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429 results for “proposed algorithms”
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Research ArticleOpen accessIn the abstractAlgorithmization of Electrostatic Model for Solving the Direct Problem of ElectrographyTagirbek Gaidarbekovich Aslanov, Naur Zamirovich Ivanov, Shamil Shamil`evich Anudinov, Tatiana Vladimirovna KarlovaAn analysis of the creation and implementation of algorithms to control cardiological processes occurring in the cardiovascular system using software and hardware diagnostic systems is a required activity. This study considers ways to improve the methods of medical data processing using electronic diagnostic systems, relying on existing methods of mathematical simulation of human body states. This study describes the development … …Journal of Computer Science, Vol. 21, Issue 4 · 7 Mar 2025 · 5,330 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Empirical Criterion for Transitive ClosureMarius OrlowskiThe paper establishes a simple and computationally economical criterion for determining whether a given adjacency matrix represents a transitive closure or not. The criterion is based on a new iterative method for finding the transitive closure adjacency matrix. This method is equivalent to but computationally more efficient than the traditional Boolean sum of successive powers of the original adjacency matrix … …Journal of Computer Science, Vol. 18, Issue 12 · 23 Dec 2022 · 5,418 accessesView PDFCite
Research ArticleOpen accessIn the abstractBreast Cancer Grading using Machine Learning Approach AlgorithmsHiba Nabeel Zalloum, Saada Al Zeer, Amir Manassra et al.Recently, Breast Cancer (BC) becomes a more common cancer disease in women and it considers the most important sign which leads to death among women. Therefore, it requires efficient methods for detecting it to reduce the risk of death. A positive prognosis and greater chances of survival are improved if the BC is detected early. Currently, machine learning plays an … …Journal of Computer Science, Vol. 18, Issue 12 · 22 Dec 2022 · 6,610 accessesView PDFCite
Research ArticleOpen accessIn the abstractBayesian Analysis of Longitudinal Ordinal Data Using Non-Identifiable Multivariate Probit ModelsXiao ZhangMultivariate probit models have been explored foranalyzing longitudinal ordinal data. However, the inherent identification issuein multivariate probit models requires the covariance matrix of the underlyinglatent multivariate normal variables to be a correlation matrix and thushinders the development of efficient Bayesian sampling methods. It is knownthat non-identifiable models may produce Markov Chain Monte Carlo (MCMC)samplers with better convergence and mixing than … …Journal of Mathematics and Statistics, Vol. 18, Issue 1 · 14 Nov 2022 · 6,044 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intelligent Approach to Develop, Assess and Optimize Energy Consumption Models for Air-Cooled Chillers using Machine Learning AlgorithmsMostafa Tahmasebi, Nabil NassifThe building sector accounts for more than 70% of the total electricity use. Chillers consume more than 50% of electrical energy during seasonal periods of building use. With the growth of the building sector and climate change, it's essential to develop energy-efficient HVAC systems that optimize the ever-increasing energy demand. This study aims to develop an energy consumption prediction model … …American Journal of Engineering and Applied Sciences, Vol. 15, Issue 3 · 8 Nov 2022 · 5,516 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Recommendation-Based Contextual Model for Talent AcquisitionChannabasamma A., Yeresime SureshIt is important to assist the job seekers in selecting the perfect jobs, which suit candidates' current skills and career objectives. Given the job description and resumes in the unstructured form, choosing the best job manually is a tedious task, so there is a need for an automated system to deal with raw data. The extraction of structured information from … …Journal of Computer Science, Vol. 18, Issue 7 · 20 Jul 2022 · 6,122 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassify Breast Cancer Patients using Hybrid Data-Mining TechniquesFaris E. Mohammed, Nadia Smaoui Zghal, Dalinda Ben Aissa, Mostafa Mahmoud El-GayarAccording to the World Health Organization (WHO), breast cancer is a disease that leads to death, especially for women who have neglected or ignored the risk factors. Doctors can classify patients according to clinical information, famous disease symptoms, or similar cases. But, some cases are difficult to detect early or diagnose accurately. Therefore, the most important challenge faced by researchers … …Journal of Computer Science, Vol. 18, Issue 4 · 12 May 2022 · 6,526 accessesView PDFCite
Research ArticleOpen accessIn the abstractBio-inspired Search Approach Cross-Domain Location Mapping for Smart Mobile Service SystemIsrael Edem Agbehadji, Abdultaofeek Abayomi, Murimo B. Mutanga et al.The health care service sector is very critical in every country. Although governments have made significant efforts to improve health infrastructure and train more qualified health professionals, the majority of them cannot find jobs within public health facilities. Furthermore, patients queue at health care facilities for hours daily for basic health care services while job creation and reducing these long … …Journal of Computer Science, Vol. 18, Issue 4 · 26 Apr 2022 · 6,158 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Integrated Machine Learning Model for Heart Disease Classification and CategorizationSrikanth Meda, Raveendrababu BhogapathiProgressions in the coordination among the machine learning algorithms, helped to achieve high accuracy and reliability in decision-making systems. Due to the impact and importance of heart diseases in real life, designing the efficient heart disease prediction model become a pivotal aspect today. Former research scholars applied the popular supervised machine learning models like Decision Trees, Naïve Bayes, ANN's, and … …Journal of Computer Science, Vol. 18, Issue 4 · 19 Apr 2022 · 6,535 accessesView PDFCite
Research ArticleOpen accessIn the abstractEthioLSocMDMTLM: Exploring Application of Topic Modeling for Building Ethiopian Language Social Media Data-Based Multilingual Transformer Language Models for Multilingual Hateful Content DetectionNaol Bakala Defersha, Kula Kekeba Tune, Solomon Teferra AbateThis study proposes topic modeling techniques to develop Ethiopian Language Social Media Data Based Multilingual Transformer Language Models for multilingual hateful content detection. We modified various multilingual pretrained models, investigated the challenges of using pre-trained transformer language models, and built multilingual hateful content detection models. Topic words with rows of 1561, 70, and 1044 extracted from Afaan Oromo, Tigrigna, and … …Journal of Computer Science, Vol. 21, Issue 2 · 31 Dec 2024 · 5,204 accessesView PDFCite