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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 96 Documents
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Search results for , issue "Vol 11, No 5: October 2021" : 96 Documents clear
Security aware information classification in health care big data Snehalata K. Funde; Gandharba Swain
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4439-4448

Abstract

These days e-medical services frameworks are getting famous for taking care of patients from far-off spots, so a lot of medical services information like the patient’s name, area, contact number, states of being are gathered distantly to treat the patients. A lot of information gathered from the different assets is named big data. The enormous sensitive information about the patient contains delicate data like systolic BP, pulse, temperature, the current state of being, and contact number of patients that should be recognized and sorted appropriately to shield it from abuse. This article presents a weightbased similarity (WBS) strategy to characterize the enormous information of health care data into two classifications like sensitive information and normal information. In the proposed method, the training dataset is utilized to sort information and it comprises of three fundamental advances like information extraction, mapping of information with the assistance of the training dataset, evaluation of the weight of input data with the threshold value to classify the data. The proposed strategy produces better outcomes with various assessment boundaries like precision, recall, F1 score, and accuracy value 92% to categorize the big data. Weka tool is utilized for examination among WBS and different existing order procedures.
Reliability assessment for electrical power generation system based on advanced Markov process combined with blocks diagram A. A. Tawfiq; M. Osama abed el-Raouf; A. A. El-Gawad; M. A. Farahat
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp3647-3659

Abstract

This paper presents the power generation system reliability assessment using an advanced Markov process combined with blocks diagram technique. The effectiveness of the suggested methodology is based on HL-I of IEEE_EPS_24_bus. The proposed method achieved the generation reliability and availability of an electrical power system using the Markov chain which based on the operational transition from state to state which represented in matrix. The proposed methodology has been presented for reliability performance evaluation of IEEE_EPS_24_bus. MATLAB code is developed using Markov chain construction. The transition between probability states is represented using changing the failure and repair rates. The reduced number of generation system are used with Markov process to assess the availability, unavailability, and reliability for the generation system. Additionally, the proposed technique calculates the frequency, time duration of states, the probability of generation capacity state which get out of service or remained in service for each state of failure, and reliability indices. A considerable improvement in reliability indices is found with using blocks diagram technique which is used to reduce the infinity number of transition states and assess the system reliability. The proposed technique succeeded at achieving accurate and faster reliability for the power system.
Mixed Hill Cipher methods with triple pass protocol methods Liqaa Saadi Mezher; Ayam Mohsen Abbass
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4449-4457

Abstract

Hill Cipher is a reimbursement coding system that converts specific textual content codes into numbers and does no longer exchange the location of fixed symbols. The symbol modifications simplest in step with the English letter table inclusive of (26) characters handiest. An encoded Hill Cipher algorithm was used that multiplication the square matrix of the apparent text with a non-public key and then combined it with the Triple Pass Protocol method used to repeat the encryption three times without relying on a personal key. Also, you could decode the code and go back it to the express textual content. The cause of mixing algorithms is to cozy the message without any key change among the sender and the recipient.
Control algorithm for the urban traffic using a realtime simulation Ilyas Khelafa; Abdelhakim Ballouk; Abdenaceur Baghdad
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp3934-3942

Abstract

Many types of research have been interesting by real-time control of urban networks. This paper, basing on a simplified urban traffic model, proposes a novel control approach based on model predictive control concept to reduce congestion and improve the safety of cars on the roads. The contributions of this paper are: First, we consider vehicle heterogeneity, represented by a mathematical model called “S Model” and integrate it with a realtime simulator to evaluate the performance of controllers on real traffic conditions. Second, in order to assess each controller's success under particular circumstances, the structured network-wide traffic controller based on model predictive control (MPC) theory is compared to a fixed time controller (FTC). Using two scenarios, different indicators are tested, i.e total time spent, vehicle number, queue length. The results show that the model predictive control quickly converges, with the different scenarios, and further improves social welfare.
Deep learning for COVID-19 diagnosis based on chest X-ray images Nashat Alrefai; Othman Ibrahim
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4531-4541

Abstract

Coronavirus disease 2019 (COVID-19) is a recent global pandemic that has affected many countries around the world, causing serious health problems, especially in the lungs. Although temperature testing is suggested as a firstline test for COVID-19, it was not reliable because many diseases have the same symptoms. Thus, we propose a deep learning method based on X-ray images that used a convolutional neural network (CNN) and transfer learning (TL) for COVID-19 diagnosis, and using gradient-weighted class activation mapping (Grad-CAM) technique for producing visual explanations for the COVID-19 infection area in the lung. The low sample size of coronavirus samples was considered a challenge, thus, this issue was overridden using data augmentation techniques. The study found that the proposed (CNN) and the modified pre-trained networks VGG16 and InceptionV3 achieved a promising result for COVID-19 diagnosis by using chest X-ray images. The proposed CNN was able to differentiate 284 patients with COVID-19 or normal with 98.2 percent for training accuracy and 96.66 percent for test accuracy and 100.0 percent sensitivity. The modified VGG16 achieved the best classification result between all with 100.0 percent for training accuracy and 98.33 percent for test accuracy and 100.0 percent sensitivity, but the proposed CNN overcame the others in the side of reducing the computational complexity and training time significantly.
Research trends on CAPTCHA: A systematic literature Igbekele Emmanuel O.; Adebiyi Ayodele A.; Ibikunle Francis A.; Adebiyi Marion O.; Olugbara O. Oludayo
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4300-4312

Abstract

The advent of technology has crept into virtually all sectors and this has culminated in automated processes making use of the Internet in executing various tasks and actions. Web services have now become the trend when it comes to providing solutions to mundane tasks. However, this development comes with the bottleneck of authenticity and intent of users. Providers of these Web services, whether as a platform, as a software or as an Infrastructure use various human interaction proof’s (HIPs) to validate authenticity and intent of its users. Completely automated public turing test to tell computer and human apart (CAPTCHA), a form of IDS in web services is advantageous. Research into CAPTCHA can be grouped into two -CAPTCHA development and CAPTCH recognition. Selective learning and convolutionary neural networks (CNN) as well as deep convolutionary neural network (DCNN) have become emerging trends in both the development and recognition of CAPTCHAs. This paper reviews critically over fifty article publications that shows the current trends in the area of the CAPTCHA scheme, its development and recognition mechanisms and the way forward in helping to ensure a robust and yet secure CAPTCHA development in guiding future research endeavor in the subject domain.
Elastic hybrid MAC protocol for wireless sensor networks Jamila Bhar; Imen Bouazzi
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4174-4182

Abstract

The future is moving towards offering multiples services based on the same technology. Then, billions of sensors will be needed to satisfy the diversity of these services. Such considerable amount of connected devices must insure efficient data transmission for diverse applications. Wireless sensor network (WSN) represents the most preferred technology for the majority of applications. Researches in medium access control (MAC) mechanism have been of significant impact to the application growth because the MAC layer plays a major role in resource allocation in WSNs. We propose to enhance a MAC protocol of WSN to overcome traffic changes constraints. To achieve focused goal, we use elastic hybrid MAC scheme. The main interest of the developed MAC protocol is to design a medium access scheme that respect different quality of services (QoS) parameters needed by various established traffic. Simulation results show good improvement in measured parameters compared to typical protocol.
The study of convex-dual-layer remote phosphor geometry in upgrading WLEDs color rendering index Huu Phuc Dang; Nguyen Thi Phuong Loan; Nguyen Thi Kim Chung; Nguyen Doan Quoc Anh
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp3890-3896

Abstract

The white-light light-emitting diode (LED) is a semiconductor light source that usually has one chip and one phosphor layer. Because of that simple structure, the color rendering index (CRI) is really poor. Therefore, structure with double layer of phosphor and multiple chips has been studied with the phosphorus proportions and densities in the silicone are constantly changed to find the best option to improve optical properties. In research, we use red phosphor Ca5B2SiO10:Eu3+ layer to place above the yellow phosphor one, and both of them have a convex design. Then, the experiments and measurements are carried out to figure out the effects of this red phosphor as well as the convex-double-layer remote phosphor design on the LED’s performances. The measured results reveal that the light output is enhanced significantly when using convex-dual-layer structure instead of the single-layer design. Additionally, the Ca5B2SiO10:Eu3+ concentration benefits CRI and CQS at around 6600 K and 7700 K correlated color temperature (CCT). Yet, the lumen output shows a slight decline as this red phosphor concentration surpass 26% wt. Through the experiments, it is found that a double layer of chip and double phosphorus is the best structure which could support the quality of CRI and luminous flux.
IoT for wheel alignment monitoring system Mohamad Hadi Sulaiman; Suhana Sulaiman; Azilah Saparon
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp3809-3817

Abstract

A great deal of previous research into wheel alignment has focused on techniques of the alignment, which involve big, bulky and high cost to maintain. Even though several approaches are required, the works are tedious and only performed in spacious area and trained mechanics. IoT is the alternatives due to the evolution of smartphone with numerous sensors to support and assist the research and development for IoT applications in vehicles. In this work, smaller and portable wheel alignment monitoring system is introduced by using communication protocol between sensors, microcontroller and mobile phone application. Thus, graphical user interface (GUI) is utilized to the system via wireless communication technology using TCP/IP Communication Protocol. The system has been tested to suit the functioning architecture system for the wheel alignment to provide the user awareness on early detection of wheel misalignment. In addition, the application has been successfully integrated with Android mobile application via TCP/IP communication protocol and view the results in smart phone in real-time.
Expert system application for reactive power compensation in isolated electric power systems A. K. Kirgizov; S. A. Dmitriev; M. Kh. Safaraliev; D. A. Pavlyuchenko; A. H. Ghulomzoda; J. S. Ahyoev
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp3682-3691

Abstract

Effective electricity use can be an option which enables to achieve significant economy while generating and transmitting of electricity. One of the most important things is to improve the electricity quality through reactive power correction up to optimum values. The current article presents the solution to compensate the reactive power in the distribution networks, in GornoBadakhshan Autonomous Oblast (GBAO) with the use of the advanced technologies based on the data collection within real time. The article describes the methodology of fuzzy logic application and bio-heuristic algorithms for the suggested solution effectiveness to be determined. Fuzzy logic application to specify the node priority for compensating devices based on the linguistic matrix power loss and voltage gives the possibility to the expert to take appropriate solutions for compensating devices installation location to be determined. The appropriate (correct) determination of the compensating devices installation location in the electric power system ensures the effective regulation of the reactive power with the least economic costs. Optimization problems related to the active power loss minimization are solved as well as the cost minimization with compensating devices to ensure the values tan(φ) not exceeding 0.35 through reducing multi-objective problem to the single-objective one using linear convolution.

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