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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

191 192 193 194 195

Business intelligence analytics using sentiment analysis-a survey Prakash P. Rokade; Aruna Kumari D
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 1: February 2019
Publisher : Institute of Advanced Engineering and Science

Sentiment analysis (SA) is the study and analysis of sentiments, appraisals and impressions by people about entities, person, happening, topics and services. SA uses text analysis techniques and natural language processing methods to locate and extract information from big data. As most of the people are networked themselves through social websites, they use to express their sentiments through these websites.These sentiments are proved fruitful to an individual, business, government for making decisions. The impressions posted on different available sources are being used by organization to know the market mood about the services they are providing. Analyzing huge moods expressed with different features, style have raised challenge for users. This paper focuses on understanding the fundamentals of sentiment analysis, the techniques used for sentiment extraction and analysis. These techniques are then compared for accuracy, advantages and limitations. Based on the accuracy for expexted approach, we may use the suitable technique.

An efficient resource sharing technique for multi-tenant databases Pallavi G. B.; P. Jayarekha
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Multi-tenancy is one of the key components of cloud computing environment. Multi-tenant database system in SaaS (Software as a Service) has gained a lot of attention in academics, research and business arena. These database systems provide scalability and economic benefits for both cloud service providers and customers(organizations/companies referred as tenants) by sharing same resources and infrastructure in isolation of shared databases, network and computing resources with Service level agreement (SLA) compliances. In a multitenant scenario, active tenants compete for resources in order to access the database. If one tenant blocks up the resources, the performance of all the other tenants may be restricted and a fair sharing of the resources may be compromised. The performance of tenants must not be affected by resource-intensive activities and volatile workloads of other tenants. Moreover, the prime goal of providers is to accomplish low cost of operation, satisfying specific schemas/SLAs of each tenant. Consequently, there is a need to design and develop effective and dynamic resource sharing algorithms which can handle above mentioned issues. This work presents a model embracing a query classification and worker sorting technique to efficiently share I/O, CPU and Memory thus enhancing dynamic resource sharing and improvising the utilization of idle instances proficiently. The model is referred as Multi-Tenant Dynamic Resource Scheduling Model (MTDRSM) .The MTDRSM support workload execution of different benchmark such as TPC-C(Transaction Processing Performance Council), YCSB(The Yahoo! Cloud Serving Benchmark)etc. and on different database such as MySQL, Oracle, H2 database etc. Experiments are conducted for different benchmarks with and without SLA compliances to evaluate the performance of MTDRSM in terms of latency and throughput achieved. The experiments show significant performance improvement over existing Mute Bench model in terms of latency and throughput.

Rotational Load Flow Method for Radial Distribution Systems Diego Issicaba; Jorge Coelho
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 3: June 2016
Publisher : Institute of Advanced Engineering and Science

This paper introduces a modified edition of classical Cespedes' load flow method to radial distribution system analysis. In the developed approach, a distribution network is modeled in different complex reference systems and reduced to a set of connected equivalent subnetworks, each without resistance, while graph topology and node voltage solution are preserved. Active power losses are then not dissipated in the modeled subnetworks and active power flows can be obtained as a consequence of radiality. Thus, the proposed method preprocesses a series of variable transformations concomitant to an iterative algorithm using a forward-backward sweep to arrive at the load flow solution. The proposed approach has been tested using literature and actual distribution networks, and efficiency improvements are verified in comparison to Cespedes' load flow method.

A Study on the Suitability of Genetic Algorithm for Adaptive Channel Equalization Jafar Mohammed
International Journal of Electrical and Computer Engineering (IJECE) Vol 2, No 3: June 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (488.172 KB)

Adaptive algorithms such as Least-Mean-Square (LMS) based channel equalizer aim to minimize the Intersymbol Interference (ISI) present in the transmission channel. However the adaptive algorithms suffer from long training time and undesirable local minima during training mode. These disadvantages of the adaptive algorithms for channel equalization have been discussed in the literature. In this paper, we propose a new adaptive channel equalizer using Genetic Algorithm (GA) which is essentially a derivative free optimization tool. This algorithm is suitably used to update the weights of the equalizer. The performance of the proposed channel equalizer is evaluated in terms of mean square error (MSE) and convergence rate and is compared with its LMS and RLS counter parts. It is observed that the new adaptive equalizer based GA offer improved performance so far as the accuracy of reception is concerned.DOI:http://dx.doi.org/10.11591/ijece.v2i3.312

Lip Image Feature Extraction Utilizing Snake’s Control Points for Lip Reading Applications Faridah Faridah; Balza Achmad; Binar Listyana S
International Journal of Electrical and Computer Engineering (IJECE) Vol 5, No 4: August 2015
Publisher : Institute of Advanced Engineering and Science

Snake is an active contour model that catches and locks image edges, then localizes them accurately. The simplest Snake consists of a set of control points that are connected by straight lines to form a closed loop. This paper discusses the application of Snake to find the visual feature of lip shapes. In most previous papers, visual feature of lip shapes is represented by Snake’s contour. In this paper, the feature of lip shapes is represented by six control points on lip Snake’s contours. By simply utilizing six control points representing one lip Snake’s contour, it is expected to reduce the burden on pattern recognition stage. To demonstrate the performance of this method, some analysis has been conducted on the effect of lip conditions and illumination. The results shows that the overall lip feature extraction using the proposed method is better for lips that have more contrast to the surrounding skin, optimum room illumination that gives the best result is in the range of 330-340 lux.

Dynamic Voltage Stability Comparison of Thermal and Wind Power Generation with Different Static and Dynamic Load Models Lina F. Acevedo; Gilbert Bothia-Vargas; John Edwin Candelo
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 3: June 2018
Publisher : Institute of Advanced Engineering and Science

This paper presents a static and dynamic voltage stability analysis of a power network with thermal and wind generation considering static and dynamic load models. The thermal plant was modeled as a synchronous machine and the wind farm as a variable speed induction generator based on a doubly-fed induction generator. The load considered the ZIP, exponential recovery, induction motor, and frequency-dependent load models. The bifurcation points were found by continuation power flow and sensitivity analyses. In addition, dynamic voltage stability assessments were performed considering changes in the moment of inertia and the frequency parameters. All simulations were carried out in a 4-bus power system and using the power system analysis toolbox (PSAT) and MATLAB script code. The results show that the thermal generator had difficulties to maintain stability under dynamic load variations and frequency changes, the wind generator had difficulties to maintain voltage for the load with induction motors, and both generators had difficulties when the moment of inertia is increased.

The best quintic Chebyshev approximation of circular arcs of order ten Abedallah M. Rababah
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

Mathematically, circles are represented by trigonometric parametric equations and implicit equations. Both forms are not proper for computer applications and CAD systems. In this paper, a quintic polynomial approximation for a circular arc is presented. This approximation is set so that the error function is of degree $10$ rather than $6$; the Chebyshev error function equioscillates $11$ times rather than $7$; the approximation order is $10$ rather than $6$. The method approximates more than the full circle with Chebyshev uniform error of $1/2^{9}$. The examples show the competence and simplicity of the proposed approximation, and that it can not be improved.

Cost-Effective Medical Robotic Telepresence Solution using Plastic Mannequin Victor O. Matthews; Segun I. Popoola; Aderemi A. Atayero; Emmanuel Adetiba; Joke A. Badejo
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 3: June 2017
Publisher : Institute of Advanced Engineering and Science

Robotic telepresence is an Information and Communication Technology (ICT) solution that has a huge potential to address the problem of access to quality healthcare delivery in rural areas. However, the capital and operating costs of available systems are considered to be unffordable for rural dwellers in emerging economies. In addition, most of these communities are not even connected to the power grid. In this paper, the authors reduced the cost of engaging a robotic telepresence solution for rural medicare by using plastic mannequin and solar photovoltaic technology. An IP camera was fixed in each of the eye sockets of the plastic mannequin. These cameras are connected to a mini-computer embedded in the plastic mannequin. A Wi-Fi module establishes an Internet connection between remote physicians and rural heathcare facilities. The system is powered by a solar photovoltaic energy source to guarantee power availability. Another unique feature of this solution is that it gives the patient a better impression of the physical presence of a physician. Comparative cost analysis with robotic telepresence available in the market showed that our system is more affordable. This development will increase the adoption of robotic telepresense in rural telemedicine.

Operation cost reduction in unit commitment problem using improved quantum binary PSO algorithm Ali Nasser Hussain; Ali Abduladheem Ismail
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science

Unit Commitment (UC) is a nonlinear mixed integer-programming problem. UC is used to minimize the operational cost of the generation units in a power system by scheduling some of generators in ON state and the other generators in OFF state according to the total power outputs of generation units, load demand and the constraints of power system. This paper proposes an Improved Quantum Binary Particle Swarm Optimization (IQBPSO) algorithm. The tests have been made on a 10-units simulation system and the results show the improvement in an operation cost reduction after using the proposed algorithm compared with the ordinary Quantum Binary Particle Swarm Optimization (QBPSO) algorithm.

Test Case Optimization and Redundancy Reduction Using GA and Neural Networks Itti Hooda; R.S. Chhillar
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

More than 50% of software development effort is spent in testing phase in a typical software development project. Test case design as well as execution consume a lot of time. Hence, automated generation of test cases is highly required. Here a novel testing methodology is being presented to test object-oriented software based on UML state chart diagrams. In this approach, function minimization technique is being applied and generate test cases automatically from UML state chart diagrams. Software testing forms an integral part of the software development life cycle. Since the objective of testing is to ensure the conformity of an application to its specification, a test “oracle” is needed to determine whether a given test case exposes a fault or not. An automated oracle to support the activities of human testers can reduce the actual cost of the testing process and the related maintenance costs. In this paper, a new concept is being presented using an UML state chart diagram and tables for the test case generation, artificial neural network as an optimization tool for reducing the redundancy in the test case generated using the genetic algorithm. A neural network is trained by the back-propagation algorithm on a set of test cases applied to the original version of the system.

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Home Page

OAI Link

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Contact Name Tole Sutikno

Contact Email ijece@iaesjournal.com

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Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

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Abstract

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