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• Introduction State of the Art The Performed Research Results Structure of this Book Biometric Systems Biometric Traits Applications Evaluation of Biometric Systems Research Trends Summary Touchless and Less-Constrained Biometrics Less-Constrained Biometric Systems Touchless Biometric Traits Touch-Based Biometric Traits Summary Fingerprint Biometrics Fingerprint Recognition Characteristics of the Fingerprint Applications Analysis of Fingerprint Samples Touch-Based Fingerprint Recognition Touchless Fingerprint Biometrics Summary Touchless Fingerprint Recognition Touchless Fingerprint-Recognition Techniques Methods Based on Two-Dimensional Samples Methods Based on Three-Dimensional Models Computation of Synthetic Touchless Fingerprint Samples Summary Experimental Results Methods Based on Single Touchless Images Methods Based on Three-Dimensional Models Comparison of Biometric-Recognition Methods Computation of Synthetic Three-Dimensional Models Summary Conclusions and Future Work Conclusions Future Work.
• (source: Nielsen Book Data)

• Introduction. Biometric Systems. Touchless and Less-Constrained Biometrics. Fingerprint Biometrics. Touchless Fingerprint Recognition. Experimental Results. Conclusions and Future Work.
• (source: Nielsen Book Data)

Offering the first comprehensive analysis of touchless fingerprint-recognition technologies, Touchless Fingerprint Biometrics gives an overview of the state of the art and describes relevant industrial applications. It also presents new techniques to efficiently and effectively implement advanced solutions based on touchless fingerprinting. The most accurate current biometric technologies in touch-based fingerprint-recognition systems require a relatively high level of user cooperation to acquire samples of the concerned biometric trait. With the potential for reduced constraints, reduced hardware costs, quicker acquisition time, wider usability, and increased user acceptability, this book argues for the potential superiority of touchless biometrics over touch-based methods. The book considers current problems in developing high-accuracy touchless recognition technology. It discusses factors such as shadows, reflections, complex backgrounds, distortions due to perspective effects, uncontrolled finger placement, inconstant resolution of the ridge pattern, and reconstruction and processing of three-dimensional models. The last section suggests what future work can be done to increase accuracy in touchless systems, such as intensive studies on extraction and matching methods and three-dimensional analytical capabilities within systems. In a world where usability and mobility have increasing relevance, Touchless Fingerprint Biometrics demonstrates that touchless technologies are also part of the future. A presentation of the state of the art, it introduces you to the field and its immediate future directions.
(source: Nielsen Book Data)
Offering the first comprehensive analysis of touchless fingerprint-recognition technologies, Touchless Fingerprint Biometrics gives an overview of the state of the art and describes relevant industrial applications. It also presents new techniques to efficiently and effectively implement advanced solutions based on touchless fingerprinting.The most.
(source: Nielsen Book Data)

• 1. Introduction
• 2. Biometric systems
• 3. Touchless and less-constrained biometrics
• 4. Fingerprint biometrics
• 5. Touchless fingerprint recognition
• 6. Experimental results
• 7. Conclusions and future work

• Introduction
• Biometric systems
• Touchless and less-constrained biometric systems
• Palmprint biometrics
• Innovative methods for touchless and less-constrained palmprint recognition
• Application and experimental evaluation of methods
• Conclusions.

This book examines the context, motivation and current status of biometric systems based on the palmprint, with a specific focus on touchless and less-constrained systems. It covers new technologies in this rapidly evolving field and is one of the first comprehensive books on palmprint recognition systems. It discusses the research literature and the most relevant industrial applications of palmprint biometrics, including the low-cost solutions based on webcams. The steps of biometric recognition are described in detail, including acquisition setups, algorithms, and evaluation procedures. Constraints and limitations of current palmprint recognition systems are analyzed and discussed. The authors also introduce innovative methods for touchless and less-constrained palmprint recognition, with the aim to make palmprint biometrics easier to use in practical, daily-life applications, and overcome the typical constraints and limitations described. Touchless Palmprint Recognition Systems targets professionals and researchers working in biometrics, image processing and three-dimensional reconstruction. Advanced-level students studying biometrics and computer science will also find this material valuable as a secondary text book or reference.

• Sensors for Human Behavior Analysis
• Related Work
• Sensor Data Interpretation for Symbolic Analysis
• Semantic Analysis
• Evaluation of the Proposed Methodology
• Conclusions.

Semantic Analysis and Understanding of Human Behaviour in Video Streaming investigates the semantic analysis of the human behaviour captured by video streaming, and introduces both theoretical and technological points of view. Video analysis based on the semantic content is in fact still an open issue for the computer vision research community, especially when real-time analysis of complex scenes is concerned. This book explores an innovative, original approach to human behaviour analysis and understanding by using the syntactical symbolic analysis of images and video streaming described by means of strings of symbols. A symbol is associated to each area of the analyzed scene. When a moving object enters an area, the corresponding symbol is appended to the string describing the motion. This approach allows for characterizing the motion of a moving object with a word composed by symbols. By studying and classifying these words we can categorize and understand the various behaviours. The main advantage of this approach lies in the simplicity of the scene and motion descriptions so that the behaviour analysis will have limited computational complexity due to the intrinsic nature both of the representations and the related operations used to manipulate them. Besides, the structure of the representations is well suited for possible parallel processing, thus allowing for speeding up the analysis when appropriate hardware architectures are used. A new methodology for design systems for hierarchical high semantic level analysis of video streaming in narrow domains is also proposed. Guidelines to design your own system are provided in this book. Designed for practitioners, computer scientists and engineers working within the fields of human computer interaction, surveillance, image processing and computer vision, this book can also be used as secondary text book for advanced-level students in computer science and engineering.
(source: Nielsen Book Data)

• Blockchain.- Security for Critical Infrastructure.- IoT Security.- Software Security.- Network.- Web Security.- Authentication.- Biometric Security.- Cryptography.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 17th International Conference on Information Security Practice and Experience, ISPEC 2022, held in Taipei, Taiwan, in November 2022. The 33 full papers together with 2 invited papers included in this volume were carefully reviewed and selected from 87 submissions. The main goal of the conference is to promote research on new information security technologies, including their applications and their integration with IT systems in various vertical sectors.
(source: Nielsen Book Data)

• From von Neumann architecture and Atanasoff's ABC to Neuro-morphic Computation and Kasabov's NeuCube: Principles and Implementations.- Applications of Computational Intelligence in Industrial and Environmental Scenarios.- Real, Imaginary and Complex Sets.- Intercriteria analysis over patterns.- From Primary to Conventional Science.- Intelligent Two-Level Optimization and Model Predictive Control of Degrading Plants.- Collaborative Clustering: New Perspective to Rank Factor Granules.- Learning through Contstraint Applications.- Autonomous Flight Control and Precise Gestural Positioning of a Small Quadrotor.- Introduction to the Theory of Randomized Machine Learning.- Grid-Type Fuzzy Models for Performance Evaluation and Condition Monitoring of Photovoltaic Systems.- Intelligent Control of Uncertain Switched Nonlinear Plants: NFG Optimum Control Synthesis via Switched Fuzzy Time-delay Systems.- Multidimensional Intuitionistic Fuzzy Quantifiers and Level Operators.- Data Processing and Harmonization for Intelligent Transportation Systems. An Application Scenario on Highway Traffic Flows.
• (source: Nielsen Book Data)

By presenting the latest advances in fuzzy sets and computing with words from around the globe, this book disseminates recent innovations in advanced intelligent technologies and systems. From intelligent control and intuitionistic fuzzy quantifiers to various data science and industrial applications, it includes a wide range of valuable lessons learned and ideas for future intelligent products and systems.
(source: Nielsen Book Data)

• Chapter 1. Prediction and Analysis on COVID-19 Using Positive and Negative Association Rule Mining.-
• Chapter 2. Hybrid Algorithm Based on DWT-DCT-RSA with Digital Watermarking for Secure Image Transfer.-
• Chapter 3. Detecting Sexually Predatory Behavior on Open-Access Online Forums.-
• Chapter 4. Swarm based Sudoku Solution: An Optimization Procedure.-
• Chapter 5. Application of Cellular Automata (CA) for Predicting Urban Growth and Loss of Vegetation and Waterbodies in Eastern India.-
• Chapter 6. Parallel Deep Learning-Driven Sarcasm Detection from Pop Culture Text and English Humor Literature.-
• Chapter 7. Sentiment Analysis of Covid-19 Tweets using Evolutionary Classification based LSTM Model.-
• Chapter 8. Clustering as a Brain-Network Detection Tool for Mental Imagery Identification.-
• Chapter 9. Comparative study of the effect of different fitness function in PSO algorithm on band selection of hyper spectral imagery.-
• Chapter 10. Breast Abnormality Detection Using Texture Feature Extracted by difference-based-variable-size Local Filter(DVLF).-
• Chapter 11. Nuclei image boundary detection based on interval type-2 fuzzy set and bat algorithm.-
• Chapter 12. Machine Learning Approach to Sentiment Analysis from Movie Reviews using Word2Vec.-
• Chapter 13. Selection of Edge Detection Techniques Based on Machine Learning Approach.-
• Chapter 14. ANN Based Self-Tuned PID Controller for Temperature Control of Heat Exchanger.-
• Chapter 15. A Novel Partitioning Algorithm to Process Large-Scale Data.
• (source: Nielsen Book Data)

This book discusses the recent research trends and upcoming applications based on artificial intelligence. It includes best selected research papers presented at the International Conference on Research and Applications in Artificial Intelligence (RAAI 2020), organized by Department of Information Technology, RCC Institute of Information technology, Kolkata, West Bengal, India during 19 - 20, December, 2020. Many versatile fields of artificial intelligence are categorically addressed through different chapters of this book. The book is a valuable resource and reference for researchers, instructors, students, scientists, engineers, managers and industry practitioners in these important areas.
(source: Nielsen Book Data)

• Invited paper
• While Mobile Encounters with Clouds
• Authentication Mechanism
• Multi-Device Anonymous Authentication
• A Mobile Device-Based Antishoulder-Surfing Identity Authentication Mechanism
• Mutual Authentication with Anonymity for Roaming Service with Smart Cards in Wireless Communications
• Cloud Computing Security
• Efficient Fine-Grained Access Control for Secure Personal Health Records in Cloud Computing
• An Energy-Efficient Task Scheduling Heuristic Algorithm without Virtual Machine Migration in Real-time Cloud Environments
• An Infrastructure-Based Framework for the Alleviation of JavaScript Worms from the OSN in Mobile Cloud Platforms
• Data Mining for Security Application
• Ld-CNNs: A Deep Learning System for Structured Text Categorization Based on LDA in Content Security
• Realtime DDoS detection in SIP Ecosystems: Machine Learning tools of the trade
• Digital Signature
• Two-in-One Oblivious Signatures Secure in the Random Oracle Model
• A New Transitive Signature Scheme
• Privacy-preserving Technologies
• Privacy-Preserving Profile Matching Protocol Considering Conditions
• Privacy Preserving Credit Systems
• Evading System-Calls Based Intrusion Detection Systems
• Network Security and Forensic
• HeapRevolver: Delaying and Randomizing Timing of Release of Freed Memory Area to Prevent Use-After-Free Attacks
• A Network Timestamp Verification Mechanism for Forensic Analysis
• Searchable Encryption
• An Efficient Secure Channel Free Searchable Encryption Scheme with Multiple Keywords
• Searchable Symmetric Encryption Supporting Queries with Multiple-Character Wildcards
• A System of Shareable Keyword Search on Encrypted Data
• Security Policy and Access Control
• An Attribute Based Protection Model for JSON Documents
• The GURA-G Administrative Model for User and Group Attribute Assignment.-On the relationship between finite domain ABAM and PreUCONA
• Security Protocols
• MD-VCMatrix: An Efficient Scheme for Publicly Verifiable Computation of Outsourced Matrix Multiplication
• Expressive Rating Scheme by Signatures with Predications on Ratees
• Symmetric Key Cryptography
• A New Adaptable Construction of Modulo Addition with Scalable Security for Stream Ciphers
• Extension of Meet-in-the-Middle Technique for Truncated Differential and Its Application to RoadRunneR
• System Security
• DF-ORAM: A Practical Dummy Free Oblivious RAM to Protect Outsourced Data Access Pattern
• PMFA: Toward Passive Message Fingerprint Attacks on Challenge-based Collaborative Intrusion Detection Networks
• Iris Cancellable Template Generation based on Indexing-First-One Hashing
• Web Security
• Detecting Malicious URLs Using Lexical Analysis
• Gatekeeping Behavior Analysis for Information Credibility Assessmenton Weibo
• Data Mining for Security Application (Short Paper)
• Finding Anomalies in SCADA Logs Using Rare Sequential Pattern Mining
• Provable Seucirty (Short Paper)
• Improved Security Proofs for Modular Exponentiation Bits
• Security Protocol (Short Paper)
• Secure Outsourced Bilinear Pairings Computation for Mobile Devices
• The Design and Implementation of Multi-Dimensional Bloom Filter Storage Matrix.

This book constitutes the proceedings of the 10th International Conference on Network and System Security, NSS 2016, held in Taipei, Taiwan, in September 2016. The 31 full and 4 short papers presented in this volume were carefully reviewed and selected from 105 submissions. They were organized in topical sections named: authentication mechanism; cloud computing security; data mining for security application; privacy-preserving technologies; network security and forensics; searchable encryption; security policy and access control; security protocols, symmetric key cryptography; system security; Web security. The volume also contains one invited paper.

• Intro
• Foreword
• Preface
• Contents
• About the Editors
• Computational Intelligence
• Transience in COVID Patients with Comorbidity Issues-A Systematic Review and Meta-Analysis Based on Indian and Southeast Asian Context
• 1 Introduction
• 1.1 Risk of COVID Patients with Comorbidity Issues
• 2 COVID Patient Statistics with Comorbidity Issues
• 3 Research Methodology
• 3.1 Search Strategy
• 4 Related Literature Survey in This Area
• 5 Discussion
• 6 Conclusion and Future Scope
• References
• NFT HUB-The Decentralized Non-Fungible Token Market Place
• 1 Introduction

• 1.1 Non-Fungible Token
• 1.2 Blockchain
• 2 Literature Survey
• 3 Proposed System
• 3.1 Blockchain
• 3.2 Ethereum Blockchain
• 3.3 Properties of Blockchain
• 3.4 Generic Elements of the Blockchain
• 3.5 Secure Hash Algorithm
• 4 Results and Discussion
• 4.1 Deployment Confirmation
• 4.2 Metamask Wallet
• 4.3 Minting Page
• 4.4 Transaction Address
• 4.5 Dashboard
• 5 Conclusion
• 5.1 Future Scope of the Project
• References
• Hashgraph: A Decentralized Security Approach Based on Blockchain with NFT Transactions
• 1 Introduction
• 1.1 Optimized Blockchain Server

• 2 Literature Survey
• 2.1 Survey Report: On Token Service
• 2.2 Survey Report: On Main-Net Access
• 2.3 Survey Report: Remove Centralized Control: Hala Systems
• 3 Proposed System
• 3.1 Non-Fungible Transaction
• 3.2 Blockchain Methodology
• 3.3 Gossip Protocol
• 3.4 Hashgraph
• 3.5 Consensus Algorithm [In Gossip Protocol]
• 3.6 HCS Implementation
• 4 Performance Evaluation
• 4.1 Transaction Cost Denomination of Our Network
• 4.2 Transaction Cost of Network on Blockchain NFT
• 5 Result and Discussion
• 6 Conclusion
• References

• Med Card: An Innovative Way to Keep Your Medical Records Handy and Safe
• 1 Introduction
• 1.1 What is Blockchain?
• 1.2 What is Machine Learning?
• 2 Literature Review
• 3 Technologies Used
• 3.1 Blockchain in Health Care
• 3.2 Machine Learning in Health Care
• 4 Proposed Idea
• 4.1 What is a Med Card?
• 4.2 Workflow
• 5 Conclusion and Future Scope
• References
• Delta Operator-Based Modelling and Control of High Power Induction Motor Using Novel Chaotic Gorilla Troop Optimizer
• 1 Introduction
• 2 Formulation of the Problem
• 3 New Chaotic Gorilla Troop Optimizer

• 4 Simulation Ouput and Their Analysis
• 5 Conclusions
• References
• An Enhanced Optimize Outlier Detection Using Different Machine Learning Classifier
• 1 Introduction
• 2 Outlier Detection
• 3 Literature Review
• 4 Proposed Methodology
• 5 Simulation Result
• 6 Conclusion
• References
• Prediction of Disease Diagnosis for Smart Healthcare Systems Using Machine Learning Algorithm
• 1 Introduction
• 2 Heart Disease
• 3 Diabetes Mellitus
• 4 Proposed Methodology
• 5 Simulation Results
• 6 Conclusion
• References

This book features research papers presented at the 1st International Conference on Innovations in Data Analytics (ICIDA 2022), held at Eminent College of Management and Technology (ECMT), West Bengal, India, during November 2930, 2022. The book presents original research work in the areas of computational intelligence, advance computing, network security and telecommunication, data science and data analytics, and pattern recognition. The book is beneficial for readers from both academia and industry. .

• Landmark identification from low-resolution real-time image pose estimation
• BLUEBOT A Bluetooth Controlled Robot for Deciding Human Intervention based on the Environment check
• Nirbhaya Naari: An Artificial Intelligence tool for detection of crime against Women
• A Clinical Decision Support System Using Machine Learning To Forecast The Risk Of Chronic Pulmonary Disease And Anthracosis
• Pre-Eclampsia Risk Factors Association with Cardiovascular Disease Prediction and Diagnosing Using Machine Learning
• A Low Resource Machine Learning Approach for Prediction of Dressler Syndrome
• Analysis of Twitter Data for Business Intelligence
• Detection and Classification of Cyber Threats in Tweets towards Prevention
• Artificial Neural Network Design for CMOS NAND Gate Using Sigmoid Function
• A Pioneer Image Steganography Method Using The SOD Algorithm.

The book constitutes proceedings of the International Conference on Intelligent Systems and Human-Machine Collaboration 2022. The papers consist of research from different domains of human-machine interaction, computer engineering like quantum computational intelligence, big data analytics, the Internet of things, etc. The book includes significant contributions from academia and industry dealing with human-machine interaction both from the theoretical development and the application point of view. It also brings out research articles in interdisciplinary platforms applying human-machine interaction. The book is useful to researchers and practitioners alike.

• Part 1: Healthcare Informatics.-
• Chapter 1. Earth Mover's Distance Based Automated Disease Tagging of Indian ECGs.-
• Chapter 2. Cardial Disease Prediction in Multi-variant Systems: A Short Survey.-
• Chapter 3. SVM-based pre-and post-treatment cancer segmentation from lung and abdominal CT images via neighbourhood-influenced features.-
• Chapter 4. Blood Cancer Detection with Microscopic Images using Machine Learning.-
• Chapter 5. A Survey on Leukemia Detection: A Machine Learning Approach.-
• Chapter 6. Periocular Region Recognition - A Brief Survey.-
• Chapter 7. A Bibliometric Analysis on the relationship between Emotional Intelligence, Self-Management and Health Information Seeking.-
• Chapter 8. Preferences in the Detailing Process Among Young and Senior Physicians.-
• Chapter 9. Perceptual Difference Patient & Physician on Negative Aspects of Social Media.-
• Chapter 10. AUTCD-Net: An Automated Framework for Efficient Covid-19 Diagnosis on Computed Tomography Scans.-
• Chapter 11. Computer aided detection of brain midline using CT images.-
• Chapter 12. Deep neural network based classification of ASD and neuro-typical subjects using functional connectivity features derived from resting state fMRI data.-
• Chapter 13. Application of Deep Learning in Healthcare.-
• Part 2: Recommendation Systems.-
• Chapter 14. A Popularity-based Recommendation System using Machine Learning.-
• Chapter 15. Machine Learning based Movies and Shows Recommendation System. etc.
• (source: Nielsen Book Data)

This book presents collection of research papers presented at International Conference on Information and Communication Technology (ICICT 2021) organized by Department of Information Technology, Sikkim Manipal Institute of Technology, Sikkim, India, during 23-24 December 2021. The book includes papers in the research area of communication networks, data science, healthcare informatics, bio-medical image processing, security of information including cryptography, machine learning applications, and AI applications.
(source: Nielsen Book Data)

• Chapter 1. Recent Trends in Electromyography Signal Processing of Neuromuscular Diseases: An Outlook.-
• Chapter 2. Conceptualization, Visualization and Modeling of Ontologies for Elementary Kinematics.-
• Chapter 3. A Deep Neural approach towards Staining and Tinting of Monochrome Images.-
• Chapter 4. Evaluation of IoT based Automatic Headlight Dimmer Systems.-
• Chapter 5. Enhanced Energy Efficient Fuzzy Logic Clustering and Network Coding Strategy for Wireless Sensor Networks (EEE-FL-NC).-
• Chapter 6. Malware Classification using Automated Transmutation and CNN.-
• Chapter 7. Content-Based Image Retrieval using Energy Based Frequency Domain Features.-
• Chapter 8. Decision Tree Based Event Detection Framework for UWSN Routing to Optimize Energy Consumption During Transmission.-
• Chapter 9. Recognizing Child Unsafe Apps through User Reviews on the Google Play store.-
• Chapter 10. Brain Tumor Classification Using Deep Learning and Big Data Analytics.-
• Chapter 11. Drone Stability Simulation Using Ros And Gazebo.-
• Chapter 12. Knowledge Management framework for the supervision of IT postgraduate research in Sri Lanka.-
• Chapter 13. RFM-based Customer Analysis and Product Recommendation System.-
• Chapter 14. Efficient Hardware Trojan Detection using Generic Feature Extraction and Weighted Ensemble Method.-
• Chapter 15. An Approach for Offline Handwritten Character Shape Reconstruction Using Active Contour and Morphological Techniques.
• (source: Nielsen Book Data)

This book gathers selected high-quality research papers presented at International Conference on Advanced Computing and Intelligent Technologies (ICACIT 2021) held at NCR New Delhi, India, during March 20-21, 2021, jointly organized by Galgotias University, India, and Department of Information Engineering and Mathematics Universita Di Siena, Italy. It discusses emerging topics pertaining to advanced computing, intelligent technologies, and networks including AI and machine learning, data mining, big data analytics, high-performance computing network performance analysis, Internet of things networks, wireless sensor networks, and others. The book offers a valuable asset for researchers from both academia and industries involved in advanced studies.
(source: Nielsen Book Data)

• Smart Drone Controller Framework - Towards an Internet of Drones.- Building of Efficient Communication System in Smart City using Wireless Sensor Network through Hybrid Optimization Technique.- Estimation of Range for Electric Vehicle Using Fuzzy Logic System.- Traffic Light Control using RFID and Deep Reinforcement Learning.- Driver Drowsiness Alert System using Real-Time Detection.- Image Processing Based Smart Traffic Control System for Smart City.- Visual Perception for Smart City Defense Administration and Intelligent Premonition Framework based on DNN.- Application of AI/IoT for Smart Renewable Energy Management in Smart Cities.- Eye-Gaze based Hands Free Access Control System for Smart City Public Interfaces.- Reliability Analysis in Cyber-Physical System Using Deep Learning for Smart Cities Industrial IoT Network Node.
• (source: Nielsen Book Data)

This book provides a valuable combination of relevant research works on developing smart city ecosystem from the artificial intelligence (AI) and Internet of things (IoT) perspective. The technical research works presented here are focused on a number of aspects of smart cities: smart mobility, smart living, smart environment, smart citizens, smart government, and smart waste management systems as well as related technologies and concepts. This edited book offers critical insight to the key underlying research themes within smart cities, highlighting the limitations of current developments and potential future directions.
(source: Nielsen Book Data)

• Archive System Using Big Data for Health care: Analysis, Architecture, and Implementation
• Data Science Team Roles and Need of Data Science: A Review of Different Cases
• Performance Analysis of Indian Stock Market via Sentiment Analysis and Historical Data
• D-Lotto: The Lottery DApp with Verifiable Randomness
• Review of Machine Learning and Data Mining Methods to Predict Different Cyberattacks
• Sentiment Analysis-An Evaluation of the Sentiment of the People: A Survey
• A Comprehensive Review on Content-Based Image Retrieval System: Features and Challenges
• A Comparative Study of Classification Techniques in Context of Microblogs Posted During Natural Disaster
• (Plus 52 other pages).

This book includes selected papers from the International Conference on Data Science and Intelligent Applications (ICDSIA 2020), hosted by Gandhinagar Institute of Technology (GIT), Gujarat, India, on January 24-25, 2020. The proceedings present original and high-quality contributions on theory and practice concerning emerging technologies in the areas of data science and intelligent applications. The conference provides a forum for researchers from academia and industry to present and share their ideas, views and results, while also helping them approach the challenges of technological advancements from different viewpoints. The contributions cover a broad range of topics, including: collective intelligence, intelligent systems, IoT, fuzzy systems, Bayesian networks, ant colony optimization, data privacy and security, data mining, data warehousing, big data analytics, cloud computing, natural language processing, swarm intelligence, speech processing, machine learning and deep learning, and intelligent applications and systems. Helping strengthen the links between academia and industry, the book offers a valuable resource for instructors, students, industry practitioners, engineers, managers, researchers, and scientists alike. .
(source: Nielsen Book Data)

• 1. An Introduction/ theoretical understanding to deep learning - challenges, feasibility in domains
• 2. Deep learning for big data
• 3. Deep learning in signal processing
• 4. Deep learning in image processing
• 5. Deep learning in video processing
• 6. Deep learning in audio/speech processing
• 7. Deep learning in data mining
• 8. Deep learning in healthcare
• 9. Deep learning in biomedical research
• 10. Deep learning in agriculture
• 11. Deep learning in environmental sciences
• 12. Deep learning in economics/e-commerce
• 13. Deep learning in forensics (biometrics recognition)
• 14. Deep learning in cybersecurity
• 15. Deep learning for smart cities, smart hospitals, and smart homes.
• (source: Nielsen Book Data)

Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models. Chapters elaborate on these models which have shown significant success in dealing with massive data for a large number of applications, given their capacity to extract complex hidden features and learn efficient representation in unsupervised settings. Chapters investigate deep learning-based algorithms in a variety of application, including biomedical and health informatics, computer vision, image processing, and more. In recent years, many powerful algorithms have been developed for matching patterns in data and making predictions about future events. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. Deep learning methods can deal with multiple levels of representation in which the system learns to abstract higher level representations of raw data. Earlier, it was a common requirement to have a domain expert to develop a specific model for each specific application, however, recent advancements in representation learning algorithms allow researchers across various subject domains to automatically learn the patterns and representation of the given data for the development of specific models.
(source: Nielsen Book Data)

• 1. An Introduction/ theoretical understanding to deep learning - challenges, feasibility in domains
• 2. Deep learning for big data
• 3. Deep learning in signal processing
• 4. Deep learning in image processing
• 5. Deep learning in video processing
• 6. Deep learning in audio/speech processing
• 7. Deep learning in data mining
• 8. Deep learning in healthcare
• 9. Deep learning in biomedical research
• 10. Deep learning in agriculture
• 11. Deep learning in environmental sciences
• 12. Deep learning in economics/e-commerce
• 13. Deep learning in forensics (biometrics recognition)
• 14. Deep learning in cybersecurity
• 15. Deep learning for smart cities, smart hospitals, and smart homes.
• (source: Nielsen Book Data)

Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models. Chapters elaborate on these models which have shown significant success in dealing with massive data for a large number of applications, given their capacity to extract complex hidden features and learn efficient representation in unsupervised settings. Chapters investigate deep learning-based algorithms in a variety of application, including biomedical and health informatics, computer vision, image processing, and more. In recent years, many powerful algorithms have been developed for matching patterns in data and making predictions about future events. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. Deep learning methods can deal with multiple levels of representation in which the system learns to abstract higher level representations of raw data. Earlier, it was a common requirement to have a domain expert to develop a specific model for each specific application, however, recent advancements in representation learning algorithms allow researchers across various subject domains to automatically learn the patterns and representation of the given data for the development of specific models.
(source: Nielsen Book Data)

• Introduction.- Introduction about Artificial Intelligence (AI) and Cloud, Fog and Edge Computing.- Internet of Things based Cloud Architecture and Its Applications.- Big Data Analytics of Internet of Things based Cloud Systems.- Machine and Deep Learning Techniques for Internet of Things based Cloud Systems.- Computer Vision: Visualizing the Smart Era with Artificial Intelligence.- Security, Privacy and Trust issues in AI Based Cloud and IoT based Cloud Systems.- AI for Smart data storage in Cloud-based Internet of Things.- Blockchain Based Solutions for AI Based Cloud and IoT based Cloud Systems.- Security and information assurance for Big Data.- Content delivery networks, or schemes using AI on stored at clouds.- Trustworthy Machine Learning for IoT-based Cloud systems.- Authentication and Control: Detecting Cyber Attacks on Cloud Using AI.- Security Management and Security Operations using Artificial Intelligence for Cloud.- Digital Trust and Reputation using Artificial Intelligence for Cloud.- Improving Information Security and Awareness in Society 5.0 and Industry 4.0 using AI.- Open Challenges and New Horizons for IoTs based Cloud Applications and AI based Cloud Applications.- Artificial Intelligence: Hope for future or Hype by Intellectuals.- Real World's Case Studies.- Conclusion.
• (source: Nielsen Book Data)

This book discusses the future possibilities of AI with cloud computing and edge computing. The main goal of this book is to conduct analyses, implementation and discussion of many tools (of artificial intelligence, machine learning and deep learning and cloud computing, fog computing, and edge computing including concepts of cyber security) for understanding integration of these technologies. With this book, readers can quickly get an overview of these emerging topics and get many ideas of the future of AI with cloud, edge, and in many other areas. Topics include machine and deep learning techniques for Internet of Things based cloud systems; security, privacy and trust issues in AI based cloud and IoT based cloud systems; AI for smart data storage in cloud-based IoT; blockchain based solutions for AI based cloud and IoT based cloud systems.This book is relevent to researchers, academics, students, and professionals.
(source: Nielsen Book Data)

The book features selected high-quality papers presented in International Conference on Computing, Power and Communication Technologies 2019 (GUCON 2019), organized by Galgotias University, India, in September 2019. Discussing in detail topics related to electronics devices, circuits and systems; signal processing; and bioinformatics, multimedia and machine learning, the papers in this book provide interesting reading for researchers, engineers, and students.