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10 articles for “decomposition algorithms”
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Research ArticleOpen accessIn the keywordsComparison of Exact Algorithms for Rectilinear Distance Single-Source Capacitated Multi-Facility Weber ProblemsChansiri Singhtaun, Peerayuth CharnsethikulProblem statement: The objective of this study is to develop efficient exact algorithms for a single source capacitated multi-facility location problem with rectilinear distance. This problem is concerned with locating m capacitated facilities in the two dimensional plane to satisfy the demand of n customers with minimum total transportation cost which is proportional to the rectilinear distance between the facilities … …Journal of Computer Science, Vol. 6, Issue 2 · 28 Feb 2010 · 7,524 accessesView PDFCite
Research ArticleOpen accessIn the abstractReal-Time Monitoring and Injury Risk Warning Algorithm Based on Data Fusion of Motor Muscle ContractionGuomin Wang, Jingying HuangThe existing sports injury warning algorithms are difficult to achieve dynamic injury risk modeling based on individual muscle characteristics while ensuring real-time fusion efficiency of multimodal signals. This article proposes a real-time muscle contraction state perception and injury risk warning algorithm based on adaptive weighted feature fusion and lightweight temporal modeling. The system synchronously collected surface electromyography (sEMG), Inertial Measurement … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 3 · 10 Aug 2026 · 1,089 accessesView PDFCite
Research ArticleOpen accessIn the abstractConvSVD++: A Hybrid Deep CF Recommender Model using Convolutional Neural NetworkMohamed Grida, Lamiaa Fayed, Mohamed HassanRecommender systems are powerful systems that give added value to business and corporation. They are relatively recent technology and they will only keep improving in the future. The most widely used algorithms for recommender systems are categorized into the traditional recommender and deep-based recommender system. The traditional recommendation algorithm suffers from sparse data that significantly degrades recommendation accuracy. The hybrid … …Journal of Computer Science, Vol. 16, Issue 12 · 13 Jan 2021 · 6,731 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of Morphological Component Analysis to Optical Image FusionGeorges Laussane Loum, Atiampo Kodjo Armand, Pandry Koffi Ghislain, Souleymane OumtanagaThe image fusion technique is widely used in remote sensing. Its purpose is to provide comprehensive information without arte facts by combining the partial information from different source images. In this study, we propose a new model of images fusion with very high spatial resolution. We use the separation capacities of the Morphological Component Analysis (MCA) to extract the smooth … …American Journal of Applied Sciences, Vol. 14, Issue 8 · 11 Aug 2017 · 7,729 accessesView PDFCite
Research ArticleOpen accessIn the abstractError Free Iterative Morphological Decomposition Algorithm for Shape RepresentationV. Vijaya Kumar, A. Srikrishna, G. Hemantha KumarProblem statement: A generalized skeleton transform allows a shape to be represented as a collection of modestly overlapped octagonal shape parts. One problem with several generalized Morphological skeleton transforms is that they generate noise after decomposition. The noise rate may not be effective for ordinary images; however this effect will be more when applied on printed or handwritten characters. Approach: … …Journal of Computer Science, Vol. 5, Issue 1 · 31 Jan 2009 · 7,517 accessesView PDFCite
Research ArticleOpen accessIn the abstractOn Embeddings of Hamiltonian Paths and Cycles in Extended Fibonacci CubesIoana Zelina, Grigor Moldovan, Ioana TascuThe interconnection network is an essential component of a distributed system or of a supercomputer based on large-sale parallel processing. Because in distributed systems the communication between processors is based on message exchange, the network topology is of a great importance. The interconnection network can be seen as a graph and the properties of a network can be studied using … …American Journal of Applied Sciences, Vol. 5, Issue 11 · 30 Nov 2008 · 7,281 accessesView PDFCite
Research ArticleOpen accessIn the abstractEdge Defection Prediction by Using Wavelet CompressionYas A.K. AlsultannyDigital image have been expanding in usage. The importance of image compression algorithms have been increased, to produce smaller file size with a lower computational requirement. The wavelet transform offers a natural decomposition of images at multiple resolutions, since the wavelet transform can decompose images into various multiresolution subbands, where the correlation exists. A novel technique for image compression by … …Journal of Computer Science, Vol. 1, Issue 3 · 30 Sep 2005 · 7,287 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA Multi-Modal Image Fusion Approach for Visual and Infrared Images via Shearlet-Based DecompositionApoorav Sharma, Shagun Sharma, Kalpna Guleria et al.The integration of optical lens technologies with night vision has become necessary due to the increasing demand to enhance public safety and surveillance, particularly in vulnerable areas, public transportation, and airports. Due to vision clarity issues or the lack of thermal information, conventional single-modality systems often fail to detect concealed dangers. This research presents a multimodal image fusion architecture that … …Journal of Computer Science, Vol. 22, Issue 1 · 2 Feb 2026 · 1,899 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAdaptive Classification Method Based on Data DecompositionAyman E. Khedr, Amira M. Idrees, Ahmed I. El SeddawyKnowledge discovery is one of the vital fields which strongly supports decision making by applying different techniques based on the targeted field and the required information. Focusing on clustering and classification techniques, this paper presents an approach for adapting one of the classification algorithms for supporting decision making procedure in radiology data analysis field. The proposed adaptation is based on … …Journal of Computer Science, Vol. 12, Issue 1 · 20 Feb 2016 · 7,423 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordCancer Classification using Support Vector Machines and Relevance Vector Machine based on Analysis of Variance FeaturesA. Bharathi, A.M. NatarajanProblem statement: The objective of this study is, to find the smallest set of genes that can ensure highly accurate classification of cancer from micro array data by using supervised machine learning algorithms. The significance of finding the minimum subset is three fold: The computational burden and noise arising from irrelevant genes are much reduced; the cost for cancer testing … …Journal of Computer Science, Vol. 7, Issue 9 · 25 Jul 2011 · 7,593 accessesView PDFCite