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25 results for “negative selection”
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Research ArticleOpen accessPhrase in the titleSwarm Negative Selection Algorithm for Electroencephalogram Signals ClassificationNasser Omer Sahel Ba-Karait, Siti Mariyam Shamsuddin, Rubita SudirmanProblem statement: The process of epilepsy diagnosis from EEG signals by a human scorer is a very time consuming and costly task considering the large number of epileptic patients admitted to the hospitals and the large amount of data needs to be scored. Therefore, there is a strong need to automate this process. Such automated systems must rely on robust … …Journal of Computer Science, Vol. 5, Issue 12 · 31 Dec 2009 · 7,205 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleStochastic Optimization for Portfolio Selection Problem with Mean Absolute Negative Deviation MeasureAnton Abdulbasah Kamil, Adli Mustafa, Khlipah IbrahimProblem statement: The most important character within optimization problem is the uncertainty of the future returns. Approach: To handle such problems, we utilized probabilistic methods alongside with optimization techniques. We developed single stage and two stage stochastic programming with recourse. The models were developed for risk adverse investors and the objective of the stochastic programming models is to minimize the … …Journal of Mathematics and Statistics, Vol. 5, Issue 4 · 31 Dec 2009 · 6,947 accessesView PDFCite
Research ArticleOpen accessIn the abstractAttribute Reduction in Bipolar Intuitionistic Fuzzy Relation SystemWeiyuan Wang, Qian WangBipolar intuitionistic fuzzy relation system (BIFRS) effectively characterize the bipolarity in real-world data by introducing positive and negative membership and non-membership degrees. To address redundancy caused by high-dimensional attributes, this paper proposes an attribute reduction method based on bipolar intuitionistic discernibility matrices. By constructing positive discernibility matrix M+∗ matrix M−∗ and negative discernibility , we systematically identify the minimal attribute … …Journal of Mathematics and Statistics, Vol. 22, Issue 1 · 16 Jul 2026 · 1,063 accessesView PDFCite
Research ArticleOpen accessIn the abstractSentiment Analysis Using Light Weight - Gradient Boosting Machine based Feature SelectionBikku Ramavath, Srikanth Kadainti, Nemani SubashSentiment analysis is a significant task in Natural Language Processing (NLP) that differentiates the emotions and opinions expressed in text or reviews. The sentiment analysis is challenging due to the complex language patterns and inappropriate or redundant features used for classification. In this research, the Light Weight - Gradient Boosting Machine (LWGBM) based feature selection is proposed to choose relevant … …Journal of Computer Science, Vol. 21, Issue 5 · 26 May 2025 · 4,695 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized Feature Selection Approach for Semi-Supervised Sentiment Analysis of E-Commerce FeedbackAlok Kumar Jena, Kakita Murali Gopal et al.In this globalized world, people prefer to buy products online without any hesitation. Usually, to acquire the quality of the product or brand, they examine the product’s reviews, which is a tedious job to do manually. The wide use of social media also encourages the users, to keep their views on the product in a global platform. By using machine … …Journal of Computer Science, Vol. 21, Issue 2 · 16 Jan 2025 · 6,179 accessesView PDFCite
Research ArticleOpen accessIn the abstractStable Isotope Diet Reconstruction of Feral Horses on the Sheldon National Wildlife Refuge, Nevada, USAMegan K. Nordquist, Todd F. Robinson, Gail H. Collins et al.Feral horse management has become a subject of significant controversy in the United States, resulting in part from opposing views of best management practices and limited empirical data. Feral horse densities increase in response to high reproductive rates and limited horse removal. with this increase, land managers are challenged with accurately quantifying horse diet selection and subsequent impacts on western … …American Journal of Animal and Veterinary Sciences, Vol. 19, Issue 2 · 4 Mar 2024 · 5,390 accessesView PDFCite
Research ArticleOpen accessIn the abstractClimate-Driven Productivity Responses and Implications for Genetic Adaptation and Breeding of Boreal Trees in KazakhstanZhadyra Baigazakova, Kuralay Mazarzhanova, Asset Satayev et al.Kazakhstan’s boreal and forest-steppe forests form the southern ecotonal edge of the West Siberian taiga, where relatively small changes in heat and moisture can trigger disproportionate impacts on tree growth, mortality, and regeneration. Although forests cover only ~4% of Kazakhstan, they provide critical ecosystem services: stabilizing hydrological regimes, buffering microclimates, protecting agricultural lands from wind and water erosion, and supporting … …OnLine Journal of Biological Sciences, Vol. 26, Issue 3 · 10 Aug 2026 · 709 accessesView PDFCite
Research ArticleOpen accessIn the abstractCorrelates of Resistance to Gastro-Intestinal Parasites Infection in South African Communal Indigenous Goat PopulationsTakalani Judas Mpofu, Khathutshelo Agree Nephawe, Bohani MtileniThe study was conducted to investigate the correlates of resistance to Gastro-Intestinal Parasites (GIPs) infection in South African communal indigenous goat. A total of 288 goats were randomly sampled for fecal and blood collection. Infection intensity was estimated through determining the fecal egg per gram using a modified McMaster technique. Packed Cell Volume (PCV), Hemoglobin (Hgb) and Mean Corpuscular Hemoglobin … …American Journal of Animal and Veterinary Sciences, Vol. 15, Issue 2 · 1 Jul 2020 · 7,200 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Analysis of Heart Disease for Diabetic Patients Using Recursive Feature Elimination with Random ForestBindushree Doddasiddavanahalli Channabasavaraju, Udayarani VinayakamurthyData Mining Techniques are used in many areas like banking, healthcare, education because of extracting relevant information from the database. Many algorithms in data mining are used to predict the disease to reduce the patient treatment cost as well as increase the diagnosis accuracy. In this research work, the risk level of diabetic heart disease patient can be predicted using … …Journal of Computer Science, Vol. 16, Issue 1 · 27 Jan 2020 · 7,931 accessesView PDFCite