Research ArticleOpen accessIn the keywordsTest Anxiety and Foreign Language Reading Anxiety in a Reading-Proficiency TestYa-Chin Tsai, Yi-Chih LiProblem statement: The impact of foreign-language anxiety has been researched with respect to the reading domain; however, how it affects reading proficiency in relation to test anxiety in a test situation is yet to be explored. Approach: This study investigated possible relationships between test anxiety, foreign language reading anxiety and English reading proficiency by using scales published in previous studies. … …Journal of Social Sciences, Vol. 8, Issue 1 · 8 Feb 2012 · 15,184 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 abstractAnchoring Public Health Forecasts: High-Precision Obesity Prevalence Estimation Via Hybrid Geodemographic Ensemble RegressionTrenton Ward, Isaac OsunmakindeObesity remains a major driver of chronic disease and rising healthcare costs in the United States. Yet, most existing predictive models rely on single-model classifiers and rarely incorporate spatial structure or ensemble-based regression, thereby limiting their ability to capture geodemographic variation. This study introduces a hybrid unsupervised–supervised ensemble framework that integrates K-Means spatial profiling with a Stacking Regressor to address … …Journal of Computer Science, Vol. 22, Issue 7 · 31 Jul 2026 · 632 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 abstractCrop Yield Prediction in Niger Using Machine Learning TechniquesMahaman Lawali Inoussa Garba, Naroua Harouna, Chaibou Kadri et al.Agriculture is the most impactful sector on Niger's economic growth. Stresses related to climate change and the environment are leading to a continuous decline in crop yield. Accurate crop yield forecasting is of paramount importance for farmers, government, policy makers, and other stakeholders to make most appropriate decisions regarding resource allocation and food security. This study examines the power of … …Journal of Computer Science, Vol. 21, Issue 8 · 16 Sep 2025 · 5,792 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Transfer Learning Approach for Student Attendance System During the COVID-19 PandemicSlimane Ennajar, Walid BouarifiMarking students' attendance has been a challenge during the COVID-19 pandemic. It is a time-consuming task due to the abnormally high number of students present during a learning session; many studies have been proposed to improve the system. However, there are still issues with each of these systems; we have employed deep transfer learning techniques using six pre-trained convolutional neural … …Journal of Computer Science, Vol. 20, Issue 3 · 16 Jan 2024 · 6,010 accessesView PDFCite
Research ArticleOpen accessIn the abstractSoft Marking Scheme of SVM Hierarchical Classifiers for Attack ClassificationAzizi Abdullah, Warhamni Jani@MokhtarClassification is a predictive modelling problem that involves assigning a class label to an instance correctly. There exist several strategies in machine learning to deal with the multi-class classification problems for attack detection. One of the popular strategies is the one-vs-one that decomposes the multi-class problem into multiple binary ones. The approach has been applied in many popular supervised learning … …Journal of Computer Science, Vol. 17, Issue 9 · 27 Sep 2021 · 6,000 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Personalized Learning Approach based on Learning SpeedHicham Aberbach, Adil Jeghal, Abdelouahed Sabri et al.This learning is a process composed of several mechanisms oriented towards the acquisition of certain knowledge, whose actors are called learner and teacher, to improve the effectiveness and usefulness of learning we need to personalize the knowledge, skills and behaviors that allow for a change to a mode of education that gives diverse learning choices to the learners, where the … …Journal of Computer Science, Vol. 17, Issue 3 · 5 Apr 2021 · 7,977 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Framework for Computerized Progress Feedback in Tertiary EducationAnnette van der Merwe, Tiny du Toit, Hennie KrugerThe dawn of democracy in South Africa in 1994 has resulted in challenges in many fields, especially in education. University enrolment rates are high and the output quality of school learners in general is delicate which threatens the graduate quality of tertiary institutions. Contrary to rising student enrolments, the attrition rates have not improved. One contributing factor is the lack … …Journal of Computer Science, Vol. 16, Issue 3 · 28 Mar 2020 · 6,943 accessesView PDFCite
Research ArticleOpen accessIn the abstractFall Detection Using the Histogram of Oriented Gradients and Decision-Based FusionMohamed Maher Ben Ismail, Arwa AlGabas, Ouiem BchirAs the number of fall incidents among elderly people and patients are continuously growing, researches boosted their researches to propose efficient automatic fall detection systems. In particular, they formulated the fall detection problem as a supervised learning task where some visual features are extracted from the video frames and used to automatically identify the position of a human as “Fall” … …Journal of Computer Science, Vol. 16, Issue 2 · 26 Feb 2020 · 7,500 accessesView PDFCite