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192 results for “Decision support”

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Research ArticleOpen accessIn the abstractIntelligent Digital Signal Modulation Recognition using Machine LearningMudhafar Haji Mala Abd, Sadegh AminifarInrecent years, modulation type recognition has received a lot of attentionacross the board. There are several methods to detect modulation types, butthere are only a few effective methods to handle signals with a higher level ofnoise. This study introduces an approach to verify the ability of differentmachine learning algorithms to automatically manage noise in detecting digitalmodulations. This research examines two … …Journal of Computer Science, Vol. 18, Issue 10 · 26 Sep 2022 · 6,098 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 · 6,531 accessesView PDFCite
Research ArticleOpen accessIn the abstractProcess Approach-Based Simulation Project Life Cycle: PAB-SPLCKhadija Ouazzani-Touhami, Kawtar Tikito, Nissrine SouissiSimulation is one of the most effective decision support tools available to designers and managers of complex systems. In particular, discrete-event simulation is widely used in a wide variety of fields, such as industry and production, finance and economics, or even health and services. In addition, the conduct of a simulation project is of extreme importance, in order to carry … …Journal of Computer Science, Vol. 19, Issue 8 · 15 Jul 2023 · 5,401 accessesView PDFCite
Research ArticleOpen accessIn the abstractBig Data in Educational Institutions using RapidMiner to Predict Learning EffectivenessEvaristus Didik Madyatmadja, David Jumpa Malem Sembiring, Sinek Mehuli Br Perangin Angin et al.Schools, universities, colleges and other educational institutions store a lot of data related to students and teachers as well as those related to education. You can analyze this data to gain insights that can improve the operational efficiency of your organization. Educational institution's needs based on student behavior, student exam results, each student's growth and changed educational regulations can be … …Journal of Computer Science, Vol. 17, Issue 4 · 29 Apr 2021 · 6,839 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 · 6,619 accessesView PDFCite
Research ArticleOpen accessIn the abstractMeta Analysis of Growth Performance of Broilers in Response to Dietary Cassava Leaf Meal InterventionChristian Anayo Mbajiorgu, Ifeanyi Princewill OgbuewuThe use of Cassava Leaf Meal (CLM) in broiler diets has gained attention due to its high crude protein content (24-35%) and other valuable nutrients. Therefore, the objective of this meta-analysis was to assess the impact of diets with and without CLM on broiler growth performance. Search performed on four bibliographic databases produced 584 articles of which 11 were used … …American Journal of Animal and Veterinary Sciences, Vol. 21, Issue 3 · 30 Sep 2026 · 586 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Active Learning Ensemble Framework for Tropical Crop Yield PredictionAmol Bhilare, Debabrata Swain, Megh Patel et al.Agriculture always has great importance among all different sectors, not only in the world but also in India. It has a significant impact on food security and largely controls the economy. At present, technological advancements have significantly enhanced agricultural productivity, but it can still be further improved by the integration of new cutting-edge techniques like Artificial intelligence. Among the factors … …Journal of Computer Science, Vol. 22, Issue 9 · 11 Sep 2026 · 829 accessesView PDFCite
Research ArticleOpen accessIn the abstractAbstractive Summarization of Long Educational Transcripts in the Era of GenAIDeepa Fernandes, Rupali Sunil WaghThe surge in online video data presents the imperative requirement of summarizing it for information compression, efficient understanding, and to support decision-making. Recent research studies have predominantly utilized structured input data for summarization. This paper explores the current state-of-the-art models in summarizing unstructured, conversational, and long transcript data. We further apply a transfer learning approach using a fine-tuned BART model, … …Journal of Computer Science, Vol. 22, Issue 8 · 7 Sep 2026 · 413 accessesView PDFCite
Research ArticleOpen accessIn the abstractImplementing a Hybrid VMD–BiTCN–BiGRU Architecture With Intelligent Optimization for Agricultural Commodity Price Prognostication in Gujarat MarketsJignesh Hirapara, Ratnesh Kumar Namdeo, Ankit Kumar Dubey et al.In the agricultural sector, the prices of pulses require adequate forecasting to plan farming activities, store and market, and guide policy-making. However, the pulse price series is highly volatile, seasonal, nonstationary, and nonlinear, and thus conventional linear time series models are not necessarily very effective. In the suggested framework, the raw price data series is decomposed using Variational Mode Decomposition … …Journal of Computer Science, Vol. 22, Issue 7 · 1 Aug 2026 · 1,042 accessesView PDFCite
Research ArticleOpen accessIn the abstractCA-LIME: A Collinearity-Aware LIME Framework for Reliable and Interpretable Explanations in Healthcare AIIdris Khan, Sachin BhoiteIn clinical tabular models, correlated biomarkers can make local explanations unstable even when predictive performance appears acceptable. This paper presents CA-LIME, a collinearity-aware extension of LIME built to address that failure mode directly. Five variations of CA-LIME Vanilla reference, VIF, PCA back projection, Ridge, and ElasticNet allow us to investigate how various correlation-control strategies alter explanation behavior. ILPD, Kaggle liver, … …Journal of Computer Science, Vol. 22, Issue 7 · 28 Jul 2026 · 813 accessesView PDFCite