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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 23, No 2: August 2021" : 66 Documents clear
Denoising electromyogram and electroencephalogram signals using improved complete ensemble empirical mode decomposition with adaptive noise S. Elouaham; A. Dliou; N. Elkamoun; R. Latif; S. Said; H. Zougagh; K. Khadiri
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.pp829-836

Abstract

The health of the brain and muscles depends on the proper analysis of electroencephalogram and electromyogram signals without noise. The latter blends into the recording of biomedical signals for external or internal reasons of the human body. Therefore, to obtain a more accurate signal, it is needed to select filtering techniques that minimize the noise. In this study, the techniques used are empirical mode decomposition and its variants. Among the new versions of variants is the improved complete ensemble empirical mode decomposition with adaptive noise. These methods are applied to electroencephalogram and electromyogram signals corrupted by natural noise and white Gaussian noise. The obtained results through the use of the improved complete ensemble empirical mode decomposition with adaptive noises how the high performance that includes minimizing the noise and the effectiveness of the components of the signals used in the present research. This method has low values of the mean square error and high values of signal-to-noise ratio compared to other methods used in this study.
Active voltage balancing strategy of asymmetric stacked multilevel inverter Mostafa Q. Kasim; Raaed F. Hassan
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.pp665-674

Abstract

Multilevel inverters (MLI) play an important role in AC applications and are undergoing continuous development in topology and control. In higher levels inverters, conventional MLIs have high components count which calls for modification of these topologies to obtain the same number of levels with fewer components to reduce cost and size. Balancing of the capacitors voltages is crucial for the operation of the MLI and it becomes more challenging in higher levels. This paper presents an active voltage balancing strategy for a reduced switch count five-leve topology which is the asymmetric stacked multilevel inverter (ASMLI). The ASMLI uses fewer components than the conventional MLIs when used in their five-levelconfiguration. The proposed active voltage balancing strategy uses simple measurements and logic to assure a balanced capacitors voltages during steady state and transients. The performance was examined and compared based on two modulation techniques with LCL filter and RL load using MATLAB/Simulink. The results show that the active voltage balancing strategy can trace all capacitors voltages to the reference value simultaneously with less than 1% voltage error, fast dynamic response, and an acceptable total harmonic distortion (THD) which allows the proposed setup to be an available option for medium voltage applications. 
Augmented binary multi-labeled CNN for practical facial attribute classification Mohammed Berrahal; Mostafa Azizi
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.pp973-979

Abstract

Both human face recognition and generation by machines are currently an active area of computer vision, drawing curiosity of researchers, capable of performing amazing image analysis, and producing applications in multiple domains. In this paper, we propose a new approach for face attributes classification (FAC) taking advantage from both binary classification and data augmentation. With binary classification we can reach high prediction scores, while augmented data prevent overfitting and overcome the lack of data for sketched photos. Our approach, named Augmented binary multilabel CNN (ABM-CNN), consists of three steps: i) splitting data; ii) transformed-it to sketch (simplification process); iii) train separately each attribute with two convolutional neural networks; the whole process includes two networks: the first (resp. the second) one is to predict attributes on real images (resp. sketches) as inputs. Through experimentation, we figure out that some attributes give high prediction rates with sketches rather than with real images. On the other hand, we build a new face dataset, more consistent and complete, by generating images using Style-GAN model, to which we apply our method for extracting face attributes. As results, our proposal demonstrates more performances compared to those of related works.
Determining subject headings of documents using information retrieval models Evi Yulianti; Laksmita Rahadianti
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.pp1049-1058

Abstract

Subject heading is a controlled vocabulary that describes the topic of adocument, which is important to find and organize library resources. Assigning appropriate subject headings to a document, however, is a time-consuming process. We therefore conduct a novel study on the effectiveness of information retrieval models, i.e.,language model (LM) andvector spacemodel (VSM), to automatically generate a ranked list of relevant subject headings, with the aim to give a recommendation for librarians to determine the subject headings effectively and efficiently. Our results show that there are a high number of our queries (up to 61%) that have relevant subject headings in the ten top-ranked recommendations and on average, the first relevant subject heading is found at the early position (3rd rank). This indicates that document retrieval methods can help the subject heading assignment process. LM and VSM are shown to have comparable performance, except when the search unit is title, VSM is superior to LM by8-22%. Our further analysis exhibits three faculty pairs that are potential to have research collaboration as their students’ thesis often have overlap subject headings: i) economy and business-social and political sciences, ii) nursing-public health and iii) medicine-public health.
Analysis of inventory management of slow-moving spare parts by using ABC techniques and EOQ model-a case study Walid Emar; Zakaria Anas Al-Omari; Sami Alharbi
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.pp1159-1169

Abstract

Computer spare parts (CSPs) inventory management (IM) is very important for many companies. Excess inventory leads to high storage costs. On the other hand, the lack of CSP has a strong impact on the quality of service. This study was conducted by Power-One Jordan Computer Hardware-Software company (POJCHSC), Amman, Jordan. The focus area was the IM department and the target sample was employees working in the management department. The results showed that factors influencing the management of slow moving CSPs include production costs, obsolescence and CSPs dependence availability and transportation costs. By forecasting during the study, the results showed that the demand for adapters and chargers would increase by 20%. This demand forecast was performed using the economical order quantity (EOQ) model. The percentage of profits made by this company is 48%, and this requires some intervention to prevent losses. The results of this study are useful to the company, as well as to other similar industries that deal with slow-moving items. These results will help to simplify IM of slow-moving items. When we focused on POJCHSC manufacturers, the disadvantages of using the traditional ABC classification model were identified. Therefore, there is a need to have an ABC classification that is improved and which takes into consideration the criticality of the slow-moving CSP.
Face recognition using enhancement discrete wavelet transform based on MATLAB Asma Abdulelah Abdulrahman; Fouad Shaker Tahir
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.pp1128-1136

Abstract

In this work, it was proposed to compress the color image after de-noise by proposing a coding for the discrete transport of new wavelets called discrete chebysheve wavelet transduction (DCHWT) and linking it to a neural network that relies on the convolutional neural network to compress the color image. The aim of this work is to find an effective method for face recognition, which is to raise the noise and compress the image in convolutional neural networks to remove the noise that caused the image while it was being transmitted in the communication network. The work results of the algorithm were calculated by calculating the peak signal to noise ratio (PSNR), mean square error (MSE), compression ratio (CR) and bit-per-pixel (BPP) of the compressed image after a color image (256×256) was entered to demonstrate the quality and efficiency of the proposed algorithm in this work. The result obtained by using a convolutional neural network with new wavelets is to provide a better CR with the ratio of PSNR to be a high value that increases the high-quality ratio of the compressed image to be ready for face recognition.
Stabilizing the spatial position of a quadrotor by the backstepping procedure Dmytro Kucherov; Andrei Kozub; Olha Sushchenko; Ruslan Skrynkovskyy
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.pp1188-1199

Abstract

The paper considers the problem of synthesizing a control law that stabilizes the spatial position of an airborne object. The control object is a quadrotor with nonlinear dynamics. To solve the stabilization problem, a mathematical model of the quadrotor has been developed, taking into account its positionin the Cartesian and Euler coordinate systems. The new control law has been synthesized using the backstepping procedure. This control law is based on the Lyapunov-type stabilization criterion. New results analysis of the quadrotor dynamics, where has been showing the dependence of the control accuracy on the parameter of the stabilization criterion also presented. An algorithm for the directed search of the procedure parameter also has been proposed. It ensures the desired quality of the transient process. Simulation results confirming the results of the oretical research have been presented as well.
Mining the crime data using naïve Bayes model Lourdes M. Padirayon; Melvin S. Atayan; Jose Sherief Panelo; Carlito R. Fagela, Jr
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.pp1084-1092

Abstract

A massive number of documents on crime has been handled by police departments worldwide and today's criminals are becoming technologically elegant. One obstacle faced by law enforcement is the complexity of processing voluminous crime data. Approximately 439 crimes have been registered in sanchez mira municipality in the past seven years. Police officers have no clear view as to the pattern crimes in the municipality, peak hours, months of the commission and the location where the crimes are concentrated. The naïve Bayes modelis a classification algorithm using the Rapid miner auto model which is used and analyze the crime data set. This approach helps to recognize crime trends and of which, most of the crimes committed were a violation of special penal laws. The month of May has the highest for index and non-index crimes and Tuesday as for the day of crimes. Hotspots were barangay centro 1 for non-index crimes and barangay centro 2 for index crimes. Most non-index crimes committed were violations of special law and for index crime rape recorded the highest crime and usually occurs at 2 o’clock in the afternoon. The crime outcome takes various decisions to maximize the efficacy of crime solutions.
A self adaptive new crossover operator to improve the efficiency of the genetic algorithm to find the shortest path Mrinmoyee Chattoraj; Udaya Rani Vinayakamurthy
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.pp1011-1017

Abstract

Route planning is an important part of road network. To select an optimized route several factors such as flow of traffic, speed limits of road. are concerned. Total cost of such a network depends on the number of junctions between the source and the destination. Due to the growth of the nodes in the network it becomes a tough job to determine the exact path using deterministic algorithms so in such cases genetic algorithms (GA) plays a vital role to find the optimized route. Crossover is an important operator ingenetic algorithm. The efficiency of thegenetic algorithmis directlyinfluenced by the time of a crossover operation. In this paper a new crossoveroperator closest-node pairing crossover (CNPC) is recommended which is explicitly designed to improve the performance of the genetic algorithm compared to other well-known crossover operators such as point based crossover and order crossover. The distance aspect of the network problem has been exploited in this crossover operator. This proposed technique gives a better result compared to the other crossover operator with the fitness value of 0.0048. The CNPC operator gives better rate of convergence compared to the other crossover operators.
A smart management system of electric vehicles charging plans on the highway charging stations Ibrahim El-Fedany; Driss Kiouach; Rachid Alaoui
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.pp752-759

Abstract

Electric vehicles (EVs) are seen as one of the principal pillars of smart transportation to relieve the airborne pollution induced by fossil CO2 emissions. However, the battery limit, especially where the journey is with a long-distance road remains the most formidable obstacle to the large-scale use of EVs. To overcome the issue of prolonged waiting charging time due to the large number of EVs may have a charging plan at the same charging station (CS) along the highway, we propose a communication system to manage the EVs charging demands. The architecture system contains a smart scheduling algorithm to minimize trip time including waiting time, previous reservations and energyare needed to reach the destination. Moreover, an automatic mechanism for updating reservation is integrated to adjust the EVs charging plans. The results of the evaluation under the Moroccan highway scenario connecting Rabat and Agadir show the effectiveness of our proposal system. 

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