
Recent Advances in Information and Communication Technology 2020
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This book gathers the proceedings of the 16th International Conference on Computing and Information Technology (IC 2 IT 2020), held on May 14th-15th, 2020, at Dusit Thani Pattaya, Thailand. The topics covered include big data, artificial intelligence, machine learning, natural language processing, speech recognition, image and video processing, and deep learning. In turn, the topics represent major research and engineering directions for autonomous driving, language assistants, automatic translation, and answering systems. Lastly, they are responses to major economic changes around the world, which are increasingly shaped by the need for enhanced globalization and worldwide cooperation, and by emerging global problems.
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Content
- Intro
- Preface
- Organization
- Program Committee
- Organizing Partners
- In Cooperation with
- Contents
- An Empirical Study Towards the Intention to Use QR Code Payment in Champasak Province, Lao People's Democratic Republic
- Abstract
- 1 Introduction
- 2 Related Literature
- 2.1 QR Code Payment System
- 2.2 Technology Acceptance Model
- 3 Research Methodology
- 3.1 Research Model
- 3.2 Data Collection
- 4 Results
- 4.1 Validity and Reliability Analysis
- 4.2 Demographic Variables
- 4.3 Correlation Analysis
- 4.4 Multicollinearity Analysis
- 4.5 Results from Multiple Linear Regression
- 5 Conclusion and Discussion
- Acknowledgment
- References
- Identifying of Decision Components in Thai Civil Case Decision by Text Classification Technique
- 1 Background
- 2 Related Work
- 3 Dataset
- 4 The Proposed Method
- 4.1 Civil Case Decision Document Pre-processing
- 4.2 Classifier Modeling of Each Civil Case Decision Component
- 5 The Experimental Results
- 6 Conclusion
- References
- Wearable Computing for Dementia Patients
- Abstract
- 1 Introduction
- 1.1 Dementia
- 2 Patient Activities Monitoring
- 3 Our Approach
- 3.1 Wearable Computing
- 3.2 Android Application for Data Collection
- 3.3 Data Preprocessing
- 3.4 Algorithms
- 4 Results
- 5 Conclusion and Future Works
- Acknowledgments
- References
- Supplement Products Data Extraction and Classification Using Web Mining
- Abstract
- 1 Introduction
- 2 Related Work
- 2.1 Web Data Extraction
- 2.2 Word Segmentation
- 2.3 Term Frequency - Inverse Document Frequency (TF-IDF)
- 2.4 Cosine Similarity
- 3 Methodology
- 3.1 Extraction Stage
- 3.2 Classification Stage
- 4 Experimental and Result
- 4.1 Data Preparation
- 4.2 Performance Evaluation
- 5 Conclusion
- Acknowledgment
- References
- Aquaponics Systems Using Internet of Things
- Abstract
- 1 Introduction
- 2 Literature Review
- 3 Methodology
- 4 Results
- 5 Conclusion
- References
- Classification of Generation of Thai Facebook Users Using Deep Learning with Probability of Words
- Abstract
- 1 Introduction
- 2 Related Works
- 2.1 Research of Using Words in Each Age Range
- 2.2 Research of Classification Age of Social Network Users
- 2.3 Research of Classification Thai Language Text
- 3 Research Experiments
- 3.1 Data
- 3.2 Preprocessing
- 3.3 Word Embedding
- 3.4 Probability of Words
- 3.5 Convolution Neural Network
- 3.6 Long-Short Term Memory (LSTM)
- 4 Methodology
- 5 Experiment Result
- 6 Conclusion
- References
- Design of an Intelligent, Safe and Secure Transport Unit for the Physical Internet
- Abstract
- 1 Introduction
- 2 Overview of the Literature
- 2.1 IATA Strategy and Regulations
- 2.2 C-ITS Concepts
- 3 Design of the iTU
- 3.1 Physical Structure
- 3.2 Information Model
- 3.3 Functional Model
- 3.4 Safety and Security
- 4 Discussion
- 5 Conclusion
- References
- Feature Selection Method Based on Correlation Tree
- Abstract
- 1 Introduction
- 2 Operation Principle
- 2.1 KDDCUP'99 Data Set
- 2.2 Pearson's Correlation and Covariance
- 2.3 Correlation Tree Feature Selection
- 3 Experiments and Analysis
- 3.1 Generate Correlation Tree and Feature List for KDDCUP'99 Data Set
- 3.2 Data Set from CC and BFS Feature Selection
- 3.3 Result and Discussion
- 4 Conclusion
- References
- Thai Words Segmentation Using an Unsupervised Learning Technique
- Abstract
- 1 Introduction
- 1.1 Background
- 1.2 Literature Review
- 2 Word Distance Concept
- 3 Genetic Algorithms for Determining Word Boundary
- 4 Implementation and Experimentation
- 5 Causes of Mis-segmentation
- 6 Improving Accuracy of the Model
- 7 Summary and Conclusion
- References
- A Framework for Designing and Evaluating Persuasive Technology in Education
- Abstract
- 1 Introduction
- 2 Literature Reviews
- 2.1 Persuasive Technology
- 2.2 Persuasive Technology in Education
- 3 Proposed Research Framework
- 4 Research Methodology
- 5 Data Analysis and Results
- 5.1 Users Requirements of Persuasive Technology Elements
- 5.2 Designing Persuasive Technology Based on Users Requirements
- 5.3 Evaluating User Performance of Using Persuasive Technology
- 6 Discussion and Conclusion
- 6.1 Hypotheses Testing Results
- 6.2 Discussion
- References
- Effectiveness of Six Text Classifiers for Predicting SET Stock Price Direction
- Abstract
- 1 Introduction
- 2 Related Work
- 2.1 Predictive Data Mining Algorithms
- 2.2 Performance Evaluation
- 3 Methodology
- 3.1 Assumptions
- 3.2 Text Processing
- 4 Result and Evaluation
- 4.1 Effectiveness of Each Classifier
- 4.2 Comparing the Six Classifiers
- 5 Conclusion
- Acknowledgement
- References
- Biomarker Identification in Colorectal Cancer Using Subnetwork Analysis with Feature Selection
- Abstract
- 1 Introduction
- 2 Materials and Methods
- 2.1 Materials
- 2.2 Methodology
- 3 Results and Discussion
- 4 Conclusion
- Acknowledgements
- References
- Smartphone Information Extraction and Integration from Web
- Abstract
- 1 Introduction
- 2 Related Work
- 3 Methodology
- 3.1 Extraction Web Extraction Layer
- 3.2 Integration Layer
- 3.3 Application Layer
- 4 Experimental and Result
- 5 Conclusion
- Acknowledgment
- References
- A Comparative Study on Artificial Neural Network and Radial Basis Function for Modelling Output Response from Computer Simulated Experiments
- Abstract
- 1 Introduction
- 2 Research Methods
- 2.1 Kriging Model
- 2.2 Radial Basis Function
- 2.3 Artificial Neural Network
- 2.4 Test Problems
- 2.5 Model Validation
- 3 Results
- 4 Conclusions
- References
- Mutation Variations in Improving Local Optima Problem of PSO
- Abstract
- 1 Introduction
- 2 Previous Works
- 2.1 Particle Swarm Optimization (PSO)
- 2.2 Enhance Particle's Exploration of Particle Swarm Optimization with Individual Particle Mutation (IMPSO) [6]
- 3 Proposed Mutation Variations
- 4 Experiments
- 4.1 Benchmark Functions
- 4.2 Experiments Setup
- 4.3 Experiments Results
- 5 Conclusion
- References
- Intruder Detection by Using Faster R-CNN in Power Substation
- Abstract
- 1 Introduction
- 2 Methodology
- 2.1 Faster Region Convolution Neural Network (Faster R-CNN)
- 2.2 Overall Process
- 2.3 Object Detection System
- 2.4 Line Notification System
- 2.5 Mean Average Precision
- 3 Experiments and Results
- 4 Conclusion
- Acknowledgments
- References
- Super-Resolution Image Generation from Enlarged Image Based on Interpolation Technique
- Abstract
- 1 Introduction
- 2 Literature Review
- 2.1 Super-Resolution (SR)
- 2.2 Interpolation
- 2.3 Bicubic Interpolation
- 2.4 Performance Measure
- 2.4.1 Peak Signal to Noise Ratio (PSNR)
- 2.4.2 Root Mean Square Error (RMSE)
- 3 Research Methodology
- 3.1 Material and Method
- 3.2 Super-Resolution Image (SRG)
- 4 Experimental Results
- 5 Conclusion
- Smart Telematics System with Beacon and Global Positioning System Technology
- Abstract
- 1 Introduction
- 2 Literature Review
- 3 Methodology
- 4 Results
- 5 Conclusion
- Acknowledgement
- References
- Incremental Object Detection Using Ensemble Modeling and Deep Transfer Learning
- Abstract
- 1 Introduction
- 2 Object Detection using Deep Learning
- 3 Proposed Model
- 3.1 Pre-trained Model
- 3.2 Transferred-Model
- 3.3 Ensemble Model
- 4 Results
- 5 Conclusion
- References
- Application of Deep Learning to Fairness-Based Power Allocation for 5G NOMA System with Imperfect SIC
- 1 Introduction
- 2 System Model and Problem Formulation
- 2.1 System Model
- 2.2 Problem Formulation
- 3 Application of Deep Learning to Fairness-Based Power Allocation
- 4 Simulation Results
- 5 Conclusion
- References
- Author Index
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