Note: Intro -- Preface -- Organization -- Contents -- Adaptive Multiple-View Label Propagation for Semi-supervised Classification -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Adaptive Multiple-View Label Propagation -- 3.1 Proposed Formulation -- 3.2 Optimization Procedure -- 3.3 Convergence Analysis -- 4 Experimental Results and Analysis -- 4.1 Face Image Databases -- 4.2 Reuters Multilingual Database -- 4.3 Handwritten Numerals Database -- 5 Conclusion -- Acknowledgements -- References -- Container Damage Identification Based on Fmask-RCNN -- Abstract -- 1 Problem Raising -- 2 Container Damage Detection Based on Mask-RCNN -- 3 The Fmask-RCNN Model -- 3.1 Feature Extraction Network -- 3.2 Path Fusion Augmentation -- 3.3 Multiple Fully Connected Layers -- 3.4 Upsampling Improvement -- 3.4.1 Fusion Upsampling -- 3.4.2 Spatial Pyramid Upsampling -- 3.5 Data Enhancement -- 4 Experiment and Analysis -- 5 Conclusion -- References -- Multiagent Reinforcement Learning for Combinatorial Optimization -- 1 Introduction -- 2 Background -- 2.1 Definitions -- 2.2 Grid Pareto Dominance -- 2.3 Model and Problem Formulation -- 2.4 MARL -- 3 MARL-GPLS -- 3.1 The Framework of MARL-GPLS -- 3.2 Initialization -- 3.3 Pareto Local Search -- 3.4 Update Q-Value -- 3.5 MARL-Based Selection -- 4 Experiment and Discussion -- 4.1 Experiment Setup -- 4.2 Effectiveness of MARL -- 4.3 Comparisons with Other Algorithms -- 5 Conclusion -- References -- Extended Kalman Filter-Based Adaptively Sliding Mode Control with Dead-Zone Compensator for an Anchor-Hole Driller -- 1 Introduction -- 2 Modeling the Rotating System of an Anchor-Hole Driller -- 2.1 Dynamic Characteristics of the Hydraulic Motor -- 2.2 Formulation of the Proportional Reversing Valve -- 2.3 Formulation of the Rotating System of an Anchor-Hole Driller -- 3 EKF-Based ASMC-DC of an Anchor-Hole Driller. , 3.1 Dead-Zone Compensator -- 3.2 Adaptively Sliding Mode Control with Dead-Zone Compensation -- 3.3 Extended Kalman Filter -- 4 Experimental Results and Discussion -- 4.1 Performances in Tracing the Pre-set Swing Angle -- 4.2 The Role of the Dead-Zone Compensator -- 4.3 Comparison on the Control Performances of Different Controllers -- 5 Conclusions -- References -- Exploring Multi-scale Deep Encoder-Decoder and PatchGAN for Perceptual Ultrasound Image Super-Resolution -- 1 Introduction -- 2 Related Work -- 2.1 Natural Image SR -- 2.2 Ultrasound Image SR -- 3 Methodology -- 3.1 Multi-scale Encoder-Decoder SR -- 3.2 Patches Discrimination and Loss Function -- 4 Experimental Results and Analysis -- 4.1 Datasets and Training Details -- 4.2 Experimental Comparisons and Analysis -- 5 Conclusion -- References -- Reliable Neighbors-Based Collaborative Filtering for Recommendation Systems -- 1 Introduction -- 2 Reliable Neighbors-Based Collaborative Filtering -- 2.1 Estimation of Missing Ratings -- 2.2 Search of Neighbor Users -- 2.3 Prediction of Final Ratings -- 3 Experiments -- 3.1 Databases -- 3.2 Performance Measure -- 3.3 Experimental Results -- 4 Conclusion -- References -- Downhole Condition Identification for Geological Drilling Processes Based on Qualitative Trend Analysis and Expert Rules -- 1 Introduction -- 2 Problem Description -- 3 The Proposed Method for Downhole Condition Identification -- 3.1 Establishment of Expert Knowledge Base -- 3.2 Extraction of Qualitative Trends -- 3.3 Identification of Downhole Conditions Based on Qualitative Trend Rules -- 4 Industrial Case Study -- 5 Conclusion -- References -- Adaptive Neural Network Control for Double-Pendulum Tower Crane Systems -- Abstract -- 1 Introduction -- 2 Problem Statement -- 2.1 Dynamic Model of Double-Pendulum Tower Crane Systems -- 2.2 Control Objectives. , 3 Controller Development and Stability Analysis -- 3.1 Adaptive Neural Network Controller Development -- 3.2 Stability/Convergence Analysis -- 4 Simulation Results and Analysis -- 5 Conclusion -- Acknowledgements -- References -- Generalized Locally-Linear Embedding: A Neural Network Implementation -- 1 Introduction -- 2 Notations -- 3 Locally Linear Embedding Revisited -- 4 Proposed Methodology -- 5 Experiments -- 5.1 Experimental Setup -- 5.2 Dimension Reduction -- 5.3 Classification -- 6 Conclusion -- References -- Semi-supervised Feature Selection Using Sparse Laplacian Support Vector Machine -- 1 Introduction -- 2 SLapSVM -- 3 Experimental Results -- 3.1 Data Description and Experimental Setting -- 3.2 Gaussian Data -- 3.3 UCI Datasets -- 3.4 Parameter Sensitivity Analysis -- 4 Conclusions -- References -- Tailored Pruning via Rollback Learning -- 1 Introduction -- 2 Rollback Learning -- 2.1 Model Parsimony Based on Filter Sparsity -- 2.2 Backtracking in Channel Selection -- 2.3 Rollback Learning via GAL Based on -- 3 Experiments -- 3.1 Datasets and Implementation Details -- 3.2 Experiments Setting on CIFAR10 -- 3.3 Ablation Study -- 3.4 Results on CIFAR10: -- 3.5 Experiments ILSVRC12 ImageNet -- 4 Conclusion -- References -- Coordinative Hyper-heuristic Resource Scheduling in Mobile Cellular Networks -- Abstract -- 1 Introduction -- 2 Problem Formulation -- 3 Parallel-Space Coordinative Hyper-heuristic Algorithm -- 3.1 Hyper-heuristic Algorithm -- 3.2 Parallel-Spacing Coordinative Hyper-heuristic Algorithm -- 4 Simulation Results -- 4.1 Parameters Setting and Test Problems -- 4.2 Effectiveness of Cooperative Searching Between Heuristic and Solution Space -- 4.3 Performance of Local Search Mechanism -- 4.4 Comparison Results on 20 Real-World Problems -- 5 Concluding Remarks -- Acknowledgement -- References. , Latent Sparse Discriminative Learning for Face Image Set Classification -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Problem Formulation -- 3.2 Optimization -- 3.3 Solve Capped Simplex Projection Problem -- 3.4 Classification -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Results on the Honda/UCSD Dataset -- 4.3 Results on the CMU Mobo Dataset -- 4.4 Results on the YouTube Celebrities Dataset -- 4.5 Running Time Comparison -- 4.6 Latent Sparse Property Analysis -- 4.7 Convergence Analysis -- 4.8 Parameter Sensitivity -- 5 Conclusion -- References -- Sparse Multi-task Least-Squares Support Vector Machine -- 1 Introdution -- 2 Multi-task Least-Squares Support Vector Machine -- 3 The Proposed SMTLS-SVM -- 3.1 Problem Formulation -- 3.2 Alternating Minimization Algorithm -- 3.3 Best-Case Analysis -- 4 Experimental Study -- 4.1 Experiment on Synthetic Data -- 4.2 Experiment on Handwritten Data -- 4.3 Experiment on Micorarray Data -- 5 Conclusions -- References -- Discriminative Subspace Learning for Cross-view Classification with Simultaneous Local and Global Alignment -- 1 Introduction -- 2 Related Works -- 2.1 Low-Rank Representation -- 2.2 Linear Discriminant Analysis -- 3 The Proposed Algorithm -- 3.1 Notations -- 3.2 Objective Function -- 3.3 Optimization Scheme -- 4 Experiments -- 4.1 Experimental Datasets -- 4.2 Experimental Results and Analysis -- 4.3 Performance Evaluations -- 5 Conclusion -- References -- A Recognition Method of Hand Gesture Based on Dual-SDAE -- 1 Introduction -- 2 Stacked Denoising Autoencoder -- 3 Structure of Dual-SDAE Network -- 4 Experiments -- 4.1 American Sign Language Dataset -- 4.2 Influence of Parameters of SDAE -- 4.3 Dual-SDAE -- 4.4 Comparison with Existing Gesture Recognition Methods -- 5 Conclusions -- References -- Image Generation from Layout via Pair-Wise RaGAN -- 1 Introduction. , 2 Related Work -- 3 Generating Realistic Image from Coarse Layout -- 3.1 Relativistic Average Generative Adversarial Network -- 3.2 Pair-Wise Relativistic Average Discriminator -- 3.3 Consistency Loss -- 3.4 Total Loss Function -- 4 Experimental Results and Analysis -- 4.1 Evaluation Metrics -- 4.2 Comparing Analysis -- 4.3 Ablation Study -- 5 Conclusion -- References -- Learning Unsupervised Video Summarization with Semantic-Consistent Network -- 1 Introduction -- 2 Related Works -- 2.1 Supervised vs. Unsupervised Video Summarization -- 2.2 Content-Based Video Summarization -- 2.3 Semantic-Based Video Summarization -- 3 The Proposed Approach -- 3.1 Keyframe Selector -- 3.2 Semantic-Consistent Descriptor -- 3.3 Model Training -- 4 Results -- 4.1 Experiment Setup -- 4.2 Quantitative Evaluation -- 4.3 Qualitative Results -- 5 Conclusion -- References -- Sustainable Competitiveness Evaluation for Container Liners Using a Novel Hybrid Method with Intuitionistic Fuzzy Linguistic Variables -- Abstract -- 1 Introduction -- 2 Theories and Methods -- 2.1 Linguistic Scale Set -- 2.2 Intuitionistic Linguistic Variable -- 2.3 Optimal Combination Weights -- 2.4 Objective Weight Determination Method -- 3 Model of Evaluation -- 4 Case Study -- 4.1 Selection of Attributes and Structure of Decision Matrixes -- 4.2 Decision Making Process -- 5 Discussion -- 6 Conclusion -- References -- 2-Dimensional Interval Neutrosophic Linguistic Numbers and Their Utilization in Group Decision Making -- 1 Introduction -- 2 2-Dimensional Interval Neutrosophic Linguistic Number -- 3 Choquet Integral Operator for 2-Dimensional Interval Neutrosophic Linguistic Numbers -- 4 A Group Decision Making Scheme Based on PROMETHEE II Model -- 5 Numerical Study -- 5.1 The Decision Making Steps -- 6 Conclusions -- References -- Cross-Modal N-Pair Network for Generalized Zero-Shot Learning. , 1 Introduction.

Note: Intro -- Preface -- Organization -- Contents -- Neural Network Theory, Cognitive Sciences, Neuro-System Hardware Implementations, and NN-Based Engineering Applications -- An Optimization Method to Boost the Resilience of Power Networks with High Penetration of Renewable Energies -- 1 Introduction -- 1.1 Backgrounds -- 1.2 An Insight to Enhance the Grid Resilience -- 2 Establishment of the Optimization Model -- 2.1 Disposal of the Uncertainty of Renewable Energy Power -- 2.2 Optimization Variable -- 2.3 Objective Function -- 2.4 Constraints -- 3 Case Study -- 3.1 Case Description -- 3.2 Analysis of Results -- 4 Conclusion -- Appendix -- References -- Systematic Analysis of Joint Entity and Relation Extraction Models in Identifying Overlapping Relations -- 1 Introduction -- 2 Related Work -- 3 Joint Extraction Model Comparison -- 3.1 Model Differences -- 3.2 Feature Separation Strategy -- 3.3 Feature Fusion Strategy -- 4 Results and Analysis -- 4.1 Datasets -- 4.2 Evaluation -- 4.3 Results -- 4.4 Analysis -- 5 Conclusions -- References -- Abnormality Detection and Identification Algorithm for High-Speed Freight Train Body -- 1 Introduction -- 2 Characterization of Examined Objects and Train Set -- 3 Abnormality Detection and Identification Based on YOLOv4 -- 4 The Improved-YOLOv4 Model -- 4.1 Data Augmentation -- 4.2 Negative Sample Mechanism -- 4.3 SECSPDarknet-53 -- 4.4 Cascade PConv Module -- 4.5 Integrated Batch Normalization -- 4.6 The Framework of Improved-YOLOv4 -- 5 Experiment and Analysis -- 6 Conclusion -- References -- Pheromone Based Independent Reinforcement Learning for Multiagent Navigation -- 1 Introduction -- 2 Background -- 2.1 Multiagent Systems (MAS) and Reinforcement Learning (RL) -- 2.2 The Mechanism of Stigmergy -- 3 Method -- 3.1 Dueling Double Deep Q-Network with Prioritized Replay. , 3.2 Digital Pheromones Coordination Mechanism -- 4 Experiments -- 4.1 Minefield Navigation Environment (MNE) -- 4.2 Effectiveness of PCDQN -- 5 Conclusion -- References -- A Deep Q-Learning Network Based Reinforcement Strategy for Smart City Taxi Cruising -- 1 Introduction -- 2 Problem Description -- 2.1 Modeling -- 2.2 Brief of Deep Reinforcement Learning -- 3 Design of DQN -- 3.1 Network Expressed Strategy -- 3.2 Procedure -- 4 Experiments and Results -- 5 Conclusions and Future Work -- References -- Weighted Average Consensus in Directed Networks of Multi-agents with Time-Varying Delay -- 1 Introduction -- 2 Problem Statement -- 3 Main Results -- 4 Simulation -- 5 Conclusion -- References -- An Improved Echo State Network Model for Spatial-Temporal Energy Consumption Prediction in Public Buildings -- 1 Introduction -- 2 Structure of Classical ESN -- 3 Chain-Structure Echo State Network -- 4 Experiment Design -- 4.1 Datasets and Model Preparation -- 4.2 Spatio-Temporal Forecasting of Hourly Building Energy Consumption -- 4.3 End-to-End Experiments on Buildings Using CESN Model -- 5 Experiment Results -- 5.1 Experimental Results of Spatio-Temporal Prediction -- 5.2 Experimental Results of End-to-End Prediction -- 6 Conclusion -- References -- Modeling Data Center Networks with Message Passing Neural Network and Multi-task Learning -- 1 Introduction -- 2 Related Work -- 2.1 Network Modeling -- 2.2 Routing Optimization -- 3 Background -- 3.1 Problem Setup -- 3.2 Overview of Message Passing Neural Network -- 3.3 State of the Art Method: RouteNet -- 4 Methods -- 4.1 The Extended Multi-output Architecture -- 4.2 Loss Function Design -- 4.3 Sample Generation -- 5 Experiments -- 5.1 Experiment Setup -- 5.2 Experiment Results -- 6 Conclusion -- References -- Machine Learning, Data Mining, Data Security and Privacy Protection, and Data-Driven Applications. , A Computational Model Based on Neural Network of Visual Cortex with Conceptors for Image Classification -- 1 Introduction -- 2 Methods -- 2.1 Spiking Neuron Model -- 2.2 Conceptors -- 3 Network Structure -- 3.1 Visual Cortex (V1) -- 3.2 The Orientation Layer (V2) -- 3.3 Decision Output Layer -- 4 Results -- 4.1 The MNIST Database -- 4.2 The ORL Face Database -- 4.3 The CASIA-3D FaceV1 Database -- 5 Conclusion -- References -- Smoothed Multi-view Subspace Clustering -- 1 Introduction -- 2 Preliminaries and Related Work -- 2.1 Graph Filtering -- 2.2 Multi-view Subspace Clustering -- 3 Proposed Methodology -- 3.1 Smoothed Multi-view Subspace Clustering -- 4 Multi-view Experiments -- 4.1 Dataset -- 4.2 Comparison Methods -- 4.3 Experimental Setup -- 4.4 Results -- 4.5 Parameter Analysis -- 5 Conclusion -- References -- Sample Reduction Using 1-Norm Twin Bounded Support Vector Machine -- 1 Introduction -- 2 1-TBSVM -- 2.1 Formulations -- 2.2 Solutions and Property Analysis -- 3 Numerical Experiments -- 3.1 Artificial Dataset -- 3.2 UCI Datasets -- 4 Conclusion -- References -- Spreading Dynamics Analysis for Railway Networks -- 1 Introduction -- 2 Data Set -- 3 COVID-19 Spreading Characteristics via Rail Network -- 3.1 Network Modeling -- 3.2 Basic Characteristics of the CHR Network -- 3.3 Spreading Characteristics Analysis -- 4 Conclusion -- References -- Learning to Collocate Fashion Items from Heterogeneous Network Using Structural and Textual Features -- 1 Introduction -- 2 Related Work -- 3 Fashion Collocation Based on Heterogenous Network -- 3.1 Overview of Our Framework -- 3.2 Network Construction -- 3.3 Structural Feature Extraction -- 3.4 Textual Feature Extraction -- 3.5 Feature Fusion -- 4 Experiment -- 4.1 Dataset -- 4.2 Experiment Settings -- 4.3 Results and Comparison -- 4.4 Parametric Study -- 5 Conclusion -- References. , Building Energy Performance Certificate Labelling Classification Based on Explainable Artificial Intelligence -- 1 Introduction -- 2 Problem Formulation -- 3 Methodology -- 3.1 ANN Modelling -- 3.2 Model Training, Test, and Evaluation -- 3.3 Explanation of the Building EPC Labelling Classification Model -- 3.4 Model Improvement and Optimisation -- 4 Case Study -- 4.1 Data Description and Processing -- 5 Results and Discussions -- 5.1 Trained Model Analysis -- 5.2 LIME XAI Results -- 6 Conclusion -- References -- Cross Languages One-Versus-All Speech Emotion Classifier -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Overall Structure -- 3.2 Feature Extraction -- 3.3 Feature Engineering -- 4 Experimental Results -- 4.1 Experimental Setup -- 4.2 Results of Feature Engineering -- 4.3 Framework Evaluation -- 5 Conclusion -- References -- A Hybrid Machine Learning Approach for Customer Loyalty Prediction -- 1 Introduction -- 2 Related Work -- 3 Research Method -- 3.1 K-Means Clustering -- 3.2 Classification Models for Prediction -- 3.3 Design of Two-Stage Model -- 4 Data -- 4.1 Dataset -- 4.2 Feature Selection and Engineering -- 4.3 Data Analysis Process -- 4.4 K-Means Clustering -- 4.5 Building Classification Models -- 4.6 Model Evaluation Techniques -- 5 Experimental Results and Discussions -- 5.1 Model Performance Review -- 5.2 Decision Tree Formulation -- 6 Conclusion and Future Work -- References -- LDA-Enhanced Federated Learning for Image Classification with Missing Modality -- 1 Introduction -- 2 Related Work -- 2.1 Federated Learning -- 2.2 Pattern Recognition with Missing Modality -- 3 Proposed Method -- 3.1 Framework -- 3.2 LDA-Based Features Aggregation -- 4 Experiments -- 4.1 Results on the MNIST Dataset -- 4.2 Results on the CIFAR-10 Dataset -- 5 Conclusion -- References. , A Data Enhancement Method for Gene Expression Profile Based on Improved WGAN-GP -- 1 Introduction -- 2 Preliminaries -- 2.1 Conditional Generative Adversarial Networks -- 2.2 Wasserstein Generative Adversarial Network Based on Gradient Penalty -- 3 The Proposed Method -- 3.1 Dataset Partition -- 3.2 Constraint Penalty Term -- 3.3 The Steps of the Proposed Method -- 4 Experiments and Discussion -- 4.1 Datasets and Algorithm Parameters Setting -- 4.2 Wasserstein Distance Index -- 4.3 Diversity Comparison on the Generated Sample with Different Methods -- 4.4 Stability Comparison on the Generated Sample Distribution Stability with Different Methods -- 4.5 Selection of the Threshold Parameter -- 5 Conclusions -- References -- Examining and Predicting Teacher Professional Development by Machine Learning Methods -- 1 Introduction -- 2 Related Works -- 3 The Proposed Questionnaire Scheme -- 4 Classification Problem and Machine Learning Methods -- 4.1 Classification Problem -- 4.2 Machine Learning Methods -- 4.3 Hyperparameter Optimization Scheme -- 5 Simulation Results -- 5.1 Identification of Significant Attributes -- 5.2 The Effect of Eight ML Methods -- 5.3 The Effect of Tuning ENS -- 5.4 The Effect of Tuning SVM -- 5.5 The Effect of Tuning ANN -- 5.6 Applying the ABC Algorithm to Tune ANN -- 6 Conclusion -- References -- Neural Computing-Based Fault Diagnosis, Fault Forecasting, Prognostic Management, and System Modeling -- A Hybrid Approach to Risk Analysis for Critical Failures of Machinery Spaces on Unmanned Ships by Fuzzy AHP -- 1 Introduction -- 2 Preliminaries -- 2.1 Fuzzy Sets and Triangular Fuzzy Numbers -- 2.2 Z-numbers -- 3 Methodology -- 4 Case Study -- 4.1 Risk Measurement -- 4.2 Analysis of Risk of Black-Outs -- 5 Discussion and Recommendations -- 6 Conclusion -- References. , A New Health Indicator Construction Approach and Its Application in Remaining Useful Life Prediction of Bearings.