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134 results for “computational methods”

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Research ArticleOpen accessIn the abstractRandom Forest-Based Genome Analysis for Disease Association and SNP Marker IdentificationXiangdong LiuAt present, genomic data analysis has the problems of insufficient model interpretation and limited computational efficiency in disease association research. As a powerful machine learning algorithm, Random Forest has demonstrated excellent ability in processing complex and multi-dimensional data sets and has gradually become a popular tool in the field of bioinformatics. The purpose of this paper is to explore how … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 2 · 25 Jul 2025 · 5,533 accessesView PDFCite
Research ArticleOpen accessIn the abstractCUDA-Powered EDSR x4: Super-Resolution for Real-Time Video EnhancementGaneshayya Shidaganti, Shubeeksh Kumaran, Vishwachetan DSuper-Resolution enhances image or video quality by upscaling frames to higher resolutions, which is essential for applications like investigative analysis demanding higher quality. However, this process is resource-intensive. GPUs, with their thousands of CUDA cores, offer significant parallel processing advantages over CPUs, enabling faster performance. This paper presents an optimized approach for real-time video enhancement using the EDSR x4 model … …Journal of Computer Science, Vol. 21, Issue 6 · 23 May 2025 · 5,805 accessesView PDFCite
Review ArticleOpen accessIn the abstractEducational Challenges in Computer-based Finite Element Analysis and Design of StructuresVagelis Plevris, Gro MarkesetComputer simulations and computational methods, such as the Finite Element Analysis (FEA) have become essential methodologies in science and engineering during the last decades, in a wide variety of academic fields. Six decades after the invention of the digital computer, advanced FE simulations are used to enhance and leapfrog theoretical and experimental progress, at different levels of complexity. Particularly in … …Journal of Computer Science, Vol. 14, Issue 10 · 26 Oct 2018 · 8,625 accessesView PDFCite
Research ArticleOpen accessIn the abstractStructural Performance of Double Laminated Glass Panels with EVA and PVB Interlayer in Four-Point Bending TestsTomáš Hána, Martina Eliášová, Zdeněk SokolMany examples of glass loadbearing structures such as handrails, panes, beams and columns can be found in modern architecture. Most of these elements are made of laminated glass panels. There is a general lack of knowledge about the transfer of shear forces between the glass plies in perpendicularly-loaded laminated panels. This transfer depends significantly on the stiffness of the polymeric … …International Journal of Structural Glass and Advanced Materials Research, Vol. 2, Issue 1 · 14 Aug 2018 · 13,274 accessesView PDFCite
Research ArticleOpen accessIn the abstractEssential Proteins Discovery Methods based on the Protein-Protein Interaction NetworksLingZhi Zhu, Junling Zhang, Lingya He et al.Essential proteins are closely related to biological survival or reproduction and have important application value in respect of the location of disease genes, disease diagnosis and treatment, drug design. In order to discovery essential proteins, the researchers have proposed experimental approaches, but these methods require laborious and time consuming. With the development of high-throughput sequencing techniques, plenty of computational methods … …American Journal of Biochemistry and Biotechnology, Vol. 13, Issue 4 · 1 Jan 2018 · 8,891 accessesView PDFCite
Review ArticleOpen accessIn the abstractHybrid Machine Learning Framework with Data Analytics Model for Privacy-Preserved Intelligent Predictive Maintenance in Healthcare IoTArun Ganji, D. Usha, P.S. RajakumarFederated Learning (FL) is a cutting-edge approach for developing machine learning (ML) models using distributed datasets while preserving data privacy and ownership. FL is particularly suited for Internet of Things (IoT) networks due to its decentralized nature, which supports In-Edge AI and maintains data locality. However, FL's complexity poses challenges in analyzing system health, making it crucial to develop robust … …Journal of Computer Science, Vol. 21, Issue 1 · 30 Nov 2024 · 5,821 accessesView PDFCite
Review ArticleOpen accessIn the abstractMachine Learning Integration for Precise Facial Micro-Expression RecognitionViola Bakiasi Shtino, Markela Muça, Senada BushatiThis study advances facial micro-expression recognition through innovative machine-learning techniques, addressing critical needs in psychology, security, and human-computer interaction. The purpose of this study is to improve micro-expression recognition through the optimization of feature transformation and machine learning algorithms. We introduce a novel approach combining Kernel Principal Component Analysis (KPCA) and Uniform Manifold Approximation and Projection (UMAP) for dimensionality reduction, … …Journal of Computer Science, Vol. 20, Issue 11 · 22 Oct 2024 · 5,592 accessesView PDFCite
Review ArticleOpen accessIn the abstractThe Popular Fuzzy-TOPSIS as the Main Method for Decision Model: An Object-Driven Model for Bibliometric-Based Literature ReviewDitdit Nugeraha UtamaFuzzy logic serves as a computational modeling method, particularly prominent in the research domain of decision models. To assess the prevalent trends in the utilization of fuzzy logic in the research landscape of decision models and its common combinations with other methods, a conceptual model for article review was developed. This study involved three simple stages: Bibliometric analysis, article review … …Journal of Computer Science, Vol. 20, Issue 11 · 11 Sep 2024 · 4,811 accessesView PDFCite
Research ArticleOpen accessIn the abstractCrime Rate Analysis and Mapping from Socio-Economic Data Using Deep Neural NetworksSanthosh Sankara, Nadeson SugithaCrime prediction is the attempt to identify and mitigate future criminal activity. Crime is typically "unpredictable"; it cannot be predicted in advance. Addressing the roots of crime has long been a priority for researchers. Extracting causality from data is difficult if the relevant data aspects are not selected. In this research activity, an innovative classification framework is defined which is … …Journal of Computer Science, Vol. 20, Issue 10 · 17 Aug 2024 · 5,089 accessesView PDFCite