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
6,393 Documents
Machine learning-based energy consumption modeling and comparison of H.264/AVC and google VP8 encoders
Yousef O. Sharrab;
Mohammad Alsmirat;
Bilal Hawashin;
Nabil Sarhan
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.pp1303-1310
Advancement of the prediction models used in a variety of fields is a result of the contribution of machine learning approaches. Utilizing such modeling in feature engineering is exceptionally imperative and required. In this research, we show how to utilize machine learning to save time in research experiments, where we save more than five thousand hours of measuring the energy consumption of encoding recordings. Since measuring the energy consumption has got to be done by humans and since we require more than eleven thousand experiments to cover all the combinations of video sequences, video bit_rate, and video encoding settings, we utilize machine learning to model the energy consumption utilizing linear regression. VP8 codec has been offered by Google as an open video encoder in an effort to replace the popular MPEG-4 Part 10, known as H.264/AVC video encoder standard. This research model energy consumption and describes the major differences between H.264/AVC and VP8 encoders in terms of energy consumption and performance through experiments that are based on machine learning modeling. Twenty-nine raw video sequences are used, offering a wide range of resolutions and contents, with the frame sizes ranging from QCIF(176x144) to 2160p(3840x2160). For fairness in comparison analysis, we use seven settings in VP8 encoder and fifteen types of tuning in H.264/AVC. The settings cover various video qualities. The performance metrics include video qualities, encoding time, and encoding energy consumption.
Target-based test path prioritization for UML activity diagram using weight assignment methods
Sornkliang, Walaiporn;
Phetkaew, Thimaporn
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i1.pp575-588
The benefit of exploratory testing and ad hoc testing by tester’s experience is that crucial bugs are found quickly. Regression testing and test case prioritization are important processes of software testing when software functions have been changed. We propose a test path prioritization method to generate a sequence of test paths that would match the testers’ interests and focuses on the target area of interest or on the changed area. We generate test paths form the activity diagrams and survey the test path prioritization from testers. We define node and edge weight to the symbols of activity diagrams by applying Time management, Pareto, Buffett, Binary, and Bipolar method. Then we propose a test path score equation to prioritize test paths. We also propose evaluation methods i.e., the difference and the similarity of test path prioritization to testers’ interests. Our proposed method had the least average of the difference and the most average of the similarity compare with the tester’s prioritization of test paths. The Bipolar method was the most suitable for assigning weights to match test path rank by the tester. Our proposed method also has given the affected path by changing area higher priority than the other test path.
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
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DOI: 10.11591/ijece.v10i6.pp5844-5852
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.
Low power pseudo-random number generator based on lemniscate chaotic map
Saber, Mohamed;
Eid, Marwa M.
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i1.pp863-871
Lemniscate chaotic map (LCM) provides a wide range of control parameters, canceling the need for several rounds of substitutions, and excellent performance in the confusion process. Unfortunately, the hardware model of LCM is complex and consumes high power. This paper presents a proposed low power hardware model of LCM called practical lemniscate chaotic map (P-LCM) depending on trigonometric identities to reduce the complexity of the conventional model. The hardware model designed and implement into the field programmable gate array (FPGA) board, Spartan-6 SLX45FGG484-3. The proposed model achieves a 48.3 % reduction in used resources and a 34.6 % reduction in power consumption compared to the conventional LCM. We also introduce a new pseudo-random number generator based on a proposed low power P-LCM model and perform the randomization tests for the proposed encryption system.
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
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DOI: 10.11591/ijece.v10i6.pp5650-5657
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).
Voltage collapse prediction using artificial neural network
Isaac, Samuel;
Adebola, Soyemi;
Ayokunle, Awelewa;
James, Katende;
Claudius, Awosope
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i1.pp124-132
Unalleviated voltage instability frequently results in voltage collapse; which is a cause of concern in power system networks across the globe but particularly in developing countries. This study proposed an online voltage collapse prediction model through the application of a machine learning technique and a voltage stability index called the new line stability index (NLSI_1). The approach proposed is based on a multilayer feed-forward neural network whose inputs are the variables of the NLSI_1. The efficacy of the method was validated using the testing on the IEEE 14-bus system and the Nigeria 330-kV, 28-bus National Grid (NNG). The results of the simulations indicate that the proposed approach accurately predicted the voltage stability index with an R-value of 0.9975 with a mean square error (MSE) of 2.182415x10−5 for the IEEE 14-bus system and an R-value of 0.9989 with an MSE of 1.2527x10−7 for the NNG 28 bus system. The results presented in this paper agree with those found in the literature.
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
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DOI: 10.11591/ijece.v10i6.pp6053-6060
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
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DOI: 10.11591/ijece.v10i6.pp6276-6282
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.
Sustainable governance in smart cities and use of supervised learning based opinion mining
Iqbal, Hena;
Paul, Sujni;
Khan, Khaliquzzaman
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i1.pp489-497
Evaluation is an analytical and organized process to figure out the present positive influences, favourable future prospects, existing shortcomings and ulterior complexities of any plan, program, practice or a policy. Evaluation of policy is an essential and vital process required to measure the performance or progression of the scheme. The main purpose of policy evaluation is to empower various stakeholders and enhance their socio-economic environment. A large number of policies or schemes in different areas are launched by government in view of citizen welfare. Although, the governmental policies intend to better shape up the life quality of people but may also impact their every day’s life. A latest governmental scheme Saubhagya launched by Indian government in 2017 has been selected for evaluation by applying opinion mining techniques. The data set of public opinion associated with this scheme has been captured by Twitter. The primary intent is to offer opinion mining as a smart city technology that harness the user-generated big data and analyse it to offer a sustainable governance model.
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
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DOI: 10.11591/ijece.v10i6.pp6153-6163
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.