Human-Assisted Intelligent Computing
Description
Human-assisted computation also called humanized or human-based computing harnesses human intelligence to solve computational problems that are beyond the scope of existing Artificial Intelligence algorithms by outsourcing certain steps to humans. This approach exploits differences in abilities between humans and computer agents creating a symbiotic human-computer interaction. Human assistance can be helpful in solving many AI-complete problems, which by definition are tasks which are impossible for computers but possible for humans. For computationally difficult tasks such as image recognition, human-based computation plays a central role in optimizing Deep Learning-based Artificial Intelligence systems, as can be seen in many citizen-science projects such as Zooniverse.
This book focuses on well-known and new methodologies of optimization techniques in human-assisted computing that are used to resolve some of the very complicated and hard problems we face today. Excitingly techniques originally developed for solutions in engineering, science and technology are being applied to areas of economics, finance and, especially the social sciences. The book reviews present and developing deep model-based methods of mathematics and the less model-based, also so-called smart or intelligent algorithms, with their roots in engineering, computer science or informatics and how combing the strengths of humans and computers can create powerful solutions. Often called heuristics and model-free, they are less rigorous mathematically, enabling the integration of bio-inspired approaches to efficiently cope with AI-complete problems. The rise of these algorithms from Artificial Intelligence research happened in parallel with the powerful progress in model-based mathematics. Often called Statistical Learning, Machine Learning, Metaheuristics or Operational Research, model-free and model-based traditions gain from the synergistic effects of humanized computing, revealing solutions to urgent real-life challenges across numerous fields. Bridging several scientific disciplines, this book will be essential reading for scientists, engineers and applied mathematicians alike.
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Mukhdeep Singh Manshahia, is an Assistant Professor at Punjabi University Patiala, Punjab, India. He is working in Sustainable Computing, Artificial Intelligence, Wireless Sensor Networks, the Internet of Things (IoT), Nature Inspired Computing, Energy Harvesting and Renewable Energy Systems. He has edited a book entitled " He has 15 years of working experience at the universities. He is an associate editor of the International Journal of Energy Optimization and Engineering (IJEOE) and a Reviewer of many WoS journals. He is a member of the Computer Society of India, IEEE and IAENG.
Prof Igor Litvinchev received his M.Sc. degree in Applied Mathematics from Moscow Institute of Physics and Technology (Fizteh), Russia; PhD in Systems Theory and Operations Research and Dr Sci(Habilitation) in Systems Modeling and Optimization from Computing Center, Russian Academy of Sciences (CCAS), Moscow. He is currently a Professor at Nuevo Leon State University, Mexico and a Leading Mathematician at CCAS. His research is focused on large-scale systems modeling, optimization and control as well as on their applications in interdisciplinary research. Professor Litvinchev is an author of 4 books and an editor of 5 more. He published more than 90 research papers in leading international journals and served in Program and Organizing Committees for more than 40 international conferences. His research was supported by more than 30 grants from NATO Scienti¿c Affairs Division and European Community; ISF (USA) and RFBR (Russia); CNPq and FAPESP (Brasil); BRFBR (Belarus); CONACYT, PROMEP and PAICYT (Mexico). Professor Litvinchev is a member of the Russian Academy of Natural Sciences and the Mexican Academy of Sciences. He is the co-founder of the Mexican Society of Operations Research and the Mexican Logistics and Supply Chain Association.
Prof Elias Munapo holds a BSc. (Hons) in Applied Mathematics (1997), MSc. in Operations Research (2002) and a PhD in Operations Research (2010). All these qualifications are from the National University of Science and Technology (N.U.S.T.) in Zimbabwe. Elias Munapo is a Professional Natural Scientist and was certified by the South African Council for Natural Scientific Professions (SACNASP) in 2012. He has vast experience in university education and has worked for five (5) institutions of higher learning. He was a lecturer at Zimbabwe Open University (ZOU) (2003-2004), Chinhoyi University of Technology (CUT) (2005-2008) and the University of South Africa (2009-2012). He became a Senior Lecturer at the University of KwaZulu-Natal (UKZN) (2013-2015). Elias Munapo joined North West University as an Associate Professor in 2016 and has been appointed Professor since January 2019. Elias Munapo was an Academic Leader/Programme Leader for Higher Degrees & Research. Elias Munapo has published over 100 research articles and one book. He is an editor of several international journals and books. He has presented at both local and international conferences and was part of the organizing committees of several local and international conferences. He is a member of the Operations Research Society of South Africa (was ORSSA - Executive Committee Member in 2012 and 2013), South African Council for Natural Scientific Professions (SACNASP) as a Certified Natural Scientist, European Conference on Operational Research (EURO) and the International Federation of Operations Research Societies (IFORS).
Gerhard-Wilhelm ("Willi") Weber, PhD, is a Professor at the Institute of Applied Mathematics (IAM) of METU, Ankara. His research is on OR, financial mathematics, economics, optimization and data mining, but also on life sciences, education and development. He received his Diploma and Doctorate in mathematics, and economics/business administration, at RWTH Aachen, and his Habilitation in mathematics at TU Darmstadt. He held Professorships by proxy at the University of Cologne, and TU Chemnitz, Germany. He is also a member of five further graduate schools, institutes and departments of METU. He has affiliations at the universities of Siegen, Ballarat, Aveiro and North Sumatra, and he is an "Advisor to EURO Conferences". At IFORS, he is chair of the "OR for Developing Countries" online resources and regional correspondent for EURO of IFORS Newsletter. He serves EURO Working Group on OR for Development (EWG ORD), EURO Working Groups on Continuous Optimization (EUROPT) and EURO Working Group Methodology of Societal Complexity as "honorary chair".
Dr J Joshua Thomas, is an associate professor at UOW Malaysia KDU Penang University College, Malaysia. He obtained his PhD (Intelligent Systems Techniques) in 2015 from University Sains Malaysia, Penang, and his Master's degree in 1999 from Madurai Kamaraj University, India. From July to September 2005, he worked as a research assistant at the Artificial Intelligence Lab at University Sains Malaysia. From March 2008 to March 2010, he worked as a research associate at the same University. Currently, he is working with Machine Learning, Big Data, Data Analytics, and Deep Learning, especially targeting on Convolutional Neural Networks (CNN) and Bi-directional Recurrent Neural Networks (RNN) for image tagging with embedded natural language processing, End to end steering learning systems and GAN. His work involves experimental research with software prototypes and mathematical modelling and design He is an editorial board member for the Journal of Energy Optimization and Engineering, and invited guest editor for the Journal of Visual Languages Communication. Recently with Computer Methods and Programs in Biomedicine. He has published more than 40 papers in leading international conference proceedings and peer-reviewed journals.
Dr Pandian Vasant holds B.Sc (Hons, II Class UPPER) in Mathematics, an MSc (Engineering Mathematics), and PhD (UNEM, Costa Rica) in Computational Intelligence (By Research). Universidad Empresarial de Costa Rica (UNEM) is accredited by: IAU (International Association of Universities), UNESCO (United Nations Educational, Scientific and Cultural Organization), THE UNITED NATIONS and BQS (Board of Quality Standards)/BPS/IQIHE (International Quality Institute for Higher Education). Dr Pandian Vasant **is an Editor-in-Chief of IJEOE (ESCI/WoS). He holds PhD in Computational Intelligence (UNEM, Costa Rica), MSc (UMS, Malaysia, Engineering Mathematics) and BSc (Hons) in Mathematics (MU, Malaysia). His research interests include Soft Computing, Hybrid Optimization, Innovative Computing and Applications. He has co-authored numerous research articles in journals, conference proceedings and book chapters. Currently, he is Editor-in-Chief of the International Journal of Energy Optimization & Engineering, and a Member of AMS (USA), NAVY Research Group (TUO, Czech Republic) and MERLIN Research Group (TDTU, Vietnam).
Content
1 Machine Learning Algorithms to Improve Crop Evapotranspiration Estimation Covering a Broad Range of Environmental Gradients in Agriculture 4.0-A Review
2 Iris-Based Biometric Cryptosystem
3 Bio-Inspired Approaches for Combined Economic Emission Dispatch problem
4 Eigenvalue Clustering for Spectrum Sensing: Throughput and Energy Evaluation For CR-IoT network
5 Modelling The Evolution of Complex Networks Arising in Applications
6 Computing the Intelligent Privacy-Engineered Organization: A Metamodel of Effective Information Transparency Enhancing Tools/Technologies
7 A Model of Cells' Regeneration Towards Smart Healthcare
8 Anomaly Detection in Location-Based Services
9 Optimized Packing Soft Ellipses
10 An Analysis of Phishing Attacks
11 HAIC and Ecological Modeling (Drought Early Warning System)
12 Attention Mechanisms in Machine Vision: A Survey of The State of The Art
13 Sparse 2d Packing in Thermal Deburring with Shock Waves Acting Effects
14 Implementation of Smart Manufacturing in SME
15 Performance Analysis of Fractal Image Compression methods for Medical Images - A Review
16 Mobile Edge Computing for Efficient Energy Management System
17 Modeling 3D Nanocomposites with Multi-Spherical Inclusions by Optimized Packing
18 Sentiment Analysis for Web Series using Deep Learning Techniques in the Times of Covid-19
19 Generalized Receiver: Signal Processing in DS-CDMA Wireless Communication Systems Over Fading Channels
20 Critical Success Factors for successfully Implementation of Smart Manufacturing in the Context of Industry 4.0
21 An Efficient Heart Disease Diagnosis Prediction Model Using Decision Tree Classifier: Streamlit
22 Mathematical And Informational Support of Decision-Making in The Field of Risk Management of Cross-Border High-Tech Projects (On The Example Of Russian-Chinese Cooperation)
23 Artificial Intelligence (AI) In the Era of Precision Medicine
24 Optimal Choice for Convenience Store Chain in Vietnam
25 Study Of Groundwater Using Hydrodynamic Models
26 Long-Term Fatigue Assessment of Offshore Monopile Structure Under Corrosive Environmental Condition
27 Estimation Of Crop Water Use in Agricultural Systems
28 IOT Based HealthCare Monitoring System for Smart City Applications
29 Smart Healthcare - The New Digital Revolution in Medical Management
30 Adequate Implementation of Simulation Tools for Enhancement Performance on Existing Network Infrastructure Devices (OPNET).
31 Artificial Intelligence Based Garbage Monitoring System for Garbage Management Using Integrated Sensors
32 Use of Internet of Things Technology in Medical Field During the Pandemic Era
33 decision making in irrigation management by adopting random forest technique in horticulture crops
34 Healthcare Information Systems and Study of Machine Learning Technology for Cancer Detection
35 Performance Comparison of Data Security Algorithms
