Note: Intro -- Organization -- Preface -- Contents -- About the Editors -- Multimedia -- Reversible Data Hiding in Encrypted Image Based on MSB Inversion -- 1 Introduction -- 2 Related Works -- 2.1 Secret Embedding Procedure -- 2.2 Message Extracting and Image Recovery -- 3 The Proposed Method -- 3.1 Image Encryption and Secret Embedding -- 3.2 Message Extracting and Image Recovery -- 4 Experimental Result -- 5 Conclusion -- References -- Comments on the Visual Binary QR Code -- 1 Introduction -- 2 Schemes of Visual Binary QR Code -- 2.1 Unitag -- 2.2 QArt -- 2.3 Halftone QR Code -- 3 Comparisons -- 4 Conclusions -- References -- NLP-Based Hardware Solution for Censoring Audio on Over-the-Top (OTT) Media Services -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Hardware Architecture -- 3.2 Software Architecture -- 4 Experiments & -- Results -- 4.1 Application Components & -- Input Dataset -- 4.2 Accommodations for Lag -- 4.3 Results -- 5 Conclusion and Future Work -- References -- Efficient Steganographic Method Based on Modulo Cube -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Preliminary Phase -- 3.2 Embedding Phase -- 3.3 Extraction phase -- 4 Experimental Results -- 5 Conclusions -- References -- A High Capacity Reversible Data Hiding in Encrypted Images Using Multi-MSB Prediction and Huffman Coding -- 1 Introduction -- 2 Proposed Method -- 2.1 Apply the Huffman Tree Building Algorithm -- 2.2 Reduce Reference Bytes -- 2.3 Remove the Redundant Length Column -- 3 Experimental Results -- 3.1 Commonly Used Test Images -- 4 Conclusion -- References -- Reversible Data Hiding Based on Bidirectional Generalized Integer Transform -- 1 Introduction -- 2 Qiu et al. Scheme -- 3 Proposed Scheme -- 4 Experimental Results -- 5 Conclusions -- References -- Network and System Security (I). , A Prototype Design on Privacy-Preserving Outsourced Bayesian Network -- 1 Introduction -- 2 Preliminaries -- 3 System Model -- 4 Construction -- 4.1 Building Blocks -- 4.2 Round Trick -- 4.3 Main Protocol -- 5 Analysis and Discussions -- 6 Conclusions -- References -- The Security Challenge of Consumers' Mobile Payment -- 1 Introduction -- 2 Consumers' Mobile Payment Use Intention -- 3 Consumers' Mobile Payment Security -- 4 Research Methodology -- 4.1 Sample and Data Sources -- 4.2 Variables and Measures -- 4.3 Reliability Analysis -- 4.4 Validity Analysis -- 5 Results -- 5.1 The Structural Equation Modeling (SEM) Results for Mobile Payment Security-Mobile Payment Use Intention -- 5.2 The Impact of Consumers' Mobile Payment Security on Consumers' Mobile Payment Use Intention -- 6 Conclusions -- References -- Research on the Analysis of Key Attack Modes in a Wireless Environment -- 1 Introduction -- 2 The Proposed Scheme -- 2.1 Method Architecture -- 2.2 Test Flow Chart -- 2.3 Introduction to WPA2 Four-Way Handshakes Process -- 3 Analysis of Key Attack Modes -- 3.1 Dictionary Cracking Mode -- 3.2 Script Cracking Mode -- 3.3 Discussion and Comparison -- 4 Conclusion -- References -- Default Risk Prediction Using Random Forest and XGBoosting Classifier -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data -- 3.2 Data Cleaning -- 3.3 Exploratory Data Analysis -- 3.4 Feature Selection Method -- 3.5 Data Split & -- Sampling -- 3.6 Classification Models -- 4 Experiments -- 4.1 XGBoosting Classifier -- 4.2 Random Forest (RF) -- 5 Conclusion -- References -- An RFID Ownership Transfer Based on Multiple Owners with Different Weights -- 1 Introduction -- 2 The Proposed Method -- 2.1 The Initial Phase -- 2.2 The Ownership Transfer Request Phase -- 2.3 The Ownership Agreement Phase -- 2.4 The Ownership Transfer Phase. , 2.5 Mutual Authentication Between the TTP and the Tag -- 2.6 Tag Verification -- 3 Conclusion -- References -- Network and System Security (II) -- Comments on a Scalable Healthcare Authentication Protocol with Attack-Resilience and Anonymous Key-Agreement -- 1 Introduction -- 2 Review of Hajian et al.'s Scheme -- 2.1 System Setup Phase -- 2.2 Registration Phase -- 2.3 Authentication Phase -- 2.4 Password Change Phase -- 2.5 User Identity Change Phase -- 3 Security Analysis -- 3.1 Gateway Authentication Failure -- 3.2 Vulnerability to Denial-of-Service Attack -- 3.3 Failed Password Change and User Identity Change -- 3.4 Compromised User Anonymity and Untraceability -- 4 Conclusions -- References -- A LWE-Based Receiver-Deniable Encryption Scheme -- 1 Introduction -- 2 Related Works -- 2.1 Deniable Encryption -- 2.2 LWE-Based Encryption -- 3 Receiver-Deniable LWE-Based Encryption -- 3.1 Concept -- 3.2 Construction -- 4 Evaluation -- 4.1 Correctness -- 4.2 Deniability -- 5 Conclusion and Future Works -- References -- Privacy-Preserved Hierarchical Authentication and Key Agreement for AI-Enabled Telemedicine Systems -- 1 Introduction -- 2 Related Works -- 2.1 AI Systems -- 2.2 Telemedicine Systems -- 2.3 Chebyshev Chaotic Maps -- 3 Proposed Scheme -- 4 Security Analysis -- 4.1 Security of Secret Key -- 4.2 Session Key Confirmation and Security of Session Key -- 4.3 Mutual Authentication -- 4.4 Unforgeability -- 4.5 Without Assistance of Registration Center (RC) -- 5 Conclusion -- References -- Fuzzy C-Means Based Feature Selection Mechanism for Wireless Intrusion Detection -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Research Design -- 3.2 Difference of FCM Center Distances -- 3.3 Auto Encoder -- 3.4 Deep Neural Network -- 3.5 Data Preprocessing -- 4 Experimental Results -- 5 Conclusion -- References. , An Active User-Side Detector for Evil Twins -- 1 Introduction -- 2 System Principle -- 2.1 Monitor Mode -- 2.2 Retransmission and Forwarding -- 2.3 Principle -- 3 Evaluation -- 3.1 Time Efficiency -- 3.2 Limitations -- 3.3 Discussion -- 4 Conclusion -- References -- AI ad Big Data Analysis (I) -- Evaluation of Recurrent Neural Network Model Training for Health Care Suggestions -- 1 Introduction -- 2 Related Work -- 3 Proposed Solution -- 3.1 LSTM-Based Total Care Prediction System -- 3.2 Feature Selection -- 3.3 Feature Encoding -- 4 System Evaluation -- 4.1 Study Population -- 4.2 The Performance Comparison of Different RNNs -- 5 Conclusion -- References -- E-learning Behavior Analytics in the Curriculum of Big Data Visualization Application -- 1 Introduction -- 2 Teaching Materials Design and Research Methods -- 2.1 Participants and Teaching Environment -- 2.2 E-leaning Variables and Analyzing Methods -- 3 Results -- 3.1 Hotspots of Online Teaching Materials -- 3.2 E-learning Behavior Analysis -- 3.3 Data Mining and Modeling -- 4 Discussion and Conclusion -- 4.1 Hotspots -- 4.2 E-learning Behavior Analysis -- 4.3 Model Prediction -- References -- Malware Detection Based on Image Conversion -- 1 Introduction -- 2 Related Work -- 2.1 Review the Image Texture Analysis Method [1] -- 2.2 Review the Classification of Convolutional Neural Network (CNN) Method [12] -- 3 Proposed Method -- 3.1 System Architecture Diagram -- 3.2 Generative Adversarial Network -- 3.3 Discrete Cosine Transform -- 3.4 Discrete Wavelet Transform -- 3.5 Convolutional Neural Network -- 4 Experiments and Results -- 5 Conclusion -- References -- Automobile Theft Detection by Driving Behavior Identification Using Deep Autoencoder -- 1 Introduction -- 2 Proposed Methods -- 2.1 Model Autoencoder -- 2.2 Deep Autoencoder for Anomaly Detection -- 2.3 Important Features -- 2.4 Dataset. , 2.5 Performance Measurement -- 3 Experimental Results -- 3.1 Performance of Anomaly Detection -- 3.2 Analysis of Important Features -- 4 Conclusions and Future Directions -- References -- Combining a Bi-LSTM-Based Siamese Network with Word2Vec Algorithm for Classifying High-Dimensional Dataset -- 1 Introduction -- 2 Related Work -- 2.1 Natural Language Processing -- 2.2 Recurrent Neural Network -- 2.3 Text Classification -- 2.4 Dimensionality Reduction -- 2.5 Siamese Network -- 3 Proposed Methods -- 3.1 Problem Definition -- 3.2 Proposed Method -- 4 Experiments -- 4.1 Proposed Method Experiment Data Source -- 4.2 Experiment 1: News Category Dataset Classification Precision After Dimensionality Reduction -- 4.3 Experiment 2: Classification Precision After IMDb Dimensionality Reduction -- 5 Conclusion -- References -- Real Time Drowsiness Detection Based on Facial Dynamic Features -- 1 Introduction -- 2 Literature Review -- 3 The Proposed Method -- 4 Experimental Results -- 5 Conclusions -- References -- AI ad Big Data Analysis (II) -- Gradient Deep Learning Boosting and Its Application on the Imbalanced Datasets Containing Noises in Manufacturing -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 3.1 Materials -- 3.2 Methods -- 4 Materials and Methods -- 4.1 Experiments -- 4.2 Results -- 5 Discussions and Conclusions -- References -- Fabric Defect Detection by Applying Structural Similarity Index to the Combination of Variational Autoencode and Generative Adversarial Network -- 1 Introduction -- 2 The Proposed Scheme -- 2.1 The Architecture of Proposed Model -- 2.2 Loss Function -- 3 Experimental Results -- 3.1 Introduction to Environment Configuration and Data Set -- 3.2 Evaluation Index -- 3.3 Performance Evaluation After Training the Model with Fabric -- 4 Conclusions -- References. , A Novel Defense Mechanism Against Label-Flipping Attacks for Support Vector Machines.

Note: Intro -- Foreword -- Preface -- Contents -- 1 Introduction to Advances in Artificial Intelligence-Based Technologies -- References -- Part I Advances in Artificial Intelligence Tools and Methodologies -- 2 Synthesizing 2D Ground Images for Maps Creation and Detecting Texture Patterns -- 2.1 Introduction -- 2.2 Synthesizing 2D Consecutive Region-Images for Space Map Generation -- 2.3 Texture Paths Detection -- 2.4 Simulated Case Study and Comparison with Other Methods -- 2.5 Discussion -- References -- 3 Affective Computing: An Introduction to the Detection, Measurement, and Current Applications -- 3.1 Introduction -- 3.2 Background -- 3.3 Detection and Measurement Devices for Affective Computing -- 3.3.1 Brain Computer Interfaces (BCIs) -- 3.3.2 Facial Expression and Eye Tracking Technologies -- 3.3.3 Galvanic Skin Response -- 3.3.4 Multimodal Input Devices -- 3.3.5 Emotional Speech Recognition and Natural Language Processing -- 3.4 Application Examples -- 3.4.1 Entertainment -- 3.4.2 Chatbots -- 3.4.3 Medical Applications -- 3.5 Conclusions -- References -- 4 A Database Reconstruction Approach for the Inverse Frequent Itemset Mining Problem -- 4.1 Introduction -- 4.2 Related Work -- 4.3 Problem Definition -- 4.3.1 Frequent Itemset Hiding Problem -- 4.3.2 Inverse Frequent Itemset Hiding Problem -- 4.4 Hiding Approach -- 4.5 Conclusion and Future Steps -- References -- 5 A Rough Inference Software System for Computer-Assisted Reasoning -- 5.1 Introduction -- 5.2 Basic Concepts -- 5.2.1 Rough Sets -- 5.2.2 Information System -- 5.2.3 Decision System -- 5.2.4 Indiscernibility Relation -- 5.3 The Approximate Algorithms for Information Systems -- 5.3.1 The Approximate Algorithm for Attribute Reduction -- 5.3.2 The Algorithm for Approximate Rule Generation -- 5.4 Implementation of the Rough Inference System. , 5.5 An Application in Electrical Engineering-A Case Study -- 5.6 Conclusions -- References -- Part II Advances in Artificial Intelligence-based Applications and Services -- 6 Context Representation and Reasoning in Robotics-An Overview -- 6.1 Introduction -- 6.2 Context -- 6.2.1 Definitions of Context -- 6.2.2 Context Aware Systems -- 6.2.3 Context Representation -- 6.3 Context Reasoning -- 6.3.1 Reasoning Approaches and Techniques -- 6.3.2 Reasoning Tools -- 6.4 Conclusions and Future Work -- References -- 7 Smart Tourism and Artificial Intelligence: Paving the Way to the Post-COVID-19 Era -- 7.1 Introduction -- 7.2 Methodology and Research Approach -- 7.3 Artificial Intelligence and Smart Tourism -- 7.3.1 Artificial Intelligence -- 7.3.2 AI Smart Tourism Recommender Systems -- 7.3.3 Deep Learning -- 7.3.4 Augmented Reality In tourism -- 7.3.5 AI Autonomous Agents -- 7.4 Smart Tourism in COVID-19 Pandemic -- 7.5 Conclusions and Future Directions -- References -- 8 Challenges and AI-Based Solutions for Smart Energy Consumption in Smart Cities -- 8.1 Introduction -- 8.2 Smart Energy in Smart Cities -- 8.3 Energy Consumption Challenges and AI Solutions -- 8.3.1 End-User Consumers in Smart Cities -- 8.3.2 Demand Forecasting -- 8.3.3 Prosumers Management -- 8.3.4 Consumption Privacy -- 8.4 Discussion -- References -- 9 How to Make Different Thinking Profiles Visible Through Technology: The Potential for Log File Analysis and Learning Analytics -- 9.1 Introduction -- 9.2 The Development of Log File Analysis and Learning Analytics -- 9.3 Analysing Log File Data in Researching Dynamic Problem-Solving -- 9.4 Extracting, Structuring and Analysing Log File Data to Make Different Thinking Profiles Visible -- 9.4.1 Aims -- 9.4.2 Methods -- 9.5 Participants -- 9.6 Instruments -- 9.7 Procedures -- 9.8 Results -- 9.9 Discussion -- 9.10 Conclusions and Limitations. , References -- 10 AI in Consumer Behavior -- 10.1 Introduction -- 10.2 Literature Review -- 10.3 Artificial Intelligence (AI) in Consumer Behavior -- 10.3.1 Artificial Intelligence -- 10.3.2 Consumer Behavior -- 10.3.3 AI in Consumer Behavior -- 10.3.4 AI and Ethics -- 10.4 Conclusion -- References -- Part III Theoretical Advances in Computation and System Modeling -- 11 Coupled Oscillator Networks for von Neumann and Non-von Neumann Computing -- 11.1 Introduction -- 11.2 Basic Unit, Network Architecture and Computational Principle -- 11.3 Nonlinear Oscillator Networks and Phase Equation -- 11.3.1 Example -- 11.4 Oscillator Networks for Boolean Logic -- 11.4.1 Registers -- 11.4.2 Logic Gates -- 11.5 Conclusions -- References -- 12 Design and Implementation in a New Approach of Non-minimal State Space Representation of a MIMO Model Predictive Control Strategy-Case Study and Performance Analysis -- 12.1 Introduction -- 12.2 Centrifugal Chiller-System Decomposition -- 12.2.1 Centrifugal Chiller Dynamic Model Description -- 12.2.2 Centrifugal Chiller Dynamic MIMO ARMAX Model Description -- 12.2.3 Centrifugal Chiller Open Loop MIMO ARMAX Discrete-Time Model -- 12.2.4 Centrifugal Chiller Dynamic MIMO ARMAX Model Nonminimal State Space Description -- 12.3 MISO MPC Strategy Design in a Minimal State Space Realization -- 12.3.1 MIMO MPC Optimization Problem Formulation -- 12.3.2 MIMO MPC Parameters Design -- 12.3.3 MIMO MPC MATLAB SIMULINK Simulation Results -- 12.4 MIMO MPC Strategy Design in a Nonminimal State Space Realization -- 12.5 Conclusions -- References.