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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 66 Documents
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Search results for , issue "Vol 19, No 1: July 2020" : 66 Documents clear
Position control of ball and beam system using robust h∞ loop shaping controller Shahad Sami Ali
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 1: July 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i1.pp91-98

Abstract

Laboratory Ball and Beam prototype (B&B) is a system designed to implement the controlling of space application studies such as aircraft flight and land. In this paper, to control the position of the rolling ball on the beam, MATLAB program will be used to design and implement PID and robust H∞ Loop Shaping controllers. The open loop response of the system is unstable, because the ball continuously rolling on the beam when a constant input applied. To stabilize the system, a PID controller used first to achieve the desired position. Then, robust H∞ Loop Shaping controller was used to achieve performance requirement for system with uncertainties. Results for the step response shows that robust H∞ Loop Shaping controller response have no over shoot, faster about 80 times when compared to step response of PID controller, it's more effective and had better performance compared to other controllers in the control of B&B system.
Detecting learning disabilities based on neuro-physiological interface of affect (NPIoA) Nurul Izzati Mat Razi; Abdul Wahab Abdul Rahman; Norhaslinda Kamaruddin
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 1: July 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i1.pp164-171

Abstract

Learning disability (LD) is a neurological processing disorder that causes impediment in processing and understanding information. LD is not only affecting academic performance but can also influence on relationship with family, friends and colleagues. Hence, it is important to detect the learning disabilities among children prior to the school year to avoid from anxiety, bully and other social problems. This research aims to implement the learning disabilities detection based on the emotions captured from electroencephalogram (EEG) to recognize the symptoms of Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD) and dyslexia in order to have early diagnosis and assisting the clinician evaluation.  The results show several symptoms that ASD children have low alpha power with the Alpha-Beta Test (ABT) power ratio and ASD U-shaped graph, ADHD children have high Theta-Beta Test (TBT) power ratio while Dyslexia have high Left-over-Right Theta (LRT) power ratio.  This can be concluded that the learning disabilities detection methods proposed in this study is applicable for ASD, ADHD and also Dyslexia diagnosis.
Performance evaluation of wireless sensor networks using LEACH protocol Anas Ali Hussien; Shaymaa Waleed Al-Shammari; Mehdi J. Marie
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 1: July 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i1.pp395-402

Abstract

Recent days witnessed considerable developments in the field of wireless sensor networks (WSNs). The applications of these networks can be seen in the simple consumer electronic devices as well as in the advanced space technology. The communication protocols are of prior importance and interest; the low-energy adaptive clustering hierarchy (LEACH) protocol is used to enhance the performance of power consumption for the WSNs nodes. The efficiency of a wireless network can be affected by different factors, such as the size of the WSN and the initial energy of the sensor node. This can inspire the researchers to develop the optimum structure of the WSNs to get its desired functionality. In this paper, the performance of the low-energy adaptive clustering hierarchy (LEACH) protocol is investigated using MATLAB to study the effect of the initial energy of the sensor node and the WSN size on the number of the running nodes. It is found that increasing the initial energy of a sensor node increases the life time of the node and hence the number of the running nodes. It has been also approved that the WSN size has an inverse proportion with the number of running sensor nodes during the use of LEACH protocol.
Estimation of the refractivity gradient from measured essential climate variables in Iyamho-Auchi, Edo State, South-South Region of Nigeria Kingsley Eghonghon Ukhurebor; Wilson Nwankwo
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 1: July 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i1.pp276-284

Abstract

Meteorological variables are crucial constituents in the estimation of refractivity disseminations and the uncharacteristic radio wave propagation situations of the troposphere as a result of their impact on radio wave communication relations over the atmosphere. In this study the measurement and assessment of air temperature, relative humidity and atmospheric pressure was carried out for a period of one year; 2018, so as to estimate the refractivity gradient over Iyamho-Auchi, Edo State, Nigeria using a self-implemented inexpensive portable meteorological monitoring device. The measurements of the essential climate variables were done at the administrative building of Edo University Iyamho by placing the meteorological monitoring device on a fixed position. The results show that the monthly estimated refractivity gradient values which would be useful in the prediction of the local radio propagation range from -20.00 N-units/km to -190.00 N-units/km with an average value of -60.67 N-units/km for the period under consideration. The findings also show that the months with limited relative humidity have greater refractivity gradient values compared to the ones with higher relative humidity. It was also observed from the results that the measured essential climate variables were having significant impacts on the estimated refractivity gradient during all the months in 2018, and these impacts were more noticeable in the months with higher relative humidity compared with the months that were having limited relative humidity. 
A survey: the role of the internet of things in the development of education Ridhab Sami Abd-Ali; Sarah Abbas Radhi; Zaid Ibrahim Rasool
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 1: July 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i1.pp215-221

Abstract

There is a demand to change the contents and activities, and adapt the methods for higher education institutions, especially, universities to let researchers and educational to act more efficiently in a digital context. A well-designed campus, finally combining technology, is basic for developing digital university by facilities for learning, teaching, and research, enhancing the student trials, and supplying the convenient settings. Within digital universities, technology can improve security, reduce costs, and offer devices for faculty, scholars, academics, and students. These advantages give more attention to university processes and evolutions, the experience of researchers, and students. In this research, we have done a study on the Internet of things and what its role in the development of education through the review for a group of previous research. In addition, we have studied the smart class and its components and the difference from the traditional class, and then we have displayed the smart laboratories and its applications. At the end of the research, the great importance of Internet things in universities and its importance to the teacher and the student was concluded by learning faster and developing and improving the educational process.
Stator winding fault detection of induction generator based wind turbine using ANN N. F. Fadzail; S. Mat Zali; M. A. Khairudin; N. H. Hanafi
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 1: July 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i1.pp126-133

Abstract

This paper presents a stator winding faults detection in induction generator based wind turbines by using artificial neural network (ANN). Stator winding faults of induction generators are the most common fault found in wind turbines. This fault may lead to wind turbine failure. Therefore, fault detection in induction generator based wind turbines is vital to increase the reliability of wind turbines. In this project, the mathematical model of induction generator based wind turbine was developed in MATLAB Simulink. The value of impedance in the induction generators was changed to simulate the inter-turn short circuit and open circuit faults. The simulated responses of the induction generators were used as inputs in the ANN model for fault detection procedures. A set of data was taken under different conditions, i.e. normal condition, inter-turn short circuit and open circuit faults as inputs for the ANN model. The target outputs of the ANN model were set as ‘0’ or ‘1’, based on the fault conditions. Results obtained showed that the ANN model can detect different types of faults based on the output values of the ANN model. In conclusion, the stator winding faults detection procedure for induction generator based wind turbines by using ANN was successfully developed.
Optimization of parameters of neuro-fuzzy model Lyalya Bakievna Khuzyatova; Lenar Ajratovich Galiullin
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 1: July 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i1.pp229-232

Abstract

The need for increasing the efficiency of the neuron-fuzzy model in the formation of knowledge bases is being updated. The task is to develop methods and algorithms for presetting and optimizing the parameters of a fuzzy neural network. To solve difficult formalized tasks, it is necessary to develop decision support systems - expert systems based on a knowledge base. ES developers are constantly faced with the problems of “extraction” and formalization of knowledge, as well as the search for new ways to obtain it. To do this, use the extraction, acquisition and formation of knowledge. Currently, the formation of knowledge bases is relevant for the creation of hybrid technologies - fuzzy neural networks that combine the advantages of neural network models and fuzzy systems. The analysis of the efficiency of the fuzzy neural network carried out in the work showed that the quality of training of the NN largely depends on the choice of the number of fuzzy granules for input drugs. In addition, to use fuzzy information formalized by the mathematical apparatus of fuzzy logic, procedures are required for selecting optimal forms and presetting the parameters of the corresponding membership functions (MF).
Mobility management for RPL protocol in internet of things Zohreh Royaee; Hamid Mirvaziri; Amid Khatibi bardsiri
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 1: July 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i1.pp451-458

Abstract

The IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) was proposed for various applications of IPv6 low power wireless networks. While RPL supports various routing metrics and is designed to be suitable for wireless sensor network environments, it does not consider the mobility of nodes. Therefore, there is a need for a method that is energy efficient and that provides stable and reliable data transmission by considering the mobility of nodes in RPL networks. In this paper a new heuristic flabellum algorithm inspired by physical and biological behaviour of flabella in the sea is presented, and bottleneck and swarm problems are resolved through managing the moving nodes by flabellum algorithm. Finally, the proposed algorithm’s performance is evaluated using the Cooja simulator. The proposed algorithm;Flabellum RPL; shows significant improvements with regards to packet delivery, and convergence and lifetime.
Exploring permissions in android applications using ensemble-based extra tree feature selection Howida Abuabker Alkaaf; Aida Ali; Siti Mariyam Shamsuddin; Shafaatunnur Hassan
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 1: July 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i1.pp543-552

Abstract

The fast development of mobile apps and its usage has led to increase the risk of exploiting user privacy. One method used in Android security mechanism is permission control that restricts the access of apps to core facilities of devices. However, that permissions could be exploited by attackers when granting certain combinations of permissions. So, the aim of this paper is to explore the pattern of malware apps based on analyzing permissions by proposing framework utilizing feature selection based on ensemble extra tree classifier method and machine learning classifier. The used dataset had 25458 samples (8643 malware apps & 16815 benign apps) with 173 features. Three dataset with 25458 samples and 5, 10 and 20 features respectively were generated after using the proposed feature selection method. All the dataset was fed to machine learning. Support Vector machine (SVM), K Neighbors Classifier, Decision Tree, Naïve bayes and Multilayer Perceptron (MLP) classifiers were used. The classifiers models were evaluated using true negative rate (TNR), false positive rate (FNR) and accuracy metrics. The experimental results obtained showed that Support Vector machine and KNeighbors Classifiers with 20 features achieved the highest accuracy with 94 % and TNR with rate of 89 % using KNeighbors Classifier. The FNR rate is dropped to 0.001 using 5 features with support vector machine (SVM) and Multilayer Perceptrons (MLP) classifiers. The result indicated that reducing permission features improved the performance of classification and reduced the computational overhead.
Towards electronic learning features in education 4.0 environment: literature study Nor Azah Mansor; Natrah Abdullah; Hayati Abd Rahman
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 1: July 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i1.pp442-450

Abstract

This paper presents electronic learning features in Education 4.0 environment. Malaysian government encourages Higher Education Institution (HEIs) to embed technologies in order to prepare future education (Education 4.0). Besides, developing skills among students is important to be more adaptable in changing the environment. Current HEIs using Learning Management System (LMS) has lack of interactive features and non-personalized learning. Therefore, this article set out to analyze the existing literature on e-learning practices in Education 4.0 and to propose e-learning features suits in Education 4.0 environment. Guided by the PRISMA Statement (Preferred Reporting Items for Systematic reviews and Meta-Analyses) review method, a systematic review of the Scopus 24 related studies. Further review of these articles resulted in seven principles of e-learning features based on the constructivism principle – Self-regulation, Personal perspective, Experiential learning, Social learning, Learning Community, Creating and Sharing Knowledge, Structure and layout which can be used to upgraded and redesigned LMS.

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