
Recent Trends and Future Technology in Applied Intelligence
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This book constitutes the thoroughly refereed proceedings of the 31st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2018, held in Montreal, QC, Canada, in June 2018.
The 53 full papers and 33 short papers presented were carefully reviewed and selected from 146 submissions. They are organized in the following topical sections: constraint solving and optimization; data mining and knowledge discovery; evolutionary computation; expert systems and robotics; knowledge representation, machine learning; meta-heuristics; multi-agent systems; natural language processing; neural networks; planning, scheduling and spatial reasoning; rough sets, Internet of Things (IoT), ubiquitous computing and big data; data science, privacy, and security; inelligent systems approaches in information extraction; and artificial intelligence, law and justice.
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Content
- Intro
- Preface
- Organization
- Contents
- Constraint Solving and Optimization
- A Method for the Online Construction of the Set of States of a Markov Decision Process Using Answer Set Programming
- 1 Introduction
- 2 Background
- 2.1 MDP and Reinforcement Learning
- 2.2 Answer Set Programming
- 3 Online ASP for MDP: oASP(MDP)
- 4 Tests and Results
- 4.1 First Test: Changes in the Wall-Free-Space Ratio
- 4.2 Second Test: Changes in the Transition Probabilities
- 5 Related Work
- 6 Conclusion
- References
- Hardware/Software Co-design for Template Matching Using Cuckoo Search Optimization
- 1 Introduction
- 2 Theoretical Background
- 3 Hardware Architecture
- 4 Results
- 5 Conclusion
- References
- Optimziation Methods for Beacon Based Foraging Algorithms
- 1 Introduction
- 2 Related Work
- 3 The Rostering Technique
- 4 Rostering Experimental Analysis
- 5 Network Optimizaiton
- 6 NetOpt Experimental Analysis
- 7 Future Work
- 8 Conclusions
- References
- On Using ``Stochastic Learning on the Line'' to Design Novel Distance Estimation Methods
- 1 Introduction
- 2 Distance Estimation: Core Concepts
- 2.1 Distance Estimation Functions (DEFs)
- 3 The Adaptive Tertiary Search and Its Use in DE
- 3.1 Updating Search Intervals
- 3.2 The Corresponding LA
- 3.3 The Corresponding Environment
- 4 Testing and Results: 2-Dimensional Environments
- 5 Conclusions
- References
- Data Mining and Knowledge Discovery
- Person Re-identification Using Masked Keypoints
- 1 Introduction
- 2 Person Re-identification
- 3 A Keypoint-Based Re-ID Method
- 3.1 Person Detection
- 3.2 Person Re-identification
- 4 Experiments
- 4.1 Data Collection
- 4.2 Parameters Setting
- 4.3 Comparing Our Method
- 5 Conclusions
- References
- Knowledge Discovery Process for Detection of Spatial Outliers
- 1 Introduction
- 2 Knowledge Discovery Process for Detection of Spatial Outliers
- 2.1 Data Preparation
- 2.2 Neighborhood Definition
- 2.3 Outlier Detection and Filtering
- 2.4 Neighborhood Description
- 2.5 Group Outlier Detection
- 2.6 Information Analysis
- 3 Proof of Concept
- 4 Conclusion
- References
- Text Modeling Using Multinomial Scaled Dirichlet Distributions
- 1 Introduction
- 2 Multinomial and Dirichlet Compound Multinomial
- 3 Multinomial Scaled Dirichlet (MSD) Distribution
- 4 MSD Mixture Model Learning
- 5 Experimental Results
- 6 Conclusion
- References
- A Comparison of Knee Strategies for Hierarchical Spatial Clustering
- 1 Introduction
- 2 Background
- 2.1 Hierarchical Clustering
- 2.2 Distance Measures
- 2.3 Knee Determination
- 3 Spatial Data and Preparation
- 4 Results
- 5 Conclusion
- References
- Credit Card Default Prediction as a Classification Problem
- Abstract
- 1 Introduction
- 2 Related Works
- 3 Proposed Credit-Card Default Prediction Approach
- 4 Classification Rules Generation
- 4.1 Creation of Initial Population
- 4.2 Genetic Operator
- 4.3 Evaluation of Individuals of the Initial Population
- 5 Experimental Setup
- 5.1 Description of the Experimental Dataset
- 5.2 Evaluation Criteria
- 6 Empirical Analysis
- 6.1 Experiment 1: GP Performance
- 6.2 Experiment 2: Comparative Study
- 7 Conclusion
- References
- Interactive Discovery of Statistically Significant Itemsets
- 1 Introduction
- 2 Preliminaries and Problem Statement
- 3 The Proposed IDPI Approach
- 3.1 Compressing the Database Using the Itemset-Tree Structure
- 3.2 Representing Queries Using the Query-Tree Structure
- 3.3 Processing Queries Efficiently Using a Query-Tree
- 4 Experimental Evaluation
- 5 Conclusion
- References
- Sampling Community Structure in Dynamic Social Networks
- 1 Introduction
- 2 Related Work
- 3 Preliminaries
- 3.1 Notations
- 3.2 Problem Formulation
- 4 Proposed Approach
- 4.1 Initialization
- 4.2 First Time Step
- 4.3 Startup Graph Selection
- 4.4 Comparing Startup Graph to Previous Graphs
- 4.5 Performing Extra Queries
- 4.6 Handling Storage Limitations
- 5 Experiments
- 5.1 Datasets
- 5.2 Experimental Setup
- 5.3 Evaluation Metrics
- 5.4 Results and Discussion
- 6 Conclusion
- References
- Predicting Success of a Mobile Game: A Proposed Data Analytics-Based Prediction Model
- Abstract
- 1 Introduction
- 2 Predicting the Success of a Mobile Game App
- 3 Methodology
- 3.1 Dataset Preparation, Configuration and Analysis
- 4 Data Analysis
- 4.1 Mobile Games Features
- 4.2 Users Behavior Dataset
- 5 Results and Discussion
- 5.1 Final Prediction Outcomes
- 5.2 Prediction from Integration of Dual Datasets
- 5.3 Proposed Actionable Model Validation
- 6 Conclusion
- References
- Online Anomaly Detection Using Random Forest
- 1 Introduction
- 2 Anomaly Detection for Streaming Data
- 3 Datasets and Evaluation Metrics
- 3.1 Datasets
- 3.2 Evaluation Metrics
- 4 Analysis of Random Trees
- 4.1 Deriving the Number of Trees and Height of Trees Using Theory of Coupon Collector Problem
- 4.2 Discussion on Score Combination
- 4.3 Building Detection Trees Using Feature Clustering
- 4.4 Experimental Results
- 5 Conclusion
- References
- Investigating Effectiveness of Linguistic Features Based on Speech Recognition for Storytelling Skill Assessment
- 1 Introduction
- 2 Related Work
- 3 Multimodal Storytelling Interaction Dataset
- 4 Multimodal Features
- 5 Experiments
- 5.1 Experimental Setting
- 5.2 Experimental Results
- 6 Discussion
- 6.1 Analysis of the Contributions of Each Linguistic Feature
- 6.2 Limitation and Future Work
- 7 Conclusions
- References
- Visual Analytics Based Authorship Discrimination Using Gaussian Mixture Models and Self Organising Maps: Application on Quran and Hadith
- Abstract
- 1 Introduction
- 2 Stylometric Features
- 2.1 Author's Pronoun Based Feature
- 2.2 On the Use of "???" (Father of) for Naming People
- 2.3 Frequency of Some Discriminative Words
- 2.4 COST Parameter Based Feature
- 2.5 Word Length Frequency
- 2.6 Frequency of the Coordination Conjunction «?» (Meaning AND)
- 2.7 Frequency of the Conjunction «?» at the Beginning of Sentence
- 3 Visual Analytics Based Clustering Methods
- 3.1 Principal Components Analysis
- 3.2 Gaussian Mixture Model Based Clustering
- 3.3 Self-Organizing Map Based Clustering
- 4 Discussion
- References
- An Optimization Approach Based on Collective Correlation Coefficient for Biomarker Extraction in the Classification of Alzheimer's Disease
- Abstract
- 1 Introduction
- 2 Related Works
- 3 Methodology
- 4 Materials and Methods
- 4.1 Data Acquisition
- 4.2 Features
- 4.3 The Models
- 5 Experimental Results
- 6 Conclusion
- Acknowledgments
- References
- Evolutionary Computation
- Lazy Conflict Detection with Genetic Algorithms
- 1 Introduction
- 2 Working Example
- 3 Lazy Conflict Detection Using Genetic Algorithms
- 4 Evaluation
- 5 Future Work
- 6 Conclusion
- References
- An Algorithm for Combinatorial Double Auctions Based on Cooperative Coevolution of Particle Swarms
- Abstract
- 1 Introduction
- 2 Problem Formulation for Combinatorial Double Auctions
- 3 Fitness Function
- 4 Discrete Cooperative Coevolving Particle Swarm Optimization (DCCPSO) Algorithm
- 5 Numerical Results
- 6 Conclusions
- Acknowledgment
- References
- Partition Crossover Evolutionary Algorithm for the Team Orienteering Problem with Time Windows
- 1 Introduction
- 2 Problem Description
- 2.1 Mathematical Formulation
- 3 Evolutionary Algorithm Based on Partition Crossover (EAPX)
- 3.1 Initial Population
- 3.2 Local Search
- 3.3 Partition Crossover for TOPTW
- 3.4 Illustrative Example
- 4 Computational Experiments
- 4.1 Experimental Setup
- 4.2 Results and Discussion
- 5 Conclusion
- References
- A High Winning Opportunities Intraday Volatility Trading Method Using Artificial Immune Systems
- Abstract
- 1 Introduction
- 2 Artificial Immune Intraday Volatility Trading Method
- 2.1 Intraday Volatility Mean Reversion Grid Trading
- 2.2 Index Equilibrium Point Forecasting
- 3 Simulation and Performance
- 3.1 Index Forecasting Test
- 3.2 Intraday Volatility Mean Reversion Grid Trading Test
- 4 Conclusion and Future Works
- References
- Expert Systems and Robotics
- Joint Angle Error Reduction for Humanoid Robots Using Dynamics Learning Tree
- Abstract
- 1 Introduction
- 1.1 Communication Error of Angle Sensor
- 1.2 Error Between Command and Sensor Values
- 2 Learning Method
- 2.1 Proposed Learning Method: Step 1: Complementation for Angle Sensor Values
- 2.2 Proposed Learning Method: Step 2: Estimation of Error between Command and Sensor Values
- 2.3 Dynamics Learning Tree
- 3 Experiments
- 3.1 Method
- 3.2 Results
- 4 Consideration
- 5 Conclusion
- References
- Closed-Loop Push Recovery for an Inexpensive Humanoid Robot
- 1 Introduction
- 2 Related Work
- 3 Approach
- 3.1 Hardware
- 3.2 Closed-Loop Control
- 4 Evaluation
- 4.1 Results
- 5 Discussion
- References
- Robot Magic: A Robust Interactive Humanoid Entertainment Robot
- 1 Introduction
- 2 Related Work
- 3 Agent Design
- 3.1 Perception Module: Supporting Recognition and Interaction
- 3.2 Learning Module: Adapting to the Environment
- 3.3 Control Module: The Hardware-Software Interface
- 3.4 Planning Module: Magic Tricks as Finite State Machines
- 3.5 Fault Tolerance and Robustness
- 4 A Full Magic Act
- 5 Evaluation
- 6 Discussion and Future Work
- References
- A Probabilistic Model for Automobile Diagnosis System: Combining Bayesian Estimator and Expert Knowledge
- 1 Introduction
- 2 Related Work
- 3 Proposed Model
- 3.1 Learning Process
- 3.2 Learning Function
- 4 Experimentation
- 4.1 Sigmoid function
- 4.2 Heuristics
- 5 Conclusion and Future Work
- References
- Knowledge Representation
- Socially-Aware Recommendation for Over-Constrained Problems
- 1 Introduction
- 2 Working Example
- 3 Building Synthetic Homogeneous Groups
- 4 Applying Group Aggregation Functions and Recommending Products to Groups
- 5 Evaluation
- 6 Conclusion and Future Work
- References
- Formalizing Arguments From Cause-Effect Rules
- 1 Introduction
- 2 Cause-Effect Rules
- 3 Dung's Argumentation Framework and Weighted Argumentation Framework
- 4 Formalisation of Cause-Effect Rules as WAF
- 5 Reasoning in the Obtained WAF
- 6 Conclusion
- References
- Merging Guaranteed Possibilistic Bases to Rank IDS Alerts
- 1 Introduction
- 2 Instantiated First Order (IFO) Formulas bouzar2015instantiated,ref6
- 3 IFO Guaranteed Possibilistic Base
- 4 Guaranteed Possibilistic Merging
- 5 Guaranteed Possibilistic Fusion to Rank IDS Alerts
- 5.1 Merging Experts Preferences
- 5.2 Ranking IDS Alerts Using Security Experts' Preferences
- 6 Conclusion
- References
- Transformation Between CP-net and CPC-net
- 1 Introduction
- 2 Background
- 3 Constructing the CPC-net from a Given CP-net
- 4 Constructing the CP-net from a Given CPC-net
- 5 Conclusions
- References
- Machine Learning
- Online Detection of Shill Bidding Fraud Based on Machine Learning Techniques
- Abstract
- 1 Introduction
- 2 Related Works
- 3 Construction of Shill Bidding Dataset
- 3.1 Raw Auction Data
- 3.2 SB Patterns and Weights
- 3.3 SB Measurement
- 4 Clustering Shill Bidding Data
- 5 Labelling Shill Bidding Data
- 6 Sampling Shill Bidding Data
- 7 SVM Classification of Shill Bidding
- 8 Simulation
- 9 Conclusion
- References
- Efficient Examination of Soil Bacteria Using Probabilistic Graphical Models
- 1 Introduction
- 2 Data Preprocessing
- 3 A Soil Bacteria Bayesian Network
- 4 A Soil Bacteria Sum-Product Network
- 5 Conclusion
- References
- Object Detection in Images Based on Homogeneous Region Segmentation
- 1 Introduction
- 2 Related Works
- 3 Proposed Method
- 3.1 Image Pre-processing
- 3.2 Region Growing Segmentation
- 3.3 Region Merging
- 4 Experimental Evaluation
- 5 Conclusions
- References
- Optimization of Just-in-Time Adaptive Interventions Using Reinforcement Learning
- 1 Introduction
- 2 Related Work
- 3 Drawing on RL for JITAI Optimization
- 4 Testbeds and Results
- 5 Discussion and Future Work
- 6 Conclusion
- References
- EP-Based Infinite Inverted Dirichlet Mixture Learning: Application to Image Spam Detection
- 1 Introduction
- 2 Model Specification
- 2.1 Finite Inverted Dirichlet Mixture Model
- 2.2 Stick-Breaking Representation
- 3 EP-Based Learning
- 3.1 Expectation Propagation
- 3.2 EP Model Learning
- 4 Experimental Results: Image Spam Detection
- 5 Conclusion
- A The calculation of Zi in Eq. (21)
- References
- Bayesian Learning of Finite Asymmetric Gaussian Mixtures
- 1 Introduction
- 2 Bayesian Model
- 2.1 Asymmetric Gaussian Mixture Model
- 2.2 Learning Algorithm
- 3 Experimental Results
- 3.1 Design of Experiments
- 3.2 Synthetic Data
- 3.3 Intrusion Detection
- 4 Conclusion and Future Work
- References
- Multiple Water-Level Seawater Temperature Prediction Method for Marine Aquaculture
- 1 Introduction
- 2 Issues and Current Status of Pearl Farming
- 3 Seawater Temperature Prediction Using Actual Data
- 3.1 Seawater Temperature Prediction Algorithm
- 3.2 Data Prediction Flow
- 4 Experimental Result
- 5 Related Works
- 6 Conclusion
- References
- Substation Signal Matching with a Bagged Token Classifier
- 1 Introduction
- 2 System Overview
- 3 Classification Methods
- 4 Evaluation
- 5 Conclusion
- References
- Meta-Heuristics
- Cuckoo Search via Lévy Flight Applied to Optimal Water Supply System Design
- 1 Introduction
- 2 Problem Statement
- 3 Cuckoo Search
- 4 Case Studies and Experimental Results
- 4.1 Two-Loop Network
- 4.2 New York City Tunnels Network
- 4.3 Convergence
- 5 Conclusions and Future Work
- References
- Performance Evaluation of Particles Coding in Particle Swarm Optimization with Self-adaptive Parameters for Flexible Job Shop Scheduling Problem
- 1 Introduction
- 2 Problem Description
- 3 PSO for FJSP
- 4 Proposed Approach
- 4.1 Self-adaptive Parameters
- 4.2 Proposed Technique
- 5 Experimental Results
- 5.1 Experimental Procedure
- 5.2 Simulation Results
- 6 Conclusion
- References
- Simulation-Based Comparison of P-Metaheuristics for FJSP with and Without Fuzzy Processing Time
- 1 Introduction
- 2 FJSP with and Without Fuzzy Processing Time
- 3 Modified PSO
- 4 Experimental Results
- 5 Conclusion
- References
- Resolving the Manufacturing Cell Design Problem via Hunting Search
- 1 Introduction
- 2 Manufacturing Cell Design Problem
- 3 Hunting Search
- 3.1 Hunting Search Steps
- 4 Experimental Results
- 5 Conclusions
- References
- Improved Exploration and Exploitation in Particle Swarm Optimization
- 1 Introduction
- 2 Background
- 3 An Analysis of Standard PSO
- 4 A Modification for Improved Exploitation
- 5 A Modification for Improved Exploration
- 6 Discussion
- 7 Conclusions
- References
- Optimizing Scale-Free Network Robustness with the Great Deluge Algorithm
- 1 Introduction
- 2 Background Information
- 2.1 Complex Networks
- 2.2 Attacking Networks
- 2.3 Optimization Procedures
- 2.4 Previous Work
- 3 Optimizing Robustness
- 3.1 R Value
- 3.2 Optimization Algorithms
- 4 Experiments
- 4.1 Simulated Annealing Parameters
- 4.2 Great Deluge Parameters
- 4.3 Simulated Annealing vs. Great Deluge
- 5 Conclusion and Future Work
- References
- Solving the MCDP Using a League Championship Algorithm
- 1 Introduction
- 2 State of the Art
- 3 Manufacturing Cell Design Problem
- 4 League Championship Algorithm (LCA)
- 5 Experimental Results
- 6 Conclusion
- References
- ACO-Based Measure for SYN Flooding Over Mobile Data Connectivity
- Abstract
- 1 Introduction
- 2 Enhancement for SYN-Flood Over Mobile Data Connectivity
- 2.1 Packet Classification
- 2.2 Flood Detection and Alarm Verification
- 2.3 Verification of Positive Alarm
- 2.3.1 Positive Reaction
- 2.3.2 Negative Reaction
- 2.3.3 Amplification of Fluctuation
- 3 Evaluation and Result Discussion
- 3.1 Evaluation Method
- 3.2 Evaluation Results
- 3.2.1 Recorded Utilization on Simulated SYN Floods
- 3.3 Discussion of Results
- 4 Conclusion
- References
- Multi-Agent Systems
- On Commitments Creation, Compliance and Violation
- Abstract
- 1 Introduction
- 1.1 A Subsection Sample
- 2 Temporal Deontic Defeasible Logic (TDDL)
- 2.1 Definite and Defeasible Proofs
- 3 Speech Acts and Dialogue Moves
- 4 Commitments
- 5 Conclusions and Future Work
- References
- Online Learning for Patrolling Robots Against Active Adversarial Attackers
- 1 Introduction
- 2 Patrolling Robots as UCB1 Bandits
- 3 Stackelberg Game for Route Selection
- 4 Balancing Exploration and Exploitation
- 4.1 Active and Dormant Routes
- 4.2 Comparison Between Different Randomization
- 5 Related Work
- 6 Conclusion
- References
- Perception of Fairness in Culturally Dependent Behavior: Comparison of Social Communication in Simulated Crowds Between Thai and Japanese Cultures
- Abstract
- 1 Introduction
- 2 System Architecture
- 3 Experiment
- 3.1 Tasks and Experimental Settings
- 3.2 Experimental Results
- 4 Discussion and Conclusion
- References
- Simultaneous Exploration and Harvesting in Multi-robot Foraging
- 1 Introduction
- 2 Related Work
- 3 Proposed Algorithm
- 4 Simulation Results
- 5 Conclusion
- References
- Natural Language Processing
- Auto-detection of Safety Issues in Baby Products
- 1 Introduction
- 2 Materials
- 3 Methods
- 3.1 Text Preprocessing
- 3.2 Feature Extraction
- 3.3 Classification
- 3.4 Validation
- 4 Results
- 5 Discussion and Conclusions
- References
- Conversation Envisioning Framework for Situated Conversation
- 1 Introduction
- 2 Situated Conversation Envisioning: Bargaining Scenario
- 2.1 Cultural Aspects of Bargaining
- 2.2 Emotional Aspect of Bargaining
- 2.3 Envisioning of the Bargaining Scenario
- 3 Virtual Reality Conversation Envisioning Framework
- 4 Conversation Description Language (CDL)
- 5 Experimental Evaluation
- 5.1 Procedure
- 5.2 Analysis of the Results
- 6 Conclusion
- References
- A Graph Based Approach to Sentiment Lexicon Expansion
- 1 Introduction
- 2 Methodology
- 2.1 Graph Generation
- 2.2 Path Generation and Utilization Rules
- 2.3 Polarity Assignment
- 3 Results and Experimentation
- 3.1 Polarity Assignment Results
- 3.2 Optimal Pathway Results
- 4 Discussion
- 4.1 Analysis of Results
- 4.2 Related Works
- 5 Conclusion
- References
- Solving Simple Arithmetic Word Problems Precisely with Schemas
- 1 Introduction
- 2 Related Work
- 3 Description of the System
- 4 Schemas
- 4.1 Representation of Schemas
- 4.2 Identification of Schemas
- 5 Natural Language Processing
- 6 Experiments
- 7 Discussion and Conclusion
- References
- Neural Networks
- The Effect of Sentiment on Stock Price Prediction
- 1 Introduction
- 2 Methodology
- 2.1 Sentiment Scores
- 2.2 Neural Network Autoregressive Models
- 2.3 Neural Network Autoregressive Models
- 3 Results
- 4 Discussion
- References
- RFedRNN: An End-to-End Recurrent Neural Network for Radio Frequency Path Fingerprinting
- 1 Introduction
- 2 RFedRNN: Sequence Learning Model for Mobile Positioning
- 2.1 Problem Statement
- 2.2 RNN Model
- 2.3 Sequence Learning Mobile Positioning Model: RFedRNN
- 3 Experimental Evaluation
- 3.1 Simulation
- 3.2 Experiment on the Real-World Dataset
- 4 Summary
- References
- A Quantitative Analysis Decision System Based on Deep Learning and NSGA-II for FX Portfolio Prediction
- Abstract
- 1 Introduction
- 2 The Quantitative Analysis Decision System
- 2.1 An Overview of the Quantitative Analysis Decision System
- 2.2 An FX Forecasting Model Based on SAE-SVR Algorithm
- 2.3 FX Portfolio Dual-Object Optimization Algorithm Based on NSGA-II
- 3 Data Processing
- 4 Empirical Analysis
- 5 Conclusion
- Acknowledgements
- References
- Towards Machine Learning Based IoT Intrusion Detection Service
- 1 Introduction
- 1.1 IoT Security Challenges
- 1.2 Intrusion Detection System
- 1.3 Artificial Neural Network
- 1.4 Random Forest
- 1.5 Network Features
- 2 Intrusion Detection Service
- 2.1 Traffic Gathering Module
- 2.2 Detection Module
- 3 Simulation Results
- 4 Conclusion and Future Work
- References
- Planning, Scheduling and Spatial Reasoning
- A Spatio-Semantic Model for Agricultural Environments and Machines
- 1 Introduction
- 2 Related Work
- 3 The SEMAP Framework
- 4 Applying SEMAP in Agriculture
- 4.1 The AgriCo Ontology
- 4.2 Instantiating the Environment Model
- 5 Application Example
- 6 Conclusion and Future Work
- References
- Chromosome Mutation vs. Gene Mutation in Evolutive Approaches for Solving the Resource-Constrained Project Scheduling Problem (RCPSP)
- 1 Introduction
- 2 Problem Description
- 3 Literature Review
- 3.1 Exact Methods
- 3.2 Approximate Methods
- 4 A Genetic Algorithm with a New Mutation Operator
- 4.1 Redundant Solutions
- 4.2 General Operators
- 4.3 Mutation
- 5 Computational Results
- 5.1 Chromosome Mutation vs. Gene Mutation
- 5.2 Comparative Assessment
- 6 Conclusions
- References
- Energy-Conserving Risk-Aware Data Collection Using Ensemble Navigation Network
- 1 Introduction
- 2 Related Work
- 3 Problem and Approach
- 4 Algorithm
- 4.1 Maximizing Reward Without Energy Constraint
- 4.2 Navigation Under Energy Constraint
- 4.3 Finding the Balance
- 5 Evaluation
- 5.1 Different Risk Distributions
- 5.2 Effect of Energy Capacity
- 6 Conclusion
- References
- Automatically Generating and Solving Eternity II Style Puzzles
- 1 Introduction
- 2 Literature Review
- 3 Generation of Eternity II Style Puzzle Datasets
- 4 Our Zero Look-Ahead Algorithm (ZLA)
- 5 Results and Discussion
- 6 Conclusion and Future Work
- References
- Rough Sets
- A Game-Theoretic Rough Set Approach for Handling Missing Data in Clustering
- 1 Introduction
- 2 A Review of Three-way Clustering
- 2.1 Basic Notions of Three-way Clustering
- 2.2 Issue of Determining Thresholds in Three-way Clustering
- 3 Game-Theoretic Rough Sets
- 4 Three-way Clustering with GTRS
- 4.1 Formulating a Game in GTRS for Three-way Clustering
- 4.2 Realization of Accuracy Versus Generality Tradeoff
- 4.3 Learning with Iterative Games in GTRS
- 5 Experimental Results and Discussion
- 6 Conclusion
- References
- Scalable Implementations of Rough Set Algorithms: A Survey
- 1 Introduction
- 2 Rough Set Based Data Reasoning
- 2.1 Rough Approximations
- 2.2 Decision Rule Generations
- 2.3 Attribute Reductions
- 3 Distributed Computing Frameworks
- 3.1 MapReduce Paradigm
- 3.2 Apache Spark
- 3.3 Hadoop MapReduce vs. Apache Spark
- 4 Scalable Implementations of Rough Set Algorithms
- 5 Remarks and Future Research
- 6 Conclusions
- References
- Fuzzy Clustering Ensemble for Prioritized Sampling Based on Average and Rough Patterns
- 1 Introduction
- 2 Study Data and Knowledge Representation
- 3 Prioritized Fuzzy Clustering Ensemble
- 4 Results and Discussions
- 5 Summary and Conclusions
- References
- Detecting Overlapping Communities in Social Networks with Voronoi and Tolerance Rough Sets
- 1 Introduction
- 2 Related Works
- 3 Preliminaries
- 3.1 Evaluation Measures and Datasets
- 4 Voronoi TRSM Method
- 5 Experiments and Results
- 6 Conclusion and Future Work
- References
- Internet of Things (IoT), Ubiquitous Computing and Big Data
- Multi-objective Optimization at the Conceptual Design Phase of an Office Room Through Evolutionary Computation
- Abstract
- 1 Introduction
- 2 Problem Definition
- 2.1 Design Variables
- 2.2 Objective Functions
- 3 Non-dominated Sorting Genetic Algorithm II (NSGA-II)
- 4 Parametric Model
- 5 Computational Results
- 6 Conclusion
- Acknowledgement
- References
- Data Analytics and Visualization for Connected Objects: A Case Study for Sleep and Physical Activity Trackers
- 1 Introduction
- 2 Main Issues with Activity Trackers from a Usefulness Persective
- 2.1 Lack of Personalization
- 2.2 Lack of Smart Functionalities
- 2.3 Lack Intuitive and Interactive Dashboards and User Interfaces
- 3 Case Study
- 3.1 Specifications of the Activity Trackers Used in the Study
- 3.2 Raw Data
- 3.3 Data Preprocessed and Enrichment
- 3.4 Analytics and High Level Feature Definition
- 3.5 Visualization
- 4 Concluding Remarks and Conclusions
- References
- Reliability-Aware Routing of AVB Streams in TSN Networks
- 1 Introduction
- 2 Related Work
- 3 Fundamentals
- 3.1 System Model
- 3.2 Transmission Reliability
- 4 Motivation
- 5 Proposed Reliability-Aware Routing
- 6 Experimental Results
- 6.1 Performance Evaluation
- 6.2 Co-optimization Case Study
- 7 Conclusion
- References
- Data Science, Privacy, and Security
- A Comparative Study on Chrominance Based Methods in Dorsal Hand Recognition: Single Image Case
- Abstract
- 1 Introduction
- 2 Comparative Study
- 2.1 YCbCr Conversion
- 2.2 Constant Interval Method
- 2.3 Covariance Interval Method
- 2.4 Fuzzy 2-Means
- 3 Evaluation of Accuracy
- 4 Conclusion and Discussion
- Acknowledgement
- References
- Frequency and Time Localization in Biometrics: STFT vs. CWT
- Abstract
- 1 Introduction
- 2 Short-Time Fourier Transformation
- 2.1 Experiments of STFT
- 3 Continuous Wavelet Transformation
- 3.1 Experiments of CWT
- 4 Conclusion and Discussion
- Acknowledgement
- References
- An Evaluation of User Movement Data
- Abstract
- 1 Introduction
- 2 Related Work
- 3 Datasets and Preparation
- 3.1 Activity Recognition Data from a Single Chest Mounted Accelerometer [3]
- 3.2 Localization Data for Posture Reconstruction [9]
- 3.3 Smartphone-Based Recognition of Human Activities and Postural Transitions [4, 8]
- 3.4 ADL Recognition Wrist-Worn Accelerometer Data Set [7]
- 4 User Movement Classification
- 5 Results and Discussions
- 6 Conclusions
- References
- Classifying Political Tweets Using Naïve Bayes and Support Vector Machines
- Abstract
- 1 Introduction
- 2 Related Work
- 3 Data Collection and Preprocessing
- 3.1 Preprocessing
- 4 Feature Extraction Methods Used
- 4.1 Bag of Words Model
- 4.2 TF-IDF
- 5 Feature Selection Using Chi-Square
- 6 Classifiers Used for Sentiment Analysis
- 6.1 Naive Bayes (NB) Classifier
- 6.2 Support Vector Machines (SVMs)
- 7 Experiment Results
- 7.1 Evaluation
- 7.2 Results and Discussion
- 8 Conclusions and Future Work
- Acknowledgements
- References
- Anti-spoofing Approach Using Deep Convolutional Neural Network
- Abstract
- 1 Introduction
- 2 Related Work
- 3 CNN Architecture Used to Mitigate Spoofing Attacks
- 4 Datasets Used
- 5 Results and Discussions
- 6 Conclusions and Future Work
- Acknowledgements
- References
- Sentiment Classification of Short Texts
- Abstract
- 1 Introduction
- 2 Related Work
- 3 Proposed Approach
- 3.1 Deep Learning Model
- 3.2 Machine Learning Algorithms
- 4 Experimental Settings
- 4.1 CNN Experimental Setup
- 4.2 Machine Learning Model's Experiment Setup
- 5 Discussion and Results
- 6 Conclusion
- References
- Study on Data Anonymization for Deep Learning
- 1 Introduction
- 2 Privacy Preserving Data Mining
- 2.1 Study on Input Data
- 2.2 Multi Party Computation
- 2.3 Study on Output Data
- 3 Deep Learning
- 4 Privacy Preserving Data Mining in Deep Learning
- 5 Data Set
- 6 Experiment
- 7 Conclusion
- References
- Information Disclosure, Security, and Data Quality
- 1 Introduction
- 2 Privacy Constraint
- 2.1 Laplace Mechanism and Random Noise
- 2.2 Anonymization
- 3 Related Works
- 4 Adaptive Differential Privacy (ADiffP) Algorithm
- 5 Data Set
- 6 Result and Discussion
- 7 Conclusion
- References
- Intelligent Systems Approaches in Information Extraction
- Adapting Named Entity Types to New Ontologies in a Microblogging Environment
- 1 Introduction and Motivation
- 2 The Proposed Approach
- 3 Experiments
- 3.1 Experimental Settings
- 3.2 Experimental Evaluation
- 4 Related Work
- 5 Conclusions and Future Work
- References
- A Rough Set Approach to Events Prediction in Multiple Time Series
- 1 Introduction
- 2 Rough Set Theory
- 2.1 Indiscernibility Relation-Based Rough Set Approach
- 2.2 Dominance Based Rough Sets Approach
- 3 Event Prediction Approach
- 3.1 Phase 1: Preprocessing
- 3.2 Phase 2: Inference of Prediction Rules
- 3.3 Phase 3: Prediction of Events and Their Intensities
- 4 Framework
- 5 Conclusion
- References
- Efficient Versus Accurate Algorithms for Computing a Semantic Logic-Based Similarity Measure
- 1 Introduction
- 2 Similarity Measure
- 2.1 Basic Definitions
- 2.2 Computing the Similarity Measure
- 3 Efficient Computation of the Similarity Measure
- 4 Accurate Computation of the Similarity Measure
- 5 Computational Complexity
- 6 Evaluation and Comparison
- 6.1 Performance Analysis
- 6.2 Comparative Study
- 7 Conclusion
- References
- Semantic Question Answering System Using Dbpedia
- Abstract
- 1 Introduction
- 2 Related Work
- 3 Proposed System Architecture
- 3.1 Question Classification
- 3.2 Questions Processing
- 3.3 Query Formulation and Execution
- 4 The Dataset
- 5 Experimental Results
- 6 Discussion
- 7 Conclusion and Future Work
- References
- Identifying Similar Sentences by Using N-Grams of Characters
- Abstract
- 1 Introduction
- 2 Methodology
- 3 Experimentations and Results
- 4 Conclusion
- References
- Performance Comparison of Intelligent Techniques Based Image Watermarking
- 1 Introduction
- 2 Image Characteristics Related to the Human Visual System
- 3 Intelligent Techniques Based Image Watermarking
- 4 Performance Comparison
- 5 Conclusion
- References
- Artificial Intelligence, Law and Justice
- Case Law Analysis with Machine Learning in Brazilian Court
- 1 Introduction
- 2 Background
- 2.1 Big Data
- 2.2 Process of Knowledge Discovery in Databases
- 2.3 Information Retrieval
- 2.4 Machine Learning and Its Limitations
- 2.5 Jurisprudence and Concepts Related to Law
- 3 Related Work
- 4 Brazilian Case Law Search Systems
- 5 Development of the Proposed Software
- 5.1 Extraction of Documents
- 5.2 Data Understanding
- 5.3 Annotation of Documents
- 5.4 Machine Learning Models
- 6 Results
- 7 Conclusion and Future Work
- References
- Meticulous Transparency-An Evaluation Process for an Agile AI Regulatory Scheme
- Abstract
- 1 Introduction
- 2 Ethical Problems in AI
- 3 What Is Meticulous Transparency?
- 4 Components of an MT Assessment
- 5 Notes on Implementation
- Acknowledgments
- References
- Towards a New Approach to Legal Indexing Using Facets
- Abstract
- 1 Introduction
- 1.1 Context
- 1.2 Research Goals
- 2 Work in Progress
- 2.1 Designing Our Model
- 2.2 Building the Prototype Gaius
- 3 Steps Ahead
- Acknowledgments
- References
- Artificial Intelligence and Predictive Justice: Limitations and Perspectives
- 1 Introduction
- 2 Previous Work
- 3 Dataset
- 4 Methodology
- 5 Planned Experiments
- 6 Conclusion
- References
- Identification of Sensitive Content in Data Repositories to Support Personal Information Protection
- 1 Introduction
- 2 Previous Work
- 3 Datasets
- 3.1 I2b2
- 3.2 Enterprise Emails
- 3.3 Domain Detection Corpus
- 4 Methodology
- 4.1 Domain Detection
- 4.2 Annotation of Enterprise Emails
- 5 Experiments and Results
- 6 Conclusion and Future Work
- References
- Erratum to: Recent Trends and Future Technology in Applied Intelligence
- Erratum to: M. Mouhoub et al. (Eds.): Recent Trends and Future Technology in Applied Intelligence, LNAI 10868, https://doi.org/10.1007/978-3-319-92058-0
- Author Index
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