Big Data Technologies and Applications: 10th EAI International Conference, BDTA 2020, and 13th EAI International Conference on Wireless Internet, ... and Telecommunications Engineering, 371)

Preface
Organization
Contents
BDTA 2020
Constructing Knowledge Graph for Prognostics and Health Management of On-board Train Control System Based on Big Data and XGBoost
	1 Introduction
	2 Architecture of Big Data-Based Platform
		2.1 Field Operation Layer
		2.2 Data Collection Layer
		2.3 Data Storage and Management Layer
		2.4 Data Processing Layer
	3 Knowledge Graph Generation Method
		3.1 System Fault-Related Features
		3.2 XGBoost-Based Model Training
		3.3 Generation of Knowledge Graph
	4 Results and Analysis
		4.1 Datasets and Experimental Platform
		4.2 Results of a Case Study
	5 Conclusion and Future Works
	References
Early Detecting the At-risk Students in Online Courses Based on Their Behavior Sequences
	1 Introduction
	2 Related Work
	3 Proposed LSTM-Based Framework
		3.1 Behavior Indicator Selection
		3.2 Sequence Data Generation and Preprocessing
		3.3 Prediction Modeling Based on LSTM
	4 Experiment and Result
		4.1 Dataset and Data Preprocessing
		4.2 Implementation Details
		4.3 Result and Discussion
	5 Conclusion and Discussion
	References
Do College Students Adapt to Personal Learning Environment (PLE)? A Single-Group Study
	1 Introduction
	2 Related Work
		2.1 Research on the Connotation of Personal Learning Environment
		2.2 Research on the Model and Framework of Personal Learning Environment
		2.3 Applied Research on Personal Learning Environment
	3 Method
		3.1 Design and Setting
		3.2 Participants
		3.3 Self-directed Learning Training
		3.4 Instruments
		3.5 Analysis
	4 Discussion
		4.1 Learners Have a Moderate Degree of Attention Deficit in Their Personal Learning Environment, Which is Manifested in Three Aspects: Perceived Attention Discontinuity, Lingering Thought, Social Media Notification
		4.2 Under Simple Training or Natural Conditions, Students Have Poor Adaptability in the Personal Learning Environment, and Their Behavior Perception and Behavior Adjustment Levels Have Improved, but They Have not yet Reached Expectations
		4.3 Participation in Online Learning has Significantly Increased the Application of Learners' Self-regulation Strategies, Especially the Application of Behavior Strategies
	5 Conclusions and Limitations
	References
A Big Data Intelligence Marketplace and Secure Analytics Experimentation Platform for the Aviation Industry
	1 Introduction
	2 Materials and Methods
		2.1 The ICARUS Technical Solution
	3 Results
		3.1 Extra-Aviation Services in an Integrated Airport Environment
		3.2 Routes Analysis for Fuel Consumption Optimization and Pollution Awareness
		3.3 Aviation-Related Disease Spreading
		3.4 Enhancing Passenger Experience with ICARUS Data
	4 Conclusions
	References
A Multi-valued Logic Assessment of Organizational Performance via Workforce Social Networking
	1 Introduction
	2 Preliminaries
		2.1 Entropy vs. Knowledge Representation and Reasoning
	3 A Declarative Knowledge Theory for Evaluating Organizational Performance Using Workforce Social Networking
		3.1 Constraints
		3.2 Academic and Organizational Strain
		3.3 Socialization
		3.4 A Computational Make-Up
	4 Conclusions and Future Work
	References
Research on the Sharing and Application of TCM Digital Resources
	1 Introduction
	2 Analysis on the Current Situation of TCM Digital Resources
		2.1 Literatures Research Status
		2.2 Current Situation of Resource Construction
	3 Application of Traditional Chinese Medicine Digital Learning Resources
		3.1 Questionnaire Design
		3.2 Respondents
		3.3 Results and Analysis
		3.4 Suggestions
	4 Conclusion
	References
Statistical Research on Macroeconomic Big Data: Using a Bayesian Stochastic Volatility Model
	1 Theoretical Basis and Research Significance
		1.1 Related Concepts
		1.2 Research Significance
	2 Purpose and Content
		2.1 Main Research Purpose
		2.2 Research Context and Technical Route
		2.3 The Main Content of the Research
	3 Analysis
	4 Conclusion
	References
Introducing and Benchmarking a One-Shot Learning Gesture Recognition Dataset
	1 Introduction
	2 Dataset Collection
	3 Benchmarked Deep Learning Architectures
		3.1 One-Shot Learning Problem Definition
		3.2 Vanilla Embedding Extraction
		3.3 Pairwise Siamese Networks
		3.4 Matching Network
	4 Experimental Set-Up
		4.1 Data Sampling and Preprocessing
		4.2 Hyperparameter Tuning
	5 Results and Discussion
	6 Conclusions
	References
NetFlow Datasets for Machine Learning-Based Network Intrusion Detection Systems
	1 Introduction
	2 Limitations of Existing Datasets
	3 NetFlow Datasets
		3.1 NetFlow
		3.2 Conversion
		3.3 Datasets
	4 Evaluation
		4.1 Binary-Class Classification
		4.2 Multi-class Classification
	5 Conclusion
	References
WiCON 2020
Performance Evaluation of Energy Detection, Matched Filtering and KNN Under Different Noise Models
	1 Introduction
	2 Signal Model and Detectors
		2.1 Signal Model
		2.2 Detectors
	3 Simulation and Analysis
		3.1 Performance of Detectors Under Ideal Conditions
		3.2 Performance of Detectors Under Non-Gaussian Noise
		3.3 Performance of Detectors with Uncertain Noise Variance
	4 Conclusions
	References
Hybrid Deep-Readout Echo State Network and Support Vector Machine with Feature Selection for Human Activity Recognition
	1 Introduction
	2 Literature Review
	3 Solution Approach
	4 Experiment Setup
		4.1 Dataset
		4.2 Evaluation Measures
		4.3 Data Scaling
		4.4 Feature Selection
	5 Results and Analysis
		5.1 Feature Selection and Normalization
		5.2 Performance of ESN
		5.3 Comparison Framework
		5.4 Threats to Validity
	6 Conclusion and Future Work
	References
Research on User Privacy Security of China’s Top Ten Online Game Platforms
	1 Preface
	2 Status Quo of Privacy Security on China’s Top Ten Online Game Platforms
	3 Research and Analysis
	4 Suggestions on Users’ Privacy Protection of Online Game Platforms
		4.1 Suggestions for the Regulatory Bodies of Online Game Platforms
		4.2 Suggestions for Game Platforms
		4.3 Suggestions for Users
	5 Conclusion
	References
Spectrum Sensing and Prediction for 5G Radio
	1 Introduction
	2 System Model and Problem Definition
	3 Deep Learning for Spectrum Sensing and Prediction - Algorithmic Solution
	4 Simulation Experiment
		4.1 Assumptions and Settings
		4.2 Simulation Results
	5 Conclusions
	References
Towards Preventing Neighborhood Attacks: Proposal of a New Anonymization’s Approach for Social Networks Data
	1 Introduction
	2 Illustration of Neighborhood Attacks
	3 Contribution
	4 Some Concepts of Social Graphs
		4.1 Neighborhood and d-Neighborhood of a Vertex
		4.2 Neighborhood Component
		4.3 Graph Isomorphism
		4.4 The Subgraph Isomorphism
		4.5 Usefulness of the Anonymized Graph and Structural Properties
	5 Proposal For A New Approach to Anonymization
		5.1 Extraction and Representation of Neighborhoods and Neighborhood Components
		5.2 Measuring the Quality of Anonymization “Cost of Anonymization”
	6 Experiments
		6.1 Result of Calculation of the Structural Properties: (Synthetic and Real Graphs)
		6.2 Analysis of the Variation of APL According to k
	7 Conclusion and Outlook
	References
Author Index