Advanced Computational Methods for Knowledge Engineering

Name: Advanced Computational Methods for Knowledge Engineering | Proceedings of the 6th International Conference on Computer Science, Applied Mathematics and Applications, ICCSAMA 2019
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Proceedings of the 6th International Conference on Computer Science, Applied Mathematics and Applications, ICCSAMA 2019

Hoai An Le Thi Hoai Minh Le Tao Pham Dinh Ngoc Thanh Nguyen(Editor)

Springer (Publisher)

Published on 19. December 2019

XIV, 426 pages

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978-3-030-38364-0 (ISBN)

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Content

Intro
Preface
Organization
Conference Chair
Program Chairs
Honorary Chair
Organizing Chairs
Publicity Chair
International Program Committee Members
External Reviewers
Organizing Committee Members
Contents
Nonconvex Optimization, DC Programming and DCA, and Applications
A New Efficient Algorithm for Maximizing the Profit and the Compactness in Land Use Planing Problem
1 Introduction
2 Problem Statement
3 DC Programming and Solution Method
3.1 A Brief Presentation of DC Programming and DCA
3.2 Reformulation and DC Algorithm
4 Numerical Results
5 Conclusion
References
A New Solution Method for a Mean-Risk Mixed Integer Nonlinear Program in Transportation Network Protection
1 Introduction
2 Problem Description
2.1 Parameters and Variables
2.2 Mathematical Model
3 Solution Method
3.1 DC Programming and DC Algorithm
3.2 DCA for CMINLP
4 Experimental Results
5 Conclusions
References
A Novel Approach for Travel Time Optimization in Single-Track Railway Networks
1 Introduction
2 Problem Description
2.1 Notation
2.2 Mathematical Model
3 Solution Method
3.1 DC Reformulation
3.2 DC Algorithm for (14)
4 Computational Experiments
5 Conclusion
References
DCA with Successive DC Decomposition for Convex Piecewise-Linear Fitting
1 Introduction
2 Solution Method by DC Programming and DCA
2.1 DCA for Solving the Problem (1)
2.2 DCA with Successive DC Decomposition for Solving the Problem (1)
2.3 Starting Point for DCA
3 Numerical Experiments
4 Conclusions
References
Solving Efficient Target-Oriented Scheduling in Directional Sensor Networks by DCA
1 Introduction
2 Problem Statement and Mathematical Modeling
3 DC Programming and DCA
4 DCA-Cut for Global Solution
5 Numerical Simulation and Conclusion
References
A Combination of CMAES-APOP Algorithm and Quasi-Newton Method
1 Introduction
2 The CMAES-APOP Algorithm
3 Combining Local Search with the CMAES-APOP
3.1 When/where Should a Local Search Be Used?
3.2 The Quasi-Newton Line Search Method
4 Numerical Experiment
5 Conclusion
References
A Triple Stabilized Bundle Method for Constrained Nonconvex Nonsmooth Optimization
1 Introduction
2 A Nonconvex Nundle Method
2.1 Work Model
2.2 Convergence
3 Numerical Experiments
3.1 Test Problems
3.2 Comments
4 Conclusion and Extensions
References
An Adapted Derivative-Free Optimization Method for an Optimal Design Application with Mixed Binary and Continuous Variables
1 Motivation
2 Derivative Free Trust-Region Method
3 Adapted Distance for Blade Design Application
4 Toy Problem
5 Preliminary Numerical Results
6 Conclusions
References
Numerical Technologies for Investigating Optimal Control Problems with Free Right-Hand End of Trajectories
1 Introduction
2 The Optimal Control Problems with Free Trajectories at the End of the Time Interval
3 Numerical Technologies for Studying OCP
4 The Optimal Control Problem in the System of Four Semiconductor Quantum Dots
5 Conclusion
References
A Genetic Algorithm Approach for Scheduling Trains Maintenance Under Uncertainty
1 Introduction
2 Literature Review
3 Mathematical Formulation
4 SAA Model
4.1 Property of SAA Model
5 The Solution Method
6 Computational Results
7 Conclusions
References
Data Mining and Data Processing
eDTWBI: Effective Imputation Method for Univariate Time Series
1 Introduction
2 The Proposed Method: eDTWBI
3 Experiments
3.1 Data Description
3.2 Experiment Process
3.3 Imputation Performance Indicator
3.4 Experiments Results
4 Conclusions and Future Work
References
Reweighted 1 Algorithm for Robust Principal Component Analysis
1 Introduction
2 Reweighted-l1 Based Algorithm for RPCA
2.1 Reweighted- l1 for Spare Optimization
2.2 Reweighted-l1 for Solving the CaPCA Problem
3 Numerical Experiments
4 Conclusion
References
A Probability-Based Close Domain Metric in Lifelong Learning for Multi-label Classification
Abstract
1 Introduction
2 Definitions
2.1 Problem Formulation
2.2 The Closeness in Probability of Two Datasets
3 Proposed Model of Lifelong Topic Modeling Using Close Domain Knowledge for Multi-label Classification
4 Experiments and Discussion
4.1 The Datasets
4.2 Experimental Scenarios
4.3 Discussions on Results of Experiments
5 Related Works
6 Conclusions
References
Applying MASI Algorithm to Improve the Classification Performance of Imbalanced Data in Fraud Detection
1 Introduction
2 Related Work
2.1 The Imbalanced Data in the Fraud Detection
2.2 The Approaches for Imbalanced Data Classification
3 Methodology
3.1 SPY and ADASYN Methods
3.2 MASI Algorithm
4 Experimental Results
4.1 Datasets
4.2 Results
5 Conclusion
References
Learning Rough Set Based Classifiers Using Boolean Kernels
1 Introduction
2 Preliminaries
2.1 Support Vector Machine
2.2 SVM with Boolean Kernels in Learning Rule-Based Classifiers for Decision Tables with Symbolic Values
3 Discretization Problem in Rough Set Theory
4 Rough Sets and SVM Hybridization
5 Conclusions
References
Using Support Vector Machine to Monitor Behavior of an Object Based WSN System
1 Introduction
2 System Model
2.1 Mobility Model
2.2 RSS Statistical Model
2.3 System State Model
3 Proposal Techniques
3.1 Architecture Diagram
3.2 Dataset Model
3.3 Support Vector Machine Technique to Classify the Bound Error Classes
4 Simulation Results
5 Conclusion
References
Stacking of SVMs for Classifying Intangible Cultural Heritage Images
1 Introduction
2 Classification of Intangible Cultural Heritage Images
2.1 The Dataset of Intangible Cultural Heritage Images
2.2 Visual Approaches for Classifying Intangible Cultural Heritage Images
3 Experimental Results
3.1 Tuning Parameters
3.2 Classification Results for 17 ICH Categories
3.3 Stacking of SVM Classifiers for Classifying 17 ICH Categories
4 Conclusion and Future Works
References
Assessment of the Water Area in the Lowland Region of the Mekong River Using MODIS EVI Time Series
Abstract
1 Introduction
2 The Study Domain
3 Material and Method
3.1 MODIS Imagery Data
3.2 Imagery Processing
3.3 Water Area Extraction
3.4 Water Area and Water Elevation
4 Results and Discussion
4.1 Temporal Variation of Extracting Water Area
4.2 Spatial Distribution of Extracting Water Area
4.3 Relationship Between Extracting Water Area and Water Elevation
5 Conclusion
Acknowledgements
References
Palmprint Recognition Using Discriminant Local Line Directional Representation
1 Introduction
2 Our Proposed Method
2.1 LLDP
2.2 (2D)2LDA
2.3 Discriminant Local Line Directional Representation
3 Experimental Results
4 Conclusion
References
Speech Assessment Based on Entropy and Similarity Measures
1 Introduction
2 What Is Similarity?
3 The Method
4 Experimental Results
5 Discussion and Conclusions
References
Machine Learning Methods and Applications
Deep Clustering with Spherical Distance in Latent Space
1 Introduction
2 Scaling Problem in a Class of Deep Clustering Algorithms
2.1 Auto-Encoder
2.2 Scaling Problem of Joint-Clustering by Auto-Encoder
3 Proposed Solution
3.1 Spherical Distance
3.2 Application for Deep Clustering with MSSC
4 Numerical Experiment
4.1 Datasets
4.2 Comparative Algorithms
4.3 Experiment Setting
4.4 Experiment Results
5 Conclusion
References
A Channel-Pruned and Weight-Binarized Convolutional Neural Network for Keyword Spotting
1 Introduction
2 Network Architecture
3 Complexity Reduction and Training Algorithms
3.1 Group Sparsity and Channel Pruning
3.2 Theoretical Aspects
3.3 Weight Binarization
4 Experimental Results
5 Conclusion and Future Work
References
Fusing of Deep Learning, Transfer Learning and GAN for Breast Cancer Histopathological Image Classification
1 Introduction
2 Proposed Approach
3 Experiments
3.1 Dataset Description
3.2 Experimental Setup
3.3 Results
4 Conclusion
References
Attentive biLSTMs for Understanding Students' Learning Experiences
1 Introduction
2 Related Work
3 An Attention-Based biLSTM for Understanding Students' Learning Experiences
3.1 Word Embeddings Layer
3.2 biLSTM Layer
3.3 Attention Layer
3.4 Output Layer
4 Experiments
4.1 Dataset
4.2 Evaluation Metrics
4.3 Experimental Setups
4.4 Experimental Results
5 Conclusion
References
Computing Residual Diffusivity by Adaptive Basis Learning via Super-Resolution Deep Neural Networks
1 Introduction
2 Construction of Adaptive Basis via DNNs
2.1 Learning Thinner Structures
2.2 Adversarial Network
3 Experimental Results of Adaptive Basis from SRGAN
4 Conclusions
References
An Intensive Empirical Study of Machine Learning Algorithms for Predicting Vietnamese Stock Prices
1 Introduction
2 Methodology
2.1 Autoregressive Integrated Moving-Average
2.2 Artificial Neural Network
2.3 Hybrid Model of ARIMA and ANN
3 Empirical Results
3.1 Data Collection
3.2 Data Preprocessing
3.3 Evaluation Method
3.4 Time Series Cross-Validation Procedure
3.5 Results and Analysis
4 Conclusion
A Appendix
A.1 List of Top 20 Stocks of VN-Index
A.2 Application Interface
References
Improvement of Production Layout in the Furniture Industry in Indonesia with the Concept of Group Technology
1 Introduction
2 Methods
3 Results
4 Discussions and Conclusions
References
Reinforcement Learning in Stock Trading
1 Introduction
2 Literature Review
3 Our Contribution
4 Reinforcement Learning
5 Experiments
5.1 Datasets
5.2 Experimental Results
6 Conclusions
References
A Survey on Forecasting Models for Preventing Terrorism
1 Introduction and Background
2 Rationale for Terrorism
2.1 Economic and Social Deprivation
2.2 State Weakness (Failed State) (Syria, Iraq, Libya, CAR, Somali)
2.3 External Caused Based on Invasion (Iraq, Afghanistan, Libya)
2.4 Religious Fundamentalism and Extremism
3 Types of Terrorism
3.1 Nuclear Terrorism
3.2 Cyber Terrorism
4 Means of Combating Terrorism
4.1 Counterterrorism Model, Machine Learning Approach
4.2 Social Network Analysis Model
4.3 Dynamic Bayesian Network
4.4 Terrorist Group Prediction Model (TGPM)
4.5 Mathematical Models for Understanding Radicalization and Terrorism MMURT
4.6 Hawkes Process Modeling
5 Conclusions and Future Works
References
On the Design of a Privacy Preserving Collaborative Platform for Cybersecurity
1 Introduction
2 Information Sharing and Privacy-Aware Design Principles
2.1 Benefits of Information Sharing in Mitigating Cyber and Physical Threats
2.2 Privacy-Aware Platform Design
3 Privacy Preserving Computation on Cloud Platforms
3.1 Secure Content-Based Routing
3.2 Secure Data Access Control
3.3 Homomorphic Encryption-Based Cloud Analysis Platform
4 Use Case: A Privacy Preserving Detection of Brute Force Attacks
5 Conclusion
References
Secure and Robust Watermarking Scheme in Frequency Domain Using Chaotic Logistic Map Encoding
1 Introduction
2 Preliminaries
2.1 Chaotic Logistic Map
2.2 Discrete Cosine Transform (DCT) and Quantized DCT (QDCT)
2.3 Singular Value Decomposition (SVD)
3 Proposed Scheme
3.1 Watermarking Embedding
3.2 Watermarking Extracting
4 Performance Evaluations of the Proposed System
4.1 Sensitive Key Analysis
4.2 Adjacent Pixels Correlation Analysis
4.3 Imperceptibility and Robustness Evaluation of the Watermarking System
5 Conclusion
References
Knowledge Information and Engineering Systems
An Improvement of Applying Multi-objective Optimization Algorithm into Higher Order Mutation Testing
1 Introduction
2 Proposed Approach and Related Works
3 Supporting Tool and PUTs
4 Results Analysis
5 Conclusions
References
Belief Merging for Possibilistic Belief Bases
1 Introduction
2 Preliminary
2.1 Possibilistic Logic
2.2 Belief Merging
3 Belief Merging for Possibilistic Logic
4 Logical Properties
5 Conclusion
References
Discrete Time Sliding Mode Control of Milling Chatter
1 Introduction
2 Modeling of Milling Process with Active Control
2.1 Active Vibration Damper (AVD) for Active Control Mechanism
3 Discrete Time Sliding Mode Control with Type-2 Fuzzy Compensation
4 Numerical Analysis
5 Conclusion
References
Efficient Processing of Recursive Joins on Large-Scale Datasets in Spark
1 Introduction
2 Related Works
2.1 Recursive Join in MapReduce
2.2 Apache Spark
2.3 Intersection Bloom Filter
2.4 Intersection Bloom Join Algorithm
3 Optimizing Recursive Joins
4 Experiment and Evaluation
4.1 Describe Clusters and Datasets
4.2 Evaluation Method
4.3 Evaluate the Approaches
5 Conclusion and Future Work
5.1 Conclusion
5.2 Future Work
References
New Feed Rate Optimization Formulation in a Parametric Domain for 5-Axis Milling Robots
1 Introduction
2 Differential Inverse Kinematics of 5-Axis CNC Machines in a Parametric Domain
3 Optimization of the Feed Rate
4 Conclusions
References
Opensource Based IoT Platform and LoRa Communications with Edge Device Calibration for Real-Time Monitoring Systems
1 Introduction
2 System Description
2.1 System Model
2.2 LoRa and LoRaWAN
3 The Opensource Platform
3.1 Opensource Based IoT Platform - BKThings
3.2 Implementation
4 Data Processing and Visualization Results
4.1 Data Processing
4.2 Data Visualization
5 Conclusions
References
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Advanced Computational Methods for Knowledge Engineering

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