Research ArticleOpen accessEvery word in the titleGlobal Supply Chain: Enhance Production Cost Efficiency Through Machine LearningLoubna Moumeni, Mohammed SaberMachine learning has enabled the discovery of various disciplines and patterns in Supply Chain Management (SCM). The entire industrial sector is striving to harness the contextual intelligence provided by machine learning by exploring new areas within the supply chain network. This article delves into Supply Chain Management (SCM) and its broader implications beyond logistics. SCM involves the resources, methods, and … …Journal of Computer Science, Vol. 20, Issue 9 · 14 Jun 2024 · 5,316 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleISSP: New Designed Software Package to Enhance E-Learning ApproachIbrahiem M.M. El Emary, Hussain F. SindiThe objective of this study was to present a new software tool assists in enhancing E-learning approach. The presented system is called Instructor- Student Software Package (ISSP). The proposed ISSP contains three main modules: firstly, the lecturing module which is designed to help instructor create lecture notes. Secondly, examination module which is designed to help instructor creates exams available over … …Journal of Computer Science, Vol. 2, Issue 2 · 28 Feb 2006 · 6,798 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleINVESTIGATION OF STUDENT'S PERSONALITY ON PAIR PROGRAMMING TO ENHANCE THE LEARNING ACTIVITY IN THE ACADEMIAV. Venkatesan, A. SankarAgile Software development is now a global phenomenon and is rapidly becoming organizations' most preferred IT process. Extreme Programming (XP) is one of the Agile Methods and Collaborative Pair Programming (CPP) is one of the very important practices of eXtreme Programming. Agile focuses team work which is very important in the field of software development. The software industry has practiced … …Journal of Computer Science, Vol. 10, Issue 10 · 26 Jun 2014 · 6,865 accessesView PDFCite
Research ArticleOpen accessIn the keywordsInstrument of Primary School Teacher CompetencyAbdulghani M. Alnoor, Ma HongyuProblem statement: The study aimed to investigating the Primary School Teacher Competency (PSTC) and design an PSTC instrument to reflect state standard and use this instrument to compare and evaluate primary school teacher competency. Approach: For this reason, the researcher formulated the following question. What are the necessary teaching competencies of Primary School Teachers (PSTC)? To find answer to the … …Journal of Social Sciences, Vol. 7, Issue 4 · 16 Sep 2011 · 8,817 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Machine Learning Approach to Predictive Analytics in Precision Agriculture for Sustainable Crop OptimizationJignesh Kariya, Pankaj MudholkarDriven by data-enabled technologies, precision agriculture is evolving into an innovative way to increase agricultural productivity and sustainability. Conventional agricultural practices face several challenges, such as poor soil quality, inappropriate crop selection, improper resource utilization, and unpredictable climate conditions. To address these limitations, this paper proposes a hybrid machine learning framework for sustainable crop optimization and predictive analysis in precision … …Journal of Computer Science, Vol. 22, Issue 10 · 10 Oct 2026 · 865 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Active Learning Ensemble Framework for Tropical Crop Yield PredictionAmol Bhilare, Debabrata Swain, Megh Patel et al.Agriculture always has great importance among all different sectors, not only in the world but also in India. It has a significant impact on food security and largely controls the economy. At present, technological advancements have significantly enhanced agricultural productivity, but it can still be further improved by the integration of new cutting-edge techniques like Artificial intelligence. Among the factors … …Journal of Computer Science, Vol. 22, Issue 9 · 11 Sep 2026 · 819 accessesView PDFCite
Research ArticleOpen accessIn the abstractCrop Disease Detection via an Improved Residual NetworkGuolin Chen, Weifeng Liu, Xinyu Zou, Xiaoxia LiDeep learning has shown substantial potential across many domains, and crop disease detection is no exception. This study investigates the application of deep learning to crop disease detection, systematically evaluating the performance of convolutional neural networks of different depths. Building on the classical ResNet-50 as the base model, we introduce a Squeeze-and-Excitation (SE) attention mechanism to enhance feature extraction. The … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 2 · 31 Jul 2026 · 898 accessesView PDFCite
Research ArticleOpen accessIn the abstractMedFusion: A Unified Multimodal Framework for Visual Question Answering and Explainable Medical RecommendationSatyajit Mahapatra, Jibitesh Mishra, Kumar Janardan Patra et al.In clinical decision-making, the ability to ask visual questions about medical images and receive accurate, personalized, and interpretable recommendations can significantly enhance practitioner support systems. This paper presents MedFusion, a unified multimodal framework that integrates Visual Question Answering (VQA), personalized medical recommendation, and explainability within a single architecture. The proposed model employs co-attention–based visual–textual fusion augmented with retrieval-enhanced reasoning to … …Journal of Computer Science, Vol. 22, Issue 5 · 20 May 2026 · 1,360 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligent Multi Model Ensemble for Engagement PredictionFahmida Begum, K Ulaga PriyaFor intelligent educational systems, the ability to monitor and respond to student engagement in real time is essential for enhancing learning outcomes. However, existing models often lack adaptability and practical deployment potential, as they depend on single data modalities, rigid ensemble mechanisms, and post-session analysis. This study introduces an intelligent multimodal ensemble framework designed to address these challenges by predicting … …Journal of Computer Science, Vol. 22, Issue 4 · 28 Apr 2026 · 1,844 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