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30 articles for “Capability Models”
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Research ArticleOpen accessIn the keywordsSOFTWARE PROCESS MATURITY AND CAPABILITY EVALUATION AND ITS IMPLEMENTATION IN THE AREAS OF E-LEARNING ORGANIZATIONSSenthilkumar Chennakrishnan, Midthe Vijayaraghavan SrinathA detailed literature review revealed that, most of the organizations develop their projects and associated software engineering activities using in-house established methods. There are discrete references in the literature on application of broad based scientific methods in designing and developing process capability and maturity models by software organizations. Documentation and extent of adherence to a well defined organized scientific method … …Journal of Computer Science, Vol. 10, Issue 4 · 21 Dec 2013 · 6,830 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Fleet Management with GPS Data in Port Terminals: A Deep Learning Architecture for Truck Position PredictionMohammed El Karkraoui, Hicham AttariuasEffective truck fleet management in port terminals is crucial for improving operational efficiency and reducing delays. However, GPS-based positioning systems often face limitations in port environments due to signal obstructions and network issues. This study explores the utilization of advanced methods for deep learning, particularly Recurrent Neural Networks (RNNs) for predicting truck positions when GPS signals are unavailable or unreliable. … …Journal of Computer Science, Vol. 21, Issue 10 · 16 Dec 2025 · 2,271 accessesView PDFCite
Research ArticleOpen accessIn the abstractAI-Based Feature Extraction Approaches for Dual Modalities of Autism Spectrum Disorder NeuroimagesMeenakshi Malviya, Chandra J, Nagendra NHigh-dimensional data, lower detection accuracy, susceptibility to manual errors, and the requirement of clinical experts are some drawbacks of conventional classification models available for Autism Spectrum Disorder (ASD) detection. To address these challenges and explore the affiliated information from advanced imaging modalities such as Magnetic Resonance Imaging (MRI) in structural MRI (sMRI) and resting state-functional MRI (rs-fMRI), the study applied … …Journal of Computer Science, Vol. 20, Issue 11 · 28 Sep 2024 · 5,087 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 abstractFuzzyNET: A Fuzzy Logic-Based Framework for Enhancing Urban Efficiency in Smart CitiesHemant Kumar, Safdar Tanweer, Parul Agarwal et al.The smart city paradigm emphasizes the strategic use of IoT, Big Data, and digital technologies to optimize urban operations and improve service delivery for citizens. Embedding digital technologies within operational workflows is driven by the objective of improving efficiency and long-term sustainability. The core transformation is Artificial Intelligence (AI) that revolutionizes management of cities through automation and instantaneous decisions based … …Journal of Computer Science, Vol. 22, Issue 7 · 19 Jul 2026 · 820 accessesView PDFCite
Research ArticleOpen accessIn the abstractInternet of Things and Human Neocortex Inspired Algorithms for the Plant Disease Prediction-Sheath Blight for Paddy PlantThangaraj Ethilu, K. Parthiban, Arockia Jayadhas S et al.Sheath blight disease (Rhizoctonia solani) poses a critical threat to paddy (Oryza sativa) production, causing up to 50% yield losses under conducive environmental conditions. Existing computer vision-based disease detection systems identify infections only after symptom manifestation, while conventional machine learning prediction models suffer from high computational demands, data preprocessing requirements, and noise sensitivity. This research proposes a novel Hierarchical Temporal … …Journal of Computer Science, Vol. 21, Issue 11 · 18 Dec 2025 · 1,772 accessesView PDFCite
Research ArticleOpen accessIn the abstractEmpirical Study on Modified Pre-Trained CNN Architectures for Fitzpatrick17k Skin Diseases Prediction ModellingSteven Matthew, Nur Afny Catur Andryani, Rojali et al.Preventing missed diagnosis of skin diseases is critical for enhancing patient outcomes. Technology support empowered by AI based algorithms have been recently developed to minimize the burden. Convolutional Neural Networks (CNNs) are increasingly utilized for image classification tasks including skin's diseases prediction modelling. Its advancement architectures such as pre-trained models, VGG16 andResNet50 provide a strong foundation to up-skill the prediction … …Journal of Computer Science, Vol. 21, Issue 7 · 8 Jul 2025 · 3,934 accessesView PDFCite
Research ArticleOpen accessIn the abstractLeafsnapNet: An Experimentally Evolved Deep Learning Model for Recognition of Plant Species based on Leafsnap Image DatasetEmmanuel Adetiba et al.Plants are very important living organisms on earth because humans and animals depend on them for nutrition, oxygen, medicine and balance in the ecosystem. Therefore, plant species recognition is critical to the improvement of agricultural productivity, mitigation of climate change and the discovery of new medicinal plants. However, species recognition has remained a difficult task even for trained botanists, because … …Journal of Computer Science, Vol. 17, Issue 3 · 1 Apr 2021 · 7,956 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of a Beta Regression Model for Covariate Adjusted ROCXing Meng, J.D. TubbsThe Receiver Operating Characteristic (ROC) curve and the area under the ROC (AUC) are widely used in determining the diagnostic capability of a binary classification procedure. Since the test performance is affected by covariates, the ROC and AUC have been utilized in a Generalized Linear Regression (GLM) setting. In this study, we revisit a problem where the AUC regression model … …Current Research in Biostatistics, Vol. 10, Issue 1 · 18 Jun 2020 · 13,966 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Algorithm To Determine The Maturity Improvement Plan For Information System Risk Management. Application On A Case StudySoumaya Amraoui, Mina Elmaallam, Hicham BensaidA good and relevant Risk Management process is a key issue when Information System effective governance is concerned. Therefore, several paradigms have been devised to help achieving such goal. Among these paradigms, maturity models are quite popular. The main aim of a maturity model is to help users improve their activities capability. However, one of the major challenges encountered when … …Journal of Computer Science, Vol. 15, Issue 8 · 1 Aug 2019 · 7,636 accessesView PDFCite