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124 results for “Hybrid Methods”
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Review ArticleOpen accessIn the abstractProspects of Using Wastewater as a Resource-Nutrient Recovery and Energy GenerationMusfique Ahmed, Chowdhury Kamrul Hasan, Hafizur Rahman et al.It is well understood that both untreated and partially treated wastewater comprise substantial amount of resources, which can be recovered and utilized for different purposes. Since Waste Water Treatment Plant (WWTP) is energy intensive and expensive, substantiating the WWTPs with Resource Recover Technologies (RRTs) will not only save a considerable amount of energy but also make the environment cleaner and … …American Journal of Environmental Sciences, Vol. 11, Issue 2 · 25 Jun 2015 · 8,183 accessesView PDFCite
Review ArticleOpen accessIn the abstractMulti-Timescale Microscopic Theory for Radiation Degradation of Electronic and Optoelectronic DevicesDanhong Huang, Fei Gao, D.A. Cardimona et al.A multi-timescale hybrid model is proposed to study microscopically the degraded performance of electronic devices, covering three individual stages of radiation effects studies, including ultra-fast displacement cascade, intermediate defect stabilization and cluster formation, as well as slow defect reaction and migration. Realistic interatomic potentials are employed in molecular-dynamics calculations for the first two stages up to 100 ns as well … …Space Science International, Vol. 3, Issue 1 · 15 Jun 2015 · 10,235 accessesView PDFCite
Research ArticleOpen accessIn the abstractDocument Clustering Based on Firefly AlgorithmAthraa Jasim Mohammed, Yuhanis Yusof, Husniza HusniDocument clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters. Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization. This study explores the adaptation of another swarm algorithm which … …Journal of Computer Science, Vol. 11, Issue 3 · 26 Mar 2015 · 7,510 accessesView PDFCite
Research ArticleOpen accessIn the abstractMULTI SCALE TIME SERIES PREDICTION FOR INTRUSION DETECTIONG. Palanivel, K. DuraiswamyWe propose an anomaly-based network intrusion detection system, which analyzes traffic features to detect anomalies. The proposed system can be used both in online as well as off-line mode for detecting deviations from the expected behavior. Although our approach uses network packet or flow data, it is general enough to be adaptable for use with any other network variable, which … …American Journal of Applied Sciences, Vol. 11, Issue 8 · 27 Jun 2014 · 6,776 accessesView PDFCite
Research ArticleOpen accessIn the abstractA NOVEL ROBUST AND EFFICIENT TOOL FOR DETECTING HETEROSCEDASTICITYWei Xiong, Maozai TianOne of the greatest values of Quantile Regression (QR) is that it provides a good procedure in the sense that QR could be much more efficient and sometimes arbitrarily more efficient in recovering the mean function than the Least Squares (LS) even when without moment conditions. However, heteroscedasticity definitely causes conditional variances of parametric or nonparametric estimates of mean functions … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 21 Mar 2014 · 6,657 accessesView PDFCite
Research ArticleOpen accessIn the abstractSoft Computing in Optimizing Assembly Lines BalancingMuhammad Zaini Matondang, Muhammad Ikhwan JambakAs part of manufacturing systems, the assembly line has become one of the most valuable researches to accomplish the real world problems related to them. Many efforts have been made to seek the best techniques in optimizing assembly lines. Problem statement: Since it was published by Salveson in 1955, some methods and techniques have been developed based on mathematical modeling. … …Journal of Computer Science, Vol. 6, Issue 2 · 28 Feb 2010 · 7,469 accessesView PDFCite
Research ArticleOpen accessIn the abstractUnbalance Quantitative Structure Activity Relationship Problem Reduction in Drug DesignD. Pugazhenthi, S. P. RajagopalanProblem statement: Activities of drug molecules can be predicted by Quantitative Structure Activity Relationship (QSAR) models, which overcome the disadvantage of high cost and long cycle by employing traditional experimental methods. With the fact that number of drug molecules with positive activity is rather fewer than that with negatives, it is important to predict molecular activities considering such an unbalanced … …Journal of Computer Science, Vol. 5, Issue 10 · 31 Oct 2009 · 6,704 accessesView PDFCite
Research ArticleOpen accessIn the abstractExploring Strategies for Parallel Computing of RS Data Assimilation with SWAP-GAShamim Akhter, Kiyoshi Honda, Yann Chemin, Putchong UthayopasAn agro-hydrological simulation model is useful for agriculture monitoring. One issue in running such model is parameter identification, especially when the target area is large such as provincial or country level. Remote Sensing (RS) provides us with useful information over large area. RS cannot observe input parameters of agro-hydrological models directly. However, a method to estimate input parameters of such … …Journal of Computer Science, Vol. 3, Issue 1 · 31 Jan 2007 · 7,209 accessesView PDFCite
Review ArticleOpen accessAll words, across the recordUnleashing the Power of Image Denoising: A Comprehensive Review of Classical to Deep Learning MethodsArchana Saini, Ayush DograImage denoising is a vital step in many image processing and computer vision professions that aims to improve picture quality by decreasing noise while maintaining important image information. In this article, a detailed overview is presented of traditional and deep learning based picture denoising approaches. Classical methods, such as linear filtering, transform domain techniques, and patch-based approaches like Non-Local Means … …Journal of Computer Science, Vol. 21, Issue 8 · 8 Oct 2025 · 3,107 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordEnhancing Kidney Stone Detection Accuracy Using Image Processing and a Hybrid Convolutional Deep Belief NetworkGeetha M. N, Barkathulla A, S. Nandhini Devi et al.Automated CKD is a rapidly expanding non-communicable ailment that significantly contributes to global mortality and morbidity. CKD impacts more than 10% of the worldwide population, leading to millions of deaths annually. This paper proposes an enhanced deep learning model for renal disease detection that integrates convolutional and involution layers to enhance classification accuracy. CKD is a worldwide health issue characterised … …Journal of Computer Science, Vol. 22, Issue 10 · 9 Oct 2026 · 749 accessesView PDFCite