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96 results for “Clustering process”
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Research ArticleOpen accessIn the abstractEnergy-Efficient Ant Colony-Based k-Hop Clustering and Transmission Range Assignment Protocol for Connectivity Construction in Dense Wireless Sensor NetworksGokou Hervé Fabrice Diédié, Boko Aka, Michel BabriConnectivity construction is the main phase of a communication-oriented topology control process. It consists of improving the current network physical topology while preserving important properties such as connectivity and symmetry. In this paper, we address the problem of combining two of the techniques commonly used for this purpose in networks composed of a large number of energy constrained wireless sensor-nodes … …Journal of Computer Science, Vol. 14, Issue 3 · 19 Mar 2018 · 7,792 accessesView PDFCite
Review ArticleOpen accessIn the abstractStatistical Binarization Techniques for Document Image AnalysisSaad M. Ismail, Siti Norul Huda Sheikh Abdullah, Fariza FauziBinarization is an important process in image enhancement and analysis. Currently, numerous binarization techniques have been reported in the literature. These binarization methods produce binary images from color or gray-level images. This article highlights an extensive review on various binarization approaches which are also referred to as thresholding methods. These methods are grouped into seven categories according to the employed … …Journal of Computer Science, Vol. 14, Issue 1 · 3 Jan 2018 · 8,160 accessesView PDFCite
Research NotesOpen accessIn the abstractReal Time Density-Based Clustering (RTDBC) Algorithm for Big DataDr. B. Ravi PrasadDensity Based Spatial Clustering of Applications with Noise (DBSCAN), a well-known Density-Based Clustering Algorithm is a advanced data clustering method with various applications in numerous fields like Satellites images, X-ray crystallography, Anomaly Detection in Temperature Data. But its run time R(n2) complexity draws a major challenge. In this research paper, we propose a new unique algorithm called Real Time Density … …Journal of Computer Science, Vol. 13, Issue 10 · 15 Aug 2017 · 7,298 accessesView PDFCite
Research ArticleOpen accessIn the abstractMultimodal Face Expression Recognition Using Parametric Exponential Linear Unit-Long Short-Term MemoryKampa Ratna Babu, Akula Suneetha, Kampa Kanthi KumarMultimodal facial expression recognition combines information from multiple modalities of audio and video to achieve the required accuracy and robustness. By integrating different data sources, multimodal systems capture different aspects of human expression. However, accurately recognizing facial expressions across audio and video modalities causes challenges due to variations in expression representation. In this research, Parametric Exponential Linear Unit-Long Short-Term Memory … …Journal of Computer Science, Vol. 20, Issue 10 · 17 Aug 2024 · 4,612 accessesView PDFCite
Research ArticleOpen accessIn the abstractGlobal Supply Chain: Enhance Production Cost Efficiency Through Machine LearningLoubna Moumeni, Mohammed SaberMachine learning has enabled the discovery of various disciplines and patterns in Supply Chain Management (SCM). The entire industrial sector is striving to harness the contextual intelligence provided by machine learning by exploring new areas within the supply chain network. This article delves into Supply Chain Management (SCM) and its broader implications beyond logistics. SCM involves the resources, methods, and … …Journal of Computer Science, Vol. 20, Issue 9 · 14 Jun 2024 · 5,316 accessesView PDFCite
Research ArticleOpen accessIn the abstractSemSimp: A Parametric Method for Evaluating the Semantic Similarity of Digital ResourcesAntonio De Nicola, Anna Formica, Ida Mele, Francesco TaglinoAbioui, H., Idarrou, A., Bouzit, A., & Mammass, D. (2018). Towards a Novel and Generic Approach for OWL Ontology Weighting. Procedia Computer Science, 127, 426–435. https://doi.org/10.1016/j.procs.2018.01.140 Adhikari, A., Dutta, B., Dutta, A., Mondal, D., & Singh, S. (2018). An intrinsic information content-based semantic similarity measure considering the disjoint common subsumers of concepts of an ontology. Journal of the Association for … …Journal of Computer Science, Vol. 20, Issue 8 · 27 May 2024 · 5,773 accessesView PDFCite
Literature ReviewOpen accessIn the abstractAdvances in Document Clustering with Evolutionary-Based AlgorithmsSarmad Makki, Razali Yaakob, Norwati Mustapha, Hamidah IbrahimDocument clustering is the process of organizing a particular electronic corpus of documents into subgroups of similar text features. Formerly, a number of conventional algorithms had been applied to perform document clustering. There are current endeavors to enhance clustering performance by employing evolutionary algorithms. Thus, such endeavors became an emerging topic gaining more attention in recent years. The aim of … …American Journal of Applied Sciences, Vol. 12, Issue 10 · 20 Oct 2015 · 7,186 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntegrating Correlation Clustering and Agglomerative Hierarchical Clustering for Holistic Schema MatchingBasel Alshaikhdeeb, Kamsuriah AhmadHolistic schema matching is the process of carrying off several number of schemas as an input and outputs the correspondences among them. Treating large number of schemas may consume longer time with poor quality. Therefore, several clustering approaches have been proposed in order to reduce the search space by partitioning the data into smaller portions which can facilitate the matching … …Journal of Computer Science, Vol. 11, Issue 3 · 3 Apr 2015 · 6,389 accessesView PDFCite
EditorialOpen accessIn the abstractData Mining in Time Series: Current Study and Future TrendTan Yan, Liudmila Ulanova, Ye Ouyang, Fengyuan XuTime series represent sequences of data points where usually their order is defined by the time when they were recorded. Thus, virtually any sequential recordings can be stored as time series: Stock prices, weather conditions, physical system parameters change, product quality monitoring, etc. This leads to ubiquity of time series in all scientific and practical fields (Esling and Agon, 2012); … …Journal of Computer Science, Vol. 10, Issue 12 · 26 Jan 2015 · 8,756 accessesView PDFCite
Research ArticleOpen accessIn the abstractA HYBRID FIREFLY ALGORITHM WITH FUZZY-C MEAN ALGORITHM FOR MRI BRAIN SEGMENTATIONMutasem K. AlsmadiImage processing is one of the essential tasks to extract suspicious region and robust features from the Magnetic Resonance Imaging (MRI). A numbers of the segmentation algorithms were developed in order to satisfy and increasing the accuracy of brain tumor detection. In the medical image processing brain image segmentation is considered as a complex and challenging part. Fuzzy c-means is … …American Journal of Applied Sciences, Vol. 11, Issue 9 · 10 Sep 2014 · 8,074 accessesView PDFCite