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International Journal of Electrical and Computer Engineering
Published by Institute of Advanced Engineering and Science
ISSN : 20888708     EISSN : 27222578     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 112 Documents
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Search results for , issue "Vol 12, No 5: October 2022" : 112 Documents clear
Design and implementation of smart guided glass for visually impaired people Md. Tobibul Islam; Mohd Abdur Rashid; Mohiuddin Ahmad; Anna Kuwana; Haruo Kobayashi
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5543-5552

Abstract

The objective of this paper is to develop an innovative microprocessor-based sensible glass for those who are square measure visually impaired. Among all existing devices in the market, one can help blind people by giving a buzzer sound when detecting an object. There are no devices that can provide object, hole, and barrier information associated with distance, family member, and safety information in a single device. Our proposed guiding glass provides all that necessary information to the blind person’s ears as audio instructions. The proposed system relies on Raspberry pi three model B, Pi camera, and NEO-6M global positioning system (GPS) module. We use TensorFlow and faster region-based convolutional neural network (R-CNN) approach for detection of objects and recognition of family members of the blind man. This system provides voice information through headphones to the ears of the blind person, and facile the blind individual to gain independence and freedom within the indoor and outdoor atmosphere.
An efficient optical inspection of photovoltaic modules deploying edge detectors and ancillary techniques Kummara Venkata Guru Raghavendra; Nutakki Tirumala Uday Kumar; Waqarullah Kazim
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4772-4781

Abstract

With the enhanced industrial and domestic energy needs, there is a great urge for renewable energy sources because of their eco-friendly nature. Solar energy is crucial among renewable energy sources and there is a great need to optimize and enhance the performance of solar energy usage that is mainly dependent on the system components. The current work has been aimed to discuss the fault detection of photovoltaic (PV) modules by evaluating an efficient, facile inspection algorithm electrical analysis for real-time applications. The paper presents a real-time experimental model for infrared thermography using a thermal imager mounted on a tripod at a suitable distance from the PV modules to capture the images in the best possible way. A novel hybrid algorithm has been proposed and the fault detection along with the electrical parameter analysis has been accurately performed on the PV modules to analyze and process various externally induced faults in the PV systems.
Traffic light control design approaches: a systematic literature review Nazar Elfadil Mohamed; Intisar Ibrahim Radwan
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5355-5363

Abstract

To assess different approaches to traffic light control design, a systematic literature review was conducted, covering publications from 2006 to 2020. The review’s aim was to gather and examine all studies that looked at road traffic and congestion issues. As well, it aims to extract and analyze protruding techniques from selected research articles in order to provide researchers and practitioners with recommendations and solutions. The research approach has placed a strong emphasis on planning, performing the analysis, and reporting the results. According to the results of the study, there has yet to be developed a specific design that senses road traffic and provides intelligent solutions. Dynamic time intervals, learning capability, emergency priority management, and intelligent functionality are all missing from the conventional design approach. While learning skills in the adaptive self-organization strategy were missed. Nonetheless, the vast majority of intelligent design approach papers lacked intelligent fear tires and learning abilities.
Robust control for a tracking electromechanical system Satybaldina Dana Karimtaevna; Kalmаganbetova Zhuldyzay Asylbekkyzy
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4883-4891

Abstract

A strategy for the design of robust control of tracking electromechanical systems based on ????∞ synthesis is proposed. Proposed methods are based on the operations on frequency characteristics of control systems designed and developed using the MATLAB robust control toolbox. Determination of the singular values for a transfer matrix of the control system reduces the disturbances and guarantees its stability margin. For selecting the weighted transfer functions, the basic recommendations are formulated. The efficiency of the proposed approach is verified by robust control of an elastically coupled two-mass system whose parameter values are adjusted by matching them with the parameters of one of the supplied robots. The simulation results confirm that the proposed strategy of design of robust control of two-mass elastic coupling system using the ????∞ synthesis is very efficient and significantly reduces the perturbation of parameters of the controlled plant.
Stress detection during job interview using physiological signal Ali Afzalian Mand; Md. Shohel Sayeed; Md. Jakir Hossen; Muhammad Amer Ridzuan bin Zuber
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5531-5542

Abstract

A job interview can be challenging and stressful even when one has gone through it many times. Failure to handle the stress may lead to unsuccessful delivery of their best throughout the interview session. Therefore, an alternative method which is preparing a video resume and interview before the actual interview could reduce the level of stress. An intelligent stress detection is proposed to classify individuals with different stress levels by understanding the physiological signal through electrocardiogram (ECG) signals. The Augsburg biosignal toolbox (AUBT) dataset was used to obtain the state-of-art results. Only five selected features are significant to the stress level were fed into neural network multi-layer perceptron (MLP) as the optimum classifier. This stress detection achieved an accuracy of 92.93% when tested over the video interview dataset of 10 male subjects who were recording the video resume for the analysis purposes.
Performance evaluation of 4-quadrature amplitude modulation over orthogonal frequency division multiplexing system in different fading channels scenarios Hasan Fadhil Mohammed; Ghanim Abdulkareem Mughir
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5123-5135

Abstract

Orthogonal frequency division multiplexing (OFDM) is a multicarrier modulation (MCM) technique that divides the wide bandwidth into parallel narrow bands, each of which is modulated by orthogonal subcarriers. Currently, OFDM is a high-spectral efficiency modulation technique that is used in a variety of wired and wireless applications. The transmitted signal in a wireless communication channel spreads from transmitter to receiver through multiple reflective paths. This triggers multipath fading, which causes variations in the received signal's amplitude and phase. Slow/fast and frequency-selective/frequency-nonselective are the main types of multipath fading channels. Therefore, in this paper, we proposed new models for modeling multipath fading channels, such as the exponential fading channel and the Gamma fading channel. In addition, new bit-error-rate (BER) derivations have been derived. The performance of the OFDM system over proposed channel models has been evaluated using Monte-Carlo simulation and compared to the Rayleigh fading channel model. The obtained results via simulations show that the exponential fading channel at a rate parameter (λ=0.5) outperforms the Rayleigh fading channel by 6 dB for all values of Eb/No, while the Gamma fading channel at (α=2) outperforms the Rayleigh fading channel by 3 dB for all values of Eb/No.
The impact of channel model on the performance of distance-based schemes in vehicular named data networks Kaoutar Ahed; Maria Benamar; Rajae El Ouazzani
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5279-5290

Abstract

Distance-based schemes present one of the methods to avoid the broadcast problem in vehicular named data networks. However, such schemes overlook the most factor in performance evaluation which is the variation in received signal strength caused by the propagation model choice. Thus, they are evaluated under one propagation model while neglecting the effect of the others. This paper evaluates the impact of the propagation variation model over three distance-based schemes, namely rapid named data networking (RNDN), enhanced vehicle on named data networking (EVNDN) and opportunistic interest forwarding protocol (OIFP). Simulation experiments are performed over three propagation models. Simulation results show that Nakagami significantly degrades network performance. However, it has a noticeable positive effect over higher distance resulting in a higher interest satisfaction ratio as compared to the other models. The RNDN exhibits a higher number of retransmissions across the Nakagami. In contrast, a higher number of retransmissions is exhibited by EVNDN when compared to the other schemes over the Friis and random. The OIFP show a higher interest satisfaction ratio when compared to EVNDN and RNDN under all models. OIFP shows robustness towards the adverse fading effects resulting from the Nakagami and exhibits lower end to end delays.
Minimizing routing overhead using signal strength in multi-hop wireless network Sachidananda S. Joshi; Sangappa Ramachandra Biradar
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5644-5656

Abstract

Constructing a stabilized route in dynamic topology and decentralized architecture is still an unsolved problem in mobile Ad-hoc networks. There are various research contributions where received signal strength has been used to enhance the routing performance. We reviewed the existing technique and found that adopting the current signal strength-based mechanism is not efficient enough to deal with overhead and energy consumption in mobile Ad-hoc networks (MANETs). The present manuscript introduces a novel routing schema called MROSS or minimizing routing overhead using signal strength (MROSS) that jointly addresses the problems of communication and network lifetime. The outcome of the study was developed using an analytical modeling approach to find MROSS significantly reduces routing overhead and energy consumption in comparison to existing routing techniques in mobile Ad-hoc network.
Efficient failure detection and consensus at extreme-scale systems Soma Sekhar Kolisetty; Battula Srinivasa Rao
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5339-5347

Abstract

Distributed systems and extreme-scale systems are ubiquitous in recent years and have seen throughout academia organizations, business, home, and government sectors. Peer-to-peer (P2P) technology is a typical distributed system model that is gaining popularity for delivering computing resources and services. Distributed systems try to increase its availability in the event of frequent component failures and functioning the system in such scenario is notoriously difficult. In order to identify component failures in the system and achieve global agreement (consensus) among failed components, this paper implemented an efficient failure detection and consensus algorithm based on fail-stop type process failures. The proposed algorithm is fault-tolerant to process failures occurring before and during the execution of the algorithm. The proposed algorithm works with the epidemic gossip protocol, which is a randomly generated paradigm of computation and communication that is both fault-tolerant and scalable. A simulation of an extreme-scale information dissemination process shows that global agreement can be achieved. A P2P simulator, PeerSim, is used in the paper to implement and test the proposed algorithm. The proposed algorithm results exhibited high scalability and at the same time detected all the process failures. The status of all the processes is maintained in a Boolean matrix.
Neural network training for serial multisensor of autonomous vehicle system Eka Nuryanto Budisusila; Sri Arttini Dwi Prasetyowati; Bhakti Yudho Suprapto; Zainuddin Nawawi
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5415-5426

Abstract

This study aims to find the best artificial neural network weight values to be applied to the autonomous vehicle system with ultrasonic multisensor. The implementation of neural network in the system required long time process due to its training process. Therefore, this research is using offline training before implementing to online training by embedding the best network weight values to obtain the outputs faster according to desired targets. Simulink were used to train the system offline. Eight ultrasonic sensors are used on all sides of the vehicle and arranged in a serial multisensory configuration as inputs of neural network. With eight inputs, one sixteen-depth hidden layer, and five outputs, it was trained using the back-propagation algorithm of artificial neural network. By 100000 iterations, the output values and the target values are almost the same, indicating its convergency with minimum of errors. The result of this training is the best weights of the networks. These weight values can be implemented as fixed-weight in online training.

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