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Research ArticleOpen accessIn the abstractHybrid Hot Strip Rolling Force Prediction using a Bayesian Trained Artificial Neural Network and Analytical ModelsAbdelkrim Moussaoui, Yacine Selaimia, Hadj A. AbbassiThe authors discuss the combination of an Artificial Neural Network (ANN) with analytical models to improve the performance of the prediction model of finishing rolling force in hot strip rolling mill process. The suggested model was implemented using Bayesian Evidence based training algorithm. It was found that the Bayesian Evidence based approach provided a superior and smoother fit to the … …American Journal of Applied Sciences, Vol. 3, Issue 6 · 30 Jun 2006 · 7,140 accessesView PDFCite
Research ArticleOpen accessIn the abstractSuVashantor: English to Bangla Machine Translation SystemsMahjabeen Akter, M. Shahidur Rahman, Muhammed Zafar Iqbal, Mohammad Reza SelimThis paper presents the system description of Machine Translation (MT) systems for English-Bangla language pair. Our goal was to create two benchmark MT systems that produce a better quality translation and comparatively higher evaluation score than existing MT systems for English to Bangla. In our experiments, we implemented two baseline MT systems using both statistical and neural methods for the … …Journal of Computer Science, Vol. 16, Issue 8 · 16 Aug 2020 · 7,451 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Students’ Academic Performance in the University Using Meta Decision Tree ClassifiersShanthini A., G. Vinodhini, R.M. ChandrasekaranStudent performance prediction is an area of concern for educational institutions. At the University level learning system, the method or rule adopted to identify the candidates who pass or fail differs depending on various factors such as the course, the department of study and so on. Predicting the result of a student in a course is an issue that has … …Journal of Computer Science, Vol. 14, Issue 5 · 28 Feb 2018 · 9,200 accessesView PDFCite
Research ArticleOpen accessIn the abstractRandom Forest Classification and Support Vector Machine for Detecting Epilepsyusing Electroencephalograph RecordsHeri Kuswanto, Mutiah Salamah, Muhammad Idrus FachruddinComplexity in data structure has led to the rapid development of computational statistics methods. Machine learning approaches have been introduced and applied to solve complex problems in many fields. This paper applies two common machine learning approaches, Random Forest (RF) and Support Vector Machine (SVM), in the detection of epilepsy. The diagnosis of epilepsy can usually only be made when … …American Journal of Applied Sciences, Vol. 14, Issue 5 · 4 May 2017 · 8,141 accessesView PDFCite
Research ArticleOpen accessIn the abstractHYBRID FEATURE SELECTION ALGORITHM FOR INTRUSION DETECTION SYSTEMSeyed Reza Hasani, Zulaiha Ali Othman, Seyed Mostafa Mousavi KahakiNetwork security is a serious global concern. Usefulness Intrusion Detection Systems (IDS) are increasing incredibly in Information Security research using Soft computing techniques. In the previous researches having irrelevant and redundant features are recognized causes of increasing the processing speed of evaluating the known intrusive patterns. In addition, an efficient feature selection method eliminates dimension of data and reduce redundancy … …Journal of Computer Science, Vol. 10, Issue 6 · 31 Jan 2014 · 7,357 accessesView PDFCite
Research ArticleOpen accessIn the abstractA NOVELTY APPROACH OF SPATIAL CO-OCCURRENCE AND DISCRETE SHEARLET TRANSFORM BASED TEXTURE CLASSIFICATION USING LPBOOSTING CLASSIFIERC. Vivek, S. AudithanRecently, the research towards Brodatz database for texture classification done at considerable amount of study has been published, the effective classification are vulnerable towards for training and test sets. This study presents the novel texture classification method based on feature descriptor, called spatial co-occurrence with discrete shearlet transformation through the LPboosting classification. It can be considered as a frame through … …Journal of Computer Science, Vol. 10, Issue 5 · 11 Jan 2014 · 6,608 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Fuzzy Fast Classification for Share Market Database with Lower and Upper BoundsSrinivasan Vaiyapuri, Rajenderan Govind, Vandar Kuzhali JaganathanIn recent years, many researchers focused on the research topic of constructing fuzzy classification system. This study introduces a Fuzzy Fast Classification (FFC) approach for large data sets. It has three phases, in the first phase the large data base is reduced with the entropy by removing the number of attribute. In the second phase an approximate classification is obtained … …American Journal of Applied Sciences, Vol. 9, Issue 12 · 8 Nov 2012 · 6,674 accessesView PDFCite
Research ArticleOpen accessIn the abstractPecan Weevil Recognition Using Support Vector Machine MethodGhulam Mubashar Hassan, Saleh Mufleh Al-SaqerProblem statement: The Pecan weevil was considered as the most dangerous pest of Pecan fruits. The aim of this research is to evaluate Support Vector Machine method (SVM) for identifying Pecan Weevil among other insects. Eventually, this recognition system will serve in a wireless imaging network for monitoring Pecan Weevils. Approach: SVM has been evaluated using two different kernel functions … …American Journal of Agricultural and Biological Sciences, Vol. 6, Issue 4 · 24 Dec 2011 · 7,927 accessesView PDFCite
Research ArticleOpen accessIn the abstractBodily Communication in Volleyball and New Data SystemGaetano RaiolaProblem statement: To verify the incidence of performance analysis data of bodily communication in volleyball and the difference of method gathering data between traditional method and new one. It recognizes the technical skills that are involved in bodily communication aspects. Thus, it analyzes and quantifies three specific technical skills relating the attacker role and the setter one in relationship to … …Journal of Social Sciences, Vol. 7, Issue 4 · 25 Oct 2011 · 8,314 accessesView PDFCite
Research ArticleOpen accessIn the abstractImplementation and Methods of Project Learning in Quantity Surveying Firms: Barriers, Enablers and Success FactorsHamzah Abdul-Rahman, Ali Mohammed Alashwal, Zatil Hidayah JamaludinProblem statement: Learning from project is vital for organizations to achieve competition and to survive in a dynamic environment. However, learning is not an easy task because there is no specific way for learning from projects. Besides, the practice of project learning and transfer knowledge to the firm’s level is still vague, specifically in the construction milieu. Approach: A questionnaire … …American Journal of Economics and Business Administration, Vol. 3, Issue 3 · 15 Sep 2011 · 7,576 accessesView PDFCite