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Securing Next-Generation Connected Healthcare Systems: Artificial Intelligence Technologies focuses on the crucial aspects of IoT security in a connected environment, which will not only benefit from cutting-edge methodological approaches but also assist in the rapid scalability and improvement of these systems. This book shows how to utilize technologies like blockchain and its integration with IoT for communication, data security, and trust management. It introduces the security aspect of next generation technologies for healthcare, covering a wide range of security and computing methodologies.Researchers, data scientists, students, and professionals interested in the application of artificial intelligence in healthcare management, data security of connected healthcare systems and related fields, specifically on data intensive secured systems and computing environments, will finds this to be a welcomed resource

This book discusses the advances of artificial intelligence and data sciences in climate change and provides the power of the climate data that is used as inputs to artificial intelligence systems. It is a good resource for researchers and professionals who work in the field of data sciences, artificial intelligence, and climate change applications

This book discusses the advances of artificial intelligence and data sciences in climate change and provides the power of the climate data that is used as inputs to artificial intelligence systems. It is a good resource for researchers and professionals who work in the field of data sciences, artificial intelligence, and climate change applications

Intro -- Preface -- Contents -- Artificial Intelligence Technology Against COVID-19 -- Digital Transformation and Emerging Technologies for Tackling COVID-19 Pandemic -- 1 Introduction -- 2 Artificial Intelligence -- 2.1 Solutions Based on Artificial Intelligence -- 2.2 Solutions Based on Deep Learning -- 3 Internet of Things -- 3.1 Solution Based on the Internet of Things -- 3.2 Solution Based on Robots -- 3.3 Solutions Based on Unmanned Aerial Vehicles (Drones) -- 4 Big Data Analytics -- 5 Blockchain Technology -- 6 Cloud and Fog Computing -- 7 The Fourth Industrial Revolution -- 8 Conclusion and Future Aspects -- References -- The Role of Emerging Technologies for Combating COVID-19 Pandemic -- 1 Introduction -- 2 Literature Reviews -- 2.1 Blockchain Technology -- 2.2 Artificial Intelligence -- 2.3 Internet of Things Technology -- 2.4 Big Data Technology -- 3 COVID-19 Datasets -- 4 Applications of Emerging Technologies in COVID-19 -- 4.1 Application of AI Against COVID-19 -- 4.2 Application of IoT Against COVID-19 -- 4.3 Application of Big Data Against COVID-19 -- 4.4 Blockchain Applications Against COVID-19 -- 5 Challenges -- 5.1 Shortage of Standard Datasets -- 5.2 Regulation Reflection -- 5.3 Security -- 5.4 Privacy Preservation -- 6 Future Directions -- 6.1 Covid19 Datasets -- 6.2 AI Against Covid19 -- 6.3 Blockchain Against COVID-19 -- 6.4 Big Data Against COVID-19 -- 6.5 Merge with Other Emerging Technologies -- 7 Conclusion -- References -- An Optimized Classification Model for COVID-19 Pandemic Based on Convolutional Neural Networks and Particle Swarm Optimization Algorithm -- 1 Introduction -- 2 Related Work -- 3 Basics and Background -- 3.1 Convolutional Part -- 3.2 Classifier Part -- 3.3 Training a CNN Network -- 4 The Proposed COVID-19 Classification Optimized Model -- 4.1 Data Preprocessing Phase -- 5 Conclusion and Future Work.

This book is divided into three parts. The first part discusses the Metaverse's basics, development, and optional applications such as 3D virtual dressing room-based user-friendly Metaverse, the use of Metaverse in the healthcare and environment sectors as well as the ethics of the Metaverse and digital virtual environments. Part two presents some chapters that discuss emerging technologies in the Metaverse world including IoT, digital twining, and artificial intelligence and shows its impact on climate change. The third part contains chapters discussing cybersecurity in the Metaverse including blockchain technology opportunities and applications and the threat of the digital humanities in the Metaverse. The book is suitable for students and academics aiming to build up their background on the Future of the Metaverse in the Virtual Era and Physical World

Intro -- Preface -- Contents -- Artificial Intelligence in Sustainability Agricultures -- Optimization of Drip Irrigation Systems Using Artificial Intelligence Methods for Sustainable Agriculture and Environment -- 1 Introduction -- 2 Mathematical Model -- 3 Algorithm -- 4 Simulation -- 5 Conclusion -- References -- Artificial Intelligent System for Grape Leaf Diseases Classification -- 1 Introduction -- 2 Materials and Methods -- 2.1 K-Means Algorithm for Fragmentation -- 2.2 Multiclass Support Vector Machine Classifier -- 3 The Proposed Artificial Intelligent Based Grape Leaf Diseases -- 3.1 Dataset Characteristic -- 3.2 Image Processing Phase -- 3.3 Image Segmentation Phase -- 3.4 Feature Extraction Phase -- 3.5 Classification Phase -- 4 Results and Discussion -- 5 Conclusions -- References -- Robust Deep Transfer Models for Fruit and Vegetable Classification: A Step Towards a Sustainable Dietary -- 1 Introduction -- 2 Related Works -- 3 Dataset Characteristics -- 4 Proposed Methodology -- 4.1 Data Augmentation Techniques -- 5 Experimental Results -- 6 Conclusion and Future Works -- References -- The Role of Artificial Neuron Networks in Intelligent Agriculture (Case Study: Greenhouse) -- 1 Introduction -- 2 Overview of AI -- 3 Agriculture and Greenhouse -- 4 Intelligent Control Systems (SISO and MIMO) -- 4.1 Particular Aspects of Information Technology on Greenhouse Cultivation -- 4.2 Greenhouse Climate Control Techniques -- 5 Modern Optimization Techniques -- 5.1 Genetic Algorithms -- 5.2 Main Attractions of GAs -- 5.3 Strong and Weak Points of FL and Neural Networks -- 6 Fuzzy Identification -- 7 Conclusion -- References -- Artificial Intelligence in Smart Health Care -- Artificial Intelligence Based Multinational Corporate Model for EHR Interoperability on an E-Health Platform -- 1 Introduction.

Theoretical and practical foundations of liquidity-adjusted value-at-risk (lvar) : optimization algorithms for portfolios selection and management / Mazin A. M. Al Janabi -- Financial analysis for mobile and cloud applications / Jennifer Brodmann and Makeen Huda -- Eye movement study of customers on video advertising marketing / Xiaolong Liu, Ruoqi Liang -- An optimization algorithm and smart model for periodic capacitated arc routing problem considering mobile disposal sites / Erfan Babaee Tirkolaee, Ali Asghar Rahmani Hosseinabadi -- Whale optimization based opinion mining analysis of e-commerce site with fuzzy clustering / K. Shankar, M. Ilayaraja, P. Deepalakshmi, S. Ramkumar, K. Sathesh Kumar, S. K.Lakshmanaprabu, Andino Maseleno -- Big data text mining in financial sector / Mirjana Pejic Bach, ivko Krstic, Sanja Seljan -- Cel: citizen economic level using SAW / Andino Maseleno, K. Shankar, Prayugo Khoir, Muhammad Muslihudin -- The investment opportunities for building smartphone applications for tourist cities in Saudi Arabia : the case of abha city / Dr. Saeed Q. Al-Khalidi Al-Maliki, Dr. Mohammed A. Al-Ghobiri -- An applied credit scoring model / Esther Castro, M. Kabir Hassan, Mark Rosa -- Intelligent distributed applications in e-commerce and e-banking / Jennifer Brodmann and Phuvadon Wuthisatian -- Feature selection-based data classification for stock price prediction using Ant Miner algorithm / Saravanan Ramalingam, Pothula Sujatha -- The value of simulations characterizing classes of symbiosis : ABCs of formulation design / K. Basaid, B. Chebli, J.N. Furze, E.H. Mayad and R. Bouharroud -- Application of project scheduling in production process for paddy cleaning machine by using Pert & CPM techniques: case study / S. Bangphan, P.Bangphan and S. Phanphet -- The managing of deep learning algorithms to enhance momentum trading strategies during the time frame to quick detect market of smart money / Khalid Abouloula, Ali Ou-Yassine and Salah-ddine Krit -- Pattern to build a robust trend indicator for automated trading / Khalid Abouloula, Ali Ou-Yassine and Salah-ddine Krit -- Index.

"Social networks provide a powerful abstraction of the structure and dynamics of diverse kinds of people or people-to-technology interaction. Web 2.0 has enabled a new generation of web-based communities, social networks, and folksonomies to facilitate collaboration among different communities. This unique text/reference compares and contrasts the ethological approach to social behavior in animals with web-based evidence of social interaction, perceptual learning, information granulation, the behavior of humans and affinities between web-based social networks. An international team of leading experts present the latest advances of various topics in intelligent-social-networks and illustrates how organizations can gain competitive advantages by applying the different emergent techniques in real-world scenarios. The work incorporates experience reports, survey articles, and intelligence techniques and theories with specific network technology problems. Topics and Features: Provides an overview social network tools, and explores methods for discovering key players in social networks, designing self-organizing search systems, and clustering blog sites, surveys techniques for exploratory analysis and text mining of social networks, approaches to tracking online community interaction, and examines how the topological features of a system affects the flow of information, reviews the models of network evolution, covering scientific co-citation networks, nature-inspired frameworks, latent social networks in e-Learning systems, and compound communities, examines the relationship between the intent of web pages, their architecture and the communities who take part in their usage and creation, discusses team selection based on members' social context, presents social network applications, including music recommendation and face recognition in photographs, explores the use of social networks in web services that focus on the discovery stage in the life cycle of these web services. This useful and comprehensive volume will be indispensible to senior undergraduate and postgraduate students taking courses in Social Intelligence, as well as to researchers, developers, and postgraduates interested in intelligent-social-networks research and related areas"--Publisher's description

"This book provides researchers readers with a synthesis of current research on developing countries experience with e-commerce"--Provided by publisher

Intro -- Introduction -- Contents -- Mobile Applications and Web Applications to Improve Competitiveness in Industry 4.0 -- Implementation of an Intelligent Model Based on Convolutional Neural Network for the Detection of Diseases in Citrus Crops Caused by Bird Pests Using an Intelligent Drone -- 1 Introduction -- 2 Project Development -- 2.1 Object Classifier and Object Detector -- 2.2 Artificial Neural Network -- 2.3 Convolutional Neural Network -- 2.4 Comparison Between an Artificial Neural Network and a CNN -- 2.5 Pixels and Neurons -- 2.6 Choice of the Crop to Be Analyzed -- 2.7 Process to Be Automated -- 3 Materials and Methods -- 3.1 Acquisition of the Images -- 3.2 Development of the Application -- 4 Results -- 5 Experimentation -- 6 Conclusions and Future Research -- References -- Intelligent Application to Detection of Arachnid Bites in Children Implementing Deep Learning Techniques, an AmI-Based Solution -- 1 Introduction -- 2 Implementation of the Intelligent Application -- 3 Spider Bite Recognition -- 3.1 Diagnosis, Prognosis and Follow-up -- 3.2 Treatment -- 3.3 Prevention -- 3.4 Methodological Proposal for the Recognition of an Arachnid Bite -- 4 Test Development -- 4.1 Module for the Recognition of Arachnids and their Bites -- 4.2 Results -- 5 Conclusions and Future Work -- References -- Evacuation Route Optimization in the Plaza de la Mexicanidad, Using Humanitarian Logistics -- 1 Introduction -- 2 Behavior of the Masses -- 2.1 Stampedes of the Masses -- 2.2 Pre-disaster Planning -- 2.3 Implementation of a Mass Victim Assistance System -- 3 Simulation Models -- 3.1 State of the Art -- 3.2 Mathematical Model -- 3.3 Simulated Case Studies and Comparison with Reality -- 3.4 Trajectory Simulation -- 4 Voronoi Diagram -- 5 Future Research and Works -- 6 Conclusions and Future Challenges -- References.

This book constitutes the refereed proceedings of the 2022 International Conference on Business Intelligence and Information Technology (BIIT 2022) held in Harbin, China, during December 1718, 2022. BIIT 2022 is organized by the School of Computer and Information Engineering, Harbin University of Commerce, and supported by Scientific Research Group in Egypt (SRGE), Egypt. The papers cover current research in electronic commerce technology and application, business intelligence and decision making, digital economy, accounting informatization, intelligent information processing, image processing and multimedia technology, signal detection and processing, communication engineering and technology, information security, automatic control technique, data mining, software development, and design, blockchain technology, big data technology, and artificial intelligence technology.

The fight against the COVID-19 pandemic still involves many struggles and challenges. The greatest challenge that most governments are currently facing is the lack of a precise, accurate, and automated mechanism for detecting and tracking new COVID-19 cases. In response to this challenge, this study proposes the first blockchain-based system, called the COVID-19 contact tracing system (CCTS), to verify, track, and detect new cases of COVID-19. The proposed system consists of four integrated components: an infection verifier subsystem, a mass surveillance subsystem, a P2P mobile application, and a blockchain platform for managing all transactions between the three subsystem models. To investigate the performance of the proposed system, CCTS has been simulated and tested against a created dataset consisting of 300 confirmed cases and 2539 contacts. Based on the metrics of the confusion matrix (i.e., recall, precision, accuracy, and F1 Score), the detection evaluation results proved that the proposed blockchain-based system achieved an average of accuracy of 75.79% and a false discovery rate (FDR) of 0.004 in recognizing persons in contact with COVID-19 patients within two different areas of infection covered by GPS. Moreover, the simulation results also demonstrated the success of the proposed system in performing self-estimation of infection probabilities and sending and receiving infection alerts in P2P communications in crowds of people by users. The infection probability results have been calculated using the binomial distribution function technique. This result can be considered unique compared with other similar systems in the literature. The new system could support governments, health authorities, and citizens in making critical decisions regarding infection detection, prediction, tracking, and avoiding the COVID-19 outbreak. Moreover, the functionality of the proposed CCTS can be adapted to work against any other similar pandemics in the future. ; Web of Science ; 8 ; 4 ; art. no. 72