International Joint Conference SOCO'17-CISIS'17-ICEUTE'17 León, Spain, September 6-8, 2017, Proceeding

 
 
Springer (Verlag)
  • erschienen am 21. August 2017
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  • XXIX, 763 Seiten
 
E-Book | PDF mit Adobe-DRM | Systemvoraussetzungen
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978-3-319-67180-2 (ISBN)
 

This volume includes papers presented at SOCO 2017, CISIS 2017, and ICEUTE 2017, all conferences held in the beautiful and historic city of León (Spain) in September 2017.

Soft computing represents a collection of computational techniques in machine learning, computer science, and some engineering disciplines, which investigate, simulate, and analyze highly complex issues and phenomena.

These proceeding

s feature 48 papers from the 12th SOCO 2017, covering topics such as artificial intelligence and machine learning applied to health sciences; and soft computing methods in manufacturing and management systems.

The book also presents 18 papers from the 10th CISIS 2017, which provided a platform for researchers from the fields of computational intelligence, information security, and data mining to meet and discuss the need for intelligent, flexible behavior by large, complex systems, especially in mission-critical domains. It addresses various topics, like identification, simulation and prevention of security and privacy threats in modern communication

networks

Furthermore, the book includes 8 papers from the 8th ICEUTE 2017. The selection of papers for all three conferences was extremely rigorous in order to maintain the high quality and we would like to thank the members of the Program Committees for their hard work in the reviewing process.

1st ed. 2018
  • Englisch
  • Cham
  • |
  • Schweiz
Springer International Publishing
  • 285 s/w Abbildungen
  • |
  • 285 schwarz-weiße Abbildungen, Bibliographie
  • 105,29 MB
978-3-319-67180-2 (9783319671802)
10.1007/978-3-319-67180-2
weitere Ausgaben werden ermittelt
  • Intro
  • Preface
  • SOCO 2017
  • Organization
  • General Chairs
  • International Advisory Committee
  • Program Committee Chairs
  • Program Committee
  • Special Sessions
  • Soft Computing Methods in Manufacturing and Management Systems
  • Program Committee
  • Artificial Intelligence and Machine Learning Applied to Health Sciences
  • Program Committee
  • SOCO 2017 Organizing Committee
  • CISIS 2017
  • Organization
  • General Chairs
  • International Advisory Committee
  • Program Committee Chairs
  • Program Committee
  • CISIS 2017 Organizing Committee
  • ICEUTE 2017
  • Organization
  • General Chairs
  • Program Committee Chairs
  • Program Committee
  • ICEUTE 2017 Organizing Committee
  • Logos
  • Contents
  • SOCO 2017: Genetic and Evolutionary Algorithms
  • Learning Bayesian Network to Predict Group Emotion in Kindergarten by Evolutionary Computation
  • Abstract
  • 1 Introduction
  • 2 Related Works
  • 2.1 Bayesian Network
  • 2.2 Learning Bayesian Network
  • 3 Proposed Method
  • 3.1 Search Procedure of Bayesian Network
  • 3.2 Determining Nodes
  • 3.3 Encoding Bayesian Network
  • 3.4 Evolutionary Operation
  • 3.5 Evaluating Fitness
  • 4 Experiment and Results
  • 4.1 Experiment Design
  • 4.2 Prediction Accuracy
  • 4.3 Analysis of the Best Individual
  • 5 Conclusion
  • Acknowledgements
  • References
  • Dynamic Resources Configuration for Coevolutionary Scheduling of Scientific Workflows in Cloud Envir ...
  • Abstract
  • 1 Introduction
  • 2 Related Works
  • 3 Problem Statement
  • 4 Proposed Solution
  • 5 Experimental Study
  • 6 Conclusion
  • Acknowledgements
  • References
  • Computation of Berge-Zhukovskii Equilibrium in Discrete Time Dynamic Games
  • 1 Introduction
  • 2 Methods
  • 2.1 Approximation of Berge-Zhukovskii Equilibria
  • 3 Numerical Experiments
  • 3.1 Benchmark
  • 3.2 Experimental Set-Up
  • 3.3 Results and Discussion
  • 4 Conclusions
  • References
  • Applying Genetic Algorithms in Chemical Engineering for Determining Zeolite Structures
  • 1 Introduction
  • 2 Problem Description of ZSD
  • 3 Application of Genetic Algorithms to Zeolite Structure Determination
  • 4 Proposal of a Genetic Algorithm for ZSD
  • 4.1 Setting Up
  • 4.2 Initialization
  • 4.3 Fitness Evaluation
  • 4.4 Crossover Operators
  • 4.5 Population Reduction
  • 5 Experimentation and Results
  • 6 Conclusions
  • References
  • SOCO 2017: Fuzzy Logic
  • Health Assessment of Automotive Batteries Through Computational Intelligence-Based Soft Sensors: An Empirical Study
  • 1 Introduction
  • 2 Soft Computing-Based Battery SoH Assessment
  • 3 Empirical Study and Discussion
  • 4 Concluding Remarks
  • References
  • Intelligent Decision System Based on Fuzzy Logic Expert System to Improve Plastic Injection Molding Process
  • Abstract
  • 1 Introduction
  • 2 Development of the Intelligent System Based on Fuzzy Logic
  • 2.1 Creation of the Knowledge Base
  • 2.1.1 Injection Molding Defects
  • 2.1.2 Injection Molding Process Simulation
  • 2.1.3 Injection Tests - Trend of Each Defect Based on Single Change of Process Variables
  • 2.2 Develop of Inference Engines
  • 2.2.1 Input Data
  • 2.2.2 Membership Functions
  • 2.2.3 Heuristic Rules
  • 2.2.4 Hybrid Fuzzy Inference Model
  • 2.3 Expert System Functioning
  • 3 Expert System Validation
  • 4 Conclusions
  • Acknowledgements
  • References
  • Acquisition and Fuzzy Processing of Physiological Signals to Obtain Human Stress Level Using Low Cos ...
  • Abstract
  • 1 Introduction
  • 2 Stress and Physiological Responses
  • 3 Hardware Platforms
  • 3.1 Arduino Uno
  • 3.2 Raspberry Pi 3
  • 4 Hardware Configuration
  • 5 Algorithms
  • 5.1 Acquisition of Physiological Signals
  • 5.2 Extraction of Relevant Parameters
  • 5.3 Fuzzy Logic Processing
  • 5.4 Storage of the Data in the LAMP Server
  • 6 Results
  • 7 Conclusions and Future Works
  • Acknowledgements
  • References
  • A Fuzzy Ordered Weighted Averaging Approach to Rerostering in Nurse Scheduling Problem
  • Abstract
  • 1 Introduction
  • 2 Basic Idea in Nurse Rerostering Problem and Related Work
  • 2.1 Basic Idea in Nurse Rerostering Problem
  • 2.2 Related Work in Nurse Rerostering Problem
  • 2.3 Fuzzy Ordered Weighted Averaging Approach
  • 3 Modeling the Nurse Rerostering Problem
  • 3.1 Empirical Data Set - Graphical Representation
  • 3.2 The Proposed Algorithm for Nurse Rerostering Problem
  • 4 Experimental Results
  • 5 Conclusion and Future Work
  • References
  • SOCO 2017: Energy Efficiency
  • Optimization of Wind Power Producer Participation in Electricity Markets with Energy Storage in a Wa ...
  • Abstract
  • 1 Introduction
  • 2 Relationship to Energy 4.0
  • 3 State of the Art
  • 4 Day-Ahead Market and Balancing Market
  • 5 Problem Formulation
  • 6 Case Study
  • 7 Conclusion
  • Acknowledgments
  • References
  • Gas Consumption Prediction Based on Artificial Neural Networks for Residential Sectors
  • 1 Introduction
  • 2 Case of Study
  • 3 ANN Type and Architecture Selection
  • 4 Methods
  • 4.1 NARX Training and parameters
  • 4.2 NARX Configurations
  • 4.3 Experiment Set
  • 4.4 Best Net Search
  • 5 Proposed ANN Hybrid Model
  • 5.1 Median and Mean Boosting Functions Comparison
  • 6 Result and Discussion
  • 7 Conclusions
  • References
  • Bioclimatic House Heat Exchanger Behavior Prediction with Time Series Modeling
  • 1 Introduction
  • 2 Case of Study
  • 2.1 Sotavento Bioclimatic House
  • 2.2 Geothermal System Under Study
  • 2.3 The Dataset Obtaining and Description
  • 3 Used Models - Time Delay Neural Networks
  • 4 Experiments and Results
  • 4.1 Experimental Setup
  • 4.2 Experiment Results
  • 5 Conclusions
  • References
  • Optimization with the Evolution Strategy by Example of Electrical-Discharge Drilling
  • Abstract
  • 1 Introduction
  • 2 Materials and Methods
  • 3 Results and Discussion
  • 4 Conclusion
  • References
  • SOCO 2017: Soft Computing Applications
  • Detection of Cardiac Arrhythmias Through Singular Spectrum Analysis of a Time-Distorted EGM Signal
  • 1 Introduction
  • 2 Current Methodologies for Detecting AF
  • 3 Proposed Methodology
  • 3.1 SSA for Extracting Oscillatory Components
  • 3.2 Distortion of the Time Scale
  • 4 Case Studies and Discussion
  • 5 Concluding Remarks and Future Work
  • References
  • An Approach to Location Extraction from Russian Online Social Networks: Road Accidents Use Case
  • Abstract
  • 1 Introduction
  • 2 Related Work
  • 3 Neural Network-Based Approach to Location Extraction
  • 4 Experimental Study
  • 5 Conclusion and Future Work
  • Acknowledgment
  • References
  • Intelligent Maintenance for Industrial Processes, a Case Study on Cold Stamping
  • 1 Introduction
  • 2 Intelligent Maintenance Techniques
  • 2.1 Filtering and Time Series Characterization
  • 2.2 Distance Metrics
  • 2.3 Time Series Data Mining
  • 3 Methodology
  • 3.1 Process Data Acquisition
  • 3.2 Analysis Description
  • 4 Results
  • 4.1 Frequent Events
  • 4.2 Critical Breakdown
  • 5 Conclusions
  • References
  • Attempts Prediction by Missing Data Imputation in Engineering Degree
  • 1 Introduction
  • 2 Case of Study
  • 3 Data Imputation Techniques
  • 3.1 MICE Algorithm
  • 3.2 AAA Algorithm
  • 3.3 Models Validation
  • 4 Results
  • 5 Conclusions
  • References
  • SOCO 2017: Data Mining and Optimization
  • Forecasting Freight Inspection Volume Using Bayesian Regularization Artificial Neural Networks: An Aggregation-Disaggregation Procedure
  • Abstract
  • 1 Introduction
  • 2 Bayesian Regularization Neural Networks
  • 3 Experimental Design
  • 3.1 The Aggregation-Disaggregation Procedure
  • 4 Results and Discussion
  • 5 Conclusions
  • Acknowledgments
  • References
  • Combining Stream Mining and Neural Networks for Short Term Delay Prediction
  • 1 Introduction
  • 2 Data Preparation with Big Data Frameworks
  • 2.1 Data Acquisition
  • 2.2 Data Preprocessing with Stream Processing Framework
  • 3 Short Term Delay Prediction
  • 4 Hybrid Stream Mining of Delay Data Streams
  • 5 Results
  • 6 Conclusions and Future Work
  • References
  • Techniques and Utilities to Improve the Design, Development and Debugging of Multiagent Applications ...
  • Abstract
  • 1 Introduction
  • 2 An Architecture to Analyze, Debug and Test Agents with Agile Principles
  • 2.1 Software Utilities and Integrated Components in Details
  • 2.2 Behavior Externalization
  • 2.2.1 Behavior Activation by Runlevels
  • 3 Application Scenarios: Two Sample Cases
  • 3.1 An Original DummyAgent Agent Test Environment
  • 3.2 A Complex, Rule-Based Agent Test Environment
  • 4 Conclusions and Future Work
  • References
  • About Nash Equilibrium, Modularity Optimization, and Network Community Structure Detection
  • 1 Introduction
  • 2 The Community Structure Detection Game
  • 3 Extremal Optimization and the Community Detection Problem
  • 4 Numerical Experiments
  • 4.1 Experimental Set-up
  • 4.2 Results and Discussion
  • 5 Conclusion
  • References
  • Design and Implementation of a Vision System on an Innovative Single Point Micro-machining Device for Tool Tip Localization
  • 1 Introduction
  • 2 Single Point Micro-machining Device Description
  • 3 Vision System
  • 3.1 Hardware Configuration to Acquire Images
  • 3.2 Vision System Implementation
  • 4 Results
  • 5 Discussion
  • 6 Conclusions
  • References
  • New Application of 3D VFH Descriptors in Archaeological Categorization: A Case Study
  • 1 Introduction
  • 2 State of the Art
  • 3 Our Novel VFH-Based Categorization Proposal
  • 4 Computational Experiments
  • 4.1 3D Datasets
  • 4.2 Analysis of Results
  • 5 Concluding Remarks
  • References
  • Spanish Patent Landscape 2013-2016
  • Abstract
  • 1 Introduction
  • 2 Patent Retrieval Architecture Platform
  • 2.1 Types of Documents
  • 2.2 International Patent Classification
  • 3 Visualization of Results
  • 3.1 Patents Between 2013 and 2016
  • 3.2 Classifications
  • 3.3 Countries Involved in Patents
  • 3.4 Relationship Between Inventors' Countries
  • 3.5 Patents Associated with Trademarks and Institutions
  • 4 Conclusions
  • Acknowledgments
  • References
  • Instability Detection on a Radial Turning Process for Superalloys
  • 1 Introduction
  • 2 Industrial Application
  • 3 Methodology
  • 3.1 Instability Detection
  • 4 Results
  • 4.1 Instability Detection
  • 5 Conclusions
  • References
  • SOCO 2017: MACHINE LEARNING
  • PAELLA as a Booster in Weighted Regression
  • 1 Introduction
  • 1.1 PAELLA Algorithm Foundations
  • 1.2 Structure of the Paper
  • 2 Experimental Survey
  • 2.1 PAELLA Boosted Regression vs. Macro Sampling
  • 2.2 PAELLA Boosted Regression vs. State of the Art
  • 3 Conclusions
  • References
  • A Data-Driven Approach to Dialog Structure Modeling
  • 1 Introduction
  • 2 Related Work
  • 3 Our Proposed Methodology for Spoken Dialog Segmentation
  • 4 Practical Application
  • 4.1 Structure of the Dialogs
  • 5 Results and Discussion
  • 6 Conclusions and Future Work
  • References
  • Inception and Specification of What-If Scenarios Using OLAP Usage Preferences
  • Abstract
  • 1 Introduction
  • 2 Related Work
  • 3 The Hybridization Process and Its Alloy Specification
  • 3.1 Defining a Data Warehouse View
  • 3.2 Data Cube Construction
  • 3.3 The Extraction of Association Rules
  • 3.4 The Extraction of OLAP Preferences
  • 3.5 The What-If Process
  • 4 Conclusions
  • References
  • Analysing the Effect of Recent Anti-pollution Policies in Madrid City Through Soft-Computing
  • Abstract
  • 1 Introduction
  • 2 Techniques and Methods
  • 2.1 Neural Dimensional-Reduction Techniques
  • 2.2 Clustering Techniques
  • 3 Real-Life Case Study
  • 4 Results and Discussion
  • 5 Conclusions and Future Work
  • References
  • SOCO 2017: Soft Computing Methods in Manufacturing and Management Systems
  • An Activity-Oriented Petri Net Simulation Approach for Optimization of Dispatching Rules for Job Sho ...
  • Abstract
  • 1 Cyclic Scheduling
  • 2 Transient States of Cyclic Production
  • 2.1 Transitional Dispatching Rules
  • 3 Activity-Oriented Petri Net Simulation Approach for Optimization
  • 3.1 The Petri Net Model
  • 3.2 Model Building Using the AOPN Approach
  • 3.3 The Run-Time Petri Net Model
  • 4 Implementing the Petri Net Model Using GPenSIM
  • 4.1 Computational Example
  • 4.2 Simulation Results
  • 5 Summary
  • Acknowledgments
  • References
  • MAC Approach Concept for Virtual Manufacturing Networks Generating
  • Abstract
  • 1 Introduction
  • 2 Concept of a Multi-agent System
  • 3 Organization Rule Determination
  • 4 VM Network Model in NetLogo Environment
  • 5 Conclusion
  • References
  • Ecodesign of Technological Processes with the Use of Decision Trees Method
  • Abstract
  • 1 Introduction
  • 2 Literature Review
  • 3 Methods
  • 3.1 Decision Tree Induction Method
  • 3.2 Method for Technological Process Design
  • 4 Expert System Supporting the Design of Technological Processes
  • 5 Discussion
  • 6 Conclusion
  • Acknowledgments
  • References
  • Modular Petri Net Models of Communicating Agents
  • Abstract
  • 1 Introduction
  • 2 Related Works
  • 2.1 Issues in Modularization
  • 3 Modular Petri Net Models Using GPenSIM
  • 3.1 Modules in GPenSIM: IO Port-Driven and IO Buffer-Driven
  • 3.2 Introduction of MOD_PRE and MOD_POST Files for Modularization
  • 4 Modeling Communicating Agents with GPenSIM
  • 4.1 An Application Example
  • 4.2 Petri Net Model Based on IO Port-Driven Modules of Communicating Agents
  • 4.3 Petri Net Model Based on IO Buffer-Driven Modules of Communicating Agents
  • 4.4 Comparing IO Port-Driven and IO Buffer-Driven Modules
  • 5 Conclusion
  • References
  • Methodology Supporting the Planning of Machining Allowances in the Wood Industry
  • Abstract
  • 1 Introduction
  • 2 Research Problem
  • 3 Methodology
  • 4 Example Application of the Methodology
  • 5 Discussion and Conclusions
  • Acknowledgements
  • References
  • Stochastic Scheduling of Production Orders Under Uncertainty
  • Abstract
  • 1 Introduction
  • 2 Scheduling of Production Orders
  • 3 Formulating Mathematical Problem and Model
  • 3.1 Decision Problem
  • 3.2 Mathematical Model
  • 4 Example of Modelling Using Stochastic Networks
  • 5 Conclusions
  • References
  • SOCO 2017: Artificial Intelligence and Machine Learning Applied to Health Sciences
  • Outcome Prediction for Salivary Gland Cancer Using Multivariate Adaptative Regression Splines (MARS) ...
  • Abstract
  • 1 Introduction
  • 2 Methods
  • 2.1 Multivariate Adaptative Regression Splines
  • 2.2 Artificial Neural Networks (ANNs) and Self Organizing Maps (SOM)
  • 2.3 Empirical Study: Patient Sample
  • 3 Results
  • 3.1 MARS Model
  • 3.2 Som
  • 4 Conclusions
  • Acknowledgements
  • References
  • An Artificial Neural Network Model for the Prediction of Bruxism by Means of Occlusal Variables
  • Abstract
  • 1 Introduction
  • 2 Methods
  • 2.1 Artificial Neural Networks
  • 2.2 Study Population
  • 2.3 Procedure Used for Performing Ensemble Model Selection
  • 3 Results
  • 4 Conclusions
  • References
  • Genetic Algorithm Based on Support Vector Machines for Computer Vision Syndrome Classification
  • Abstract
  • 1 Introduction
  • 2 Methods
  • 2.1 Case of Study
  • 2.2 Data Collection
  • 2.3 Support Vector Machines
  • 2.4 Genetic Algorithms
  • 3 Results and Discussion
  • 3.1 Results
  • 3.2 Discussion and Conclusions
  • References
  • A Methodology for the Detection of Relevant Single Nucleotide Polymorphism in Prostate Cancer by Mea ...
  • Abstract
  • 1 Introduction
  • 2 Methods
  • 2.1 Multivariate Adaptive Regression Splines
  • 2.2 Backpropagation Artificial Neural Networks
  • 2.3 Study Population
  • 2.4 The Proposed Algorithm
  • 3 Results and Discussion
  • 4 Conclusions
  • References
  • A Multiregressive Approach for SNPs Identification in Prostate Cancer
  • Abstract
  • 1 Introduction
  • 2 Methods
  • 2.1 Recursive Partitioning
  • 2.2 Multivariate Adaptive Regression Splines
  • 2.3 Study Population
  • 2.4 The Methodology
  • 3 Results and Discussion
  • 4 Conclusions
  • References
  • Comparison of the Periimplant Bone Stress Distribution on Three Fixed Partial Supported Prosthesis D ...
  • Abstract
  • 1 Introduction
  • 2 Materials and Methods
  • 2.1 Finite Element Model Design
  • 2.2 Material Properties and Interface Conditions
  • 3 Results
  • 4 Discussion
  • 4.1 Bridge Design
  • 4.2 Occlusal Loading Direction
  • 5 Conclusions
  • References
  • PoDA Algorithm: Predictive Pathways in Colorectal Cancer
  • Abstract
  • 1 Introduction
  • 2 Methods
  • 2.1 Pathway List
  • 2.2 Subject Study
  • 2.3 Samples Processing
  • 2.4 Pathway of Distinction Analysis
  • 3 Results
  • 3.1 Pathway List
  • 3.2 Study Subjects
  • 3.3 PoDA
  • 4 Discussion
  • References
  • Sparse Representation Based Anomalies Detection in Electrocardiography Signals
  • Abstract
  • 1 Introduction
  • 2 Related Work
  • 3 Sparse Representation of ECG Signal
  • 3.1 The Proposed Data Model
  • 3.2 Sparse Representation Models with Outliers
  • 4 Dictionary Learning Method of Resistant-to-Outlier
  • 5 The Proposed Solution
  • 5.1 Problem Formulation of Sparse Representation with Outlier
  • 5.2 Modified AMA Algorithm for Anomaly Detection
  • 6 Experimental Results
  • 7 Conclusions
  • References
  • A SMOTE Extension for Balancing Multivariate Epilepsy-Related Time Series Datasets
  • 1 Introduction
  • 2 The SMOTE Algorithm
  • 3 Tackling the TS Balancing Problem Through AVG_TS_SMOTE
  • 4 Experiments and Results
  • 4.1 Experimental Setup
  • 4.2 Correlation Between Each Feature and the Class
  • 5 Conclusions
  • References
  • Mining Temporal Causal Relations in Medical Texts
  • Abstract
  • 1 Introduction: Time and Causation
  • 2 Allen's Temporal Relations and Its Fuzzyfication
  • 3 Mining Causal Relations
  • 3.1 Creating a Causal Graph
  • 4 Causation and Time
  • 5 Conclusions and Future Work
  • Acknowledgments
  • References
  • A Machine Learning Based System for Analgesic Drug Delivery
  • Abstract
  • 1 Introduction
  • 2 Methods
  • 2.1 ANI Monitor
  • 2.2 Description of the Anaesthetic Process
  • 2.3 Data Analysis
  • 3 Results
  • 4 Conclusions
  • Acknowledgements
  • References
  • Assessing Feature Selection Techniques for a Colorectal Cancer Prediction Model
  • 1 Introduction
  • 2 Feature Selection and Ranking
  • 2.1 Feature Selection with Filters
  • 2.2 Feature Selection with Wrapper Approaches
  • 2.3 Feature Selection with Embedded Approaches
  • 3 Stability of Feature Selectors
  • 3.1 Similarity Measures
  • 3.2 The Stability for a Set of Rankings or Lists
  • 4 Experimental Results with a Colorectal Cancer Dataset
  • 4.1 Colorectal Cancer (CRC) Dataset
  • 4.2 Feature Ranking Algorithms
  • 4.3 Analysis of Feature Rankings for Classification
  • 4.4 Ranking Stability Analysis
  • 5 Conclusions
  • References
  • Data Mining Techniques for the Estimation of Variables in Health-Related Noisy Data
  • 1 Introduction
  • 1.1 Health Issues Caused by High Ozone Concentration
  • 1.2 Predictions in Ozone Models
  • 2 PAELLA Algorithm
  • 3 Experimental Analysis
  • 3.1 Pollution Dataset
  • 3.2 Experiments and Results
  • 4 Discussion
  • 5 Conclusions
  • References
  • An Intelligent Model to Predict ANI in Patients Undergoing General Anesthesia
  • 1 Introduction
  • 2 Case of Study
  • 3 Model Approach
  • 3.1 Dataset Obtaining and Description
  • 3.2 Used Techniques
  • 4 Results
  • 5 Conclusions
  • References
  • CISIS 2017: Mathematical Algorithms and Models
  • Coupling the PAELLA Algorithm to Predictive Models
  • 1 Introduction
  • 1.1 A Primer on PAELLA
  • 1.2 Structure of the Paper
  • 2 Experimental Analysis
  • 2.1 Description of the Artificial Dataset
  • 2.2 Raw Data Model
  • 2.3 PAELLA Filtered Data Model
  • 2.4 Binning the Occurrence Vector
  • 2.5 Macro Sampling
  • 2.6 Micro Sampling
  • 3 Conclusions
  • References
  • Query Based Object Retrieval Using Neural Codes
  • 1 Introduction
  • 2 Related Work
  • 3 Methodology
  • 3.1 Object Detection
  • 3.2 Object Retrieval
  • 4 Experiments and Results
  • 4.1 Dataset: ImageNet-IndoorObjects
  • 4.2 Experimental Setup
  • 4.3 Detection Accuracy and Running Time of the Network
  • 4.4 Similarity Score Based Retrieval
  • 4.5 Confidence Score Based Retrieval
  • 4.6 Comparison of both Retrieval Methods
  • 5 Conclusion
  • References
  • Parallel Performance of the Boundary Element Method in Thermoelastic Contact Problems
  • 1 Introduction
  • 2 Methods
  • 2.1 Introduction to the Problem
  • 2.2 Coefficient Calculation
  • 3 Experiments
  • 3.1 Comparison by Type of Problem
  • 3.2 Comparison by Presence of Symmetry
  • 4 Conclusions
  • References
  • A New Simple Attack on a Wide Class of Cryptographic Sequence Generators
  • 1 Introduction
  • 2 Basic Concepts
  • 3 Linear Properties of the Shrunken Sequence
  • 4 Cryptanalytic Attack
  • 4.1 A Simple Example
  • 4.2 Numerical Results
  • 5 Different Attacks over This Sequence Generator
  • 6 Conclusions
  • References
  • CISIS 2017: Infrastructure and Network Security
  • Adaptive Database Intrusion Detection Using Evolutionary Reinforcement Learning
  • Abstract
  • 1 Introduction
  • 2 Related Works
  • 3 The Proposed Model
  • 3.1 Virtual Query Data
  • 3.2 Adaptive Database Intrusion Detection Model
  • 4 Experiments
  • 4.1 Experiment Settings
  • 4.2 Results
  • 5 Conclusions
  • Acknowledgements.
  • References
  • Learning Classifier Systems for Adaptive Learning of Intrusion Detection System
  • Abstract
  • 1 Introduction
  • 2 Related Works
  • 3 Method
  • 3.1 Intrusion Detection System Architecture
  • 3.2 Query Log Parsing and Feature Extraction
  • 3.3 Accuracy Based Learning Classifier Systems
  • 3.3.1 Encoding
  • 3.3.2 Rule Representation
  • 3.3.3 Performance Component
  • 3.3.4 Update Fitness and Genetic Algorithm
  • 4 Experiments
  • 5 Conclusions
  • Acknowledgements
  • References
  • Time Series Forecasting Using Holt-Winters Model Applied to Anomaly Detection in Network Traffic
  • Abstract
  • 1 Introduction
  • 2 Overview of Adaptive Prediction Methods Using Exponential Smoothing
  • 3 Time Series Forecasting for Network Anomaly Detection
  • 3.1 The Holt-Winters Model for Estimation of Network Traffic Variability
  • 3.2 The Selection of Model Order and Parameters Estimation
  • 3.3 Automatic Forecasting Algorithm
  • 4 Experimental Results
  • 5 Conclusions
  • References
  • Software Defined Networking Opportunities for Intelligent Security Enhancement of Industrial Control Systems
  • 1 Introduction
  • 2 Overview of ICS
  • 2.1 Network Architecture
  • 3 Evolution of Cyber Security Demands in Industrial Systems
  • 4 SDN Benefits in Securing ICS
  • 4.1 SDN Research
  • 4.2 Exploitable Affinities
  • 4.3 Protocols and Experimentation Tools
  • 5 Discussion and Future Research Lines
  • 6 Conclusions
  • References
  • CISIS 2017: Applications of Intelligent Methods for Security
  • Empirical Study to Fingerprint Public Malware Analysis Services
  • 1 Introduction
  • 2 Related Work
  • 3 Characterization of Public Malware Analysis Services
  • 4 Experiments and Discussion
  • 4.1 Experiment Description
  • 4.2 Machine Characterization
  • 4.3 Discussion
  • 5 Evasion of PMAS Fingerprinting
  • 6 Conclusions and Future Work
  • References
  • Illegal Activity Categorisation in DarkNet Based on Image Classification Using CREIC Method
  • 1 Introduction
  • 2 Methodology
  • 2.1 Image Classification and Descriptors Used
  • 2.2 Ideal Radius Selection
  • 2.3 Radius Estimation
  • 3 Experimentation and Results
  • 3.1 Datasets
  • 3.2 Implementation Details
  • 3.3 Results
  • 3.4 Radius Estimation
  • 4 Conclusions
  • References
  • AES-CTR as a Password-Hashing Function
  • 1 Introduction
  • 2 Description
  • 2.1 Parameters
  • 2.2 Elements
  • 2.3 Initialization
  • 2.4 Output
  • 3 Analysis
  • 3.1 Performance
  • 3.2 Security
  • 4 Conclusions
  • References
  • FAST: A High-Performance Architecture for Heterogeneous Big Data Forensics
  • 1 Introduction
  • 2 Related Work
  • 2.1 File Carving: Signature-Based Detection Algorithms
  • 2.2 Sparse Memory Pointers
  • 3 Implementation
  • 4 Experimental Results
  • 5 Conclusion
  • References
  • CISIS 2017: Identification, Simulation and Prevention of Security and Privacy Threats in Modern Communication Networks
  • New Approaches of Epidemic Models to Simulate Malware Propagation
  • 1 Introduction
  • 2 Critical Revision of the Proposed Mathematical Models
  • 3 New Mathematical Model to Simulate Malware Propagation
  • 4 Existence and Uniqueness of Solutions
  • 5 Stability Analysis
  • 5.1 Equilibrium Points and Basic Reproductive Number
  • 5.2 Local Stability of Equilibria
  • 5.3 Global Stability of Equilibria
  • 6 Numerical Simulations and Control Measures
  • 7 Conclusions and Future Work
  • References
  • A SEIR Model for Computer Virus Spreading Based on Cellular Automata
  • 1 Introduction
  • 2 Cellular Automata on Graphs
  • 3 The SEIR Proposed Model
  • 4 Examples and Discussion
  • 5 Conclusions
  • References
  • A Proposal for Using a Cryptographic National Identity Card in Social Networks
  • 1 Introduction
  • 2 Smart Card Concepts
  • 3 DNIe 2.0
  • 4 DNIe 3.0
  • 5 Proposed Framework
  • 6 Conclusions
  • References
  • A Parameter-Free Method for the Detection of Web Attacks
  • 1 Introduction
  • 2 Taxonomy of the Main Procedures for Anomaly Detection in HTTP Traffic
  • 3 URL Anomaly Detection Method Based on NCD
  • 4 Methodology and Results
  • 4.1 Data Preparation
  • 4.2 Results
  • 5 Conclusions
  • References
  • A Review of Cryptographically Secure PRNGs in Constrained Devices for the IoT
  • 1 Introduction
  • 2 Literature Survey
  • 2.1 PRNG and TRNG Target for Wireless Sensor Networks
  • 2.2 PRNG in RFID
  • 3 Analysis of Trifork Suitability for Using in Constrained Devices
  • 4 Conclusions
  • References
  • Encrypted Cloud: A Software Solution for the Secure Use of Free-Access Cloud Storage Services
  • 1 Introduction
  • 2 Main Components of Encrypted Cloud
  • 3 Key Distribution Protocol
  • 4 Users Management Protocol
  • 5 Data Redundancy Policy
  • 6 Conclusions and Future Work
  • References
  • ICEUTE 2017
  • A Proposal to Integrate Conversational Interfaces in Mobile Learning Applications
  • 1 Introduction
  • 2 State of the Art
  • 3 Framework to Develop Educative Conversational Apps
  • 4 Practical m-Learning Multimodal Application
  • 5 Evaluation
  • 5.1 Desing of the Evaluation Process
  • 5.2 Discussion of the Results and Improvement Suggestions
  • 6 Conclusions and Future Work
  • References
  • Developing Cooperative Evaluation Methodologies in Higher Education
  • 1 Introduction
  • 2 Academic Context
  • 3 Evaluation Methodologies
  • 4 Project Results
  • 5 Conclusions
  • References
  • Assessment of the Recent Postgraduates in Cybersecurity on Barriers and Required Skills for Their Ea ...
  • Abstract
  • 1 Cybersecurity Overview
  • 2 Barriers to Early Career in Cybersecurity
  • 2.1 Social/Institutional Challenges
  • 2.2 Personal Challenges
  • 3 Method and Data
  • 4 Results
  • 4.1 Early Career Barriers
  • 4.2 Required Skills and Knowledge vs Personality Traits
  • 4.3 Success Factors
  • 5 Conclusions
  • References
  • Analysis of Professional Ethics in Engineering Undergraduate Degrees
  • 1 Introduction
  • 2 Professional Ethics and Engineering Degrees
  • 3 Analysis of Ethics Contents, Methodology and Some Results
  • 4 Conclusions
  • References
  • PID-ITS: An Intelligent Tutoring System for PID Tuning Learning Process
  • Abstract
  • 1 Introduction
  • 2 Software to Teach the PID Tuning Discipline
  • 3 PID Intelligent Tutoring System (ITS)
  • 3.1 PID Tuning Procedure
  • 3.2 ITS Architecture
  • 4 Exercise Example
  • 5 Conclusions and Future Works
  • References
  • Teaching Project Management to Multicultural Students: A Case Study at Universities of León and Xiangtan
  • Abstract
  • 1 Introduction
  • 2 Method
  • 2.1 Project Management Course
  • 2.2 Teaching Agreement Between University of León and University of Xiangtan
  • 2.3 Participants
  • 2.4 Data Collection
  • 3 Analysis and Results
  • 3.1 Grades
  • 3.2 Sociology
  • 3.3 Acquisition of Competences
  • 4 Discussion
  • 5 Conclusions
  • Acknowledgements
  • References
  • Analysis of the Online Interactions of Students in the Project Management Learning Process
  • Abstract
  • 1 Introduction
  • 2 Method
  • 2.1 Participants
  • 2.2 Procedure
  • 2.3 Data Analysis
  • 3 Results
  • 3.1 Descriptive Analysis
  • 3.2 Correlation
  • 3.3 Text Mining Results
  • 4 Conclusions
  • Acknowledgements
  • References
  • A Virtual Learning Environment to Support Project Management Teaching
  • 1 Introduction
  • 2 Main Characteristics of the Proposed VLE
  • 3 VLE Development and Implementation
  • 3.1 The PPM Software
  • 3.2 The CMS
  • 3.3 The Global Discussion Group
  • 3.4 The Survey Software
  • 3.5 The Specifically Developed Tool
  • 4 Results
  • 5 Conclusions
  • References
  • Author Index

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