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92 articles for “Imbalance”
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Research ArticleOpen accessEvery word in the titleSENSOR NETWORK PERIODICAL DATA ASSEMBLY USING IMBALANCED CLUSTERING ENERGY EFFICIENT MECHANISMK. Munusamy, R. M.S. ParvathiFast technical advances and development in wireless communication resulted in the huge consumption of wireless sensor networks. The nodes in these networks are ready to be sensed, processing the data and transmitting radio units. While several research works have been conducted related to the power-aware and energy-efficiency using Cooperative Networking protocol (CONET) that reforms clusters but the multiple rate remains … …Journal of Computer Science, Vol. 10, Issue 10 · 28 Jun 2014 · 6,648 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Convolutional Neural Network Approach for Skin Lesion Classification Using Imbalanced Dataset with Image AugmentationZhyar Yassin Abdalla, Nor Hazlyna Harun, Mohammed Shihab AhmedA significant threat to people's health all over the world is skin cancer. The purpose of this research is to improve the detection of skin cancer by utilizing a CNN classification model that makes use of preprocessing and augmentation techniques. The HAM10000 dataset is used, and the imbalance it contains is addressed by resizing the images to 120×120 pixels and … …Journal of Computer Science, Vol. 20, Issue 11 · 10 Sep 2024 · 5,427 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEmpirical Analysis of Employees with Tertiary Education Occupational ImbalancesAndrei B. Ankudinov, Oleg V. LebedevHigh percentage of graduates (among the highest in the world) with university degrees combined with unacceptably low level of utilization of acquired qualifications and generally low quality of education in the majority of Russian universities result in huge structural imbalances. The article presents quantitative estimates of disproportions between the educational levels of employees with higher education and their professional occupation … …American Journal of Applied Sciences, Vol. 10, Issue 10 · 10 Oct 2013 · 6,808 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleReduced Levels of Testosterone Induce LDL Oxidation and Atherosclerotic Lesions Involving Inflammatory Imbalance and Reduced Macrophage ApoptosisPlacielle Fiorezi Filete, Flávia de Souza Andrade Moraes, Girlandia Alexandre Brasil et al.Atherosclerosis is among the major cardiovascular diseases that cause death in the world. Men who are deficient in androgen hormones are more susceptible to this disease. The aim of this study was to evaluate the influence of reduced levels of testosterone on the lipid profile, pro and anti-inflammatory cytokines, apoptosis of peritoneal macrophages and the development of atherosclerosis in LDLr-/-mice, … …OnLine Journal of Biological Sciences, Vol. 19, Issue 4 · 6 Dec 2019 · 7,338 accessesView PDFCite
Research ArticleOpen accessIn the keywordsForecasting Corporate Financial Distress Using Explainable Machine Learning: Implications for Risk Management TechnologyKanjana Hinthaw, Warawut NarkbunnumFinancial distress prediction is a critical task in financial risk management, yet it remains challenging due to class imbalance, complex financial structures, and limited model interpretability. This study develops an integrated machine learning framework that combines feature selection, class imbalance handling, threshold optimization, and Explainable Artificial Intelligence (XAI) to improve both predictive performance and decision-making reliability. Using a dataset of … …Journal of Computer Science, Vol. 22, Issue 7 · 22 Jul 2026 · 1,130 accessesView PDFCite
Research ArticleOpen accessIn the keywordsComparative Analysis of Fraud Detection Methods in Banking Using Machine Learning TechniquesYoussef Tounsi, Ennouri TaziFraud detection in banking requires algorithms that balance classification performance, computational efficiency, and regulatory interpretability, criteria that are rarely benchmarked together. We present a comprehensive evaluation of nine machine learning approaches (Logistic Regression, Decision Tree, Random Forest, SVM, SGD, XGBoost, CatBoost, LightGBM, and MLP) across three datasets differing in size, imbalance severity, and feature type (synthetic, real-world PCA-anonymized, and large-scale … …Journal of Computer Science, Vol. 22, Issue 6 · 22 Jun 2026 · 1,341 accessesView PDFCite
Research ArticleOpen accessIn the keywordsUncertainty-Aware Ensemble Models for Improved Defect Detection in Noisy DataMadhavi Perla, Gadi Lava Raju, A Radha Krishna et al.Software defect prediction plays a crucial role in ensuring software quality and reliability, especially as modern systems become more complex and data rich. This study introduces an uncertainty-aware ensemble learning framework aimed at improving defect classification performance in noisy and imbalanced datasets, particularly those from the PROMISE and NASA KC1 repositories. The proposed model integrates multiple classifiers in a multi-learner … …Journal of Computer Science, Vol. 22, Issue 4 · 27 Apr 2026 · 1,542 accessesView PDFCite
Research ArticleOpen accessIn the keywordsRadiation Triggered Phenotypic Changes of Regulatory T CellsLantao Liu, Yan Peng, Deqin Zhang, Dongsheng NiuIonizing radiation disrupts the immune balance easily. Regulatory T (Treg) cells directly affect the immune balance after radiation exposure. Meanwhile, the present study is to investigate the survival ability and phenotypic changes of Treg cells induced by 60Co γ-rays in order to expand the understanding on how Treg cells modulated by radiation. Mice lymphocytes were isolated from thymus and spleen … …American Journal of Biochemistry and Biotechnology, Vol. 18, Issue 1 · 20 Mar 2022 · 5,828 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCost-based Reweighting for Principal Lq Support Vector Machines for Sufficient Dimension ReductionAndreas ArtemiouIn this work we try to address the imbalance of the number of points which naturally occurs when slicing the response in Sufficient Dimension Reduction methods (SDR). Specifically, some recently proposed support vector machine based (SVM-based) methodology suffers a lot more due to the properties of the SVM algorithm. We target a recently proposed algorithm called Principal LqSVM and we … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 5 Sep 2019 · 7,254 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Collaborative Prediction of Presence of Arrhythmia in Human Heart with Electrocardiogram Data using Machine Learning Algorithms with AnalyticsSelvaraj Rajalakshmi, Kuthadi Venu MadhavHuman heart is the major organ of human being which could fail the other systems in the body at the same time. Hence predicting heart disease is one of the challenging researches that requires meticulous analysis of heart rhythms properly. The irregular heart rhythms or beat is referred to as the Arrhythmia where heart rhythms with low or high rates … …Journal of Computer Science, Vol. 15, Issue 2 · 22 Feb 2019 · 7,508 accessesView PDFCite