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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

270 271 272 273 274

Finding Bad Code Smells with Neural Network Models Dong Kwan Kim
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 6: December 2017
Publisher : Institute of Advanced Engineering and Science

Code smell refers to any symptom introduced in design or implementation phases in the source code of a program. Such a code smell can potentially cause deeper and serious problems during software maintenance. The existing approaches to detect bad smells use detection rules or standards using a combination of different object-oriented metrics. Although a variety of software detection tools have been developed, they still have limitations and constraints in their capabilities. In this paper, a code smell detection system is presented with the neural network model that delivers the relationship between bad smells and object-oriented metrics by taking a corpus of Java projects as experimental dataset. The most well-known object-oriented metrics are considered to identify the presence of bad smells. The code smell detection system uses the twenty Java projects which are shared by many users in the GitHub repositories. The dataset of these Java projects is partitioned into mutually exclusive training and test sets. The training dataset is used to learn the network model which will predict smelly classes in this study. The optimized network model will be chosen to be evaluated on the test dataset. The experimental results show when the modelis highly trained with more dataset, the prediction outcomes are improved more and more. In addition, the accuracy of the model increases when it performs with higher epochs and many hidden layers.

Design of smart wireless changeover for continuous electric current feeding from power sources of variable capacities Haider A. H. Alobaidy; Hikmat N. Abdullah; Tariq M. Salman
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Electric power has become a vital element for life today. Despite this importance, electric power consumers in Iraq suffer from the problem of noncontinuity and daily electric power supply interruption. This problem led to the use of various sources of electric power as an alternative to compensate for the shortage of electric power provided by the Iraqi national grid. In this work, a smart wireless changeover device is designed using wireless sensor networks technology aiming to solve problem caused by the multiplicity of power sources received at home and governmental buildings in Iraq by controlling operation of some electrical devices (which consume high current) in the home or workplace automatically when changing source of electricity from one to another. This solution will help to ensure the continuity of electric current feeding from power sources of variable capacities, also, to rationalize power consumption by assigning an operation priority to electric devices. Furthermore, a statistical measurement as a case study was performed in a building with a total power consumption of 160.8 KW/h. The result showed that the device functions effectively and it is capable of achieving an average saving in power of about 50% to 86% depending on the applied priorities and case study scenario.

FEM Analysis of Squirrel Cage Induction Motor Fed with Raised Sine Wave Supply Balakrishnan M S; Theagarajan R
International Journal of Electrical and Computer Engineering (IJECE) Vol 3, No 2: April 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (387.458 KB)

AC motors are used frequently for many industrial applications such as material handling, traction, electric vehicles etc. A novel non-sinusoidal modulation technique employing Raised Sine Wave (RSW) for the PWM inverter is proposed in this paper. Squared Sine Wave has a distinct advantage of reduced rate of change at zero crossing of each half cycle, and eliminates the need for dead band. An Finite Element Analysis (FEM) is carried out to study its suitability for AC Induction Motor. The results show that the operation has a constant startup torque for all load conditions, thus providing a smooth start from zero speed to full rated speed. This feature makes it most suitable for applications requiring frequent startup such as traction. The operation of the conventional Variable Frequency Drives using Conventional Sine Wave (CSW) is compared with the results obtained with RSW supply.DOI:http://dx.doi.org/10.11591/ijece.v3i2.1705

Blind separation of complex-valued satellite-AIS data for marine surveillance: a spatial quadratic time-frequency domain approach Omar Cherrak; Hicham Ghennioui; Nadege Thirion Moreau; El Hossein Abarkan
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science

In this paper, the problem of the blind separation of complex-valued Satellite-AIS data for marine surveillance is addressed. Due to the specific properties of the sources under consideration: they are cyclo-stationary signals with two close cyclic frequencies, we opt for spatial quadratic time-frequency domain methods. The use of an additional diversity, the time delay, is aimed at making it possible to undo the mixing of signals at the multi-sensor receiver. The suggested method involves three main stages. First, the spatial generalized mean Ambiguity function of the observations across the array is constructed. Second, in the Ambiguity plane, Delay-Doppler regions of high magnitude are determined and Delay-Doppler points of peaky values are selected. Third, the mixing matrix is estimated from these Delay-Doppler regions using our proposed non-unitary joint zero-(block) diagonalization algorithms as to perform separation.

Face Recognition Based on Symmetrical Half-Join Method using Stereo Vision Camera Edy Winarno; Agus Harjoko; Aniati Murni Arymurthy; Edi Winarko
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 6: December 2016
Publisher : Institute of Advanced Engineering and Science

The main problem in face recognition system based on half-face pattern is how to anticipate poses and illuminance variations to improve recognition rate. To solve this problem, we can use two lenses on stereo vision camera in face recognition system. Stereo vision camera has left and right lenses that can be used to produce a 2D image of each lens. Stereo vision camera in face recognition has capability to produce two of 2D face images with a different angle. Both angle of the face image will produce a detailed image of the face and better lighting levels on each of the left and right lenses. In this study, we proposed a face recognition technique, using 2 lens on a stereo vision camera namely symmetrical half-join. Symmetrical half-join is a method of normalizing the image of the face detection on each of the left and right lenses in stereo vision camera, then cropping and merging at each image. Tests on face recognition rate based on the variety of poses and variations in illumination shows that the symmetrical half-join method is able to provide a high accuracy of face recognition and can anticipate variations in given pose and illumination variations. The proposed model is able to produce 86% -97% recognition rate on a variety of poses and variations in angles between 0 °- 22.5 °. The variation of illuminance measured using a lux meter can result in 90% -100% recognition rate for the category of at least dim lighting levels (above 10 lux).

A Graph-based approach for text query expansion using pseudo relevance feedback and association rules mining Siham Jabri; Azzeddine Dahbi; Taoufiq Gadi
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

Pseudo-relevance feedback is a query expansion approach whose terms are selected from a set of top ranked retrieved documents in response to the original query. However, the selected terms will not be related to the query if the top retrieved documents are irrelevant. As a result, retrieval performance for the expanded query is not improved, compared to the original one. This paper suggests the use of documents selected using Pseudo Relevance Feedback for generating association rules. Thus, an algorithm based on dominance relations is applied. Then the strong correlations between query and other terms are detected, and an oriented and weighted graph called Pseudo-Graph Feedback is constructed. This graph serves for expanding original queries by terms related semantically and selected by the user. The results of the experiments on Text Retrieval Conference (TREC) collection are very significant, and best results are achieved by the proposed approach compared to both the baseline system and an existing technique.

Network Function Modeling and Performance Estimation Mario Baldi; Amedeo Sapio
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

This work introduces a methodology for the modelization of network functions focused on the identification of recurring execution patterns as basic building blocks and aimed at providing a platform independent representation. By mapping each modeling building block on specific hardware, the performance of the network function can be estimated in termsof maximum throughput that the network function can achieve on the specific execution platform. The approach is such that once the basic modeling building blocks have been mapped, the estimate can be computed automatically for any modeled network function. Experimental results on several sample network functions show that although our approach cannot be very accurate without taking in consideration traffic characteristics, it is very valuable for those application where even loose estimates are key. One such example is orchestration in network functions virtualization (NFV) platforms, as well as in general virtualization platforms where virtual machine placement is based also on the performanceof network services offered to them. Being able to automatically estimate the performance of a virtualized network function (VNF) on different execution hardware, enables optimal placement of VNFs themselves as well as the virtual hosts they serve, while efficiently utilizing available resources.

Comprehensive identification of sensitive and stable ISFET sensing layer high-k gate based on ISFET/electrolyte models Ahmed M. Dinar; A. S. Mohd Zain; F. Salehuddin
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 2: April 2019
Publisher : Institute of Advanced Engineering and Science

The ISFET sensing membrane is in direct contact with the electrolyte solution, determining the starting sensitivity of these devices. A SiO2 gate dielectric shows a low response sensitivity and poor stability. This paper proposes a comprehensive identification of different high-k materials which can be used for this purpose, rather than SiO2. The Gouy-Chapman and Gouy-Chapman-Stern models were combined with the Site-binding model, based on surface potential sensitivity, to achieve the work objectives. Five materials, namely Al2O3, Ta2O5, Hfo2, Zro2 and SN2O3, which are commonly considered for micro-electronic applications, were compared. This study has identified that Ta2O5 have a high surface potential response at around 59mV/pH, and also exhibits high stability in different electrolyte concentrations. The models used have been validated with real experimental data, which achieved excellent agreement. The insights gained from this study may be of assistance to determine the suitability of different materials before progressing to expensive real ISFET fabrication.

Evaluation of Integrated Digital Forensics Investigation Framework for the Investigation of Smartphones Using Soft System Methodology Ruuhwan Ruuhwan; Imam Riadi; Yudi Prayudi
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

The handling of digital evidence can become an evidence of a determination that crimes have been committed or may give links between crime and its victims or crime and the culprit. Soft System Methodology (SSM) is a method of evaluation to compare a conceptual model with a process in the real world, so deficiencies of the conceptual model can be revealed thus it can perform corrective action against the conceptual model, thus there is no difference between the conceptual model and the real activity. Evaluation on the IDFIF stage is only done on a reactive and proactive process stages in the process so that the IDFIF model can be more flexible and can be applied on the investigation process of a smartphone.

An educational fuzzy temperature control system Peshraw Salam; Dogan Ibrahim
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Control engineering is one of the important engineering topics taught at many engineering based universities around the world in most undergraduate and postgraduate courses. The control engineering curriculum includes both the classical feedback based control theory and the state space theory. The modern control theory is based on the intelligent control algorithms utilizing the soft computing techniques, such as the fuzzy control theory and neural networks. Laboratory work is an important part of any control engineering course. The problem with the modern control theory laboratories is that it is essential to offer simple experiments to students so that they can easily put the complex theories they have learned in their courses into practice and see and understand the results. This paper describes the design of a low-cost fuzzy based microcontroller temperature control system using off the shelf products. The developed system should provide a low-cost fuzzy control experiment in the laboratories for students studying control engineering.

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Home Page

OAI Link

Editorial Team

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Contact Name Tole Sutikno

Contact Email ijece@iaesjournal.com

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Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

Abstract

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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