Note: Intro -- Preface -- Contents -- Part IIntelligent Systems and Informatics (I) -- 1 Automatic Rules Generation Approach for Data Cleaning in Medical Applications -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Data Quality in Medical Applications -- 4 Proposed Approach -- 5 Experimental Study -- 5.1 Experimental Setting -- 5.2 Experimental Results -- 6 Conclusions -- References -- 2 Action Classification Using Weighted Directional Wavelet LBP Histograms -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Proposed Action Representation and Description -- 3.1 Weighted Directional Wavelet Local Binary Pattern Histogram -- 3.2 Global Description Using Invariant Moments -- 4 Experimental Results -- 4.1 Human Action Dataset -- 4.2 Experiments and Results -- 5 Conclusions -- References -- 3 Markerless Tracking for Augmented Reality Using Different Classifiers -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Theoretical Background -- 4 Methodology -- 4.1 Camera Calibration -- 4.2 Camera Pose Estimation -- 4.3 System Framework -- 4.4 Implementation Details -- 5 Experimental Results -- 6 Conclusion -- References -- 4 An Experimental Comparison Between Seven Classification Algorithms for Activity Recognition -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Classification Methods -- 3.1 Naïve Bayes Classification -- 3.2 K-Nearest Neighbor Classification -- 3.3 Neural Network -- 3.4 Support Vector Machine -- 3.5 Dynamic Time Warping -- 3.6 1 Gesture Recognition -- 3.7 D1 Recognition -- 4 Experimental Methodology and Results -- 5 Discussion and Conclusion -- References -- Machine Learning Based Classification Approach for Predicting Students Performance in Blended Learning -- 1 Introduction -- 2 Core Concepts -- 2.1 Support Vector Machines (SVMs) -- 2.2 Random Forests (RF) -- 3 The Proposed Classification System -- 3.1 Pre-processing Phase. , 3.2 Feature Extraction Phase -- 3.3 Classification Phase -- 4 Experimental Results -- 5 Conclusions and Future Work -- References -- 6 Detection of Dead Stained Microscopic Cells Based on Color Intensity and Contrast -- Abstract -- 1 Introduction -- 2 Literature Survey -- 3 Proposed System -- 4 Result and Discussion -- 5 Conclusion -- Acknowledgment -- References -- Digital Opportunities for 1st Year University Students' Educational Support and Motivational Enhancement -- 1 Introduction -- 2 Testbed -- 3 Getting of the Raw Data -- 4 Results of Feedback -- 5 Numerical Results of Student Activities -- 6 Conclusions -- References -- 8 Building Numbers with Rods: Lesson Plans with Cuisenaire Method -- Abstract -- 1 Introduction -- 2 Lesson Plans -- 2.1 Worksheet 1 -- 2.2 Worksheet 2 -- 3 Application in the Field of ICT -- 4 Conclusion -- References -- Part IIMultimedia Computingand Social Networks -- Telepresence Robot Using Microsoft Kinect Sensor and Video Glasses -- 1 Introduction -- 2 The Proposed System -- 2.1 Human--Robot Interaction Using Microsoft Kinect Sensor -- 2.2 Compositing User's Video and Robot Scene's Video -- 2.3 Telepresence Using Video Glasses -- 3 Experiment Results -- 4 Conclusions -- References -- Video Flash Matting: Video Foreground Object Extraction Using an Intermittent Flash -- 1 Introduction -- 2 Video Flash Matting -- 3 Experiments and Discussions -- 4 Conclusions and Future Work -- References -- Enhanced Region Growing Segmentation for CT Liver Images -- 1 Introduction -- 2 Morphological Operations -- 3 Filtering Techniques: Preliminaries -- 4 Region Growing Segmentation -- 5 CT Liver Segmentation Proposed Approach -- 5.1 Preprocessing Phase: Applying Filters and Ribs Boundary Detection -- 5.2 Region Growing Phase -- 6 Experimental Results and Discussion -- 7 Conclusion and Future Work -- References. , A Multi-Objective Genetic Algorithm for Community Detection in Multidimensional Social Network -- 1 Introduction -- 2 Related Work -- 3 Community Detection in M-D Networks Problem -- 4 Algorithm Description -- 5 Experimental Results -- 5.1 Synthetic Network Dataset -- 5.2 Real World Social Network Data -- 5.3 Further Analysis -- 6 Conclusion and Future Work -- References -- 13 Creativity in the Era of Social Networking: A Case Study at Tertiary Education in the Greek Context -- Abstract -- 1 Introduction -- 2 Literature Review on Creativity and Social Network Tools -- 3 Research Methodology -- 4 Data Analysis and Discussion -- 5 Conclusions -- References -- OCR System for Poor Quality Images Using Chain-Code Representation -- 1 Introduction -- 2 The Proposed System -- 2.1 Characters Extraction -- 2.2 Characters Recognition -- 2.3 Estimated Text Correction -- 3 Experiment Results -- 3.1 Datasets -- 3.2 Results of Chain-Code Representation -- 3.3 Results of the Proposed System -- 4 Conclusions -- References -- Human Thermal Face Extraction Based on SuperPixel Technique -- 1 Introduction -- 2 Theoretical Background -- 2.1 Quick-Shift Method -- 2.2 Otsu's Thresholding Method -- 3 Proposed Thermal Face Extraction Model -- 4 Experimental Results and Discussion -- 5 Conclusion -- References -- Unsupervised Brain MRI Tumor Segmentation with Deformation-Based Feature -- 1 Background -- 2 Methods -- 2.1 Segmentation of Lateral Ventricles -- 2.2 3-Dimensional Alignment -- 2.3 Transforming Lateral Ventricular Deformation to Feature -- 3 Experiments -- 3.1 Experimental Settings and Evaluation Methods -- 3.2 Results and Discussion -- 4 Conclusion -- References -- Face Sketch Synthesis and Recognition Based on Linear Regression Transformation and Multi-Classifier Technique -- 1 Introduction -- 2 Preliminaries -- 2.1 Gabor Features. , 2.2 Linear Discriminant Analysis (LDA) -- 2.3 Classifier Fusion -- 3 Proposed Model -- 3.1 Photo to Sketch Transformation -- 3.2 Training Phase -- 3.3 Testing Phase -- 4 Experimental Results and Discussion -- 4.1 Experimental Setup -- 4.2 First Experiment (Photo to Pseudo-Sketch Transformation) -- 4.3 Second Experiment (Face Sketch Recognition) -- 4.4 Discussion -- 5 Conclusions and Future Work -- References -- Part IIISwarms Optimization and Applications -- A New Learning Strategy for Complex-Valued Neural Networks Using Particle Swarm Optimization -- 1 Introduction -- 2 Complex-Valued Neural Networks -- 3 Particle Swarm Optimization -- 4 Problem Formulation -- 5 Data Description and Processing -- 6 Experimental Results -- 7 Conclusions -- References -- A XOR-Based ABC Algorithm for Solving Set Covering Problems -- 1 Introduction -- 2 Problem Description -- 3 Artificial Bee Colony Algorithm -- 4 Improving Solution Quality and Solving Speed -- 5 Experiments and Results -- 6 Conclusions -- References -- 20 Abdominal CT Liver Parenchyma Segmentation Based on Particle Swarm Optimization -- Abstract -- 1 Introduction -- 2 Preliminaries -- 3 The Proposed Segmentation Approach -- 3.1 Preprocessing Phase -- 3.2 CT Image Clustering Based on PSO Phase -- 3.3 Post-Processing Phase: Morphological Operators -- 3.4 Region of Interest Extraction Phase -- 3.5 Evaluation Phase -- 4 Experimental Results and Discussion -- 5 Conclusion and Future Works -- References -- Grey Wolf Optimizer and Case-Based Reasoning Model for Water Quality Assessment -- 1 Introduction -- 2 The Proposed GWO-CBR Hybrid Classification Model -- 2.1 Case Representation Phase -- 2.2 Retrieve Phase -- 2.3 Reuse/Adapt Phase -- 2.4 Revise Phase -- 2.5 Retrain Phase -- 3 Experimental Analysis and Discussion -- 4 Conclusions and Future Work -- References. , New Rough Set Attribute Reduction Algorithm Based on Grey Wolf Optimization -- 1 Introduction -- 2 Preliminaries -- 2.1 Rough Set Theory -- 2.2 Grey Wolf Optimization -- 3 Rough Set Based on Gray Wolf for Attribute Reduction (GWORSAR) -- 4 Experimental Results and Discussions -- 5 Conclusion -- References -- Solving Manufacturing Cell Design Problems Using a Shuffled Frog Leaping Algorithm -- 1 Introduction -- 2 Related Work -- 3 Manufacturing Cell Design Problem -- 3.1 Similarity Matrices -- 4 Shuffled Frog Leaping Algorithm -- 4.1 Discretization of Decision Variables -- 5 Experimental Result -- 6 Conclusion and Future Work -- References -- A Hybrid Bat-Regularized Kaczmarz Algorithm to Solve Ill-Posed Geomagnetic Inverse Problem -- 1 Introduction -- 2 The Proposed Regularized Kaczmarz Model -- 3 Experimental Results and Discussion -- 4 Conclusion and Future Work -- References -- A Fish Detection Approach Based on BAT Algorithm -- 1 Introduction -- 2 The Bat Algorithm: An Overview -- 3 The Proposed Approach -- 4 Experimental Results and Discussion -- 5 Conclusions and Future Directions -- References -- Part IVHybrid Intelligent Systems -- Hybrid Differential Evolution and Simulated Annealing Algorithm for Minimizing Molecular Potential Energy Function -- 1 Introduction -- 2 The Problem of Minimizing Molecular Potential Energy Function -- 3 Hybrid Differential Evolution Algorithm for Minimizing Molecular Potential Energy Function -- 3.1 The Proposed HDESA Algorithm -- 4 Numerical Experiments -- 4.1 Parameter Setting -- 4.2 The General Performance of the Proposed HDESA with the Minimization of Molecular Potential Energy Function Problem -- 4.3 Comparison Between the Proposed HDESA Algorithm and Other Algorithms -- 5 Conclusion -- References -- A Hybrid Classification Model for EMG Signals Using Grey Wolf Optimizer and SVMs -- 1 Introduction. , 2 Related Work.

Note: Intro -- Preface -- Contents -- Sentiment Analysis -- 1 Using Deep Neural Networks for Extracting Sentiment Targets in Arabic Tweets -- Abstract -- 1 Introduction -- 2 Background -- 3 Data Collection and Annotation -- 4 Building Word Embeddings -- 5 The Implemented Models -- 5.1 The Baseline Model -- 5.2 The Deep Neural Network Model -- 5.2.1 Bidirectional Long Short-Term Memory Networks (BI-LSTMs) -- 5.2.2 The Conditional Random Fields (CRF) Tagging Model -- 5.2.3 BI-LSTM-CRF -- 6 Performance Evaluation -- 7 Conclusion -- Acknowledgements -- References -- 2 Evaluation and Enrichment of Arabic Sentiment Analysis -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Challenges Arabic Sentiment Analysis -- 3.1 Encoding -- 3.2 Sentiment Analysis Impacted Due to Unavailability of Punctuations -- 3.3 Excess Resources Required -- 3.4 Sarcastic Tamper -- 3.5 One Word Represents Two Polarities -- 3.6 Indifferent Writing Style -- 3.7 Free Writing Style -- 3.8 Word Short Forms -- 3.9 Same Word Usage for Both Polarities -- 4 Data Collection -- 5 Implementation of Arabic Sentiment Analysis -- 6 Evaluation and Results -- 7 Conclusion -- References -- 3 Hotel Arabic-Reviews Dataset Construction for Sentiment Analysis Applications -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Arabic Sentiment Analysis -- 4 Hotel Arabic Reviews Dataset (HARD) -- 4.1 Collection -- 4.2 Properties -- 5 Sentiment Analysis -- 5.1 Text Pre-processing -- 5.2 Feature Extraction -- 5.3 Classifiers -- 6 Experimental Results -- 6.1 Bag of Words -- 6.2 Lexicon-Based Classification -- 7 Conclusions -- References -- 4 Using Twitter to Monitor Political Sentiment for Arabic Slang -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Corpus Collection and Preparation -- 3.2 Pre-processing -- 3.3 Text Classification -- 4 Results and Evaluation. , 5 Conclusion and Future Work -- References -- Estimating Time to Event of Future Events Based on Linguistic Cues on Twitter -- 1 Introduction -- 2 Related Research -- 3 Time-to-Event Estimation Method -- 4 Experimental Set-Up -- 4.1 Data Sets -- 4.2 Features -- 4.3 Training and Test Regimes -- 4.4 Evaluation and Baselines -- 4.5 Hyperparameter Optimization -- 5 Test Results -- 6 Discussion -- 7 Conclusions and Future Work -- References -- Machine Translation -- Automatic Machine Translation for Arabic Tweets -- 1 Introduction -- 2 Arabic Language Challenges Within NLP and Social Media -- 2.1 Modern Standard Arabic Challenges for MT -- 2.2 Arabic Language in Microblogs -- 3 Overview of Statistical Machine Translation -- 3.1 Language Model -- 3.2 Word Alignment -- 3.3 Translation Model -- 3.4 Decoding -- 4 Translating Arabic Tweets -- 4.1 Data Collection -- 4.2 Data Collection -- 4.3 Experiments -- 4.4 Results -- 4.5 Discussion -- 5 Conclusion and Future Work -- References -- Developing a Transfer-Based System for Arabic Dialects Translation -- 1 Introduction -- 2 Related Studies -- 3 Arabic Language Variation -- 4 Machine Translation Paradigms -- 4.1 Rule Based MT -- 4.2 Statistical MT -- 4.3 Hybrid MT -- 5 (ALMoFseH) Arabic Dialects Machine Translation -- 6 Methodology -- 6.1 Building a Lexical Database -- 6.2 The Transfer System -- 6.3 Naive Bayesian Classifier (NB) -- 6.4 Rewrite Rules for Dialectal Normalization -- 6.5 Functional Model -- 7 Evaluation of the System -- 8 Results -- 9 Conclusion -- References -- 8 The Key Challenges for Arabic Machine Translation -- Abstract -- 1 Introduction -- 2 Challenges for Arabic Translation -- 2.1 Classical Arabic -- 2.2 Modern Standard Arabic -- 2.3 Dialect Arabic -- 3 Machine Translation in Natural Language Processing -- 3.1 Metaphor Translation -- 3.2 Metaphor in Holy Quran. , 3.3 Metaphor in Modern Standard Arabic -- 3.4 Metaphor in Dialect Arabic -- 4 Named Entity Recognition Translation -- 5 Word Sense Disambiguation Translation -- 6 Conclusion -- References -- Information Extraction -- Graph-Based Keyword Extraction -- 1 Introduction -- 2 Related Work -- 3 Research Methodology -- 3.1 Overview -- 3.2 The Proposed Methodology -- 3.3 Dataset -- 3.4 Data Processing -- 3.5 Learn Classifier and TF/IDF -- 3.6 Performance Evaluation -- 4 Discussion -- 5 Conclusion and Future Prospects -- References -- 10 CasANER: Arabic Named Entity Recognition Tool -- Abstract -- 1 Introduction -- 2 State of the Art on NER Systems -- 2.1 Previous NE Categorization -- 2.2 NER Approaches and Systems -- 3 ANE Identification and Categorization -- 3.1 Identification of the ANE Forms and Categories -- 3.2 Relationship Between ANEs -- 4 Proposed Method -- 4.1 Analysis Transducer Establishment -- 4.2 Synthesis Transducer Establishment -- 5 Implementation and Evaluation -- 6 Conclusion -- References -- 11 Semantic Relations Extraction and Ontology Learning from Arabic Texts-A Survey -- Abstract -- 1 Introduction -- 2 Arabic Semantic Relation Extraction and Ontology Learning -- 3 Arabic Semantic Relation Extraction -- 3.1 Semantic Relation Extraction Between Arabic Named Entities -- 3.1.1 Rule-Based Approach -- 3.1.2 Machine Learning Approach -- 3.1.3 Hybrid Approach -- 3.2 Semantic Relation Extraction Between Arabic Ontological Concepts -- 4 Arabic Ontology Learning -- 4.1 Upper Ontology -- 4.1.1 Arabic WordNet Ontology -- 4.1.2 Formal Arabic Ontology -- 4.2 Domain Ontology -- 4.2.1 General Domains -- Manual Approach -- Statistical Approach -- Linguistic Approach -- Hybrid Approach -- Uncategorized -- 4.2.2 Islamic Domain -- Quran Ontology -- Hadith Ontology -- 5 Conclusion -- Information Retrieval and Question Answering. , 12 A New Semantic Distance Measure for the VSM-Based Information Retrieval Systems -- Abstract -- 1 Introduction -- 2 The Proposed Approach -- 2.1 A Novel Indexing Approach -- 2.2 The Significance Level of a Concept (SLC) -- 2.3 Semantic Distance Between Query and CS -- 3 System Architecture -- 4 Experimental Analysis -- 4.1 Experimental Setup -- 4.2 Experiments, Results, and Evaluation -- 4.2.1 The Conceptualization Levels -- 4.2.2 The Retrieval Capability -- 4.2.3 The Ranking Accuracy -- 5 Conclusion and Future Work -- Appendix: The Implementation Algorithms -- References -- An Empirical Study of Documents Information Retrieval Using DWT -- 1 Introduction -- 2 Background -- 2.1 Term Signal -- 2.2 Weighting Scheme -- 2.3 Document Segmentation -- 2.4 Wavelet Transform Algorithm -- 3 Design Issues and Implementation of Information Retrieval Using DWT -- 3.1 Problems and Design Issues -- 3.2 Implementation of the Suggested Model -- 3.3 Document Segmentation -- 3.4 Term Weighting -- 4 Experiments and Results -- 5 Conclusion -- References -- 14 A Review of the State of the Art in Hindi Question Answering Systems -- Abstract -- 1 Introduction -- 2 A Typical Pipeline Architecture of a Question Answering System -- 2.1 Question Processing -- 2.1.1 Question Classification -- 2.2 Answer Type Determination -- 2.3 Keyword Extraction -- 2.4 Query Expansion -- 2.5 Document Processing -- 2.5.1 Passage Retrieval -- 2.6 Answer Extraction -- 2.6.1 Named Entity Recognition -- 2.6.2 Answer Scoring and Ranking -- 2.6.3 Answer Presentation -- 3 Developments in Hindi Question Answering System -- 3.1 Developments in Tasks of Question Answering Systems -- 4 Introduction to Hindi Language and Its Challenges for QASs -- 5 Tools and Resources for Hindi Question Answering -- 6 Future Scopes -- References -- Text Classification. , 15 Machine Learning Implementations in Arabic Text Classification -- Abstract -- 1 Introduction -- 2 Problem Definition -- 2.1 Problem Scope, Input and Output -- 2.2 Problem Formalization -- 3 Text Classification Steps -- 3.1 Data Selection and Preparation -- 3.2 Text Preprocessing -- 3.3 Document Indexing and Term Weighting Methods -- 3.4 Feature Reduction -- 4 Classification Algorithms -- 5 Arabic Text Classification -- 6 Directions for Further Research -- 7 Conclusion -- References -- Authorship and Time Attribution of Arabic Texts Using JGAAP -- 1 Introduction -- 2 Background -- 2.1 Authorship Attribution and NLP -- 2.2 Authorship Attribution in Arabic -- 3 Data -- 3.1 Corpus Description -- 3.2 Selection of Texts -- 4 Methods -- 4.1 JGAAP -- 4.2 Canonicizers -- 4.3 Event Drivers -- 4.4 Analysis Methods -- 5 Results -- 5.1 Character n-grams -- 5.2 Word n-grams -- 5.3 Word Length -- 5.4 Rare Words -- 5.5 Most Common Words -- 6 Analysis of Errors -- 7 Future Work and Conclusions -- References -- 17 Automatic Text Classification Using Neural Network and Statistical Approaches -- Abstract -- 1 Reviewing the Previous Work -- 2 Preprocessing Procedures for the Two Proposed Classifiers -- 2.1 Word Extraction -- 2.2 Stop Words Removal -- 2.3 Word Stemming -- 2.4 Improvements -- 2.5 Reuters 21,758 Test Collection for Text Categorization -- 2.6 Term Weighting Techniques -- 3 The Proposed Statistical Classifier -- 3.1 Converting the Text Documents into a Database -- 3.2 The Resulting Database Model -- 3.3 Weighting Techniques -- 3.4 Improvements for Weighting -- 3.5 Experimental Details -- 4 Neural Network Based Classifier -- 4.1 Dimensionality Reduction for Text Categorization -- 4.2 The Proposed Neural Network Based Text Classifier -- 4.3 Experimental Details -- 5 Comparison Between Proposed Statistical Classifier and the Neural Network Based Classifier. , 6 Conclusions.

Note: Intro -- Preface -- Contents -- About the Editors -- The Swarm Is More Than the Sum of Its Drones -- 1 Introduction -- 1.1 From Drones to Swarms -- 1.2 The Challenge of Deploying a Swarm Indoors -- 1.3 Contributions of This Chapter -- 1.4 Situating the Chapter in the Context of the Literature -- 1.5 The Intended Audience for this Chapter -- 2 Background -- 2.1 An Internet of Drones -- 2.2 Application Areas for Drones, and Swarms of Drones -- 2.3 Swarming Behaviour in Natural Sciences -- 2.4 Summary -- 3 Modelling Indoor WSN Deployment -- 3.1 The Model for the Drones -- 3.2 The Model for the Application -- 3.3 The Model for the Scenario/Environments -- 3.4 Performance Measures -- 3.5 Defining Characteristics of the Approach -- 4 A Decentralised and Self-organising Approach -- 4.1 Inspiration from Nature -- 4.2 A Voronoi Tessellation-Based Approach -- 4.3 Defining Characteristics -- 4.4 The BISON Algorithm Family -- 4.5 Materials and Methods -- 4.6 Results and Discussion -- 5 The World Is a Messy Place (Full of Uncertainty and Noise) -- 5.1 The Impact of Noise -- 5.2 Materials and Methods -- 5.3 Results and Discussion -- 6 Swarm Behaviour: Drift and Diffusion -- 6.1 Measuring Group Behaviour in Biology: Drift and Diffusion -- 6.2 Materials and Methods -- 6.3 Results and Discussion -- 7 Conclusion -- 7.1 Towards an InterNET of Drones: Swarming Behaviour -- 7.2 A Word of Caution -- 8 Abbreviations and Notations -- References -- Underwater Drones for Acoustic Sensor Network -- 1 Introduction -- 2 Dynamics of Drone Modeling -- 3 Underwater Acoustic Architecture -- 3.1 Static Two-Dimensional UW-ANs -- 3.2 Static Three-Dimensional UW-ANs -- 3.3 Three-Dimensional Hybrid UW-ANs -- 4 Control and Navigation of Drone Vehicle -- 4.1 Control Law Subsystem -- 4.2 Control Allocation Subsystem -- 4.3 Navigation of AUV's -- 5 Design Issues of Acoustic Drones. , 6 Underwater Network Challenges -- 7 Emerging Applications of Underwater Drones -- 8 Conclusion and Discussion -- References -- Smart Agriculture Using IoD: Insights, Trends and Road Ahead -- 1 Introduction -- 2 Remote Sensing and Digital Image Processing for Environment Monitoring by Drones -- 2.1 Remote Sensing -- 2.2 Remote Sensing Platforms in Agriculture -- 2.3 Digital Image Processing -- 3 Drone Technology and Developments -- 3.1 Drone Systems -- 3.2 Components of an Agricultural Internet of Drone -- 3.3 Imaging Cameras Used by Agricultural Drones -- 4 Applications of Drones in Agriculture -- 4.1 Soil Properties Analysis -- 4.2 Planting and Weed Control -- 4.3 Crop Spraying -- 4.4 Crop Monitoring -- 4.5 Irrigation -- 4.6 Health Assessment -- 5 Case Study -- 6 Challenges in IoD -- 7 Conclusion -- 8 Future Work -- References -- Towards a Smarter Surveillance Solution: The Convergence of Smart City and Energy Efficient Unmanned Aerial Vehicle Technologies -- 1 Introduction -- 2 Related Work -- 2.1 Smart City and Challenges in Surveillance Use Case -- 2.2 Unmanned Aerial Vehicles -- 2.3 Internet of Drones -- 2.4 Energy Conservation in Drones -- 3 Energy Management Proposed Framework for UAVs -- 3.1 Tilt-Rotor Drone-Based Energy Conservation Framework for UAVs in Smart City Surveillance -- 4 Case Study on IoD Based Surveillance -- 4.1 Case Study on Singapore: An Energy-Efficient Smart City -- 4.2 Case Study on India: Smart City Surveillance in India -- 5 Potential Implications and Suggestion for Future Research in Smart City Surveillance -- 6 Conclusion -- References -- Efficient Design of Airfoil Employing XFLR for Smooth Aerodynamics of Drone -- 1 Introduction -- 1.1 Airfoil: Heart of Aircraft -- 2 Motivation -- 3 Science-Behind Drone Flight -- 4 Understanding the Heart of Aircraft-Airfoil -- 5 Results -- 6 Future Scope -- 7 Conclusion. , References -- Drone-Based Monitoring and Redirecting System -- 1 Introduction -- 2 Related Work -- 3 Case Studies -- 4 Conclusion -- References -- Drone Application in Smart Cities: The General Overview of Security Vulnerabilities and Countermeasures for Data Communication -- 1 Introduction -- 2 Background -- 2.1 Smart City -- 2.2 Drones -- 2.3 Challenges for Drones in Smart Cities -- 2.4 Data Communication Methods -- 3 Cybersecurity -- 3.1 Threats and Attacks -- 4 Security Countermeasures -- 4.1 Detection Measures -- 4.2 Defense Mechanisms -- 5 Conclusion -- References -- Cloud-Based Drone Management System in Smart Cities -- 1 Introduction -- 2 Related Works -- 3 Cloud-Based Drone Management System -- 3.1 Physical Layer -- 3.2 Cloud Layer -- 3.3 Control Layer -- 4 Components of Drone -- 4.1 Software -- 4.2 Hardware -- 4.3 Communication Method -- 5 Experimental Study and Evaluation -- 5.1 Experimental Setup -- 5.2 Experimental Results -- 5.3 Discussion and Future Research Directions -- 6 Conclusion -- References -- Smart Agriculture: IoD Based Disease Diagnosis Using WPCA and ANN -- 1 Introduction -- 2 Literature Review -- 3 Proposed System Design -- 3.1 The IoD Based System Architecture -- 4 Result and Discussion -- 5 Performance Analysis -- 6 Conclusion -- References -- DroneMap: An IoT Network Security in Internet of Drones -- 1 Introduction -- 2 Overview of IoD and UAV -- 2.1 Layers of UAV Drone -- 2.2 UAV Sensor Technologies in 5G Networks -- 3 Security Threats and Attacks of IoDT (Internet of Drones Things) -- 4 Security Issues Associated by IoD -- 5 Evaluation of IoD Control Sensors -- 6 Conclusions -- References.

Note: Intro -- Preface -- Contents -- Contributors -- Forensic Analysis in Cloud Computing -- 1 Cloud Computing Forensic Analysis: Trends and Challenges -- Abstract -- 1 Introduction -- 2 Cloud Computing Environment -- 2.1 The Cloud Models -- 2.2 The Cloud Structure and Services -- 3 Digital Forensics -- 3.1 Digital Forensics Common Phases -- 3.1.1 Identification -- 3.1.2 Acquisition and Preservation -- 3.1.3 Analysis -- 3.1.4 Presentation -- 3.2 Digital Evidence -- 3.3 Digital Forensic Analysis -- 4 Forensic Analysis in the Cloud Environment -- 4.1 Isolation of Crime Scene in Cloud -- 4.2 Pros and Cons of Forensic Analysis in Cloud -- 4.3 Challenges of Analysis and Examination -- 4.4 Conclusions and Open Research Issues -- References -- Data Storage Security Service in Cloud Computing: Challenges and Solutions -- 1 Introduction -- 2 Data Storage Auditing Methods -- 2.1 Public Auditing Versus Private Auditing -- 2.2 Auditing Single-Copy Versus Multiple-Copy Data -- 2.3 Static Versus Dynamic Data Auditing -- 3 Access Control Methods -- 3.1 Traditional Encryption -- 3.2 Broadcast Encryption -- 3.3 Identity-Based Encryption -- 3.4 Hierarchical Identity-Based Encryption -- 3.5 Attribute-Based Encryption -- 3.6 Hierarchical Attribute-Based Encryption -- 3.7 Role-Based Access Control -- 4 Comparative Analysis of Security Methods on Cloud Data Storage -- 4.1 Performance Analysis of Data Storage Auditing Methods -- 4.2 Performance Analysis of Access Control Methods -- 5 Discussions and Concluding Remarks -- 6 Conclusion -- References -- Homomorphic Cryptosystems for Securing Data in Public Cloud Computing -- 1 Introduction -- 2 Cloud Computing -- 3 Security Issues in Cloud Computing -- 4 Why Homomorphic Encryption (HE)? -- 5 Homomorphic Encryption (HE) -- 6 Different Encryption Cryptosystem -- 6.1 Somewhat Homomorphic Encryption (SHE). , 6.2 Fully Homomorphic Encryption (FHE) -- 7 Result and Discussion -- 8 Conclusion -- References -- 4 An Enhanced Cloud Based View Materialization Approach for Peer-to-Peer Architecture -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Solutions and Recommendations -- 4 The Experimental Results -- 5 Future Research Directions -- 6 Conclusion -- Appendix -- References -- 5 Distributed Database System (DSS) Design Over a Cloud Environment -- Abstract -- 1 Introduction -- 2 Background -- 3 Research Issues -- 4 Solutions and Recommendations -- 4.1 Application Client Layer -- 4.2 Distributed Database System Manager Layer -- 4.3 Distributed Database Clusters Layer -- 5 Enhanced Allocation and Replication Technique -- 6 Experimental Results -- 7 Clustering Distributed Database Sites -- 7.1 Clustering Distributed Database Sites Based on Region Fields -- 7.2 Clustering Distributed Database Sites Based on Communication Costs Between Network Sites -- 8 Future Research Directions -- 9 Conclusions -- References -- Additional Reading -- 6 A New Stemming Algorithm for Efficient Information Retrieval Systems and Web Search Engines -- Abstract -- 1 Introduction -- 2 Background -- 3 The System Methodology -- 3.1 The System Architecture -- 3.2 The Enhance Porter Stemming Algorithm (EPSA) -- 3.3 The Ranking Algorithm -- 4 Performance Studies -- 4.1 Evaluation of the EPSA Algorithm -- 4.2 Experimental Results -- 5 Conclusion -- References -- Forensics Multimedia and Watermarking Techniques -- 7 Face Recognition via Taxonomy of Illumination Normalization -- Abstract -- 1 Introduction -- 2 Illumination Normalization Face Recognition -- 2.1 Illumination Normalization -- 2.1.1 Wavelet-Based (WA) -- 2.1.2 Steerable Filtering-Based -- 2.1.3 Non-local Means Based -- 2.1.4 Adoptive Non-local Mean -- 2.2 Illumination Modeling -- 2.2.1 Single Scale Retinex (SSR). , 2.2.2 Multi Scale Retinex (MSR) -- 2.2.3 Adaptive Single Scale Retinex (ASR) -- 2.3 Illumination Invariant Feature Extraction -- 2.3.1 Homomorphic Filtering-Based Normalization (HOMO) -- 2.3.2 Discrete Cosine Transformation (DCT) -- 2.3.3 Isotropic Diffusion-Based Normalization -- 2.3.4 Modified Anisotropic Diffusion (MAD) -- 2.3.5 Difference of Gaussian (DoG) -- 3 Current Trends -- 4 Comparisons -- 5 Discussion -- 6 Conclusion -- References -- 8 Detecting Significant Changes in Image Sequences -- Abstract -- 1 Introduction -- 2 Background Feature Analysis -- 3 Problem Statement and Legacy Techniques for Solution -- 4 Image Content Interpretation and Comparison -- 4.1 Construction of Voronoi Diagrams on Salient Image Points -- 4.2 Similarity Metrics for Voronoi Diagram Comparison -- 4.3 Procedure of Image Change Detection -- 5 Test Collections, Processing Evaluation and Development Trends -- 6 Conclusion -- References -- 9 VW16E: A Robust Video Watermarking Technique Using Simulated Blocks -- Abstract -- 1 Introduction -- 2 Block Simulation -- 3 Test the Imperceptibility -- 3.1 Test Results of VW16E Technique for the Video Sample 1 -- 3.2 Test Results of VW16E Technique for the Video Sample 2 -- 3.3 Test Results of VW16E Technique for the Video Sample 3 -- 3.4 Test Results of VW16E Technique for the Video Sample 4 -- 3.5 Test Results of VW16E Technique for the Video Sample 5 -- 3.6 Test Results of VW16E Technique for the Video Sample 6 -- 3.7 Test Results of VW16E Technique for the Video Sample 7 -- 3.8 Test Results of VW16E Technique for the Video Sample 8 -- 3.9 Test Results of VW16E Technique for the Video Sample 9 -- 3.10 Test Results of VW16E Technique for the Video Sample 10 -- 3.11 Test Results of VW16E Technique for the Video Sample 11 -- 3.12 Test Results of VW16E Technique for the Video Sample 12. , 3.13 Test Results of VW16E Technique for the Video Sample 13 -- 3.14 Test Results of VW16E Technique for the Video Sample 14 -- 4 Discussion and Analysis on Test and Evaluation -- 4.1 Attacks on Video Sample No 1 -- 4.1.1 Crop Attack on Video Sample No 1 -- 4.1.2 Frame Deletion Attack on Video Sample No 1 -- 4.1.3 Frame Exchange Attack on Video Sample No 1 -- 4.1.4 Frame Insert Attack on Video Sample No 1 -- 4.1.5 Rotate Attack on Video Sample No 1 -- 4.1.6 Reverse Rotate Attack on Video Sample No 1 -- 4.1.7 Salt and Pepper Attack on Video Sample No 1 -- 4.1.8 Shift Frames Attack on Video Sample No 1 -- 4.1.9 Superimpose Attack on Video Sample No 1 -- 5 Conclusion -- References -- 10 A Robust and Computationally Efficient Digital Watermarking Technique Using Inter Block Pixel Differencing -- Abstract -- 1 Introduction -- 2 Related Literature -- 3 Proposed Watermarking Algorithm -- 3.1 Block Pre-processing -- 3.2 Watermark Embedding -- 3.3 Watermark Extraction -- 4 Experimental Results and Discussions -- 4.1 Imperceptivity Analysis -- 4.2 Payload Analysis -- 4.3 Robustness Analysis -- 4.3.1 Salt and Pepper Noise -- 4.3.2 Addition of Gaussian Noise -- 4.3.3 Sharpening -- 4.3.4 Cropping -- 4.3.5 Rotation Attack -- 4.3.6 JPEG Compression -- 4.3.7 Rotation + Cropping -- 4.3.8 Salt and Pepper Noise + Gaussian Noise -- 4.3.9 Salt and Pepper Noise + Gaussian Noise + Sharpening -- 4.4 Computational Complexity Analysis -- 5 Conclusion -- Acknowledgments -- References -- 11 JPEG2000 Compatible Layered Block Cipher -- Abstract -- 1 Introduction -- 1.1 Background -- 2 Literature Review -- 2.1 Applications -- 2.2 Approaches -- 3 Proposed Approach -- 4 Performance Analysis -- 5 Discussion and Conclusions -- References -- Digital Forensic Applications -- 12 Data Streams Processing Techniques -- Abstract -- 1 Introduction -- 2 Background -- 2.1 Data Streams. , 2.2 Data Steams Processing -- 2.3 Sliding Windows -- 2.4 Continuous Query Optimization -- 3 Continuous Queries Processing -- 3.1 Continuous Queries Processing Based on Multiple Query Plans -- 3.2 Continuous Queries with Probabilistic Guarantees -- 3.3 Continuous Bounded Queries Processing -- 3.4 Continuous Queries Processing Over Sliding Window Join -- 3.5 Continuous Pattern Mining -- 3.6 Continuous Top-K Queries Processing -- 3.7 Continuous Nearest Neighbor Queries Processing -- 3.8 Continuous Queries Processing Based Tree Structure -- 3.9 Continuous Skyline Queries Processing -- 3.10 Multi Continuous Queries Processing -- 4 Data Streams Execution Environments -- 4.1 Parallel and Distributed Stream Processing -- 4.1.1 Data Streams Processing Based on Map Reduce Framework -- 4.1.2 Data Streams Processing Based on the Query Mega Graph (QMG) -- 4.1.3 Data Streams Processing Based on Task Graph Structure -- 4.1.4 Data Streams Processing in Traffic Distributed Networks -- 4.1.5 Controlling Streams Processing on Overload Conditions -- 4.2 Data Streams Processing Based on Cloud Environment -- 5 Research Issues -- 6 Solutions and Recommendations -- 7 Future Research Directions -- 8 Conclusion -- References -- Evidence Evaluation of Gait Biometrics for Forensic Investigation -- 1 Introduction -- 2 Gait Biometrics -- 2.1 Gait Datasets -- 2.2 Gait Recognition Methods -- 3 Gait Analysis for Forensics -- 3.1 Descriptive-Based Methods -- 3.2 Metric-Based Methods -- 4 Evidence Evaluation and Challenges -- 5 Conclusions -- References -- 14 Formal Acceptability of Digital Evidence -- Abstract -- 1 Introduction -- 2 Research Goals -- 2.1 Research methodology -- 3 Data Collection and Sample Characteristic -- 4 Research Results -- 5 Defining the Formal Acceptability of Digital Evidence -- 6 Implementing Rules Through DEMF -- 7 Conclusion -- References. , A Comprehensive Android Evidence Acquisition Framework.

Note: Intro -- Title Page -- Preface -- Organization -- Contents -- Invited Papers -- Sequence Package Analysis and Soft Computing: Introducing a New Hybrid Method to Adjust to the Fluid and Dynamic Nature of Human Speech -- Introduction -- A New Hybrid Method -- BNF (Backus-Naur Form) -- Domain-Independent -- Language-Independent -- Granularity -- Illustrations -- High Anger Level -- Moderate Anger Level -- Coda -- References -- Controller Tuning Using a Cauchy Mutated Artificial Bee Colony Algorithm -- Introduction -- Permanent Magnet Synchronous Motor -- Problem Formulation -- Artificial Bee Colony Algorithm -- Modified Artificial Bee Colony Algorithm -- Experimental Results -- Application to Parameter Estimation of PI Controller in PMSM Drive -- Conclusions -- References -- Image Analysis and Processing -- Automatic Detection of White Grapes in Natural Environment Using Image Processing -- Introduction -- DDR Unique Characteristics and Their Impact on the System -- The Grape Recognition System -- Results and Discussion -- Conclusions and OngoingWork -- References -- Securing Patients Medical Images and Authentication System Based on Public Key Infrastructure -- Introduction -- Securing Patients Medical Images and Authentication System -- The RSA Encryption/Decryption Algorithm -- DCT Embedding/Extracting Watermarked Algorithm -- Experimental Results and Performance Analysis -- Conclusions -- References -- Image Segmentation Using Ant System-Based Clustering Algorithm -- Introduction -- Related Work -- Ant System-Based Clustering Algorithm -- Pheromone Accumulation -- Local Pheromone Summing -- Data Labeling -- Experimental Results and Discussion -- Conclusions -- References -- Validation of a Hyperspectral Content-Based Information Retrieval (RS-CBIR) System Upon Scarce Data -- Introduction -- Hyperspectral CBIR System -- The DAMA Strategy. , RS-CBIR Validation -- CBIR Quality Assessment -- Proposed Validation Strategy -- Experiment and Results -- Conclusions -- References -- A Robust Algorithm for Enhancement of Remotely Sensed Images Based on Wavelet Transform -- Introduction -- Related Work -- Wavelet Transform -- Wavelet Shrinkage -- Wavelet-Based Denoising Algorithm -- Experiment -- Preprocessing -- Results and Discussion -- Conclusion and Future Work -- References -- ARIAS: Automated Retinal Image Analysis System -- Introduction -- AnOverview -- Automated Retinal Image Analysis System (ARIAS) -- Pre-processing Phase -- Segmentation Phase -- Vessel Tree Tracking Phase -- Identification Phase -- Experimental Results and Discussion -- Conclusions and Future Work -- References -- Contrast Enhancement of Breast MRI Images Based on Fuzzy Type-II -- Introduction -- An Overview -- MRI Breast Imaging Technology -- Fuzzy Image Processing -- Type-II Fuzzy Sets Enhancement Algorithm -- Experimental Results -- Conclusions -- References -- Intelligent Systems -- Tree Generation Methods Comparison in GAP Problems with Low Quality Data -- Introduction -- White Box Models SAP Learning with LQD -- Tree-Generation Algorithms -- Experimentation and Results -- Conclusions and Future Work -- References -- Neural-Network- Based Modeling of Electric Discharge Machining Process -- Introduction -- Artificial Neural Network -- Neural Network Modeling Considerations -- Network Architecture -- Learning Rate Coefficient -- Momentum Term -- Data Preprocessing -- Experiments -- Neural Network Training -- Results -- Conclusion -- References -- An Adaptive Sigmoidal Activation Function Cascading Neural Networks -- Introduction -- The Proposed Algorithm -- Network Growing Strategy and Adaptive Sigmoidal Activation Function -- Adaptive Sigmoidal Activation Function Cascading Neural Network -- Experimental Design. , Results and Discussions -- Conclusion -- References -- Loop Strategies and Application of Rough Set Theory in Robot Soccer Game -- Introduction -- Strategy Description -- Loop Strategy Detection -- Detection of Loop Strategies -- Conclusion -- References -- Learning Patterns from Data by an Evolutionary-Fuzzy Approach -- Introduction -- Genetic Programming for Classifier Evolution -- Fuzzy Classifier -- Experiments -- Conclusions -- References -- A Predictive Control System for Concrete Plants. Application of RBF Neural Networks for Reduce Dosing Inaccuracies -- Introduction -- System Description -- Application of RBF in Predicting Radial -- Results -- References -- Weighted Cross-Validation Evolving Artificial Neural Networks to Forecast Time Series -- Introduction -- Time Series Forecasting with Artificial Neural Networks (ANN) -- Automatic Design of Artificial Neural Networks (ADANN) -- Cross-Validation -- Ensembles -- Experiments and Results -- Conclusions -- References -- Multi-agents and Ambient Intelligence -- Role Playing Games and Emotions in Dispute Resolution Environments -- Introduction -- Ambient Intelligence and Online Dispute Resolution -- Intelligent Environments for Dispute Resolution -- Simulation of Users -- Simulation of Emotions -- Conclusion and Future Work -- References -- Image Processing to Detect and Classify Situations and States of Elderly People -- Introduction -- Detector Agent -- Preprocess, Extraction of Relevant Information -- Mixture of Classifiers, General Process -- Classifiers -- Relevant Factors -- Classification Model -- Results and Conclusions -- References -- Soft Computing Models for the Development of Commercial Conversational Agents -- Introduction -- Our Proposal to Introduce Soft Computing Models in Commercial Conversational Agents. , Soft Computing Approach Proposed for the Implementation of the Dialog Manager -- Development of a Railway Information System Using the Proposed Technique -- Evaluation of the Developed Conversational Agent -- Conclusions -- References -- Regulatory Model for AAL -- Introduction -- Legal Issues in Biometric Identification -- Principles of a Regulatory Model -- Regulatory Model for AAL Developments -- Conclusions -- References -- Classification and Clustering Methods -- Austenitic Stainless Steel EN 1.4404 Corrosion Detection Using Classification Techniques -- Introduction -- Methodology -- Experimental Procedure -- Results -- Conclusions -- References -- Prediction of Peak Concentrations of PM10 in the Area of Campo de Gibraltar (Spain) Using Classification Models -- Introduction -- The Study Area and the Data -- Methodology -- Experimental Procedure -- Results and Discussion -- Conclusions -- References -- A Rough Clustering Algorithm Based on Entropy Information -- Introduction -- Rough Sets: Foundations -- Discretization -- Discretization Method Selection -- Proposed Clustering Algorithm -- Implementation and Experiments -- Evaluation Criteria and Performance Analysis -- Evaluation Criteria -- Performance Analysis -- Conclusions and Future Work -- References -- Credit Scoring Data for Information Asset Analysis -- Introduction -- Related Work -- Models -- Algorithms -- Tools and Frameworks -- Problem Description -- Classification Algorithms -- Multilayer Perceptron -- Feature Selection Algorithm -- Neural Networks with Feature Selection -- Analysis -- Suggestive System -- Case Study -- Proposed Algorithm -- Results -- Conclusion -- References -- Evolutionary Computation -- Improving Steel Industrial Processes Using Genetic Algorithms and Finite Element Method -- Introduction -- Experiences and Results -- Tuning traightening rocess of teel ections. , Optimising Tension evelling rocess -- Optimising the Material Behaviour Model in Finite Element Models -- Conclusion -- References -- Genetic Algorithms Combined with the Finite Elements Method as an Efficient Methodology for the Design of Tapered Roller Bearings -- Introduction -- Proposed Methodology -- Creating the Reduced Non-linear Model. Step 1 -- Replacing the Rollers by Beams. Step 2 -- Application of Genetic Algorithms. Step 3 -- Replacement of Beams and Plates in Full Model -- Case Study and Results -- Conclusions -- References -- An Interactive Genetic Algorithm for the Unequal Area Facility Layout Problem -- Introduction -- Problem Formulation -- Suggested Approach -- Layout Representation -- Encoding Structure -- Interactive Genetic Algorithm -- Test Example -- Test Methodology -- Conclusions -- References -- Combining Evolutionary Generalized Radial Basis Function and Logistic Regression Methods for Classification -- Introduction -- Generalized Radial Basis Function -- Neuro-Logistic models -- Estimation of Neuro-Logistic Parameters -- Experiments -- Database Description -- Experimental Design and Statistical Analysis -- Conclusions -- References -- Applications -- Short-Term Wind Energy Forecasting Using Support Vector Regression -- Introduction -- Problem Description -- Formalization -- NREL Data -- Related Work -- Support Vector Regression -- Experimental Analysis -- Loss Function Parameter Study -- Small-Scale Analysis: Wind Grid Point Level -- Large-Scale Analysis: Wind Park Level -- Conclusion -- References -- An Efficient Hybrid Soft Computing Approach to the Generalized Vehicle Routing Problem -- Introduction -- The Local-Global Approach to the GVRP -- An Efficient Algorithm for Solving the Generalized Vehicle Routing Problem -- Genetic Representation -- The Fitness Value -- Initial Population -- Genetic Operators. , Genetic Parameters.

Note: Intro -- Preface -- Contents -- Health Monitoring of Artificial Satellites -- Tensor-Based Anomaly Detection for Satellite Telemetry Data -- 1 Introduction -- 2 Satellite Telemetry Data Anomalies Detection -- 3 Tensor-Based Anomaly Detection (TAD) -- 3.1 Supervised Models -- 4 Tensor Decomposition -- 5 Pervious Anomaly Detection Techniques for Satellite Telemetry Data -- 6 Tensor-Based Anomaly Detection Technique for Satellite Telemetry Data -- 7 Conclusions -- References -- Machine Learning in Satellites Monitoring and Risk Challenges -- 1 Satellite Orbit -- 1.1 Different Orbits of Satellites -- 1.2 Different Uses of Satellites -- 2 Satellites Monitoring -- 2.1 Satellite Remote Sensing -- 2.2 Data Characteristics -- 3 Risk Challenges -- 3.1 Space Weather Impacts -- 3.2 Debris -- 4 Importance of Machine Learning and Applications -- 5 Conclusion -- References -- Formalization, Prediction and Recognition of Expert Evaluations of Telemetric Data of Artificial Satellites Based on Type-II Fuzzy Sets -- 1 Introduction -- 2 Creation of Expert Evaluation Models Based on Type-I Fuzzy Sets -- 3 Creation of Generalized Expert Evaluation Models Based on Interval Type-II Fuzzy Sets -- 4 Weighted Intervals for Interval Type-2 Fuzzy Sets -- 5 Prediction of Expert Evaluations Based on Linear Regression with Initial Interval Type-II Data -- 6 Prediction of Expert Evaluations Based on Linear Regression with Initial Special Case of Interval Type-2 Fuzzy Sets -- 7 Prediction of Expert Evaluations Based on Nonlinear Regression with Initial Interval Type-II Data -- 8 Prediction of Quantitative Parameters Values Based on Linear Regression with Interval Type-II Coefficients -- 9 Conclusions -- References -- Intelligent Health Monitoring Systems for Space Missions Based on Data Mining Techniques -- 1 Introduction -- 2 Satellite Telemetry Data. , 2.1 Characteristics of Satellite Telemetry Data -- 3 Health Monitoring System -- 3.1 Health Monitoring Based on Conventional Techniques -- 3.2 Intelligent Health Monitoring Based on Data Mining Techniques -- 3.3 Intelligent Health Monitoring Applications -- 4 Conclusion -- References -- Design, Implementation, and Validation of Satellite Simulator and Data Packets Analysis -- 1 Introduction and Basics -- 2 Satellite Simulator Design Phase -- 2.1 The Output of Communication Subsystems -- 2.2 Parameters of Simulator Inputs -- 2.3 Communication Subsystem Simulator GUI -- 2.4 Data Packets -- 3 Satellite Communications System Segments -- 3.1 The Ground Segment (GS) -- 3.2 The Space Segment (SS) -- 3.3 The Control Segment (CS) -- 4 Satellite Applications -- 5 Satellite Functions -- 6 Satellite Orbits and Pointing Angles -- 7 Satellite Links -- 7.1 The Basic Satellite Link -- 7.2 Design of the Satellite Link -- 7.3 Quantities for a Satellite RF Link -- 7.4 Digital Links -- 8 Satellite Communication Advantages -- 9 Satellite Communication Disadvantages -- 10 Conclusion -- References -- Telemetry Data Analytics and Applications -- Crop Yield Estimation Using Decision Trees and Random Forest Machine Learning Algorithms on Data from Terra (EOS AM-1) & -- Aqua (EOS PM-1) Satellite Data -- 1 Introduction -- 2 Related Work -- 2.1 Machine Learning-A Brief Overview -- 2.2 Machine Learning in Agriculture -- 2.3 Crop Yield Estimation -- 3 Methodology Adopted -- 3.1 About DSSAT v4.6 Crop Simulation Model -- 3.2 Study Methodology Flow chart -- 3.3 Dataset Used -- 4 Results and Discussions -- 4.1 Decision Tree Interpretation -- 4.2 Random Forest Interpretation -- 4.3 Normalized Difference Vegetation Index as a Performance Measure -- 5 Future Scope -- 6 Conclusion -- References -- Data Analytics Using Satellite Remote Sensing in Healthcare Applications. , 1 Introduction and Historical Perspective -- 1.1 Working of Satellite -- 1.2 Artificial Satellites Classification -- 2 Change Detection -- 3 Data Pre-processing -- 4 Data Mining and Its Techniques -- 4.1 Bayesian Framework -- 4.2 Data Visualization Tools -- 4.3 Data Mining Tools -- 5 Literature Review of Related Work in Visual Data Mining -- 6 Proposed Model for Remote Sensing Using Data Mining -- 7 Data Visualization and Outcomes -- 8 Conclusion -- References -- Design, Implementation, and Testing of Unpacking System for Telemetry Data of Artificial Satellites: Case Study: EGYSAT1 -- 1 Introduction -- 2 The Unpacking System -- 2.1 Unpacking Module -- 2.2 Limit Checking Module -- 2.3 Mining Module -- 3 Case Study: EGYSAT1 -- 3.1 EGYSAT1 Unpacking Module Design -- 3.2 Test Data -- 4 Conclusion -- References -- Multiscale Satellite Image Classification Using Deep Learning Approach -- 1 Introduction -- 2 Related Work -- 3 Convolutional Neural Networks -- 4 Proposed Methodology -- 5 Experimental Results -- 5.1 Remote Sensing Datasets -- 5.2 Results -- 6 Conclusion -- References -- Security Issues in Telemetry Data -- Security Approaches in Machine Learning for Satellite Communication -- 1 Introduction -- 2 Cognitive Satellite Communication Issues Using Machine Learning -- 2.1 Satellite Communication Channel from Earth to GEO Orbit -- 2.2 Land Cover Prediction from Satellite Imagery Using Machine Learning -- 2.3 Performance Analysis of LEO Satellite Networks -- 2.4 An Adaptive Routing Based on an Improved ACO Technique in Leo Satellite Networks -- 2.5 Rainfall Estimation Using Carrier to Noise of Satellite Communication -- 2.6 Deep Learning for Amazon Satellite Image Analysis -- 2.7 Satellite Super Resolution Images Using Deep Learning -- 3 Security and Prevention from Cyber Attacks in Satellite Communication. , 3.1 Non-reliable Data Source Identification Using Machine Learning Algorithm -- 3.2 Deep Learning and Machine Learning for Interruption in Network -- 3.3 Security Protected Procedures Using Machine Learning -- 3.4 Reinforcement Learning -- 3.5 Extreme Learning Machine -- 3.6 Malware Detection Using Machine Learning -- 4 Conclusion -- References -- Machine Learning Techniques for IoT Intrusions Detection in Aerospace Cyber-Physical Systems -- 1 Introduction -- 2 Background -- 2.1 Aerospace Cyber-Physical Systems (CPS) -- 2.2 Internet of Things -- 2.3 Security Overview in IoT -- 2.4 Machine Learning Techniques -- 3 The Proposed Detection Method -- 3.1 Module 1: Dataset Generation -- 3.2 Module 2: Data Pre-processing -- 3.3 Module 3: Data Classification -- 4 Implementation -- 4.1 Evaluation Metrics -- 4.2 Experimental Setup -- 4.3 Experimental Results and Evaluations -- 5 Conclusion and Future Works -- References.

Note: Intro -- Preface -- Contents -- Energy Efficient Optimal Routing for Communication in VANETs via Clustering Model -- 1 Introduction -- 2 Review of Existing Research Papers -- 2.1 The Significance of Energy Efficient Routing -- 3 System Model -- 4 Network Topology -- 4.1 Vehicle Clustering -- 4.2 Head Selection -- 4.3 Energy Efficient Optimization Model -- 5 Result and Discussion -- 5.1 Evaluation Metrics -- 6 Conclusion -- References -- Mobility and QoS Analysis in VANET Using NMP with Salp Optimization Models -- 1 Introduction -- 2 Related Works -- 3 Mobility Analysis -- 3.1 Mathematical Expression -- 3.2 VANET Network Topology -- 3.3 Proposed Architecture -- 3.4 Optimization Process -- 4 Result Analysis -- References -- Studying Connectivity Probability and Connection Duration in Freeway VANETs -- 1 Introduction -- 2 Instantaneous Connectivity of VANETs -- 2.1 Effect of Safe Driving Distance in Free-Flow Traffic -- 2.2 Connectivity in Wide Traffic Jam Conditions -- 3 Connection Duration Estimation -- 4 Conclusions -- References -- A Survey of Different Storage Methods for NGN Mobile Networks: Storage Capacity, Security and Response Time -- 1 Introduction -- 2 Overview -- 2.1 The Millimeter Waves -- 2.2 Small Cell -- 2.3 Massive MIMO -- 2.4 Full Duplex -- 2.5 Beamforming -- 3 Storage Methods for Mobile Networks -- 3.1 Cloud Computing -- 3.2 Mobile Cloud Computing -- 3.3 Mobile Edge Cloud -- 3.4 Hadoop -- 3.5 Device to Device -- 3.6 Software Defined Mobile Edge Cloud -- 4 Related Works -- 5 Discussion -- 6 Conclusion -- References -- Application of Artificial Intelligence Approach for Optimizing Management of Road Traffic -- 1 Introduction -- 2 Takagi-Sugeno's (TS) Fuzzy Models -- 2.1 Structural Adjustment -- 2.2 Parametric Adjustment -- 3 A State of the Art -- 4 Approaches -- 5 Results -- 5.1 First Simulation -- 5.2 Second Simulation. , 5.3 Comments -- 6 Conclusion -- References -- Mobility Condition to Study Performance of MANET Routing Protocols -- 1 Introduction -- 2 Related Works -- 3 Used Mobility Metric -- 3.1 Mobility Models Overview -- 3.2 Used Mobility Metric -- 4 Simulation and Results -- 4.1 Simulation Environment -- 4.2 Performance Metrics -- 4.3 Results and Discussion -- 5 Conclusion -- References -- Internet of Vehicles Over Named Data Networking: Current Status and Future Challenges -- 1 Introduction -- 2 From Host-Centric to Content-Oriented Communication -- 3 Vehicular NDN Solutions -- 3.1 VNDN Forwarding Strategies & -- Mobility -- 3.2 VNDN Cache Management -- 3.3 VNDN Security -- 4 Challenges and Future Directions -- 4.1 Content, Data, and Service Naming -- 4.2 Mobility Support -- 4.3 Blockchain-Based Secure VNDN -- 4.4 Social Awareness -- 4.5 NDN-Based Vehicular Clouds -- 4.6 Cooperative Applications -- 4.7 Technology Heterogeneity -- 4.8 Business Models -- 5 Conclusion -- References -- Internet of Things Smart Home Ecosystem -- 1 Introduction -- 2 Internet of Things (IoT) -- 2.1 Definition of IoT -- 2.2 Architecture of IoT -- 2.3 Domains of Applications of the Internet of Things -- 3 IoT Smart Home Ecosystem -- 3.1 Domestic Comfort -- 3.2 Home Automation Systems Operation -- 4 Network Layer for the IoT Smart Home Ecosystem: WiFi Protocol -- 4.1 Typologies and Operating Mode -- 4.2 The Transmission Channels -- 4.3 Transmission Technologies -- 4.4 WiFi Physical Frames -- 5 Middleware Layer for the IoT Smart Home Ecosystem: ATM Protocol -- 5.1 Nature of ATM Flow -- 5.2 Principles of ATM Networks -- 5.3 ATM Cells -- 5.4 Head of a Cell -- 5.5 ATM Connections -- 5.6 ATM Sublayer Model -- 6 Simulation of the IoT Smart Home Ecosystem Using OPNET Network Simulator -- 6.1 Performance Study of the ATM Porotocol -- 6.2 Performance Study of the WiFi Porotocol. , 6.3 Performance Comparison Between ATM and IP Core Network -- 7 Conclusion -- References -- An Enhanced Adhoc Approach Based on Active Help to Detect Data Flow Anomalies in a Loop of a Business Modeling -- 1 Introduction -- 2 Related Work -- 3 Verification Approach with a Loop Modeling -- 3.1 Description of Symbols Used in the Model Loop -- 3.2 Verification Model with a Loop -- 4 Description of the New Approach and Implementation -- 4.1 Description and Definitions -- 4.2 Proposed Approach -- 4.3 Verification of Conflicting Data and Redundant Data -- 4.4 Results of Rules Implementation -- 5 Conclusion -- References -- An Adaptive Vehicular Relay and Gateway Selection Scheme for Connecting VANETs to Internet via 4G LTE Cellular Network -- 1 Introduction -- 2 Related Networks -- 3 System Model -- 4 Proposed Relay and Gateway Selection Scheme -- 4.1 Metrics of Gateway Selection -- 4.2 Vehicular Gateway Selection Algorithm -- 4.3 Metrics of Relay Selection -- 4.4 Vehicular Relay Selection Algorithm -- 5 Routing Path Discovery to the Mobile Gateway -- 6 Performance Evaluation -- 6.1 Varying Number of Vehicular Gateway Candidates -- 6.2 Varying Maximum Speed -- 7 Conclusion and Future Work -- References -- Mobility Management: From Traditional to People-Centric Approach in the Smart City -- 1 Smart City Definitions: An Overview -- 2 Main Characteristics of a Smart City -- 3 Smart Mobility -- 3.1 Main Innovations for Smart Mobility -- 3.2 The Model "Mobility as a Service" as Engagement Tool -- 4 Sustainable Urban Mobility Plans: The People-Centric Approach -- 5 Mobility Management: The State-of-the-Art in Italy -- 6 Conclusion -- References.

Note: Intro -- Emergent Web Intelligence: Advanced Information Retrieval -- Editorial Preface -- 1 Contextual and Conceptual Information Retrieval and Navigation on the Web -- 2 Automatic Invocation Linking for Collaborative Web-Based Corpora -- 3 WS-Query - A Framework to Efficiently Query Semantic Web Service -- 4 RDF-GL: A SPARQL-Based Graphical Query Language for RDF -- 5 Semantics-Based Intelligent Indexing and Retrieval of Digital Images - A Case Study -- 6 Harvesting Intelligence in Multimedia Social Tagging Systems -- 7 User Profiles Modeling in Information Retrieval Systems -- 8 Human-Web Interactions -- 9 Web Recommender Agents with Inductive Learning Capabilities -- 10 Capturing the Semantics of User Interaction: A Review and Case Study -- 11 Analysis of Usage Patterns in Large Multimedia Websites -- 12 An Adaptation Framework for Web Multimedia Presentations -- 13 A Multifactor Secure Authentication System for Wireless Payment -- 14 A Lightweight Authentication Protocol for Web Applications in Mobile Environments -- 15 Developing Access Control Model of Web OLAP over Trusted and Collaborative Data Warehouses -- 16 Security in Distributed Collaborative Environments: Limitations and Solutions -- 17 A Low-Cost and Secure Solution for e-Commerce -- 18 Hyperchaotic Encryption for Secure E-Mail Communication -- Index.

Note: Intro -- Preface -- Contents -- Machine Learning in Feature Selection -- Hybrid Feature Selection Method Based on the Genetic Algorithm and Pearson Correlation Coefficient -- 1 Introduction -- 2 Feature Selection Based on Hybridization -- 2.1 Evolutionary Algorithms -- 2.2 The Genetic Algorithm -- 2.3 Hybrid Feature Selection -- 3 The Proposed Approach: Hybrid Feature Selection Based on the GA and PCC -- 3.1 GA for the Proposed Method -- 3.2 Pearson Correlation Coefficient (PCC) -- 3.3 Merging Feature Subsplits -- 4 Experimetal Study -- 4.1 Datasets -- 4.2 Performance Measures -- 4.3 Experiments and Discussion -- 5 Conclusion -- References -- Weighting Attributes and Decision Rules Through Rankings and Discretisation Parameters -- 1 Introduction -- 2 Background -- 2.1 Nature of Stylometric Data -- 2.2 Ranking of Features -- 2.3 Supervised Discretisation -- 2.4 CRSA Classifiers -- 2.5 Weighting Rules -- 3 Framework of Experiments -- 3.1 Weighting Features -- 3.2 CRSA Decision Rules -- 3.3 Weighting Rules -- 4 Test Results -- 5 Conclusions -- References -- Greedy Selection of Attributes to Be Discretised -- 1 Introduction -- 2 Discretisation -- 2.1 Supervised Discretisation -- 2.2 Test Sets Discretisation -- 3 Greedy Methods for Selection of Attributes -- 3.1 Forward Sequential Selection -- 3.2 Backward Sequential Selection -- 4 Experiments and Results -- 4.1 Classifier -- 4.2 Experimental Datasets -- 4.3 Results -- 5 Conclusions -- References -- Machine Learning in Classification and Ontology -- Machine Learning for Enhancement Land Cover and Crop Types Classification -- 1 Introduction -- 2 Related Work -- 3 Materials and Classifiers -- 3.1 Study Area and Satellite Images -- 3.2 Ground Truth Datasets -- 3.3 Classifiers -- 4 Experimental Results -- 4.1 Experiments Setup -- 4.2 Parallel Processing Setup -- 4.3 Results. , 4.4 Overall Classification Performance -- 5 Conclusion -- References -- An Optimal Machine Learning Classification Model for Flash Memory Bit Error Prediction -- 1 Introduction -- 2 Related Research -- 3 Experimental Setup -- 3.1 Data Collection -- 3.2 Data Analysis -- 4 Classification Models -- 4.1 Model Inputs and Outputs -- 4.2 Data Subsampling -- 4.3 Machine Learning Methods -- 4.4 Classification Methodology -- 4.5 Results Comparison -- 5 Ensemble Classifier -- 5.1 Ensembling Introduction -- 5.2 Base Classifier 1: Gradient Boosting, Random Subsampling -- 5.3 Base Classifier 2: Gradient Boosting, Inverse PDF-based Subsampling -- 5.4 Base Classifier 3: Weighted SVM, Random Subsampling -- 5.5 Ensemble Process -- 5.6 Ensemble Results -- 6 Knowledge-Based Optimisation -- 6.1 Overview -- 6.2 Algorithm Results -- 6.3 Final Algorithm -- 7 Summary and Conclusions -- References -- Comparative Analysis of the Fault Diagnosis in CHMLI Using k-NN Classifier Based on Different Feature Extractions -- 1 Introduction -- 2 Open Circuit (OC) Fault Analysis of CHMLI -- 3 Proposed Fault Diagnosis Method -- 3.1 Probabilistic PCA Based Feature Extraction -- 3.2 K-Nearest Neighbor (k-NN) -- 4 Simulation and Experimental Results and Discussion -- 5 Conclusion -- References -- Design and Development of an Intelligent Ontology-Based Solution for Energy Management in the Home -- 1 Introduction -- 2 Energy -- 2.1 Non-renewable Energies -- 2.2 Renewable Energies -- 3 Production and Consumption of Electricity in Algeria -- 3.1 Electricity Generation in Algeria Based on Renewable Energies -- 3.2 Demand and Forecasts Electricity in Algeria -- 4 The Smart Home -- 4.1 The Smart Home Operations -- 4.2 The Criteria for Selecting a Home Automation System -- 4.3 The Smart Home Benefits -- 5 Ontology -- 5.1 The Ontology History -- 5.2 Ontology and Semantic Web Architecture. , 5.3 The Ontology Components -- 5.4 Ontology Editors -- 5.5 Ontology Development Methods -- 5.6 Anomalies and Ontology Evaluation -- 6 Solution Design -- 6.1 Presentation of the Domain, Objectives, and Research on Similar Work-Based Ontology -- 6.2 Designate Interesting Terms and Explain the Ontology Classes -- 6.3 Design Properties with Facets, Instances, and Relations of Ontology -- 7 Implementation of the Solution -- 7.1 Implementation in Protégé 5 -- 7.2 Implementation of Reasoning Rules -- 8 Case Study -- 8.1 Presentation of the Environment -- 8.2 Energy Consumption Scenarios -- 8.3 Analysis and Discussion -- 9 Conclusion and Perspectives -- References -- Towards a Personalized Learning Experience Using Reinforcement Learning -- 1 Introduction -- 2 Related Work -- 3 Reinforcement Learning -- 4 Proposed Approach -- 4.1 Main Components -- 4.2 State-Action-Reward -- 5 Evaluations -- 6 Opportunities That Big Data Offer to PL -- 7 Conclusions and Future Work -- References -- Towards Objective-Dependent Performance Analysis on Online Sentiment Review -- 1 Introduction -- 2 State of Art -- 2.1 Online Sentiment Analysis Process -- 2.2 Online Sentiment Evaluation -- 2.3 Sentiment Analysis Challenges -- 2.4 Sentiment Analysis Performance -- 3 Sentiment Performance Criteria -- 3.1 Proposed Performance Criteria -- 3.2 The Sentiment Accuracy-Performance Type (F-measure) -- 3.3 The Runtime-Performance Type -- 3.4 The Sentiment Performance Perspectives Criteria -- 3.5 Compared Techniques -- 4 Experiments and Results -- 4.1 Datasets -- 4.2 Accuracy and Performance Comparison -- 4.3 Experiments Results -- 5 Conclusion -- References -- Enhancing Performance of Hybrid Named Entity Recognition for Amazighe Language -- 1 Introduction -- 2 Literature Review -- 2.1 Rule-Based Approach -- 2.2 Machine Learning (ML) Approach -- 2.3 Hybrid Approach -- 3 Amazighe Language. , 4 Amazighe Named Entity Recognition Challenges -- 5 Experimental Setup -- 5.1 System Architecture -- 5.2 The Rule Based Component -- 5.3 The Machine-Learning Component -- 6 Results and Discussions -- 6.1 Experiment Data Sets: The Amazighe Data -- 6.2 Performance Evaluation of the Hybrid System -- 6.3 Evaluation Results -- 6.4 Speed Discussion -- 7 Conclusion and Future Directions -- References -- A Real-Time Aspect-Based Sentiment Analysis System of YouTube Cooking Recipes -- 1 Introduction -- 2 Related Works -- 3 The Proposed System Overview -- 4 Methodology -- 4.1 Pre-processing -- 4.2 Subjectivity Detection -- 4.3 Feature Extraction from YouTube Cooking Recipes Reviews -- 4.4 Sentiment Classification -- 5 Experiments -- 5.1 Data Collection and Analysis -- 5.2 Evaluation -- 6 Results and Discussion -- 6.1 Experiment with the Subjectivity Detection Training Model -- 6.2 Evaluation on Aspect Extraction -- 6.3 Evaluation on Sentiment Classifications -- 7 Conclusion and Future Works -- References -- Detection of Palm Tree Pests Using Thermal Imaging: A Review -- 1 Introduction -- 2 Traditional Detection Methods -- 2.1 Visual Inspection -- 2.2 Acoustic Detection -- 2.3 Chemical Detection -- 3 Thermal Detection Methods -- 3.1 Thermal Imaging Detection -- 3.2 Thermal Infested Palm Detection -- 4 Analysis -- 5 Conclusion -- References -- Unleashing Machine Learning onto Big Data: Issues, Challenges and Trends -- 1 Introduction -- 1.1 An Overview on Big Data -- 1.2 An Introduction to Machine Learning -- 2 Processing Big Data -- 2.1 Issues, Challenges and Opportunities in Big Data Processing Using Machine Learning -- 2.2 Trends and Open Issues in Big Data Processing Using Machine Learning -- 3 Conclusions -- References -- Bio-inspiring Optimization and Applications -- Bio-inspired Based Task Scheduling in Cloud Computing -- 1 Introduction -- 2 Related Work. , 3 The Proposed H_BAC Algorithm -- 4 System Implementation -- 4.1 Simulation Environment -- 4.2 Performance Metrics -- 5 Simulation Results -- 5.1 First Experiment -- 5.2 Second Experiment -- 6 Conclusions -- References -- Parameters Optimization of Support Vector Machine Based on the Optimal Foraging Theory -- 1 Introduction -- 2 Basic Knowledge -- 2.1 Support Vector Machine -- 2.2 Optimal Foraging Algorithm -- 3 The Proposed OFA for SVM Parameter Optimization Algorithm -- 3.1 Parameters Initialization -- 3.2 Fitness Function, Positions Updates and Termination Criteria -- 4 Experimental Results and Discussion -- 4.1 Datasets Description -- 4.2 Results and Discussion -- 5 Conclusion -- References -- Solving Constrained Non-linear Integer and Mixed-Integer Global Optimization Problems Using Enhanced Directed Differential Evolution Algorithm -- 1 Introduction -- 2 Problem Statement and Constraint Handling -- 3 Differential Evolutions -- 3.1 Initialization of a Population -- 3.2 Mutation -- 3.3 Recombination (Crossover) -- 3.4 Selection -- 4 The Proposed Algorithm (MI-EDDE) -- 4.1 Novel Mutation Scheme -- 4.2 Constraint Handling -- 4.3 Integer Variables Handling -- 5 Experiments and Discussion -- 6 Conclusions -- References -- Optimizing Support Vector Machine Parameters Using Bat Optimization Algorithm -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Support Vector Machine (SVM) Classifier -- 3.2 Bat Algorithm (BA) -- 4 The Proposed Model: BA-SVM -- 5 Experimental Results and Discussion -- 5.1 Illustrative Example -- 5.2 Real Data Experiments -- 5.3 Experimental results -- 6 Conclusions and Future Work -- References -- Performance Evaluation of Sine-Cosine Optimization Versus Particle Swarm Optimization for Global Sequence Alignment Problem -- 1 Introduction -- 2 Pairwise Sequence Alignment -- 3 Sine-Cosine Optimization Algorithm (SCA). , 4 Particle Swarm Optimization (PSO).

Note: 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. , 2 The Common Goal to Reduce Margin of Error in the HC Sector -- 3 Defining EPRs, EHRs and Clinical Systems -- 4 Some Hurdles in an EHR System -- 5 Overcoming Interoperability Issues -- 6 Barriers in EHR Interoperability -- 7 Characteristics and Improvements of the UK-NHS Model -- 8 Summary of MNC/MNE Characteristics -- 9 Proposed Solutions-the UK-NHS Model or the MNC Organizational Model -- 10 E-Health and AI -- 11 Conclusions -- References -- Predicting COVID19 Spread in Saudi Arabia Using Artificial Intelligence Techniques-Proposing a Shift Towards a Sustainable Healthcare Approach -- 1 Introduction -- 2 Literature Review -- 3 Experimental Methodology -- 3.1 Dataset Description and Pre-processing -- 3.2 Building Models -- 4 Model Evaluation Results and Analysis -- 5 Sustainable Healthcare Post COVID 19 for SA -- 5.1 Sustainable Healthcare -- 5.2 Staff and Clinical Practice Sustainability During the Pandemic -- 5.3 Expand Hospital-at-Home During the COVID-19 Pandemic -- 5.4 COVID-19 Pandemic and Sustainable Development Groups -- 5.5 Research Directions -- 6 Conclusion -- References -- Machine Learning and Deep Learning Applications -- A Comprehensive Study of Deep Neural Networks for Unsupervised Deep Learning -- 1 Introduction -- 2 Feedforward Neural Network -- 2.1 Single Layer Perceptron -- 2.2 Multi-Layer Perceptron -- 3 Deep Learning -- 3.1 Restricted Boltzmann Machines (RBMs) -- 3.2 Variants of Restricted Boltzmann Machine -- 3.3 Deep Belief Network (DBN) -- 3.4 Autoencoders (AEs) -- 4 Applications and Implications of Deep Learning -- 4.1 Sustainable Applications of Deep Learning -- 5 Challenges and Future Scope -- References -- An Overview of Deep Learning Techniques for Biometric Systems -- 1 Introduction -- 1.1 Deep Learning -- 1.2 Deep Learning for Biometric -- 2 Deep Learning in Neural Networks -- 2.1 Autoencoders AEs. , 2.2 Deep Belief Networks DBN -- 2.3 Recurrent Neural Networks RNN -- 2.4 Convolutional Neural Networks CNNs -- 3 Deep Learning Frameworks -- 4 Biometrics Systems -- 4.1 Deep Learning for Unimodal Biometrics -- 4.2 Deep Learning for Multimodal Biometrics -- 5 Challenges -- 6 Conclusion and Discussion -- References -- Convolution of Images Using Deep Neural Networks in the Recognition of Footage Objects -- 1 Introduction -- 2 Statement of the Problem -- 3 Image Processing by Non-Parametric Methods -- 4 Using a Convolutional Neural Network in a Minimum Sampling Image Recognition Task -- 5 Deep Learning -- 6 Presence of Small Observations Samples -- 7 Example of Application of a Convolutional Neural Network -- 8 Conclusion -- References -- A Machine Learning-Based Framework for Efficient LTE Downlink Throughput -- 1 Introduction -- 2 4G/LTE Network KPIs -- 3 ML Algorithms Used in the Framework -- 3.1 Dimension Reduction Algorithm -- 3.2 K-Means Clustering Algorithm -- 3.3 Linear Regression Algorithm with Polynomial Features -- 4 A ML-Based Framework for Efficient LTE Downlink Throughput -- 4.1 Phase 1: Preparing Data for ML -- 4.2 Phase 2: Data Visualization and Evaluation -- 4.3 Phase 3: Analyzing Quality Metric -- 5 Experimental Results and Discussion -- 6 Conclusion -- References -- Artificial Intelligence and Blockchain for Transparency in Governance -- 1 Introduction -- 2 Literature Review of Research Paper -- 2.1 Conceptual Framework -- 2.2 Review Based Work -- 2.3 Implementation Based Work -- 2.4 Comparative Analysis -- 3 Selection and Justification of the Preferred Method -- 4 Preferred Method Detailed Comparison -- 5 Conclusions -- References -- Artificial Intelligence Models in Power System Analysis -- 1 Introduction -- 2 AI Techniques: Basic Review -- 2.1 Expert Systems (ES) -- 2.2 Genetic Algorithms (GA). , 2.3 Artificial Neural Networks (ANNs to NNWs) -- 2.4 Fuzzy Logic -- 3 AI Applications in Power System -- 3.1 AI in Transmission Line -- 3.2 Smart Grid and Renewable Energy Systems-Power System Stability -- 3.3 Expert System Based Automated Design, Simulation and Controller Tuning of Wind Generation System -- 3.4 Real-Time Smart Grid Simulator-Based Controller -- 3.5 Health Monitoring of the Wind Generation System Using Adaptive Neuro-Fuzzy Interference System (ANFIS) -- 3.6 ANN Models-Solar Energy and Photovoltaic Applications -- 3.7 Fuzzy Interference System for PVPS (Photovoltaic Power Supply) System -- 4 Sustainability in Power System Under AI Technology -- 5 Conclusion and Future Work -- References -- Internet of Things for Water Quality Monitoring and Assessment: A Comprehensive Review -- 1 Introduction -- 2 Water Quality Assessment in Environmental Technology -- 3 Internet of Things in Water Quality Assessment -- 4 Water Quality Monitoring Systems -- 4.1 Hardware and Software Design -- 4.2 Smart Water Quality Monitoring Solutions -- 5 An Empirical Evaluation of IoT Applications in Water Quality Assessment -- 6 Conclusions -- References -- Contribution to the Realization of a Smart and Sustainable Home -- 1 Introduction -- 2 AI -- 2.1 Some Applications of AI -- 2.2 AI Methodological Approaches -- 3 IoT -- 3.1 The IoT History -- 3.2 Operation -- 3.3 Areas of Application -- 3.4 Relationship Between IoT and IA -- 4 Smart Home -- 4.1 Home Automation Principles -- 4.2 Definition of the Smart Home -- 4.3 Ambient Intelligence -- 4.4 Communicating Objects -- 5 Home Automation Technologies -- 5.1 Wireless Protocols -- 5.2 802.15.4 -- 5.3 Carrier Currents -- 5.4 Wired Protocols -- 5.5 1-Wire -- 6 Home Automation Software -- 6.1 OpenHAB -- 6.2 FHEM -- 6.3 HEYU -- 6.4 Domogik -- 6.5 Calaos -- 6.6 OpenRemote -- 6.7 LinuxMCE. , 7 Home Automation and Photovoltaic Energy -- 8 Implementation -- 8.1 Cost of Home Automation -- 8.2 Hardware and Software Used -- 9 Conclusion -- References -- Appliance Scheduling Towards Energy Management in IoT Networks Using Bacteria Foraging Optimization (BFO) Algorithm -- 1 Introduction -- 2 Review of Related Literature -- 3 System Model -- 3.1 Category of Loads -- 3.2 Specific Objectives of This Work -- 3.3 Description of Major Home Appliances Considered -- 3.4 Length of Operation Time -- 3.5 Appliances Scheduling Optimization Problem Formulation -- 4 BFA Meta-Heuristic Optimization Technique -- 4.1 Chemotaxis -- 4.2 Reproduction -- 4.3 Elimination and Dispersal -- 5 Experiment Results and Discussion -- 5.1 User Comfort -- 5.2 Electricity Cost -- 5.3 Load or Electricity Consumption -- 5.4 Peak Average Ratio (PAR) -- 5.5 Load Balancing -- 6 Conclusion -- References.