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Fault-Tolerant and Data-Intensive Resource Scheduling and Management for Scientific Applications in Cloud Computing

Zulfiqar Ahmad, Ali Imran Jehangiri, Mohammed Alaa Ala'anzy, Mohamed Othman, Arif Iqbal Umar
2021 Sensors  
Therefore, this research work presents a cluster-based, fault-tolerant and data-intensive (CFD) scheduling for scientific applications in cloud environments.  ...  Cloud computing is a fully fledged, matured and flexible computing paradigm that provides services to scientific and business applications in a subscription-based environment.  ...  Acknowledgments: The authors gratefully acknowledge the Ministry of Higher Education Malaysia for in partial financial support through the Fundamental Research Grant Scheme with reference code FRGS/1/2018  ... 
doi:10.3390/s21217238 pmid:34770545 pmcid:PMC8587021 fatcat:u53ocebfavfgnog7rwdkwdwz4e

Review of Metaheuristics Inspired from the Animal Kingdom

Elena Niculina Dragoi, Vlad Dafinescu
2021 Mathematics  
The search for powerful optimizers has led to the development of a multitude of metaheuristic algorithms inspired from all areas.  ...  In addition, an analysis of the mechanisms used to ensure diversity was performed. The results obtained showed that the most frequently used mechanisms belong to the niching category.  ...  Acknowledgments: The authors want to thank Florin Leon for his valuable insights and suggestions regarding the use of animal inspired metaheuristics.  ... 
doi:10.3390/math9182335 fatcat:lu4w7xjignedjazicqibu6ks2q

Efficient Time-Series Forecasting Using Neural Network and Opposition-Based Coral Reefs Optimization

Thieu Nguyen, Tu Nguyen, Binh Minh Nguyen, Giang Nguyen
2019 International Journal of Computational Intelligence Systems  
The algorithm is built as an improvement for coral reefs optimization (CRO) using opposition-based learning (OBL).  ...  In addition, with used real datasets, we intend to concentrate on applying OCRO-MLNN to distributed systems in order to enable the proactive resource allocation capability for e-infrastructures (e.g. clouds  ...  The list contains Mothflame optimization algorithm [50] , Whale optimization algorithm [51] , Salp Swarm Algorithm [52] , Grasshopper optimization algorithm [53] , Harris Hawks optimization [54] ,  ... 
doi:10.2991/ijcis.d.190930.003 fatcat:2eugogcxyvcyhou7vhpmfh2cpq

A comprehensive survey of sine cosine algorithm: variants and applications

Asma Benmessaoud Gabis, Yassine Meraihi, Seyedali Mirjalili, Amar Ramdane-Cherif
2021 Artificial Intelligence Review  
This paper presents a brief overview of the basic SCA and its variants divided into modified, multi-objective, and hybridized versions.  ...  Since its introduction by Mirjalili in 2016, SCA has attracted great attention from researchers and has been widely used to solve different optimization problems in several fields.  ...  Hybridization with Harris Hawks optimization algorithm In the work of Fu et al. (2020) , MSCAHHO was proposed using SCA, HHO, and mutation operator to tune the parameters of Support Vector Machine (SVM  ... 
doi:10.1007/s10462-021-10026-y pmid:34092884 pmcid:PMC8171367 fatcat:moutlepxhvgvbk2arulqyaut6q

Early Recognition and Discrimination of COVID-19 Severity using Slime Mould Support Vector Machine for Medical Decision-making

Beibei Shi, Hua Ye, Jian Zheng, Yefei Zhu, Ali Asghar Heidari, Long Zheng, Huiling Chen, Liangxing Wang, Peiliang Wu
2021 IEEE Access  
for SVM.  ...  For more information, see https://creativecommons.org/licenses/by/4.0/ VOLUME 9, 2021  ...  optimization algorithm [101] , harris hawks optimization [102] , hunger games search [103] , whale optimization algorithm (WOA) [104] , [105] , fruit fly optimization algorithm [106] , [107] and  ... 
doi:10.1109/access.2021.3108447 fatcat:dr5r7rr4rzcvxj3wvdubefhrbm

Heuristic and Metaheuristic Methods for the Unrelated Machines Scheduling Problem: A Survey [article]

Marko Đurasević, Domagoj Jakobović
2021 arXiv   pre-print
computing.  ...  However, no study has until now tried to systematise the research in which heuristic methods are applied for the UPMSP.  ...  Both methods use a simple DR for constructing the initial solution. A problem from the cloud computing domain is examined in [255] .  ... 
arXiv:2107.13106v1 fatcat:e3eijbxklbeulefyv3t5kcu2im

2021 Index IEEE Transactions on Cybernetics Vol. 51

2021 IEEE Transactions on Cybernetics  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  -that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021.  ...  ., +, TCYB March 2021 1272-1285 An Elite Gene Guided Reproduction Operator for Many-Objective Optimization.  ... 
doi:10.1109/tcyb.2021.3139447 fatcat:myjx3olwvfcfpgnwvbuujwzyoi

The Intertwine of Brain and Body: A Quantitative Analysis on How Big Data Influences the System of Sports

Devansh Patel, Dhwanil Shah, Manan Shah
2020 Annals of Data Science  
Big data, artificial intelligence, data analytics, machine learning, neural networks are promising prospects in the industry right now and subsequently the posterity for the current technological landscape  ...  Hence, this paper offers a deeper look into how the entire sports industry has been affected in a multi-faceted way.  ...  Acknowledgements The authors are grateful to Department of Chemical Engineering, School of Technology, Pandit Deendayal Petroleum University and Indus University for permission to publish this research  ... 
doi:10.1007/s40745-019-00239-y fatcat:babkr7bwnjbmnj6dyi55wyy7aa

A novel hybrid hunger games search algorithm with differential evolution for improving the behaviors of non-cooperative animals

Shaolang Li, Xiaobo Li, Hui Chen, Yuxin Zhao, Junwei Dong
2021 IEEE Access  
However, HGS tends to stagnate in local optimal for some complex optimization problems and remains premature convergence.  ...  The experimental results demonstrate that DECEHGS has competitive performance in global optimization tasks and engineering problems compared with state-ofthe-art algorithms.  ...  Huiling Chen for his helpful suggestions and anonymous reviewers' valuable comments.  ... 
doi:10.1109/access.2021.3132617 fatcat:perixca3pbbfniapx5zsabifmq

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
Highlights include a comprehensive review of deep learning in electron microscopy; large new electron microscopy datasets for machine learning, dataset search engines based on variational autoencoders,  ...  Philosophy in Physics is typeset for physical printing and binding.  ...  In addition, part of the text in section 1.2 is adapted from our earlier work with permission 201 under a Creative Commons Attribution 4.0 73 license.  ... 
doi:10.5281/zenodo.4598227 fatcat:hm2ksetmsvf37adjjefmmbakvq

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
Highlights include a comprehensive review of deep learning in electron microscopy; large new electron microscopy datasets for machine learning, dataset search engines based on variational autoencoders,  ...  Philosophy in Physics is typeset for physical printing and binding.  ...  In addition, part of the text in section 1.2 is adapted from our earlier work with permission 201 under a Creative Commons Attribution 4.0 73 license.  ... 
doi:10.5281/zenodo.4591029 fatcat:zn2hvfyupvdwlnvsscdgswayci

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
Highlights include a comprehensive review of deep learning in electron microscopy; large new electron microscopy datasets for machine learning, dataset search engines based on variational autoencoders,  ...  in Physics will be typeset for physical printing and binding.  ...  In addition, part of the text in section 1.2 is adapted from our earlier work with permission 201 under a Creative Commons Attribution 4.0 73 license.  ... 
doi:10.5281/zenodo.4399748 fatcat:63ggmnviczg6vlnqugbnrexsgy

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
Highlights include a comprehensive review of deep learning in electron microscopy; large new electron microscopy datasets for machine learning, dataset search engines based on variational autoencoders,  ...  in Physics will be typeset for physical printing and binding.  ...  In addition, part of the text in section 1.2 is adapted from our earlier work with permission 201 under a Creative Commons Attribution 4.0 73 license.  ... 
doi:10.5281/zenodo.4413249 fatcat:35qbhenysfhvza2roihx52afuy

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
Highlights include a comprehensive review of deep learning in electron microscopy; large new electron microscopy datasets for machine learning, dataset search engines based on variational autoencoders,  ...  in Physics will be typeset for physical printing and binding.  ...  In addition, part of the text in section 1.2 is adapted from our earlier work with permission 201 under a Creative Commons Attribution 4.0 73 license.  ... 
doi:10.5281/zenodo.4429792 fatcat:qs6yuapx4vdbdmwna7ix7nnwty

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
Highlights include a comprehensive review of deep learning in electron microscopy; large new electron microscopy datasets for machine learning, dataset search engines based on variational autoencoders,  ...  in Physics will be typeset for physical printing and binding.  ...  In addition, part of the text in section 1.2 is adapted from our earlier work with permission 201 under a Creative Commons Attribution 4.0 73 license.  ... 
doi:10.5281/zenodo.4415407 fatcat:6dejwzzpmfegnfuktrld6zgpiq
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