Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016

Volume 2
 
 
Springer (Verlag)
  • erschienen am 22. August 2017
  • |
  • XIII, 1070 Seiten
 
E-Book | PDF mit Adobe-DRM | Systemvoraussetzungen
E-Book | PDF mit Wasserzeichen-DRM | Systemvoraussetzungen
978-3-319-56991-8 (ISBN)
 

These proceedings of the SAI Intelligent Systems Conference 2016 (IntelliSys 2016) offer a remarkable collection of papers on a wide range of topics in intelligent systems, and their applications to the real world. Authors hailing from 56 countries on 5 continents submitted 404 papers to the conference, attesting to the global importance of the conference's themes. After being reviewed, 222 papers were accepted for presentation, and 168 were ultimately selected for these proceedings. Each has been reviewed on the basis of its originality, novelty and rigorousness.

The papers not only present state-of-the-art methods and valuable experience from researchers in the related research areas; they also outline the field's future development.

1st ed. 2018
  • Englisch
  • Cham
  • |
  • Schweiz
Springer International Publishing
  • 472 s/w Abbildungen
  • |
  • 472 schwarz-weiße Abbildungen, Bibliographie
  • 132,80 MB
978-3-319-56991-8 (9783319569918)
10.1007/978-3-319-56991-8
weitere Ausgaben werden ermittelt
  • Intro
  • Editor's Preface
  • Contents
  • Automatic Bharatnatyam Dance Posture Recognition and Expertise Prediction Using Depth Cameras
  • 1 Introduction
  • 2 Related Work
  • 3 Overview of Our Framework
  • 4 Posture and Expertise Data Collection
  • 4.1 Sensing Setup
  • 4.2 Posture Selection and Representation
  • 4.3 Expertise Annotation
  • 5 Feature Extraction and Classification
  • 5.1 Feature Extraction
  • 5.2 Classifiers
  • 6 Experimental Results
  • 6.1 Pose Recognition
  • 6.2 Expertise Prediction
  • 7 Discussion and Future Work
  • 8 Conclusion
  • References
  • A Logo-Based Approach for Recognising Multiple Products on a Shelf
  • Abstract
  • 1 Introduction
  • 2 Literature Review
  • 3 Methodology
  • 3.1 Using Logo Detection
  • 3.2 Without Using Logo Detection
  • 4 Experimental Setup and Results
  • 4.1 Dataset
  • 4.2 Results
  • 5 Conclusion
  • References
  • Unsupervised Text Binarization in Handwritten Historical Documents Using k-Means Clustering
  • 1 Introduction
  • 2 Proposed Method
  • 2.1 Contrast Enhancement and Noise Removal Method
  • 2.2 Normalization
  • 2.3 Unsupervised Based Document Image Binarization
  • 3 Experimental Results
  • 3.1 Quantitative Results
  • 4 Conclusion
  • References
  • Feature Fusion for Facial Landmark Point Location
  • Abstract
  • 1 Introduction
  • 2 SIFT
  • 3 LBP
  • 4 Gabor Wavelets
  • 5 Fusion of Features
  • 5.1 Performance of Regressor Using Single Feature
  • 5.2 Performance of Regressor Using Fusion of Features
  • 6 Conclusions
  • References
  • Fast Graph-Based Object Segmentation for RGB-D Images
  • 1 Introduction
  • 2 Background
  • 3 Enhanched Segmentation
  • 3.1 Color
  • 3.2 Depth
  • 3.3 Saliency
  • 3.4 Removing Texture Edges
  • 3.5 Weight Function
  • 3.6 Post-processing
  • 4 Experimental Results
  • 4.1 Rutgers APC RGB-D Dataset
  • 4.2 RGB-D Scenes Dataset
  • 4.3 Multiple-Instance Dataset
  • 5 Conclusion
  • References
  • Image Splicing Detection Using Electromagnetism-Like Based Descriptor
  • Abstract
  • 1 Introduction
  • 2 EMag
  • 3 Dimension Reduction Method
  • 4 Experimental Results
  • 4.1 Classifier
  • 4.2 Classification
  • 4.3 Comparison with Other Methods
  • 5 Conclusion
  • References
  • Enhanced Object Segmentation for Vehicle Tracking and Dental CBCT by Neuromorphic Visual Processing with Controlled Neuron
  • Abstract
  • 1 Introduction
  • 2 Brain-Inspired Neuromorphic Vision of Robust Object Detection
  • 2.1 Object Detection in Real Life Environment
  • 2.2 Tooth Segmentation
  • 3 Robust Object Segmentation by Controlled Rectifier Neurons
  • 3.1 Vehicle Object Segmentation for Tracking at Night
  • 3.2 Enhancement of CBCT Image for Tooth Segmentation
  • 4 Conclusion
  • Acknowledgment
  • References
  • A Robust, Real-Time Capable Framework for Fully Automated Order Picking of Pouch-Parceled Goods
  • 1 Introduction
  • 2 Related Approaches
  • 3 Cover Belt Conveyor System
  • 4 Marker Detection Framework
  • 4.1 Marker Designs
  • 4.2 Velocity Estimation
  • 4.3 Parallel Windowed Time Series Analysis
  • 4.4 Feature-Based Classification
  • 5 Cutting Line Detection
  • 6 Experimental Results
  • 6.1 Test Setup
  • 6.2 Accuracy
  • 6.3 Run Time
  • 7 Conclusion and Future Work
  • References
  • Ensemble Neural Networks and Image Analysis for On-Site Estimation of Nitrogen Content in Plants
  • Abstract
  • 1 Introduction
  • 2 Data Acquisition
  • 2.1 Farm Experiment
  • 2.2 Image Acquisition
  • 2.3 SPAD Meter Readings
  • 2.4 Actual Nitrogen Measurement Using Combustion Method
  • 2.5 Image Segmentation and Features Extraction
  • 3 Back-Propagation Neural Network and Committee Machines Based Nitrogen Prediction
  • 4 Results and Discussions
  • 4.1 SPAD Meter Based Nitrogen Amount Prediction
  • 4.2 Image-Based Nitrogen Amount Prediction
  • 5 Conclusion and Future Works
  • References
  • Bag of Features vs Vector of Locally Aggregated Descriptors
  • 1 Introduction
  • 2 Related Work
  • 3 Features Quantization
  • 3.1 Bag-of-Feature (BoF)
  • 3.2 Vector of Locally Aggregated Descriptors (VLAD)
  • 4 Experimental Setup
  • 4.1 Datasets
  • 4.2 Features Extraction
  • 4.3 Features Quantization
  • 5 Performance Evaluation
  • 6 Conclusion
  • References
  • Image Segmentation Using Clustering Methods
  • Abstract
  • 1 Introduction
  • 2 Related Work
  • 3 DBSCAN and K-means Algorithms
  • 4 The Proposed Method
  • 5 Tests and Results
  • 6 Conclusion
  • References
  • MR Brain Images Segmentation Using Joint Information and Fuzzy C-Means
  • Abstract
  • 1 Introduction
  • 2 Fuzzy C-Means Technique [13]
  • 3 Fuzzy Joint Information Segmentation (FJIS)
  • 4 Experimental Results
  • 5 Conclusion
  • References
  • Visual Odometry for Pedestrians Based on Orientation Attributes of SURF
  • 1 Introduction
  • 2 Foundations
  • 2.1 Image Processing - Interest Points
  • 2.2 Visual Odometry
  • 2.3 Pedestrian Dead Reckoning
  • 3 Related Work
  • 3.1 Visual Odometry
  • 3.2 Pedestrian Dead Reckoning
  • 3.3 Visual Positioning Systems
  • 4 Concept
  • 4.1 Basic Workflow
  • 4.2 Image Sequence and Feature Detection
  • 4.3 Preprocessing
  • 4.4 Motion Estimation - Step Detection
  • 4.5 Motion Estimation - Heading Estimation
  • 4.6 Motion Estimation - Trajectory Building
  • 5 Evaluation
  • 5.1 General Set-Up
  • 5.2 Evaluation Method
  • 5.3 Parameter Settings
  • 5.4 Scenarios
  • 6 Conclusion
  • References
  • Strategic Development and Dynamic Models of Supply Chains: Search for Effective Model Constructions
  • Abstract
  • 1 Problematics of Strategic Development and Integrated Simulation of Supply Chains
  • 2 System Modeling of Supply Chains
  • 3 Conclusion
  • References
  • Multi-resource Minority Games: Redefining the Game
  • 1 Introduction
  • 2 The Minority Game
  • 2.1 Evaluation Criteria
  • 3 Related Works
  • 4 The Multi-resource Minority Game
  • 5 Experimental Results
  • 6 Conclusion and Future Work
  • References
  • Agent-Based Outsourcing Solution for Agency Service Management
  • Abstract
  • 1 Introduction
  • 2 Problem Analysis and Background
  • 3 Motivation
  • 4 Existing Solutions Overview
  • 5 Agent-Based Model
  • 6 Solution Vision
  • 7 Implementation and Tests
  • 8 Conclusion
  • References
  • Petri Nets for Mobile Agent: Theory and Application
  • Abstract
  • 1 Introduction
  • 2 Multi Agent Systems
  • 2.1 The Agent
  • 2.2 Related Works
  • 3 Petri Nets Mobile Agents Model
  • 3.1 Definition of PNMAM
  • 3.2 Definition of Constraints Parameters
  • 3.3 Assumptions of Uniqueness
  • 4 Strain on the Environment of a Petri Net Mobile Agent
  • 4.1 Constraint on Group of Agents in a Network of Mobile Agents in Petri
  • 4.2 Pre Functions Provided
  • 4.3 Interpretation of Possible Values Prj
  • 4.4 Interpretation of Possible Values Prgj
  • 4.5 Overall Membership Function to an Environment
  • 4.6 Membership Function Local Group
  • 4.7 Membership Function Local Group
  • 4.8 Based Communication Between Two Mobile Agents
  • 4.9 Function Migrate-External
  • 4.10 Function of Internal Migration Between Two Groups
  • 5 Specification Problem of "Production Management"
  • 5.1 Specification of the Environment
  • 5.2 Specifying Transitions
  • 6 Conclusion
  • References
  • Multi-agent System for Safeguarding Children Online
  • Abstract
  • 1 Introduction
  • 2 Background
  • 3 Safechat System Design
  • 3.1 Software Agents and Their Environment
  • 3.2 Ontology Development
  • 3.3 SparQL Ontology Queries
  • 4 Safechat System Implementation
  • 5 Conclusion and Future Work
  • 5.1 Future Work
  • References
  • Synthetizing Qualitative (Logical) Patterns for Pedestrian Simulation from Data
  • 1 Introduction
  • 1.1 Aim of the Paper
  • 1.2 Structure of the Paper
  • 2 Basic Agent-Based Model for Pedestrians
  • 3 Background: Formal Concept Analysis
  • 3.1 Implication Basis
  • 3.2 Armstrong Rules
  • 3.3 Association Rules and Luxenburger Basis
  • 3.4 Simulation Process by Means of Attribute Selection
  • 4 Representing Agent's Knowledge by Means of FCA
  • 4.1 Detailed Potentials (8 Attributes)
  • 4.2 Simplified Potentials (42 Attributes)
  • 5 Contextual Selection for Pedestrians
  • 6 FCA-based Simulation of Pedestrian Flow
  • 6.1 Analysing Simulation Results
  • 7 On the Robustness of the Model
  • 8 Related Work
  • 9 Conclusions and Future Work
  • References
  • Learning to Negotiate Optimally in a Multi-agent Based Negotiation System for Web Service Selection
  • Abstract
  • 1 Introduction
  • 2 Related Work
  • 3 A Decision Tree Learning Framework
  • 3.1 A Comparative Study Between the Learning Techniques
  • 3.2 The Learning Model
  • 3.3 The C4.5 Learning Algorithm
  • 3.4 The Training Data Set
  • 3.5 The Decision Tree Construction
  • 4 The Negotiation Support with Learning Decision Tree Model
  • 4.1 The Negotiation Web Service Based Selection System
  • 4.2 The Learning Model Integration in the Chicken Game Negotiation Strategy
  • 5 Experimentation
  • 6 Conclusion
  • References
  • Hybrid Service Discovery Approach for Peer-to-peer Web Service Systems
  • 1 Introduction
  • 2 Background Work
  • 3 Web Services Feature Extraction and Clustering
  • 3.1 Feature Extraction from WSDL Documents
  • 3.2 Web Service Clustering
  • 4 Service Discovery in the P2P Environment
  • 4.1 Service Discovery in a Super-Peer Network
  • 4.2 Service Discovery Across Super-Peers
  • 5 Experimental Results
  • 6 Conclusion
  • References
  • Embodied Conversational Agent-Based Deception Detection
  • Abstract
  • 1 Introduction
  • 2 Literature Synopsis and Hypotheses
  • 3 Deception Experiment
  • 4 Methodology
  • 4.1 Participants
  • 4.2 Procedure
  • 4.3 Sensors
  • 5 Results
  • 5.1 Electrodermal Activity
  • 5.2 Oculometrics
  • 5.3 Vocalics
  • 6 Summary of Hypothesis Results
  • 7 Discussion
  • 8 Conclusion
  • References
  • An Efficient Agent Scheming in Distributed Time Varying Networks
  • 1 Introduction
  • 2 Preliminary Study
  • 2.1 Graph Theory
  • 2.2 Matrix Theory
  • 3 Proposed Model
  • 3.1 Proposed Algorithm
  • 4 Simulation Results
  • 4.1 Example 1
  • 4.2 Example 2
  • 4.3 Example 3
  • 4.4 Example 4
  • 4.5 Example 5
  • References
  • An Object-Oriented Agent Framework for HEMS
  • Abstract
  • 1 Introduction
  • 2 The Smart Home Problem Description
  • 2.1 Hardware Environment of Our Smart Home
  • 2.2 A Smart Meter as an Agent
  • 3 An Object-Oriented Agent Framework
  • 3.1 A Generic Agent
  • 3.2 State and State Update
  • 3.3 Communication Protocols
  • 3.4 Web Services
  • 3.5 Actions
  • 3.6 Event-Response Rules
  • 3.7 HEMS: A Smart Home Agent
  • 3.8 A Home Resident Agent
  • 4 Evaluation of Our Agent Framework
  • 5 Related Works and Discussion
  • 6 Conclusion
  • Acknowledgement
  • References
  • An Ontology for Modelling Human Machine Interaction in Smart Environments
  • 1 Introduction
  • 2 Related Work
  • 2.1 Smart Environment Ontologies
  • 2.2 Ontologies in Robotics
  • 3 EISE Ontology
  • 3.1 Competency Questions
  • 3.2 Sensors and Actuators
  • 3.3 Time and Time Intervals
  • 3.4 Spatial Information
  • 3.5 Ontology Composition
  • 4 Validation
  • 5 Conclusion and Future Work
  • References
  • Evolutionary Testing Using Particle Swarm Optimization in IOT Applications
  • Abstract
  • 1 Introduction
  • 2 Methodology
  • 3 Related Work
  • 4 Conclusion
  • References
  • Deep Learning Based Semantic Video Indexing and Retrieval
  • Abstract
  • 1 Introduction
  • 2 Related Work
  • 3 Video Indexing
  • 3.1 Features Extraction and Film Segmenting
  • 3.2 Graph-Oriented Indexing
  • 4 Video Retrieval
  • 4.1 Searching by Structured Queries
  • 4.2 Searching by Sample Video
  • 4.3 Searching by Sample Images
  • 5 Conclusion
  • References
  • Using Machine Learning for Evaluating the Quality of Exercises in a Mobile Exergame for Tackling Obesity in Children
  • Abstract
  • 1 Introduction
  • 2 State of the Art
  • 2.1 Exergames
  • 2.2 Automatic Recognition of Human Activities
  • 2.3 Gaming Behavior
  • 3 Mission Kid
  • 3.1 Overview
  • 3.2 Architecture
  • 4 Automatic Learning of Physical Exercise Quality
  • 4.1 Data Collection
  • 4.2 Qualification of the Exercises
  • 4.3 Extraction of Features from Exercises
  • 5 Evaluation
  • 6 Implementing Mission Kid in Android
  • 7 Assessing the Quality of the Exercise
  • 8 Conclusion
  • Acknowledgment
  • References
  • Machine Learning Approaches to Predict Repetitive Transcranial Magnetic Stimulation Treatment Response in Major Depressive Disorder
  • Abstract
  • 1 Introduction
  • 2 Materials and Methods
  • 2.1 Subjects
  • 2.2 QEEG Techniques and Cordance Calculations
  • 2.3 rTMS Session Procedures and Ratings
  • 2.4 Artificial Neural Network Based Classifier
  • 2.5 Support Vector Based Classifier
  • 2.6 Decision Tree Classifier
  • 3 Results
  • 4 Discussion and Conclusions
  • Acknowledgement
  • References
  • A Machine Learning Based Model for Software Cost Estimation
  • Abstract
  • 1 Introduction
  • 2 Research Objectives
  • 3 Literature Review
  • 3.1 Cost Estimations
  • 3.2 Effort Estimations
  • 4 Experiment
  • 5 Methodology
  • 6 Conclusion and Future Work
  • References
  • Performance Analysis of Various Missing Value Imputation Methods on Heart Failure Dataset
  • Abstract
  • 1 Introduction
  • 2 Related Work
  • 3 Heart Failure Dataset
  • 4 Missing Value Imputation Methods
  • 4.1 K Nearest Neighbour Imputation (KNNI)
  • 4.2 Expectation Maximization Imputation (EM)
  • 4.3 K-Mean Imputation
  • 4.4 Most Common Imputation (MCI)
  • 4.5 Concept Most Common Imputation (CMCI)
  • 4.6 Support Victor Machine (SVM) Imputation
  • 5 Classification
  • 5.1 C4.5/ J48
  • 5.2 REPTree
  • 5.3 Random Forest (RF)
  • 6 Experiments and Results
  • 7 Conclusion
  • References
  • Deep Reinforcement Learning: An Overview
  • Abstract
  • 1 Introduction
  • 2 Reinforcement Learning
  • 3 Deep Learning
  • 3.1 Autoencoders
  • 3.2 Convolutional Neural Networks
  • 3.3 Recurrent Neural Networks
  • 4 Deep Supervised and Unsupervised Learning Models for Reinforcement Learning
  • 4.1 Combination of RL Techniques with Supervised Learning Approaches of Deep Neural Networks
  • 4.2 Combination of RL Techniques with Unsupervised Learning Approaches of Deep Neural Networks
  • 4.3 Deep RL for Partially Observable MDPs (POMDPs) Environments
  • 5 Conclusion and Future Work in Deep Reinforcement Learning
  • References
  • Cantilever Beam Natural Frequency Prediction Using Artificial Neural Networks
  • Abstract
  • 1 Introduction
  • 2 Dynamic Analysis
  • 3 Prediction of Natural Frequency Using Artificial Neural Networks
  • 4 Conclusion
  • References
  • Deep Learning with Random Neural Networks
  • 1 Introduction
  • 2 Dense Clusters of Homogenous Cells with Soma-to-Soma Excitation
  • 2.1 The Transfer Function for Homogenous Clusters
  • 3 Learning Rules for Simple RNN Multi-layer Classifiers
  • 4 Combining the Spiking Model and the Extreme Learning Machine
  • 4.1 Performance Testing
  • 5 Improved Classifier Combining Spiking Model and Extreme Learning Machine
  • 5.1 The Classifier
  • 5.2 Update Rules for the ELM
  • 6 Conclusions
  • References
  • Short-Term Localized Weather Forecasting by Using Different Artificial Neural Network Algorithm in Tropical Climate
  • Abstract
  • 1 Introduction
  • 2 Literature
  • 2.1 Related Works
  • 2.2 Artificial Neural Network
  • 3 Study Area
  • 4 Methodology
  • 4.1 Data Cleaning
  • 4.2 ANN Design
  • 4.3 Experimental Setup
  • 4.4 Accuracy Performance Indices
  • 5 Results and Discussions
  • 6 Conclusion and Future Works
  • References
  • Initialising Deep Neural Networks: An Approach Based on Linear Interval Tolerance
  • 1 Introduction
  • 2 Interval Analysis and Tolerance Problem
  • 3 Interval Tolerance Solution and the DLIT Algorithm
  • 4 Datasets
  • 5 Experiments and Results
  • 6 Conclusion and Future Work
  • References
  • Query Caching and Answering Using an Atom Based Neuro-Architecture
  • 1 Introduction
  • 1.1 Student Information
  • 1.2 Course Information
  • 1.3 Associative Relation
  • 2 Literature Review
  • 2.1 Query and Query Processing
  • 2.2 Query Optimization
  • 3 Proposed Caching Model
  • 3.1 Atoms
  • 3.2 Decomposition
  • 3.3 Creating Atoms
  • 3.4 Atom Definition Block (ADB)
  • 3.5 Answering a Query Using Cached Atoms
  • 3.6 Atom Resizing and Hit Ratios
  • 4 Atom Comparison
  • 5 Query Retrieval
  • 6 Conclusion
  • References
  • Integration of Fuzzy C-Means and Artificial Neural Network for Short-Term Localized Rainfall Forecast in Tropical Climate
  • Abstract
  • 1 Introduction
  • 2 Literature
  • 2.1 Related Works
  • 2.2 Fuzzy C-Means Clustering
  • 2.3 Artificial Neural Network
  • 3 Study Area
  • 4 Methodology
  • 4.1 Data Cleaning
  • 4.2 ANN Design
  • 4.3 Experimental Setup
  • 4.4 Performance Indices
  • 5 Results and Discussions
  • 6 Conclusion
  • References
  • Position Control and Stabilization of Fully Actuated AUV using PID Controller
  • 1 Introduction
  • 2 Configuration and Kinematic Model
  • 3 Thruster Model
  • 4 Dynamic Model
  • 5 Disturbance Model
  • 6 Simulation Results
  • 7 Future Work
  • 8 Conclusion
  • References
  • Motion Control of a Terrain Following Unmanned Aerial Vehicle Under Uncertainty
  • Abstract
  • 1 Introduction
  • 2 System Integrations
  • 3 Modeling of a Quadrotor
  • 3.1 Description of a Quadrotor System
  • 3.2 Dynamic Equations of a Quadrotor
  • 4 Control Design
  • 4.1 PID Control Technique
  • 4.2 Altitude Control
  • 4.3 Horizontal Motion Control
  • 5 Simulation Results
  • 6 Conclusions
  • 7 Future Work
  • References
  • Adjustment of Tele-Operator Learning When Provided with Different Levels of Sensor Support While Driving Mobile Robots
  • Abstract
  • 1 Introduction
  • 2 The Mobile Robot System
  • 3 Experiments
  • 3.1 Initial Experiments
  • 3.2 Results from Initial Experiments
  • 3.3 Discussion of the First Set of Experiments
  • 3.4 Abbreviations and AcronymsSecond Set of Experiments
  • 3.5 Results from Later Experiments
  • 3.6 Discussion Concerning Later Experiments
  • 4 Overall Discussion and Conclusions
  • References
  • Controlling Line Follower Robot with the Remote Web Server
  • 1 Introduction
  • 2 Infrastructure of the Line Follower Robot
  • 2.1 The Chassis and Body
  • 2.2 Sensors-Optical Reflection Sensor TCRT5000
  • 2.3 L293D Motor Driver
  • 2.4 PIC16F877A
  • 2.5 Power Circuit
  • 2.6 PID Control Algorithms
  • 3 Programming
  • 4 Proposed Novel Method to Control the Line Follower Robot with Web Server
  • 5 Web Server Performance Testing
  • 6 Conclusion
  • References
  • Development of Guided Autonomous Navigation for Indoor Material Handling Applications
  • Abstract
  • 1 Introduction
  • 2 Methodology
  • 2.1 Gyroscope
  • 2.2 Encoders
  • 2.3 Ultrasonic Sensors
  • 2.4 Estimation of Absolute Heading Angle by Fusing Data from Gyro and Encoder Using Kalman Filter
  • 3 Implementation
  • 3.1 Joystick Control for Learning Mode
  • 3.2 Generating Map from Data Stored in Memory
  • 3.3 Path Tracking in Autonomous Mode
  • 3.4 PID Controller for Heading Correction
  • 3.5 Software Design
  • 4 Experimental Evaluation
  • 4.1 Heading Angle Estimation Using Kalman Filter
  • 4.2 Efficiency of the Controller in Maintaining the Required Heading Angle
  • 4.3 Autonomous Navigation Along Trained Path
  • 5 Conclusion
  • 6 Scope for Future Work
  • References
  • Rule-Based System to Assist a Tele-Operator with Driving a Mobile Robot
  • Abstract
  • 1 Introduction
  • 2 Input from the Joystick and Sensors
  • 2.1 The Ultrasonics
  • 2.2 Mapping the Environbment Ahead of the Mobile Robot
  • 2.3 Interpreting the Joystick
  • 3 Kinematics of a Bobcat II Base
  • 4 Control and the Rules
  • 5 Testing and Results
  • 6 Conclusions
  • References
  • Path Following of Underactuated Catamaran Surface Vessel (WAM-V) Using Fuzzy Waypoint Guidance Algorithm
  • Abstract
  • 1 Introduction
  • 2 Mathematical Model
  • 3 Waypoint Guidance Algorithm
  • 3.1 Algorithm Description
  • 3.2 Fuzzy Reasoning
  • 4 Control Design
  • 5 Simulation Results and Discussion
  • 6 Conclusion and Future Work
  • References
  • Review of Potential Attacks on Robotic Swarms
  • 1 Introduction
  • 1.1 Introduction to Swarm Robotics
  • 1.2 Introduction to the Problem
  • 1.3 Overview of Security Considerations
  • 1.4 Attacking a Swarm
  • 2 Threat Types
  • 2.1 Denial of Service
  • 2.2 Masquerade
  • 2.3 System Penetration
  • 2.4 Authorisation Violation
  • 2.5 Planting
  • 2.6 Communications Monitoring (Eavesdropping)
  • 2.7 Modification of Data in Transit
  • 2.8 Misappropriation
  • 3 The Adversary
  • 4 Attacks on Swarms
  • 4.1 Manner of Attack
  • 4.2 Attacker's Knowledge of a Swarm
  • 4.3 Attack Types
  • 4.4 Attack Vectors
  • 5 Discussion
  • 6 Conclusion and Future Work
  • References
  • SIMSSP: Secure Instant Messaging System for Smart Phones
  • 1 Introduction
  • 2 Related Work
  • 3 Design and Algorithms
  • 4 Simple Prototype Implementation and Verification
  • 5 Conclusion
  • References
  • Elastic Serial Substitution Box for Block Ciphers with Integrated Hash Function Generation
  • Abstract
  • 1 Introduction
  • 2 Conventional S Box and Properties
  • 2.1 Nonlinearity
  • 2.2 Bijection
  • 2.3 Balance
  • 2.4 Bit Independent Criteria or Correlation Immunity
  • 2.5 Completeness
  • 2.6 Strict Avalanche Criteria (SAC)
  • 2.7 Extended Properties- Static and Dynamic
  • 3 Data Integrity Verification Using Hash Functions
  • 4 The Proposed S Box Integrted with Hash Generator
  • 4.1 Toeplitz Based Hashing Function
  • 4.2 Controller
  • 4.3 Data Selection Network
  • 4.4 S Boxes
  • 4.5 Operation
  • 5 Implementation Details, Security and Result Analysis
  • 5.1 Properties Achieved with the Proposed Design
  • 5.2 Security
  • 5.3 Timing
  • 5.4 Implementation
  • 5.5 Result Analysis
  • 6 Conclusion and Future Scope
  • References
  • A Model of a Malware Infected Automated Guided Vehicle for Experimental Cyber-Physical Security
  • 1 Introduction
  • 2 Cyber Attacks on Production Facilities
  • 3 Scenario
  • 4 Modelling
  • 4.1 To Simulate, or Not to Simulate?
  • 4.2 A New Model?
  • 5 Model Implementation
  • 5.1 Supervisory Control
  • 5.2 Subordinate Control
  • 5.3 Platform
  • 6 Malware
  • 6.1 Type
  • 6.2 Trigger
  • 6.3 Payload
  • 6.4 Implementation
  • 7 Evaluation with an Example
  • 7.1 Stepping Through the Scenario
  • 7.2 How Does This Compare with Other Models of AGV Failure?
  • 8 Conclusions
  • References
  • JIR2TA: Joint Invocation of Resource-Based Thresholding and Trust-Oriented Authentication in Mobile Adhoc Network
  • Abstract
  • 1 Introduction
  • 2 Review of Literature
  • 3 Problem Statement
  • 4 Contribution of Proposed System
  • 5 Research Methodology
  • 5.1 Designing a Scheme for Resource-Based Thresholding
  • 5.2 Designing a Scheme for Trust-Based Authentication
  • 6 Implementation
  • 6.1 Algorithm-1: Resource-based Thresholding
  • 6.2 Algorithm-2: Trust-based Authentication
  • 7 Result Analysis
  • 7.1 Analysis of Computational Time
  • 7.2 Analysis of Packet Delivery Ratio
  • 7.3 Analysis of End-to-End Delay
  • 7.4 Analysis of Throughput
  • 8 Conclusion
  • Acknowledgments
  • References
  • HADM: Hybrid Analysis for Detection of Malware
  • 1 Introduction
  • 2 Feature Sets
  • 2.1 Hybrid Analysis Features
  • 2.2 Feature Vector Representations
  • 2.3 Graph Representation
  • 3 Deep Learning Model
  • 3.1 Restricted Boltzmann Machine
  • 3.2 Deep Auto-Encoder
  • 4 Classification
  • 4.1 Kernel Matrix Construction for Vectors
  • 4.2 Kernel Matrix Construction for Graphs
  • 4.3 Support Vector Machine
  • 4.4 Multiple Kernel Learning
  • 4.5 Hierarchical MKL
  • 5 Experimental Results
  • 5.1 Dataset
  • 5.2 Evaluation Metrics
  • 5.3 Results from Original Vector and Graph Set
  • 5.4 Results from DNN
  • 5.5 Results from First Level MKL
  • 5.6 Result from Second Level MKL
  • 5.7 Results from Concatenating Original Feature Vectors
  • 5.8 Comparison with State-of-the-art
  • 6 Related Work
  • 7 Conclusion and Future Work
  • References
  • Resolving DRDoS Attack in Cloud Database Service Using Common Source IP and Incremental Replacement Strategy
  • Abstract
  • 1 Introduction
  • 2 Related Work
  • 3 Methodology
  • 3.1 Proposed Detection Scheme
  • 3.2 Resolving DRDoS Attack
  • 4 Results Analysis
  • 4.1 Experiments
  • 4.2 Discussion of Experimental Results
  • 4.3 Evaluations
  • 5 Conclusion
  • Acknowledgment
  • References
  • Effective Solutions for Most Common Vulnerabilities in Web Applications
  • 1 Introduction
  • 1.1 Applications and Motivations
  • 1.2 Our Contribution
  • 1.3 Road Map
  • 2 FixWebSQLInjection
  • 2.1 Vulnerability Detail
  • 2.2 Solutions
  • 3 FixWebXSS
  • 3.1 Vulnerability Detail
  • 3.2 XSS Injection Process
  • 3.3 XSS Attacks Can Cause Different Damages Some Are
  • 3.4 XSS Attacks Can Be Categorized into Three Main Types
  • 3.5 Solutions
  • 4 FixWebCSRF
  • 4.1 Solutions
  • 5 FixOtherVulnerabilities
  • 5.1 Security Misconfiguration
  • 5.2 Unvalidated Redirects and Forwards
  • 5.3 No Account Lockout
  • 5.4 Insecure Password Policy
  • 5.5 HTTPS Not Enforced
  • 6 Conclusions
  • References
  • Chaos-Based Audio Steganography and Cryptography Using LSB Method and One-Time Pad
  • 1 Introduction
  • 2 Related Work
  • 3 Chaotic Maps
  • 3.1 Logistic Map
  • 3.2 Piecewise Linear Chaotic Map
  • 4 One-Time Pad
  • 5 The Proposed Method
  • 5.1 Message Encryption
  • 5.2 Message Hiding
  • 6 Experimental Results
  • 6.1 Wave Form Analysis
  • 6.2 Signal to Noise Ratio
  • 6.3 Key Space
  • 7 Conclusion
  • References
  • A Smart Card Web Server in the Web of Things
  • 1 Introduction
  • 2 Related Work
  • 3 Proposal Overview
  • 4 Example Use Cases
  • 4.1 Assumptions
  • 5 Architecture-Protocol
  • 6 Process Duration Time Estimation
  • 7 Local Single Sign-On
  • 8 Security Analysis
  • 8.1 Advantages
  • 8.2 Disadvantages
  • 9 Conclusion-Future Work
  • References
  • Semantic Events
  • Abstract
  • 1 Introduction: Cyber-Attacks and Software Logs
  • 2 The State of Practice in Event Logging
  • 2.1 Problems with Representation and Understanding
  • 3 Solution: Semantic Events and Attributes
  • 3.1 Interpretation and Representation
  • 3.1.1 Whodunwhat? Which Software?
  • 3.1.2 Which Users?
  • 3.1.3 Which Triggers?
  • 3.1.4 Other Participants?
  • 3.1.5 Other Considerations
  • 3.2 Promoting Re-Use of Semantic Events
  • 4 Related Work: Evaluative Comparison
  • 5 Conclusion and Outlook
  • Acknowledgment
  • References
  • In-Home Assisted Living for Elderly Dementia Care
  • Abstract
  • 1 Introduction
  • 2 Related Works
  • 3 Task Monitoring and Intervention
  • 3.1 System Architecture
  • 3.2 Probabilistic Inference Based on DBN
  • 4 Results and Discussion
  • 5 Conclusion
  • References
  • Weibo Surveillance of Public Awareness to Ebola Disaster in China
  • Abstract
  • 1 Introduction
  • 2 Social Media in Disease Surveillance
  • 3 Weibo Data Collection and Analysis
  • 3.1 Trend Analysis
  • 3.2 Keyword Extraction
  • 3.3 Social Network Analysis
  • 4 Analysis Results
  • 4.1 Change Tendency of Public Attention
  • 4.2 Hot Topics of Exploration Points
  • 4.3 Network Evolution
  • 5 Conclusions
  • References
  • A Mobile Healthcare Application for Chronic Diseases Patient
  • Abstract
  • 1 Introduction
  • 2 Android Operating System
  • 3 Problem Statement
  • 4 Methodology
  • 4.1 Data Investigation
  • 4.2 System Modeling
  • 4.3 System Architecture
  • 4.4 Building the System (System Design)
  • 5 System Methods
  • 6 System Evaluation
  • 7 Conclusions and Future Work
  • References
  • Flexure Hinge Based Fully Compliant Prosthetic Finger
  • Abstract
  • 1 Introduction
  • 2 Flexure Hinge
  • 2.1 Classification of Flexure Hinges
  • 2.2 Design and Analysis of Flexure Hinge
  • 3 Evaluation System
  • 4 Test-Bed for Flexure Hinge
  • 4.1 Three-Dimensional Model
  • 4.2 Fabrication of Flexure Hinge
  • 4.3 Bending Performance Test
  • 5 Experimental Results
  • 6 Conclusion and Future Work
  • References
  • Design, Develop, and Deploy a Wellness Index Dashboard Utilizing Commonly Available Sensors in the Form of Wearable Technology to Monitor Heterogeneous Data
  • Abstract
  • 1 Project Description
  • 2 Broader Impacts of the Proposed Work
  • 2.1 Goals
  • 2.2 Objectives
  • 3 Strategy
  • 4 Approach
  • 5 Four Core Behaviors
  • 5.1 Sleep
  • 5.2 Gait
  • 5.3 Hydration and Ingestion
  • 6 Solution
  • 7 Conclusion
  • References
  • A Reconfigurable Connected Health Platform Using ZYNQ System on Chip
  • Abstract
  • 1 Introduction
  • 2 Literature Review
  • 3 Proposed System
  • 3.1 System Overview
  • 3.2 System Architecture
  • 4 Software and Hardware Implementation and Results
  • 4.1 Software Implementation
  • 4.2 Hardware Implementation
  • 5 Conclusion
  • Acknowledgment
  • References
  • A Review of Current Technology-Based Intervention for School Aged Children with Autism Spectrum Disorder
  • Abstract
  • 1 Introduction
  • 2 Methods
  • 2.1 Literature Search Procedures
  • 2.2 Inclusion Criteria
  • 3 Technology-Based Intervention
  • 3.1 Languages and Literacy
  • 3.2 Social Skills
  • 3.3 Emotion Recognition
  • 4 Conclusion
  • References
  • Accelerated Particle Swarm Algorithm for Optimal Allocation of Capacitor Banks in Radial Distribution Feeders
  • Abstract
  • 1 Introduction
  • 2 Capacitor Placement Problem Formulation
  • 3 Particle Swarm Optimization
  • 3.1 Basic Concept of Particle Swarm Optimization
  • 3.2 Accelerated Particle Swarm Optimization
  • 3.3 The Algorithm Steps
  • 4 Implementation and Results
  • 4.1 The First Feeder
  • 4.2 The Second Feeder
  • 4.3 The Third Feeder
  • 5 Conclusions
  • References
  • Particle Swarm Optimization Algorithms for Maximizing Area Coverage in Wireless Sensor Networks
  • Abstract
  • 1 Introduction
  • 2 Problem Formulation
  • 3 Related Works
  • 4 Proposed Algorithms
  • 4.1 PSO Algorithm
  • 4.1.1 Individual Representation
  • 4.1.2 Initialization and Fitness Function
  • 4.1.3 Updating Individuals
  • 4.2 DPSO Algorithm
  • 5 Experiment Results
  • 5.1 Experimental Settings
  • 5.2 Computational Results
  • 6 Conclusion
  • Acknowledgment
  • References
  • Particle Swarm Optimization Based Placement of Data Acquisition Points in a Smart Water Metering Network
  • 1 Introduction
  • 2 Particle Swarm Optimization
  • 3 The DAP Placement Optimization Problem
  • 4 The PSO Based DAP Placement Mechanism in the Tsumeb SWMN
  • 4.1 The Tsumeb SWMN
  • 4.2 The Implementation of the PSO Based DAP Placement Mechanism in the Tsumeb SWMN
  • 5 Results and Discussions
  • 5.1 PSO Results
  • 5.2 DAP Locations
  • 5.3 Comparison Between PSO Based DAP Placement and Meter Density Based DAP Placement Mechanism
  • 6 Conclusion
  • References
  • Maritime Static Target Search Based on Particle Swarm Algorithm
  • Abstract
  • 1 Introduction
  • 2 Discrete Maritime Static Target Search Problem
  • 3 Static Target Search Based on Particle Swarm Algorithm
  • 4 Experimental Results
  • 5 Conclusion
  • References
  • Vehicle Logo Recognition Using SIFT Representation and SVM
  • Abstract
  • 1 Introduction
  • 2 Literature Survey
  • 3 SIFT Features
  • 4 SIFT-Based Vehicle Logo Classification
  • 5 Experimental Results
  • 6 Conclusion
  • References
  • Design and Performance Evaluation of a Committee Machine for Gas Identification
  • 1 Introduction
  • 1.1 Data Acquisition System
  • 1.2 Classifiers Overview
  • 1.3 Committee Machine
  • 1.4 Simulations Results
  • 2 Conclusion
  • References
  • Efficient Way of Feature Extraction for the Recognition of Handwritten Arabic Characters
  • Abstract
  • 1 Introduction
  • 2 Related Works
  • 3 Preprocessing and Feature Extraction Method
  • 3.1 Preprocessing
  • 3.2 Local Binary Pattern
  • 4 Proposed Solution
  • 4.1 Different Configuration of Image Decomposition According to the Global Vision
  • 4.2 Different Configuration of Image Decomposition According to the Local Vision
  • 5 Conclusion
  • References
  • Fast Fingerprint Rotation Recognition Technique Using Circular Strings in Lexicographical Order
  • 1 Introduction
  • 1.1 Fingerprint Recognition and Pattern Matching
  • 1.2 Road Map
  • 2 Related Works
  • 3 Our Approach
  • 3.1 Stage 1: Orientation Identification
  • 3.2 Stage 2: Verification and Matching
  • 4 The Experiment
  • 4.1 Rotation and Speed
  • 5 Conclusion and Future Work
  • References
  • Steady Illumination Color Local Ternary Pattern as a Feature Extractor in Iris Authentication
  • Abstract
  • 1 Introduction
  • 2 Related Work
  • 3 Methodology
  • 3.1 Local Ternary Patterns
  • 3.2 Steady Illumination Colour Local Ternary Pattern
  • 3.3 Procedure for Applying SIcLTP, Is as Follows [12]
  • 3.4 Experimental Set up and Process
  • 4 Result and Discussion
  • 5 Conclusion
  • References
  • A Review of Frequent Pattern Mining Algorithms for Uncertain Data
  • Abstract
  • 1 Introduction
  • 1.1 Frequent Pattern Mining
  • 1.2 Uncertainty in Data
  • 1.3 Probabilistic Model for Uncertain Data
  • 1.4 Objectives of the Paper
  • 2 Frequent Pattern Mining of Uncertain Data
  • 2.1 Uncertain Frequent Pattern Mining Using Candidate Generate-and-Test Paradigm (U-Apriori)
  • 2.2 Uncertain Frequent Pattern Mining Using Tree Structures
  • 2.3 CUF Tree Structure
  • 2.4 PUF Tree Structure
  • 3 Constrained Uncertain Frequent Pattern Mining
  • 4 Uncertain Frequent Pattern Mining from Big Data
  • 5 Conclusion
  • References
  • Exploring Patient-Oriented Healthcare Support System by Using General Bayesian Network
  • Abstract
  • 1 Introduction
  • 2 Value of GBN in Designing an Inference Engine of PACDSS
  • 3 Target Problem and Features of Dataset
  • 4 Experiments
  • 5 Concluding Remarks
  • References
  • Neural Networks for Robotic Detection of Mastitis in Dairy Cows: Netherlands and New Zealand Perspectives
  • Abstract
  • 1 Introduction
  • 2 Objectives
  • 3 Background
  • 4 Materials and Methods
  • 4.1 Self Organising Maps
  • 4.2 Fuzzy Self Organising Maps
  • 5 Results
  • 6 Summary and Conclusions
  • Acknowledgments
  • References
  • Feature Selection for Document Retrieval in the Export Control Domain
  • Abstract
  • 1 Introduction
  • 2 Document Retrieval System
  • 3 Method
  • 4 Experiments and Results
  • 5 Conclusion
  • References
  • Applications of Artificial Intelligence in the Export Control Domain
  • Abstract
  • 1 Introduction
  • 2 Related Work
  • 3 Applications of Artificial Intelligence in Export Control
  • 4 Discussion and Conclusion
  • References
  • Automatic Question Answering System for Consumer Products
  • 1 Introduction
  • 2 System Architecture
  • 2.1 Offline Data Processing
  • 2.2 Online System
  • 3 Experiments
  • 4 Conclusion
  • References
  • Data Workflow for Extension Framework to Interpret and Transform Human Behavior
  • Abstract
  • 1 Introduction
  • 2 Dimensions of Human Behaviour
  • 2.1 Subject Dimensions in Human Behavior
  • 2.2 Situational Dimensions in Human Behavior (Driven)
  • 2.3 Other Humans in Human Behavior (Driver)
  • 2.4 Objective Dimensions of the Subject (from Observation, Captured Video, Image, Audio, Biometric Data)
  • 3 Example Explaining One Dataset Using Extenics Matter Element Concept
  • 3.1 Application of Extenics
  • 3.1.1 Trigger Stage
  • 3.1.2 Problem Solving Stage
  • 4 Datasciences for Data Workflow
  • 5 Dataflow Framework for Human Behaviour Interpretation and Transformation
  • 6 Conclusion
  • Appendix A
  • References
  • Credibility Perception for Arab Users
  • Abstract
  • 1 Introduction
  • 2 Data Collection and Survey Study Design
  • 3 Basic Analysis of Credibility Rating Values and Labelers' Data
  • 3.1 Labellers' Age
  • 3.2 Labellers' Gender
  • 3.3 Labellers' Education
  • 3.4 Labellers' Twitter Features and Usage
  • 3.5 Labellers' personality trust trait
  • 3.6 Labellers' Topic Familiarity and Interest
  • 4 Conclusions
  • References
  • Measuring Player's Behaviour Change over Time in Public Goods Game
  • 1 Introduction
  • 2 Background and Related Work
  • 2.1 Public Goods Game
  • 2.2 External Cluster Validity
  • 3 Methodology
  • 4 Tests and Results
  • 4.1 Tests with Synthesised Data
  • 4.2 Tests with Public Goods Games Data
  • 5 Measuring Players' Strategy Changes Using MONIC
  • 6 Summary and Conclusions
  • References
  • Audiovisual Compression Techniques Using DCT-DWT and LPC Codec for Audiovisual Human Machines Interfaces
  • Abstract
  • 1 Introduction
  • 2 Video Compression
  • 2.1 DCT for Video Compression
  • 2.2 Compression Using Wavelet Analysis
  • 2.3 Linear Predictive Coding (LPC) for Audio Compression
  • 3 Simulation Results
  • 3.1 Databases
  • 3.2 DCT Compression
  • 3.3 DWT Compression
  • 3.4 LPC Compression
  • 3.5 Comparison Framework
  • 4 Conclusion
  • References
  • Author Index

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