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11 results for “Feature-Aware”
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Research ArticleOpen accessEvery word in the titleLatent Feature-Based Trust-Aware Model for Service Delegation in Social Internet of Things (SIoT)Rahul, Venkatesh, Satish B BasapurThe integration of social networking concepts into the Internet of Things (IoT) paradigm has given rise to Social IoT (SIoT) ecosystems, aiming to address challenges related to network navigation, service discovery, and service composition. A fundamental issue in SIoT is the careful selection of trustworthy devices that provide services. A service provider can offer multiple and diverse services, and different … …Journal of Computer Science, Vol. 21, Issue 12 · 9 Jan 2026 · 1,802 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEW-GAT: Edge-Weighted Graph Attention Framework for Patient-Aware Heart Disease Classification Using Feature-to-Feature Similarity GraphsRamakrishna Reddy Badveli, Nijaguna Gollara Siddappa, Sundeep Kumar KanipakapatnamHeart disease remains an important cause of global death, requiring accurate and clinically interpretable prediction models. However, traditional Machine Learning (ML) methods often fail to capture meaningful dependencies among clinical features and lack robustness across diverse patient populations. To overcome these issues, this research introduces an Edge-Weighted Graph Attention Network (EW-GAT) for patient-aware heart disease classification. The approach first models … …Journal of Computer Science, Vol. 22, Issue 7 · 25 Jul 2026 · 912 accessesView PDFCite
Research ArticleOpen accessIn the abstractExplainability Aware Heterogeneous Temporal Graph Transformer for Automated Genetic Disorder Detection from Genomic DataPuvaneswari Subramaniapillai, Indirani Govindasamy, Revathy GurumurthyGenetic disorders affect millions worldwide, posing major challenges for accurate diagnosis and effective treatments. New developments in genomic technologies, especially Next-Generation Sequencing (NGS), have enhanced the classification of genetic modification and improved diagnostic abilities. Moreover, the Machine Learning (ML) and Deep Learning (DL) methods emerged as efficient tools for evaluating the intricate genomic data and determining the patterns, which can … …Journal of Computer Science, Vol. 22, Issue 11 · 14 Oct 2026 · 566 accessesView PDFCite
Review ArticleOpen accessIn the abstractHuman Activity Recognition at the Edge: A Systematic Review of Machine Learning Models, Deployment Constraints, and Latency Energy Accuracy Trade offsJose Antonio Rojas Guillén, Wini Ebelin Quispe Bautista, Arturo Gamarra MorenoHuman Activity Recognition (HAR) has become a key component of intelligent healthcare monitoring, assisted living, sports analytics, smart environments, and wearable computing. However, the migration of HAR models from cloud-centered architectures to edge, embedded, mobile, and wearable platforms introduces constraints related to computational capacity, memory footprint, battery consumption, inference time, and real-time responsiveness. This study presents a systematic literature review … …Journal of Computer Science, Vol. 22, Issue 8 · 7 Sep 2026 · 593 accessesView PDFCite
Research ArticleOpen accessIn the abstractEpsilon-Insensitive Primal Loss With Support Vector Machine for Robust Cotton Leaf Disease ClassificationPavana Kumar Eramachetty Dhanajayalu, Malathi Sivasamy, Chitveli Siva Balaji YadavCotton diseases significantly reduce both yield and quality of crops, making early and accurate identification of the disease crucial for effective prevention and control. However, achieving a balance between lightweight models and precise classification of cotton diseases remains challenging. This difficulty arises primarily from the dispersed nature of disease symptoms and interference from noisy backgrounds, which complicate the detection process. … …Journal of Computer Science, Vol. 22, Issue 6 · 5 Aug 2026 · 755 accessesView PDFCite
Research ArticleOpen accessIn the abstractCA-LIME: A Collinearity-Aware LIME Framework for Reliable and Interpretable Explanations in Healthcare AIIdris Khan, Sachin BhoiteIn clinical tabular models, correlated biomarkers can make local explanations unstable even when predictive performance appears acceptable. This paper presents CA-LIME, a collinearity-aware extension of LIME built to address that failure mode directly. Five variations of CA-LIME Vanilla reference, VIF, PCA back projection, Ridge, and ElasticNet allow us to investigate how various correlation-control strategies alter explanation behavior. ILPD, Kaggle liver, … …Journal of Computer Science, Vol. 22, Issue 7 · 28 Jul 2026 · 806 accessesView PDFCite
Research ArticleOpen accessIn the abstractUncertainty-Aware Ensemble Models for Improved Defect Detection in Noisy DataMadhavi Perla, Gadi Lava Raju, A Radha Krishna et al.Software defect prediction plays a crucial role in ensuring software quality and reliability, especially as modern systems become more complex and data rich. This study introduces an uncertainty-aware ensemble learning framework aimed at improving defect classification performance in noisy and imbalanced datasets, particularly those from the PROMISE and NASA KC1 repositories. The proposed model integrates multiple classifiers in a multi-learner … …Journal of Computer Science, Vol. 22, Issue 4 · 27 Apr 2026 · 1,542 accessesView PDFCite
EditorialOpen accessIn the abstractIs Rerum® the New Coley's Vaccine?Marco RuggieroColey's Vaccine and Cancer Immunotherapy Dr. William B. Coley is credited for having been the first to translate the observation of an association between bacterial infections, high fever and cancer remission into a successful cancer treatment. However, it is worth noting that such an association dates back to at least one century before Coley's times; as Wiemann and Starnes from … …American Journal of Immunology, Vol. 13, Issue 2 · 31 May 2017 · 12,281 accessesView PDFCite
Research ArticleOpen accessIn the abstractREVIEW ON MULTI-AGENT SYSTEM COLLABORATION IN LEARNING MANAGEMENT SYSTEM DOMAIN BY DEPLOYING WIRELESS SENSOR NETWORKS FOR STUDENT LOCATION DETECTIONA. K. Mwinyi, S. A.R. AL-Haddad, S. J. Bin Hashim, R. Bin Hj AbdullahStudent location detection in Learning Management System (LMS) by utilizing Multi-Agent System (MAS) which contains sensor nodes is a new area of research. This study reviews several studies to ascertain the potential of integrating these two technologies to automate students’ class attendance in Higher Learning Institutions (HLIs). Currently, the HLIs are using paper-based process to record students’ attendance in the … …Journal of Computer Science, Vol. 10, Issue 6 · 30 Jan 2014 · 7,677 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Data Mining Model for Students’ Choice of College Major Based on Rough Set TheoryLuai Al-ShalabiLiterature is focusing on identifying factors that influence students’ initial choice of major and few have studied students’ involvements after registration in a selected major and this study is one of the few. This study aims to determine the important factors that influence high school students’ choice of major based on data mining techniques. A questionnaire was designed to collect … …Journal of Computer Science, Vol. 15, Issue 8 · 22 Aug 2019 · 7,827 accessesView PDFCite