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146 results for “clusters”

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Research ArticleOpen accessIn the abstractEvaluation of Sweet Sorghum Varieties for Bioethanol Production Under Dryland ConditionsIldar Bogapov, Marden Baidalin, Oksana Kibalnik, Saltanat BaidalinaThe objective of this study was to evaluate the productivity potential and theoretical bioethanol yield of 12 sweet sorghum genotypes under dryland conditions of Northern Kazakhstan during the 2024-2025 growing seasons using a quantitative experimental design. Significant varietal differences in agronomic traits were observed depending on meteorological conditions. In 2024, the highest theoretical bioethanol yield was achieved by Sevilya (1417 … …OnLine Journal of Biological Sciences, Vol. 26, Issue 2 · 16 Jul 2026 · 411 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproving Clustering Robustness through Fuzzy Ensemble of K-Means and Mean ShiftLNC. Prakash K., Palamakula Ramesh Babu, Shaik Thaseentaj et al.Ensemble clustering has emerged as a powerful strategy to improve the robustness and accuracy of unsupervised learning, particularly when individual algorithms struggle with noisy, heterogeneous, or high-dimensional data. This study introduces a fuzzy-based ensemble approach that integrates the complementary strengths of K-Means and Mean Shift clustering, followed by fuzzy membership assignment for data points that remain ambiguous. The inclusion of … …Journal of Computer Science, Vol. 22, Issue 5 · 20 May 2026 · 1,257 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Detailed Preserving Medical Image Denoising Using Cluster-Wise PCA Thresholding and Iterative Mean FilteringMohit Sharma, Ayush Dogra, Anita Gupta et al.Image denoising is a vital process in medical imaging that involves removing noise or distortions introduced during image acquisition. Random noise can degrade image quality and reduce contrast, making accurate analysis more challenging. This paper presents a detail-preserving medical image denoising framework based on a hybrid methodology that combines cluster-wise Principal Component Analysis (PCA) thresholding with Iterative Mean Filtering (IMF). … …Journal of Computer Science, Vol. 22, Issue 4 · 18 Apr 2026 · 1,787 accessesView PDFCite
Research ArticleOpen accessIn the abstractPreventing Deforestation in the Indian Landscape Through Neural Network-Based Intelligence Using Sound Event Detection and Advanced Feature Extraction TechniquesSallauddin Mohmmad, Suresh Kumar SanampudiForests play a vital role in maintaining ecological balance, regulating the climate, and conserving biodiversity. However, India’s forest landscape has witnessed significant changes between 1980 and 2024 due to deforestation, afforestation, and evolving conservation strategies. To address the challenges associated with forest monitoring, we proposed a model based on Sound Event Detection using a dataset comprising four classes: chainsaw sounds, … …Journal of Computer Science, Vol. 21, Issue 12 · 20 Jan 2026 · 1,899 accessesView PDFCite
Research ArticleOpen accessIn the abstractExplosion of the Science Modification of Newtonian Dynamics Via Mach’s Inertia Principle and Generalization in Gravitational Quantum Bound Systems and Finite Range of the Gravity-Carriers, Consistent Merely On the Bosons and the FermionsMohsen LutephyNewtonian gravity is modified here via Mach's inertia principle (inertia fully governed by universe) and it is generalized to gravitationally quantum bound systems, resulting scale invariant fully relational dynamics (mere ordering upon actual objects), answering to rotation curves and velocity dispersions of the galaxies and clusters (large scale quantum bound systems), successful in all dimensions and scales from particle to … …Physics International, Vol. 11, Issue 1 · 10 Aug 2020 · 7,782 accessesView PDFCite
Special issueSmart MaterialsAmerican Journal of Engineering and Applied Sciences · 28 Jan 2020
Research ArticleOpen accessIn the abstractAdaptive Data Transformation for Enhanced Clustering Performance in Diagnostic SystemsMohammed Subhi Al-BatahThis paper presents an enhanced approach to the Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) algorithm, aimed at improving clustering accuracy in medical data, specifically for breast cancer diagnosis. The proposed method introduces a modified data transformation technique to optimize the original BIRCH algorithm. This transformation refines the clustering process, resulting in significant improvements in diagnostic accuracy. The modified … …Journal of Computer Science, Vol. 21, Issue 9 · 17 Oct 2025 · 2,287 accessesView PDFCite
Research ArticleOpen accessIn the abstractMultimedia Image Retrieval Using Novel Modelling of Combined Binary Patterns with Reduced DimensionsM. Geetha Yadav, SP. ChokkalingamAdvancements in computer vision have transformed image retrieval. However, many existing systems struggle to bridge the semantic gap between low-level features and high-level user expectations. This study proposed a new approach that combines texture and colour features to enhance retrieval accuracy and user satisfaction. The proposed method employs the HSV colour model to extract colour features, focusing on dominant features … …Journal of Computer Science, Vol. 21, Issue 4 · 14 Apr 2025 · 5,213 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparative Analysis of Smote and CSSF Techniques for Diabetes Classification Using Imbalanced DataBashar Hamad Aubaidan, Rabiah Abdul Kadir, Mohamad Taha IjabDiabetes, a prevalent chronic metabolic disorder, poses a significant burden on healthcare systems worldwide. Accurate and timely diagnosis is crucial for effective management and complication prevention. Machine learning presents a promising solution but often faces challenges due to class imbalance within datasets, particularly the underrepresentation of diabetic cases. To address this issue, we introduce Cluster-based Synthetic Sample Filtering (CSSF), a … …Journal of Computer Science, Vol. 20, Issue 9 · 22 Jul 2024 · 4,998 accessesView PDFCite