Research ArticleOpen accessIn the abstractRelational Contracting in the Building Sector in Jordan as a Substitute to Conventional Formal MethodsRazan Aleasawi, Sultan TarawnehThe socioeconomic policies within the Hashemite Kingdom of Jordan aim to enhance the Public-Private Partnership (PPP), one of the Relational Contracting models, to encourage investment, improve public services, upgrade infrastructure and boost financial resources, in line with Jordan 2025 Vision (Ministry of Municipal Affairs, 2014). The construction sector itself has a growth plan of 5% in order to meet this … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 1 · 25 Mar 2020 · 6,673 accessesView PDFCite
Research ArticleOpen accessIn the abstractPandemic Analysis and Preparedness Using a Three Layer Machine Learning ApproachArtika Singh, Manisha JailiaOutbreak analysis provides research-based information and data to enable scientific decision-making to manage an effective response to a pandemic. Pandemic analysis has its own set of challenges, such as limited data, the need for real time analysis, and the complexity of outbreak patterns. This study proposes a hybrid approach to manage such a spread through a 3-layer machine learning-based outbreak … …Journal of Computer Science, Vol. 22, Issue 11 · 15 Oct 2026 · 614 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Data Mining Driven Framework for Image-Based Crop Stress Analysis Using IPCA, FP-Growth, ConvLSTM, and Sequential ModelsA. Josephine, A. SubhashiniDetecting crop stress before it becomes serious has a major impact on the food supply. It helps in avoiding the loss of crops, increases productivity and helps farmers to practice precision farming. Most technologies today are designed specifically to either detect crop stress or to predict how well the crop will grow. Many of the technologies do not combine the … …Journal of Computer Science, Vol. 22, Issue 8 · 21 Aug 2026 · 922 accessesView PDFCite
Research ArticleOpen accessIn the abstractAttribute Reduction in Bipolar Intuitionistic Fuzzy Relation SystemWeiyuan Wang, Qian WangBipolar intuitionistic fuzzy relation system (BIFRS) effectively characterize the bipolarity in real-world data by introducing positive and negative membership and non-membership degrees. To address redundancy caused by high-dimensional attributes, this paper proposes an attribute reduction method based on bipolar intuitionistic discernibility matrices. By constructing positive discernibility matrix M+∗ matrix M−∗ and negative discernibility , we systematically identify the minimal attribute … …Journal of Mathematics and Statistics, Vol. 22, Issue 1 · 16 Jul 2026 · 1,063 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn AI-Assisted Research Automation System for Scholarly Paper Retrieval and Review With Workflow OrchestrationSompoch Tongnamtiang, Manirath Wongsim, Natarpha SatchawateeThe rapid growth of scholarly publications has increased the complexity of conducting rigorous and reproducible literature reviews, while traditional manual review processes are increasingly constrained by information overload, time consumption, and inconsistencies in screening decisions. This study proposes an AI-assisted research automation system that integrates workflow orchestration with literature retrieval and review support mechanisms to address these challenges. The workflow … …Journal of Computer Science, Vol. 22, Issue 7 · 6 Jul 2026 · 1,491 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredictive Mathematical Modeling and Classification of Retail Sales Orders Using AI Machine Learning TechniquesMohammad Subhi Al-Batah, Mowafaq Salem Alzboon, Hamzeh ZureigatThis study presents a systematic mathematical model known as a low-code approach to classifying retail sales orders by size using AI machine learning techniques within the Orange Data Mining platform. Leveraging a real-world sales dataset sourced from Kaggle, we implemented and evaluated ten classification models, including ensemble learners (AdaBoost, Gradient Boosting), probabilistic classifiers (Naïve Bayes), distance-based methods (kNN), and interpretable … …Journal of Computer Science, Vol. 22, Issue 3 · 10 Mar 2026 · 1,567 accessesView PDFCite
Research ArticleOpen accessIn the abstractSystematic Literature Review of Graph Neural Networks in Disaster Management: Methods, Applications, and Future DirectionsSularno, Wendi Boy, Putri Anggraini et al.The increasing frequency and complexity of natural disasters underscore the urgent need for intelligent systems that support timely and effective decision-making. Graph Neural Networks (GNNs) have emerged as a powerful deep-learning paradigm for modeling spatial and relational data, offering distinct advantages for disaster management. This study presents a Systematic Literature Review (SLR) of GNN-based approaches for disaster mitigation, emergency response, … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 2,036 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluating Online Learning in India: Insights from StudentsRitu Gupta, Anuradha Khattar, Meetu Bhatia Grover et al.As technology has advanced, the educational system has undergone numerous modifications. The benefits of online teaching and learning include increased accessibility, reduced costs, and the opportunity to learn at any time and from any location. However, a few drawbacks of this approach include a decline in student involvement, a lack of face-to-face interaction with classmates and teachers, and technical difficulties. … …Journal of Computer Science, Vol. 22, Issue 1 · 10 Feb 2026 · 1,595 accessesView PDFCite