Showing papers in "Bulletin of Electrical Engineering and Informatics in 2018"
TL;DR: In this paper, the optical properties of nanocomposites were studied and the experimental results showed that the absorbance, absorption coefficient, refractive index, extinction coefficient, real and imaginary parts of dielectric constant and optical conductivity of (PVP-CMC) blend are increased with increase of the MgO nanoparticles concentration.
Abstract: Nanocomposites used in many optical devices applications. This aims to preparation of new type of polymer and study their optical properties. The polyvinyl pyrrolidone-carboxymethyl cellulose blend and magnesium oxide nanocomposites have been fabricated. The nanocomposites are prepared for different concentrations of polymer blend and magnesium oxide nanoparticles. The optical properties of nanocomposites were studied. The experimental results showed that the absorbance, absorption coefficient, refractive index, extinction coefficient, real and imaginary parts of dielectric constant and optical conductivity of (PVP-CMC) blend are increased with increase of the MgO nanoparticles concentration. The transmittance and energy band gap are decreased with increase of the MgO nanoparticles concentration. The nanocomposites have high absorbance in UV region which may be used for radiation shielding application.
38 citations
TL;DR: In the AASP bridge system under consideration, the soil area subjected to compaction at reference points is just over 1% of the 70% protraction of modern machines, which ensures stable operation of technological mechanisms in a programmed robotic mode with a minimum of unproductive energy costs associated with movement.
Abstract: Improvement of modern technical systems and technologies. Increasing the productivity of modern agricultural machines with increasing their weight, which leads, in the course of their work, to a significant compaction of the soil. The heterogeneity of the soil, as a bearing surface, causes not adjustable fluctuations in the workplace, which makes automation of the application of robotics more difficult. Modern solutions to the problems of reducing the negative impact on the soil, increasing the permeability of aggregates due to the reconstruction of the propulsors do not give the proper effect. More cardinally solve these problems, as well as the ability to implement automation and robotics bridge systems such as ABAC, moving along rail tracks, AASP on vertical piles and point gravel-halide supports with concrete platforms. The most promising of these is the AAS platform, which is a 30x10 m bridge structure that moves by step-by-step extension, the beams onto 3 subsequent pads located 10 m away. After entering the new position of the bridge platform, along the long 30-meter span beams Moves the work-technological module with a set of working elements, performing the programmed operations. Thus, in the AASP bridge system under consideration, the soil area subjected to compaction at reference points is just over 1% of the 70% protraction of modern machines. Compared to the ABAC system, moving along railways, the equipment of point supports is much less expensive and requires insignificant operating costs. At the same time, the rigidity of AASP design ensures stable operation of technological mechanisms in a programmed robotic mode with a minimum of unproductive energy costs associated with movement.
29 citations
TL;DR: An analysis of LPWA underlying technology in licensed and unlicensed spectrum by means of literature review and comparative assessment of Sigfox, LoRa, NB-IoT and LTE-M is provided to provide a simple guideline on how to match a specific application profile with the best fit connectivity features.
Abstract: There are many platforms in licensed and license free spectrum that support LPWA (low power wide area) technology in the current markets. However, lack of standardization of the different platforms can be a challenge for an interoperable IoT environment. Therefore understanding the features of each technology platform is essential to be able to differentiate how the technology can be matched to a specific IoT application profile. This paper provides an analysis of LPWA underlying technology in licensed and unlicensed spectrum by means of literature review and comparative assessment of Sigfox, LoRa, NB-IoT and LTE-M. We review their technical aspect and discussed the pros and cons in terms of their technical and other deployment features. General IoT application requirements is also presented and linked to the deployment factors to give an insight of how different applications profiles is associated to the right technology platform, thus provide a simple guideline on how to match a specific application profile with the best fit connectivity features.
18 citations
TL;DR: The aim of this work is to develop an end device in smart home system that will support power conservation function indirectly, specifically a curtain open/close controller, using the 28BYJ-48 stepper motor as actuator with the assistance of ULN2003A driver.
Abstract: In this paper, a curtain controller for smart home is presented. The aim of this work is to develop an end device in smart home system that will support power conservation function indirectly, specifically a curtain open/close controller. To achieve this, the 28BYJ-48 stepper motor is used as actuator with the assistance of ULN2003A driver. The motor is controlled using STM32L100RCT6 microcontroller, which is chosen due to its low power consumption. The microcontroller controls the motor’s direction by using a pulse width modulation logic signals emitted from four GPIO pins, which works based on data transmitted from central host through ZigBee protocol on Mesh network. Meanwhile, from the user’s side, the control is done by using Android-based application, which is connected to central host through Bluetooth. Based on the testing conducted on a miniature curtain, the curtain can be controlled wirelessly through the Android application. Furthermore, the device consumes power 210.5 mW for idle condition and 1,586 mW for process condition. The amount of the consumed power makes it suitable for low-power operation and in alignment with the smart home system’s overall aim for power conservation in the wireless sensor network-based smart home system.
17 citations
TL;DR: This study has used a large-scale real-world data set to identify the efficiency of clustering technique to improve the classification model and found that applying K-means clustering prior to KNN model helps in reducing the computation time.
Abstract: Product classification is the key issue in e-commerce domains. Many products are released to the market rapidly and to select the correct category in taxonomy for each product has become a challenging task. The application of classification model is useful to precisely classify the products. The study proposed a method to apply clustering prior to classification. This study has used a large-scale real-world data set to identify the efficiency of clustering technique to improve the classification model. The conventional text classification procedures are used in the study such as preprocessing, feature extraction and feature selection before applying the clustering technique. Results show that clustering technique improves the accuracy of the classification model. The best classification model for all three approaches which are classification model only, classification with hierarchical clustering and classification with K-means clustering is K-Nearest Neighbor (KNN) model. Even though the accuracy of the KNN models are the same across different approaches but the KNN model with K-means clustering had the shortest time of execution. Hence, applying K-means clustering prior to KNN model helps in reducing the computation time.
17 citations
TL;DR: The new approach Defense-through-Deception network security model is presented that improves the traditional passive protection by applying deception techniques to them that give insights into the limitations posed by the Defense-In-Depth (DID) Model.
Abstract: Denial of Service (DOS) and (DDOS) Distributed Denial of Service attacks have become a major security threat to university campus network security since most of the students and teachers prepare online services such as enrolment, grading system, library etc. Therefore, the issue of network security has become a priority to university campus network management. Using online services in university network can be easily compromised. However, traditional security mechanisms approach such as Defense-In-Depth (DID) Model is outdated in today’s complex network and DID Model has been used as a primary cybersecurity defense model in the university campus network today. However, university administration should realize that Defense-In-Depth (DID) are playing an increasingly limited role in DOS/DDoS protection and this paper brings this fact to light. This paper presents that the Defense-In-Depth (DID) is not capable of defending complex and volatile DOS/DDOS attacks effectively. The test results were presented in this study in order to support our claim. The researchers established a Defense-In-Depth (DID) Network model at the Central Luzon State University and penetrated the Network System using DOS/DDOS attack to simulate the real network scenario. This paper also presents the new approach Defense-through-Deception network security model that improves the traditional passive protection by applying deception techniques to them that give insights into the limitations posed by the Defense-In-Depth (DID) Model. Furthermore, this model is designed to prevent an attacker who has already entered the network from doing damage.
16 citations
TL;DR: This survey covers basic concepts of cross spectral matching, visual and thermal features extraction, and state of the art descriptors, and provides a description of better feature selection methods inCross spectral matching.
Abstract: In recent years, cross spectral matching has been gaining attention in various biometric systems for identification and verification purposes. Cross spectral matching allows images taken under different electromagnetic spectrums to match each other. In cross spectral matching, one of the keys for successful matching is determined by the features used for representing an image. Therefore, the feature extraction step becomes an essential task. Researchers have improved matching accuracy by developing robust features. This paper presents most commonly selected features used in cross spectral matching. This survey covers basic concepts of cross spectral matching, visual and thermal features extraction, and state of the art descriptors. In the end, this paper provides a description of better feature selection methods in cross spectral matching.
16 citations
TL;DR: The term of WiFi-friendly building is introduced by considering signal propagations, the obstacle impact, as well as proposing an ornament-attaced reflector and a hole-in-the-wall structure to improve WiFi signal distribution.
Abstract: The 802.11 networks (wireless fidelity (WiFi) networks) have been the main wireless internet access infrastructure within houses and buildings. Besides access point placement, building architectures contribute to the WiFi signal spreading. Even dough WiFi installation in buildings becomes prevalent; the building architectures still do not take WiFi-friendliness into considerations. Current research on building and WiFi are on access point location, location based service and home automation. In fact, the more friendly the building to WiFi signal, the more efficient the 802.11 based wireless infrastructure. This paper introduces the term of WiFi-friendly building by considering signal propagations, the obstacle impact, as well as proposing an ornament-attaced reflector and a hole-in-the-wall structure to improve WiFi signal distribution. Experiment results show that obstacle materials made of concrete reducing WiFi signal the most, followed by metal and wood. Reflecting materials are able to improve the received signal level, for instance, the implemented ornament-attached reflector is able improving the received signal up to 6.56 dBm. Further, the hole-in-the-wall structure is successfully increasing WiFi signal up to 2.3 dBm.
16 citations
TL;DR: The findings may practically helpful for stakeholders in the sampled institution, but it may also theoretically useful for researchers in regard to the readiness and success issues of ISI.
Abstract: Information system integration (ISI) is one of the development concerns for organizations to enhance business competitiveness. However, the implementations still present its failures. Despite the ISI may successful technically; but it still seems to be unsuccessful because of the human and management issues. The issues may relate to the readiness constructs of ISI. This study was aimed to know the status of the readiness and success of ISI and to assess the influential factors of the integration in the sampled institution. About 160 samples were purposely involved by considering their key informant characteristics. The data were analyzed using the partial least squares-structural equation modeling (PLS-SEM) method. The findings revealed only the user satisfaction variable that mediated the positive effects of the readiness variables towards variable of the system integration success. Besides, the findings may practically helpful for stakeholders in the sampled institution, but it may also theoretically useful for researchers in regard to the readiness and success issues of ISI.
15 citations
TL;DR: The performance of Support Vector Machine (SVM) and Decision Tree (DT) in classifying emotions from Malay folklores is presented and it showed that DT outperformed SVM by more than 22.2% accuracy rate.
Abstract: In this paper, the performance of Support Vector Machine (SVM) and Decision Tree (DT) in classifying emotions from Malay folklores is presented. This work is the continuation of our storytelling speech synthesis work to add emotions for a more natural storytelling. A total of 100 documents from children short stories are collected and used as the datasets of the text-based emotion recognition experiment. Term Frequency-Inverse Document Frequency (TF-IDF) is extracted from the text documents and classified using SVM and DT. Four types of common emotions, which are happy, angry, fearful and sad are classified using the two classifiers. Results showed that DT outperformed SVM by more than 22.2% accuracy rate. However, the overall emotion recognition is only at moderate rate suggesting an improvement is needed in future work. The accuracy of the emotion recognition should be improved in future studies by using semantic feature extractors or by incorporating deep learning for classification.
15 citations
TL;DR: This research uses binary particle swarm optimization algorithm and Bus Injection to Branch Current-Branch Current to Bus Voltage (BIBC-BCBV) method to analyze the radial system power flow to minimize power losses and voltage drop as well as decreasing the voltage stability level.
Abstract: Power losses and voltage drop are existing problems in radial distribution networks. This power losses and voltage drop affect the voltage stability level. Reconfiguring the network is a form of approach to improve the quality of electrical power. The network reconfiguration aims to minimize power losses and voltage drop as well as decreasing the Voltage Stability Index (VSI). In this research, network reconfiguration uses binary particle swarm optimization algorithm and Bus Injection to Branch Current-Branch Current to Bus Voltage (BIBC-BCBV) method to analyze the radial system power flow. This scheme was tested on the 33-bus IEEE radial distribution system 12.66 kV. The simulation results show that before reconfiguration, the active power loss is 202.7126 kW and the VSI is 0.20012. After reconfiguration, the active power loss and VSI decreased to 139.5697 kW and 0.14662, respectively. It has decreased the power loss for 31.3136% significantly while the VSI value is closer to zero.
TL;DR: In this article, the authors compared the performance of two methods, Adaptive Neuro Fuzzy Inference (ANFIS) method and Multiple Linear Regression (MLP) method, which uses a mathematical approach.
Abstract: Solar radiation forecasting is important in solar energy power plants (SEPPs) development. The electrical energy generated from the sunlight depends on the weather and climate conditions in the area where the SEPPs are installed. The condition of solar irradiation will indirectly affect the electrical grid system into which the SEPPs are injected, i.e. the amount and direction of the power flow, voltage, frequency, and also the dynamic state of the system. Therefore, the prediction of solar radiation condition is very crucial to identify its impact into the system. There are many methods in determining the prediction of solar radiation, either by mathematical approach or by heuristic approach such as artificial intelligent method. This paper analyzes the comparison of two methods, Adaptive Neuro Fuzzy Inference (ANFIS) method, which belongs into the heuristic methods, and Multiple Linear Regression (MLP) method, which uses a mathematical approach. The performance of both methods is measured using the root mean square error (RMSE) and the mean absolute error (MAE) values. The data of the Swiss Basel city from Meteoblue are used to test the performance of the two methods being compared. The data are divided into four cases, being classified as the training data and the data used as predictions. The solar radiation prediction using the ANFIS method indicates the results which are closer to the real measurement results, being compared to the the use MLP method. The average values of RMSE and MAE achieved are 123.27 W/m 2 and 90.91 W/m 2 using the ANFIS method, being compared to 138.70 W/m 2 and 101.56 W/m 2 respectively using the MLP method. The ANFIS method gives better prediction performance of 12.51% for RMSE and 11.71% for MAE with respect to the use of the MLP method.
TL;DR: This research provides considerations of the noise and frequency bandwidth analysis in designing Transimpedance Amplifier to cope with the required design specification of a VLC system.
Abstract: In a visible light communication (VLC) system, there are many modules involved. One of the important modules is Transimpedance Amplifier (TIA) that resides in the analog front-end receiver (Rx-AFE). TIA is responsible for performing signal conversion from current signal, which is provided from the photodiode (PD) to voltage signal. It is the reason why the TIA should be operating in low noise condition and wide bandwidth of frequency. These will enable a flexible coverage of the VLC system in performing its signal processing. Hence, in this research, we provide considerations of the noise and frequency bandwidth analysis in designing TIA to cope with the required design specification of a VLC system.
TL;DR: A nonlinear model based on time series neural network system (TSNN) to improve the highly nonlinear dynamic model of an automotive lead acid cell battery and the ANN and nonlinear autoregressive exogenous model (NARX) models achieved satisfying results.
Abstract: The paper studies a nonlinear model based on time series neural network system (TSNN) to improve the highly nonlinear dynamic model of an automotive lead acid cell battery. Artificial neural network (ANN) take into consideration the dynamic behavior of both input-output variables of the battery charge-discharge processes. The ANN works as a benchmark, its inputs include delays and charging/discharging current values. To train our neural network, we performed a pulse discharge on a lead acid battery to collect experimental data. Results are presented and compared with a nonlinear Hammerstein-Wiener model. The ANN and nonlinear autoregressive exogenous model (NARX) models achieved satisfying results.
TL;DR: The proposed Wind energy-UPQC is design in Matlab simulation for reduction of voltage sag, swell, harmonics in load current and compensation of active and reactive power.
Abstract: The extensive use of non-linear loads in domestic, industrialand commercial services origin harmonic complicationsHarmonics make malfunctions in profound equipment, voltage drop across the network, conductor heat increases and overvoltage through resonance All these problems can be remunerated by using Unified Power Quality Controller (UPQC) and the operation of UPQC depends upon the available voltage across capacitor present in dc link If the capacitor voltage is maintained constant then it gives satisfactory performance The proposed research is basically on designing of Wind energy fed to the dc link capacitor of UPQCso as to maintain propervoltageacross it and operate the UPQC for power quality analysis The proposed technique is the grouping of shunt and series Active Power Filter (APF) to form UPQC which is fed wind energy system and connected to grid for better response in the output In this paper, the simulation model of series APF, shunt APF, UPQC and Wind energy with UPQC are design in Matlab The proposed Wind energy-UPQC is design in Matlab simulation for reduction of voltage sag, swell, harmonics in load current and compensation of active and reactive power
TL;DR: This paper proposed merged-Long Short-term Memory for forecasting ground visibility at the airpot using timeseries of predictor variable combined with another variable as moderating variable and showed the best average accuracy for forecasting visibility using merged Long Short- term Memory model and temperature and dew point as a moderating Variable.
Abstract: Over decades, weather forecasting has attracted researchers from worldwide communities due to itssignificant effect to global human life ranging from agriculture, air trafic control to public security. Although formal study on weather forecasting has been started since 19 th century, research attention to weather forecasting tasks increased significantly after weather big data are widely available. This paper proposed merged-Long Short-term Memory for forecasting ground visibility at the airpot using timeseries of predictor variable combined with another variable as moderating variable. The proposed models were tested using weather timeseries data at Hang Nadim Airport, Batam. The experiment results showedthe best average accuracy for forecasting visibility using merged Long Short-term Memory model and temperature and dew point as a moderating variable was (88.6%); whilst, using basic Long Short-term Memory without moderating variablewasonly (83.8%) respectively (increased by 4.8%).
TL;DR: In this article, the structural and dielectric properties of poly-methyl methacrylate-lead oxide nanocomposites were studied and it was shown that the electrical conductivity increases with increase in frequency of applied electric field.
Abstract: Piezoelectric materials have been prepared from (poly-methyl methacrylate-lead oxide) nanocomposites for electronic applications. The lead oxide nanoparticles were added to poly-methyl methacrylate by different concentrations are (4, 8, and 12) wt%. The structural and dielectric properties of nanocomposites were studied. The results showed that the dielectric constant and dielectric loss of nanocomposites decrease with increase in frequency of applied electric field. The A.C electrical conductivity increases with increase in frequency. The dielectric constant, dielectric loss and A.C electrical conductivity of poly-methyl methacrylate increase with increase in lead oxide nanoparticles concentrations. The results of pressure sensor showed that the electrical resistance of (PMMA-PbO 2 ) nanocomposites decreases with increase in pressure.
TL;DR: This study aims to estimate the RR from electrocardiogram (ECG) and photoplethysmogram (PPG) signals, which consist of passive and non-invasive acquisition modules, and reveals that the filtering method efficiently extracted respiratory information from the ECG and PPG signals.
Abstract: Abnormal vital signs often predict a serious condition of acutely ill hospital patients in 24 hours. The notable fluctuations of respiratory rate (RR) are highly predictive of deteriorations among the vital signs measured. Traditional methods of detecting RR are performed by directly measuring the air flow in or out of the lungs or indirectly measuring the changes of the chest volume. These methods require the use of cumbersome devices, which may interfere with natural breathing, are uncomfortable, have frequently moving artifacts, and are extremely expensive. This study aims to estimate the RR from electrocardiogram (ECG) and photoplethysmogram (PPG) signals, which consist of passive and non-invasive acquisition modules. Algorithms have been validated by using PhysioNet’s Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II)’s patient datasets. RR estimation provides the value of mean absolute error (MAE) for ECG as 1.25 bpm (MIMIC-II) and 1.05 bpm for the acquired data. MAE for PPG is 1.15 bpm (MIMIC-II) and 0.90 bpm for the acquired data. By using 1-minute windows, this method reveals that the filtering method efficiently extracted respiratory information from the ECG and PPG signals. Smaller MAE for PPG signals results from fewer artifacts due to easy sensor attachment for the PPG because PPG recording requires only one-finger pulse oximeter sensor placement. However, ECG recording requires at least three electrode placements at three positions on the subject’s body surface for a single lead (lead II), thereby increasing the artifacts. A reliable technique has been proposed for RR estimation.
TL;DR: By installing DG in the transmission system, voltage stability and voltage profile can be improved, while power losses can be minimized, by installing Whale Optimization Algorithm (WOA) Based Technique for Distributed Generation Installation in Transmission System.
Abstract: This paper presents Whale Optimization Algorithm (WOA) Based Technique for Distributed Generation Installation in Transmission System. In this study, WOA optimization engine is developed for the installation of Distributed Generation (DG). Prior to the optimization process, a pre-developed voltage stability index termed Fast Voltage Stability Index (FVSI) was used as an indicator to identify the location for the DG to be installed in the system. Meanwhile, for sizing the DG WOA is employed to identify the optimal sizing. By installing DG in the transmission system, voltage stability and voltage profile can be improved, while power losses can be minimized. The proposed algorithm was tested on 30-bus radial distribution network. Results obtained from the EP were compared with firefly algorithm (FA); indicating better results. This highlights the strength of WOA over FA in terms of minimizing total losses.
TL;DR: This paper reviews the existing works on mobile BI Acceptance Model for organizational decision-making and two user acceptance models which are Technologyacceptance Model and Technology Acceptance model for Mobile Services will be review.
Abstract: Mobile Business Intelligence (BI) is the ability to access BI-related data such as key performance indicators (KPIs), business metric and dashboard through mobile device. Mobile BI addresses the use-case of remote or mobile workers that need on-demand access to business-critical data. User acceptance on mobile BI is an essential in order to identify which factors influence the user acceptance of mobile BI application. Research on mobile BI acceptance model on organizational decision-making is limited due to the novelty of mobile BI as newly emerged innovation. In order to answer gap of the adoption of mobile BI in organizational decision-making, this paper reviews the existing works on mobile BI Acceptance Model for organizational decision-making. Two user acceptance models which are Technology Acceptance Model and Technology Acceptance Model for Mobile Services will be review. Realizing the essential of strategic organizational decision-making in determining success of organizations, the potential of mobile BI in decision-making need to be explore. Since mobile BI still in its infancy, there is a need to study user acceptance and usage behavior on mobile BI in organizational decision-making. There is still opportunity for further investigate the impact of mobile BI on organizational decision-making.
TL;DR: The object of this paper is to develop an inverter which is used for variable speed drives with increase in output voltage by eliminating transformer and filter circuit.
Abstract: Z-source based multilevel inverters are the recent topologies as they have boosting ability and near sinusoidal output waveforms. This paper proposes different inverter topologies such as Z-source multilevel inverter and quasi Z-source multilevel inverter. This paper also deals with switched inductor and improved switched inductor topologies with quasi Z-network. The proposed switched inductor system reduces the voltage stresses caused by capacitors, power devices and diodes. In addition to multilevel inverter advantages, the proposed configuration employs Z-source inverter advantages. The Z-source inverter as compared to the traditional inverter is less costly, less complex, more efficient and more reliable. The performance of the proposed configurations is analysed by varying passive elements in impedance network and is simulated in MATLAB/SIMULINK. Phase disposition (PD) pulse width modulation (PWM) technique is applied on the proposed configurations and performance parameters are measured by the fast Fourier transform FFT analysis. The object of this paper is to develop an inverter which is used for variable speed drives with increase in output voltage by eliminating transformer and filter circuit. The performance is checked with standared parameter of the inverter.
TL;DR: In this article, the authors evaluate the different sizing of solar PV system for university buildings under the Net Energy Metering (NEM) scheme and find that the amount of solar energy generated and used by the load per year is between 5.10% and 20.20% from the total annual load demand.
Abstract: Malaysia has moved forward by promoting the use of renewable energy such as solar PV to the public to reduce dependency on fossil fuel-based energy resources. Due to the concern on high electricity bill, Universiti Malaysia Perlis (UniMAP) is keen to install solar PV system as an initiative for energy saving program to its buildings. The objective of this paper is to technically and economically evaluate the different sizing of solar PV system for university buildings under the Net Energy Metering (NEM) scheme. The study involves gathering of solar energy resource information, daily load profile of the buildings, sizing PV array together with grid-connected inverters and the simulation of the designed system using PVsyst software. Based on the results obtained, the amount of solar energy generated and used by the load per year is between 5.10% and 20.20% from the total annual load demand. Almost all solar energy generated from the system will be self-consumed by the loads. In terms of profit gained, the university could reduce its electricity bill approximately between a quarter to one million ringgit per annum depending on the sizing capacity. Beneficially, the university could contribute to the environmental conservation by avoiding up to 2,000 tons of CO 2 emission per year.
TL;DR: In this article, a review of recent developments in QDSSCs and their key components, including the photoanode, sensitizer, electrolyte and counter electrode, is presented.
Abstract: Quantum dot-sensitized solar cell (QDSSC) has an analogous structure and working principle to the dye sensitizer solar cell (DSSC). It has drawn great attention due to its unique features, like multiple exciton generation (MEG), simple fabrication and low cost. The power conversion efficiency (PCE) of QDSSC is lower than that of DSSC. To increase the PCE of QDSSC, it is required to develop new types of working electrodes, sensitizers, counter electrodes and electrolytes. This review highlights recent developments in QDSSCs and their key components, including the photoanode, sensitizer, electrolyte and counter electrode.
TL;DR: F fuzzy logic technics is used in order to solve the problem of large number of platform users and automating tutor tasks and creating an artificial agent that is elaborate in basing on the learners activities, especially the assessment of their collaborative behaviors.
Abstract: The aim of this paper is the introduction of intelligence in e-learning collaborative system In such system, the tutor plays an important role to facilitate collaboration between users and boost less active among them to get more involved for good pedagogical action However, the problem lies in the large number of platform users, and the tutor tasks become difficult if not impossible Therefore, we used fuzzy logic technics in order to solve this problem by automating tutor tasks and creating an artificial agent This agent is elaborate in basing on the learners activities, especially the assessment of their collaborative behaviors After the implementation of intelligent collaborative system by using Moodle platform, we have tested it The reader will discover our approach and relevant results
TL;DR: In this article, a conceptual framework based on absorptive capacity approach for an IT governance performance model in the higher education is proposed, which contributes theoretically by extending the knowledge of IT governance by exploring a new perspective on organizational learning.
Abstract: Information Technology (IT) governance has been emerging as a central issue in many organizations. This is because IT governance is key to realizing IT business value. Past studies have focused on the three aspects of IT governance, namely, structural capability, process capability and relational capability. At the same time, some studies have suggested that IT governance process should be viewed as a learning process rather than a problem solving process. Based on this scenario, the role of knowledge and knowledge based processes should be the central focus of IT governance. As a learning process, IT governance effectiveness can be determined by how much impact IT governance practices has influenced on decision-makers’ thinking and actions. In this case, knowledge capacity absorbed from IT governance experience reflects a certain level of organizational learning (OL) achieved which later influences the level of IT governance performance. Since studies that adopt this perspective is lacking, this paper proposes a conceptual framework based on absorptive capacity approach for an IT governance performance model in the higher education. The paper contributes theoretically by extending the knowledge of IT governance by exploring a new perspective on OL.
TL;DR: In this paper, a compact square slot patch antenna characterstics for wireless body area network (WBANs) applications is presented, which operates at 5.8 GHz of the ISM Band for WBAN applications.
Abstract: This paper presents a compact square slot patch antenna characterstics for wireless body area network (WBANs) applications.The assessment of the effects of electromagnetic energy (EM) on the human head is necessary because the sensitivity of human head to high radiation level. Although, structuring of low EM antennas is a major problem in the improvement of portable device and reducing the size of of the antenna is a major concern. However, performance of antenna reduces when antenna operates near human body which is lossy and complex in nature. The proposed antenna operates at 5.8GHz of the ISM Band for WBAN applications. The antenna has been designed and simulated with two different types of multilayer human head phantoms to characterize the antenna near the human head.The multilayer head phantom is constructed by five layers tissues head model using CST Microwave studio. Therefore, antenna with spherical phantom has the highest SAR value 0.206 W/Kg, while antenna with cubical phantom contributed the lowest SAR value of 0.166 for 10 g tissue at 5.8 GHz frequency exposed, whereas, the antenna with cubical phantom and spherical phantom have gain of 6.46 dBi and 6.2 dBi GHz respectively. It was observed that antenna performance significantly increased. The presented prototype has a potential to work for ISM applications.
TL;DR: In this article, a conceptual framework based on the Theory of Reasoned Action (TRA), Theory of Planned Behavior (TPB) and Unified Theory of Acceptance and Use of Technology (UTAUT) was proposed to study the knowledge management (KM) behavior of executives in Malaysia who work in different sectors and involved in Information Technology (IT) related fields.
Abstract: In this paper, we investigated the knowledge management (KM) behavior of executives in Malaysia who work in different sectors and involved in Information Technology (IT) related fields We proposed a conceptual framework based on the Theory of Reasoned Action (TRA), the Theory of Planned Behavior (TPB) and Unified Theory of Acceptance and Use of Technology (UTAUT) to study their intention and involvement in KM initiatives The knowledge creation theory (SECI process) was employed to operationalize KM intention and KM behavior We proposed six independent variables that represent the social-cultural nature of KM as the antecedence of KM intention These variables are trust, management support, decentralization, IT support, performance expectancy (PE), and effort expectancy (EE) Seventy-four executives from both private and government-linked organizations responded to our online questionnaire SmartPLS3 was used to run the analysis The reliability was ensured with the factor loadings, Cronbach’s alpha, Composite Reliability (CR) that met the fit requirement of above 06, 07 and 07 respectively The convergent validity was confirmed through average variance extracted (AVE) that met the fit requirement of above 05 The discriminant validity was assessed by using Fornell and Larcker’s criterion Finally, the structural model confirmed that only PE of KM, and EE of KM are the significant predictors of KM intention and the KM intention significantly predicts KM behavior The implications of the findings are discussed in detail at the end of the paper
TL;DR: Enhanced Local binary pattern reduced the dimension of the image and extracts the salient information on each sub region and achieved a higher recognition rate than other local descriptors.
Abstract: Face recognition is an emerging research area in recognition of the people. A novel feature extraction technique was introduced for robust face recognition. Enhanced Local binary pattern (EnLBP) divided the image into sub regions. For each sub region, the salient features are extracted by obtaining the mean value of each sub region. In LBP, each pixel was replaced by applying LBP into each sub region. In this paper, the mean value of sub region was replaced for the sub region. It reduced the dimension of the image and extracts the salient information on each sub region. The extracted features are compared with similarity measures to recognize the person. EnLBP reduces the operation time and computational complexity of the system. The experimental results were carried out in the standard benchmark database LFW-a. The proposed system achieved a higher recognition rate than other local descriptors.
TL;DR: Comparison of proposed method with existing method show that proposed method results more detailed output in estimating risk of information security threat.
Abstract: Involvement of digital information in almost of enterprise sectors makes information having value that must be protected from information leakage. In order to obtain proper method for protecting sensitive information, enterprise must perform risk analysis of threat. However, enterprises often get limitation in measuring risk related information security threat. Therefore, this paper has goal to give approach for estimating risk by using information value. Techniques for measuring information value in this paper are text mining and Jaccard method. Text mining is used to recognize information pattern based on three classes namely high business impact, medium business impact and low business impact. Furthermore, information is given weight by Jaccard method. The weight represents risk levelof information leakage in enterprise quantitatively. Result of comparative analysis with existing method show that proposed method results more detailed output in estimating risk of information security threat.
TL;DR: This paper deals with the novel design and implementation of asynchronous microprocessor by using HDL on Vivado tool wherein it has the capability of handling even I-Type, R-Type and Jump instructions with multiplier instruction packet.
Abstract: This paper deals with the novel design and implementation of asynchronous microprocessor by using HDL on Vivado tool wherein it has the capability of handling even I-Type, R-Type and Jump instructions with multiplier instruction packet. Moreover, it uses separate memory for instructions and data read-write that can be changed at any time. The complete design has been synthesized and simulated using Vivado. The complete design is targeted on Xilinx Virtex-7 FPGA. This paper more focuses on the use of Vivado Tool for advanced FPGA device. By using Vivado we get enhaced analysis result for better view of properly Route & Placed design.