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International Journal of Electrical and Computer Engineering

IJECE
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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 6,301 Documents

274 275 276 277 278

Profit Driven Decision Assist System to Select Efficient IaaS Providers Mohan Murthy MK; Sanjay HA; Supreeth BM
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

IaaS providers provide infrastructure to the end users with various pricing schemes and models. They provide different types of virtual machines (small, medium, large, etc.). Since each IaaS provider uses their own pricing schemes and models, price varies from one provider to the other for the same requirements. To select a best IaaS provider, the end users need to consider various parameters such as SLA, pricing models/schemes, VM heterogeneity, etc. Since many parameters are involved, selecting an efficient IaaS provider is a challenging job for an end user. To address this issue, in this work we have designed, implemented and tested a decision-assist system which assists the end users to select efficient IaaS provider(s). Our decision-assist system consists of an analytical model to calculate the cost and decision strategies to assist the end user in selecting the efficient IaaS provider(s). The decision assist system considers various relevant parameters such as VM configuration, price, availability, etc. to decide the efficient IaaS provider(s). Rigorous experiments have been conducted by emulating various IaaS providers, and we have observed that our DAS successfully suggests the efficient IaaS provider/ providers by considering the input parameters given by the user.

Comparative Analysis of Metaheuristic Approaches for Makespan Minimization for No Wait Flow Shop Scheduling Problem Laxmi A. Bewoor; V. Chandra Prakash; Sagar U. Sapkal
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 1: February 2017
Publisher : Institute of Advanced Engineering and Science

This paper provides comparative analysis of various metaheuristic approaches for m-machine no wait flow shop scheduling (NWFSS) problem with makespan as an optimality criterion. NWFSS problem is NP hard and brute force method unable to find the solutions so approximate solutions are found with metaheuristic algorithms. The objective is to find out the scheduling sequence of jobs to minimize total completion time. In order to meet the objective criterion, existing metaheuristic techniques viz. Tabu Search (TS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are implemented for small and large sized problems and effectiveness of these techniques are measured with statistical metric.

A survey of big data and machine learning Surender Reddy Salkuti
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science

This paper presents a detailed analysis of big data and machine learning (ML) in the electrical power and energy sector. Big data analytics for smart energy operations, applications, impact, measurement and control, and challenges are presented in this paper. Big data and machine learning approaches need to be applied after analyzing the power system problem carefully. Determining the match between the strengths of big data and machine learning for solving the power system problem is of utmost important. They can be of great help to plan and operate the traditional grid/smart grid (SG). The basics of big data and machine learning are described in detailed manner along with their applications in various fields such as electrical power and energy, health care and life sciences, government, telecommunications, web and digital media, retailers, finance, e-commerce and customer service, etc. Finally, the challenges and opportunities of big data and machine learning are presented in this paper.

An Ozone Reactor Design with Various Electrod Configurations Agung Warsito; Abdul Syakur; Galuh Susilowati
International Journal of Electrical and Computer Engineering (IJECE) Vol 1, No 2: December 2011
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (344.004 KB)

Environmental pollution is increasing, including water pollution due to industrial and household. To overcome this, there are three main concerns, namely the policy and environmental management, environmental awareness of society, and utilization of appropriate technologies to overcome pollution. This study is an attempt to overcome the problems of environmental pollution by designing, creating, and applying appropriate technology to make Ozone reactor with high-voltage corona discharge plasma technology. There are some methods of electrod configuration, namely wire-cylinder, spiral-cylinder, wire-cylinder with Dielectric Barrier Discharge (DBD), and spiral-cylinder with DBD. Corona discharge occurs between high-voltage electrod of each configuration ionize Oxygen flowed in the reactor, thus generating plasma and forming Ozone. The test of four Ozone reactors have been done by wastewater treatment in the form of soft drink samples, obtain the fading colors of wastewater, which is increasingly fade over many cycles of waste treatment process conducted in Ozon reactor. Based on comparison of four of Ozone reactor, it is obtained waste water treatment more maximal on reactor Ozone configuration of spiral-cylinder electrod with DBD. Keywords: Ozone reactor, electrods configuration, corona discharge, wastewaterDOI:http://dx.doi.org/10.11591/ijece.v1i2.79

Gauss-Seidel Method based Voltage Security Analysis of Distribution System Gagari Deb; Kabir Chakraborty
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 1: February 2018
Publisher : Institute of Advanced Engineering and Science

Complexity of modern power network and Large disturbance results voltage collapse. So, voltage security analysis is important in power system. Indicators are helpful in voltage stability analysis, as they give information about the state of the system. In this paper a new indicator namely Distribution System Stability Indicator (DSSI) has been formulated using the information of Phasor Measurement Unit (PMU).The proposed indicator (DSSI) is tested on standard IEEE 33 bus radial distribution system. The suggested indicator is also applicable to the equivalent two bus system of a multi-bus power system. The proposed indicator is calculated for different contingent conditions at different system load configurations. The result of DSSI is verified with the standard indicator (VSI) which proves applicability of the proposed indicator. The bus voltages of all the buses at base loading and at maximum loading are evaluated for base data and for tripping of most critical line.

Performance Evaluation of Unscented Kalman Filter for Gaussian and non-Gaussian Tracking Application Leela Kumari. B; Padma Raju. K
International Journal of Electrical and Computer Engineering (IJECE) Vol 3, No 1: February 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (280.576 KB)

State estimation theory is one of the best mathematical approaches to analyze variants in the states of the system or process. The state of the system is defined by a set of variables that provide a complete representation of the internal condition at any given instant of time. Filtering of Random processes is referred to as Estimation, and is a well defined statistical technique. There are two types of state estimation processes, Linear and Nonlinear. Linear estimation of a system can easily be analyzed by using Kalman Filter (KF) but is optimal only when the model is linear .But Most of the state estimation problems are nonlinear, thereby limiting the practical applications of the KF and EKF. Unscented Kalman filter and Particle filter are best known for nonlinear estimates. The approach in this paper is to analyze the algorithm for maneuvering target tracking using bearing only measurements for both Gaussian /Nongaussian distributions where UKF provides better probability of state estimation. Montecarlo computer simulations are used to analyse the performance .The simulations results showed that UKF provides better performance for Gaussian distributed models compared to the nongaussian models.DOI:http://dx.doi.org/10.11591/ijece.v3i1.326

Development of a portable community video surveillance system S. Fakhar A. G; A. Fauzan K; M. Saad H; R. Affendi H; K. H. Fen
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science

In 2016, a crime rate has been evidently increasing particularly in Kuala Lumpur areas, including reports on house break-ins, car thefts, motorcycle thefts and robbery. One way of deterring such cases is by installing CCTV monitoring system in premises such as houses or shops, but this usually requires expensive equipment and installation fees. In this paper a cheaper alternative of a portable community video surveillance system running on Raspberry Pi 3 utilizing OpenCV is presented. The system will detect motion based on image subtraction algorithm and immediately inform users when intruders are detected by sending a live video feed to a Telegram group chat, as well as sound the buzzer alarm on the Raspberry Pi. Additionally, any Telegram group members can request images and recorded videos from the system at any time by sending a get request in Telegram which will be handled by Telegram Bot. This system uses the Pi NoIR camera module as the image acquisition device equipped with a 36 LED infrared illuminator for night vision capability. In addition to the Python language, OpenCV, a computer vision simulation from Intel is also used for image processing tasks. The performance analysis of the completed system is also presented computational complexity while offering improved flexibility. The performance time is also presented, where the whole process is run with a noticeable 3 seconds delay in getting the final output.

Issues of K Means Clustering While Migrating to Map Reduce Paradigm with Big Data: A Survey Khyati R Nirmal; K.V.V. Satyanarayana
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 6: December 2016
Publisher : Institute of Advanced Engineering and Science

In recent times Big Data Analysis are imminent as essential area in the field of Computer Science. Taking out of significant information from Big Data by separating the data in to distinct group is crucial task and it is beyond the scope of commonly used personal machine. It is necessary to adopt the distributed environment similar to map reduce paradigm and migrate the data mining algorithm using it. In Data Mining the partition based K Means Clustering is one of the broadly used algorithms for grouping data according to the degree of similarities between data. It requires the number of K and initial centroid of cluster as input. By surveying the parameters preferred by algorithm or opted by user influence the functionality of Algorithm. It is the necessity to migrate the K means Clustering on MapReduce and predicts the value of k using machine learning approach. For selecting the initial cluster the efficient method is to be devised and united with it. This paper is comprised the survey of several methods for predicting the value of K in K means Clustering and also contains the survey of different methodologies to find out initial center of the cluster. Along with initial value of k and initial centroid selection the objective of proposed work is to compact with analysis of categorical data.

Modified JSEG algorithm for reducing over-segmentation problems in underwater coral reef images Mohammad Sameer Aloun; Muhammad Suzuri Hitam; Wan NuralJawahir Hj Wan Yussof; Abdul Aziz K Abdul Hamid; Zainuddin Bachok
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

The original JSEG algorithm has proved to be very useful and robust in variety of image segmentation case studies.However, when it is applied into the underwater coral reef images, the original JSEG algorithm produces over-segementation problem, thus making this algorithm futile in such a situation. In this paper, an approach to reduce the over-segmentation problem occurred in the underwater coral reef image segmentation is presented. The approach works by replacing the color histogram computation in region merge stage of the original JSEG algorithm with the new computation of color and texture features in the similarity measurement. Based on the perceptual observation results of the test images, the proposed modified JSEG algorithm could automatically segment the regions better than the original JSEG algorithm.

Improving E-Learning by Integrating a Metacognitive Agent Hanane Elbasri; Adil Haddi; Hakim Allali
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

The major disadvantage of the current Learning Management Systems is the lack of learner assistance in their learning processes and, therefore, they can not replace the presence of the teacher who ensures the progress of learning. In fact, we proposed to integrate, for each learner, a metacognitive agent that supported the metacognitive assistance and extracts the defectsin the learning process and strategies. The goal is to invite the learner to correct himself and improve his learning method. Metacognitive questionnaires were distributed to a group of 100 students before, during and after a computer course. The goal is to evaluatethe metacognitive attributes and to determine their influence on the success of learning. Decision trees were used as data analysis tools to extract a set of rules and to discover the influence of these metacognitive attributes on the result obtained by the learners. The results indicate that there are relationships between the different metacognitive attributes and the learners’ success. We note there is the influence of metacognitive incitement on learner outcomes, which reflects the degree of understanding of a learning pedagogical unit by the learner.

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Home Page

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Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

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Contact Name
Tole Sutikno

Contact Email
ijece@iaesjournal.com

Phone
-

Journal Mail Official
ijece@iaesjournal.com

Editorial Address
-

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA