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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 116 Documents
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Search results for , issue "Vol 10, No 6: December 2020" : 116 Documents clear
Identification of interstitial lung diseases using deep learning Nidhin Raju; Anita H. B.; Peter Augustine
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v10i6.pp6283-6291

Abstract

The advanced medical imaging provides various advantages to both the patients and the healthcare providers. Medical Imaging truly helps the doctor to determine the inconveniences in a human body and empowers them to make better choices. Deep learning has an important role in the medical field especially for medical image analysis today. It is an advanced technique in the machine learning concept which can be used to get efficient output than using any other previous techniques. In the anticipated work deep learning is used to find the presence of interstitial lung diseases (ILD) by analyzing high-resolution computed tomography (HRCT) images and identifying the ILD category. The efficiency of the diagnosis of ILD through clinical history is less than 20%. Currently, an open chest biopsy is the best way of confirming the presence of ILD. HRCT images can be used effectively to avoid open chest biopsy and improve accuracy. In this proposed work multi-label classification is done for 17 different categories of ILD. The average accuracy of 95% is obtained by extracting features with the help of a convolutional neural network (CNN) architecture called SmallerVGGNet.
A generalized switching function-based SVM algorithm of single-phase three-leg converter with active power decoupling Watcharin Srirattanawichaikul
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v10i6.pp6189-6201

Abstract

In this paper, a generalized switching function-based space vector modulation (SVM) algorithm is presented and evaluated to minimize the dc voltage utilization and the ac utility grid current total harmonic distortion. This paper explores the control and modulation techniques of a single-phase three-leg converter with an active power decoupling method, where a generalized SVM algorithm is proposed and evaluated for easy implementation in a digital control platform. The active power decoupling method with the proposed converter can be achieved via dependent control and modulation techniques. The control method is separated into the ac active power control part and the dc power ripple control part, which can maintain a unity power factor at the ac utility grid and reduced the double-frequency ripple power effect on the dc-side. Simulation results validate the performance of the modulation algorithm and its control and demonstrate the feasibility of the proposed power converter, as well as the two mentioned operation modes of the power converter.
Software engineering based self-checking process for cyber security system in VANET Muntadher Naeem Yasir; Muayad Sadik Croock
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1328.568 KB) | DOI: 10.11591/ijece.v10i6.pp5844-5852

Abstract

Newly, the cyber security of Vehicle Ad hoc Network (VANET) includes two practicable: Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I), that have been considered due to importance. It has become possible to keep pace with the development in the world. The people safety is a priority in the development of technology in general and particular in of VANET for police vehicles. In this paper, we propose a software engineering based self-checking process to ensure the high redundancy of the generated keys. These keys are used in underlying cyber security system for VANET. The proposed self-checking process emploies a set of NIST tests including frequency, block and runs as a threshold for accepting the generated keys. The introduced cyber security system includes three levels: Firstly, the registration phase that asks vehicles to register in the system, in which the network excludes the unregistered ones. In this phase, the proposed software engineeringbased self-checking process is adopted. Secondly, the authentication phase that checks of the vehicles after the registration phase. Thirdly, the proposed system that is able to detect the DOS attack. The obtained results show the efficient performance of the proposed system in managing the security of the VANET network. The self-checking process increased the randomness of the generated keys, in which the security factor is increased.
Temperature characteristics of FinFET based on channel fin width and working voltage Yousif Atalla; Yasir Hashim; Abdul Nasir Abd. Ghafar; Waheb A. Jabbar
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (693.526 KB) | DOI: 10.11591/ijece.v10i6.pp5650-5657

Abstract

This paper shows the temperature sensitivity of FinFET and the possibility of using FinFET as a temperature Nano sensor based on Fin width of transistor. The multi-gate field effect transistor (MuGFET) simulation tool is used to examine the temperature effect on FinFET characteristics. Current-voltage characteristics with various temperatures and channel Fin width (WF= 5,10,20,40 and 80 nm) are at first simulated, the diode mode connection has been used in this study. The best temperature sensitivity of the FinFET is has been considered under the biggest ∆I at the working voltage VDD with range of 0–5 V. According to the results, the temperature sensitivity increased linearly with all the range of channel Fin width (5-80 nm), also, the lower gate Fin width (WF=5nm) with higher sensitivity can achieved with lower working voltage (VDD=1.25 V).
Development modeling methods of analysis and synthesis of fingerprint deformations images Haider Hassan Majeed AlKaraawi; Mohammed Qasim Dhahir; Ibrahim Ahmed Alameri; Mowafak K. Mohsen
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1351.874 KB) | DOI: 10.11591/ijece.v10i6.pp6053-6060

Abstract

The current study is to develop modeling methods, Analysis and synthesis of fingerprints deformations images and their application in problems of automatic fingerprint identification. In the introduction justified urgency of the problem, is given a brief description of thematic publications. In this study will review of modern technologies of biometric technologies and methods of biometric identification, the review of fingerprint identification systems, investigate for distorting factors. The influence of deformations is singled out, the causes of deformation of fingerprints are analyzed. The review of modern ways of the account and modeling of deformations in problems of automatic fingerprint identification is given. The scientific novelty of the work is the development of information technologies for the analysis and synthesis of deformations of fingerprint images. The practical value of the work in the application of the developed methods, algorithms and information technologies in fingerprints identification systems. In addition, it has been found that our paper "devoted to research methods and synthesis of the fingerprint deformations" is a more appropriate choice than other papers.
PSO-CCO_MIMO-SA: A particle swarm optimization based channel capacity optimzation for MIMO system incorporated with smart antenna Shivapanchakshari T. G.; H. S. Aravinda
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v10i6.pp6276-6282

Abstract

With the radio channels physical limits, achieving higher data rate in the multi-channel systems is been a biggest concern. Hence, various spatial domain techniques have been introduced by incorporating array of antenna elements (i.e., smart antenna) in recent past for the channel limit expansion in mobile communication antennas. These smart antennas help to yield the improved array gain or bearm forming gain and hence by power efficiency enhanmaent in the channel and antenna range expansion. The use of smart antenna leads to spatial diversity and minimizes the fading effect and improves link reliability. However, in the process of antenna design, the proper channel modelling is is biggest concern which affect the wireless system performance. The recent works of MIMO design systems have discussed the issues in number of antenna selection which suggests that optimization of MIMO channel capacity is required. Hence, a Particle Swarm Optimization based channel capacity optimzation for MIMO system incorporated with smart antenna is introduced in this paper. From the outcomes it is been found that the proposed PSO based MIMO system achieves better convergenece speed which results in better channel capacity.
Optimal planning of RDGs in electrical distribution networks using hybrid SAPSO algorithm Mohammed Hamouda Ali; Mohammed Mehanna; Elsaied Othman
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v10i6.pp6153-6163

Abstract

The impact of the renewable distributed generations (RDGs), such as photovoltaic (PV) and wind turbine (WT) systems can be positive or negative on the system, based on the location and size of the DG. So, the correct location and size of DG in the distribution network remain an obstacle to achieving their full possible benefits. Therefore, the future distribution networks with the high penetration of DG power must be planned and operated to improve their efficiency. Thus, this paper presents a new methodology for integrated of renewable energy-based DG units with electrical distribution network. Since the main objective of the proposed methodology is to reduce the power losses and improve the voltage profile of the radial distribution system (RDS). In this regard, the optimization problem was formulated using loss sensitivity factor (LSF), simulated annealing (SA), particle swarm optimization (PSO) and a combination of loss sensitivity index (LSI) with SA & PSO (LSISA, LSIPSO) respectively. This paper contributes a new methodology SAPSO, which prevents the defects of SA & PSO. Optimal placement and sizing of renewable energy-based DG tested on 33-bus system. The results demonstrate the reliability and robustness of the proposed SAPSO algorithm to find the near-optimal position and size of the DG units to mitigate the power losses and improve the radial distribution system's voltage profile.
Evaluation of non-parametric identification techniques in second order models plus dead time Carlos Robles-Algarín; Omar Rodríguez; Adalberto Ospino
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v10i6.pp6340-6348

Abstract

In this paper, a set of non-parametric identification techniques are used in order to obtain second order models plus dead time for an underdamped system. Initially, non-parametric techniques were used to identify the system from the temperature data of a coal-heated oven. In this case, the identification techniques proposed by Stark, Jahanmiri - Fallahi and Ogata were used, which require obtaining two or three points of the step response for the system under study. In addition, the Matlab PID Tuner app was used to identify the underdamped system and compare the results with the other methods. The results show that the PID Tuner and the method proposed by Ogata are the ones that best represent the dynamics of the underdamped system, taking into account the values for the Integral Absolute Error (IAE) and the correlation coefficient. With the Stark method an IAE of 181.56 was obtained, while with the PID Tuner the best performance was achieved with an IAE of 21.59. In terms of the results obtained with the cross correlation, the best performance was achieved with the PID tuner and the Stark method.
Investigating a theoretical framework for e-learning technology acceptance Barween Al Kurdi; Muhammad Alshurideh; Said A. Salloum
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v10i6.pp6484-6496

Abstract

E-learning has gained recognition and fame in delivering and distributing educational resources, and the same has become possible with the occurrence of Internet and Web technologies. The research seeks to determine the factors that influence students' acceptance of E-learning and to find out the way these factors determine the students' intention to employ E-learning. A theoretical framework was developed based on the technology acceptance model (TAM). To obtain information from the 270 university students who utilized the E-learning system, a questionnaire was formulated. The results revealed that “social influence, perceived enjoyment, self-efficacy, perceived usefulness, and perceived ease of use” are the strongest and most important predictors in the intention of and students towards E-learning systems. The outcomes offer practical implications for practitioners, lawmakers, and developers in effective E-learning systems implementation to improve ongoing interests and activities of university students in a virtual E-learning atmosphere, valuable recommendations for E-learning practices are given by the research findings, and these may turn out to be as guidelines for the efficient design of E-learning systems.
Motion artifacts reduction in cardiac pulse signal acquired from video imaging Murthad Al-Yoonus; Mustafa H. Alhabib; Mustafa Zuhaer Nayef Al-Dabagh; M. F. L. Abdullah
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1162.675 KB) | DOI: 10.11591/ijece.v10i6.pp5687-5693

Abstract

This study examines the possibility of remotely measuring the cardiac pulse activity of a patient, which could be an alternative technique to the classical method. This type of measurement is non-invasive. However, several limitations may deteriorate the accuracy of the results, including changes in ambient illumination, motion artifacts (MA) and other interferences that may occur through video recording. The paper in hand presents a new approach as a remedy for the aforementioned problem in cardiac pulse signals extracted from facial video recordings. Partitioning provides the basis for the presented MA reduction method; the acquired signals are partitioned into two sets for each second and every partition is shifted to the mean level and then all the partitions are recombined again into one signal, which is followed by low-pass filtering for enhancement. The proposed compared with ordinary pulse oximetry Photoplethysmographic (PPG) method. The resulted correlation coefficient was found (0.957) when calculated between the results of the proposed method and the ordinary one. Experiments were implemented using a common camera by creating a dataset from 11 subjects. The ease of implementation of this method with a simple that can be used to monitor the cardiac pulse rates in both home and the clinical environments.

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