Computer Intelligence Against Pandemics
Description
This book introduces the most recent research and innovative developments regarding the new strains of COVID-19. While medical and natural sciences have been working instantly on deriving solutions and trying to protect humankind against such virus types, there is also a great focus on technological developments for improving the mechanism - momentum of science for effective and efficient solutions. At this point, computational intelligence is the most powerful tools for researchers to fight against COVID-19. Thanks to instant data-analyze and predictive techniques by computational intelligence, it is possible to get positive results and introduce revolutionary solutions against related medical diseases. By running capabilities - resources for rising the computational intelligence, technological fields like Artificial Intelligence (with Machine / Deep Learning), Data Mining, Applied Mathematics are essential components for processing data, recognizing patterns, modelling new techniques and improving the advantages of the computational intelligence more. Nowadays, there is a great interest in the application potentials of computational intelligence to be an effective approach for taking humankind more step away, after COVID-19 and before pandemics similar to the COVID-19 many appear.
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Dr. Siddhartha Bhattacharyya [FRSA (UK), FIET (UK), FIE (I), FIETE, LFOSI, SMIEEE, SMACM, SMAAIA, SMIETI] did his Bachelors in Physics, Bachelors in Optics and Optoelectronics, and Masters in Optics and Optoelectronics from the University of Calcutta, India in 1995, 1998, and 2000 respectively. He completed his Ph.D. in Computer Science and Engineering from Jadavpur University, India in 2008. He is the recipient of the University Gold Medal from the University of Calcutta for his Masters. He is the recipient of several coveted awards including the Distinguished HoD Award and Distinguished Professor Award conferred by the Computer Society of India, Mumbai Chapter, India in 2017, the Honorary Doctorate Award (D. Litt.) from The University of South America, and the South East Asian Regional Computing Confederation (SEARCC) International Digital Award ICT Educator of the Year in 2017. He has been appointed as the ACM Distinguished Speaker for the tenure of 2018-2020. He has been inducted into the People of ACM hall of fame by ACM, the USA in 2020. He has been appointed as the IEEE Computer Society Distinguished Visitor for the tenure of 2021-2023. He has been elected as a full foreign member of the Russian Academy of Natural Sciences and the Russian Academy of Engineering. He has been elected a full fellow of The Royal Society for Arts, Manufacturers and Commerce (RSA), London, UK.
He is currently serving as the Principal of Rajnagar Mahavidyalaya, Rajnagar, Birbhum. He served as a Professor in the Department of Computer Science and Engineering of Christ University, Bangalore. He served as the Principal of RCC Institute of Information Technology, Kolkata, India during 2017-2019. He has also served as a Senior Research Scientist in the Faculty of Electrical Engineering and Computer Science of VSB Technical University of Ostrava, Czech Republic (2018-2019). Prior to this, he was the Professor of Information Technology at RCC Institute of Information Technology, Kolkata, India. He served as the Head of the Department from March 2014 to December 2016. Prior to this, he was an Associate Professor of Information Technology at RCC Institute of Information Technology, Kolkata, India from 2011-2014. Before that, he served as an Assistant Professor in Computer Science and Information Technology at the University Institute of Technology, The University of Burdwan, India from 2005-2011. He was a Lecturer in Information Technology at Kalyani Government Engineering College, India during 2001-2005. He is a co-author of 6 books and the co-editor of 88 books and has more than 400 research publications in international journals and conference proceedings to his credit. He has got two PCTs and 19 patents to his credit. He has been a member of the organizing and technical program committees of several national and international conferences. He is the founding Chair of ICCICN 2014, ICRCICN (2015, 2016, 2017, 2018), and ISSIP (2017, 2018) (Kolkata, India). He was the General Chair of several international conferences like WCNSSP 2016 (Chiang Mai, Thailand), ICACCP (2017, 2019) (Sikkim, India) and (ICICC 2018 (New Delhi, India), and ICICC 2019 (Ostrava, Czech Republic).
He is the Associate Editor of several reputed journals including Applied Soft Computing, IEEE Access, Evolutionary Intelligence, and IET Quantum Communications. He is the editor of the International Journal of Pattern Recognition Research and the founding Editor in Chief of the International Journal of Hybrid Intelligence, Inderscience. He has guest-edited several issues with several international journals. He is serving as the Series Editor of IGI Global Book Series Advances in Information Quality and Management (AIQM), De Gruyter Book Series Frontiers in Computational Intelligence (FCI), CRC Press Book Series(s) Computational Intelligence and Applications & Quantum Machine Intelligence, Wiley Book Series Intelligent Signal and Data Processing, Elsevier Book Series Hybrid Computational Intelligence for Pattern Analysis and Understanding and Springer Tracts on Human Centered Computing.
His research interests include hybrid intelligence, pattern recognition, multimedia data processing, social networks, and quantum computing.
He is a life fellow of the Optical Society of India (OSI), India, a life fellow of the International Society of Research and Development (ISRD), UK, a fellow of the Institution of Engineering and Technology (IET), UK, a fellow of Institute of Electronics and Telecommunication Engineers (IETE), India and a fellow of Institution of Engineers (IEI), India. He is also a senior member of the Institute of Electrical and Electronics Engineers (IEEE), USA, International Institute of Engineering and Technology (IETI), Hong Kong, and the Association for Computing Machinery (ACM), USA.
He is a life member of the Cryptology Research Society of India (CRSI), Computer Society of India (CSI), Indian Society for Technical Education (ISTE), Indian Unit for Pattern Recognition and Artificial Intelligence (IUPRAI), Center for Education Growth and Research (CEGR), Integrated Chambers of Commerce and Industry (ICCI), and Association of Leaders and Industries (ALI). He is a member of the Institution of Engineering and Technology (IET), UK, International Rough Set Society, International Association for Engineers (IAENG), Hong Kong, Computer Science Teachers Association (CSTA), USA, International Association of Academicians, Scholars, Scientists and Engineers (IAASSE), USA, Institute of Doctors Engineers and Scientists (IDES), India, The International Society of Service Innovation Professionals (ISSIP) and The Society of Digital Information and Wireless Communications (SDIWC). He is also a certified Chartered Engineer of the Institution of Engineers (IEI), India. He is on the Board of Directors of the International Institute of Engineering and Technology (IETI), Hong Kong.
Dr. Jyoti Sekhar Banerjee , B. Tech., M.E, Ph.D. (Engg.), is currently serving as the Head of the Department in the Computer Science and Engineering (AI & ML) Department at the Bengal Institute of Technology, Kolkata, India, and visiting researcher (Post Doc) at Nottingham Trent University, UK. Additionally, He is also the Professor-in-Charge, of R & D and Consultancy Cell of BIT. He has teaching and research experience spanning 17 years and completed one IEI-funded project. He also served many other reputed educational Institutes in India in various positions. He is a member of the IEEE, CSI, ISTE, IEI, ISOC, and IAENG and a fellow of IETE. He is the present honorary Secretary-cum-Treasurer, of the ISTE WB Section. He is the present honorary Secretary of the Computer Society of India, Kolkata Chapter. He is also the Execom Member of the IETE, Kolkata Centre. He has published over fifty papers in various international journals, conference proceedings, and book chapters. He worked as the Associate Editor in the Journal of Mechanics of Continua and Mathematical Sciences; now, he is an International Editorial Board member of JMCMS. He is the lead author of "A Text Book on Mastering Digital Electronics: Principle, Devices, and Applications". He also filed two Indian patents. He has also co-authored another book and is currently processing six edited books in reputed international publishers like Springer, CRC Press, De Gruyter, etc. Presently he is also processing two more textbooks; those are now in press. Currently, he is serving as the General Chair of International conferences like CRC Press published "Global Conference on Artificial Intelligence and Applications" (GCAIA 2021, 2022), Scopus Indexed Springer published 1st International Conference on Human-Centric Smart Computing (ICHCSC 2022). Dr. Banerjee served as a Guest Editor of ICAUC_ES 2021 and ICPAS-2021 issues in the IOP Journal of Earth and Environmental Science , Physics, Scopus indexed proceeding. Guest Editor in JESTEC journal (Scopus, WOS) Journal. His areas of research interests include Computational Intelligence, Cognitive Radio, Sensor Networks, AI/ML, Network Security, Different Computing Techniques, IoT, WBAN (e-healthcare), and Expert Systems.
Dr. Sergey Gorbachev received a Ph.D. degree in National Research Tomsk State University, Russia, in 2003. Íe worked as a Senior Researcher at the International Laboratory Systems of technical vision, National Research Tomsk State University. He is currently a Professor with the School of Artificial Intelligence, Chongqing University of Education, China. He is an Academician of the Russian Academy of Engineering. He has published 8 monographs, 20 book chapters, 18 patents and certificates of computer programs, and more than 160 papers in reviewed journals, and proceedings of conferences. His research interests include neural-fuzzy networks, ensemble models, soft computing, deep learning, quantum-inspired computing, image processing, data mining, and neutrosophic cognitive maps.
Dr. Khan Muhammad received his PhD in Digital Contents from Sejong University, South Korea in February 2019. He was an Assistant Professor in the Department of Software, Sejong University from March 2019 to February 2022. He is currently the director of Visual Analytics for Knowledge Laboratory (VIS2KNOW Lab) and an Assistant Professor (Tenure-Track) in the Department of Applied AI, School of Convergence, College of Computing and Informatics, Sungkyunkwan University, Seoul, South Korea. His research interests include intelligent video surveillance, medical image analysis, information security, video summarization, multimedia data analysis, computer vision, and smart cities. He has registered 10 patents and contributed more than 220 papers in peer-reviewed journals and conference proceedings in his research areas. He is an Associate Editor/Editorial Board Member for more than 15 journals. He was among the most highly cited researchers in 2021 and 2022, according to the Web of Science (Clarivate).
Dr. Mario Köppen received his Masters degree in solid-state physics at Humboldt-University of Berlin in 1991. Afterward, he worked as a scientific assistant at the Central Institute for Cybernetics and Information Processing in Berlin. From 1992 to 2006, he worked with the Fraunhofer Institute for Production Systems and Design Technology and achieved a doctoral degree at the Technical University Berlin. He has published more than 150 peer-reviewed papers in conference proceedings, journals, and books and played an active role in various conferences, incl. the WSC online conference series on Soft Computing in Industrial Applications, and the HIS conference series on Hybrid Intelligent Systems. He is a founding member of the World Federation of Soft Computing and since 2016 Editor-in-Chief of Applied Soft Computing journal. In 2006, he became a JSPS fellow at the Kyushu Institute of Technology in Japan, a Professor at the Network Design and Research Center (NDRC) in 2008, and Professor at the Graduate School of Creative Informatics of the Kyushu Institute of Technology in 2013.
Content
Dedication
The editors would like to dedicate this volume to the departed souls during the COVID-19 pandemic.
Preface
The global pandemic COVID-19 operates its devastation for more than 2 years globally. As of October 5, 2022, more than 624 million people were infected with this disease, and more than 6.5 million lost their lives worldwide. This novel coronavirus is not only a threat to life but also diminishing the economy of the world. Different medical institutes, virology, and pharmacology research centers strive to develop vaccines, antidotes, and antibiotics to eliminate the virus and mitigate its effects on patients. Now, different newly invented vaccines are applied through the scheduled vaccination process, which is continuing globally to eliminate this deadly virus.
However, we have experienced different waves of COVID-19 caused by some new strains of COVID-19. Since December 2020, several coronavirus variants have been identified and are under investigation. Each new variant raises questions: Are people more at risk of getting sick? Will the COVID-19 vaccines still work? Are there new or different things we should do now to stay safe? So, an exciting area of research is that the invented vaccines, whether effective to mitigate the new strains or some modifications, must be ensured. Hence, again, the entire COVID-19 research is under scrutiny in every aspect whenever a new strain is identified.
This volume introduces the most recent research and innovative developments regarding the new strains of COVID-19. While the subfields of medical and natural sciences have been working instantly on deriving solutions and trying to protect humankind against such virus types, there is also a great focus on technological developments for improving the mechanism - momentum of science for effective and efficient solutions. At this point, computer intelligence is the most powerful tool for researchers to fight against COVID-19. Thanks to instant data analysis and predictive techniques by computer intelligence, it is possible to get positive results and introduce revolutionary solutions against related medical diseases. By running capabilities - resources for rising computational intelligence, technological fields like artificial intelligence (AI) (with machine learning (ML)/deep learning (DL)), data mining, and applied mathematics are essential components for processing data, recognizing patterns, modeling new techniques, and improving the advantages of computational intelligence. Nowadays, there is a great interest in the application potentials of computer intelligence to be an effective approach for taking humankind one step away, after COVID-19 and before pandemics similar to COVID-19 may appear. The need to guarantee that newly developed vaccinations are successful in preventing the spread of new strains of viruses, is an intriguing field of study. In this context, the book aims to inform the target audience about the latest findings - results regarding a wide variety of computer intelligence applications for fighting against the new strains of COVID-19.
This volume presents the most recent research and innovative developments regarding the new strains of COVID-19. This volume also focuses on the instant data analysis and predictive techniques by computer intelligence, discussion to get positive results, and the introduction of revolutionary solutions against related medical diseases. The volume comprises 15 contributory chapters to report the latest developments in this direction.
The COVID-19 pandemic is one of the biggest catastrophes of this century. Since January 2020, global COVID-19-induced mortality has attained a new record every day and continues its hegemony even in 2022. Nations are fighting wave after wave of the attacks of this pandemic. The humiliating devastation, non-guaranteed preventive option, and zero-guaranteed treatments have left human beings in extreme despair. An inestimable escalation in victimization has already created a mismatch between the current rate of occupancy in clinical establishments, quarantine centers, and skilled care demand. The emergence of such a pandemic is not new but uncommon. History has evidenced the outbreaks of major diseases like cholera, plague, swineflu, AIDS, SARS-Cov, and Mars-Cov. Each pandemic has challenged the very fundamental existence of mankind. The mutual relationship between the causes and effects of infection is heterogeneous and complex. It has been observed that epidemics, endemics, and pandemics are caused by zoonotic pathogens, that is, bacteria, viruses, or parasites, that are transmitted to humans through the environment or direct contact with food, water, or animals. Regardless of the various speculative theories, investigating the proper mechanism of transmission and developing methods to control and prevent incidents are essential. Vaccination is the only path to salvation from such a pandemic. Rather, a fusion of treatment and prevention has the ability to escape such an attack. During any pandemic, survival instincts have driven the human community into a behavioral shift. But, every pandemic leaves the same question, are we ready to face the next one?
Chapter 1 has summarized and fundamentally addressed the historical emergence of different pandemics in the human community of the world. Moreover, a brief outcome of the management of the COVID-19 pandemic has also been observed.
AI is the precise simulation of human intelligence by machines. AI and computer-aided diagnosis are routinely used in medical imaging. In the context of the COVID-19 pandemic, early and accurate diagnosis of COVID-19 cases reduces the spread and mortality caused by SARS-CoV-2, the causative agent of COVID-19. AI has been used to improve the precise detection of COVID-19 cases. The gold standard for the detection of SARS-CoV-2 is RT-PCR. However, RT-PCR is a time-consuming process that can give false-negative results and requires skilled laboratory technicians, which may not be possible in some resource-constrained regions. Contrastingly, AI-based screening and detection of specific changes in X-ray and CT scan images of suspected COVID-19 patients can offer a cost-effective, speedy, and accurate diagnosis of clinical cases. The convolutional neural network (CNN), a DL algorithm, can improve the accuracy and reliability of the diagnosis of COVID-19 from chest X-rays. An enormous amount of training data is required to make accurate predictions of clinical cases via CNN. Several pretrained models such as GoogLeNet, AlexNet, VGG, and open databases such as GitHub can help with the training of DL networks. In Chapter 2, we look at how AI, ML, and DL can be used to improve the specificity, sensitivity, and accuracy of SARS-CoV-2 diagnosis.
Depression, stress, and anxiety are major issues affecting society among many age groups over a period of time. Of late, the COVID-19 pandemic has brought a jump in a phenomenal increase in cases among the younger age group population. In Chapter 3, the authors attempt to explore various DASS-21 variables among millennials and Gen-Z adults due to COVID-19. A strong association between DASS-21 variables and COVID-19 was established among Gen-Z and millennials. Based on the survey, various factors were ranked to understand the COVID-19 effect on DASS-21 variables. It is found that gender and educational qualifications played no role in the effect of COVID-19 on Gen-Z and millennials. Uncertainty in job and business emerges to be a major cause of depression, anxiety, and stress. The results obtained could help psychologists and government bodies to take appropriate steps to improve the mental health conditions of Gen-Z and millennials in society.
COVID-19 has cost 5 million lives worldwide and destabilized the economic and healthcare systems in just two years. An important strategy to combat COVID-19 is to propose a fast and accurate method of screening infected persons. One such efficient technique of screening is doing radiology examinations using chest X-rays. It was found in earlier studies that people affected with COVID-19 display abnormalities in chest radiography images. A large number of works detecting COVID-19 are presently available however; the works do not give a high accuracy of detection. Motivated by this drawback, a deep network-based solution to determine COVID-19 from X-rays of the chest has been proposed in Chapter 4. With the advent of the different variants of the COVID-19 virus determining whether a patient is affected by COVID-19 is not enough. The variant of COVID-19 also needs to be determined. The proposed work also provides an efficient algorithm for variant detection, that is, delta, omicron, or alpha variant. The proposed algorithm is split into two stages. Detection of COVID-19 is undertaken in the first stage, and in the next stage, the variant detection of COVID-19 is done for patients whose test results are COVID-19 positive. The proposed CNN model is inspired by the residual network model ResNet50. The suggested CNN model is inspired by the residual network model ResNet50. The model proposed is efficient and produces a high accuracy of 99.47% for stage 1 of the algorithm, that is, COVID-19 detection, and an accuracy of 98.46% for stage 2, that is, COVID-19 variant detection on the used dataset obtained from images of patients of Eastern India.
The coronavirus disease that caused the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) affected a bulk population worldwide. Understanding the evolution and...
