliance, availability, and safety while at the same time reducing costs, risks, and environmental damage. Conventional power system lacks digital communication, remote monitoring & control, and consumer participation. Fiber-optic cabling in digital substations will attain not only real-time data transmission but also remote maintenance. The comparison between conventional and digital substations has also been presented in this work along with latest trends in smart protection. Electronic protection and control devices based on a microprocessor, communicating with cloud servers, will enhance the flexibility to control and monitor the digital substations. A significant amount of data generated by components in the electrical substations will allow greater sophistication of the monitoring, diagnostic, protection and optimization capabilities of the facilities. The goal for the review of said advancements is to have a smart electrical system with greater efficiency and better user experience.

Read more…

This paper proposes Halbach array PM linear generators for direct conversion of ocean or sea wave energy. This generator is proposed to be directly coupled to a reciprocating wave energy system which may be a valued alternative for pneumatic and hydraulic systems. In this research, air-cored permanent magnet PM linear generator has been optimally designed according to optimal cost and performance indices. The design depends on Halbach array PM arrangement. The design this linear generator is appropriate for direct extraction of energy from sea waves specially at small wave amplitude. The finite element method and the space harmonic analysis are used to develop the electromagnetic design of this topology. In this article, the concept of the extraction of maximum permissible power from sea waves is established according to the direct wave energy converters hydrodynamics model. The dynamic analysis of the Halbach array linear generator is investigated during the state of maximum power extraction.

Read more…

Recommender Systems (RSs) are termed as web-based applications that make use of filtering methods and several machine learning algorithms to suggest relevant user objects. It can be said that some techniques are usually adopted or trained to develop these systems that generate lists of suitable recommendations. Conventionally, RS uses a single rating approach to preference user recommendation over an item. Recently, multi-criteria technique has been identified as a new approach of recommending user items based on several attributes or features of user items. This new technique of item recommendation has been adopted to solve several recommendation problems compared to the single rating approach. Furthermore, the predictive performance of the multi-criteria technique when tested proves to be further efficient as compared to the traditional single ratings approach. This paper gives a comparative study between two models that are based on the features and architecture of fuzzy sets system and adaptive genetic algorithm. Genetic Algorithms (GAs) are robust and stochastic search techniques centered on natural selection and evaluation that are often applied when encountering optimization problems. Fuzzy logic (FL) on the other hand, is known for its wide application in diverse fields in science. This study aims to evaluate, analyze, and compare the predictive performance of both methods and present their results. The study has been accomplished using Yahoo! Movies dataset, and the results of the performance of each model have been presented in this paper. The results proved that both techniques have significantly enhanced the system’s accuracy.

Read more…

Traditionally bathymetry survey is generally carried out using boat, research vessel, and small craft which is equipped with the echo sounding instrument and involves many persons as the vessel crew. The survey method demands an additional cost because of the extra man power and an expensive vessel operational cost. An autonomous surface vehicle (ASV) which is equipped with echo sounder was developed by adopting small water-plane area twin hull (SWATH) hull form to support bathymetry survey in the coastal environment. The paper is focused on the design of hull and control system of the SWATH-ASV, electronic device and sensor selection for control of the vehicle. The hull and control system is designed to organize the surface vehicle to perform the defined mission from ground control station. The hull form geometry, hardware and software of the SWATH-ASV and the control system are presented.

Read more…

To reduce its high last mile logistics cost, a company may explore different options such as a horizontal collaboration with another company that has a similar logistics requirement. Traditionally, the collaboration can be conducted through an outsource contract mechanism where the company may need to guarantee a certain number of logistics demands or usage for a fixed period of time. This may incur a fixed transportation and logistics cost for the company. For a company who has more fluctuated logistics demands, it would be difficult to guarantee a certain number of logistics demands or usage for an outsourcing mechanism. The company may end up paying more than it should. Alternatively, the company may want to explore horizontal collaboration with a more flexible contract mechanism such as the “4th party milk run” (4PMR). The 4PMR model leverages on the last mile excess capacity of one company to fulfill the last mile logistics demands for another company based on a pay-per-use arrangement. Using the 4PMR model, the fixed transportation and logistics cost would be translated into a marginal cost. This paper describes the 4PMR model, including the optimization model and its computation experiment on two last mile logistics scenarios. The first scenario is a hypothetical scenario based on our field study in Jakarta, Indonesia with a small number of deliveries, while the second scenario is an actual scenario with a large number of deliveries based on existing routes of a Logistics Service Provider (LSP) in Surabaya, Indonesia. The experiment results show that 4PMR is able to provide a significant reduction in last mile logistics cost. To complement the experiment results, industry perspectives for implementing the 4PMR model is also reviewed.

Read more…

While the Kalman filter, including its many variants, has been the staple of the tracking community, it also has been shown to have drawbacks, particularly when tracking through a maneuver. The most common issue is a lag in the position of the target track compared to the true target position as the target performs its maneuver. Another more problematic issue can occur where the filter covariance collapses, requiring the filter to be reinitialized. Techniques exist to compensate for maneuvers, but generating their response relies on detection of error between the estimated trajectory and the measured target position. In this effort, a maneuver detection routine is developed that can be used in conjunction with more standard maneuver compensation approaches. This routine is able to validate the existence of a maneuver more quickly than use of the inherent detection relied upon in the other methods. Maneuver detection is performed by an evidence accrual system that uses a fuzzy Kalman filter to incorporate new information and provide a level of evidence that maneuver is occurring. The input data uses behavior characteristics of the Kalman gain vector from the tracking algorithm.

Read more…

Nowadays, the realization and follow-up of a team activity takes place in different execution environments (e.g. mobile phone, PC) through the use of computer applications. This implies context changes that generate interruptions in the activity. To improve the continuity of an activity with the reduction of interruptions during the development of this activity, would help to finish a task in a shorter time. An example of interruption occurs when a user initiates an activity on a device and decides to continue working on it on a different device, thus facing additional steps that must be performed to obtain the updated information on the desired device. The interruptions can be found in several domains as in the previous example that refers to the work developed through multi-devices or collaborative systems (CS). In this article we present a proposal for a model that incorporates the continuity attribute in the CS development process, to support its users to carry out Collaborative Activities (CA) through different devices with the least possible number of interruptions, so that that way the user does not require additional steps that extend the time of the task and negatively affect the process of transferring his CA to another device.

Read more…

High gain-bandwidth product and visible/UV contrast photodetectors are vital in Visible Light Communication (VLC) and Ultraviolet (UV) reflectance imaging applications respectively. We adopt material and structural optimization to perceive such photodetectors with back-illuminated Optical Field Effect Transistor (OPFET) wherein any potential difference in absorption coefficient of the semiconductor material between the visible and the UV range (higher in the UV region) can be explored at its full potential. The results have been analyzed using the photoconductive and the photovoltaic effects, the series resistance effects, scaling rules- induced effects, and channel length-variation effects. We consider the three most prominent and functional materials in the visible range (Si, GaAs, and InP) for material-based optimization. Structural optimization is performed employing a range of medium gate lengths. The gate electrodes utilized are Indium-Tin-Oxide (ITO) for Si and GaAs with high Schottky barrier heights of ~0.71 eV and ~0.98 eV respectively whereas the Schottky contact on InP is gold (Au) with a high barrier height of ~0.8 eV. The operating visible and UV wavelengths are 600 nm and 350 nm respectively. The results suggest that GaAs OPFET has wide bandwidth potential in the gigahertz range apart from its high sensitivity and visible/UV contrast features. The InP-based OPFET exhibits high sensitivity and sub-gigahertz frequency response; and can compete or surpass the GaAs OPFET in terms of the visible/UV contrast ratio. The Si OPFET shows bandwidth in the megahertz range along with high sensitivity but exhibits low contrast ratio. The structural parameters have a significant effect on the detector response. The results are in-line with the experiments. This paper reflects the performance of the investigated detectors towards the said applications through optimization and the associated analysis represents the dependence of the obtained response on the device material and structural parameters, thus, opening the door for further research.

Read more…

The purpose of this study was to investigate the impact of the implementation of the Online Appointment Scheduling system and Pharm Partner system technologies on the quality of working life for users in a small healthcare environment at the University of Technology, Jamaica. Both qualitative and quantitative methods were employed. Two data collection instruments were: interviews and survey forms. The sample included Health Clinic and Pharmacy staff and users of these facilities. The investigation covered a one (1) year period. The Statistical Package for the Social Sciences software version 24.0 and NVivo software were used for data entry and analysis of the surveys and interviews respectively. Findings supported that the systems improved users’ quality of working life. Reduced waiting time for patients to access doctors and receive their prescription from both facilities. Pharmacists were able to dispense drugs to patients at a faster rate. Most manual functions at both facilities were automated: the retrieval of patient’s appointment scheduled information at health clinic and the retrieval of patient’s records at the pharmacy. Pharmacy inventory system was automated, patients at the health clinic were able to go online and see doctors available for appointments.

Read more…

An artificial neural network (ANN) computing system can be significantly influenced by its implementation type. The software implemented ANN can produce high accuracy output with slow computation time performance compared to hardware implemented ANN which runs at a faster computation time but with low accuracy. Normally, software implementation reduces the proficiency and efficiency of the model. Robot performance plays an important role as it needs fast response to process information that is applied with ANN. As a consequence, the proposed research focuses on comparison between hardware and software implementation multilayer perceptron (MLP) for cart follower in Field Programmable Logic Array (FPGA). Both of the software and hardware models produced the same precision where the output distance at angles -10°, 0° and 10° shows same percentage error. Besides that, both of the models have similar root mean square error (RMSE) which are 0.469, 0.479 and 0.267 at -10°, 0° and 10° respectively. The processing time of MLP model implemented in hardware and software are at 1.91?s and 78.06?s respectively. Thus, it can be concluded that hardware implementation is better than software implementation.

Read more…

In this work, kaolin powder was filled in PP/LDPE blend as the filler with the amount from 0 to 14 wt%. The ratio of PP/LDPE was fixed as 50/50 in all the experiments. The tensile strength, impact strength, and hardness were investigated in according with ASTM. The results showed that the tensile strength of PP/LDPE blend was slightly increased, the hardness was also increased while the impact strength was decreased in the presence of kaolin powder as the filler from 0 to 14 wt.%.

Read more…

The integrating model becomes one of key trends in engineering design. The more the product has functional specifications, the more the industrial consumer apply in many fields. In this paper, a fusion design of architecture platform for autonomous system is demonstrated. It is greater due to combining the specifications of various types in commercial market such as driving structure, multi-functional model or autonomous level. Therefore, plentiful advantages of systems are converged into one platform. From customer’s requirements, the system parameters and specifications are offered to consult during the process of design. To compare with previous works, the enhancement of tractor-trailer, lifting-carrier and auto-feeder using differential driving mechanism is merged successfully. The detailed design of prototype involves the development of hardware components and infrastructure. Later, the modeling of autonomous system is simulated on computer to meet the employed conditions. The force analyzing scheme helps to predict the working ability to complete their mission. To verify the proposed design, an experimental version of this system is tested in different cases. In mode of lifting carrier, the vehicle and cargo that become a rigid body, follow the reference trajectory in practical map. In another circumstance, vehicle plays a role as leader which take along with cargo, as follower. From these results, it can be seen that the proposed design is feasible, effective and capable in real world. In future works, a fleet of autonomous vehicles mixing multi-modes in the same map should be considered.

Read more…

Metals of lead and some lead alloys, lead oxide, nickel and cobalt were recovered from exhausted battery by combined hydrometallurgy and pyro metallurgical method. The spent batteries were dismantled and leached in hot 2M and 5M nitric acid. The unleached fraction was heated with sodium carbonate to produce lead oxide. Salts in the leached solution were analyzed by Inductively Coupled Plasma ICP. Lead was precipitated as hydroxide on cold with ammonia. Nickel and cobalt metals in solution were extracted by solvent extraction using LEWATIT MP 600 ion exchange resin. Metals loaded by the organic phase were stripped by HCl. Metals hydroxides were reduced with ascorbic acid or hydrazine hydrate to ultrafine free metals, Lead alloys were prepared by encapsulating the alloying metal oxide or organic salts in the host lead metal and heated at 800 °C. The end products were investigated with Energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), X-ray fluorescence (XRF), Inductively Coupled Plasma (ICP), and Scanning Electron Microscope (SEM). Results revealed that the spent grids contain 94.2 % lead, aluminium 0.12% nickel 0.05 % and cobalt 0.053 %. The particle size of the reduced metals was found in range of 15-60 um, LEWATIT MP 600 ion exchange resin is specific adsorbent for nickel and cobalt. Distribution constant Kd value of the stripping step decreased in the order Ni and Co. Lead-Al-Mg alloy was prepared by heat treatment of terminal taps at 500 °C. The obtained lead alloys were investigated with EDX and SEM. The extent of recovery of lead metal and lead calcium aluminum alloy amount to 94.3% and 96.4% with high purity. Lead -calcium alloy was homogeneous and contain calcium particles with 5 ums.

Read more…

Modern universities aim at carrying capacity human resources component in its tri dharma (Three Pillars of Higher Education). UPI with sufficient conditions in the management of several resources has undoubtedly tried to establish itself as a modern university. The superior human resource support in every competition and the university’s tri dharma is the primary resource of UPI. The results of all HR roles have become inputs for the management of digital data and information. Therefore, communication management containing the university’s strategic policies can be effectively and promptly translated as well as implemented by human resources. To conduct dissemination and sustainability both nationally and internationally, this research formulated three main components in managing policy communication on human resources in a modern university, which include: (a) architecture vision, (b) value change; (c) flow diagrams, all of which refer to the achievement of vision and mission.

Read more…

The problem of recognizing traffic sign boards in a correct fashion is one of the major challenges since there is an alarming rate of increase in the number of road accidents happening because of incorrect interpretation of traffic sign boards in bad weather conditions. In this paper, a comparative analysis of various noise removal techniques based on calculating different parameters which decide the quality of input roadway symbol like Mean Squared Error (MSE), Peak Signal to Noise Ratio (PSNR) as well as Structural Similarity for measuring Image Quality (SSIM) is being performed and the best technique will be chosen among them which gives minimum Mean Squared Error (MSE) value and maximum Peak Signal to Noise Ratio (PSNR) and Structural Similarity for measuring the Image Quality (SSIM) values. This technique will be quite useful for de-noising a given image which is present in both the testing and the training image databases.

Read more…

Spatial and temporal isolation is a crucial issue in embedded systems executing multiple tasks with several levels of criticality. This is considerably significant in the context of multi-processor (or multi-core) embedded systems running multiple mixed-criticality applications in parallel. This work deals with the issue of isolation of different application classes on Network on Chip (NoC) architectures and proposes a lightweight hardware mechanism able to support mixed-criticality requirements and specifically designed to be introduced into existing network interfaces. This mechanism supports the execution of different and contemporary applications with several criticality levels by supervising the messages exchange among network nodes, with the introduction of limited hardware and software overhead on the monitored network. The proposed solution is described and evaluated by means of logical simulations and an implementation on reconfigurable logic, using a reference NoC architecture with mesh topology. Scalability of the proposed approach is also discussed and evaluated by means of network simulations. Results show an area occupation less than 1% in a 3×3 mesh NoC, and a good scalability of the proposed mechanism in an 8×8 mesh network, indicating it as a valid lightweight solution able to enforce isolation in NoCs.

Read more…

In this paper, a multiple-objective Metaheuristics study is discussed. Initially, three mono-objective metaheuristics will be explored in order to design and optimize Radio-Frequency integrated inductors. These metaheuristics are: An evolutionary algorithm called The Differential Evolution (DE), An algorithm supported on Newton’s laws of gravity and motion called the Gravitational Search Algorithm (GSA) and, finally, A swarm intelligence algorithm called the Particle Swarm Optimization (PSO). The performances of these three mono-objective metaheuristics are evaluated and compared over three benchmark functions and one application to optimize the layout of a RF silicon-based planar spiral inductor, the double ?-model is adopted. Secondly, three references multi-objective metaheuristics using Pareto front are used respectively the multi-objective PSO (MOPSO), the Pareto envelope-based selection algorithm-II (PESAII) and the multi-objective evolutionary algorithm based on decomposition (MOEA/D). The performances of these multi-objective optimization algorithms are evaluated and compared over two bi-objective benchmark functions and the same application used in the first section. Two conflicting performances were optimized, namely the quality factor ‘Q’ (to be maximized) and the device area ‘dout’ (to be minimized) for the RF inductor. It was concluded that the multiple-objective PSO are significantly more efficient and robust for difficult problems than the other metaheuristics.

Read more…