International Journal of Electrical and Computer Engineering
International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.
Articles
6,301 Documents
A non-negative matrix factorization based clustering to identify potential tuna fishing zones
Devi Fitrianah;
Hisyam Fahmi;
Achmad Nizar Hidayanto;
Pang Ning-Tan;
Aniati Murni Arymurthy
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i6.pp5458-5466
Many nonnegative matrix factorization based clusterings are employed in discovering pattern and knowledge. Considering the sparseness nature of our data set about the daily tuna fishing data, we attempted to utilize a clustering approach, which is based on non-negative matrix factorization. Adding sparseness constraint and assigning good initial value in the modified NMF method, a proposed algorithm Direct-NMFSC yielded better result cluster compared to other methods which are also utilizing sparse constraint to their approaches, SNMF and NMFSC. The result of this study shows that Direct-NMFSC has 5.376 times of iteration number less than NMFSC in average with 531.97 as the CH index result. The determination of potential fishing zones is one of the essential efforts in the potential fishing zone mapping system for tuna fishing. By means of this novel data-driven study to construct the information and to identify the potential tuna fishing zones is done. We also showed that utilizing the Direct-NMFSC can spot and identify the potential tuna fishing zones presented in red cluster that covers both the spatial and temporal information.
Pneumatic positioning control system using constrained model predictive controller: Experimental repeatability test
Siti Fatimah Sulaiman;
M. F. Rahmat;
Ahmad Athif Faudzi;
Khairuddin Osman;
S. I. Samsudin;
A. F. Z. Abidin;
Noor Asyikin Sulaiman
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i5.pp3913-3923
Most of the controllers that were proposed to control the pneumatic positioning system did not consider the limitations or constraints of the system in their algorithms. Non-compliance with the prescribed system constraints may damage the pneumatic components and adversely affect its positioning accuracy, especially when the system is controlled in real-time environment. Model predictive controller (MPC) is one of the predictive controllers that is able to consider the constraint of the system in its algorithm. Therefore, constrained MPC (CMPC) was proposed in this study to improve the accuracy of pneumatic positioning system while considering the constraints of the system. The mathematical model of pneumatic system was determined by system identification technique and the control signal to the valves were considered as the constraints of the pneumatic system when developing the controller. In order to verify the accuracy and reliability of CMPC, repetitive experiments on the CMPC strategy was implemented. The existing predictive controller, that was used to control the pneumatic system such as predictive functional control (PFC), was also compared. The experimental results revealed that CMPC effectively improved the position accuracy of the pneumatic system compared to PFC strategy. However, CMPC not capable to provide a fast response as PFC.
Adaptive hysteresis band current control of grid connected PV inverter
R. S. Ravi Sankar;
A. Venkatesh;
Deepika Kollipara
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i4.pp2856-2863
In this paper, adaptive hysteresis band current controller is implemented to control the current injected into the grid. Initially it was implemented by B.K Bose for control of the machine drive. Now it is implemented for the grid connected PV inverter, to control the current injected into Grid. It is well suitable for the distribution generation. The adaptive hysteresis band controller changes the bandwidth based on the modulating frequency, supply voltage, input DC voltage and slope of the reference current. Consequently, the controller generates pulses to the inverter. It is advantageous over the conventional hysteresis controller, as the switching frequency is maintained almost constant. Thereby quality of grid current is also improved. It is verified in time domain analysis of simulation using MATLAB.
A novel predictive model for capturing threats for facilitating effective social distancing in COVID-19
Salma Firdose;
Surendran Swapna Kumar;
Ravinda Gayan Narendra Meegama
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v12i1.pp596-604
Social distancing is one of the simple and effective shields for every individual to control spreading of virus in present scenario of pandemic coronavirus disease (COVID-19). However, existing application of social distancing is a basic model and it is also characterized by various pitfalls in case of dynamic monitoring of infected individual accurately. Review of existing literature shows that there has been various dedicated research attempt towards social distancing using available technologies, however, there are further scope of improvement too. This paper has introduced a novel framework which is capable of computing the level of threat with much higher degree of accuracy using distance and duration of stay as elementary parameters. Finally, the model can successfully classify the level of threats using deep learning. The study outcome shows that proposed system offers better predictive performance in contrast to other approaches.
Star-rating evaluation model for rating the energy-efficiency level of android google play apps
Abdullah Mahmoud Almasri;
Luis Borges Gouveia
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i2.pp1599-1612
The tremendous increase in smartphone usage is accompanied by an increase in the need for more energy. This preoperational relationship between modern technology and energy generates energy-greedy apps, and therefore power-hungry end users. With many apps falling under the same category in an app store, these apps usually share similar functionality. Because developers follow different design and development schools, each app has its energy-consumption habits. Since apps share similar features, an end-user with limited access to recharging resources would prefer an energy-friendly app rather than a popular energy-greedy app. However, app stores do not indicate the energy behavior of the apps they offer, which causes users to randomly choose apps without understanding their energy-consumption behavior. A review of the relevant literature was provided covering various energy-saving techniques. The results gave an initial impression about the popularity of the usage of two power-saving modes where the average usage of these modes did not exceed 31% among the total 443 Android users. To address this issue, we propose a star-rating evaluation model (SREM), an approach that generates a tentative energy rating label for each app. The model was tested on 7 open-source apps to act as a primary evaluation sample. To that end, SREM adapts current energy-aware refactoring tools to demonstrate the level of energy consumption of an app and presents it in a star-rating schema similar to the Ecolabels used on electrical home appliances. As per our results, SREM helped in saving 35% of smartphone energy.
Disturbance observer-based controller for inverted pendulum with uncertainties: Linear matrix inequality approach
Van-Phong Vu;
Minh-Tam Nguyen;
Anh-Vu Nguyen;
Vi-Do Tran;
Tran Minh Nguyet Nguyen
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i6.pp4907-4921
A new approach based on linear matrix inequality (LMI) technique for stabilizing the inverted pendulum is developed in this article. The unknown states are estimated as well as the system is stabilized simultaneously by employing the observer-based controller. In addition, the impacts of the uncertainties are taken into consideration in this paper. Unlike the previous studies, the uncertainties in this study are unnecessary to satisfy the bounded constraints. These uncertainties will be converted into the unknown input disturbances, and then a disturbance observer-based controller will be synthesized to estimate the information of the unknown states, eliminate completely the effects of the uncertainties, and stabilize inverted pendulum system. With the support of lyapunov methodology, the conditions for constructing the observer and controller under the framework of linear matrix inequalities (LMIs) are derived in main theorems. Finally, the simulations for system with and without uncertainties are exhibited to show the merit and effectiveness of the proposed methods.
Analysis of on-off current ratio in asymmetrical junctionless double gate MOSFET using high-k dielectric materials
Hakkee Jung;
Byungon Kim
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i5.pp3882-3889
The variation of the on-off current ratio is investigated when the asymmetrical junctionless double gate MOSFET is fabricated as a SiO2/high-k dielectric stacked gate oxide. The high dielectric materials have the advantage of reducing the short channel effect, but the rise of gate parasitic current due to the reduction of the band offset and the poor interface property with silicon has become a problem. To overcome this disadvantage, a stacked oxide film is used. The potential distributions are obtained from the Poission equation, and the threshold voltage is calculated from the second derivative method to obtain the on-current. As a result, this model agrees with the results from other papers. The on-off current ratio is in proportion to the arithmetic average of the upper and lower high dielectric material thicknesses. The on-off current ratio of 104 or less is shown for SiO2, but the on-off current ratio for TiO2 (k=80) increases to 107 or more.
Detecting spam e-mails using stop word TF-IDF and stemming algorithm with Naïve Bayes classifier on the multicore GPU
Manjit Jaiswal;
Sukriti Das;
Khushboo Khushboo
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i4.pp3168-3175
A spam filter is a program which is used to identify unwanted emails and prevents those messages from getting into a user's mail. The study was focused on how the algorithms can be applied on a number of e-mails consisting of both ham and spam e-mails. First, the working principle and steps which are followed for implementation of stop words, TF-IDF and stemming algorithm on NVIDIA’s Tesla P100 GPU are discussed and to verify the findings by executing of Naïve Bayes algorithm. After complete training and testing of the spam e-mails dataset taken from Kaggle by using the proposed method, we got a high training accuracy of 99.67% and got a testing accuracy of about 99.03% on the multicore GPU that boosted the speed of execution of training time period and testing time period which is improved of training and testing accuracy around 0.22% and 0.18% respectively when compared to that after applying only Naïve Bayes i.e. conventional method to the same dataset where we found training and testing accuracy to be 99.45% and 98.85% respectively. Also, we found that training time taken on GPU is 1.361 seconds which was about 1.49X faster than that taken on CPU which is 2.029 seconds. And the testing time taken on GPU is 1.978 seconds which was about 1.15X faster than that taken on CPU which is 2.280 seconds.
Counteraction to information influence in social networking services by means of fuzzy logic system
Kateryna Molodetska;
Vladyslav Solonnikov;
Oleksandr Voitko;
Ihor Humeniuk;
Oleksandr Matsko;
Oleksii Samchyshyn
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i3.pp2490-2499
The article describes a decision support system based on fuzzy inference aimed to automate the procedure of choosing a model of formalizing the interaction between actors in virtual communities of social networking services and synergistic management of such processes. The developed system aims to increase the effectiveness of counteracting threats to information security of the state in social networking services. The mathematical apparatus of the fuzzy set theory and the Mamdani algorithm are the basis for the functioning of the decision support system. The usage of the developed fuzzy inference system will remove the ambiguity of information security expertise in the course of choosing approaches to formalization and the model of synergistic management of actors’ interaction in the conditions of incomplete information and ambiguous assessment of the state information security threat in social networking services.
Design and analysis of multiple read port techniques using bank division with XOR method for multi-ported-memory on FPGA platform
Druva Kumar S.;
Roopa M.
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i6.pp4785-4793
The multiple read and write operations are performed simultaneously by multi-ported memories and are used in advanced digital design applications on reprogrammable field-programmable gate arrays (FPGAs) to achieve higher bandwidth. The Memory modules are configured by block RAM (BRAMs), which utilizes more area and power on FPGA. In this manuscript, the techniques to increase the read ports for multi-ported memory modules are designed using the bank division with XOR (BDX) approach. The read port techniques like two read-one write (2R1W) memory, hybrid mode approach either 2R1W or 4R memory, and hierarchical BDX (HBDX) Approach using 2R1W/4R memory are designed on FPGA platform. The Proposed work utilizes only slices and look-up table (LUT's) rather than BRAMs while designing the memory modules on FPGA, which reduces the computational complexity and improves the system performance. The experimental results are analyzed on Artix-7 FPGA. The performance parameters like slices, LUT utilization, maximum frequency (Fmax), and hardware efficiency are analyzed by concerning different memory depths. The 4R1W memory design using the HBDX approach utilizes 4% slices and works at 449.697 MHz operating frequency on Artix-7 FPGA. The proposed work provides a better platform to choose the proper read port technique to design an efficient modular multiport memory architecture.