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295 results for “learning methods”

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Research NotesOpen accessIn the keywordsCould the Hybrid form of Lecturing and Active Learning be used as a Curricular Tool for Medical Education of Immunology in Algeria?Kheir Eddine Kerboua, Kamal DjenouhatLecturing has been the predominant mode of instruction since universities were founded in Western Europe over 900 y ago and still the sole method of instruction in the developing countries. However, claiming that adopting a specific new method will have reproducible results regardless the population’s characteristics is simply not possible. In this study, we sought to demonstrate that hybrid form … …American Journal of Immunology, Vol. 15, Issue 1 · 6 Dec 2019 · 7,217 accessesView PDFCite
Review ArticleOpen accessIn the keywordsA Wide Scale Classification of Class Imbalance Problem and its Solutions: A Systematic Literature ReviewGillala Rekha, Amit Kumar Tyagi, V. Krishna ReddyIn today’s world, most of the data (real world) is present in imbalanced form by nature. This is because of not having efficient algorithms to put this data (i.e., generated data by billion of internet- connected devices (IoTs)) in respective format. Imbalanced data poses a great challenge to (both) data mining and machine learning algorithms. The imbalanced dataset consists of … …Journal of Computer Science, Vol. 15, Issue 7 · 3 Jul 2019 · 9,372 accessesView PDFCite
Research ArticleOpen accessIn the keywordsBiometric Gait Recognition Based on Machine Learning AlgorithmsMohamed SayedIt is crucial to find methods that analyze large amount of data captured by cameras and/or various sensors installed all around us. Machine learning becomes a prevailing tool in analyzing such data that signifies behavioral characteristics of human beings. Gait as an identifier for use in individual recognition systems has respective and almost certainly unique key features for each person … …Journal of Computer Science, Vol. 14, Issue 7 · 6 Aug 2018 · 8,984 accessesView PDFCite
Research ArticleOpen accessIn the keywordsInstructional Methods to Computer Science Education as Investigated by Computer Science TeachersAndreas Zendler, Dieter KlaudtAnswers to the questions of which instructional methods are suitable for school, what instructional methods should be applied in teaching individual subjects and how instructional methods support the act of learning represent challenges to general education and education in individual subjects. This article focuses on computer science teachers´ examination of instructional methods supporting knowledge processes in the act of learning. … …Journal of Computer Science, Vol. 11, Issue 8 · 19 Nov 2015 · 7,883 accessesView PDFCite
Research ArticleOpen accessIn the keywordsModerators of the Effectiveness of Adult Learning Method PracticesCarl J. Dunst, Carol M. TrivetteProblem statement: The purpose of the analyses reported in this study was to identify the moderators of the effectiveness of evidence-based adult learning method practices. Approach: The particular practices that were found most effective in 58 randomized controlled design studies of four adult learning methods were examined to identify the conditions under which learner outcomes were optimized. Results: Thirteen different … …Journal of Social Sciences, Vol. 8, Issue 2 · 18 Feb 2012 · 11,541 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFeature Subset Selection for Hot Method Prediction using Genetic Algorithm wrapped with Support Vector MachinesSandra Johnson, Valli ShanmugamProblem statement: All compilers have simple profiling-based heuristics to identify and predict program hot methods and also to make optimization decisions. The major challenge in the profile-based optimization is addressing the problem of overhead. The aim of this work is to perform feature subset selection using Genetic Algorithms (GA) to improve and refine the machine learnt static hot method predictive … …Journal of Computer Science, Vol. 7, Issue 5 · 7 May 2011 · 7,234 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
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 abstractLeveraging Modified Cascaded Fully Convolutional Neural Networks and Optimized Swin U-Net for Liver Lesion PredictionSugandha Chakraverti, Tejaswi Khanna, Vijay ShuklaLiver lesions are abnormal growths that can develop for various reasons, some of which are noncancerous (benign) while others are cancerous. Machine learning and, deep learning techniques are employed for liver health assessment and lesion detection, but the quality and, diversity of training data can hinder the performance, leading to overfitting or underfitting. These models often need extensive pre-processing and … …Journal of Computer Science, Vol. 22, Issue 10 · 8 Oct 2026 · 372 accessesView PDFCite
Research ArticleOpen accessIn the abstractTAGN-IDC: Implicit Discrete Constraints for Tsunami Aware Graph Neural Networks in Spatial Evacuation RoutingSularno, Wendi Boy, Putri Anggraini et al.Tsunami evacuation route requires rapid identification of safe evacuation paths under dynamically changing hazard conditions. A major challenge is incorporating hard binary road-blockage constraints caused by tsunami inundation while maintaining end-to-end differentiability for deep learning models. Existing approaches commonly rely on continuous relaxations or stochastic sampling techniques, which either compromise physical feasibility or increase computational complexity. This study proposes the … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 704 accessesView PDFCite