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International Journal of Electrical and Computer Engineering

IJECE
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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 6,301 Documents

292 293 294 295 296

Unit vector template generator applied to a new control algorithm for an UPQC with instantaneous power tensor formulation, a simulation case study Yeison Alberto Garcés Gómez; Nicolás Toro García; Fredy Edimer Hoyos
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

In this paper we present a new algorithm to generate the reference signals to control the series and parallel power inverters in an unified power quality conditioner “UPQC” to enhance power quality. The algorithm is based in the instantaneous power tensor formulation which it is obtained by the dyadic product between the instantaneous vectors of voltage and current in n-phase systems. The perfect harmonic cancelation algorithm “PHC” to estimate the current reference in a shunt active power filter was modified to make it hardy to voltage sags through unit vector template generation “UVGT” while from the same algorithm it extracts the voltage reference for series active power filter. The model was validated by mean of simulations in Matlab-Simulink®.

Glioblastomas brain tumour segmentation based on convolutional neural networks Moh'd Rasoul Al-Hadidi; Bayan AlSaaidah; Mohammed Al-Gawagzeh
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Brain tumour segmentation can improve diagnostics efficiency, rise the prediction rate and treatment planning. This will help the doctors and experts in their work. Where many types of brain tumour may be classified easily, the gliomas tumour is challenging to be segmented because of the diffusion between the tumour and the surrounding edema. Another important challenge with this type of brain tumour is that the tumour may grow anywhere in the brain with different shape and size. Brain cancer presents one of the most famous diseases over the world, which encourage the researchers to find a high-throughput system for tumour detection and classification. Several approaches have been proposed to design automatic detection and classification systems. This paper presents an integrated framework to segment the gliomas brain tumour automatically using pixel clustering for the MRI images foreground and background and classify its type based on deep learning mechanism, which is the convolutional neural network. In this work, a novel segmentation and classification system is proposed to detect the tumour cells and classify the brain image if it is healthy or not. After collecting data for healthy and non-healthy brain images, satisfactory results are found and registered using computer vision approaches. This approach can be used as a part of a bigger diagnosis system for breast tumour detection and manipulation.

Artificial neural network based unity power factor corrector for single phase DC-DC converters Hussain Attia
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Due to the negative effects of the non-linear semiconductor devices and the passive electrical components (inductor and capacitor) in the converter circuits, and that are deteriorating the power factor (PF) and total harmonics distortion (THD) of grid current, this study proposes a novel unity PF correction controller based on a new algorithm of neural network to improve the performance of a single phase boost DC-DC converter with respect to the mentioned concerns. The controller guarantees stable load voltage. The PF corrector, firstly measures the phase shift between grid voltage and grid current waveforms, then through a new artificial neural network (ANN) algorithm, a suitable duty cycle is predicted to guide and control the converter to reduce the phase shift between grid voltage and grid current as possible to have maximum PF which is unity PF, and to improve the THD level of grid current. The proposed system is simulated and evaluated via Simulink of MATLAB, the simulation results are collected at constant duty cycle and at controlled duty cycle through the proposed PF controller using different loads. The presented PF controller guarantees the unity power factor, and enhances the grid alternating current THD.

Texture classification of fabric defects using machine learning Yassine Ben Salem; Mohamed Naceur Abdelkrim
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

In this paper, a novel algorithm for automatic fabric defect classification was proposed, based on the combination of a texture analysis method and a support vector machine SVM. Three texture methods were used and compared, GLCM, LBP, and LPQ. They were combined with SVM’s classifier. The system has been tested using TILDA database. A comparative study of the performance and the running time of the three methods was carried out. The obtained results are interesting and show that LBP is the best method for recognition and classification and it proves that the SVM is a suitable classifier for such problems. We demonstrate that some defects are easier to classify than others.

Modelling turn away intention of information technology professionals in Bangladesh: a partial least squares approach Md. Shohel Arman; Rozina Akter; Imran Mahmud; T. Ramayah
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Despite, Bangladesh produces many IT graduates each year but only one tenth of total graduates contribute in IT development sector. In order to keep the contribution to economy through IT development, it is crucial for IT industry to know the factors that influence turn away of IT graduates. In this paper, building upon role stress theory, we develop a research model to explore the influence of workplace exhaustion and threat of professional obsolescence (TPO). Data were gathered from 185 IT professionals from 15 different IT companies through survey questionnaire. The structural equation modelling technique was used to test the paths. The results suggests that strong influence of TPO on turn-away intentions. Result also suggests significant roles of work overload, family-career conflict and control over career and workplace exhaustion on turn away intention. This paper contributes to the body of work dedicated to helping us better understand the turn away behaviour from the workplace exhaustion and TPO perspectives. From the viewpoint of practice, this research sheds light on some of the challenges that the IT industry might face when making strategy and policy to control turn away from IT profession in Bangladesh

The resistance of routing protocols against DDOS attack in MANET Maha Abdelhaq; Raed Alsaqour; Mada Alaskar; Fayza Alotaibi; Rawan Almutlaq; Bushra Alghamdi; Bayan Alhammad; Malak Sehaibani; Donia Moyna
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

A Mobil Ad hoc Network (MANET) is a wireless multi-hop network with various mobile, self-organized and wireless infrastructure nodes. MANET characteristics such as openness restricted resources and decentralization impact node efficiency and made them easy to be affected by various security attacks, especially Distributed Denial of Service (DDoS) attacks. The goal of this research is to implement a simulation model called DDoS Attack Simulation Model (DDoSM) in Network Simulator 2(NS-2) and to examine the effect of DDoS Attack on various routing protocol types in MANET namely: Zone Routing Protocol (ZRP), Ad hoc On-Demand Distance Vector (AODV) protocol and Location-Aided Routing (LAR) protocol. The introduced model uses the NS-2 simulator to apply DDoS on the three chosen routing protocols. In terms of throughput and end-to-end latency under the consequences of the attack, the performance of three routings protocols was analyzed.

The effects of multiple layers feed-forward neural network transfer function in digital based Ethiopian soil classification and moisture prediction Belete Biazen Bezabeh; Abrham Debasu Mengistu
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

In the area of machine learning performance analysis is the major task in order to get a better performance both in training and testing model. In addition, performance analysis of machine learning techniques helps to identify how the machine is performing on the given input and also to find any improvements needed to make on the learning model. Feed-forward neural network (FFNN) has different area of applications, but the epoch convergences of the network differs from the usage of transfer function. In this study, to build the model for classification and moisture prediction of soil, rectified linear units (ReLU), Sigmoid, hyperbolic tangent (Tanh) and Gaussian transfer function of feed-forward neural network had been analyzed to identify an appropriate transfer function. Color, texture, shape and brisk local feature descriptor are used as a feature vector of FFNN in the input layer and 4 hidden layers were considered in this study. In each hidden layer 26 neurons are used. From the experiment, Gaussian transfer function outperforms than ReLU, sigmoid and tanh transfer function. But the convergence rate of Gaussian transfer function took more epoch than ReLU, Sigmoid and tanh.

Review of high-speed phase accumulator for direct digital frequency synthesizer Abdulkareem Dawah Abbas
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

A review of high-speed pipelined phase accumulator (PA) is proposed in this paper. The detail explanation of ideas, methods and techniques used in previous researches to improve the PA throughput designs were surveyed. The Brent–Kung (BK) adder was modified in this paper to be applied in pipelined PA architecture. A comparison of different adder circuits, includes a modified BK, ripple carry adder (RCA), Kogge-Stone adder (KS) and other prefix adders were applied to architect the PA based on Pipeline technique. The presented pipelined PA design circuit with multiple frequency control word (FCW) and different adders were coded Verilog hardware description language (HDL) code, compiled and verified with field programmable gate array (FPGA) kit platform. The comparison result shows that the modified BK adder has fast performances. The shifted clocking technique is utilized in the proposed pipelined PA circuit to reduce the unwanted repetitive D-flip flop (DFF) registers (coming from the pipeline technique), while preserving the high speed.

The effect of recovery satisfaction on citizens loyalty perception: a case study of mobile government services Ibrahim Almarashdeh
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Use of mobile services is an integral part of today’s life. Organizations, government agencies as well as service providers in the market employ mobile services or application in reaching their citizens or users worldwide. Notably, service failure issues might frustrate users in using mobile service, but usually, service providers would employ the strategy of recovery as solution. Recovery strategy aims to sustain the relationship with users following service failure. Somehow, the factors that might impact recovery process are unclear. It is also unclear if users will use the service again following the completion of recovery process. Hence, in this study, a survey on 743 adults was carried out, and the data were analyzed using SEM to determine the factors that impact users’ recovery satisfaction the most and the impact of recovery satisfaction on citizens loyalty to use mobile government in the future. The finding of this study illustrated that expect of self-efficacy, all factors proposed in the research model found to has a significant impact on recovery satisfaction. Among all the supported hypothesis, the highest impact on recovery satisfaction comes from perceived trust in government as the initial predictor to use the service

Computational scrutiny of image denoising method found on DBAMF under SPN surrounding Vorapoj Patanavijit
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Traditionally, rank order absolute difference (ROAD) has a great similarity capacity for identifying whether the pixel is SPN or noiseless because statistical characteristic of ROAD is desired for a noise identifying objective. As a result, the decision based adaptive median filter (DBAMF) that is found on ROAD technique has been initially proposed for eliminating an impulsive noise since 2010. Consequently, this analyzed report focuses to examine the similarity capacity of denoising method found on DBAMF for diverse SPN Surrounding. In order to examine the denoising capacity and its obstruction of the denoising method found on DBAMF, the four original digital images, comprised of Airplane, Pepper, Girl and Lena, are examined in these computational simulation for SPN surrounding by initially contaminating the SPN with diverse intensity. Later, all contaminated digital images are denoised by the denoising method found on DBAMF. In addition, the proposed denoised image, which is computed by this DBAMF denoising method, is confronted with the other denoised images, which is computed by Standard median filter (SMF), Gaussian Filter and Adaptive median filter (AMF) for demonstrating the DBAMF capacity under subjective measurement aspect.

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Tole Sutikno

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Kota yogyakarta,

Daerah istimewa yogyakarta

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Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Tole Sutikno

Contact Email ijece@iaesjournal.com

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Journal Mail Official ijece@iaesjournal.com

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Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Tole Sutikno

Contact Email
ijece@iaesjournal.com

Phone
-

Journal Mail Official
ijece@iaesjournal.com

Editorial Address
-

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA