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58 articles for “k-means clustering algorithm”
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Research ArticleOpen accessIn the keywordsDDoS Attack Detection Using Enhanced Neural Network Algorithm in Software-Defined NetworksHema Surendrakumar Dhadhal, Paresh P KotakWith the uncommon advancement of technology and networking, the world today is totally relying on it. The most obvious drawback of this technical progress resulted in several possible dangers. A Distributed Denial of Service (DDoS) attack is one in which a large number of compromised systems work together to prevent service from being provided to the targeted system. Consequently, to … …Journal of Computer Science, Vol. 19, Issue 6 · 24 May 2023 · 5,721 accessesView PDFCite
Research ArticleOpen accessIn the keywordsNon-Decimated Wavelet Transform and Vector Quantization for Lossy Medical Images CompressionHend A. Elsayed, Qusay E. Majeed, Mohammed M. El SherbinyThis study presents a new approach for lossy medical image compression using vector quantization. Recently, the digital image has been a reliable replacement for a hard copy of medical images, therefore, an effort has been made to ensure maintaining high-quality images to use for archiving, classification, or automated diagnostics support. Although the medical application contains all sorts of the images … …Journal of Computer Science, Vol. 19, Issue 3 · 24 Feb 2023 · 5,403 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA HYBRID FIREFLY ALGORITHM WITH FUZZY-C MEAN ALGORITHM FOR MRI BRAIN SEGMENTATIONMutasem K. AlsmadiImage processing is one of the essential tasks to extract suspicious region and robust features from the Magnetic Resonance Imaging (MRI). A numbers of the segmentation algorithms were developed in order to satisfy and increasing the accuracy of brain tumor detection. In the medical image processing brain image segmentation is considered as a complex and challenging part. Fuzzy c-means is … …American Journal of Applied Sciences, Vol. 11, Issue 9 · 10 Sep 2014 · 8,074 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Descriptive Analysis of Students Learning Skills Using Bloom’s Revised TaxonomyJoy Christy Antony Sami, Umamakeswari ArumugamThe academic committees worldwide suggest technical institutions to follow Revised Bloom’s Taxonomy (RBT), a framework that helps to develop learning objectives. The model classifies a hierarchy of educational objectives such as cognitive, sensory and affective domains that are not only helping the students to evolve thinking abilities but also to identify the skills they are lacking with. Analysis of students … …Journal of Computer Science, Vol. 16, Issue 2 · 4 Sep 2019 · 8,539 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAdaptive Acceptance Criterion (AAC) Algorithm for Optimization ProblemsAnmar AbuhamdahOptimization methods commonly are designed for solving the optimization problems. Local search algorithms are optimization method, which are good candidate in exploiting the search space. However, most of them need parameter tuning and incapable of escaping from local optima. This work proposes non-parametric Acceptance Criterion (AC) that not relies on user-defined, which motivate to propose an Adaptive Acceptance Criterion (AAC). … …Journal of Computer Science, Vol. 11, Issue 4 · 23 Jul 2015 · 6,969 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPREDICTION OF GLIOMA USING GENETIC OPTIMIZED NEURAL NETWORKS. Karpagam, S. GowriNeural networks are a computational paradigm model of the human brain that has become popular in recent years. We have tried to address the problem of Glioma by creating a more accurate classifier which can act as an expert assistant to medical practitioners. Brain stem gliomas are now recognized as a heterogenous group of tumors. In this study proposed a … …Journal of Computer Science, Vol. 9, Issue 11 · 1 Oct 2013 · 6,693 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPredicting Missing Attribute Values Using k-Means ClusteringNambiraj Suguna, Keppana Gowder ThanushkodiProblem statement: Predicting the value for missing attributes is an important data preprocessing problem in data mining and knowledge discovery tasks. Several methods have been proposed to treat missing data and the one used more frequently is deleting instances containing at least one missing value of a feature. When the dataset has minimum number of missing attribute values then we … …Journal of Computer Science, Vol. 7, Issue 2 · 25 Feb 2011 · 7,873 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Fog Resource Provisioning and Resource Allocation using MKFCM and FPANagarjun E, Dharamendra Chouhan, Dilip Kumar SMThe expansion of Internet of Things (IoT) deployments has motivated the Fog Computing (FC) paradigm, which brings mobile-edge and cloud resources together under a single model. Allocating and provisioning application tasks across such environments poses challenges due to constrained resource capabilities, heterogeneity, mobility, network hierarchy, and unpredictability. This paper addresses the need for additional computing devices that prioritize delay-sensitive applications … …Journal of Computer Science, Vol. 22, Issue 10 · 6 Oct 2026 · 462 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized Movie Recommendation Using Hybrid Jaccard-Based K-Means Clustering Using Apache SparkShiba Prasad Dash, Rajesh Kumar Sahoo, Ram Chandra Barik et al.The need for recommendations specific to each person's interests is growing every day, making recommendation systems increasingly important in people's lives. Researchers have paid close attention to the rapid expansion of e-commerce businesses and online video streaming services like Hotstar, YouTube, and Netflix. The collaborative filtering-based RS system aims to suggest such films or videos to users based on their … …Journal of Computer Science, Vol. 22, Issue 9 · 23 Sep 2026 · 602 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Misuse and Anomaly Intrusion Detection System Using Hybrid Supervised and Unsupervised Data Mining ApproachesHoma Molavi, Mohammad KhanbabaeiIntrusion Detection Systems (IDSs) play a crucial role in monitoring computer network security. Data mining and machine learning techniques facilitate the identification of intrusion patterns within large volumes of data. Hybrid data mining models have become increasingly popular in IDSs due to their enhanced effectiveness. This study presents a novel hybrid IDS that combines misuse and anomaly detection by integrating … …Journal of Computer Science, Vol. 22, Issue 6 · 6 Jul 2026 · 999 accessesView PDFCite