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International Journal of Electrical and Computer Engineering
Published by Institute of Advanced Engineering and Science
ISSN : 20888708     EISSN : 27222578     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics 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.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 6,393 Documents
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Enhancing light scattering effect of white LEDs with ZnO nanostructures My Hanh Nguyen Thi; Nguyen Thi Phuong Loan; Hoang Van Ngoc
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp3838-3843

Abstract

Pc-LEDs, the lighting method that blends blue LED light with yellow light from phosphor to discharge white radiation, is one of the most advance known for high lumen output. However, pc-LEDs has inferior due to angular CCT deviation, which prevent pc-LEDs from reaching better performance. As a result, this research is conducted to address the need of pc-LEDs development by introducing a configuration doped with ZnO nanoparticles. The finite-difference time-domain (FDTD) method and the phosphor layer containing ZnO were applied in the experiments. The effect of ZnO-filled on the performance of color quality pc-LEDs is confirmed through calculated results. In particular, the uniformity of scattered light is improved with the presence of ZnO. In addition, ZnO particles also minimize the deviation of color temperature and enhance the color quality. Although there is a small decline in lumen output to achieve better color temperature uniformity, however, with suitable concentrations such as 0.25% N-ZnO, 0.25% S-ZnO, and 0. 75% R-ZnO, the decline is acceptable. The research on ZnO pc-LEDs demonstrates that this affordable and simple configuration can improve lighting properties and create other directions to enhance white light
One input voltage and three output voltage universal biquad filters with orthogonal tune of frequency and bandwidth May Phu Pwint Wai; Amornchai Chaichana; Winai Jaikla; Surapong Siripongdee; Peerawut Suwanjan
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i4.pp2962-2973

Abstract

This research paper contributes the one input three output voltage mode universal biquad filters with linear and electronic control of the natural frequency (w0), using two commercially available ICs, LT1228s as active device with two grounded capacitors, five resistors. The presented universal biquad filters can simultaneously provide three voltage-mode filtering functions, low-pass (LP), high-pass (HP) and band-pass (BP) without changing the circuit architecture. Furthermore, the first presented biquad filter provides low impedance at HP, BP voltage output nodes and LP, BP output voltage nodes are low impedance for the second proposed filter which is easy cascade ability with other voltage mode circuits without the employment of buffer circuits. The quality factor (Q) of both proposed filters is orthogonally adjusted from the passband voltage gain and w0. The proposed filters are simulated and experimented with commercially accessible ICs, LT1228. The simulated and experimental results demonstrate the filtering performances.
Towards the prospection of an optimal thermal response of ZnO surge arrester in HV power system Abdelhakim Bendakir; Abdelhafid Bayadi; Djalel DIB
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp1865-1875

Abstract

In order to understand the thermal and electrical properties of surge arrester under standard climatic conditions, it would be useful to evaluate the heating progression in its different elements. These are constituted of heterogeneous materials, which have physical and electrical nonlinear properties along the surge arrester. Temperature predicting solutions for zinc oxide ceramic blocks provide fundamental elements of the electrothermal material characteristics in view of the lifetime estimation. Electrothermal phenomenon analysis of surge arresters is based on empirically-determined parameter models, using finite element method (FEM) simulated on COMSOL Multiphysics software which is a more precise approach compared to the existing models. In this paper, the behavioural model has been developed to study the surge arresters in both cases: the steady state and overvoltage state (lightning). Previous published works validate the first simulation results. This work is therefore extended to consider other operating states, which illustrate the dependence of the type of surge on the amplitudes and durations of electrothermal phenomena.
A modified mayfly-SVM approach for early detection of type 2 diabetes mellitus Ratna Patil; Sharvari Tamane; Shitalkumar Adhar Rawandale; Kanishk Patil
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i1.pp524-533

Abstract

Diabetes mellitus is a chronic disease that affects many people in the world badly. Early diagnosis of this disease is of paramount importance as physicians and patients can work towards prevention and mitigation of future complications. Hence, there is a necessity to develop a system that diagnoses type 2 diabetes mellitus (T2DM) at an early stage. Recently, large number of studies have emerged with prediction models to diagnose T2DM. Most importantly, published literature lacks the availability of multi-class studies. Therefore, the primary objective of the study is development of multi-class predictive model by taking advantage of routinely available clinical data in diagnosing T2DM using machine learning algorithms. In this work, modified mayfly-support vector machine is implemented to notice the prediabetic stage accurately. To assess the effectiveness of proposed model, a comparative study was undertaken and was contrasted with T2DM prediction models developed by other researchers from last five years. Proposed model was validated over data collected from local hospitals and the benchmark PIMA dataset available on UCI repository. The study reveals that modified Mayfly-SVM has a considerable edge over metaheuristic optimization algorithms in local as well as global searching capabilities and has attained maximum test accuracy of 94.5% over PIMA.
Electrochemical batteries for smart grid applications Surender Reddy Salkuti
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp1849-1856

Abstract

This paper presents a comprehensive review of current trends in battery energy storage systems, focusing on electrochemical storage technologies for Smart Grid applications. Some of the batteries that are in focus for improvement include Lithium-ion, metal-air, Sodium-based batteries and flow batteries. A descriptive review of these batteries and their sub-types are explained along with their suitable applications. An overview of different types and classification of storage systems has been presented in this paper. It also presents an extensive review on different electrochemical batteries, such as lead-acid battery, lithium-based, nickel-based batteries and sodium-based and flow batteries for the purpose of using in electric vehicles in future trends. This paper is going to explore each of the available storage techniques out there based on various characteristics including cost, impact, maintenance, advantages, disadvantages, and protection and potentially make a recommendation regarding an optimal storage technique.
Multi-objective NSGA-II based community detection using dynamical evolution social network Muhammed E. Abd Alkhalec Tharwat; Mohd Farhan Md Fudzee; Shahreen Kasim; Azizul Azhar Ramli; Mohammed K. Ali
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4502-4512

Abstract

Community detection is becoming a highly demanded topic in social networking-based applications. It involves finding the maximum intraconnected and minimum inter-connected sub-graphs in given social networks. Many approaches have been developed for community’s detection and less of them have focused on the dynamical aspect of the social network. The decision of the community has to consider the pattern of changes in the social network and to be smooth enough. This is to enable smooth operation for other community detection dependent application. Unlike dynamical community detection Algorithms, this article presents a non-dominated aware searching Algorithm designated as non-dominated sorting based community detection with dynamical awareness (NDS-CD-DA). The Algorithm uses a non-dominated sorting genetic algorithm NSGA-II with two objectives: modularity and normalized mutual information (NMI). Experimental results on synthetic networks and real-world social network datasets have been compared with classical genetic with a single objective and has been shown to provide superiority in terms of the domination as well as the convergence. NDS-CD-DA has accomplished a domination percentage of 100% over dynamic evolutionary community searching DECS for almost all iterations.
Proportional fair buffer scheduling algorithm for 5G enhanced mobile broadband Asmae Mamane; M. Fattah; M. El Ghazi; Y. Balboul; M. El Bekkali; S. Mazer
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4165-4173

Abstract

The impending next generation of mobile communications denoted 5G intends to interconnect user equipment, things, vehicles, and cities. It will provide an order of magnitude improvement in performance and network efficiency, and different combinations of use cases enhanced mobile broadband (eMBB), ultra reliable low latency communications (URLLC), massive internet of things (mIoT) with new capabilities and diverse requirements. Adoption of advanced radio resource management procedures such as packet scheduling algorithms is necessary to distribute radio resources among different users efficiently. The proportional fair (PF) scheduling algorithm and its modified versions have proved to be the commonly used scheduling algorithms for their ability to provide a tradeoff between throughput and fairness. In this article, the buffer status is combined with the PF metric to suggest a new scheduling algorithm for efficient support for eMBB. The effectiveness of the proposed scheduling strategy is proved through à comprehensive experimental analysis based on the evaluation of different quality of service key performance indicators (QoS KPIs) such as throughput, fairness, and buffer status.
Fully automatic segmentation of intima/adventitia of the vessel using Bezier curve from intravascular ultrasound Kwang Baek Kim; Doo Heon Song
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2640-2646

Abstract

Although medical image segmentation field is regarded as one of most established fields, still fully automatic segmentation to extract target object with high accuracy from intravascular ultrasound (IVUS) is very active area of research. In this paper, we propose a fully automatic morphological approach using Bezier curve in interpolating the boundaries of intima/adventitia of the vessel from IVUS with careful binarization algorithms. In experiment with 800 IVUS images, the proposed method is as good as fuzzy C-means based approach in comparison with human expert’s result with 84.4% satisfaction and better than other morphological method in all performance indices of curve fitting with 97.02% in accuracy and 58.19% in precision.
Formalization of the prediction and ranking of software development life cycle models Laiali Almazaydeh; Moath Alsafasfeh; Reyad Alsalameen; Shoroq Alsharari
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i1.pp534-540

Abstract

The study of software engineering professional practices includes the use of the formal methodology in a software development. Identifying the appropriate methodology will not only reduce the failure of software but will also help to deliver the software in accordance with the predetermined budget and schedule. In literature, few works have been developed a tool for prediction of the most appropriate methodology for the specific software project. In this paper, a method for selecting an appropriate software development life cycle (SDLC) model based on a ranking manner from the highest to the lowest scoring is presented. The selection and ranking of appropriate SDLC elaborate the related SDLC’s critical factors, these factors are given different weights according to the SDLC, then these weights are used by the proposed mathematical method. The proposed approach has been extensively experimented on a dataset by software practitioners who are working in the software industry. Experimental results show that, the proposed method represents an applicable tool in predicting and ranking suitable SDLC models on various types of projects, such as: life-critical systems, commercial uses systems, and entertainment applications.
An index based road feature extraction from LANDSAT-8 OLI images Sama Lenin Kumar Reddy; C. V. Rao; P. Rajesh Kumar; R. V. G. Anjaneyulu; B. Gopala Krishna
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i2.pp1319-1336

Abstract

Road feature extraction from the remote sensing images is an arduous task and has a significant role in various applications of urban planning, updating the maps, traffic management, etc. In this paper, a new band combination (B652) to form a road index (RI) from OLI multispectral bands based on the spectral reflectance of asphalt, is presented for road feature extraction. The B652 is converted to road index by normalization. The morphological operators (top-hat or bottom-hat) uses on RI to enhance the roads. To sharpen the edges and for better discrimination of features, shock square filter (SSF), is proposed. Then, an iterative adaptive threshold (IAT) based online search with variational min-max and Markov random fields (MRF) model are used on the SSF image to segment the roads and non-roads. The roads are extracting by using the rules based on the connected component analysis. IAT and MRF model segmentation methods prove the proposed index (RI) able to extract road features productively. The proposed methodology is a combination of saturation based adaptive thresholding and morphology (SATM), and saturation based MRF (SMRF), applied to OLI images of several urban cities of India, producing the satisfactory results. The experimental results with the quantitative analysis presented in the paper.

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