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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
Single line to ground fault detection and location in medium voltage distribution system network based on neural network Ahmed K. Abbas; Sumaya Hamad; Nuha A. Hamad
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.pp621-632

Abstract

The aim of this project was to detect and locate the single ground failure lines that occurs in medium voltage (MV) networks on the transmission lines (TL). Compared with anther faults, single line-to-ground (SLG) is the most frequent. The neural network (NN) algorithm was advanced in order to discover and locate SLG faults. The network is simulated through simulated numerous defects at various locations, as well as changing earth resistance from (or 100 Ω) to TL to gather all of the data. In the electromagnetic transients’ program (EMTP) program software, the existing fault have been measured. In addition, the waves were evaluated by utilize MATLAP's fastfourier-transform to calculate the waves of top three of them, On the MV network are fifty hundred faults are simulated all data in the neural network at MATLAB were trained and examined to improve the NN algorithm according to this data. Comparing all the simulated location faults that have been applied with those all locations detected in the NN algorithm, the overall error between them has been found to be very low and not to exceed 0.7. The Simulink circuit was created from this algorithm and checked in order to predict each failure could occur in the future in the MV network.
Optimal path discovery for two moving sinks with a common junction in a wireless sensor network Satish Tunga; Sadashiva V. Chakrasali; N. Shylashree; Latha B. N.; Mamatha A. S.
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.pp879-889

Abstract

A new algorithm is described for determining the optimal round-trip paths for two moving sinks in a wireless sensor network. The algorithm uses binary integer programming to select two non-overlapping shortest paths except having a common junction node to cover all the sensor nodes. The two paths are balanced as nearly equal as possible. That is the sensor nodes along each path are equal or differ by just one depending on whether the total number of sensor nodes excluding the junction node is even or odd. In this method, both the path lengths are made equal or very nearly equal while the total length is minimized. This integrated approach is a novel and unique solution to solve the dual moving sink path problem in a wireless sensor network.
Performance evaluation of new blind OFDM signal recognition based on properties of the second-order statistics using universal software radio peripheral platform Mohamed Firdaoussi; Hicham Ghennioui; Mohamed El Kamili; Mohamed Lamrini
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.pp1227-1236

Abstract

In the context of cognitive radio (CR) or various military and civilian applications, modulation recognition (MR) is one of the most popular technical processes in the field of communication system recognition, by which the modulation type of the unknown received signal can be identified automatically by estimating one or more parameters of the modulated signal. This paper presents the performance evaluation of the new proposed blind system recognition method using only a particular property of the second-order statistics of the orthogonal frequency division multiplexing (OFDM) modulated signal. The effectiveness of the proposed method is illustrated using the implementation on universal software radio peripheral (USRP) platform. A comparison with computer simulations using MATLAB software is also performed, emphasizing the good performances of the method while the results obtained are close. We show the efficiency and behavior of the proposed method in the context of wireless communication systems based on OFDM modulation (3GPP/LTE, WiMAX, DVBT-2K, IEEE 802.22-1K,IEEE 802.22-2K, IEEE 802.22-4K). The proposed method can detect OF DM signals among other digital signals in a systematic and intelligent way even with low SNR values (when approaching to SNR=-2dB, the decision criteria tends towards 0).
Two-terminal fault detection and location for hybrid transmission circuit Muhd Hafizi Idris; Mohd Rafi Adzman; Hazlie Mokhlis; Mohammad Faridun Naim Tajuddin; Haziah Hamid; Melaty Amirruddin
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.pp639-649

Abstract

This paper presents the algorithms developed to detect and locate the faults ata hybrid circuit. First, the fault detection algorithm was developed using the comparison of total positive-sequence fault current between pre-fault and fault times to detect the occurrence of a fault. Then, the voltage check method was used to decide whether the fault occurred at overhead line (OHL) or cable section. Finally, the fault location algorithm using the impedance-based method and negative-sequence measurements from both terminals of the circuit were used to estimate the fault point from local terminal. From the tests of various fault conditions including different fault types, fault resistance and fault locations, the proposed method successfully detected all fault cases at around 1 cycle from fault initiation and with correct faulted section identification. Besides that, the fault location algorithm also has very accurate results of fault estimation with average error less than 1 km and 1%. 
Efficient reconfigurable architecture for moving object detection with motion compensation Sridevi N.; M. Meenakshi
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.pp802-810

Abstract

The detection and tracking of object in large data surveillance requires a proper motion estimation and compensation techniques which are generally used to detect accurate movement from video stream. In this paper, a novel hardware level architecture involving motion detection, estimation, and compensation is proposed for real-time implementation. The motion vectors are obtained using 16×16 sub-blocks with a novel parallel D flip flop architecture in this work to arrive at an optimised architecture. The sum of absolute difference (SAD) is then calculated by optimized absolute difference and adder blocks designed using kogge-stone adder which helps in improving the speed of the architecture. The controller block is designed by finite state machine model used for synchronization of all the operations. Further, the comparator and compensation blocks are optimized by using basic logical elements and the Kogge-stone adder. Finally, the proposed architecture is implemented on Zynq Z7-10 field-programmable gate array (FPGA) and simulated using System Generator tool for real time traffic signal. The hardware and software parameters are compared with the existing techniques which shows that the proposed architecture is efficient than existing methods of design.
Control of prosthetic hand by using mechanomyography signals based on support-vector machine classifier Firas Saaduldeen Ahmed; Noha Abed-Al-Bary Al-jawady
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.pp1180-1187

Abstract

Prosthetic devices are necessary to help amputees achieve their daily activity in the natural way possible. The prosthetic hand has controlled by type of signals such as electromyography (EMG) and mechanomyography (MMG). The MMG signals have represented mechanical signals that generate during muscle contraction. These signals can be detected by accelerometers or microphones and any kind of sensors that can detect muscle vibrations. The contribution of the current paper is classifying hand gestures and control prosthetic hands depends on pattern recognition through accelerometer and microphone are to detect MMG signals. In addition to the cost of prosthetic hand less than other designs. Six subjects are involved. In this present work is the devices. In this study, two of them are amputee subjects. Each subject performs seven classes of movements. Pattern recognition (PR) is used to classify hand gestures. The wavelet packet transform (WPT) and root mean square (RMS) as features extracted from the signals and support vector machine (SVM) as a classifier. The average accuracy is 88.94% for offline tests and 84.45% for online tests. 3D printing technology is used in this study to build prosthetic hands.
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. 
Performance analysis of encryption and decryption algorithm Pronika Pronika; S. S. Tyagi
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.pp1030-1038

Abstract

In this tumultuous 21st century, we are surrounding by lots of applications such as social media websites all over the internet or this era can also define as digital era in which everything is accessible over the internet. There are billions of internet users all over the world and they share their information over the same and because of this lots of people intentionally trying to steal the confidential data of other people, so it is always advisable to share and store data in encrypted form. In this paper, we discuss different encryption and decryption algorithms and compare them with respect to time take by these algorithms for encrypting and decrypting different sizes of files.
Cloud-based architecture for face identification with deep learning using convolutional neural network Aditya Herlambang; Putu Wira Buana; I Nyoman Piarsa
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.pp811-820

Abstract

The use of a face as a biometric to identify a person in order to keep the system safe from an unauthorized person has advantages over other biometric characteristics. The face as a biometric has more structure and a wider area than other biometrics, while can be retrieved in a non-invasive manner. We proposed a cloud-based architecture for face identification with deep learning using convolutional neural network. Face identification in this study used a cloud-based engine with four stages, namely face detection with histogram of oriented gradients (HOG), image enhancement, feature extraction using convolutional neural network, and classification using k-nearest neighbor (KNN), SVM, as well as random forest algorithm. This study conducted a classification experiment with cloud-based architecture using three different datasets, namely Faces94, Faces96 and University of Manchester Institute of Science and Technology (UMIST) face dataset. The results from this study are with the proposed cloud-based architecture, the best accuracy is obtained by KNN algorithm with an accuracy of 99% on Faces94 dataset, 99% accuracy on Faces96 dataset, 97% on UMIST face dataset, and performance of the three algorithms decreased in UMIST face dataset with facial variations from various angles from left to right profile.
Performance evaluation of NB-IoT in-band deployment mode in suburban area Karina Turzhanova; Sergey Konshin; Valery Tikhvinskiy; Alexandr Solochshenko
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.pp855-862

Abstract

There given to discuss the study results about one of three deployment scenarios performance (in-band deployment mode) of the narrow-band internet of things (NB-IoT) technology. The study is carrying out with help of simulation modeling and experimental testing of the main network parameters, namely: radio coverage, network capacity, user experience, and their dependencies on each other. Comparison of the results of a physical experiment and simulation modeling shows their high convergence and confirms the adequacy of the applied testing methodology. As a case scenario provided an example of NB-IoT implementation on a 4G mobile network in the 800 MHz band, in a suburban area for remote metering applications. The article presents the applying testing methodology of NB-IoT that adapted to the local conditions of radio network planning. Based on the obtained data, adducing the main conclusions about the feasibility of using an in-band scenario for deploying NB-IoT on a 4G network in a suburban environment.

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