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31 results for “K-means Clustering Analysis”

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Research ArticleOpen accessIn the abstractSpatio-Temporal Anomaly Detection in Groundwater Electrical Conductivity Using a Hybrid Framework of Isolation Forest and AutoencoderEunji Lee, Seunghyun Lim, Seojun Lee, Abhijit DebnathMonitoring groundwater quality is vital for environmental safety and resource sustainability. This study combines Isolation Forest and Autoencoder models to detect anomalies in Electrical Conductivity (EC) and temperature, using monthly data collected in South Korea between 2006 and 2023. Linear regression and the Mann-Kendall test reveal a weak, episodic downward EC trend. Seasonal decomposition indicates annual cyclicality, while residual analysis … …Journal of Computer Science, Vol. 22, Issue 1 · 14 Feb 2026 · 1,918 accessesView PDFCite
Research ArticleOpen accessIn the abstractMultimodal Face Expression Recognition Using Parametric Exponential Linear Unit-Long Short-Term MemoryKampa Ratna Babu, Akula Suneetha, Kampa Kanthi KumarMultimodal facial expression recognition combines information from multiple modalities of audio and video to achieve the required accuracy and robustness. By integrating different data sources, multimodal systems capture different aspects of human expression. However, accurately recognizing facial expressions across audio and video modalities causes challenges due to variations in expression representation. In this research, Parametric Exponential Linear Unit-Long Short-Term Memory … …Journal of Computer Science, Vol. 20, Issue 10 · 17 Aug 2024 · 4,612 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalysis of Big Data Football Club Market Value Using K-Means and Linear Regression Mining MethodsJohanes Fernandes Andry, Riama Sibarani, Vlavio Nathanael YeftaFootball clubs store a lot of data about their players, squad, transfer market, and market value, so big data is needed to process this data. This data can be analyzed to gain insight into the club's market value. Changes in player performance, age, and squad size can be analyzed using statistical methods. These digital data will provide information about the … …Journal of Computer Science, Vol. 19, Issue 2 · 10 Feb 2023 · 5,991 accessesView PDFCite
EditorialOpen accessIn the abstractData Mining in Time Series: Current Study and Future TrendTan Yan, Liudmila Ulanova, Ye Ouyang, Fengyuan XuTime series represent sequences of data points where usually their order is defined by the time when they were recorded. Thus, virtually any sequential recordings can be stored as time series: Stock prices, weather conditions, physical system parameters change, product quality monitoring, etc. This leads to ubiquity of time series in all scientific and practical fields (Esling and Agon, 2012); … …Journal of Computer Science, Vol. 10, Issue 12 · 26 Jan 2015 · 8,756 accessesView PDFCite
Research ArticleOpen accessIn the abstractVIRTUAL MINING MODEL FOR CLASSIFYING TEXT USING UNSUPERVISED LEARNINGS. Koteeswaran, E. Kannan, P. VisuIn real world data mining is emerging in various era, one of its most outstanding performance is held in various research such as Big data, multimedia mining, text mining etc. Each of the researcher proves their contribution with tremendous improvements in their proposal by means of mathematical representation. Empowering each problem with solutions are classified into mathematical and implementation models. … …American Journal of Applied Sciences, Vol. 11, Issue 5 · 20 Feb 2014 · 6,582 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Ant-Based Clustering Algorithm with Cluster Analysis TechniquesWafa’a Omar, Amr Badr, Abd El-Fattah HegazyCluster analysis is a data mining technology designed to derive a good understanding of data to solve clustering problems by extracting useful information from a large volume of mixed data elements. Recently, researchers have aimed to derive clustering algorithms from nature’s swarm behaviors. Ant-based clustering is an approach inspired by the natural clustering and sorting behavior of ant colonies. In … …Journal of Computer Science, Vol. 9, Issue 6 · 7 Jun 2013 · 7,306 accessesView PDFCite
Research ArticleOpen accessIn the abstractOnline Forums Hotspot Prediction Based on Sentiment AnalysisK. Nirmala Devi, V. Murali BhaskarnProblem statement: Online forums hotspot prediction is one of the significant research areas in web mining, which can help people make proper decision in daily life. Online forums, news reports and blogs, are containing large volume of public opinion information. Rapid growth of network arouses much attention on public opinion, it is important to analyse the public opinion in time … …Journal of Computer Science, Vol. 8, Issue 8 · 11 Jul 2012 · 7,360 accessesView PDFCite
Research ArticleOpen accessIn the abstractHeart Localization from Magnetic Resonance Images SequenceAhmed Farag, Mahmoud FakhreldinProblem statement: Heart localization is an important step in cardiac Magnetic Resonance Images (MRI) analysis. This study aims to locate the moving heart region from MRI sequence of images. Approach: The idea is to use the motion detection techniques to isolate the heart region from the background image and then apply morphological operations to construct a moving heart region mask. … …Journal of Computer Science, Vol. 8, Issue 4 · 30 Jan 2012 · 6,852 accessesView PDFCite
Research ArticleOpen accessIn the abstractSegmentation of Medical Image using Clustering and Watershed AlgorithmsM.C. Jobin Christ, R.M.S. ParvathiProblem statement: Segmentation plays an important role in medical imaging. Segmentation of an image is the division or separation of the image into dissimilar regions of similar attribute. In this study we proposed a methodology that integrates clustering algorithm and marker controlled watershed segmentation algorithm for medical image segmentation. The use of the conservative watershed algorithm for medical image analysis … …American Journal of Applied Sciences, Vol. 8, Issue 12 · 22 Oct 2011 · 8,780 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Rough Set based Gene Expression Clustering AlgorithmJ. Jeba Emilyn, K. RamarProblem statement: Microarray technology helps in monitoring the expression levels of thousands of genes across collections of related samples. Approach: The main goal in the analysis of large and heterogeneous gene expression datasets was to identify groups of genes that get expressed in a set of experimental conditions. Results: Several clustering techniques have been proposed for identifying gene signatures and … …Journal of Computer Science, Vol. 7, Issue 7 · 28 Jun 2011 · 6,830 accessesView PDFCite