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Research ArticleOpen accessIn the abstractA SURVEY: PARTICLE SWARM OPTIMIZATION BASED ALGORITHMS TO SOLVE PREMATURE CONVERGENCE PROBLEMBahareh Nakisa, Mohd Zakree Ahmad Nazri, Mohammad Naim Rastgoo, Salwani AbdullahParticle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method based on the social behaviors of birds flocking or fish schooling. Although PSO is represented in solving many well-known numerical test problems, but it suffers from the premature convergence. A number of basic variations have been developed due to solve the premature convergence problem and improve quality … …Journal of Computer Science, Vol. 10, Issue 9 · 24 Apr 2014 · 8,788 accessesView PDFCite
Research ArticleOpen accessIn the abstractA SURVEY: PARTICLE SWARM OPTIMIZATION-BASED ALGORITHMS FOR GRID COMPUTING SCHEDULING SYSTEMSFaruku Umar Ambursa, Rohaya LatipBio-inspired heuristics have been promising in solving complex scheduling optimization problems. Several researches have been conducted to tackle the problems of task scheduling for the heterogeneous and dynamic grid systems using different bio-inspired mechanisms such as Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO). PSO has been proven to have a relatively more promissing performance in dealing … …Journal of Computer Science, Vol. 9, Issue 12 · 25 Nov 2013 · 6,662 accessesView PDFCite
Research ArticleOpen accessIn the abstractArtificial Bee Colony Algorithm Integrated with Fuzzy C-mean Operator for Data ClusteringM. Krishnamoorthi, A. M. NatarajanClustering task aims at the unsupervised classification of patterns in different groups. To enhance the quality of results, the emerging swarm-based algorithms now-a-days become an alternative to the conventional clustering methods. In this study, an optimization method based on the swarm intelligence algorithm is proposed for the purpose of clustering. The significance of the proposed algorithm is that it uses … …Journal of Computer Science, Vol. 9, Issue 4 · 6 May 2013 · 6,304 accessesView PDFCite
Research ArticleOpen accessIn the abstractContent Based Image Retrieval of Ultrasound Liver Diseases Based on Hybrid ApproachR. Suganya, S. RajaramProblem statement: In the past few years, immense improvement was obtained in the field of Content-Based Image Retrieval (CBIR). Nevertheless, existing systems still fail when applied to medical image databases. Simple feature-extraction algorithms that operate on the entire image for characterization of color, texture, or shape cannot be related to the descriptive semantics of medical knowledge that is extracted from … …American Journal of Applied Sciences, Vol. 9, Issue 6 · 24 Mar 2012 · 7,648 accessesView PDFCite
Research ArticleOpen accessIn the abstractFall Detection Using the Histogram of Oriented Gradients and Decision-Based FusionMohamed Maher Ben Ismail, Arwa AlGabas, Ouiem BchirAs the number of fall incidents among elderly people and patients are continuously growing, researches boosted their researches to propose efficient automatic fall detection systems. In particular, they formulated the fall detection problem as a supervised learning task where some visual features are extracted from the video frames and used to automatically identify the position of a human as “Fall” … …Journal of Computer Science, Vol. 16, Issue 2 · 26 Feb 2020 · 7,505 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Pedestrian Detection Using Context InformationJorge Candido, Mauricio MarengoniDetecting pedestrians among other objects in a digital image is a relevant task in the field of computer vision. This paper presents a method to improve the performance of a pedestrian detection algorithm using context information. A neural network is used to classify the region below pedestrian candidates as being floor or non-floor. We assume that a pedestrian must be … …Journal of Computer Science, Vol. 14, Issue 7 · 6 Aug 2018 · 7,224 accessesView PDFCite
Research ArticleOpen accessIn the abstractSentiment Analysis of Arabic Tweets in e-LearningHamed AL-Rubaiee, Renxi Qiu, Khalid Alomar, Dayou LiIn this study, we present the design and implementation of Arabic text classification in regard to university students' opinions through different algorithms such as Support Vector Machine (SVM) and Naive Bayes (NB). The aim of the study is to develop a framework to analyse Twitter "tweets" as having negative, positive or neutral sentiments in education or, in other words, to … …Journal of Computer Science, Vol. 12, Issue 11 · 4 Feb 2017 · 9,077 accessesView PDFCite
Research ArticleOpen accessIn the abstractCOMPUTER AIDED SEGMENTATION OF BRAIN TISSUES USING SOFT COMPUTING TECHNIQUESD. Ramkumar, I. Jacob Raglend, K. BatriIn this study, an efficient computer aided classification of brain tissue in to Gray Matter (GM), White Matter (WM) and Cerebro-Spinal Fluid (CSF) is proposed. The proposed work consists of the following sub blocks like denosing, feature extraction and Classifier. This initial partition is performed by ANFIS after extracting the textural features like local binary pattern and histogram features. The … …American Journal of Applied Sciences, Vol. 11, Issue 6 · 17 Apr 2014 · 6,668 accessesView PDFCite
Research ArticleOpen accessIn the abstractAUTHORSHIP CATEGORIZATION IN EMAIL INVESTIGATIONS USING FISHER’S LINEAR DISCRIMINANT METHOD WITH RADIAL BASIS FUNCTIONA. Pandian, Md. Abdul Karim SadiqEmail plays a vital role in faster communication. Lots of mails are sent to common public with falsified information that appears to be a realistic. It is mandatory to trace the origin of the email and the authors/systems responsible for generating such emails. Representative signatures of email are to be generated using lexical and syntactic based methods. The signature of … …Journal of Computer Science, Vol. 10, Issue 6 · 31 Jan 2014 · 6,690 accessesView PDFCite
Research ArticleOpen accessIn the abstractA REVIEW ON THE DEVELOPMENT OF INDONESIAN SIGN LANGUAGE RECOGNITION SYSTEMSutarman, Mazlina Abdul Majid, Jasni Mohamad ZainSign language is mainly employed by hearing-impaired people to communicate with each other. However, communication with normal people is a major handicap for them since normal people do not understand their sign language. Sign language recognition is needed for realizing a human oriented interactive system that can perform an interaction like normal communication. Sign language recognition basically uses two approaches: … …Journal of Computer Science, Vol. 9, Issue 11 · 27 Sep 2013 · 8,698 accessesView PDFCite