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Research ArticleOpen accessIn the keywordsNEW BURST ASSEMBLY AND SCHEDULING TECHNIQUE FOR OPTICAL BURST SWITCHING NETWORKSV. Kavitha, V. PalanisamyThe Optical Burst Switching is a new switching technology that efficiently utilizes the bandwidth in the optical layer. The key areas to be concentrated in Optical Burst Switching (OBS) networks are the burst assembly and burst scheduling i.e., assignment of wavelengths to the incoming bursts. This study presents a New Burst Assembly and Scheduling (NBAS) technique in a simultaneous multipath … …Journal of Computer Science, Vol. 9, Issue 8 · 6 Jul 2013 · 6,944 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Tool for Generation and Minimization of Test Suite by Mutant Gene AlgorithmSelvakumar Subramanian, Ramaraj NatarajanProblem statement: This study proposes a new idea for generation of minimized test suite in the test case generation using the mutant gene algorithm, which not only identifies the best test cases but also reduces the number of test cases generated, selects test cases optimally there improving the performance in testing of software. Test cases are generated by using branch … …Journal of Computer Science, Vol. 7, Issue 10 · 9 Aug 2011 · 7,164 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnsemble Feature Selection for Elderly Health Condition ClassificationRattanawadee PanthongFeature selection is a pivotal technique for constructing classification models with high-dimensional data. It facilitates the identification and elimination of redundant or irrelevant features, thereby reducing model complexity and enhancing predictive accuracy. The success of a classification model largely depends on the quality of the selected features. Accordingly, feature selection is performed during data preparation, prior to data processing, to … …Journal of Computer Science, Vol. 22, Issue 8 · 31 Aug 2026 · 774 accessesView PDFCite
Research ArticleOpen accessIn the abstractReal-Time Monitoring and Injury Risk Warning Algorithm Based on Data Fusion of Motor Muscle ContractionGuomin Wang, Jingying HuangThe existing sports injury warning algorithms are difficult to achieve dynamic injury risk modeling based on individual muscle characteristics while ensuring real-time fusion efficiency of multimodal signals. This article proposes a real-time muscle contraction state perception and injury risk warning algorithm based on adaptive weighted feature fusion and lightweight temporal modeling. The system synchronously collected surface electromyography (sEMG), Inertial Measurement … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 3 · 10 Aug 2026 · 1,089 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Grey Wolf Optimizer and Deep Transfer Learning-Based Intrusion Detection System for IoTKapil Shrivastava, Manish Tiwari, Prasun ChakrabartiThe rapid proliferation of Internet of Things (IoT) devices has driven significant advancements in connectivity and automation, but it has also introduced substantial cybersecurity risks, including intrusions and cyberattacks. To address these challenges, this study proposes a hybrid intrusion detection framework that combines advanced optimization techniques with ensemble deep learning to enhance detection accuracy and computational efficiency. The proposed framework … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 1,506 accessesView PDFCite
Research ArticleOpen accessIn the abstractSentiment Analysis Using Light Weight - Gradient Boosting Machine based Feature SelectionBikku Ramavath, Srikanth Kadainti, Nemani SubashSentiment analysis is a significant task in Natural Language Processing (NLP) that differentiates the emotions and opinions expressed in text or reviews. The sentiment analysis is challenging due to the complex language patterns and inappropriate or redundant features used for classification. In this research, the Light Weight - Gradient Boosting Machine (LWGBM) based feature selection is proposed to choose relevant … …Journal of Computer Science, Vol. 21, Issue 5 · 26 May 2025 · 4,695 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Semantic Web Retrieval Through Ontology-Driven Feature Extraction: A Novel PropositionMeer Hazar Khan, Muhammad Imran Sharif, Mehwish Mehmood et al.Web images represent unstructured data sets which often lead to challenges when users try to locate distinct images via text-based searches on the web. Such difficulties stem from different factors, e.g., redundant image storage, irrelevant metadata tags, and incorrect associations. To overcome this issue, we propose a semantic model based on the ontology language that enables users to find images … …Journal of Computer Science, Vol. 20, Issue 5 · 23 Feb 2024 · 5,562 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntegrated Information Security Policy Model for Saudi Arabia OrganizationsWad GhabanInformation Security Policy (ISP) is an important domain used to preserve the confidentiality, integrity, and availability of sensitive data. However, it is an ambiguous and diverse domain due to the diversity of security policies and the multiplicity nature of organization systems. Numerous specific and generic ISP models have been offered for several purposes. The offered models have numerous redundant procedures, … …Journal of Computer Science, Vol. 19, Issue 4 · 14 Mar 2023 · 5,467 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Interval Type-2 Fuzzy Association Rule Mining Approach to Pattern Discovery in Breast Cancer DatasetOlufunke Oladipupo, Oluwole Olajide, Stephen Adubi et al.In the literature, several methods explored to analyze breast cancer dataset have failed to sufficiently handle quantitative attribute sharp boundary problem to resolve inter and intra uncertainties in breast cancer dataset analysis. In this study an Interval Type-2 fuzzy association rule mining approach is proposed for pattern discovery in breast cancer dataset. In the first part of this analysis, the … …Journal of Computer Science, Vol. 17, Issue 3 · 6 Apr 2021 · 7,164 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Analysis of Heart Disease for Diabetic Patients Using Recursive Feature Elimination with Random ForestBindushree Doddasiddavanahalli Channabasavaraju, Udayarani VinayakamurthyData Mining Techniques are used in many areas like banking, healthcare, education because of extracting relevant information from the database. Many algorithms in data mining are used to predict the disease to reduce the patient treatment cost as well as increase the diagnosis accuracy. In this research work, the risk level of diabetic heart disease patient can be predicted using … …Journal of Computer Science, Vol. 16, Issue 1 · 27 Jan 2020 · 7,931 accessesView PDFCite