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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 68 Documents
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Search results for , issue "Vol 20, No 1: October 2020" : 68 Documents clear
Classification of seizure and seizure free EEG signals using optimal mother wavelet and relative power Nilima Salankar; Sangita B. Nemade; Varsha P. Gaikwad
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 1: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i1.pp197-205

Abstract

This paper presents an approach for the selection of mother wavelet for classification of EEG epilepsy signals .Wavelet transform is very popular for analyzing signals in time and frequency domain. But as there are various wavelet families exist and not a one fits to all, in this study author have experimented with 51 wavelets from six different families haar (haar), daubechies (Db), symlet (Sym), coiflets (Coif), biorthogonal (Bior) and discrete meyer (Dmey). Optimal mother wavelet is selected on the basis of highest correlation between input signal and reconstructed signal. With Discrete wavelet transform four levels of decomposition have been used to create the five EEG rhythms delta, theta, alpha, beta and gamma. Five features kurtosis, skew, mean, standard deviation and relative power have been extracted from each decomposed level by using the optimal mother wavelet. Statistical significance of the extracted features has been computed by Mann Whitney U test with significance level p<0.05 and statistical parameters sensitivity, specificity and accuracy for performance evaluation of the classifier have been computed. Results shown that out of six experimented wavelet families, five families with eight wavelets have qualified the correlation test.  Out of five extracted feature relative power is more statistically significant for all type of classification and all EEG bands .Classifier used is support vector machine and accuracy of classifier lies in the range of 74% to 100 % for 14 classifications between different subsets.
A comparative analysis of an electronic exams versus paper exams between different gender of iraqi students Marwa M. Ismail; Bashar S. Bashar; Bashar B. Qas Elias
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 1: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i1.pp423-429

Abstract

When students believe they can get smarter, they understand that effort makes them stronger. Therefore, they put in extra time and effort, and that leads to higher achievement. Besides that, the arrangement of question papers and answer sheets process for a high number of students takes a long time. In this paper, the sheet exam has been proposed to change into an electric exam (E-exam). This system depended on the client-server framework to convert the traditional exam environment into an electronic exam, providing multiple and different questions at the same time. In additions, kept the grades of students and providing them automatically. In this paper, Visual Studio and Microsoft SQL server have been proposed to develop the electronic exam. The questionnaire is made by distributed it among 30 students, and after the data analysis, the results have been collected have been represented a response rate of 100%. It is recommended that, to take electronic exams and e-learning for students periodically. To improve their performance through continuous training on computerized exams and to increase the student’s efficiency in this type of learning.
Performance analysis of millimeter wave 5G networks for outdoor environment: propagation perspectives Naser Al-Falahy; Mohammed AlMahamdy; Ali M. Mahmood
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 1: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i1.pp214-221

Abstract

To cope with the massive growth in global mobile data traffic for 2020 and beyond, the fifth generation (5G) system is required to be developed as the current 4G system is expected to fall short behind the provision of such growth. 5G systems is anticipated to use millimeter wave (mm-wave) frequency bands (20 to 90) GHz, due to the availability of wide chunk of unexploited bandwidth. This is revolutionary step to use these bands because of their very different propagation conditions, atmospheric absorption and hardware constraints. However, such challenges could be compensated by means of beamforming/beamsteering and larger antenna array. In this paper, a comparative study aided with ray-tracing simulation has been performed to assess the feasibility of mm-wave in 5G system. Propagation characteristics of the 28GHz and 73 GHz bands have been studied and compared in a street canyon outdoor environment to simulate 5G outdoor mobile access. Simulation results were shown along with their comparison for both of the aforementioned frequencies. The results of propagation comparison have been reported in terms of path loss, k-factor, delay spread and received power for both 28 and 73 GHz bands.
Multiverse optimisation based technique for solving economic dispatch in power system Muhammad Haziq Suhaimi; Ismail Musirin; Muzaiyanah Hidayab; Shahrizal Jelani; Mohd Helmi Mansor
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 1: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i1.pp485-491

Abstract

Economic dispatch (ED) is one of the many important components in a power system operation. It is designed to calculate the exact amount of power generation needed to ensure a minimum cost of generation. A power system with multiple generators should be running under an economic condition. The operating cost has to be minimised for any feasible load demand. The increase of power demand is getting higher throughout the year. Economic dispatch is used to schedule and control all output of the fossil-fuel or coal-generators to satisfy the system load demand at a minimum cost. This paper presents the multiverse optimisation (MVO) for solving the economic dispatch in a power system. The proposed Multiverse optimisation engine developed in this study is implemented on the IEEE 30-Bus reliability test system (RTS). It has five generators, all of which are denoted as the control variables for the optimisation process. To reveal the superiority of MVO, a similar process was conducted using evolutionary programming (EP). Results from both techniques were compared, and it was revealed that MVO had outperformed EP in terms of reduced cost of generation for the system.
Support-vector machine and naïve bayes based diagnostic analytic of harmonic source identification Mohd Hatta Jopri; Abdul Rahim Abdullah; Jingwei Too; Tole Sutikno; Srete Nikolovski; Mustafa Manap
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 1: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i1.pp1-8

Abstract

A harmonic source diagnostic analytic is a vital to identify the location and type of harmonic source in the power system. This paper introduces a comparison of machine learning (ML) algorithm which are support vector machine (SVM) and naïve bayes (NB). Voltage and current features are used as the input for ML are extracted from time-frequency representation (TFR) of S-transform. Several unique cases of harmonic source location are considered, whereas harmonic voltage and harmonic current source type-load are used in the diagnosing process. To identify the best ML, the performance measurement of the propose method including accuracy, specificity, sensitivity, and F-measure are calculated. The adequacy of the proposed methodology is tested and verified on IEEE 4-bust test feeder and each ML algorithm is executed for 10 times due to different partitions and to prevent any overfitting result.
Assisted learning of C programming through automated program repair and feed-back generation Sara Mernissi Arifi; Rachid Ben Abbou; Azeddine Zahi
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 1: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i1.pp454-464

Abstract

Programming courses are among all the current academic curricula for engineering studies. Unfortunately, students often face difficulties already on the basic concepts. Both students and teachers believe that practical sessions and guided learning lead to good outcomes. On the other hand, it is virtually difficult considering the number of students enrolled on programming courses. This paper presents an automated assessment system for programming assignments, based on two different methods: static and dynamic analysis. The presented system aims at providing the student with an ongoing and various feedback delivered according to the category and the recurrence of errors. The system imbeds an automated error repairing feature for the purposes of insuring the assessment process achievement. It operates if the student fails to submit a correct program despite the feed-back provided by the system. In such cases, the system uses a penalty mechanism, customized by the teacher to grade the student’s program. Testing the presented automated system, through assessing real students’ assignments, showed promising results compared to manual assessment.
An efficient hybrid model for secure transmission of data by using efficient data collection and dissemination (EDCD) algorithm based WSN Mustafa Mahmood Akawee; Mohanad Ali Meteab Al-Obaidi; Haider Mohammed Turki Al-Hilfi; Sabbar Insaif Jassim; Tole Sutikno
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 1: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i1.pp545-551

Abstract

Wireless sensor network (WSN) is one of the most important elements of the Internet of Things paradigm. Energy consumption is a vital issue in IoT and WSN.  Security primitives in the IoT are energy consuming. Addressed the security issue for transmitted data by IoT sensor node add another challenge in term of energy consumption. finding the satisfactory solutions that reduce power consumption at the same time as making sure the required security services is not always an easy undertaking. Therefore, in this article, we proposed an efficient hybrid model for secure transmission of data from sensor nodes to receivers in WSN applications.  The proposed model includes two algorithms rivest–shamir–adleman (RSA) and efficient data collection and dissemination (EDCD). The key idea behind the proposed model is to prevent to secure sensed data if no significant change between the current data and the last transmitted data by the apply EDCD1 algorithm, which that will help in saving the sensor node energy. The reason for that the size of cipher data is so large compared to the sensed data, which that will increase the energy consumption.  The outcome results shown that the proposed model has a high performance compared to RSA in term of energy consumption.
A review of control algorithm for autonomous guided vehicle Faiza Gul
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 1: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i1.pp552-562

Abstract

The autonomous guided vehicle is a efficient and effective platform for control system. Their non-linear nature helps in analysing the control algorithms more efficiently and effectively. The main objective of path planning is to find the optimal and shortest path avoiding the time complexity so environment can be modelled completely for vehicle. The paper includes explanation of different systems together with numerous algorithms have been discussed with advantages and disadvantages for example: Fuzzy control, Neural Control, Back-stepping control, Adaptive control, Sliding mode control and PID control and linear quadratic regulator. The conclusion includes the hybrid system integration based on the advantages and disadvantages presented in this paper.

Page 7 of 7 | Total Record : 68

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