Review ArticleOpen accessIn the abstractKinetic Models for Anaerobic Fermentation Processes-A ReviewEmmanuel Amagu EchieguA review of basic kinetic models describing the generation of biomass and utilization of substrates in anaerobic fermentation processes is presented as well as the stoichiometric and empirical models for the prediction of biogas production. The applications of these models to anaerobic reactor systems such as the CSTR, activated sludge, plug flow reactor, etc are also presented. These models are … …American Journal of Biochemistry and Biotechnology, Vol. 11, Issue 3 · 24 Jul 2015 · 8,316 accessesView PDFCite
Research ArticleOpen accessIn the abstractDiagnosis of Cardiovascular Diseases with Bayesian ClassifiersAlaa Elsayad, Mahmoud FakhrCardiovascular disease or atherosclerosis is any disease affecting the cardiovascular system. They include coronary heart disease, raised blood pressure, cerebrovascular disease, peripheral artery disease, rheumatic heart disease, congenital heart disease and heart failure. They are treated by cardiologists, thoracic surgeons, vascular surgeons, neurologists and interventional radiologists. The diagnosis is an important yet complicated task that needs to be done accurately … …Journal of Computer Science, Vol. 11, Issue 2 · 25 Mar 2015 · 7,498 accessesView PDFCite
Research ArticleOpen accessIn the abstractINJECT AN ELASTIC GRID COMPUTING TECHNIQUES TO OPTIMAL RESOURCE MANAGEMENT TECHNIQUE OPERATIONSR. Surendran, B. Parvatha VarthiniEvaluation of sharing on the Internet well- developed from energetic technique of grid computing. Dynamic Grid Computing is Resource sharing in large level high performance computing networks at worldwide. Existing systems have a Limited innovation for resource management process. In proposed work, Grid Computing is an Internet based computing for Optimal Resource Management Technique Operations (ORMTO). ORMTO are Elastic scheduling … …Journal of Computer Science, Vol. 9, Issue 8 · 9 Jul 2013 · 6,736 accessesView PDFCite
Research ArticleOpen accessIn the abstractObservation Modeling for Continuous Predicting Global and Diffuse Solar Radiation on Horizontal SurfaceSomporn Hongkong, Singthong PattanasethanonMathematical modeling for continuous prediction of solar energy is inevitable for energy systems. General, existing models are mostly empirical and data dependent. This article has to present a variable model for predicting global and diffuse solar radiation on the horizontal plane. The model considered in this study has applied Hidden Markov Model (HMM) with two observations. The databases were measured … …American Journal of Environmental Sciences, Vol. 9, Issue 3 · 23 May 2013 · 6,797 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of Neuro-Fuzzy Techniques for Solar RadiationW. A. Rahoma, U. Ali Rahoma, A. H. HassanProblem statement: The prediction is very useful in solar energy applications because it permits to estimate solar data for locations where measurements are not available. The developed artificial intelligence models predict the solar radiation time series more effectively compared to the conventional procedures based on the clearness index. Approach: The forecasting ability of some models could be further enhanced with … …Journal of Computer Science, Vol. 7, Issue 10 · 11 Aug 2011 · 7,077 accessesView PDFCite
Research ArticleOpen accessIn the abstractModelisation of Nitrification under Inhibited Environment by Moving Bed Bio-Film Reactor TechniquePham Thi Hong Duc, Le Van Cat, Jean-Luc VaselProblem statement: Nitrification by Moving Bed Biofilm Reactor (MBBR) involves physical, chemical and biological processes to remove toxic ammonia for aquaculture that are governed by a variety of parameters, like substrate and dissolved oxygen concentrations, organic matters, temperature, pH, alkalinity and turbulence level, which impact negatively or positively on nitrification kinetics. Approach: The situation becomes more serious as the reaction … …American Journal of Environmental Sciences, Vol. 6, Issue 6 · 31 Dec 2010 · 6,946 accessesView PDFCite
Research ArticleOpen accessIn the abstractSwarm 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 accessAll words, across the recordIntelligent Multi Model Ensemble for Engagement PredictionFahmida Begum, K Ulaga PriyaFor intelligent educational systems, the ability to monitor and respond to student engagement in real time is essential for enhancing learning outcomes. However, existing models often lack adaptability and practical deployment potential, as they depend on single data modalities, rigid ensemble mechanisms, and post-session analysis. This study introduces an intelligent multimodal ensemble framework designed to address these challenges by predicting … …Journal of Computer Science, Vol. 22, Issue 4 · 28 Apr 2026 · 1,844 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA Context-Aware Temporal Convolutional Network for Water Replacement Prediction in Catfish Biofloc Ponds With Imbalanced Event HandlingYaddarabullah, Inanpi Hidayati Sumiasih, Mutiara Dewi PuspitawatiWater replacement is a biologically critical yet under-automated decision in biofloc-based aquaculture systems. Mistimed actions can destabilize microbial ecosystems, elevate fish mortality, and compromise sustainability through excessive water usage. Traditional rule-based heuristics often fail to account for the nonlinear and multiscale dynamics of pond environments. To address this, we propose a Context-Aware Temporal Convolutional Network (CA-TCN), a rare-event classification framework … …Journal of Computer Science, Vol. 22, Issue 3 · 5 Mar 2026 · 1,664 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordPost-COVID Impact Analysis and Effective Recommendation Solutions Over Risk Prediction Using Hybrid ModelBoddeti Jaggan Mohan Ravi Kumar, P. V. G. D. Prasad Reddy, G SrinivasThe COVID-19 pandemic (2019-2022) resulted in significant global mortality, largely attributed to the virus's unpredictable pathophysiology, rapid disease progression affecting multiple organ systems, and initial lack of effective treatments. This study systematically examines post-COVID-19 complications across major organ systems, including respiratory dysfunction, cardiovascular complications, renal disorders, musculoskeletal pain, gastrointestinal disturbances, neurological sequelae, alopecia, endocrine and metabolic dysregulation, and mental health … …Journal of Computer Science, Vol. 21, Issue 11 · 23 Dec 2025 · 1,643 accessesView PDFCite