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9781668478844: Controlling Epidemics With Mathematical and Machine Learning Models

Synopsis

Communicable diseases have been an important part of human history. Epidemics afflicted populations, causing many deaths before gradually fading away and emerging again years after. Epidemics of infectious diseases are occurring more often, and spreading faster and further than ever, in many different regions of the world. The scientific community, in addition to its accelerated efforts to develop an effective treatment and vaccination, is also playing an important role in advising policymakers on possible non-pharmacological approaches to limit the catastrophic impact of epidemics using mathematical and machine learning models. Controlling Epidemics With Mathematical and Machine Learning Models provides mathematical and machine learning models for epidemical diseases, with special attention given to the COVID-19 pandemic. It gives mathematical proof of the stability and size of diseases. Covering topics such as compartmental models, reproduction number, and SIR model simulation, this premier reference source is an essential resource for statisticians, government officials, health professionals, epidemiologists, sociologists, students and educators of higher education, librarians, researchers, and academicians.

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À propos des auteurs

Abraham Varghese , M. Sc, MTech, B. ED, Ph.D. is currently serving as a faculty member in the Information Technology Department of the University of Technology and Applied Sciences, Sultanate of Oman, Dr. Abraham Varghese has more than 20 years of teaching experience. His academic qualifications include a Ph.D. in Content-Based Image Retrieval from Anna University, Chennai, an MTech from National Institute of Technology (NITK), Surathkal, and an M. Sc (Mathematics) from Bharadidasan University. Many of his papers are published in international journals of repute, and he is a regular reviewer for numerous international journals. Among the awards he has received are the Active researcher award from the University of Technology and Applied Sciences, Muscat, the Omani association for intellectual property and artificial intelligence award for the covid-19 project, the Distinguished researcher award from the data processing and researcher group, and the Outstanding researcher award from Venus International Research, VIRA 2023. In addition to authoring a book on C programming and data structures, he is also an active researcher in machine learning, deep learning, and Mathematical modeling. He has been working as a principal Investigator of various funded projects approved by the Ministry of Education Innovation and Research (MoHEIR), Sultanate of Oman.

Eduardo M. Lacap , Jr., M. Sc., Ph. D. Dr. Eduardo is a farmer, fisherman, mentor, husband, father, and statistician. He held some leadership roles including interim Head of a University Statistical Center, Regional Coordinator of a Philippine Statistics organization, and Dean of College of Science in a state university. He was a professorial lecturer in a School of Graduate Studies handling methods of research and statistical analysis. Currently, he is connected to University of Technology and Applied Sciences where he mainly served as a lecturer and data analyst. Besides teaching, curriculum development and reviews were his main tasks across the university. In addition, he consistently served as a consultant for policy analysis of the University through statistically driven artifacts of which some had been used as evidence to amend or replace an existing policy. He had prepared numerous data-driven white papers for the University using analytics which directly or indirectly influences policy makers in crafting their decision.

Ibrahim Sajath , M Sc., Ph.D., is a faculty in the Mathematics Section, IT Department, University of Technology and Applied Sciences, Muscat, Sultanate of Oman. Before joining UTAS in 2007, he was an Assistant Professor, Department of Mathematics, BSA Crescent Engineering College, affiliated to Anna University, Chennai, India. Awarded with National Merit Scholarship, he received his B.S and M.S degrees in Mathematics from University of Madras and his Doctoral degree from Anna University, Chennai, India. He has published many research articles on fixed and common fixed points of single valued, multi-valued and hybrid mappings in the field of Fixed Point Theory both in the classical and fuzzy sense. As a coordinator, he organized and conducted a National Level Workshop on Mathematical Tools in Teaching, Education and Research, funded by All India Council of Technical Education (AICTE). His current areas of research interests are Fixed point theory, Graph theory and Mathematical Modeling.

M. Kamal Kumar , M Sc., M. Phil, Ph.D. Dr. M. Kamal Kumar has around 20 years of experience in Academic field, where he has had the roles of Professor, researchers, Mentor, Counsellor, Team Leader, Chief Coordinator, Journal Reviewer, Chief Exam Superintendent, Placement officers, consultant and others. He completed his bachelors from prestigious St. Joseph College, Bangalore, Masters in Bangalore University, M. Phil from Madurai Kamaraj University, and Doctorate from Visvesvaraya Technological University, Belgaum, India. He also has a Diploma in Computer Application and he is a life skill trainer. His interests include Graph theory and Philosophy. His research contributions have found their way to various prestigious journals. He has published 27 research papers. He has also won several awards and appreciations few to mention Best Teacher, Best Paper presentation, Certificate of Excellence in ISO AUDIT, Rai University, Certificate of Excellence NBA and NAAC audit, CMR Institute of Technology, Service award, CMRIT and others. He is also a national subject expert involved in designing question papers for national-level exams. He is also involved in various committees of Curriculum Development, Organizing, Content Development and maintenance of E-Learning resources, Online Assessment, and Grading. He is also done External Thesis Evaluations for reputed universities like Visvesvaraya Technological University, Madras Universities, Anna University, Bharathidasan University, PRIST University, Vels Institute of Science, Technology & Advanced Studies, Bharathiar University and others.

Shajidmon Kolamban , M Sc., M Phil., B Ed., is currently working as a Faculty in Mathematics section, IT Department, University of Technology and Applied Sciences, Muscat, Sultanate of Oman. He has more than 15 years of experience in Teaching and Research (India and Oman). He has published many research articles in reputed journals (including Nature, Elsevier, Springer) in the field of Graph Theory, Numerical Analysis, Differential Equations, Mathematical Modelling, and ICT in Education. He has co-authored a funded project titled “Prediction, Analysis and Smart Mask based Social Distancing System for Corona Virus Disease (COVID-19)” and the project team won the best research award in AI and Intellectual Property competition, by Oman Intellectual Property Association and Innovation Oasis on 31 March 2021.Currently he is guiding two funded projects approved by the Ministry of Higher Education, Research and innovation, Oman (MoHERI/BFP). He was presented with the ‘Model Employee of the year award’ for the academic year 2021-22 instituted by the University of Technology and Applied Sciences, Muscat, Sultanate of Oman.

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9781799883432: Controlling Epidemics With Mathematical and Machine Learning Models

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Kartoniert / Broschiert. Etat : New. KlappentextCommunicable diseases have been an important part of human history. Epidemics afflicted populations, causing many deaths before gradually fading away and emerging again years after. Epidemics of infectious diseases are occurri. N° de réf. du vendeur 711741639

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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Communicable diseases have been an important part of human history. Epidemics afflicted populations, causing many deaths before gradually fading away and emerging again years after. Epidemics of infectious diseases are occurring more often, and spreading faster and further than ever, in many different regions of the world. The scientific community, in addition to its accelerated efforts to develop an effective treatment and vaccination, is also playing an important role in advising policymakers on possible non-pharmacological approaches to limit the catastrophic impact of epidemics using mathematical and machine learning models. Controlling Epidemics With Mathematical and Machine Learning Models provides mathematical and machine learning models for epidemical diseases, with special attention given to the COVID-19 pandemic. It gives mathematical proof of the stability and size of diseases. Covering topics such as compartmental models, reproduction number, and SIR model simulation, this premier reference source is an essential resource for statisticians, government officials, health professionals, epidemiologists, sociologists, students and educators of higher education, librarians, researchers, and academicians. N° de réf. du vendeur 9781668478844

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