Research NotesOpen accessEvery word in the titleReal Time Density-Based Clustering (RTDBC) Algorithm for Big DataDr. B. Ravi PrasadDensity Based Spatial Clustering of Applications with Noise (DBSCAN), a well-known Density-Based Clustering Algorithm is a advanced data clustering method with various applications in numerous fields like Satellites images, X-ray crystallography, Anomaly Detection in Temperature Data. But its run time R(n2) complexity draws a major challenge. In this research paper, we propose a new unique algorithm called Real Time Density … …Journal of Computer Science, Vol. 13, Issue 10 · 15 Aug 2017 · 7,298 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleFractional Lion Algorithm-An Optimization Algorithm for Data ClusteringSatish Chander, P. Vijaya, Praveen DhyaniClustering divides the data available as bulk into meaningful, useful groups (Clusters) without any prior knowledge about the data. Cluster analysis provides an abstraction from individual data objects to the clusters in which those objects reside. It is a key technique in the data mining and has become an important issue in many fields. This paper presents a novel Fractional … …Journal of Computer Science, Vol. 12, Issue 7 · 12 Aug 2016 · 7,673 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSegmentation 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 accessEvery word in the titleAn Efficient Ant Algorithm for Swarm-Based Image ClusteringSalima Ouadfel, Mohamed BatoucheA collective approach to resolve the segmentation problem was proposed. AntClust is a new ant-based algorithm that uses the self-organizing and autonomous brood sorting behavior observed in real ants. Ants and pixels are scatted on a discrete array of cells represented the ants’ environment. Using simple local rules and without any central control, ants form homogeneous clusters by moving pixels … …Journal of Computer Science, Vol. 3, Issue 3 · 31 Mar 2007 · 7,155 accessesView PDFCite
Research ArticleOpen accessIn the keywordsIoT Anomaly Detection Using Picture Fuzzy Clustering ApproachFehmin Nadira Laskar, Vijo Arul Selvi M., Fokrul Alom Mazarbhuiya et al.Improving the effectiveness of security systems without slowing them down is a major challenge in cybersecurity. Many methods have been explored for detecting anomalous behaviour in network data, with fuzzy set-based approaches standing out for their potential. The Internet of Things (IoT) consists of many connected devices that constantly generate large amounts of data and perform tasks in real time. … …Journal of Computer Science, Vol. 22, Issue 3 · 6 Mar 2026 · 1,515 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAdaptive Data Transformation for Enhanced Clustering Performance in Diagnostic SystemsMohammed Subhi Al-BatahThis paper presents an enhanced approach to the Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) algorithm, aimed at improving clustering accuracy in medical data, specifically for breast cancer diagnosis. The proposed method introduces a modified data transformation technique to optimize the original BIRCH algorithm. This transformation refines the clustering process, resulting in significant improvements in diagnostic accuracy. The modified … …Journal of Computer Science, Vol. 21, Issue 9 · 17 Oct 2025 · 2,287 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDeep Learning Approach to Mitigate DDoS Attacks in SDNHema Surendrakumar Dhadhal, Paresh Kotak, Parvez Faruki, Atul GonsaiThe rise of Distributed Denial of Service (DDoS) attacks remains a significant obstacle to network security and availability. This abstract presents a new hybrid model for DDoS mitigation in Software-Defined Networking (SDN) environments, combining a Semi-supervised Deep Extreme Learning Machine (Semi-Deep ELM) with a hybrid architecture. SDN's centralized control and programmability create an ideal platform for implementing advanced mitigation strategies. … …Journal of Computer Science, Vol. 20, Issue 9 · 5 Jul 2024 · 5,338 accessesView PDFCite
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 keywordsData Clustering-based Metaheuristic for Physical Internet Supply Chain NetworkAbdelsamad Chouar, Samir Tetouani, Aziz Soulhi, Jamila ElalamiIn this study, a data clustering-driven technique is proposed for a Physical Internet Supply Chain Network (PI-SCN) to reduce data complexity, process time compression, and lankness of process optimization. Given a set of data points, a clustering algorithm aims to classify each data-points into a specific group. Each group should have similar properties and/or features, while data points in different … …Journal of Computer Science, Vol. 18, Issue 4 · 21 Apr 2022 · 6,472 accessesView PDFCite