Research ArticleOpen accessIn the keywordsA Review on Clustering and Outlier Analysis Techniques in DataminingS. Koteeswaran, P. Visu, J. JanetProblem statement: The modern world is based on using physical, biological and social systems more effectively using advanced computerized techniques. A great amount of data being generated by such systems; it leads to a paradigm shift from classical modeling and analyses based on basic principles to developing models and the corresponding analyses directly from data. The ability to extract useful … …American Journal of Applied Sciences, Vol. 9, Issue 2 · 26 Dec 2011 · 7,375 accessesView PDFCite
Research ArticleOpen accessIn the keywordsBodily 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 keywordsImproved Application of Paraconsistent Artificial Neural Networks in Diagnosis of Alzheimer's DiseaseHelder F.S. Lopes, Jair M. Abe, Paulo A.M. Kanda et al.Problem statement: The visual analysis of Electroencephalogram (EEG) activity has shown useful as a complementary tool in Alzheimer Disease (AD diagnosis) when the diagnosis remains uncertain, in addition to be used in some clinical protocols. However, this analysis is subject to the inherent equipment imprecision, biological artifact, electrical records, and subjective physician interpretation of the visual analysis variation. The Artificial … …Neuroscience International, Vol. 2, Issue 1 · 6 Oct 2011 · 12,068 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Integrated Framework for Mixed Data Clustering Using Self Organizing MapHari Prasad Devaraj, M. PunithavalliProblem statement: Clustering plays an important role in data mining of large data and helps in analysis. This develops a vast importance in research field for providing better clustering technique. There are several techniques exists for clustering the similar kind of data. But only very few techniques exists for clustering mixed data items. This leads to the requirement of better … …Journal of Computer Science, Vol. 7, Issue 11 · 18 Aug 2011 · 7,307 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEvaluating some Reliability Analysis Methodologies in Seismic DesignA. El Ghoulbzouri, A. Khamlichi, F. Lopez Almansa et al.Problem statement: Accounting for uncertainties that were present in geometric and material data of reinforced concrete buildings was performed in this study within the context of performance based seismic engineering design. Approach: Reliability of the expected performance state is assessed by using various methodologies based on finite element nonlinear static pushover analysis and specialized reliability software package. Reliability approaches that … …American Journal of Engineering and Applied Sciences, Vol. 4, Issue 3 · 18 Aug 2011 · 7,847 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Fuzzy Mathematical Programming Approach to DEA ModelsA. Azadeh, S.F. Ghaderi, Z. Javaheri, M. SaberiEvaluating the performance of activities or organizations by traditional Data Envelopment Analysis (DEA) as efficiency frontier analysis models requires crisp input/output data. However, in real-world problems inputs and outputs are often imprecise. This study develops DEA models using imprecise data represented by fuzzy sets. An important outcome of assessing relative efficiencies within a group of Decision Making Units (DMUs) in … …American Journal of Applied Sciences, Vol. 5, Issue 10 · 31 Oct 2008 · 7,232 accessesView PDFCite
Research ArticleOpen accessIn the keywordsGradient Boosting for Heart Stroke Prediction: Investigating Unexpected Risk FactorsAniket Kailas Shahade, Priyanka V. DeshmukhHeart stroke prediction is a critical area in healthcare, aiming to identify individuals at risk and provide timely intervention. This research leverages machine learning algorithms, including Decision Tree, Random Forest, AdaBoost, and Gradient Boost, to predict the likelihood of stroke, with Gradient Boosting delivering the most accurate results. Our analysis uncovers intriguing and unexpected relationships between stroke risk and various … …Journal of Computer Science, Vol. 21, Issue 1 · 16 Dec 2024 · 4,943 accessesView PDFCite
Case ReportOpen accessIn the keywordsComputational Analysis of Environmental Risk ConditionersBarbara Carla Coelho Batista, João Victor Dutra Balboa, Caio Vincenzo Reis Dima et al.The intense urbanization process since the 1970s, coupled with the lack of adequate housing and social policies, has led large urban centers to disordered occupations and situations of geotechnical risk. These occupations were not implemented in a technically correct manner from the point of view of civil engineering, considering landscaping, drainage and paving, as well as edification. Areas at risk … …American Journal of Environmental Sciences, Vol. 16, Issue 5 · 16 Oct 2020 · 6,797 accessesView PDFCite
Research ArticleOpen accessIn the keywordsRHALSA: Ranking Hotels using Aspect Level Sentiment AnalysisNibedita Panigrahi, Asha TOpinion play a vital role which impacts the business in large extent. Users by-and-large depend on the reviews of others to avail the services. Online hotel bookings are becoming popular because of mobile applications being used on smart phones for placing the bookings from far away in advance along with the access to their reviews on different aspects. In this … …Journal of Computer Science, Vol. 14, Issue 11 · 15 Nov 2018 · 7,547 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Comparative Study of Data Mining approaches for Bag of Visual Words Based Image ClassificationSahar Abd El Hameed Mokhtar, Heba Ahmed ElnemrImage classification is one of the most significant and challenging tasks in computer vision. The goal of this task is to build a system that is capable to reveal an image label within a collection of different image categories. This paper presents and discusses the application of various data mining techniques for image classification based on Bag of Visual Words … …Journal of Computer Science, Vol. 14, Issue 1 · 12 Jan 2018 · 7,990 accessesView PDFCite