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• Session 1. Modeling and Simulation of Biological Processes
• A Formal Model for Gene Regulatory Networks with Time Delays
• Modelling fim Expression in Escherichia Coli K12
• Study of the Structural Pathology Caused by CYP2C9 Polymorphisms towards Flurbiprofen Metabolism Using Molecular Dynamics Simulation
• 3D Structure Modeling of a Transmembrane Protein, Fatty Acid Elongase
• Session 2. Gene Expression Analysis
• Sequential Application of Feature Selection and Extraction for Predicting Breast Cancer Aggressiveness
• On Assigning Individuals from Cryptic Population Structures to Optimal Predicted Subpopulations: An Empirical Evaluation of Non-parametric Population Structure Analysis Techniques
• Extended Constraint-Based Boolean Analysis: A Computational Method in Genetic Network Inference
• Mining LINE-1 Characteristics That Mediate Gene Expression
• Session 3. Biological Sequence Analysis and Network Reconstruction
• Mining Regulatory Elements in Non-coding Regions of Arabidopsis thaliana
• Prediction of Non-coding RNA and Their Targets in Spirulina platensis Genome
• Reconstruction of Starch Biosynthesis Pathway in Cassava Using Comparative Genomic Approach
• Session 4. Bio-data Visualization and Biological Databases
• Catalog of Genetic Variations (SNPs and CNVs) and Analysis Tools for Thai Genetic Studies
• The Genome Atlas Resource
• INVERTER: INtegrated Variable numbER Tandem rEpeat findeR
• Design of an Enterobacteriaceae Pan-Genome Microarray Chip
• Session 5. Medical and Biomedical Informatics
• Multi-objective Particle Swarm Optimisation for Phase Specific Cancer Drug Scheduling
• A Vaccine Strategy for Plant Allergy by RNA Interference
• An in Silico Approach
• Unsupervised Algorithms for Population Classification and Ancestry Informative Marker Selection
• Genome-Based Screening for Drug Targets Identification: Application to Typhoid Fever.

This book constitutes the refereed proceedings of the First International Conference on Computational Systems-Biology and Bioinformatics, CSBio 2010, held in Bangkok, Thailand, in November 2010. The 19 revised full papers presented were carefully reviewed and selected from a total of 48 submissions. The papers cover a wide range of topics and are organized in five topical sections on modeling and simulation of biological processes, gene expression analysis, biological sequence analysis and network reconstruction, bio-data visualization and biological databases, as well as medical and biomedical informatics.

• Agents and Complex Systems.- Data Mining and Its Applications.- Evolutionary Algorithms and Optimization.- Intelligent Systems and their Applications.- Nature Inspired Creative Computing.- Smart Workspace and Image Processing.
• (source: Nielsen Book Data)

This PALO volume constitutes the Proceedings of the 19th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES 2015), held in Bangkok, Thailand, November 22-25, 2015. The IES series of conference is an annual event that was initiated back in 1997 in Canberra, Australia. IES aims to bring together researchers from countries of the Asian Pacific Rim, in the fields of intelligent systems and evolutionary computation, to exchange ideas, present recent results and discuss possible collaborations. Researchers beyond Asian Pacific Rim countries are also welcome and encouraged to participate. The theme for IES 2015 is "Transforming Big Data into Knowledge and Technological Breakthroughs". The host organization for IES 2015 is the School of Information Technology (SIT), King Mongkut's University of Technology Thonburi (KMUTT), and it is technically sponsored by the International Neural Network Society (INNS). IES 2015 is collocated with three other conferences; namely, The 6th International Conference on Computational Systems-Biology and Bioinformatics 2015 (CSBio 2015), The 7th International Conference on Advances in Information Technology 2015 (IAIT 2015) and The 10th International Conference on e-Business 2015 (iNCEB 2015), as a major part of series of events to celebrate the SIT 20th anniversary and the KMUTT 55th anniversary.
(source: Nielsen Book Data)

• Artificial Intelligence Aided Neurodevelopmental Disorders Diagnosis: Techniques Revisited.- Deep Learning Implementation for Dark Matter Particle Detection.- Augmentation of Handwritten Devanagari Character Dataset Using DCGAN.- Deep Reinforcement Learning for Optimal Traffic Control.- Ensemble Semi-Supervised Machine Learning Algorithm for Classifying Complaint Tweets.- Underwater Image Enhancement Using Fusion Stretch Method.- A Novel Approach for Semantic Microservices Description and Discovery towards Smarter Applications.
• (source: Nielsen Book Data)

This book is a collection of peer-reviewed best selected research papers presented at the Second International Conference on Machine Intelligence and Smart Systems (MISS 2021), organized during September 24-25, 2021, in Gwalior, India. The book presents new advances and research results in the fields of machine intelligence, artificial intelligence and smart systems. It includes main paradigms of machine intelligence algorithms, namely (1) neural networks, (2) evolutionary computation, (3) swarm intelligence, (4) fuzzy systems and (5) immunological computation. Scientists, engineers, academicians, technology developers, researchers, students and government officials will find this book useful in handling their complicated real-world issues by using machine intelligence methodologies.
(source: Nielsen Book Data)

• Synesthetic Learning Pedagogy (SLP): An Exploratory Investigation.- MSB/LSB Prediction Based Reversible Data Hiding In Encrypted Images: A Survey.- A Review of Image Enhancement Techniques in Medical Imaging.- Smartphone User Identification and Authentication based on Raw Accelerometer Walking Activity Data Using Convolutional Neural Networks.- Elastic Optical Network: A Promising Solution For Future Communication Networks Considering Differentiated CoS.- Smart Home Energy Prediction With GTU Recurrent Neural Network Model.
• (source: Nielsen Book Data)

This book is a collection of peer-reviewed best selected research papers presented at the First International Conference on Machine Intelligence and Smart Systems 2020 (MISS 2020), organized during September 24-25, 2020, in Gwalior, India. The book presents new advances and research results in the fields of machine intelligence, artificial intelligence and smart systems. It includes main paradigms of machine intelligence algorithms, namely (1) neural networks, (2) evolutionary computation, (3) swarm intelligence, (4) fuzzy systems and (5) immunological computation.
(source: Nielsen Book Data)

• Data Mining.- Healthcare Analytics-Improving Healthcare Outcomes using Big Data Analytics.- Human Activity Recognition.- Image Processing and Computer Vision.- Natural Language Processing.- Recommender Systems.- The 13th International Workshop on Artificial Intelligence and Cybersecurity.
• (source: Nielsen Book Data)

The two-volume set CCIS 1332 and 1333 constitutes thoroughly refereed contributions presented at the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020.*For ICONIP 2020 a total of 378 papers was carefully reviewed and selected for publication out of 618 submissions. The 191 papers included in this volume set were organized in topical sections as follows: data mining; healthcare analytics-improving healthcare outcomes using big data analytics; human activity recognition; image processing and computer vision; natural language processing; recommender systems; the 13th international workshop on artificial intelligence and cybersecurity; computational intelligence; machine learning; neural network models; robotics and control; and time series analysis. * The conference was held virtually due to the COVID-19 pandemic.
(source: Nielsen Book Data)

• Computational Intelligence.- Machine Learning.- Neural Network Models.- Robotics and Control.- Time Series Analysis.
• (source: Nielsen Book Data)

The two-volume set CCIS 1332 and 1333 constitutes thoroughly refereed contributions presented at the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020.*For ICONIP 2020 a total of 378 papers was carefully reviewed and selected for publication out of 618 submissions. The 191 papers included in this volume set were organized in topical sections as follows: data mining; healthcare analytics-improving healthcare outcomes using big data analytics; human activity recognition; image processing and computer vision; natural language processing; recommender systems; the 13th international workshop on artificial intelligence and cybersecurity; computational intelligence; machine learning; neural network models; robotics and control; and time series analysis. * The conference was held virtually due to the COVID-19 pandemic.
(source: Nielsen Book Data)

• Intro
• Preface
• Organization
• Contents
• Part I
• Human-Computer Interaction
• A Genetic Feature Selection Based Two-Stream Neural Network for Anger Veracity Recognition
• 1 Introduction
• 2 Method
• 2.1 Dataset
• 2.2 Network Architecture
• 2.3 Two-Stream Architecture
• 2.4 Data Pre-processing and Feature Selection
• 3 Experiments and Discussions
• 3.1 Experiment Settings
• 3.2 Baseline Model
• 3.3 Experiments on GFS and Two-Stream Architecture
• 3.4 Discussion
• 4 Conclusion and Future Work
• References

• An Efficient Joint Training Framework for Robust Small-Footprint Keyword Spotting
• 1 Introduction
• 2 System Description
• 2.1 Masking-Based Speech Enhancement Method
• 2.2 Feature Transformation Block
• 2.3 Keyword Spotting System
• 3 Experiments and Results
• 3.1 Experimental Settings
• 3.2 Results
• 4 Conclusions
• References
• Hierarchical Interactive Matching Network for Multi-turn Response Selection in Retrieval-Based Chatbots
• 1 Introduction
• 2 Related Work
• 3 Hierarchical Interactive Matching Network
• 3.1 Task Description
• 3.2 Model Overview

• 3.3 Multi-level Attention Representation
• 3.4 Two-Level Hierarchical Interactive Matching
• 3.5 Aggregation
• 4 Experiments
• 4.1 Dataset
• 4.2 Evaluation Metric
• 4.3 Baseline Models
• 4.4 Experiment Settings
• 4.5 Experiment Results
• 4.6 Discussions
• 5 Conclusion
• References
• Investigation of Effectively Synthesizing Code-Switched Speech Using Highly Imbalanced Mix-Lingual Data
• 1 Introduction
• 2 Related Work
• 2.1 Data Sets for the CS TTS
• 2.2 Text Representation for CS TTS
• 3 Proposed Method
• 3.1 General Framework
• 3.2 CS Front-End
• 3.3 Synthesis Module

• 4 Data Description
• 5 Experiments
• 5.1 Input Representations
• 5.2 Experimental Setup
• 5.3 Experimental Results
• 6 Conclusion
• References
• Image Processing and Computer Vision
• A Feature Fusion Network for Multi-modal Mesoscale Eddy Detection
• 1 Introduction
• 2 Related Work
• 2.1 Non-deep Learning Algorithms
• 2.2 Deep Learning Algorithms
• 3 Methodology
• 3.1 FusionNet
• 3.2 The Loss Function
• 4 Experiments
• 4.1 The Multi-modal Dataset
• 4.2 Experimental Results
• 5 Conclusion
• References
• A Hybrid Self-Attention Model for Pedestrians Detection
• 1 Introduction

• 2 Related Work
• 2.1 Pedestrian Detection
• 2.2 Attention Mechanism
• 3 Proposed Method
• 3.1 Revisiting the CSP Detector
• 3.2 Channel Attention
• 3.3 Spatial Attention
• 3.4 Hybrid Attention Fusion Strategy
• 4 Experiments
• 4.1 Dataset and Evaluation Metrics
• 4.2 Ablation Study
• 4.3 Comparison with State of the Arts
• 5 Conclusion
• References
• DF-PLSTM-FCN: A Method for Unmanned Driving Based on Dual-Fusions and Parallel LSTM-FCN
• 1 Introduction
• 2 Related Work
• 3 DF-PLSTM-FCN
• 3.1 Driving Model
• 3.2 Network Structure
• 3.3 Feature Fusion
• 3.4 Decision Fusion

The three-volume set of LNCS 12532, 12533, and 12534 constitutes the proceedings of the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020. Due to COVID-19 pandemic the conference was held virtually.The 187 full papers presented were carefully reviewed and selected from 618 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The first volume, LNCS 12532, is organized in topical sections on human-computer interaction; image processing and computer vision; natural language processing.
(source: Nielsen Book Data)

• Intro
• Preface
• Organization
• Contents
• Part II
• Computational Intelligence
• A Novel Mathematic Entorhinal-Hippocampal System Building Cognitive Map
• 1 Introduction
• 2 Model Description
• 2.1 Architecture of the System
• 2.2 Neuron Model
• 2.3 Learning Algorithm
• 2.4 Visual Calibration
• 3 Experiment Result
• 3.1 Environment
• 3.2 Experiment for Cognitive Map Building
• 3.3 Experiment for Distribution of the Weight
• 3.4 Experiment for Property Verification
• 4 Discussion
• 4.1 Discussion on Cells and Parameters of the Model

• 4.2 Discussion on the Distribution of the Weight
• 4.3 Discussion on the Activities of Place Cells
• 5 Conclusion
• References
• Adaptive Risk-Return Control in Motor Planning
• 1 Introduction
• 2 Modeling
• 3 Model Evaluation
• 4 Summary and Discussion
• References
• Discrete Mother Tree Optimization for the Traveling Salesman Problem
• 1 Introduction
• 2 Discrete Mother Tree Algorithm (DMTO)
• 2.1 Solution Representation
• 2.2 Swap Operation
• 2.3 Updating the TMT
• 2.4 Updating the Solutions of the FPCTs Group
• 2.5 Updating the Solutions of FCTs Group

• 2.6 Updating the Solutions of LPCTs Group
• 2.7 DMTO Climate Change
• 3 Discrete Particle Swarm Optimization for TSPs
• 3.1 Discrete Particle Swarm Optimization (DPSO)
• 3.2 Updated Version of Discrete Particle Swarm Optimization (UDPSO)
• 4 Experimentation
• 5 Conclusion and Future Works
• References
• Dynamic Cloud Workflow Scheduling with a Heuristic-Based Encoding Genetic Algorithm
• 1 Introduction
• 2 Definition and Background
• 2.1 Workflow Modeling
• 2.2 Resource Modeling
• 2.3 Extended CPM
• 2.4 Objective Functions
• 3 Algorithm
• 3.1 Batch Processing

• 3.2 Scheduling Generator
• 3.3 Heuristic-Based Encoding GA
• 4 Experiments and Analysis
• 4.1 Efficiency of Single Heuristic Rules
• 4.2 Heuristic-Based GA vs. Pure GA
• 5 Conclusion
• References
• Multi-strategy Evolutionary Computation for Automated Jigsaw Puzzles
• 1 Introduction
• 2 Related Work
• 3 The Multi-strategy Evolution Algorithm
• 3.1 Compatibility Between Pieces and the Objective Function
• 3.2 Selector
• 3.3 Elite-Based Crossover
• 3.4 Four-Strategy Mutation
• 3.5 Diversity Enhancement Strategy
• 4 Experiments
• 4.1 Experimental Setup and Test Sets

• 4.2 Performance Metrics
• 4.3 Comparison Results
• 4.4 In-Depth Performance of MSEA
• 5 Conclusion
• References
• Real Valued Card Counting Strategies for the Game of Blackjack
• 1 Introduction
• 2 The Game of Blackjack
• 2.1 Card Counting Principles
• 2.2 Efficiency Metrics
• 2.3 Card Counting Strategies
• 3 Methods
• 3.1 Genetic Algorithm
• 3.2 Expert Advisor Mobile Application
• 4 Experiments and Results
• 4.1 Integer Weights
• 5 Conclusions
• References
• Machine Learning
• A Feature Selection Approach to Visual Domain Adaptation in Classification
• 1 Introduction

The three-volume set of LNCS 12532, 12533, and 12534 constitutes the proceedings of the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020. Due to COVID-19 pandemic the conference was held virtually. The 187 full papers presented were carefully reviewed and selected from 618 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The second volume, LNCS 12533, is organized in topical sections on computational intelligence; machine learning; robotics and control.
(source: Nielsen Book Data)

• Intro
• Preface
• Organization
• Contents
• Part III
• Biomedical Information
• Classification of Neuroblastoma Histopathological Images Using Machine Learning
• 1 Introduction
• 2 Methodology
• 2.1 Dataset
• 2.2 Experimental Setup
• 3 Results
• 4 Discussion
• 5 Conclusion
• References
• Data Mining ENCODE Data Predicts a Significant Role of SINA3 in Human Liver Cancer
• 1 Introduction
• 2 Methods
• 3 Results
• 3.1 Co-location of TFBS Analysis
• 3.2 HBV-transfection Effect on Histone Modification
• 4 Discussion
• References

• Diabetic Retinopathy Detection Using Multi-layer Neural Networks and Split Attention with Focal Loss
• 1 Introduction
• 2 Related Work
• 3 Methodology
• 3.1 Proposed Approach
• 3.2 Dataset
• 3.3 Data Pre-processing
• 3.4 Metrics for Performance Evaluation
• 4 Experimental Results and Discussion
• 5 Analysis
• 6 Conclusion
• References
• Enhancer-DSNet: A Supervisedly Prepared Enriched Sequence Representation for the Identification of Enhancers and Their Strength
• 1 Introduction
• 2 Materials and Methods
• 3 Proposed Enhancer-DSNet Methodology
• 4 Benchmark Dataset

• 5 Evaluation Metrics
• 6 Experimental Setup and Results
• 6.1 Results
• 7 Conclusion
• References
• Machine Learned Pulse Transit Time (MLPTT) Measurements from Photoplethysmography
• 1 Introduction
• 2 Design
• 2.1 Machine Learned Pulse Transit Time
• 2.2 HeartPy Pulse Transit Time
• 3 Analysis
• 3.1 Methods
• 4 Results
• 4.1 BIDMC Patient 6 Drilldown
• 5 Discussion
• 5.1 Limitations
• 6 Conclusion
• References
• Weight Aware Feature Enriched Biomedical Lexical Answer Type Prediction
• 1 Introduction
• 2 Related Work
• 3 Methodology
• 3.1 Pre-processing

• 3.2 Feature Selection
• 3.3 LAT Prediction
• 4 Experimental Study
• 4.1 Dataset and Experiment Configuration
• 4.2 Evaluation Metrics and Baseline
• 4.3 Results and Discussion
• 5 Conclusion and Future Work
• References
• Neural Data Analysis
• Decoding Olfactory Cognition: EEG Functional Modularity Analysis Reveals Differences in Perception of Positively-Valenced Stimuli
• 1 Introduction
• 2 Methodology
• 2.1 Recruitment of Participants
• 2.2 Experimental Protocol
• 2.3 EEG Data Acquisition and Preprocessing
• 2.4 EEG Data Analysis
• Community Detection
• 3 Results

• 3.1 Partitioning the Functional Connectivity Networks
• 3.2 Inter-module Metrics
• 3.3 Intra-module Metrics
• 4 Discussion
• 4.1 Alterations in the Inter-module Metrics in the Community Functional Connectivity Organisation
• 4.2 Variations in the Intra-module Metrics in the Community Functional Connectivity Organisation
• 5 Conclusions
• A Appendix: Anatomical Segregation of ROIs in Communities
• References
• Identifying Motor Imagery-Related Electroencephalogram Features During Motor Execution
• 1 Introduction
• 2 Method
• 2.1 Experiment and Preprocessing Procedure

The three-volume set of LNCS 12532, 12533, and 12534 constitutes the proceedings of the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020. Due to COVID-19 pandemic the conference was held virtually. The 187 full papers presented were carefully reviewed and selected from 618 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The third volume, LNCS 12534, is organized in topical sections on biomedical information; neural data analysis; neural network models; recommender systems; time series analysis.
(source: Nielsen Book Data)