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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 9,174 Documents
 590   591   592   593   594 
Evaluation of the stability enhancement of the conventional sliding mode controller using whale optimization algorithm Aws Mahmood Abdullah; Ali Mohsin Kaittan; Mustafa Sabah Taha
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp744-756

Abstract

The proposed work is an attempt to investigate the stability of the nonlinear system by using a whale optimization algorithm as of one of the meta-heuristic optimization methods, and this investigation was conducted on a single inverted pendulum as a study model. The evaluation measures which were used in this article values of gain and sliding surface of the conventional sliding mode controller to illustrate the extent of the system`s stability. Furthermore, control action, the relationship between error and its derivative, desired, and actual position in addition to sliding response graphically showed the feasibility of the proposed solution. The attained results illustrated considerable improvement in the settling time and minimizing the impact of chattering behavior.
Automatic control of motors through Simocode pro, and its effect on the performance of the process of filling and dispensing of chemical inputs Omar Chamorro-Atalaya; Augusto Sanchez-Ayte; Carlos Dávila-Ignacio; Orlando Ortega-Galicio; Nestor Alvarado-Bravo; Almintor Torres-Quiroz; Florcita Aldana-Trejo
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 1: July 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i1.pp179-187

Abstract

This article aims to describe the design of an automatic control system for the automated management of motor drives through Simocode pro; and determine the effect from the quantitative point of view on the performance of the filling and dispatch process of chemical inputs from the perspective of dispatch time and the amount of input spilled in the tank filling stage. For this, the programming of the programmable logic controller was carried out using the simatic step 7 software, then the distributed control system (DCS Siemens S410) was programmed, using the PCS7 V8.1 software, where the control logic and simocode pro integration is carried out through the profibus protocol, which is monitored from an human-machine interface (HMI) interface. Once the control system was implemented, it was possible to reduce the operating time from 60 minutes on average to 35 minutes, which reflects an improvement of 41.66%; this in turn generates an increase in the number of tank filling by 62.84%. Likewise, it is possible to reduce the amount of chemical inputs spilled in the filling stage; this improvement represents 88.60%.
Analysis of the performance of grounding grids buried in heterogeneous soil under impulse current Amina Djaborebbi; Boubakeur Zegnini; Djillali Mahi
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp571-579

Abstract

The present paper is devoted to analyzing the transient behaviour of simple grounding grids subjected to impulse lightning current. The transmission line method (TLM) involving mutual coupling between conductors will be used. The transient behaviour of grounding grids buried in homogeneous and in heterogeneous soil is going to be evaluated into a complete time domain solution. Different simulations carried out altering, the influence of the grid dimensions, the kind of the ground and the current injection point on the grid voltage and impedance will be presented. Simulation results will be shown for two extreme cases: in the first case the current is in the center of the grid and in the second one it is injected in one corner of the two configurations of grids. The obtained results show that the grid 1x1 gives the lowest transient potential when the injection point is in lower resistivity side, and the grid 2x2 presents better behavior when the current is injected at center point. It is obvious that the suggested simulations are in a good agreement, with corresponding results of other researchers.
Evaluation of SVM performance in the detection of lung cancer in marked CT scan dataset Hamdalla Fadil Kareem; Muayed S AL-Huseiny; Furat Y. Mohsen; Enam A. Khalil; Zainab S. Hassan
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 3: March 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i3.pp1731-1738

Abstract

This paper concerns the development/analysis of the IQ-OTH/NCCD lung cancer dataset. This CT-scan dataset includes more than 1100 images of diagnosed healthy and tumorous chest scans collected in two Iraqi hospitals. A computer system is proposed for detecting lung cancer in the dataset by using image-processing/computer-vision techniques. This includes three preprocessing stages: image enhancement, image segmentation, and feature extraction techniques. Then, support vector machine (SVM) is used at the final stage as a classification technique for identifying the cases on the slides as one of three classes: normal, benign, or malignant. Different SVM kernels and feature extraction techniques are evaluated. The best accuracy achieved by applying this procedure on the new dataset was 89.8876%.
A machine learning for environmental noise classification in smart cities Ali, Yaseen Hadi; Rashid, Rozeha A.; Abdul Hamid, Siti Zaleha
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 3: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i3.pp1777-1786

Abstract

The sound at the same decibel (dB) level may be perceived either as annoying noise or as pleasant music. Therefore, it is necessary to go beyond the state-of-the-art approaches that measure only the dB level and also identify the type of the sound especially when the sound is recorded using a microphone. This paper presented a case study that considers the ability of machine learning models to identify sources of environmental noise in urban areas and compares the sound levels with the recommended levels by the World Health Organization (WHO). The approach was evaluated with a dataset of 44 sound samples grouped in four sound classes that are highway, railway, lawnmowers, and birds. We used mel-frequency cepstral coefficients for feature extraction and supervised algorithms that are Support vector machine (SVM), k-nearest neighbors (KNN), bootstrap aggregation (Bagging), and random forest (RF) for noise classification. We evaluated performance of the four algorithms to determine the best one for the classification of sound samples in the data set under consideration. The findings showed that the noise classification accuracy is in the range of 95%-100%. Furthermore, all the captured data exceeded the recommended levels by WHO which can cause adverse health effects.
Automated system for monitoring and control of the liquid wax production process Martín Díaz-Choque; Carlos Dávila-Ignacio; Augusto Sanchez-Ayte; Guillermo Morales-Romero; Almintor Torres-Quiroz; Nestor Alvarado-Bravo; Florcita Aldana-Trejo
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 2: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i2.pp782-790

Abstract

This article describes the design of an automated system for the automatic monitoring and control of the liquid wax production process, in order to quantify its effect on productivity indicators. For which initially the procedure for obtaining the automation will be described; then the results obtained will be presented, the same ones that will be identified through a comparative analysis. During the investigation it was determined that, through the use of a programmable logic controller, it was possible to improve the precision of the dosage of components in the liquid wax production process; By achieving acorrect dosage, it is achieved that the physical-chemical factors that intervene in the quality of the final product, which are the pH and specific density, are within the limits established by the company, this is reflected in the decrease 38.77% of the amount of monthly loss of raw material, thus achieving the optimization of the productivity of the production of liquid wax by 83.69% per month, compared to the non-automated process. 
Employing opposite ratings users in a new approach to collaborative filtering Abdellah El Fazziki; Yasser El Madani El Alami; Jalil Elhassouni; Ouafae El Aissaoui; Mohammed Benbrahim
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 1: January 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i1.pp450-459

Abstract

Over the past few decades, various recommendation system paradigms have been developed for both research and industrial purposes to satisfy the needs and preferences of users when they deal with enormous data. The collaborative filtering (CF) is one of the most popular recommendation techniques, although it is still immature and suffers from some difficulties such asparsity, gray sheep and scalability impeding recommendation quality. Therefore, we propose a new CF approach to deal with the gray sheep problem in order to improve the predictions accuracy. To realize this goal, our solution aims to infer new users from real ones existing in datasets. This transformation allows for creating users with opposite preferences to the real ones. On the one hand, our approach permits to amplify the number of neighbors, especially in the case of users who have unusual behavior (gray sheep). On the other hand, it facilitates building a dense similar neighborhood. The basic assumption behind this is that if user X is not similar to user Y, then the imaginary user ¬X is similar to the user Y. The performance of our approach was evaluated using two datasets, MovieLens and FilmTrust. Experimental results have shown that our approach surpasses many traditional recommendation approaches.
Fast and accurate primary user detection with machine learning techniques for cognitive radio networks G. A. Pethunachiyar; B. Sankaragomathi
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 1: January 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i1.pp472-478

Abstract

Spectrum decision is an important and crucial task for the secondary user to avail the unlicensed spectrum for transmission. Managing the spectrum is an efficient one for spectrum sensing. Determining the primary user presence in the spectrum is an essential work for using the licensed spectrum of primary user. The information which lacks in managing the spectrum are the information about the primary user presence, accuracy in determining the existence of user in the spectrum, the cost for computation and difficult in finding the user in low signal-to noise ratio (SNR) values. The proposed system overcomes the above limitations. In the proposed system, the various techniques of machine learning like decision tree, support vector machines, naive bayes, ensemble based trees, nearest neighbour’s and logistic regression are used for testing the algorithm. As a first step, the spectrum sensing is done in two stages with Orthogonal Frequency Division Multiplexing and Energy Detection algorithm at the various values of SNR. The results generated from the above algorithm is used for database generation. Next, the different machine learning techniques are trained and compared for the results produced by different algorithms with the characteristics like speed, time taken for training and accuracy in prediction. The accuracy and finding the presence of the user in the spectrum at low SNR values are achieved by all the algorithms. The computation cost of the algorithm differs from each other. Among the tested techniques, k-nearest neighbour (KNN) algorithm produces the better performance in a minimized time.
Future smart grid communication-deployment of IoT: opportunities and challenges Payal Soni; J. Subhashini
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 1: July 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i1.pp14-22

Abstract

India’s electrical power system grid also known as the power grid is serving us from a very long time. In this duration, there were no major developments or changes reported in the power grid system. Electrical power consumer demand is increasing drastically and the present grid system is not able to fulfil these emerging requirements. To fulfil the requirements of future power load, we need a modified system which has to be reliable, secure, intelligent and efficient. By converting the power grid into the smart grid will be a promising solution for adopting the above properties. Communication Infrastructure is a major part of the smart grid. The end-user can reduce their expenditure on electricity demand by using smart home appliance, to keep away from the rush hours and also make use of the renewable energy instead from utility, is a great example of deployment of internet of things (IoT) in grid communication. In this paper, we have provided a survey of different communication technology, applications, benefits and challenges in communication infrastructure, spatially IoT.
Enhancement in data security and integrity using minhash technique Sa'ed Abed; Lamis Waleed; Ghadeer Aldamkhi; Khaled Hadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 3: March 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i3.pp1739-1750

Abstract

Data encryption process and key generation techniques protect sensitive data against any various attacks. This paper focuses on generating secured cipher keys to raise the level of security and the speed of the data integrity checking by using the MinHash function. The methodology is based on applying the cryptographic algorithms rivest-shamir-adleman (RSA) and advanced encryption standard (AES) to generate the cipher keys. These keys are used in the encryption/decryption process by utilizing the Pearson Hash and the MinHash techniques. The data is divided into shingles that are used in the Hash function to generate integers and in the MinHash function to generate the public and the private keys. MinHash technique is used to check the data integrity by comparing the sender’s and the receiver’s encrypted digest. The experimental results show that the RSA and AES algorithms based on the MinHash function have less encryption time compared to the normal hash functions by 17.35% and 43.93%, respectively. The data integrity between two large sets is improved by 100% against the original algorithm in terms of completion time, and 77% for small/medium data and 100% for large set data in terms of memory utilization.

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