Note: Intro -- Preface -- Acknowledgements -- Contents -- Contributors -- List of Figures -- List of Tables -- Methodologies on Supply Chain -- 1 Impact of Managers and Human Resources on the Supply Chain Performance -- 1.1 Introduction -- 1.2 Literature Review and Hypotheses -- 1.2.1 Managerial Commitment -- 1.2.2 Learning Environment in the SC -- 1.2.3 Employee Competencies -- 1.2.4 Supply Chain Performance -- 1.3 Methodology -- 1.3.1 Step 1. Literature Review and Survey Design -- 1.3.2 Step 2. Survey Administration -- 1.3.3 Step 3. Data Screening -- 1.3.4 Step 4. Statistical Validation of Data -- 1.3.5 Step 5. Sample Descriptive Analysis -- 1.3.6 Step 6. Structural Equation Model -- 1.3.7 Step 7. Sensitivity Analysis -- 1.4 Results -- 1.4.1 Descriptive Analysis of the Sample -- 1.4.2 Validation of Latent Variables -- 1.4.3 Structural Equation Model -- 1.4.4 Effects Analysis -- 1.4.5 Sensitivity Analysis -- 1.5 Conclusions and Industrial Implications -- References -- 2 The Role of Employees' Performance and External Knowledge Transfer on the Supply Chain Flexibility -- 2.1 Introduction -- 2.2 Literature Review and Hypothesis -- 2.2.1 External Knowledge Transfer (EKT) -- 2.2.2 Supply Chain Complexity (SCC) -- 2.2.3 Employee's Performance (EP) -- 2.2.4 Supply Chain Flexibility (SCF) -- 2.3 Methodology -- 2.3.1 Literature Review and Questionnaire Development -- 2.3.2 Questionnaire Application -- 2.3.3 Data Debugging and Validation -- 2.3.4 Structural Equation Modeling -- 2.4 Results -- 2.4.1 Descriptive Analysis of Sample -- 2.4.2 Questionnaire Statistic Validation -- 2.4.3 Structural Equation Modeling -- 2.4.4 Direct Effects -- 2.4.5 Indirect Effects -- 2.4.6 Total Effects -- 2.4.7 Sensitivity Analysis -- 2.5 Conclusions -- References -- 3 Modern Slavery in the Global Supply Chains: The Challenges of Legislations and Mandatory Disclosures. , 3.1 Introduction -- 3.2 Explaining Modern Slavery in the Global Supply Chain Through Institutional Theory -- 3.2.1 Conditions Responsible for Modern Slavery in Global Supply Chains -- 3.3 Global Initiatives to Address and Eradicate Modern Slavery in the Supply Chains -- 3.3.1 The Know (Due Diligence) and Show (Disclosure) Frameworks for Company's Law -- 3.4 Transparency Legislations on Modern Slavery -- 3.4.1 The UK Modern Slavery Act 2015 -- 3.4.2 The California Transparency in Supply Chain Act (2010) -- 3.4.3 The French Duty of Vigilance Law (2017) -- 3.5 Challenges with Legislations Requiring Mandatory Disclosures on Modern Slavery -- 3.6 Conclusion and Recommendations -- References -- 4 Urban Goods Distribution Under Environmental Contingency in Medellín -- 4.1 Introduction -- 4.2 Theory Background -- 4.3 Methodology -- 4.4 Case of Study -- 4.4.1 Environmental Contingency in the City -- 4.4.2 Case Analysis -- 4.5 Conclusions -- References -- 5 Operational Risk Management in a Retail Company -- 5.1 Introduction -- 5.1.1 Risk Identification -- 5.1.2 Risk Assessment and Prioritization -- 5.2 Methodology -- 5.3 Results -- 5.3.1 Phase 1 and 2. Identifying Internal Variables, the "WHATs", and Determining Their Relative Significance -- 5.3.2 Phase 3. Identifying Strategic Objectives or "HOWs" -- 5.3.3 Phase 4 and 5. Determining the Correlation Between the "WHATs" and the "HOWs", and Assigning a Weight to Each HOW -- 5.3.4 Phase 6 and 7. Determining Risks' Impacts on the Strategic Objectives, "HOWs", and Establishing Risks' Priorities -- 5.3.5 Strategies or Actions to Mitigate Operational Risks -- 5.4 Conclusions -- References -- 6 Knowledge and Skills of a Logistics Manager Required by the Manufacturing Industry of Ciudad Juárez -- 6.1 Introduction -- 6.2 Logistics: Definition -- 6.3 Importance of Logistics -- 6.4 Skills of the Logistics Professional. , 6.5 Skills and Knowledge in Logistics Required by Companies -- 6.6 Theoretical Model -- 6.6.1 Supply Chain Management -- 6.6.2 Quantitative Methods -- 6.6.3 Information Technologies -- 6.6.4 Finance -- 6.6.5 Legislation -- 6.6.6 Soft Skills -- 6.7 Methodology -- 6.8 Results -- 6.8.1 Construction of the Path Diagram -- 6.8.2 Conversion of the Path Diagram in a Model of Measurement and Factorial Equations -- 6.8.3 Identification of the Model -- 6.8.4 Evaluation of the Criteria of the Goodness of Adjustment -- 6.8.5 Measures of Goodness of Global Adjustment -- 6.8.6 Measures of Goodness of Incremental Adjustment -- 6.8.7 Measures of Adjustment of Parsimony -- 6.8.8 Interpretation of the Model -- 6.9 Conclusions -- References -- Techniques in Supply Chain -- 7 Supply Chain in Small and Medium-Sized Enterprises in the Furniture Industry -- 7.1 Introduction -- 7.2 Literature Review -- 7.2.1 Case Studies and Focus Group -- 7.2.2 Supply Chain Management -- 7.2.3 Failure Mode, Effects and Criticality Analysis (FMECA) -- 7.2.4 Main Contributions -- 7.3 Methodology -- 7.3.1 Case Study -- 7.3.2 Diagnostics Based on Pre-specified Procedures -- 7.4 Results -- 7.4.1 Step 1, Operation Flow -- 7.4.2 Step 2, Qualitative Framework Analysis for Focus Groups -- 7.4.3 Step 3, Areas and Activities Associated with the Supply Chain and Its Failures Focus Group No. 1 (FG1) -- 7.4.4 Step 4, Identification of the Root Cause of Failure and the Criteria for the Criticality Analysis FG No. 2 (FG2) -- 7.4.5 Step 5, Evaluation of the Criticality of the Failure and Calculation of the Risk Priority Number (RPN), FG No. 3 (FG3) -- 7.4.6 Remarks on the Calculation of the RPN -- 7.4.7 Step 6, Solution Means to Counteract the Root Causes, FG No. 4 (FG4) -- 7.4.8 Economic Impact of Failures -- 7.5 Conclusions -- References. , 8 A New Methodology to Forecast and Manage Inventory in Mobile Warehouses -- 8.1 Introduction -- 8.2 Literature Review -- 8.2.1 Mobile Warehouses and Mobile Depots -- 8.2.2 Forecasting Time Series -- 8.2.3 Inventory Management Theory -- 8.3 Forecasting and Inventory Management Methodology Proposal -- 8.3.1 Demand Classification and Categorization -- 8.3.2 Forecast Method Selection -- 8.3.3 Forecasting -- 8.3.4 Inventory Management Method -- 8.3.5 What, How Much, Where, and When -- 8.4 Study Case: ZDelivery -- 8.5 Methodology Applied to the Case Study -- 8.5.1 Interest Problematic Definition and Data Collection -- 8.5.2 Mathematical Tools and Models -- 8.5.3 Computer-Based Methods -- 8.5.4 Testing and Refinement -- 8.5.5 Preparation and Generalization -- 8.6 Results -- 8.6.1 Interest Problematic Definition and Data Collection -- 8.6.2 Mathematical Tools and Models -- 8.6.3 Computer-Based Methods -- 8.6.4 Preparation and Generalization -- 8.7 Conclusions -- 8.8 Limitations and Further Research -- References -- 9 Mathematical Model for Product Allocation in Warehouses -- 9.1 Introduction -- 9.2 Goods Allocation in Warehouses -- 9.3 Product Allocation Model -- 9.3.1 Genetic Algorithm to Solve the Product Allocation Model -- 9.4 Model Application -- 9.4.1 Results and Discussions -- 9.5 Conclusions -- References -- 10 Designing a Supply Chain for the Generation of Bioenergy from the Anaerobic Digestion of Citrus Effluents -- 10.1 Introduction -- 10.2 Literature Review -- 10.2.1 Citrus Production (in Mexico and at the Global Level) -- 10.2.2 Supply and Distribution of Citrus in Mexico -- 10.2.3 Citrus Industry in Mexico -- 10.2.4 Residues from the Citrus Industry -- 10.2.5 Anaerobic Digestion -- 10.2.6 Biogas Production -- 10.2.7 Inhibition by D-Limonene in Anaerobic Digestion -- 10.2.8 High-Rate Reactors -- 10.2.9 State-of-the-Art -- 10.3 Methodology. , 10.3.1 Case Study -- 10.3.2 Energy Analysis Using Biogas -- 10.4 Results -- 10.5 Conclusions -- References -- 11 Effective Design of Service Supply Chains in México -- 11.1 Introduction -- 11.2 Importance of Service Sector in Mexico -- 11.2.1 Challenges and Trends in Supply Chains in Mexico -- 11.3 Elements Associated with the Design of a Distribution Network -- 11.3.1 Types of Distribution Network of the Supply Chain -- 11.4 Supply Chain Management -- 11.4.1 Management Models -- 11.5 Indicators of Customer Service -- 11.6 Lean Supply Chain -- 11.6.1 Value Chain -- 11.7 Importance of the Supply Chain as a Competitive Advantage -- 11.7.1 Importance of Technology in Supply Chains -- 11.8 Conclusions -- References -- 12 Systemic Approach for the Design of Renewable Energy Supply Chain Generated from Biomass -- 12.1 Introduction -- 12.2 Tools for Renewable Energy Study -- 12.2.1 Biomass in the Energy Sector -- 12.2.2 Design and Assessment of Renewable Supply Chains Using System Dynamics -- 12.3 Conceptual Design of the Biomass-Based Power Generation Supply Chain -- 12.3.1 Methodology -- 12.3.2 Case Study Selection Module -- 12.3.3 Case Study -- 12.4 Results -- 12.4.1 Balance Loop B1 -- 12.4.2 Balance Loop B2 -- 12.4.3 Balance Loop B3 -- 12.4.4 Reinforcing Loop R1 -- 12.4.5 Reinforcing Loop R2 -- 12.4.6 Distribution Loop -- 12.5 Conclusions and Future Work -- References -- 13 Supply Chain Design by Minimizing Equivalent Present Cost Considering Weighted Variable Costs -- 13.1 Introduction -- 13.2 Literature Review -- 13.3 Methodology -- 13.3.1 Model Description -- 13.3.2 Mathematical Formulation -- 13.3.3 Solution Approach -- 13.4 Results -- 13.5 Conclusions -- References -- Tools on Supply Chain -- 14 Perishable Product Sensitivity Analysis in the Design of an Inventory Control System in a Three-Echelon Fruit Supply Chain -- 14.1 Introduction. , 14.2 Problem Statement.

Note: Intro -- Preface -- Acknowledgements -- Contents -- Contributors -- List of Figures -- List of Tables -- Key Points -- Decision Support Systems for Industry -- 1 FINALGRANT: A Financial Linked Data Graph Analysis and Recommendation Tool -- Abstract -- 1 Introduction -- 2 Fundamental Analysis -- 2.1 Financial Ratios -- 2.2 Financial Statements -- 2.3 Financial Statements in XBRL -- 3 The XBRL-Linked Data Transformation Process with FINALGRANT -- 3.1 Semantic Model for Financial Data -- 4 Case Study: Financial Analysis of Walmart with FINALGRANT -- 4.1 Walmart's Current Ratio -- 4.2 Walmart's Working Capital Ratio -- 4.3 Walmart's Acid-Test Ratio -- 4.4 Debt Ratio -- 4.4.1 Walmart's Debt Ratio -- 4.5 Additional Data -- 4.6 Case Study Conclusions -- 5 Research Conclusions and Further Work Recommendations -- Acknowledgements -- References -- 2 Constructing and Interrogating Actor Histories -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Actors and Histories -- 4 Constructing Histories -- 5 Interrogation of Histories -- 5.1 Typed Logic Programming -- 5.2 Meta Representation -- 5.3 Meta Interpreter -- 6 Evaluation -- 7 Conclusion -- References -- 3 Challenges in the Design of Decision Support Systems for Port and Maritime Supply Chains -- Abstract -- 1 Introduction -- 2 Components of a Decision Support System -- 3 Methodology -- 4 DSS in Port and Maritime Supply Chains: State of the Art -- 4.1 Journals and Research Groups Descriptive Statistics -- 4.2 Problems and Solution Approaches -- 4.2.1 Shipping Lines Problems -- 4.2.2 Container and Bulk Terminals -- 4.2.3 Interface Port-Container (Bulk) Terminals -- 4.2.4 Port and Maritime Management Issues -- 4.3 Data Analytics Methods -- 4.4 Collective Decision Making and Technological Innovations -- 5 Discussion and Implications -- 5.1 Discussion -- 5.2 Implications -- 6 Conclusions -- Acknowledgements. , References -- 4 Analyzing the Impact of a Decision Support System on a Medium Sized Apparel Company -- Abstract -- 1 Introduction -- 2 Background -- 2.1 Related Works -- 2.2 The Representative Apparel Company -- 3 The Proposed DSS -- 3.1 The Design of the DSS -- 3.2 The Development of the DSS -- 4 Results and Discussion -- 5 Conclusion -- Acknowledgements -- References -- 5 A Multicriteria Decision Support System Framework for Computer Selection -- Abstract -- 1 Introduction -- 1.1 Computer Adoption -- 1.2 Computer Attributes -- 1.3 The Multi-attribute Approach for Alternative Selection -- 1.4 Research Problem and Objective -- 2 Methodology -- 2.1 Integrating the Decision Group -- 2.2 Identifying Attributes -- 2.3 Selecting Evaluation Attributes -- 2.4 Identifying Alternatives -- 2.5 Selecting a Multi-attribute Technique -- 2.6 AHP and TOPSIS Techniques -- 2.6.1 AHP: Attribute Weighting -- 2.6.2 TOPSIS -- 3 Case Study -- 3.1 Integrating the Decision Group -- 3.2 Identifying Alternatives -- 3.3 Evaluated Attributes -- 3.3.1 Quantitative Attributes -- 3.3.2 Qualitative Attributes -- 3.3.3 Final Decision Matrix -- 3.3.4 Attributes Weighting-Using AHP -- 3.3.5 Normalization of Attributes -- 3.3.6 Weighting Normalized Attributes -- 3.3.7 Calculating Distances to the Ideal Solution -- 3.3.8 Calculating the Decision Index -- 4 Conclusion -- 5 Future Research -- References -- 6 An Agent-Based Memetic Algorithm for Solving Three-Level Freight Distribution Problems -- Abstract -- 1 Introduction -- 2 The Three-Level Logistic Distribution Problem -- 2.1 Mathematical Formulation Three-Level Logistic Distribution Problem -- 2.2 Multi-Agent Systems for Solving Logistics Problems -- 3 Methodology -- 3.1 Multi-agent Model -- 3.2 Agent-Based Memetic Algorithm -- 4 Results -- 5 Conclusions -- References. , Case Studies: Clinical, Emergency Management and Pollution Control -- 7 DiabSoft: A System for Diabetes Prevention, Monitoring, and Treatment -- Abstract -- 1 Introduction -- 2 Related Works -- 3 Architecture of DiabSoft System -- 3.1 Overview of the Architecture Based on Its Functionality -- 4 Case Study -- 4.1 User Monitoring -- 4.1.1 Record of Symptoms, Vital Signs and User Habits -- 4.1.2 Recommendations for Diabetes Prevention and Care -- 5 Conclusions and Future Directions -- Acknowledgements -- References -- 8 Health Monitor: An Intelligent Platform for the Monitorization of Patients of Chronic Diseases -- Abstract -- 1 Introduction -- 2 State of the Art -- 3 Health Monitor's Architecture -- 3.1 Parameters Monitoring -- 3.2 Alerts Management -- 3.3 Health Recommender Module -- 3.4 Monitoring of Patients -- 4 Evaluation and Results -- 4.1 Selection of Participants -- 4.2 Generation of Recommendations -- 4.3 Analysis of Results -- 5 Conclusions -- Acknowledgements -- References -- 9 Reliable and Smart Decision Support System for Emergency Management Based on Crowdsourcing Information -- Abstract -- 1 Introduction -- 2 Related Work -- 3 The RESCUER Vision -- 4 The Realisation of the RESCUER Vision -- 4.1 Gathering Data -- 4.2 Prioritising Data -- 4.3 Analysing Text -- 4.4 Analysing Images -- 4.5 Analysing Videos -- 4.6 Aggregating Data -- 4.7 Visualising Relevant Data -- 4.8 Further Features -- 5 The Evaluation of the RESCUER Solution -- 6 Conclusion -- Acknowledgements -- References -- 10 Intelligent Decision Support for Unconventional Emergencies -- Abstract -- 1 Introduction -- 2 Brief Account of Related Work -- 3 An Intelligent Decision Support System for Unconventional Emergencies -- 3.1 Research Gaps -- 3.2 Problem Statement -- 3.3 Tools -- 4 Knowledge Representation and Storage. , 4.1 Creating the Ontology of Emergency Situations and Resources -- 4.2 Archiving Past Experiences (Storing Cases) -- 4.3 Expertise Acquisition (Codifying Rules) -- 5 Generating Recommendations -- 5.1 Input and Data Pre-processing Layer (IDPL) -- 5.2 Two Level Computation Layer (2LCL) -- 5.3 Output and Data Dissemination Layer (ODDL) -- 6 Concluding Remarks and Future Proposals -- References -- 11 Information Technology in City Logistics: A Decision Support System for Off-Hour Delivery Programs -- Abstract -- 1 Introduction -- 2 Literature Review -- 3 Insights on OHD Programs-Bogota's Case -- 4 OHD Key Performance Indicators -- 4.1 KPIs Methodology Calculation -- 4.1.1 Logistics Performance KPIs -- 4.1.2 Time KPIs -- 4.1.3 Cost KPIs -- 5 Decision Support System for OHD Programs -- 5.1 Solution Architecture -- 6 Conclusions and Future Research -- References.

Note: Intro -- Preface -- Acknowledgements -- Contents -- Contributors -- List of Figures -- List of Tables -- Part I Industrial Applications -- 1 Merging Event Logs for Inter-organizational Process Mining -- 1.1 Introduction -- 1.2 Related Work -- 1.3 Preliminaries and Definitions -- 1.4 Methodology -- 1.4.1 Phase 1: Processing of Event Logs -- 1.4.2 Phase 2: Identifying the Correlation Between Events -- 1.4.3 Phase 3: Collaboration Discovery -- 1.5 Results -- 1.6 Conclusions -- References -- 2 Towards Association Rule-Based Item Selection Strategy in Computerized Adaptive Testing -- 2.1 Introduction -- 2.2 Background -- 2.3 Related Work -- 2.4 Methods and Analysis -- 2.4.1 CAT Process with ARM as Item Selection Criterion -- 2.4.2 Collection and Preparation of Data -- 2.4.3 Evaluation of Algorithms -- 2.5 Results and Discussion -- 2.6 Recommendations -- 2.7 Conclusions and Future Work -- References -- 3 Uncertainty Linguistic Summarizer to Evaluate the Performance of Investment Funds -- 3.1 Introduction -- 3.2 Preliminaries -- 3.2.1 Uncertain Logic -- 3.2.2 Linguistic Summarizer -- 3.3 Problem and Methodology -- 3.3.1 Data Set -- 3.3.2 Linguistic Summaries -- 3.4 Results -- 3.4.1 Checking the First Uncertain Proposition FileRef="494983_1_En_3_Figa_HTML.png" Format="PNG" Color="BlackWhite" Type="LinedrawHalftone" Rendition="HTML" Height="77" Resolution="300" Width="150 -- 3.4.2 Truth Value Versus Probability Measure -- 3.4.3 Scope and Other Possibilities -- 3.5 Conclusions -- References -- 4 Map-Bot: Mapping Model of Indoor Work Environments in Mobile Robotics -- 4.1 Introduction -- 4.2 Materials and Methods -- 4.3 Results and Discussion -- 4.3.1 Mobile Robotic Agent -- 4.3.2 Communication Interface -- 4.3.3 Navigation Module Magalhães -- 4.3.4 Vespucci: Mapping Module for Indoor Environments -- 4.4 Conclusions and Future Work -- References. , 5 Production Analysis of the Beekeeping Chain in Vichada, Colombia. A System Dynamics Approach -- 5.1 Introduction -- 5.2 Literature Review -- 5.3 Methodological Approach -- 5.3.1 Causal Diagram -- 5.3.2 Forrester Diagram -- 5.4 Results -- 5.5 Conclusions -- References -- 6 Effect of TPM and OEE on the Social Performance of Companies -- 6.1 Introduction -- 6.1.1 JIT -- 6.1.2 Overall Equipment Effectiveness (OEE) -- 6.1.3 Total Productive Maintenance (TPM) -- 6.1.4 Social Benefits -- 6.1.5 Chapter Objective -- 6.2 Hypothesis -- 6.3 Methodology -- 6.3.1 Questionnaire Developing -- 6.3.2 Questionnaire Application -- 6.3.3 Registration and Data Debugging -- 6.3.4 Questionnaire Validation -- 6.3.5 Structural Equation Model -- 6.4 Results -- 6.4.1 Description of the Sample -- 6.4.2 Validation of Latent Variables -- 6.4.3 Descriptive Analysis of Variables -- 6.4.4 Structural Equation Model -- 6.4.5 Sensitivity Analysis -- 6.5 Conclusions -- References -- 7 ENERMONGRID: Intelligent Energy Monitoring, Visualization and Fraud Detection for Smart Grids -- 7.1 Introduction -- 7.2 Related Work -- 7.3 ENERMONGRID -- 7.3.1 Architecture -- 7.3.2 Types of Data and Reports -- 7.3.3 Considerations and Restrictions -- 7.3.4 Real-Time Data Anomalies -- 7.3.5 Reading Rates of Original Reports -- 7.3.6 KPIs of Energy Balances -- 7.3.7 Alerts -- 7.4 Work Approach -- 7.5 Related Projects: INDIGO -- 7.6 Conclusions, Related Work and Future Work -- References -- Part II Decision-Making Systems for Industry -- 8 Measuring Violence Levels in Mexico Through Tweets -- 8.1 Introduction -- 8.2 Related Works -- 8.3 Model for Knowledge Acquisition -- 8.4 Methodology -- 8.4.1 Keyword Selection Layer -- 8.4.2 Pre-processing Data Layer -- 8.4.3 Data Processing Layer -- 8.5 Results -- 8.5.1 Hashtag Analysis -- 8.5.2 State-Level Analysis -- 8.5.3 Metropolitan Zone Level Analysis. , 8.6 Conclusions -- References -- 9 Technology Transfer from a Tacit Knowledge Conservation Model into Explicit Knowledge in the Field of Data Envelopment Analysis -- 9.1 Introduction -- 9.2 Literature Review -- 9.2.1 CCR-I Model-Multiplicative Form -- 9.2.2 CCR-O Model-Multiplicative Form -- 9.2.3 BCC Model -- 9.2.4 BCC-I Model-Multiplicative Form -- 9.2.5 BCC-O Model-Multiplicative Form -- 9.2.6 Non-discretionary Models -- 9.3 Results and Discussion -- 9.3.1 Layer Model for the Conservation of Tacit Knowledge in the DEA On-Discretionary Models -- 9.3.2 SEUMOD Model -- 9.4 Conclusions and Future Work -- References -- 10 Performance Analysis of Decision Aid Mechanisms for Hardware Bots Based on ELECTRE III and Compensatory Fuzzy Logic -- 10.1 Introduction -- 10.2 State of the Art -- 10.3 Background -- 10.3.1 ELECTRE Method -- 10.3.2 Fuzzy Logic -- 10.3.3 Compensatory Fuzzy Logic -- 10.4 Proposed Architecture for Decision Aid -- 10.5 Analysis of Proposed Decision Aid Mechanism -- 10.5.1 Experimental Design -- 10.5.2 Case of Study -- 10.5.3 Instance Definition -- 10.5.4 Artificial Decision Maker -- 10.5.5 Historical Data -- 10.5.6 Performance Indicators -- 10.5.7 Validation -- 10.6 Results -- 10.6.1 Elicitation of Thresholds and Reference Values -- 10.6.2 Definition of CFL Rules -- 10.6.3 Performance Measurement Using Indicators S1 y S2 -- 10.7 Successful Cases and Discussion -- 10.8 Conclusions -- References -- 11 A Brief Review of Performance and Interpretability in Fuzzy Inference Systems -- 11.1 Introduction -- 11.2 Background of the Study -- 11.2.1 Knowledge Discovery -- 11.2.2 Fuzzy Logic -- 11.2.3 Compensatory Fuzzy Logic -- 11.2.4 Archimedean Compensatory Fuzzy Logic -- 11.2.5 Fuzzy Inference Systems -- 11.2.6 Inference in Compensatory Fuzzy Systems -- 11.2.7 Performance of Systems Based on Fuzzy Rules. , 11.2.8 Semantic Interpretability in Fuzzy Systems -- 11.2.9 Restrictions and Interpretability Criteria -- 11.3 Literature Analysis on Surveys and Reviews -- 11.4 Research Methodology -- 11.5 Research Analysis -- 11.5.1 A Basic Case of Study of Interpretability with CFL -- 11.5.2 Interpretability Comparison of CFL Whit Other Fuzzy Logic Structures -- 11.5.3 Related Works in Balancing Accuracy-Interpretability -- 11.5.4 Related Works in Interpretable Inference with CFL -- 11.6 Research Findings and Discussion -- 11.6.1 Analytics of Research Papers -- 11.6.2 Discussion of Papers on Accuracy-Interpretability -- 11.6.3 Open Trends to Research -- 11.7 Future Research Focus -- 11.8 Conclusions and Recommendations -- References -- 12 Quality and Human Resources, Two JIT Critical Success Factors -- 12.1 Introduction -- 12.1.1 Quality and JIT -- 12.1.2 Human Factors and JIT Benefits -- 12.2 Methodology -- 12.2.1 Survey Development -- 12.2.2 Data Collection -- 12.2.3 Data Analysis and Survey Validation -- 12.2.4 Descriptive Analysis -- 12.2.5 Structural Equation Model -- 12.3 Results -- 12.3.1 Sample Description -- 12.3.2 Data Validation -- 12.3.3 Descriptive Analysis -- 12.3.4 Structural Equation Model -- 12.4 Conclusions and Industrial Implications -- References -- 13 Operational Risks Management in the Reverse Logistics of Lead-Acid Batteries -- 13.1 Introduction -- 13.2 Methodology -- 13.2.1 Characterization of the Recovery Process -- 13.2.2 Identifying Risks at Every Stage of the Process -- 13.2.3 Risk Prioritization Using Fuzzy Quality Function Deployment -- 13.2.4 Actions to Mitigate or Eliminate Critical Risks -- 13.3 Results -- 13.3.1 Characterization of the Recovery Process -- 13.3.2 Identification of Operational Risks -- 13.3.3 Prioritization of Operational Risks -- 13.3.4 Actions to Mitigate or Eliminate Critical Risks -- 13.4 Conclusions. , References -- 14 Dynamic Evaluation of Livestock Feed Supply Chain from the Use of Ethanol Vinasses -- 14.1 Introduction -- 14.2 Background -- 14.2.1 Vinasse for Energy Production -- 14.2.2 Vinasse as Soil Fertilizer -- 14.2.3 Vinasse for Animal Feed Production -- 14.3 Conceptual Design of the Vinasse-Based LF Supply Chain -- 14.3.1 Methodology -- 14.3.2 Case Study -- 14.4 Results -- 14.4.1 Causal Diagram -- 14.4.2 Simulation Model -- 14.5 Conclusions and Future Work -- References -- Part III Artificial Intelligence Techniques -- 15 Comparative Analysis of Decision Tree Algorithms for Data Warehouse Fragmentation -- 15.1 Introduction -- 15.2 Background -- 15.3 Related Works -- 15.4 Method -- 15.4.1 Collection and Preparation of Data -- 15.4.2 Application of Decision Tree Algorithms -- 15.5 Results -- 15.6 Conclusions and Future Work -- References -- 16 Data Analytics in Financial Portfolio Recovery Management -- 16.1 Introduction -- 16.2 Literature Review -- 16.3 Proposed Approach -- 16.3.1 Data Collection -- 16.3.2 Data Preprocessing -- 16.4 Results -- 16.5 Conclusion and Future Work -- References -- 17 Task Thesaurus as a Tool for Modeling of User Information Needs -- 17.1 Introduction -- 17.2 Domain Ontologies and Task Thesauri as Main Semantic Elements of User Profile -- 17.2.1 Domain Ontologies and Their Formal Models -- 17.2.2 Task Thesaurus as a Personified View on the Domain Ontology -- 17.3 Methods of Thesaurus Development -- 17.3.1 IR Thesaurus Generation Algorithm -- 17.3.2 Semantic Similarity Estimations as a Theoretic Basis of Ontology-Based Thesaurus Generation -- 17.3.3 Ontological Relations as an Instrument of Task Thesaurus Generation -- 17.4 Practical Use of Task Thesauri in Various Intelligent Applications -- 17.4.1 Search Results Filtering by Task Thesaurus. , 17.4.2 Analysis of User Competencies for Selection of Learning Resources.

Note: Intro -- Preface -- Acknowledgements -- Contents -- Contributors -- List of Figures -- List of Tables -- Knowledge Acquisition & -- Representation -- 1 Personalization of Ontologies Visualization: Use Case of Diabetes -- 1.1 Introduction -- 1.2 State of the Art -- 1.2.1 Personalization of Ontologies Visualization -- 1.2.2 Diabetes Mellitus -- 1.2.3 Diabetes Ontologies -- 1.3 Approach -- 1.3.1 Overview -- 1.3.1.1 Navigation Menus -- 1.3.1.2 Treemaps -- 1.3.1.3 Site Maps and Site Indexes -- 1.3.2 Facets -- 1.3.3 Approach Validation -- 1.4 Case Study -- 1.5 Conclusions and Future Work -- Author's contributions -- References -- 2 Semantic Data Integration of Big Biomedical Data for Supporting Personalised Medicine -- 2.1 Introduction -- 2.2 Preliminaries -- 2.2.1 The 5Vs Model for Biomedical Data -- 2.2.2 Knowledge Modeling and Ontologies -- 2.2.3 Ontologies in the Biomedical Domain -- 2.2.4 The RDF Mapping Language (RML) -- 2.2.5 Federated Query Processing -- 2.3 Related Work -- 2.3.1 Big Data -- 2.3.2 Semantic Data Integration -- 2.3.3 Knowledge Management and Query Processing -- 2.3.4 Data Privacy -- 2.4 A Knowledge-Driven Framework -- 2.5 Applying the Knowledge-Driven Framework in Big Data Based Project iASiS -- 2.5.1 Big Biomedical Data Sources -- 2.5.2 Techniques for Extracting Knowledge from Big Biomedical Data -- 2.5.3 The iASiS Unified Schema -- 2.5.4 The Knowledge Graph Creation -- 2.5.5 Exploring and Querying a Knowledge Graph -- 2.5.6 Knowledge Discovery over a Knowledge Graph -- 2.6 Conclusions and Future Work -- Acknowledgements -- References -- 3 Interaction Net as a Representation Model of a Programming Language -- 3.1 Introduction -- 3.2 Interactions Nets as a Model for the Programming Language -- 3.2.1 Realization of the Model of Computation to the Programming Language -- 3.2.2 Operating Conditions Language. , 3.3 Implementation of Interactions -- 3.3.1 Reference Languages -- 3.3.2 Operating Environment -- 3.3.3 Infrastructure-Less and Operation -- 3.3.4 Architecture Networks -- 3.3.5 Implementation of Interactions -- 3.4 Programming Language Tests -- 3.4.1 Expansion of Coverage -- 3.4.2 Sensor Network -- 3.4.3 Node Connectivity -- 3.5 Comparison with Other Programming Languages -- 3.6 Conclusions -- References -- 4 An Adaptive Trust Model for Achieving Emergent Cooperation in Ad Hoc Networks -- 4.1 Introduction -- 4.2 Related Work: Cooperation Models in Ad Hoc Networks -- 4.2.1 Cooperation Models -- 4.2.2 Social Dilemmas -- 4.3 An Adaptive Model of Trust -- 4.4 Simulation Scenarios -- 4.4.1 Scenario 1: No Error -- 4.4.2 Scenario 2: Errors in the Communication Process -- 4.4.3 Scenario 3: A Dynamic Population -- 4.5 A Meta-strategy on Cooperative-Competitive Games -- 4.6 Conclusions -- References -- 5 Operational Risk Identification in Ground Transportation Activities: Ontology-Approach -- 5.1 Introduction -- 5.2 Literature Review -- 5.2.1 Supply Chain Risk Management (SCRM) -- 5.2.2 Operational Risk Management -- 5.2.3 Risk Identification -- 5.2.4 Ontologies -- 5.3 Methodology -- 5.3.1 Determine the Domain and Scope of the Ontology, Its Purpose and Its Objective -- 5.3.2 Consider Reusing Existing Ontologies -- 5.3.3 Enumerate Important Terms in the Ontology -- 5.3.4 Define the Classes and the Class Hierarchy -- 5.3.5 Define the Properties of Classes-Slots -- 5.3.6 Define the Facets of the Slots -- 5.3.7 Create Instances -- 5.4 Results -- 5.4.1 Determine the Domain and Scope of the Ontology, Its Purpose and Its Objective -- 5.4.2 Consider Reusing Existing Ontologies -- 5.4.3 Enumerate Important Terms in the Ontology -- 5.4.4 Define the Classes and the Class Hierarchy -- 5.4.5 Define the Properties of Classes-Slots -- 5.4.6 Create Instances. , 5.5 Conclusions and Industrial Implications -- References -- 6 Challenges in RDF Validation -- 6.1 Introduction -- 6.2 RDF Data Model -- 6.3 Validating RDF Data -- 6.3.1 ShEx -- 6.3.2 SHACL -- 6.3.3 Comparing ShEx and SHACL -- 6.3.4 Language S -- 6.3.5 From SHACL to S -- 6.3.6 From ShEx to S -- 6.4 Challenges -- 6.4.1 Negation, Recursion and Semantics -- 6.4.2 Shapes Libraries and Reusability -- 6.5 Shapes and the Semantic Web Stack -- 6.5.1 Data Transformation -- 6.5.2 Schema Inference -- 6.5.3 Validation, Modelling and Visualization -- 6.5.4 Validation Usability -- 6.5.5 Real Time and Streaming Validation -- 6.6 Conclusions and Future Work -- Acknowledgements -- References -- 7 A Bayesian Network Model for the Parkinson's Disease: A Study of Gene Expression Levels -- 7.1 Introduction -- 7.2 Theoretical Context -- 7.2.1 Genetic Aspects of PD -- 7.2.2 Microarrays -- 7.2.3 Machine Learning -- 7.2.4 Modeling Classes -- 7.2.4.1 Neurological Disease Control -- Alzheimer's Disease -- Multisystemic Atrophy -- Progressive Supranuclear Palsy -- Corticobasal Degeneration -- Healthy Control -- 7.2.5 Genes and Levels of Gene Expression -- 7.2.6 Biomarkers -- 7.3 State-of-the-Art -- 7.4 Materials and Methods -- 7.4.1 Data Set -- 7.4.2 Data Pre-processing -- 7.4.3 Normalization -- 7.4.4 Bayesian Networks -- 7.4.5 Discretization -- 7.4.6 Anova -- 7.4.7 WEKA -- 7.5 Methodology -- 7.6 Results and Discussion -- 7.6.1 Normalization of the GDS2519 Database -- 7.6.2 Bayesian Networks -- 7.6.3 Discussion -- 7.7 Conclusions and Future Work -- 7.7.1 Conclusions -- 7.7.2 Future Work -- Acknowledgements -- References -- Semantic Web Applications -- 8 Use of Sentiment Analysis Techniques in Healthcare Domain -- 8.1 Introduction -- 8.2 State of the Art on the Use of Sentiment Analysis in Healthcare Domain -- 8.3 Design of a Module for Obtaining Sentiments and Emotions. , 8.4 Process for Performing Sentiment Analysis -- 8.5 Case Studies in Healthcare Domain -- 8.5.1 Obtaining Medicines Reputation -- 8.5.2 Obtaining Medical Doctors Reputation -- 8.6 Conclusions and Future Work -- Acknowledgements -- References -- 9 Medic-Us: Advanced Social Networking for Intelligent Medical Services and Diagnosis -- 9.1 System in a Nutshell -- 9.2 Introduction -- 9.3 Related Work -- 9.4 Medic-Us -- 9.4.1 Presentation Layer -- 9.4.2 Services Layer -- 9.4.3 Business Logic Layer -- 9.4.4 Data Layer -- 9.5 Social Network Environment -- 9.5.1 Sentiment Analysis of Physician's Reviews -- 9.6 Knowledge Representation -- 9.7 Knowledge Enhancement -- 9.7.1 MedlinePlus Extraction -- 9.7.2 Automatic Summarization of Medical Literature -- 9.7.3 Named Entities Recognition for Symptoms Extraction -- 9.8 Virtual Medical Office -- 9.9 Medical Trainer -- 9.10 Conclusions -- References -- 10 Semantic PHI-Base Web Interface: A Web Tool to Interact and Visualize Plant-Pathogen Interactions Data -- 10.1 Introduction -- 10.2 Semantic PHI-Base -- 10.3 Semantic PHI-Base Web Interface -- 10.3.1 Search Interface -- 10.3.2 Visualization Interface -- 10.4 Conclusions and Future Work -- References -- 11 FASELOD: A Faceted Search Engine in Linked Open Datasets Using Voice Recognition -- 11.1 Introduction -- 11.2 Related Works -- 11.2.1 Faceted Search Engines -- 11.2.2 Projects that Apply NLP -- 11.3 Application Architecture -- 11.4 Case Studies -- 11.4.1 Search for Medical Information Related to Prediabetes -- 11.4.2 Search for Medical Information, of a Student, Related to Obesity and Overweight -- 11.5 Conclusions and Future Work -- References -- 12 ARLOD: Augmented Reality Mobile Application Integrating Information Obtained from the Linked Open Drug Data -- 12.1 Introduction -- 12.2 Related Works -- 12.2.1 AR in the Medical Field. , 12.2.2 LOD Cloud in the Medical Field -- 12.3 ARLOD Architecture -- 12.3.1 Architecture Description -- 12.3.1.1 Components Description -- 12.3.1.2 Architecture Workflow -- 12.4 Case Study -- 12.4.1 Case Study: Search for the Different Routes of Administration that a Drug Has -- 12.4.2 Case Study: Search for Information About a Drug for Educational Purposes -- 12.5 Conclusions and Future Work -- References.

Note: Intro -- Preface -- Acknowledgements -- Contents -- Contributors -- Part I Methods and Techniques -- 1 A Vertical Fragmentation Method for Multimedia Databases Considering Content-Based Queries -- 1.1 Introduction -- 1.2 Background -- 1.3 State of the Art -- 1.4 Design of CBRVF -- 1.4.1 CBRVF -- 1.4.2 Web Application Design -- 1.5 Results and Discussion -- 1.6 Conclusion and Future Work -- References -- 2 An Approach Based on Process Mining Techniques to Support Software Development -- 2.1 Introduction -- 2.2 Background -- 2.3 Related Work -- 2.4 Framework -- 2.4.1 Phase 1: Event Log Management -- 2.4.2 Phase 2: Process Model Discovery -- 2.4.3 Phase 3: Statistics -- 2.5 Results -- 2.5.1 Case of a Purchase Order Process -- 2.5.2 Case of an Air Quality Monitoring System Process -- 2.6 Conclusions -- References -- 3 Analysis of Canonical Heuristic Methods for the Optimization of an Investment Portfolio -- 3.1 Introduction -- 3.2 Evolutionary Algorithms -- 3.3 Investment Portfolio -- 3.4 Theoretical Scaffolding -- 3.5 Genetic Algorithm -- 3.6 Differential Evolution -- 3.7 Artificial Immunological System -- 3.8 Methodology -- 3.9 Results -- 3.10 Conclusions -- References -- 4 Design of a Dynamic Horizontal Fragmentation Method for Multimedia Databases -- 4.1 Introduction -- 4.2 Background -- 4.3 Related Works -- 4.4 Design of a Dynamic Horizontal Fragmentation Method for Multimedia Databases -- 4.5 Results and Discussion -- 4.6 Conclusion -- References -- 5 Efficient Archiving Method for Handling Preferences in Constrained Multi-objective Evolutionary Optimization -- 5.1 Introduction -- 5.2 Problem Statement -- 5.3 Multi-objective Evolutionary Algorithms -- 5.3.1 Algorithms of Multi-Objective Evolutionary Optimization -- 5.3.2 Preference-Based MOEAs -- 5.3.3 Assessing Performance -- 5.4 Proposal -- 5.4.1 Archiving Regions of Interest. , 5.5 Experimental Step -- 5.5.1 Problems to Be Solved -- 5.5.2 Algorithms for Comparison -- 5.5.3 Parameter Settings -- 5.6 Results and Discussion -- 5.6.1 Results on Unconstrained Problems (DTLZ) -- 5.6.2 Results on Constrained Problems (C-DTLZ) -- 5.6.3 Results on Real-World Multi-Objective Problems -- 5.7 Conclusions and Future Work -- References -- 6 Evaluation of Machine Learning Techniques for Malware Detection -- 6.1 Introduction -- 6.2 Related Work -- 6.3 Background -- 6.3.1 Machine Learning Techniques -- 6.3.2 Measurement -- 6.4 Methodology -- 6.4.1 Data Preprocessing -- 6.4.2 Data Representation -- 6.4.3 Model Training/Testing -- 6.5 Results -- 6.5.1 Data Sets -- 6.5.2 Performance -- 6.6 Conclusions -- References -- 7 Implementation of Reinforcement-Learning Algorithms in Autonomous Robot Navigation -- 7.1 Introduction -- 7.2 Systematic Review of the Literature -- 7.2.1 Heuristic Algorithms -- 7.2.2 Applications of Reinforcement Learning -- 7.2.3 Synthesis and Considerations -- 7.3 Characteristics of Reinforcement Learning Algorithms -- 7.4 Methodology -- 7.4.1 Reinforcement Learning Algorithms -- 7.4.2 System Structure -- 7.4.3 Experiment Description -- 7.5 Results -- 7.6 Conclusions -- References -- 8 Trends on Decision Support Systems: A Bibliometric Review -- 8.1 Introduction -- 8.2 Methodology -- 8.2.1 PRISMA Method -- 8.2.2 Analysis with VOSviewer -- 8.3 Results -- 8.3.1 General Data of the DSS Applied -- 8.3.2 Authors, Organizations, and Countries that Publish the Most -- 8.3.3 Most Used Keywords -- 8.3.4 Most Cited Papers, Journals, Authors, Organizations, and Countries -- 8.3.5 Evolutions and Trends -- 8.4 Conclusions -- References -- 9 Use of Special Cases of Ontologies for Big Data Analysis in Decision Making Systems -- 9.1 Introduction -- 9.2 Ontological Representation of Knowledge. , 9.3 Ontologies in Knowledge Organization Systems -- 9.4 Decision Making Models and External Knowledge -- 9.5 Semantization of Big Data Technology -- 9.6 Use of Big Data Analysis in DMS -- 9.7 Semantic Processing of Metadata for Big Data -- 9.8 Generation of Ontologies for DM -- 9.8.1 Wiki Ontologies -- 9.8.2 Task Thesauri -- 9.9 Practical Use of Proposed Approach -- 9.10 Conclusion -- References -- 10 Multicriteria Decision Making Methods-A Review and Case of Study -- 10.1 Introduction -- 10.2 Bibliometric Analysis of MCDM -- 10.2.1 The Timeline of Multicriteria Decision Models -- 10.2.2 Journals and Authors in MCDM -- 10.2.3 The Most Cited MCDM Documents and Their Keywords -- 10.2.4 The Application Areas of MCDM -- 10.2.5 Institutions and Countries that Publish the Most on MCDM -- 10.2.6 The Funding Sources in MCDM Research -- 10.3 Case Study -- 10.3.1 The Research Problem -- 10.3.2 Methodology -- 10.4 Results from Case Study -- 10.4.1 Obtaining the Subjective Attribute Values -- 10.4.2 The Final Decision Matrix (FDM) -- 10.4.3 Normalizing the Alternatives -- 10.4.4 Obtaining the Weights for Attributes -- 10.4.5 Weighting the Normalized Matrix -- 10.4.6 Distance to Ideal Positive and Ideal Negative -- 10.4.7 Proximity Indexes -- 10.5 Conclusions -- References -- Part II Cases of Study -- 11 Bitcoin Price Forecasting Through Crypto Market Variables: Quantile Regression and Machine Learning Approaches -- 11.1 Introduction and Related Literature -- 11.2 Methodology -- 11.2.1 Quantile Regression Model -- 11.2.2 Machine Learning Approach -- 11.3 Data -- 11.3.1 Determining Data Set for Quantile Regression Model and Machine Learning -- 11.4 Empirical Results and Discussion -- 11.4.1 Quantile Regression Results -- 11.4.2 Machine Learning Results -- 11.5 Conclusions -- References. , 12 Crops Classification in Small Areas Using Unmanned Aerial Vehicles (UAV) and Deep Learning Pre-trained Models from Detectron2 -- 12.1 Introduction -- 12.1.1 Technologies 4.0 for Crop Classification -- 12.1.2 Types of Images Obtained by UAVs -- 12.1.3 Artificial Intelligence Methods Applied in Agriculture -- 12.1.4 Methods for Object Detection with Deep Learning -- 12.1.5 Transfer Learning -- 12.2 Materials and Method -- 12.2.1 Study Area -- 12.2.2 Data Collection -- 12.2.3 Data Labeling -- 12.2.4 Data Description -- 12.2.5 Detectron2 -- 12.2.6 Common Settings for COCO Models -- 12.2.7 ImageNet Pretrained Models -- 12.3 Results and Analysis -- 12.4 Conclusions -- 12.5 Future Work -- References -- 13 Design and Evaluation of Strategies to Mitigate the Impact of Dengue in Healthcare Institutions Through Dynamic Simulation -- 13.1 Introduction -- 13.2 State of the Art -- 13.3 Methodology -- 13.3.1 Conceptualization -- 13.3.2 Formulation -- 13.4 Results and Discussion -- 13.4.1 Test -- 13.4.2 Implementation -- 13.4.3 Sensitivity Analysis -- 13.5 Conclusion and Future Directions -- References -- 14 Detecting Arrhythmia Using the IoT Paradigm -- 14.1 Introduction -- 14.2 Related Work -- 14.3 Wearables for CVD Detection -- 14.4 A Web Application for AF Detection: Architecture and Functionality -- 14.5 Case Study: People Monitoring for Arrhythmia Detection -- 14.5.1 Application Features -- 14.5.2 Parameters and Rules for Arrhythmia Detection -- 14.5.3 Patient Monitoring -- 14.6 Conclusion and Future Directions -- References -- 15 Emotion Detection in Learning Environments Using Facial Expressions: A Brief Review -- 15.1 Introduction -- 15.2 State of the Art -- 15.3 API Analysis of Emotion Detection from Facial Expressions -- 15.4 Case Study: Emotions Recognition in a Learning Environment -- 15.5 Conclusion and Future Directions -- References. , 16 Face Recognition-Eigenfaces -- 16.1 Introduction -- 16.2 Background and Related Works -- 16.2.1 Eigenfaces -- 16.2.2 Linear Discriminant Analysis (LDA) -- 16.3 Datasets -- 16.4 Architecture, Models and Data Preparation -- 16.5 Results -- 16.5.1 Metrics Comparison and Outliers Detection -- 16.5.2 Eigenfaces -- 16.5.3 Face Space -- 16.5.4 Projection of an Image on the Face Space -- 16.5.5 Face Recognition -- 16.6 Conclusions -- References -- 17 Genetic Algorithm for the Optimization of the Unequal-Area Facility Layout Problem -- 17.1 Introduction -- 17.2 The Unequal-Area Facility Layout Problem -- 17.3 Genetic Algorithm for the Optimization of the UAFLP -- 17.3.1 Solution Encoding and Representation -- 17.3.2 Fitness Function -- 17.3.3 Selection Operator -- 17.3.4 Crossover and Mutation Operators -- 17.3.5 Validation of the GA for Optimizing the UAFLP -- 17.4 Results of the GA Optimization for the Case of the Garment Industry -- 17.5 Conclusions -- References -- 18 Microsimulation Calibration Integrating Synthetic Population Generation and Complex Interaction Clusters to Evaluate COVID-19 Spread -- 18.1 Introduction -- 18.2 Agent-Based Microsimulation and Its Application to Disease Spread -- 18.3 Synthetic Population Generation -- 18.4 Synthetic Population Generation Integrated with Complex Interaction Clusters -- 18.5 Application of the Proposed Synthetic Population Generation -- 18.6 Microsimulation of COVID-19 Spread -- 18.7 Conclusions -- References -- 19 A Decision Support System for Container Handling Operations at a Seaport Terminal with Disturbances: Design and Concepts -- 19.1 Introduction -- 19.2 Related Work -- 19.2.1 Yard Operations -- 19.2.2 DSS for Container Terminals -- 19.2.3 Disturbances in Container Terminals -- 19.3 Disturbances Characterization: Case Study of Chilean Ports -- 19.4 DSS Proposal and Concepts. , 19.5 Conclusion and Future Directions.

Note: Intro -- Preface -- Acknowledgements -- Contents -- Contributors -- List of Figures -- List of Tables -- Semantic Web Applications -- 1 im4Things: An Ontology-Based Natural Language Interface for Controlling Devices in the Internet of Things -- Abstract -- 1.1 Introduction -- 1.2 Related Works -- 1.3 im4Things System -- 1.3.1 im4Things App -- 1.3.1.1 Bot Configuration -- 1.3.1.2 Instant Messaging -- 1.3.2 im4Things Cloud Service -- 1.3.2.1 im4Things API -- 1.3.2.2 Communication Management -- 1.3.2.3 Security -- 1.3.2.4 Understanding Module -- 1.3.3 im4Things Bot -- 1.3.3.1 Conversational Agent -- 1.4 Evaluation and Results -- 1.4.1 Subjects -- 1.4.2 Procedure -- 1.4.3 Results -- 1.4.4 Discussion -- 1.5 Conclusions and Future Research -- Acknowledgements -- References -- 2 Knowledge-Based Leisure Time Recommendations in Social Networks -- Abstract -- 2.1 Introduction -- 2.2 Related Work -- 2.3 Social Networking, Semantics and QoS Foundations -- 2.3.1 Influence in Social Networks -- 2.3.2 Leisure Time Places Semantic Information and Similarity -- 2.3.3 Physical Distance-Based and Thematic-Based Location Similarity -- 2.3.4 Leisure Time Places QoS Information -- 2.3.5 User's Profile for Enabling Recommendations -- 2.4 The Leisure Time Recommendation Algorithm -- 2.5 Experimental Evaluation -- 2.5.1 Determining the Number of Influencers -- 2.5.2 Estimating the Taxonomy Level of Places Categories of Interest per User -- 2.5.3 Interest Probability Threshold -- 2.5.4 Recommendation Formulation Time -- 2.5.5 User Satisfaction -- 2.6 Conclusions and Future Work -- References -- 3 An Ontology Based System for Knowledge Profile Management -- Abstract -- 3.1 Introduction -- 3.2 Theoretical Background -- 3.3 State of the Art -- 3.3.1 Ontologies for Knowledge Management -- 3.3.2 Ontologies for Users' Profile Management. , 3.4 An Ontology for Knowledge Profile Management -- 3.4.1 Development of the Ontology -- 3.4.1.1 Specification -- 3.4.1.2 Conceptualization -- 3.5 Results -- 3.5.1 The Case Study -- 3.5.2 Ontology Implementation -- 3.5.2.1 Determination of Base Components -- 3.5.2.2 Detailed Definition of Base Components -- 3.5.2.3 Normalization -- 3.6 Discussion and Conclusion -- Acknowledgements -- References -- 4 Sentiment Analysis Based on Psychological and Linguistic Features for Spanish Language -- Abstract -- 4.1 Introduction -- 4.2 Related Work -- 4.3 Corpus -- 4.4 LIWC and Stylometric Variables -- 4.5 Machine Learning Approach -- 4.6 Experiment -- 4.6.1 Combination of LIWC Dimensions and Stylometric Dimension -- 4.6.2 Text Analysis with LIWC and WordSmith -- 4.6.3 Training a Machine Learning Algorithm and Validation Test -- 4.7 Evaluation and Results -- 4.7.1 Results for the Tourism Corpus -- 4.8 Discussion of Results -- 4.8.1 Comparison -- 4.9 Conclusion and Future Work -- Acknowledgements -- References -- Knowledge Acquisition and Representation -- 5 Knowledge-Based System in an Affective and Intelligent Tutoring System -- Abstract -- 5.1 Introduction -- 5.2 Related Work -- 5.3 Fermat Architecture and ITS Knowledge Representation -- 5.3.1 The System Archetypes -- 5.3.2 Fermat's Architectural Style -- 5.3.3 Intelligent Tutoring System into Fermat Social Network -- 5.3.4 Knowledge Representation in the Intelligent Tutoring System -- 5.4 Recognizing Emotional States -- 5.4.1 Artificial Neural Network for Recognizing Emotional States -- 5.4.1.1 Training and Testing the Network with Emotional States -- 5.5 The Decision Network -- 5.5.1 Integrating Affect into the ITS -- 5.6 Evaluation and Results -- 5.6.1 Fermat Real-Time Evaluation -- 5.7 Conclusions and Future Directions -- Acknowledgments -- References. , 6 A Software Strategy for Knowledge Transfer in a Pharmaceutical Distribution Company -- Abstract -- 6.1 Introduction -- 6.2 Theoretical Background -- 6.2.1 Knowledge and Knowledge Management -- 6.2.2 Knowledge Transfer -- 6.3 Software Strategy -- 6.3.1 Identification -- 6.3.1.1 Knowledge Identification -- 6.3.1.2 Knowledge Assessment -- 6.3.2 Capture/Storage -- 6.3.2.1 Capture of Missing Knowledge -- 6.3.2.2 Knowledge Repository -- 6.3.3 Transfer/Visualization -- 6.3.3.1 Enablers -- 6.3.3.2 Enabling Tools -- 6.3.4 Application -- 6.3.4.1 Usage Assessment -- 6.4 Software Strategy Implementation -- 6.4.1 Identification -- 6.4.1.1 Knowledge Identification -- 6.4.1.2 Knowledge Assessment -- 6.4.2 Capture/Storage -- 6.4.2.1 Knowledge Repository -- 6.4.3 Transfer/Visualization -- 6.4.3.1 Enabling Processes and Tools -- 6.4.4 Application -- 6.4.4.1 Usage Assessment -- 6.5 Conclusions -- References -- 7 GEODIM: A Semantic Model-Based System for 3D Recognition of Industrial Scenes -- Abstract -- 7.1 Introduction -- 7.2 State of the Art -- 7.2.1 Object Recognition -- 7.2.2 Semantic on Object Recognition -- 7.3 GEODIM Overview -- 7.3.1 Process of Geometric Primitives Recognition -- 7.3.2 Semantic Enrichment Process -- 7.3.3 Semantic Model -- 7.4 A Real Use Case: Objects Recognition in an Industrial Facility -- 7.4.1 Recognition Process of Geometric Primitives -- 7.4.2 Semantic Enrichment Process -- 7.5 Evaluation -- 7.6 Conclusions and Future Work -- Acknowledgements -- References -- 8 Beyond Interoperability in the Systems -- Abstract -- 8.1 Introduction -- 8.2 The Challenge of Interoperability in the Industry 4.0 -- 8.3 Related Work -- 8.4 The Advanced Industrial Technical Interoperability Concept (TIC) -- 8.4.1 Introduction -- 8.4.2 Description of the TIC Layer -- 8.4.3 Basic Interoperability Functions. , 8.4.4 Application of the TIC Layer to Manage Complex Design Reuse Scenarios -- 8.5 Discussion of the TIC Layer in Industry 4.0 Toolchains -- 8.6 Conclusions and Future Work -- Acknowledgements -- References -- Knowledge-Based Decision Support Systems (Tools for Industrial Knowledge Management) -- 9 Knowledge-Based Decision Support Systems for Personalized u-lifecare Big Data Services -- Abstract -- 9.1 Introduction -- 9.2 Related Work -- 9.3 Proposed Platform -- 9.3.1 Data Acquisition and Management -- 9.3.2 Data Wrangling -- 9.3.2.1 Data Cleansing -- 9.3.2.2 Data Transformation -- 9.3.2.3 Data Loading -- 9.3.3 Big Data Storage and Processing -- 9.3.4 Learning Models -- 9.3.5 Model Interface -- 9.3.6 Knowledge Bases -- 9.3.7 Reasoner and Inferencing Services -- 9.3.8 Analytical Services -- 9.3.9 u-Lifecare Services API -- 9.4 Case Study -- 9.5 Conclusion -- References -- 10 Decision Support System for Operational Risk Management in Supply Chain with 3PL Providers -- Abstract -- 10.1 Introduction -- 10.2 State of the Art -- 10.2.1 Supply Chain Risk Management-SCRM -- 10.2.2 Operational Risk -- 10.2.3 Outsourcing as a Logistics Strategy -- 10.2.4 Risk in 3PL Operations -- 10.3 Proposed Model -- 10.3.1 Risk Identification -- 10.3.2 Risk Prioritization -- 10.3.3 Risk Quantification -- 10.3.4 Risk Management -- 10.4 Case Study -- 10.4.1 Risk Identification -- 10.4.2 Risk Prioritization -- 10.4.3 Risk Quantification -- 10.4.4 Risk Management -- 10.5 Concluding Remarks -- References -- 11 Assessment of Ergonomic Compatibility on the Selection of Advanced Manufacturing Technology -- Abstract -- 11.1 Introduction -- 11.2 Literature Review -- 11.2.1 Models for Assessment and Selection of AMT -- 11.2.2 Applications of Fuzzy Logic in Manufacturing -- 11.2.3 Fuzzy Inference -- 11.2.4 Axiomatic Design for the Assessment and Selection of AMT -- 11.3 Methodology. , 11.3.1 Methods -- 11.3.2 Mathematical Model -- 11.3.3 Results Using a Numerical Example -- 11.3.4 Conclusions and Future Research -- Acknowledgements -- References -- 12 Developing Geo-recommender Systems for Industry -- Abstract -- 12.1 Introduction -- 12.2 State of the Art -- 12.2.1 Recommender Systems in Different Domains -- 12.2.2 Geographic Information Systems Applied to Environmental and Urban Studies -- 12.3 How to Develop a Geographic Recommender System? -- 12.3.1 Development Tools for Recommender Systems -- 12.4 Usage Scenarios of Geographic Recommender Systems -- 12.4.1 Geo-recommendations for Selecting Points of Sale (Pos) -- 12.4.2 Geo-recommendations for Product Deliveries -- 12.4.3 Touristic Geo-recommendations -- 12.4.4 Geo-recommendation for Public Transportation -- 12.4.5 Geo-recommendations for Sale Offers Within a Specific Radius -- 12.4.6 GEOREMSYS: A Geo-recommender System for Selecting POS -- 12.5 Conclusions -- Acknowledgements -- References -- 13 Evaluation of Denoising Methods in the Spatial Domain for Medical Ultrasound Imaging Applications -- Abstract -- 13.1 Introduction -- 13.2 Review of Speckle Noise Reduction Methods for Ultrasound Medical Images -- 13.2.1 Transform Domain Methods -- 13.2.2 Spatial Domain Methods -- 13.3 Multiplicative Noise Model -- 13.4 Speckle Denoising Filters Compared in This Chapter -- 13.4.1 Average Filter -- 13.4.2 Median Filter -- 13.4.3 Frost Filter -- 13.4.4 Kuan et al. Filter -- 13.4.5 Lee Filter -- 13.4.6 Gamma MAP Filter -- 13.4.7 Anisotropic Diffusion -- 13.4.7.1 Speckle Reducing Anisotropic Diffusion (SRAD) -- 13.5 Metrics -- 13.6 Results -- 13.7 Conclusions -- Acknowledgements -- References -- Appendix A: Attributes for AMT Ergonomic Evaluation -- Appendix B: Rates Given by Experts to Milling Machines Alternatives -- References.