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386 results for “modeling approach”
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Research ArticleOpen accessIn the abstractAn Automatic Transformation Method from the E3value Model to IFML Model: An MDA ApproachNassim Kharmoum, Soumia Ziti, Yassine Rhazali, Fouzia OmaryNowadays the software industry has known a significant growth, while the end-users have become very demanding. In this sense, the model transformation has become one of the essential solutions to ensure competitiveness in the field of the software industry domain. For that, the Object Management Group (OMG) proposes for the Model-Driven Architecture (MDA) approach three abstraction levels, namely Computation Independent … …Journal of Computer Science, Vol. 15, Issue 6 · 12 Jun 2019 · 7,899 accessesView PDFCite
EditorialOpen accessIn the abstractFocalize the Structure of Myd88 in TLR Signaling Pathway to Modulate Innate Immune Response: New Target for Old DiseasesShuai Xing, Ping ZhouAll diseases have their Achilles’ Heel to target and this is especially true for immunorelated diseases which must be treated by targeting the immune system somewhere and somehow correctly. In the most recent decade, immunologists recognized that the Toll-Like Receptor (TLR) signaling pathway in innate immune system plays a double-edged role in the pathogenesis of many notorious diseases. Although the … …American Journal of Immunology, Vol. 13, Issue 3 · 6 Sep 2017 · 7,865 accessesView PDFCite
Research ArticleOpen accessIn the abstractReinforcement Learning in Financial Services: Modelling Payment Switching as a Multi-Armed Bandit ProblemIshaya Gambo, Christopher Agbonkhese, Segun Aina et al.The ever-evolving landscape of digital payments demands continuous innovation and self-improvement. This study addresses this imperative by simulating a model for payment routing, a crucial aspect of the digital payment ecosystem. To achieve this, industry professionals were interviewed to inform the approach, emphasizing data randomization for effective data collection. Using Python, a randomized dataset is created and three Reinforcement Learning … …Journal of Computer Science, Vol. 20, Issue 11 · 12 Oct 2024 · 4,717 accessesView PDFCite
Research ArticleOpen accessIn the abstractDevelopment of Big Data Classifier for Biomedicine Early Diagnosis: An Experimental Approach Using Machine Learning MethodsMa Beth Solas Concepcion, Bobby Dioquino Gerardo, Frank Ibañez Elijorde et al.In the fast-phase world, data availability is abundant due to a rapid adaptation increase of big data technologies. Large amounts of data have been generated and collected at an unprecedented speed and scale, introducing a revolution in medical research practices for biomedicine informatics. Thus, there is an immense demand for statistically rigorous approaches, especially in the medical diagnosis discipline. Therefore, … …Journal of Computer Science, Vol. 20, Issue 4 · 1 Feb 2024 · 5,516 accessesView PDFCite
Research ArticleOpen accessIn the abstractFlock Optimization Algorithm-Based Deep Learning Model for Diabetic Disease Detection ImprovementDivager Balasubramaniyan, Nor Azura Husin, Norwati Mustapha et al.Worldwide, 422 million people suffer from diabetic disease, and 1.5 million die yearly. Diabetes is a threat to people who still fail to cure or maintain it, so it is challenging to predict this disease accurately. The existing systems face data over-fitting issues, convergence problems, non-converging optimization complex predictions, and latent and predominant feature extraction. These issues affect the system's … …Journal of Computer Science, Vol. 20, Issue 2 · 8 Jan 2024 · 5,216 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hierarchical Clustering Approach for DBpedia based Contextual Information of TweetsVenkatesha Maravanthe, Prasanth Ganesh Rao, Anita Kanavalli et al.The past decade has seen a tremendous increase in the adoption of Social Web leading to the generation of enormous amount of user data every day. The constant stream of tweets with an innate complex sentimental and contextual nature makes searching for relevant information a herculean task. Multiple applications use Twitter for various domain sensitive and analytical use-cases. This paper … …Journal of Computer Science, Vol. 16, Issue 3 · 25 Mar 2020 · 7,254 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Electric Vehicle Charging Demand Prediction Using a Novel SAE-DNN Neural Network Model for Probabilistic ForecastingNaga Raju Hari Manikyam, A. Thangam, J. Murugachandravel et al.The rapid growth and widespread adoption of Electric Vehicles (EVs) play a crucial role in the progress of intelligent transportation systems, resulting in a significant decrease in environmentally damaging greenhouse gas emissions. The increase in EV usage has made it crucial to develop charging infrastructure to keep up with the growing demand. Precisely predicting EV charging demand is crucial to … …Journal of Computer Science, Vol. 21, Issue 10 · 11 Dec 2025 · 3,543 accessesView PDFCite
Research ArticleOpen accessIn the abstractLeast Absolute Deviation Regression and Least Squares for Modeling Retention Indices of Set Compounds Food and Pollutants of the EnvironmentFatiha Mebarki, Khadija Amirat, Salima Ali Mokhnach, Djellol MessadiConsidering the importance of the statistical analysis of regression in modeling based separately on study for Quantitative structure retention indices on Carbowax 20 M (ICw20M) and OV-101 columns (IOV-101) relationships (QSRR) are determined for 114 pyrazines. The detection of influential observations for the standard least squares regression model is a problem which has been extensively studied. Least Absolute Deviation regression … …American Journal of Applied Sciences, Vol. 14, Issue 5 · 5 Jun 2017 · 7,431 accessesView PDFCite
Research ArticleOpen accessIn the abstractSparse Representation Tracking with Auxiliary Adaptive Appearance ModelsJunqiu Wang, Chao Yang, Zhichao Gan, Yasushi YagiWe propose an effective tracking algorithm based on sparse representation and auxiliary adaptive appearance modeling. Based on a sparse representation, l1 minimization can follow targets in challenging situations. Unfortunately, tracking approaches based on l1 minimization are likely to be inefficient because they measure using dense coefficient distributions. The number of target candidates can be very large when the state space … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 1 · 14 Jan 2017 · 7,681 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplying Dempster Shafer Theory and Causal Inference in Investigating Internet of Things Digital Forensic ChallengeMohamed El-Dosuky, Sherif K. Ratib et al.The rapid growth of IoT ecosystems has transformed digital forensics, creating challenges in analyzing distributed, heterogeneous, and uncertain evidence. Conventional forensic methods often struggle to handle ambiguous and conflicting IoT data, highlighting the need for robust frameworks that effectively manage uncertainty across multiple evidence sources. This research presents a hybrid forensic framework that integrates Dempster Shafer Theory (DST) for probabilistic … …Journal of Computer Science, Vol. 22, Issue 10 · 10 Oct 2026 · 901 accessesView PDFCite