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• Intro; Preface; Contents; List of Figures; List of Tables; 1 On Using Fuzzy Logic to Control a Simulated Hexacopter Carrying an Attached Pendulum; 1.1 Introduction; 1.2 Description of the Controlled Plant: The Hexacopter; 1.3 Proposed Multi-layer Controller; 1.3.1 Pre-processing Phase; 1.3.2 Post-processing Phase; 1.4 The Fuzzy Controllers; 1.4.1 The Fuzzy Method; 1.4.2 Roll Stabilization; 1.4.3 Pitch Stabilization; 1.4.4 Heading to Goal (Yaw Controller); 1.4.5 The Horizontal Navigation; 1.4.6 The Vertical Navigation; 1.5 Experiment and Results; 1.5.1 Overview of the Experiment; 1.5.2 Results

• 1.5.3 Discussion1.6 Conclusions and Future Work; References; 2 Monocular Pose Estimation for an Unmanned Aerial Vehicle Using Spectral Features; 2.1 Introduction; 2.2 Homography-Based Pose Estimation; 2.2.1 Review of Plane-Induced Homography; 2.2.2 Homography Decomposition; 2.3 Spectral Features Correspondence; 2.3.1 Corresponding Points; 2.4 Implementation and Results; 2.4.1 Spectral Features Evaluation; 2.4.2 Pose Estimation in Simulated Quadcopter; 2.5 Conclusions; References; 3 Simultaneous Navigation and Mapping in an Autonomous Vehicle Based on Fuzzy Logic; 3.1 Introduction

• 3.2 Virtual Robot Experimentation Platform3.3 Autonomous Vehicle; 3.4 Navigation and Mapping; 3.4.1 Trajectory Planning; 3.4.2 Navigation; 3.4.3 Decision Tree; 3.5 Simulation; 3.6 Case Study; 3.7 Conclusions; References; 4 Fully Scalable Parallel Hardware for Wheeled Robot Navigation Using Fuzzy Control; 4.1 Introduction; 4.2 Fuzzy Controlllers; 4.3 Fuzzy Models for Wheeled Robot Navigation; 4.4 The Proposed Macro-architecture; 4.5 Micro-architecture of the Functional Units; 4.5.1 Membership Function Unit; 4.5.2 Membership Function Memory; 4.5.3 Fuzzification Unit; 4.5.4 Inference Unit

• 4.5.5 Defuzzification Unit4.6 Performance Results; 4.7 Conclusion; References; 5 Nonlinear Correction for an Energy Estimator Operating at Severe Pile-Up Conditions; 5.1 Introduction; 5.2 High-Energy Signal Pile-Up; 5.3 Online Linear Estimation; 5.3.1 Minimum Variance Linear Unbiased Estimator; 5.3.2 Maximum Likelihood Estimation; 5.4 Nonlinear Correction; 5.5 Performance Comparisons; 5.5.1 Data Set; 5.5.2 Nonlinear Corrector Design; 5.5.3 Efficiency Tests; 5.5.4 Bias and Linearity; 5.5.5 Performance at Different Occupancy Levels; 5.5.6 Exploring the ANN Generalization; 5.6 Conclusions

• 8 Human
• Machine Musical Composition in Real-Time Based on Emotions Through a Fuzzy Logic Approach

This book discusses a number of real-world applications of computational intelligence approaches. Using various examples, it demonstrates that computational intelligence has become a consolidated methodology for automatically creating new competitive solutions to complex real-world problems. It also presents a concise and efficient synthesis of different systems using computationally intelligent techniques.

• Advanced Classification of Remote Sensing High Resolution Imagery.- An Application for the Management of Natural Resources.- Analyzing the Impact of Strategic Performance Management Systems and Role Ambiguity on Performance: A Qualitative Approach.- Advanced Radial Approach to Resource Location Problems.- Verbal Decision Analysis Applied to the Prioritization of Influencing Factors in Distributed Software Development.- Agile Documentation Tool Concept.- Pervasive Business Intelligence: A Key Success Factor for Business.- Annotated Documents and Expanded CIDOC-CRM Ontology in the Automatic Construction of a Virtual Museum.
• (source: Nielsen Book Data)

This book primarily addresses Intelligent Information Systems (IIS) and the integration of artificial intelligence, intelligent systems and technologies, database technologies and information systems methodologies to create the next generation of information systems. It includes original and state-of-the-art research on theoretical and practical advances in IIS, system architectures, tools and techniques, as well as "success stories" in intelligent information systems. Intended as an interdisciplinary forum in which scientists and professionals could share their research results and report on new developments and advances in intelligent information systems, technologies and related areas - as well as their applications - , it offers a valuable resource for researchers and practitioners alike.
(source: Nielsen Book Data)

• From a Small Liberal Arts College to the World: Our Blended Courses, SPOC, and MOOCs in Italian Studies.- Giving Exible Learners a Head Start on Higher Education: Designing and Implementing a Pre-induction Socialization MOOC.- The E.M.M.A. Experience: Emerging Patterns and Factors for Success.- Mentoring Learners in MOOCs: a New Way to Improve Completion Rates.- Towards e-Presence at Distance as a Way to Reach and Share e-Quality: the Case of the ECO sMOOCs.- Additional Functionalities to Convert an xMOOC into an xLMOOC.- A Principled Approach to the Design of Collaborative MOOC Curricula.- Towards Full Engagement for Open Online Education. A Practical Experience for a MicroMaster.- From Low-Scale to Collaborative, Gamified and Massive-Scale Courses: Redesigning a MOOC.- Innovation in EU Communication: MOOCs from the European Committee of the Regions.- Does Gamification in MOOC Discussion Forums Work.- A MOOC-based Flipped Class: Lessons Learned from the Orchestration Perspective.- An International Collaboration in the Design Experience of a MOOC Series.- Measuring the Degree of Innovation in Education through the Implementation of an Indicator Based on Analyzing MOOC-related Activities.- Towards a Typology of MOOC Activity Patterns: Learners Who never Rest.- Improving MOOC Student Learning through Enhanced Peer-to-Peer Tasks.- Who Wants to Chat on a MOOC? Lessons from a Peer Recommender System.- Weekly Predicting the At-risk MOOC Learners Using Dominance-based Rough Set Approach.- MOOC Friends and Followers: An Analysis of Twitter Hashtag Networks.- Understanding Learning and Teaching in MOOCs from the Perspectives of Students and Instructors: a Review of Literature from 2014 to 2016.- Effect of Free Certificate Discontinuation in Completion Rates of MOOC.- Challenges of Identifying Second Language English Speakers in MOOCs.- MOOC Quality Evaluation System: Tomsk State University Experience.- The Drivers of Employer Support for Professional Skill Development in MOOCs.- To Change or not to Change? That's the Question on MOOC-Success, Barriers and Their Implications.- Follow-up of Learning Activities in Open edX: a Case Study at the University of Cauca.- Increasing Educational Value: the Transformation of MOOCs into Open Educational Resources.- Implementation Intention and How it Affects Goal Achievement in MOOCs.- A Social Learning Grid for MOOCs: Exploring a FutureLearn Case.- The Double Classroom: Design Patterns Using MOOCs in Teacher Education.- Early Prediction and Variable Importance of Certificate Accomplishment.- Types of Dropout in Adaptive Open Online Courses.- Exploring the Role of Assessment in Developing Learners' Critical Thinking in Massive Open Online Courses. .
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 5th European Conference, EMOOCs 2017, held in Leganes, Madrid, Spain, in May 2017. The 23 full and 10 short papers presented in this volume were carefully reviewed and selected from 53 submissions. Massive Open Online Courses (MOOCs) have marked a milestone in the use of technology for education. The reach, potential, and possibilities of EMOOCs are immense. But they are not only restricted to global outreach: the same technology can be used to improve teaching on campus and training inside companies and institutions. .
(source: Nielsen Book Data)

• Automatic Classification and Recommendation.- Cultural Heritage and Indigenous Knowledge.- Data Sharing and Retrieval.- Lexical and Discourse Analysis.- Mobile Applications.- Search Results Presentation and Visualization.- Social Media.- User Behaviors.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 19th International Conference on Asia-Pacific Digital Libraries, ICADL 2017, held in Bangkok, Thailand, in November 2017. The 21 full papers and 6 short papers presented in this book were carefully reviewed and selected from 51 submissions. The paper topics of ICADL 2017 covered a wide spectrum from various areas, including information visualization, data mining/extraction, cultural heritage preservation, personalized service and user modeling, novel library content and use environments, electronic publishing, preservation systems and algorithms, social networking and information systems, Internet of things, cloud computing and applications, mobile services, interoperability issues, open source tools and systems, security and privacy, multi-language support, metadata and cataloguing, search, retrieval and browsing interfaces to all forms of digital content, e-Science/e-Research data and knowledge management, and cooperative service and community service.
(source: Nielsen Book Data)

• Chapter 1: Requirements for Digital Preservation.-
• Chapter 2: Metadata in Long-term Digital Preservation.-
• Chapter 3: The CREDO Project.-
• Chapter 4: CREDO Repository Architecture.-
• Chapter 5: Information Processing in CREDO Long-term Archive.-
• Chapter 6: Metadata in CREDO Long-term Archive.-
• Chapter 7: Persistence Management in Long-term Digital Archive.-
• Chapter 8: Power Efficiency and Scheduling Access to the Archive.-
• Chapter 9: Information Management in Federated Digital Archives.
• (source: Nielsen Book Data)

This book addresses the process of maintaining digital objects through time to ensure continued access, an aspect that has become a crucial issue in recent years. It offers a concise yet comprehensive discussion of key concepts and requirements for long-term digital preservation, and presents a pioneering framework for digital repositories that enables the long-term archiving and metadata management for large volumes of digital resources based on a system that has already been completely designed and launched. In the framework, the reliability of information readouts is ensured by the repository with two-level data recording replication and monitoring mechanisms in the repository management system (RMS) and the file systems, and by the RMS's distributed nature. The advanced RMS allows operations on the archival storage to be scheduled, while also taking into account low energy consumption requirements. After presenting the framework in detail, the book assesses and demonstrates the approach's viability in terms of delivering accessibility, authenticity and usability. As such, the book offers a valuable resource for information technology (IT) researchers and practitioners, as well as archivists and librarians.
(source: Nielsen Book Data)

• Machine learning: online learning, regression, label classification, deep learning, feature selection, recommendation system.- Knowledge discovery: recommendation system, community detection, pattern mining, misc.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 20th International Conference on Discovery Science, DS 2017, held in Kyoto, Japan, in October 2017, co-located with the International Conference on Algorithmic Learning Theory, ALT 2017. The 18 revised full papers presented together with 6 short papers and 2 invited talks in this volume were carefully reviewed and selected from 42 submissions. The scope of the conference includes the development and analysis of methods for discovering scientific knowledge, coming from machine learning, data mining, intelligent data analysis, big data analysis as well as their application in various scientific domains. The papers are organized in topical sections on machine learning: online learning, regression, label classification, deep learning, feature selection, recommendation system; and knowledge discovery: recommendation system, community detection, pattern mining, misc.
(source: Nielsen Book Data)

• Algorithms and models for computation with biomolecular systems.- Computational processes in vitro and in vivo.- Molecular motors and molecular robotics.- Studies of fault-tolerance and error correction.- Software tools for analysis, simulation, and design.- Synthetic biology and in vitro evolution.- Applications in engineering, physics, chemistry, biology, and medicine.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 23th International Conference on DNA Computing and Molecular Programming, DNA 23, held Austin, TX, USA, in September 2017. The 16 full papers presented were carefully selected from 23 submissions. Research in DNA computing aims to draw together mathematics, computerscience, physics, chemistry, biology, and nanotechnology to address the analysis, design, and synthesis of information-based molecular systems. The papers address all areas related to biomolecular computing such as: algorithms and models for computation with biomolecular systems; computational processes in vitro and in vivo; molecular motors and molecular robotics; studies of fault-tolerance and error correction; software tools for analysis, simulation, and design; synthetic biology and in vitro evolution; applications in engineering, physics, chemistry, biology, and medicine. .
(source: Nielsen Book Data)

• Emerging technologies for open access to education and learning.-Emerging technologies supported personalized and adaptive learning.-Emerging technologies support for intelligent tutoring.- Emerging technologies support for game-based and joyful learning.- Emerging technologies of pedagogical issues.- Emerging technologies for affective learning and emerging technologies for tangible learning.
• (source: Nielsen Book Data)

This book constitutes the thoroughly refereed post-workshop proceedings of the First International Symposium, SETE 2016, held in conjunction with ICWL 2016, Rome, Italy, in October 2016. The 81 revised papers, 59 full and 22 short ones, were carefully reviewed and selected from 139 submission. They cover latest findings in various areas, such as emerging technologies for open access to education and learning; emerging technologies supported personalized and adaptive learning; emerging technologies support for intelligent tutoring; emerging technologies support for game-based and joyful learning; emerging technologies of pedagogical issues; emerging technologies for affective learning and emerging technologies for tangible learning.
(source: Nielsen Book Data)

• Design and Usability.- Biomedical and Health Informatics.- Activity and Recognition.- Independent Living Technology.- Smart Home Technology.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 15th International Conference on Smart Homes and Health Telematics, ICOST 2017, held in Paris, France, in August 2017. The 18 regular papers, 5 short papers together with 2 invited talks included in this volume were carefully reviewed and selected from numerous submissions. The conference features a dynamic program incorporating a range of design, development, deployment and evaluation of Smart Urban Environments, Assistive Technologies, Chronic Disease Management, Coaching and Health Telematics systems.
(source: Nielsen Book Data)

• A Computational Study of Neighborhood Operators for Job-shop Scheduling Problems with Regular Objectives.- A Genetic Algorithm for Multi-Component Optimization Problems: the Case of the Travelling Thief Problem.- A Hybrid Feature Selection Algorithm Based on Large Neighborhood Search.- A Memetic Algorithm to Maximise the Employee Substitutability in Personnel Shift Scheduling.- Construct, Merge, Solve and Adapt versus Large Neighborhood Search for Solving the Multi-Dimensional Knapsack Problem: Which One Works Better When.- Decomposing SAT Instances with Pseudo Backbones.- Efficient Consideration of Soft Time Windows in a Large Neighborhood Search for the Districting and Routing Problem for Security Control.- Estimation of Distribution Algorithms for the Firefighter Problem.- LCS-Based Selective Route Exchange Crossover for the Pickup and Delivery Problem with Time Windows.- Multi-rendezvous Spacecraft Trajectory Optimization with Beam P-ACO.- Optimizing Charging Station Locations for Electric Car-Sharing Systems.- Selection of Auxiliary Objectives Using Landscape Features and Offline Learned Classifier.- Sparse, Continuous Policy Representations for Uniform Online Bin Packing via Regression of Interpolants.- The Weighted Independent Domination Problem: ILP Model and Algorithmic .
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 17th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2017, held in Amsterdam, The Netherlands, in April 2017, co-located with the Evo*2017 events EuroGP, EvoMUSART and EvoApplications. The 16 revised full papers presented were carefully reviewed and selected from 39 submissions. The papers cover both empirical and theoretical studies on a wide range of academic and real-world applications. The methods include evolutionary and memetic algorithms, large neighborhood search, estimation of distribution algorithms, beam search, ant colony optimization, hyper-heuristics and matheuristics. Applications include both traditional domains, such as knapsack problem, vehicle routing, scheduling problems and SAT; and newer domains such as the traveling thief problem, location planning for car-sharing systems and spacecraft trajectory optimization. Papers also study important concepts such as pseudo-backbones, phase transitions in local optima networks, and the analysis of operators. This wide range of topics makes the EvoCOP proceedings an important source for current research trends in combinatorial optimization.
(source: Nielsen Book Data)

• A Survey of Diversity Oriented Optimization: Problems, Indicators, and Algorithms.- Global Multi-Objective Optimization by Means of Cell Mapping Techniques.- Percentile via Polynomial Chaos Expansion: Bridging Robust Optimization with Reliability.- Evolutionary Equilibrium Detection in Multicriteria Games.- A New Estimation of Distribution Algorithm for Nash Equilibria Detection.- Multi-Objective Optimisation by Self-Adaptive Evolutionary Algorithm.- Evidence Based Multidisciplinary Robust Optimization for Mars Micro Entry Probe Design.- A Simulation-Based Algorithm for the Probabilistic Traveling Salesman Problem.- Average Cuboid Volume as a Convergence Indicator and Selection Criterion for Multi-Objective Biochemical Optimization.
• (source: Nielsen Book Data)

This book comprises nine selected works on numerical and computational methods for solving multiobjective optimization, game theory, and machine learning problems. It provides extended versions of selected papers from various fields of science such as computer science, mathematics and engineering that were presented at EVOLVE 2013 held in July 2013 at Leiden University in the Netherlands. The internationally peer-reviewed papers include original work on important topics in both theory and applications, such as the role of diversity in optimization, statistical approaches to combinatorial optimization, computational game theory, and cell mapping techniques for numerical landscape exploration. Applications focus on aspects including robustness, handling multiple objectives, and complex search spaces in engineering design and computational biology.
(source: Nielsen Book Data)

• Intro
• Preface
• Organization
• CLEF Steering Committee
• Contents
• Full Papers
• A Pinch of Humor for Short-Text Conversation: An Information Retrieval Approach
• 1 Introduction
• 2 Related Work
• 3 Data
• 3.1 Joke Collection
• 3.2 Yahoo!Answers
• 4 Retrieval Models
• 4.1 BM25
• 4.2 Query Term Reweighting Model (QTR)
• 4.3 doc2vec
• 5 Evaluation
• 5.1 Yahoo!Answers
• 5.2 Lab Evaluation
• 6 Conclusion and Future Work
• References
• A Component-Level Analysis of an Academic Search Test Collection.
• 1 Introduction
• 2 Component-Level Evaluation in Academic Search

• 3 Study Configurations
• 3.1 Test Collection and Test IR System
• 3.2 Component-Level Configurations
• 3.3 Analysis Steps
• 4 Analyzing Component Performance
• 4.1 Document and Topic Structure
• 4.2 IR System Components
• 5 Conclusion
• References
• A Component-Level Analysis of an Academic Search Test Collection.
• 1 Introduction
• 2 Query Performance Prediction
• 3 Study Configurations
• 3.1 Test Collection and Test IR System
• 3.2 Analysis Steps
• 4 Analyzing Query Performance
• 4.1 Recall Base
• 4.2 Topic Specificity
• 4.3 Semantic Heterogeneity of Topic Terms

• 5 Conclusion
• References
• Improving the Reliability of Query Expansion for User-Generated Speech Retrieval Using Query Performance Prediction
• 1 Introduction
• 2 Previous Work on QE for Spoken Content
• 3 UGS Test Collection
• 3.1 UGS Document Set
• 3.2 Query and Relevance Sets
• 4 Initial Investigation of QE for UGS Retrieval
• 4.1 Retrieval Model
• 4.2 Query Expansion
• 4.3 Passage-Based QE
• 4.4 Experimental Results
• 5 Query Performance Prediction for QE
• 5.1 Query Performance Prediction Methods
• 5.2 Evaluation
• 6 Adaptive Passage-Based QE for UGS Retrieval

• 7 Conclusions and Further Studies
• References
• Optimized Convolutional Neural Network Ensembles for Medical Subfigure Classification
• 1 Introduction
• 2 Revisiting Participation at ImageCLEF 2016
• 3 Dataset Analysis
• 3.1 Data Generation Process
• 3.2 Problems of the Dataset
• 3.3 Suggestions for Future Datasets
• 4 Methodology
• 5 Evaluation
• 5.1 Results Without Additional Images from ImageCLEF 2013
• 5.2 Self-training Using a PubMedCentral Database Snapshot
• 6 Conclusion
• References
• IRIT-QFR: IRIT Query Feature Resource
• 1 Introduction
• 2 Query Features

• 2.1 Document Collection Independent Pre-retrieval Features: WordNet-Based and Other Linguistic Features
• 2.2 Document Collection Dependent Pre-retrieval Features
• 2.3 Post-retrieval Features
• 2.4 Collections for Which the Features Have Been Estimated
• 3 Analysis of the Resource
• 3.1 Descriptive Analysis
• 4 Applications
• 5 Conclusion
• References
• Evaluating and Improving the Extraction of Mathematical Identifier Definitions
• 1 Introduction
• 2 Related Work
• 2.1 Statistical Feature Analysis (ST)
• 2.2 Pattern Matching (PM)
• 2.3 Machine Learning
• 3 Methodology

This book constitutes the refereed proceedings of the 8th International Conference of the CLEF Initiative, CLEF 2017, held in Dublin, Ireland, in September 2017. The 7 full papers and 9 short papers presented together with 6 best of the labs papers were carefully reviewed and selected from 38 submissions. In addition, this volume contains the results of 10 benchmarking labs reporting their year long activities in overview talks and lab sessions. The papers address all aspects of information access in any modality and language and cover a broad range of topics in the field of multilingual and multimodal information access evaluation.
(source: Nielsen Book Data)

• International Workshop on Fetal and Infant Image Analysis, FIFI 2017:
• Template-Free Estimation of Intracranial Volume: A Preterm Birth Animal Model Study / Juan Eugenio Iglesias, Sebastiano Ferraris, Marc Modat, Willy Gsell, Jan Deprest, Johannes L. van der Merwe et al.
• Assessing Reorganisation of Functional Connectivity in the Infant Brain / Roxane Licandro, Karl-Heinz Nenning, Ernst Schwartz, Kathrin Kollndorfer, Lisa Bartha-Doering, Hesheng Liu et al.
• Fetal Skull Segmentation in 3D Ultrasound via Structured Geodesic Random Forest / Juan J. Cerrolaza, Ozan Oktay, Alberto Gomez, Jacqueline Matthew, Caroline Knight, Bernhard Kainz et al.
• Fast Registration of 3D Fetal Ultrasound Images Using Learned Corresponding Salient Points / Alberto Gomez, Kanwal Bhatia, Sarjana Tharin, James Housden, Nicolas Toussaint, Julia A. Schnabel
• Automatic Segmentation of the Intracranial Volume in Fetal MR Images / N. Khalili, P. Moeskops, N. H. P. Claessens, S. Scherpenzeel, E. Turk, R. de Heus et al.
• Abdomen Segmentation in 3D Fetal Ultrasound Using CNN-powered Deformable Models / Alexander Schmidt-Richberg, Tom Brosch, Nicole Schadewaldt, Tobias Klinder, Angelo Cavallaro, Ibtisam Salim et al.
• Multi-organ Detection in 3D Fetal Ultrasound with Machine Learning / Caroline Raynaud, Cybèle Ciofolo-Veit, Thierry Lefèvre, Roberto Ardon, Angelo Cavallaro, Ibtisam Salim et al.
• Robust Regression of Brain Maturation from 3D Fetal Neurosonography Using CRNs / Ana I. L. Namburete, Weidi Xie, J. Alison Noble
• 4th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2017:
• Segmentation of Retinal Blood Vessels Using Dictionary Learning Techniques / Taibou Birgui Sekou, Moncef Hidane, Julien Olivier, Hubert Cardot
• Detecting Early Choroidal Changes Using Piecewise Rigid Image Registration and Eye-Shape Adherent Regularization / Tiziano Ronchetti, Peter Maloca, Christoph Jud, Christoph Meier, Selim Orgül, Hendrik P. N. Scholl et al.
• Patch-Based Deep Convolutional Neural Network for Corneal Ulcer Area Segmentation / Qichao Sun, Lijie Deng, Jianwei Liu, Haixiang Huang, Jin Yuan, Xiaoying Tang
• Model-Driven 3-D Regularisation for Robust Segmentation of the Refractive Corneal Surfaces in Spiral OCT Scans / Joerg Wagner, Simon Pezold, Philippe C. Cattin
• Automatic Retinal Layer Segmentation Based on Live Wire for Central Serous Retinopathy / Dehui Xiang, Geng Chen, Fei Shi, Weifang Zhu, Xinjian Chen
• Retinal Image Quality Classification Using Fine-Tuned CNN / Jing Sun, Cheng Wan, Jun Cheng, Fengli Yu, Jiang Liu
• Optic Disc Detection via Deep Learning in Fundus Images / Peiyuan Xu, Cheng Wan, Jun Cheng, Di Niu, Jiang Liu
• 3D Choroid Neovascularization Growth Prediction with Combined Hyperelastic Biomechanical Model and Reaction-Diffusion Model / Chang Zuo, Fei Shi, Weifang Zhu, Haoyu Chen, Xinjian Chen
• Retinal Biomarker Discovery for Dementia in an Elderly Diabetic Population / Ahmed E. Fetit, Siyamalan Manivannan, Sarah McGrory, Lucia Ballerini, Alexander Doney, Thomas J. MacGillivray et al.
• Non-rigid Registration of Retinal OCT Images Using Conditional Correlation Ratio / Xueying Du, Lun Gong, Fei Shi, Xinjian Chen, Xiaodong Yang, Jian Zheng
• Joint Optic Disc and Cup Segmentation Using Fully Convolutional and Adversarial Networks / Sharath M. Shankaranarayana, Keerthi Ram, Kaushik Mitra, Mohanasankar Sivaprakasam
• Automated Segmentation of the Choroid in EDI-OCT Images with Retinal Pathology Using Convolution Neural Networks / Min Chen, Jiancong Wang, Ipek Oguz, Brian L. VanderBeek, James C. Gee
• Spatiotemporal Analysis of Structural Changes of the Lamina Cribrosa / Charly Girot, Hiroshi Ishikawa, James Fishbaugh, Gadi Wollstein, Joel Schuman, Guido Gerig
• Fast Blur Detection and Parametric Deconvolution of Retinal Fundus Images / Bryan M. Williams, Baidaa Al-Bander, Harry Pratt, Samuel Lawman, Yitian Zhao, Yalin Zheng et al.
• Towards Topological Correct Segmentation of Macular OCT from Cascaded FCNs / Yufan He, Aaron Carass, Yeyi Yun, Can Zhao, Bruno M. Jedynak, Sharon D. Solomon et al.
• Boosted Exudate Segmentation in Retinal Images Using Residual Nets / Samaneh Abbasi-Sureshjani, Behdad Dashtbozorg, Bart M. ter Haar Romeny, François Fleuret
• Development of Clinically Based Corneal Nerves Tortuosity Indexes / Fabio Scarpa, Alfredo Ruggeri
• A Comparative Study Towards the Establishment of an Automatic Retinal Vessel Width Measurement Technique / Fan Huang, Behdad Dashtbozorg, Alexander Ka Shing Yeung, Jiong Zhang, Tos T. J. M. Berendschot, Bart M. ter Haar Romeny
• Automatic Detection of Folds and Wrinkles Due to Swelling of the Optic Disc / Jason Agne, Jui-Kai Wang, Randy H. Kardon, Mona K. Garvin
• Representation Learning for Retinal Vasculature Embeddings / Luca Giancardo, Kirk Roberts, Zhongming Zhao.

This book constitutes the refereed joint proceedings of the International Workshop on Fetal and Infant Image Analysis, FIFI 2017, and the 6th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 8 full papers presented at FIFI 2017 and the 20 full papers presented at OMIA 2017 were carefully reviewed and selected. The FIFI papers feature research on advanced image analysis approaches focused on the analysis of growth and development in the fetal, infant and paediatric period. The OMIA papers cover various topics in the field of ophthalmic image analysis.
(source: Nielsen Book Data)

• Foundations of Flexible Querying.- Recommendation and Ranking.- Technologies for Flexible Representations and Querying.- Knowledge Discovery and Information/Data Retrieval.- Intuitionistic Sets.- Generalized Net Model.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 12th International Conference on Flexible Query Answering Systems, FQAS 2017, held in London, UK, in June 2017. The 21 full papers presented in this book together with 4 short papers were carefully reviewed and selected from 43 submissions. The papers cover the following topics: foundations of flexible querying; recommendation and ranking; technologies for flexible representations and querying; knowledge discovery and information/data retrieval; intuitionistic sets; and generalized net model.
(source: Nielsen Book Data)

• Intro; Contents; Introduction; 1 Flow Tasks in Networks in Crisp Conditions; 1.1 Basic Concepts of the Flow Theory; 1.2 Selecting of the Arc Capacities; 1.2.1 Factors Leading to the Problem Statements in Fuzzy Conditions; 1.3 Fuzzy Logic as the Main Tool of Dealing with Uncertainty; 1.4 Flow Tasks in Transportation Networks; 1.4.1 Maximum Flow Finding in a Network; 1.4.2 Maximum Flow Finding in a Network with Nonzero Lower Flow Bounds; 1.4.3 Minimum Cost Flow Finding in a Network; 1.4.4 Minimum Cost Flow Finding in a Network with Nonzero Lower Flow Bounds; 1.5 Flow Tasks in Dynamic Networks

• 1.5.1 Maximum Flow Finding in Dynamic Networks with Zero and Nonzero Lower Flow Bounds1.5.2 Minimum Cost Flow Finding in Dynamic Network with Zero and Nonzero Lower Flow Bounds; 1.6 Summary; References; 2 Maximum and Minimum Cost Flow Finding in Networks in Fuzzy Conditions; 2.1 Maximum Flow Finding in a Network with Fuzzy Arc Capacities; 2.2 Method of Fuzzy Calculations with Fuzzy Numbers; 2.3 Maximum Flow Finding in a Network with Fuzzy Nonzero Lower and Upper Flow Bounds; 2.4 Minimum Cost Flow Finding in a Network with Fuzzy Arc Capacities and Transmission Costs

• 2.4.1 Potential Method for the Minimum Cost Flow Finding in a Network with Fuzzy Arc Capacities and Transmission2.5 Minimum Cost Flow Finding in a Network with Fuzzy Nonzero Lower, Upper Flow Bounds and Transmission Costs; 2.6 Summary; References; 3 Flow Tasks Solving in Dynamic Networks with Fuzzy Lower, Upper Flow Bounds and Transmission Costs; 3.1 Definition of the Fuzzy Dynamic Network; 3.2 Maximum Flow Finding in Dynamic Network with Fuzzy Transit Arc Capacities; 3.3 Maximum Flow Finding in Dynamic Network with Fuzzy Transit Nonzero Lower and Upper Flow Bounds

• 3.4 Minimum Cost Flow Finding in Dynamic Network with Fuzzy Transit Arc Capacities and Transmission Costs3.5 Minimum Cost Flow Finding in Dynamic Network with Fuzzy Nonzero Lower, Upper Flow Bounds and Transmission Costs; 3.6 Summary; References; 4 Implementing the Program for Solving the Flow Tasks in Networks in Fuzzy Conditions; 4.1 Functional Purpose of Proposed Program Complex; 4.2 Description of the Logical Structure of the Software Mode; 4.3 Preparing of Input Data Using GIS ObjectLand; 4.4 Summary; References; Conclusion

This book offers a comprehensive introduction to fuzzy methods for solving flow tasks in both transportation and networks. It analyzes the problems of minimum cost and maximum flow finding with fuzzy nonzero lower flow bounds, and describes solutions to minimum cost flow finding in a network with fuzzy arc capacities and transmission costs. After a concise introduction to flow theory and tasks, the book analyzes two important problems. The first is related to determining the maximum volume for cargo transportation in the presence of uncertain network parameters, such as environmental changes, measurement errors and repair work on the roads. These parameters are represented here as fuzzy triangular, trapezoidal numbers and intervals. The second problem concerns static and dynamic flow finding in networks under fuzzy conditions, and an effective method that takes into account the network's transit parameters is presented here. All in all, the book provides readers with a practical reference guide to state-of-the art fuzzy methods for solving flow tasks and offers a valuable resource for all researchers and postgraduate students in the fields of network theory, fuzzy models and decision-making. .

• Invited Contribution.- An Invitation to Knowledge Space Theory.- Historical Paper.- Implications and Dependencies between Attributes.- Regular Contributions.- The implication logic of (n, k)-extremal lattices.- Making use of empty intersections to improve the performance of CbO-type algorithms.- On the Usability of Probably Approximately Correct Implication Bases. -Formal Concept Analysis in a Logical Programming Setting for Visualization Oriented (Power) Graph Compression.- A Proposition for Sequence Mining Using Pattern Structures. -An investigation of user behavior in educational platforms using Temporal Concept Analysis. -Hierarchies of Weighted Closed Partially-Ordered Patterns for Enhancing Sequential Data Analysis.- First Notes on Maximum Entropy Entailment for Quantified Implications. - On overfitting of classifiers making a lattice.- Learning Thresholds in Formal Concept Analysis.- The Linear Algebra in Extended Formal Concept Analysis over Idempotent Semifields.- Distributed and Parallel Computation of the Canonical Direct Basis.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 14th International Conference on Formal Concept Analysis, ICFCA 2017, held in Rennes, France, in June 2017. The 13 full papers presented in this volume were carefully reviewed and selected from 37 submissions. The book also contains an invited contribution and a historical paper translated from German and originally published in "Die Klassifkation und ihr Umfeld", edited by P. O. Degens, H. J. Hermes, and O. Opitz, Indeks-Verlag, Frankfurt, 1986. The field of Formal Concept Analysis (FCA) originated in the 1980s in Darmstadt as a subfield of mathematical order theory, with prior developments in other research groups. Its original motivation was to consider complete lattices as lattices of concepts, drawing motivation from philosophy and mathematics alike. FCA has since then developed into a wide research area with applications much beyond its original motivation, for example in logic, data mining, learning, and psychology.
(source: Nielsen Book Data)

• Session types for Link failures.- Learning-based compositional parameter synthesis for event-recording automata.- Modularising opacity verification for Hybrid Transactional Memory.- Proving opacity via linearizability: a sound and complete method.- On futures for streaming data in ABS.- Session-based concurrency, reactively.- Procedural choreographic programming.- An observational approach to defining linearizability on weak memory models.- Applying a dependency mechanism in the formal development of voting protocol models using event-B.- Weak simulation quasimetric in a gossip scenario.- Reasoning about distributed secrets.- Classical higher-order processes.- Weak nominal modal logic.- Type inference of simulink hierarchical block diagrams in Isabelle.- Creating Buchi automata for multi-valued model checking.- Privacy assessment using static taint analysis.- EPTL - a temporal logic for weakly consistent systems.
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This book constitutes the proceedings of the 37th IFIP WG 6.1 International Conference on Formal Techniques for Distributed Objects, Components, and Systems, FORTE 2017, held in Neuchatel, Switzerland, in June 2017, as part of the 12th International Federated Conference on Distributed Computing Techniques, DisCoTec 2017. The 13 revised full papers presented together with 3 short and 1 tool papers were carefully reviewed and selected from 30 submissions. The papers present a wide range of topics on distributed computing models and formal specification, testing, and verification methods.
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• Machine learning.- data mining methods.- deep learning, bioinformatics and health informatics.- intelligent information systems.- knowledge-based system.- mining temporal, spatial and spatio-temporal data.- text and Web mining.- big data analytics and stream data mining.- granular and soft clustering for data science.- knowledge discovery with formal concept analysis and related formalisms.- data mining competition on trading based on recommendations.
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This book constitutes the proceedings of the 23rd International Symposium on Foundations of Intelligent Systems, ISMIS 2017, held in Warsaw, Poland, in June 2017. The 56 regular and 15 short papers presented in this volume were carefully reviewed and selected from 118 submissions. The papers include both theoretical and practical aspects of machine learning, data mining methods, deep learning, bioinformatics and health informatics, intelligent information systems, knowledge-based systems, mining temporal, spatial and spatio-temporal data, text and Web mining. In addition, four special sessions were organized; namely, Special Session on Big Data Analytics and Stream Data Mining, Special Session on Granular and Soft Clustering for Data Science, Special Session on Knowledge Discovery with Formal Concept Analysis and Related Formalisms, and Special Session devoted to ISMIS 2017 Data Mining Competition on Trading Based on Recommendations, which was launched as a part of the conference.
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• Chapter 1 Comparative Study on Fractional Order PID and PID Controllers on Noise Suppression for Manipulator Trajectory Control.-
• Chapter 2 Control of the Temperature of a Finite Diffusive Interface Medium using the CRONE Controller.-
• Chapter 3 Grey Predictor Assisted Fuzzy and Fractional Order Fuzzy Control of a Moving Cart Inverted Pendulum.-
• Chapter 4 H Design with Fractional-Order PI D Type Controllers.-
• Chapter 5 On the Electronic Realizations of Fractional-Order Phase-Lead-Lag Compensators with OpAmps and FPAAs.-
• Chapter 6 Robust Adaptive Supervisory Fractional Order Controller for Optimal Energy Management in Wind Turbine with Battery Storage.-
• Chapter 7 Robust Adaptive Interval Type-2 Fuzzy Synchronization for a Class of Fractional Order Chaotic Systems.-
• Chapter 8 Optimal Fractional Order Proportional-Integral-Differential Controller for Inverted Pendulum with Reduced Order Linear Quadratic Regulator.-
• Chapter 9 Towards a Robust Fractional Order PID Stabilizer for Electric Power Systems.-
• Chapter 10 Application of Fractional Order Controllers on Experimental and Simulation Model of Hydraulic Servo System.
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The book reports on the latest advances in and applications of fractional order control and synchronization of chaotic systems, explaining the concepts involved in a clear, matter-of-fact style. It consists of 30 original contributions written by eminent scientists and active researchers in the field that address theories, methods and applications in a number of research areas related to fractional order control and synchronization of chaotic systems, such as: fractional chaotic systems, hyperchaotic systems, complex systems, fractional order discrete chaotic systems, chaos control, chaos synchronization, jerk circuits, fractional chaotic systems with hidden attractors, neural network, fuzzy logic controllers, behavioral modeling, robust and adaptive control, sliding mode control, different types of synchronization, circuit realization of chaotic systems, etc. In addition to providing readers extensive information on chaos fundamentals, fractional calculus, fractional differential equations, fractional control and stability, the book also discusses key applications of fractional order chaotic systems, as well as multidisciplinary solutions developed via control modeling. As such, it offers the perfect reference guide for graduate students, researchers and practitioners in the areas of fractional order control systems and fractional order chaotic systems.
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• Chapter 1: what a fuzzy set is and what it is not?.-
• Chapter 2: Fuzzy random variables a la Kruse & Meyer and a la Puri & Ralescu: key differences and coincidences.-
• Chapter 3: Statistical Inference for Incomplete Ranking Data: A Comparison of two Likelihood-Based Estimators.-
• Chapter 4: Interval Type-2 Defuzzification Using Uncertainty Weights.-
• Chapter 5: Exploring time-resolved data for patterns and validating single clusters.-
• Chapter 6: Interpreting Cluster Structure in Waveform Data with Visual Assessment and Dunn's Index.-
• Chapter 7: A shared encoder DNN for integrated recognition and segmentation of traffic scenes.-
• Chapter 8: Fuzzy ontology support for knowledge mobilisation.
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This book is a collection of several contributions which show the state of the art in specific areas of Computational Intelligence. This carefully edited book honors the 65th birthday of Rudolf Kruse. The main focus of these contributions lies on treating vague data as well as uncertain and imprecise information with automated procedures, which use techniques from statistics, control theory, clustering, neural networks etc. to extract useful and employable knowledge. .
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• Foundational (Co)datatypes and (Co)recursion for Higher-Order Logic.- Designing Theory Solvers with Extensions.- First-Order Interpolation of Non-Classical Logics Derived from Propositional Interpolation.- A New Description Logic with Set Constraints and Cardinality Constraints on Role Successors.- Interpolation, Amalgamation and Combination (the Non-disjoint Signatures Case).- Subtropical Satisfiability.- Finitariness of Elementary Unification in Boolean Region Connection Calculus.- Metric Temporal Description Logics with Interval-Rigid Names.- Superposition with Integrated Induction.- The Bernays-Schoenfinkel-Ramsey Fragment with Bounded Difference Constraints over the Reals is Decidable.- Decidable Verification of Decision-Theoretic Golog.- Pushing the Boundaries of Reasoning About Qualified Cardinality Restrictions.- Complexity Analysis for Term Rewriting by Integer Transition Systems.- Using Ontologies to Query Probabilistic Numerical Data.- Merging Fragments of Classical Logic.- On Solving Nominal Fixpoint Equations.- Parallel Closure Theorem for Left-Linear Nominal Rewriting Systems.- Solving SAT and MaxSAT with a Quantum Annealer: Foundations and a Preliminary Report.- The Boolean Solution Problem from the Perspective of Predicate Logic. .
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This book constitutes the proceedings of the 11th International Symposium on Frontiers of Combining Systems, FroCoS 2017, held in Brasilia, Bazil, in September 2017. The 17 papers presented in this volume were carefully reviewed and selected from 26 submissions. They were organized in topical sections named: description and temporal logics, decision procedures, decidability and verification, SAT, SMT and automated theorem proving, term rewriting, and properties and combinations of logics. The paper 'Subtropical Satisfiability' is open access under a CC BY 4.0 license via link.springer.com. .
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• Novel imaging and analysis methods for myocardial tissue characterization and remodeling.- Advanced cardiac image analysis tools for diagnostic and interventions.- Electrophysiology: mapping and biophysical modeling.- Biomechanics and flow: modeling and tissue property measurements.
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This book constitutes the refereed proceedings of the 9th International Conference on Functional Imaging and Modeling of the Heart, held in Toronto, ON, Canada, in June 2017. The 48 revised full papers were carefully reviewed and selected from 63 submissions. The focus of the papers is on following topics: novel imaging and analysis methods for myocardial tissue characterization and remodeling; advanced cardiac image analysis tools for diagnostic and interventions; electrophysiology: mapping and biophysical modeling; biomechanics and flow: modeling and tissue property measurements.
(source: Nielsen Book Data)

• Neural Networks
• . Neural Networks with Feedback and Self-organization Introduction
• Fuzzy Inference Systems and Fuzzy Neural Networks
• Application of Fuzzy Logic Systems and Fuzzy Neural Networks in Forecasting Problems in Macroeconomics and Finance
• Fuzzy Neural Networks in Classification Problems
• Inductive Modeling Method (gmdh) in Problems of Intellectual Data Analysis and Forecasting
• The Cluster Analysis in Intellectual Systems
• Genetic Algorithms and Evolutionary Programing
• Problem of Fuzzy Portfolio optimization Under Uncertainty And Its Solution With Application of Computational Intelligence Methods.

This monograph is dedicated to the systematic presentation of main trends, technologies and methods of computational intelligence (CI). The book pays big attention to novel important CI technology- fuzzy logic (FL) systems and fuzzy neural networks (FNN). Different FNN including new class of FNN- cascade neo-fuzzy neural networks are considered and their training algorithms are described and analyzed. The applications of FNN to the forecast in macroeconomics and at stock markets are examined. The book presents the problem of portfolio optimization under uncertainty, the novel theory of fuzzy portfolio optimization free of drawbacks of classical model of Markovitz as well as an application for portfolios optimization at Ukrainian, Russian and American stock exchanges. The book also presents the problem of corporations bankruptcy risk forecasting under incomplete and fuzzy information, as well as new methods based on fuzzy sets theory and fuzzy neural networks and results of their application for bankruptcy risk forecasting are presented and compared with Altman method. This monograph also focuses on an inductive modeling method of self-organization - the so-called Group Method of Data Handling (GMDH) which enables to construct the structure of forecasting models almost automatically. The results of experimental investigations of GMDH for forecasting at stock exchanges are presented. The final chapters are devoted to theory and applications of evolutionary modeling (EM) and genetic algorithms. The distinguishing feature of this monograph is a great number of practical examples of CI technologies and methods application for solution of real problems in technology, economy and financial sphere, in particular forecasting, classification, pattern recognition, portfolio optimization, bankruptcy risk prediction under uncertainty which were developed by authors and published in this book for the first time. All CI methods and algorithms are presented from the general system approach and analysis of their properties, advantages and drawbacks that enables practitioners to choose the most adequate method for their own problems solution. .

• Position Papers.- With or without Meaning? Hype Cycles in Language Technology and what We Can Learn from Them.- Observatory for Language Resources and Machine Translation in Europe - LT Observatory.- The Rise of the Conversational Interface: A new Kid on the Block.- Spanish Language Technologies Plan.- Improving Collaboration between the European Language Technology Industry & Research: A new Framework for Supply & Demand.- Contributed Papers.- LifeLine dialogues with Roberta.- An affective utility model of user motivation for counselling dialogue systems.- Exploring flexibility in natural language generation throughout discursive analysis of new textual genres.- Bootstrapping technique + embeddings = Emotional corpus annotated automatically.- Rapid construction of a web-enabled medical speech to sign language translator using recorded video.- Incorporating syllable phonotactics to improve grapheme to phoneme translation.- Hybrid conceptual and statistical measure for semantic textual similarity evaluation.- General representation model for text similarity.- Extending feature decay algorithms using alignment entropy.- Towards a topic discovery and tracking system with application to news items.
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This book constitutes revised selected papers from the Second International Workshop on Future and Emerging Trends in Language Technology, FETLT 2016, which took place in Seville, Spain, in November 2016. The 10 full papers and 5 position papers presented in this volume were carefully reviewed and selected from 18 submissions. In 2016 the conference focused on Machine Learning and Big Data. .
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• Fuzzy Numbers.- Dual Numbers.- Fuzzy Dual Numbers.- Fuzzy Dual Linear Matrix Inequalities.- Fuzzy Estimation of Distribution Matrices.- Fuzzy Dual Entropy and Applications.- Fuzzy Dual Programming.
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This is the first book focusing exclusively on fuzzy dual numbers. In addition to offering a concise guide to their properties, operations and applications, it discusses some of their advantages with regard to classical fuzzy numbers, and describes the most important operations together with a set of interesting applications in e.g. optimization, decision-making and system design. The book provides students, researchers and professionals the necessary theoretical background to apply this particular subset of fuzzy numbers to decision-making problems involving uncertainty. Further, it shows how to solve selected engineering and management problems and includes detailed numerical examples.
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• Fuzzy measures and transforms.- Granularity and multi-logics.- Clustering and learning.- Knowledge systems.- Soft computing and applications.
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This book constitutes the proceedings of the 11th International Workshop on Fuzzy Logic and Applications, WILF 2016, held in Naples, Italy, in December 2016. The 22 revised full papers presented together with 2 invited lectures were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on fuzzy measures and transforms; granularity and multi-logics, clustering and learning; knowledge systems; and soft computing and applications.
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• Part I: Foundations.- Introduction.- Genetic Algorithms.- Parameters.- Part II: Solution Spaces.- Multimodality.- Constraints.- Multiple Objectives.- Part III: Advanced Concepts.- Theory.- Machine Learning.- Applications.- Part IV: Ending.- Summary and Outlook.- Index.- References.
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This book introduces readers to genetic algorithms (GAs) with an emphasis on making the concepts, algorithms, and applications discussed as easy to understand as possible. Further, it avoids a great deal of formalisms and thus opens the subject to a broader audience in comparison to manuscripts overloaded by notations and equations. The book is divided into three parts, the first of which provides an introduction to GAs, starting with basic concepts like evolutionary operators and continuing with an overview of strategies for tuning and controlling parameters. In turn, the second part focuses on solution space variants like multimodal, constrained, and multi-objective solution spaces. Lastly, the third part briefly introduces theoretical tools for GAs, the intersections and hybridizations with machine learning, and highlights selected promising applications.
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• Intro; Preface; Organization; Contents; Oral Presentations; Evolutionary Program Sketching; 1 Introduction; 2 Program Sketching; 3 Evolutionary Program Sketching; 3.1 Problem Specification; 3.2 Instruction Set; 3.3 Fitness Function; 3.4 Exploiting the Feedback from Hole Completion; 4 Related Work; 5 Experimental Evaluation; 6 Discussion; 7 Conclusion; References; Exploring Fitness and Edit Distance of Mutated Python Programs; 1 Introduction; 2 Related Work; 3 Our Implementation of Genetic Improvement; 3.1 Fitness Function; 3.2 Search Algorithm; 4 Experimental Setup

• 4.1 Description of the Programs Targeted by GI5 Results; 5.1 Change in Fitness; 5.2 Average Fitness with Respect to Edit List Size; 5.3 Discrete Steps in Fitness; 6 Conclusions; References; Differentiable Genetic Programming; 1 Introduction; 2 Program Encoding; 3 The Algebra of Truncated Polynomials; 3.1 The Link to Taylor Polynomials; 3.2 Non Rational Functions; 4 Example of a dCGP; 5 Learning Constants in Symbolic Regression; 5.1 Ephemeral Constants Approach; 5.2 Weighted dCGP Approach; 6 Solution to Differential Equations; 7 Discovery of Prime Integrals; 8 Conclusions; References

• Evolving Game State Features from Raw Pixels1 Introduction; 2 Related Research; 3 Materials; 3.1 Games; 3.2 Handcrafted Game State Features; 4 Evolving Video Game State Visual Features Using Genetic Programming; 4.1 Evolving Game State Features; 4.2 Voting for Actions; 5 Results; 6 Conclusion; References; Emergent Tangled Graph Representations for Atari Game Playing Agents; 1 Introduction; 2 Background; 3 The Arcade Learning Environment; 3.1 Screen State Space Representation; 4 Evolving Tangled Program Graphs; 4.1 Coevolving Teams of Programs; 4.2 Emergent Modularity

• 4.3 Diversity Maintenance5 Empirical Experiments; 5.1 Experimental Setup; 5.2 Results; 5.3 Solution Analysis; 6 Conclusion and Future Work; References; A General Feature Engineering Wrapper for Machine Learning Using -Lexicase Survival; 1 Introduction; 2 Feature Engineering Wrapper; 2.1 -lexicase Survival; 2.2 Scaling; 3 Related Work; 4 Experimental Analysis; 4.1 Problems; 5 Results; 5.1 Hyper-Parameter Optimization; 5.2 Problem Performance; 5.3 Statistical Analysis; 6 Discussion; 7 Conclusions; References; Visualising the Search Landscape of the Triangle Program; 1 Genetic Improvement

• 2 Triangle Program Software Engineering Benchmark3 Binary Representation: Replacing Comparisons with One Alternative; 3.1 High Order Binary Schema Are Not Deceptive; 3.2 Binary Schema Predict All Solutions of the Triangle Program; 3.3 Local Search Landscape of the Binary Space; 4 Original All Comparisons; 4.1 Fitness Space of Triangle Program; 4.2 High Order Schema Analysis; 4.3 Local Search for the Triangle Program; 4.4 Local Optima Networks; 5 Conclusions; References; RANSAC-GP: Dealing with Outliers in Symbolic Regression with Genetic Programming; 1 Introduction; 2 Background; 2.1 Outliers

This book constitutes the refereed proceedings of the 20th European Conference on Genetic Programming, EuroGP 2017, held in Amsterdam, The Netherlands, in April 2017, co-located with the Evo* 2017 events, EvoCOP, EvoMUSART, and EvoApplications. The 14 revised full papers presented together with 8 poster papers were carefully reviewed and selected from 32 submissions. The wide range of topics in this volume reflects the current state of research in the field. Thus, we see topics and applications including program synthesis, genetic improvement, grammatical representations, self-adaptation, multi-objective optimisation, program semantics, search landscapes, mathematical programming, games, operations research, networks, evolvable hardware, and program synthesis benchmarks.
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• From the content: Geometry, Action and Movement.- Numerical Analyzis and Optimization.- Foundation of Human Movement.
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This book aims at gathering roboticists, control theorists, neuroscientists, and mathematicians, in order to promote a multidisciplinary research on movement analysis. It follows the workshop " Geometric and Numerical Foundations of Movements " held at LAAS-CNRS in Toulouse in November 2015[1]. Its objective is to lay the foundations for a mutual understanding that is essential for synergetic development in motion research. In particular, the book promotes applications to robotics --and control in general-- of new optimization techniques based on recent results from real algebraic geometry.
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• Statistics on non-linear data.- Shape space.- Optimal Transport & Applications.- Statistical Manifold & Hessian Information Geometry.- Statistical Manifold and Hessian Information Geometry.- Monotone Embedding in Information Geometry.- Information Structure in Neuroscience.- Geometric Robotics and Tracking.- Geometric Mechanics and Robotics.- Stochastic Geometric Mechanics and Lie Group Thermodynamics.- Probability on Riemannian Manifolds.- Divergence Geometry.- Non-parametric Information Geometry.- Optimization on Manifold.- Computational Information Geometry.- Probability Density Estimation.- Session Geometry of Tensor-Valued Data.- Geodesic Methods with Constraints.- Applications of Distance Geometry.
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This book constitutes the refereed proceedings of the Third International Conference on Geometric Science of Information, GSI 2017, held in Paris, France, in November 2017. The 101 full papers presented were carefully reviewed and selected from 113 submissions and are organized into the following subjects: statistics on non-linear data; shape space; optimal transport and applications: image processing; optimal transport and applications: signal processing; statistical manifold and hessian information geometry; monotone embedding in information geometry; information structure in neuroscience; geometric robotics and tracking; geometric mechanics and robotics; stochastic geometric mechanics and Lie group thermodynamics; probability on Riemannian manifolds; divergence geometry; non-parametric information geometry; optimization on manifold; computational information geometry; probability density estimation; session geometry of tensor-valued data; geodesic methods with constraints; applications of distance geometry.
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• Introduction.- Radon Transform based Automatic Posture Recognition in Ballet Dance.- Fuzzy Image Matching Based Posture Recognition in Ballet Dance.- Gesture Driven Fuzzy Interface System For Car Racing Game.- Type-2 Fuzzy Classifier based Pathological Disorder Recognition.- Probabilistic Neural Network based Dance Gesture Recognition.- Differential Evolution based Dance Composition.- EEG-Gesture based Artificial Limb Movement for Rehabilitative Applications.- Conclusions and Future Directions.- Index.
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This book presents a thorough analysis of gestural data extracted from raw images and/or range data with an aim to recognize the gestures conveyed by the data. It covers image morphological analysis, type-2 fuzzy logic, neural networks and evolutionary computation for classification of gestural data. The application areas include the recognition of primitive postures in ballet/classical Indian dances, detection of pathological disorders from gestural data of elderly people, controlling motion of cars in gesture-driven gaming and gesture-commanded robot control for people with neuro-motor disability. The book is unique in terms of its content, originality and lucid writing style. Primarily intended for graduate students and researchers in the field of electrical/computer engineering, the book will prove equally useful to computer hobbyists and professionals engaged in building firmware for human-computer interfaces. A prerequisite of high school level mathematics is sufficient to understand most of the chapters in the book. A basic background in image processing, although not mandatory, would be an added advantage for certain sections.
(source: Nielsen Book Data)

• Preface.- Acknowledgements.- 1 From Natural to Synthetic Swarms.- 2 Glowworm Swarm Optimization: Algorithm Development.- 3 Theoretical Foundations.- 4 Multimodal Function Optimization.- 5 Experiments using Physical Simulations and Real Robots.- 6 Applications to Ubiquitous Computing Environments.- 7 Pursuit of Multiple Mobile Signal Sources.- 8 GSO Applications and Extensions.
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This book provides a comprehensive account of the glowworm swarm optimization (GSO) algorithm, including details of the underlying ideas, theoretical foundations, algorithm development, various applications, and MATLAB programs for the basic GSO algorithm. It also discusses several research problems at different levels of sophistication that can be attempted by interested researchers. The generality of the GSO algorithm is evident in its application to diverse problems ranging from optimization to robotics. Examples include computation of multiple optima, annual crop planning, cooperative exploration, distributed search, multiple source localization, contaminant boundary mapping, wireless sensor networks, clustering, knapsack, numerical integration, solving fixed point equations, solving systems of nonlinear equations, and engineering design optimization. The book is a valuable resource for researchers as well as graduate and undergraduate students in the area of swarm intelligence and computational intelligence and working on these topics.
(source: Nielsen Book Data)

• Introduction to Granular Computing, Pattern Recognition and Data Mining.- Classification using Fuzzy Rough Granular Neural Networks.- Clustering using Fuzzy Rough Granular Self-Organizing Map.- Fuzzy Rough Granular Neural Network and Unsupervised Feature Selection.
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This book provides a uniform framework describing how fuzzy rough granular neural network technologies can be formulated and used in building efficient pattern recognition and mining models. It also discusses the formation of granules in the notion of both fuzzy and rough sets. Judicious integration in forming fuzzy-rough information granules based on lower approximate regions enables the network to determine the exactness in class shape as well as to handle the uncertainties arising from overlapping regions, resulting in efficient and speedy learning with enhanced performance. Layered network and self-organizing analysis maps, which have a strong potential in big data, are considered as basic modules, . The book is structured according to the major phases of a pattern recognition system (e.g., classification, clustering, and feature selection) with a balanced mixture of theory, algorithm, and application. It covers the latest findings as well as directions for future research, particularly highlighting bioinformatics applications. The book is recommended for both students and practitioners working in computer science, electrical engineering, data science, system design, pattern recognition, image analysis, neural computing, social network analysis, big data analytics, computational biology and soft computing.
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• Part I: Information Theoretic and Aggregation Issues.- Part II: Applications in Modeling, Decision Making, Control, and Other Areas.- Part III: Some Bibliometric Remarks.
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This book offers a comprehensive report on the state-of-the art in the broadly-intended field of "intelligent systems". After introducing key theoretical issues, it describes a number of promising models for data and system analysis, decision making, and control. It discusses important theories, including possibility theory, the Dempster-Shafer theory, the theory of approximate reasoning, as well as computing with words, together with novel applications in various areas, such as information aggregation and fusion, linguistic data summarization, participatory learning, systems modeling, and many others. By presenting the methods in their application contexts, the book shows how granular computing, soft computing and fuzzy logic techniques can provide novel, efficient solutions to real-world problems. It is dedicated to Professor Ronald R. Yager for his great scientific and scholarly achievements, and for his long-lasting service to the fuzzy logic, and the artificial and computational intelligence communities. It has been motivated by the authors' appreciation of his original thinking and groundbreaking ideas, with a special thought to his valuable research on the computerized implementation of various aspects of human cognition for decision-making and problem-solving. .
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• Preface.-
• Chapter 1: Introduction.- Part I: Generalized Related Set Based Approach.-
• Chapter 2: Information System for Relational Data.-
• Chapter 3: Properties of Granular-Relational Data Mining Framework.-
• Chapter 4: Association Discovery and Classification Rule Mining.-
• Chapter 5: Rough-Granular Computing.- Part II: Description Language Based Approach.-
• Chapter 6: Compound Information Systems.-
• Chapter 7: From Granular-Data Mining Framework to its Relational Version.-
• Chapter 8: Relation-Based Granules.-
• Chapter 9: Compound Approximation Spaces.- Conclusions.- References.- Index.
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This book provides two general granular computing approaches to mining relational data, the first of which uses abstract descriptions of relational objects to build their granular representation, while the second extends existing granular data mining solutions to a relational case. Both approaches make it possible to perform and improve popular data mining tasks such as classification, clustering, and association discovery. How can different relational data mining tasks best be unified? How can the construction process of relational patterns be simplified? How can richer knowledge from relational data be discovered? All these questions can be answered in the same way: by mining relational data in the paradigm of granular computing! This book will allow readers with previous experience in the field of relational data mining to discover the many benefits of its granular perspective. In turn, those readers familiar with the paradigm of granular computing will find valuable insights on its application to mining relational data. Lastly, the book offers all readers interested in computational intelligence in the broader sense the opportunity to deepen their understanding of the newly emerging field granular-relational data mining.
(source: Nielsen Book Data)

• Intro
• Workshop Editors
• Preface GRAIL 2017
• Organization
• Preface MFCA 2017
• Organization
• Preface MICGen 2017
• Organization
• Contents
• First International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2017
• Classifying Phenotypes Based on the Community Structure of Human Brain Networks
• 1 Introduction
• 2 Similarity of Brain Network Community Structures
• 2.1 Detecting Communities in Structural Brain Networks
• 2.2 Measuring Distance Between Community Structures
• 3 Classifying Connectomes Based on their Community Structure

• 4 Experiments: Network-Based Alzheimer's Disease Classification
• 4.1 Data and Network Construction
• 4.2 Experimental Setup
• 4.3 Results and Discussion
• 5 Conclusions
• References
• Autism Spectrum Disorder Diagnosis Using Sparse Graph Embedding of Morphological Brain Networks
• 1 Introduction
• 2 Proposed Sparse Graph Embedding of High-Order Morphological Brain Networks for Autism Classification
• 3 Results and Discussion
• 4 Conclusion
• References
• Topology of Surface Displacement Shape Feature in Subcortical Structures
• 1 Introduction
• 2 Methods
• 2.1 Shape Feature

• 2.2 Shape Topology
• 2.3 Persistent Homology
• 2.4 Experiments
• 2.5 Imaging and Demographics
• 3 Results
• 4 Discussion and Conclusion
• References
• Graph Geodesics to Find Progressively Similar Skin Lesion Images
• 1 Introduction
• 2 Methods
• 3 Results
• 4 Conclusions
• References
• Uncertainty Estimation in Vascular Networks
• 1 Introduction
• 2 Background
• 3 Uncertainty Estimation by Means of Sampling
• 3.1 Perturbation Sampler
• 3.2 Gibbs Sampler
• 4 Experiments and Results
• 5 Conclusion
• References

• Extraction of Airways with Probabilistic State-Space Models and Bayesian Smoothing
• 1 Introduction
• 2 Method
• 2.1 Tracking Individual Branches
• 2.2 Process and Measurement Models
• 2.3 Bayesian Smoothing
• 2.4 Tree as a Collection of Branches
• 2.5 Application to Airways
• 3 Experiments and Results
• 3.1 Data
• 3.2 Error Measure, Initial Parameters and Tuning
• 3.3 Results
• 4 Discussion and Conclusions
• References
• Detection and Localization of Landmarks in the Lower Extremities Using an Automatically Learned Conditional Random Field
• 1 Introduction
• 2 Related Work

• 3 Methods
• 3.1 Landmark Localization Using Regression Tree Ensembles
• 3.2 CRF with Pool of Potential Functions and ``Missing'' Label
• 3.3 Learning of Parameters and Removing Potentials
• 4 Results
• 5 Discussion and Conclusions
• References
• 6th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017
• Bridge Simulation and Metric Estimation on Landmark Manifolds
• 1 Introduction
• 2 Landmarks Manifolds and Stochastic Landmark Dynamics
• 2.1 Brownian Motion
• 2.2 Large Deformation Stochastics
• 3 Brownian Bridge Simulation
• 3.1 Bridge Sampling

This book constitutes the refereed joint proceedings of the First International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2017, the 6th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017, and the Third International Workshop on Imaging Genetics, MICGen 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 7 full papers presented at GRAIL 2017, the 10 full papers presented at MFCA 2017, and the 5 full papers presented at MICGen 2017 were carefully reviewed and selected. The GRAIL papers cover a wide range of graph based medical image analysis methods and applications, including probabilistic graphical models, neuroimaging using graph representations, machine learning for diagnosis prediction, and shape modeling. The MFCA papers deal with theoretical developments in non-linear image and surface registration in the context of computational anatomy. The MICGen papers cover topics in the field of medical genetics, computational biology and medical imaging.
(source: Nielsen Book Data)

• Cryptography, security and biometric techniques ; Reducing costs in HSM-based data centers / R. De Prisco, A. De Santis, and M. Mannetta
• Secure user authentication on smartphones via sensor and face recognition on short video clips / Chiara Galdi, Michele Nappi, and Jean-Luc Dugelay
• A hybrid approach for private data protection in the cloud / Amal Ghorbel, Mahmoud Ghorbel, and Mohamed Jmaiel
• An efficient and secure design of redactable signature scheme with redaction condition control / Jinhua Ma, Jianghua Liu, Min Wang, and Wei Wu
• New publicly verifiable computation for batch matrix multiplication / Xiaoyu Zhang, Tao Jiang, Kuan-Ching Li, and Xiaofeng Chen
• A multi-source homomorphic network coding signature in the standard model / Wenbin Chen, Hao Lei, Jin Li, Chongzhi Gao, Fufang Li, and Ke Qi
• Trust-ABAC towards an access control system for the internet of things / Hamdi Ouechtati and Nadia Ben Azzouna
• Privacy preserving multimodal biometric authentication in the cloud / Neyire Deniz Sarier
• MOHAB : mobile hand-based biometric recognition / Silvio Barra, Maria De Marsico, Michele Nappi, Fabio Narducci, and Daniel Riccio
• Further improvement on an efficient and secure three-factor based authenticated key exchange scheme using elliptic curve cryptosystems / Chun-Ta Li, Chin-Ling Chen, Cheng-Chi Lee, and Chien-Ming Chen

• Advanced network services, algorithms and optimization ; A study of interference cancellation for NOMA downlink near-far effect to support big data / Shaoyu Dou, Xin Su, Dongmin Choi, Pankoo Kim, and Chang Choi
• Dynamic latency sensitivity recognition : an application to energy saving / S. Al Haj Baddar, A. Merlo, M. Migliardi, and F. Palmieri
• TPS : an efficient VM scheduling algorithm for HPC applications in cloud / Duoqiang Wang, Wei Dai, Chi Zhang, Xuanhua Shi, and Hai Jin
• Improved upper and lower bounds for the close enough traveling salesman problem / Francesco Carrabs, Carmine Cerrone, Raffaele Cerulli, and Ciriaco D'Ambrosio
• Object storage in cloud computing environments : an availability analysis / Giuliana Carullo, Mario Di Mauro, Michele Galderisi, Maurizio Longo, Fabio Postiglione, and Marco Tambasco
• Energy-efficient dynamic consolidation of virtual machines in big data centers / Shuting Xu, Chase Q. Wu, Aiqin Hou, Yongqiang Wang, and Meng Wang
• Influence maximization in social media networks using hypergraphs / Flora Amato, Vincenzo Moscato, Antonio Picariello, and Giancarlo Sperli
• A modified segmentation approach for overlapping elliptical objects with various sizes / Guanghui Zhao, Xingyan Zi, Kaitai Liang, Panyi Yun, and Junwei Zhou
• Privacy and temporal aware allocation of data in decentralized online social networks / Andrea De Salve, Barbara Guidi, Paolo Mori, Laura Ricci, and Vincenzo Ambriola
• A unifying orchestration operating platform for 5G / Antonio Manzalini, Marco Di Girolamo, Giuseppe Celozzi, Fulvio Bruno, Giuliana Carullo, Marco Tambasco, Gino Carrozzo, Fulvio Risso, and Gabriele Castellano
• Identification of energy hotspots : a case study of the very fast decision tree / Eva Garcia-Martin, Niklas Lavesson, and Håkan Grahn

• Mobile and pervasive computing ; Prolonging lifetime in wireless sensor networks with interference constraints / Francesco Carrabs, Raffaele Cerulli, Ciriaco D'Ambrosio, and Andrea Raiconi
• An orchestrated security platform for internet of robots / Mehrnoosh Monshizadeh, Vikramajeet Khatri, Raimo Kantola, and Zheng Yan
• A novel clustering solution for wireless sensor networks / Anxi Wang, Shuzhen Pan, Chen Wang, Jian Shen, and Dengzhi Liu
• Reliable data collection for wireless sensor networks using unmanned aerial vehicles / Alexandru-Valentin Vlăduță, Ion Bica, Victor-Valeriu Patriciu, and Florin Pop
• Flaw recovery in cloud based bio-inspired peer-to-peer systems for smart cities / Bogdan Mocanu, Florin Pop, Alexandra Mihaita (Mocanu), Ciprian Dobre, Valentin Cristea, and Aniello Castiglione
• DPCAS : data prediction with cubic adaptive sampling for wireless sensor networks / Leonardo C. Monteiro, Flavia C. Delicato, Luci Pirmez, Paulo F. Pires, and Claudio Miceli
• Cybersecurity ; Personalized privacy preserving collaborative filtering / Mengmeng Yang, Tianqing Zhu, Yang Xiang, and Wanlei Zhou
• Know your enemy : stealth configuration-information gathering in SDN / Mauro Conti, Fabio De Gaspari, and Luigi V. Mancini
• SOOA : exploring special on-off attacks on challenge-based collaborative intrusion detection networks / Wenjuan Li, Weizhi Meng, and Lam-For Kwok
• Assessment of security threats via network topology analysis : an initial investigation / Marcello Trovati, Win Thomas, Quanbin Sun, and Georgios Kontonatsios
• You surf so strange today : anomaly detection in web services via HMM and CTMC / Maddalena Favaretto, Riccardo Spolaor, Mauro Conti, and Marco Ferrante

• Parallel and distributed computing ; CDLP : a core distributing policy based on logic partitioning / Alin Zhong, Shun Ren, and Shouzhi Xu
• A profit-maximum resource allocation approach for mapreduce in data centers / Xiaolu Zhang, Weidong Li, Xi Liu, and Xuejie Zhang
• An efficient implementation of the algorithm by Lukáš et. al. on Hadoop / Giuseppe Cattaneo, Umberto Ferraro Petrillo, Michele Nappi, Fabio Narducci, and Gianluca Roscigno
• Integration of data distribution service and Raspberry Pi / Marisol García-Valls, Daniel Garrido, and Manuel Díaz
• Ontologies and smart applications ; Semantic knowledge and service models for energy-aware systems / Jarmo Kalaoja
• Transferring remote ontologies to the edge of internet of things systems / Xiang Su, Pingjiang Li, Huber Flores, Jukka Riekki, Xiaoli Liu, Yuhong Li, and Christian Prehofer
• A mobile context-aware information system to support tourism events / Fabio Clarizia, Saverio Lemma, Marco Lombardi, and Francesco Pascale
• On ontological digital storytelling to enrich tourist destinations and attractions with a mobile tailored story / Fabio Clarizia, Saverio Lemma, Marco Lombardi, and Francesco Pascale
• Healthcare support systems ; Design of a secure emergency communication system based on cloud for pregnancy / Guan-Chen Li, Chin-Ling Chen, Feng Lin, Jungpil Shin, and Cheng Gu
• A trust application in participatory sensing : elder reintegration / Alexandra Mihaita (Mocanu), Ciprian Dobre, Florin Pop, Bogdan Mocanu, Valentin Cristea, and Christian Esposito
• DABEHR : decentralized attribute-based electronic health record system with constant-size storage complexity / Ye Li, Kaitai Liang, Chunhua Su, and Wei Wu
• Automatic diagnosis metabolic system via a [italic]k-nearest neighbour classifier / Omar Behadada, Meryem Abi-Ayad, Georgios Kontonatsios, and Marcello Trovati

• 1st international workshop on digital knowledge ecosystems ; Harnessing mobile pervasive computing to enhance livelihood processes : farmer response to a mobile agriculture information system / L.N.C. De Silva, J.S. Goonetillake, G.N. Wikramanayake, and A. Ginige
• Social computing : new pervasive computing paradigm to enhance triple bottom line / Marie D. Fernando, Athula Ginige, and Ana Hol
• Digital knowledge ecosystem for empowering users to self-manage diabetes through context specific actionable information / Maneesh Mathai, Athula Ginige, Uma Srinivasan, and Federico Girosi
• Human-centered design of a personal medical assistant : putting polypharmacy management into patient's hand! / Monica Sebillo, Giuliana Vitiello, Danilo Cuciniello, and Serena Carrabs
• A digital knowledge ecosystem to increase participation in emergency warnings and alerts management / Paloma Díaz, Teresa Onorati, and Ignacio Aedo
• An intelligent framework for predicting state war engagement from territorial data / Giovanni Acampora, Genoveffa Tortora, and Autilia Vitiello
• 1st workshop on cloud security modeling, monitoring and management (CS3M) ; BYODCert : toward a cross-organizational BYOD paradigm / Alessio Merlo
• Security-centric evaluation framework for IT services / Smrati Gupta, Jaume Ferrarons-Llagostera, Jacek Dominiak, Victor Muntés-Mulero, Peter Matthews, and Erkuden Rios
• Multi-cloud applications security monitoring / Pamela Carvallo, Ana R. Cavalli, Wissam Mallouli, and Erkuden Rios
• Secure microGRID in cloud : the coSSMic case study / Massimiliano Rak and Salvatore Venticinque
• Towards model-based security assessment of cloud applications / Valentina Casola, Alessandra De Benedictis, and Roberto Nardone
• Security assurance of (multi- )cloud application with security SLA composition / Massimiliano Rak
• Security issues in cloud computing / Parnian Najafi Borazjani
• Erratum to : An orchestrated security platform for internet of robots / Mehrnoosh Monshizadeh, Vikramajeet Khatri, Raimo Kantola, and Zheng Yan.

This book constitutes the proceedings of the 12th International Conference on Green, Pervasive, and Cloud Computing, GPC 2017, held in Cetara, Italy, in May 2017 and the following colocated workshops: First International Workshop on Digital Knowledge Ecosystems 2017; and First Workshop on Cloud Security Modeling, Monitoring and Management, CS3M 2017. The 58 full papers included in this volume were carefully reviewed and selected from 169 initial submissions. They deal with cryptography, security and biometric techniques; advances network services, algorithms and optimization; mobile and pervasive computing; cybersecurity; parallel and distributed computing; ontologies and smart applications; and healthcare support systems.
(source: Nielsen Book Data)

• Intro; Preface; Contents; Introduction; 1 Exploring Grouping Problems in Industry; 1.1 Introduction; 1.2 Identifying Grouping Problems in Industry; 1.2.1 Cell Formation in Manufacturing Systems; 1.2.2 Assembly Line Balancing; 1.2.3 Job Shop Scheduling; 1.2.4 Vehicle Routing Problem; 1.2.5 Home Healthcare Worker Scheduling; 1.2.6 Bin Packing Problem; 1.2.7 Task Assignment Problem; 1.2.8 Modular Product Design; 1.2.9 Group Maintenance Planning; 1.2.10 Order Batching; 1.2.11 Team Formation; 1.2.12 Earnings Management; 1.2.13 Economies of Scale; 1.2.14 Timetabling

• 1.2.15 Student Grouping for Cooperative Learning1.2.16 Other Problems; 1.3 Extant Modeling Approaches to Grouping Problems; 1.4 Structure of the Book; References; 2 Complicating Features in Industrial Grouping Problems; 2.1 Introduction; 2.2 Research Methodology; 2.3 Research Findings; 2.4 Complicating Features; 2.4.1 Model Conceptualization; 2.4.2 Myriad of Constraints; 2.4.2.1 Intra-Group Relationship; 2.4.2.2 Inter-Group Relationship; 2.4.2.3 Group Size Limits; 2.4.2.4 Grouping Limit; 2.4.3 Fuzzy Management Goals; 2.4.4 Computational Complexity; 2.5 Suggested Solution Approaches

• 2.6 SummaryReferences; Grouping Genetic Algorithms; 3 Grouping Genetic Algorithms: Advances for Real-World Grouping Problems; 3.1 Introduction; 3.2 Grouping Genetic Algorithm: An Overview; 3.2.1 Group Encoding; 3.3 Crossover; 3.3.1 Mutation; 3.3.2 Inversion; 3.4 Grouping Genetic Algorithms: Advances and Innovations; 3.4.1 Group Encoding Strategies; 3.4.1.1 Encoding Strategy 1; 3.4.1.2 Encoding Strategy 2; 3.4.2 Initialization; 3.4.2.1 User-Generated Seeds; 3.4.2.2 Random Generation; 3.4.2.3 Constructive Heuristics; 3.4.3 Selection Strategies; 3.4.3.1 Stochastic Sampling Without Replacement

• 3.4.4 Rank-Based Wheel Selection Strategy3.4.5 Crossover Strategies; 3.4.5.1 Two-Point Group Crossover; 3.4.5.2 Adaptive Crossover; 3.4.6 Mutation Strategies; 3.4.6.1 Swap Mutation; 3.4.6.2 Split Mutation; 3.4.6.3 Merge Mutation; 3.4.6.4 Adaptive Mutation; 3.4.7 Inversion; 3.4.7.1 Two-Point Inversion; 3.4.7.2 Single-Point Inversion; 3.4.7.3 Adaptive Inversion; 3.4.8 Replacement Strategies; 3.4.9 Termination Strategies; 3.4.9.1 Iteration Count (ItCount); 3.4.9.2 Iterations Without Improvement (ItWithoutImp); 3.4.9.3 Hybrid Criteria; 3.5 Application Areas; 3.6 Summary; References

• 4 Fuzzy Grouping Genetic Algorithms: Advances for Real-World Grouping Problems4.1 Introduction; 4.2 Preliminaries: Fuzzy Logic Control; 4.3 Fuzzy Grouping Genetic Algorithms: Advances and Innovations; 4.3.1 FGGA Coding Scheme; 4.3.2 Initialization; 4.3.3 Fuzzy Fitness Evaluation; 4.3.3.1 Multifactor Evaluation; 4.3.3.2 Fuzzy Goal-Oriented Fitness Evaluation; 4.3.4 Fuzzy Genetic Operators; 4.3.4.1 Fuzzy Controlled Genetic Parameters; Convergence Measure; Diversity Measure; Crossover Probability; Mutation Probability; Inversion Probability; 4.3.4.2 Fuzzy Logic Controlled Crossover

This book presents advances and innovations in grouping genetic algorithms, enriched with new and unique heuristic optimization techniques. These algorithms are specially designed for solving industrial grouping problems where system entities are to be partitioned or clustered into efficient groups according to a set of guiding decision criteria. Examples of such problems are: vehicle routing problems, team formation problems, timetabling problems, assembly line balancing, group maintenance planning, modular design, and task assignment. A wide range of industrial grouping problems, drawn from diverse fields such as logistics, supply chain management, project management, manufacturing systems, engineering design and healthcare, are presented. Typical complex industrial grouping problems, with multiple decision criteria and constraints, are clearly described using illustrative diagrams and formulations. The problems are mapped into a common group structure that can conveniently be used as an input scheme to specific variants of grouping genetic algorithms. Unique heuristic grouping techniques are developed to handle grouping problems efficiently and effectively. Illustrative examples and computational results are presented in tables and graphs to demonstrate the efficiency and effectiveness of the algorithms. Researchers, decision analysts, software developers, and graduate students from various disciplines will find this in-depth reader-friendly exposition of advances and applications of grouping genetic algorithms an interesting, informative and valuable resource.

• 2.2 Kernel-Radius-Based Feature Extraction Method
• 3 Experiments
• 3.1 Database
• 3.2 The Experimental Results and Discussions
• 4 Conclusion
• References
• Some Directions of Medical Informatics in Russia
• Abstract
• 1 Gelfand's Approach to Medical Informatics
• 1.1 Personal Applicability of the Result
• 1.2 Using the Experience of a Doctor
• 1.3 Proof of the Result
• 2 Medical Information System "Transfusiology"
• 3 Time-Oriented Multi-image Case History
• Way to the "Disease Image" Analysis
• Acknowledgements
• References

• A Computer Simulation Approach to Reduce Appointment Lead-Time in Outpatient Perinatology Department ...
• Abstract
• 1 Introduction
• 2 Related Work
• 3 Modeling the Perinatology Department: A Case Study in a Maternal-Child Hospital
• 4 Conclusions and Future Work
• References
• Engaging Patients, Empowering Doctors in Digitalization of Healthcare
• Abstract
• 1 Introduction
• 2 Methods and Discussion
• 3 Conclusion
• Acknowledgements
• References
• Developing a Tunable Q-Factor Wavelet Transform Based Algorithm for Epileptic EEG Feature Extraction
• Abstract
• 1 Introduction

• 2 Datasets and Methods
• 2.1 Experimental Data
• 2.2 Methodology
• 3 Performance Measurements
• 4 Experimental Results and Discussions
• 5 Conclusions
• References
• Granular Computing Combined with Support Vector Machines for Diagnosing Erythemato-Squamous Diseases
• 1 Introduction
• 2 The Basic Knowledge of GrC and SVM
• 2.1 The Basic Idea of GrC
• 2.2 Support Vector Machines
• 3 GrC and SVM Based Feature Selection Algorithm
• 3.1 Feature search strategies
• 3.2 Search for Best Parameters
• 3.3 GrC Combined SVM Feature Selection Algorithm
• 4 Experiments and Results

• 4.1 The Erythemato-Squamous Diseases Dataset
• 4.2 Experimental Results and Analysis
• 5 Conclusions
• References
• A Semantically-Enabled System for Inflammatory Bowel Diseases
• 1 Introduction
• 2 System
• 3 Semantic Queries
• 4 Experiments
• 4.1 Basic Information
• 4.2 IBD Onset Distribution
• 4.3 Season and Smoking Factors Analysis
• 5 Related Research
• 6 Conclusions
• References
• Early Classification of Multivariate Time Series Based on Piecewise Aggregate Approximation
• Abstract
• 1 Introduction
• 2 Background
• 3 Related Work

This book constitutes the refereed proceedings of the 6th International Conference on Health Information Science, HIS 2017, held in Moscow, Russia, in October 2017. The 11 full papers and 7 short papers presented were carefully reviewed and selected from 44 submissions. The papers feature multidisciplinary research results in health information science and systems that support health information management and health service delivery. They relate to all aspects of the conference scope, such as medical/health/biomedicine information resources such as patient medical records, devices and equipments, software and tools to capture, store, retrieve, process, analyze, and optimize the use of information in the health domain; data management, data mining, and knowledge discovery, management of publichealth, examination of standards, privacy and security issues; computer visualization and artificial intelligence for computer aided diagnosis; development of new architectures and applications for health information systems.
(source: Nielsen Book Data)

• Hesitant Fuzzy Multiple Criteria Decision Analysis Based on TOPSIS.- Hesitant Fuzzy Multiple Criteria Decision Analysis Based on TODIM.- Hesitant Fuzzy Multiple Criteria Decision Analysis Based on QUALIFLEX.- Hesitant Fuzzy Multiple Criteria Decision Analysis Based on LINMAP.- Consensus Model-Based Hesitant Fuzzy Multiple Criteria Group Decision Analysis.
• (source: Nielsen Book Data)

The book offers a comprehensive introduction to methods for solving multiple criteria decision making and group decision making problems with hesitant fuzzy information. It reports on the authors' latest research, as well as on others' research, providing readers with a complete set of decision making tools, such as hesitant fuzzy TOPSIS, hesitant fuzzy TODIM, hesitant fuzzy LINMAP, hesitant fuzzy QUALIFEX, and the deviation modeling approach with heterogeneous fuzzy information. The main focus is on decision making problems in which the criteria values and/or the weights of criteria are not expressed in crisp numbers but are more suitable to be denoted as hesitant fuzzy elements. The largest part of the book is devoted to new methods recently developed by the authors to solve decision making problems in situations where the available information is vague or hesitant. These methods are presented in detail, together with their application to different type of decision-making problems. All in all, the book represents a valuable reference guide for graduate students and researchers in the both fields of fuzzy logic and decision making. .
(source: Nielsen Book Data)

• Digital inclusion.- Contextualizing ICT based Vocational Education for Rural Communities: Addressing Ethnographic Issues and Assessing Design Principles.- Enhancing Access to eLearning for People with Intellectual Disability: Integrating Usability with Learning.- Identifying support opportunities for foreign students: Disentangling language and non-language problems among a unique population.- PersonaBrowser Status Quo and Lessons learned from a Persona-Based Presentation Metaphor of WCAG.- Women in Crisis Situations: Empowering and Supporting Women through ICTs.- Games.- Effects of Image-Based Rendering and Reconstruction on Game Developers Efficiency, Game Performance, and Gaming Experience.- Exploring In-the-Wild Game-based Gesture Data Collection.- From Objective to Subjective Difficulty Evaluation in Video Games.- Improved Memory Elicitation in Virtual Reality: New Experimental Results and Insights.- Practice in Reality for Virtual Reality Games: Making Players Familiar and Confident with a Game.- Human perception, cognition and behaviour.- I Smell Creativity: Exploring the Effects of Olfactory and Auditory Cues to Support Creative Writing Tasks.- Night Mode, Dark Thoughts: Background Color Influences the Perceived Sentiment of Chat Messages.- Subjective usability, mental workload assessments and their impact on objective human performance.- What is user's perception of Naturalness? An Exploration of Natural User Experience.- Information on demand, on the move, and gesture interaction.- Presenting Information on the Driver's Demand on a Head-Up Display.- Seeing Through the Eyes of Heavy Vehicle Operators.- TrackLine: Refining touch-to-track Interaction for Camera Motion Control on Mobile Devices.- Understanding Gesture Articulations Variability.- Watching Your Back While Riding Your Bike: Designing for Preventive Self-Care During Motorbike Commuting.- Interaction at the workplace.- FeetForward: on Blending New Classroom Technologies into Secondary School Teachers' Routines.- Human-Building Interaction: When the machine becomes a building.- Investigating Wearable Technology for Fatigue Identification in the Workplace.- Leveraging Conversational Systems to assists New Hires during Onboarding.- RemindMe: Plugging a Reminder Manager into Email for Enhancing Workplace Responsiveness.- The Cost of Improved Overview: An analysis of the Use of Electronic Whiteboards in Emergency Departments.- Interaction with children.- An interactive elementary tutoring system for oral health education using an augmented approach.- Empowered and Informed: Participation of Children in HCI.- Gaze Awareness in Agent-Based Early-Childhood Learning Application.- Puffy: a Mobile Inflatable Interactive Companion for Children with Neurodevelopmental Disorder.
• (source: Nielsen Book Data)

The four-volume set LNCS 10513-10516 constitutes the proceedings of the 16th IFIP TC 13 International Conference on Human-Computer Interaction, INTERACT 2017, held in Mumbai, India, in September 2017. The total of 68 papers presented in these books was carefully reviewed and selected from 221 submissions. The contributions are organized in topical sections named: Part I: adaptive design and mobile applications; aging and disabilities; assistive technology for blind users; audience engagement; co-design studies; cultural differences and communication technology; design rationale and camera-control. Part II: digital inclusion; games; human perception, cognition and behavior; information on demand, on the move, and gesture interaction; interaction at the workplace; interaction with children. Part III: mediated communication in health; methods and tools for user interface evaluation; multi-touch interaction; new int eraction techniques; personalization and visualization; persuasive technology and rehabilitation; and pointing and target selection. .
(source: Nielsen Book Data)

• Intro
• Preface
• Organization
• Contents
• Data Mining, Knowledge Discovery and Big Data
• Word Embedding Based Event Detection on Social Media
• 1 Introduction
• 2 Related Work
• 3 Proposed Method
• 3.1 Data Collection
• 3.2 Data Preprocessing
• 3.3 Word Embedding
• 3.4 Clustering Algorithm
• 4 Experiments and Results
• 5 Conclusion
• References
• Sentiment Analysis on TripAdvisor: Are There Inconsistencies in User Reviews?
• 1 Introduction
• 2 Sentiment Analysis
• 2.1 The Sentiment Analysis Problem
• 2.2 Sentiment Analysis Methods (SAMs)
• 3 Methodology

• 3.1 TripAdvisor
• 3.2 Web Scraping
• 3.3 Experimental Setup
• 4 Experiment Results
• 4.1 The Data Sets
• 4.2 Analysis of Results
• 5 Conclusions and Future Work
• References
• Sentiment Classification from Multi-class Imbalanced Twitter Data Using Binarization
• 1 Introduction
• 2 Proposed Classification System
• 2.1 General Overview
• 2.2 Feature Space Reduction with Multiple Correspondence Analysis
• 2.3 Balancing the Skewed Distributions
• 2.4 Weighted Classifier Combination
• 3 Feature Extraction
• 4 Experimental Study
• 4.1 Dataset
• 4.2 Set-Up
• 4.3 Results and Discussion

• 5 Conclusions and Future Works
• References
• An Ontology for Generalized Disease Incidence Detection on Twitter
• Abstract
• 1 Introduction
• 1.1 Related Work
• 2 Materials and Methods
• 2.1 An Ontology for Disease Incidence Detection on Twitter
• 2.2 Feature Extraction
• 3 The Twitter Disease Incidence Detection Pipeline
• 3.1 Corpus Generation
• 3.2 Model Training
• 3.3 Doc2Vec Tuning
• 4 Evaluation
• 4.1 Results and Discussion
• 5 Conclusion and Future Work
• References

• Hybrid Methodology Based on Bayesian Optimization and GA-PARSIMONY for Searching Parsimony Models by Combining Hyperparameter Optimization and Feature Selection
• 1 Introduction
• 2 Materials and Methods
• 2.1 Extreme Gradient Boosting Machines
• 2.2 Bayesian Optimization
• 2.3 GA-PARSIMONY Methodology
• 2.4 Hybrid Method Based on Bayesian Optimization and GA-PARSIMONY
• 3 Experiments
• 3.1 Datasets and Validation Process
• 3.2 GA-PARSIMONY Settings
• 3.3 Bayesian Optimization Settings
• 3.4 Hybrid Method Settings
• 4 Results and Discussion
• 5 Conclusions
• References

• Concept Discovery in Graph Databases
• 1 Introduction
• 2 Background
• 2.1 Concept Discovery
• 2.2 Graph Databases
• 3 The Proposed Method
• 4 Experiments
• 4.1 Datasets and Experimental Setting
• 4.2 Experimental Results
• 5 Conclusion
• References
• Leveraging Distributed Representations of Elements in Triples for Predicate Linking
• 1 Introduction
• 2 Problem Definition
• 3 Related Work
• 4 Approach
• 4.1 Statistical Pattern-Based Candidate Generation
• 4.2 Similarity-Based Candidate Generation
• 4.3 Candidate Selection
• 5 Experiment
• 5.1 Dataset
• 5.2 Setting

This volume constitutes the refereed proceedings of the 12th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2017, held in La Rioja, Spain, in June 2017. The 60 full papers published in this volume were carefully reviewed and selected from 130 submissions. They are organized in the following topical sections: data mining, knowledge discovery and big data; bioinspired models and evolutionary computing; learning algorithms; visual analysis and advanced data processing techniques; data mining applications; and hybrid intelligent applications.
(source: Nielsen Book Data)

• History of SCIA.- Motion analysis and 3D vision.- Pattern detection and recognition.- Machine learning.- Image processing and applications.- Feature extraction and segmentation.- Remote sensing.- Medical and biomedical image analysis.- Faces, gestures and multispectral analysis.
• (source: Nielsen Book Data)

The two-volume set LNCS 10269 and 10270 constitutes the refereed proceedings of the 20th Scandinavian Conference on Image Analysis, SCIA 2017, held in Tromso, Norway, in June 2017. The 87 revised papers presented were carefully reviewed and selected from 133 submissions. The contributions are structured in topical sections on history of SCIA; motion analysis and 3D vision; pattern detection and recognition; machine learning; image processing and applications; feature extraction and segmentation; remote sensing; medical and biomedical image analysis; faces, gestures and multispectral analysis.
(source: Nielsen Book Data)

• History of SCIA.- Motion analysis and 3D vision.- Pattern detection and recognition.- Machine learning.- Image processing and applications.- Feature extraction and segmentation.- Remote sensing.- Medical and biomedical image analysis.- Faces, gestures and multispectral analysis.
• (source: Nielsen Book Data)

The two-volume set LNCS 10269 and 10270 constitutes the refereed proceedings of the 20th Scandinavian Conference on Image Analysis, SCIA 2017, held in Tromso, Norway, in June 2017. The 87 revised papers presented were carefully reviewed and selected from 133 submissions. The contributions are structured in topical sections on history of SCIA; motion analysis and 3D vision; pattern detection and recognition; machine learning; image processing and applications; feature extraction and segmentation; remote sensing; medical and biomedical image analysis; faces, gestures and multispectral analysis.
(source: Nielsen Book Data)

• Intro; Preface; Organization; Contents
• Part I; Contents
• Part II; Video Analysis and Understanding; A Rank Aggregation Framework for Video Interestingness Prediction; 1 Introduction; 2 Related Work; 3 Feature Extraction; 3.1 Histogram of Motion Patterns; 3.2 Mel-Frequency Cepstral Coefficients; 4 Ranking Models; 5 Rank Aggregation Framework; 5.1 Borda Method; 5.2 Reciprocal Rank Fusion; 5.3 Multiplicative Rank Aggregation; 6 Experiments and Results; 7 Conclusions; References; Graph-Based Hierarchical Video Cosegmentation; 1 Introduction; 2 Graph-Based Hierarchical Clustering.

• 3 Proposed Method4 Experiments; 5 Conclusion; References; Interest Region Based Motion Magnification; 1 Introduction; 2 Related Work; 3 Interest Region Based Motion Magnification; 3.1 Object Segmentation; 3.2 Scribble Drawing and Alpha Matting; 3.3 Video Magnification; 3.4 Pipeline; 4 Experiments and Discussion; 5 Conclusion; References; Investigating the Use of Space-Time Primitives to Understand Human Movements; 1 Introduction; 2 Shearlet Theory: An Overview; 3 Building Dictionaries of Space-Time Primitives; 4 Experimental Analysis; 4.1 Dataset and Experimental Protocol.

• 4.2 Preliminary Investigation5 Discussion; References; Organizing Videos Streams for Clustering and Estimation of Popular Scenes; 1 Introduction; 2 Related Works; 3 RECfusion System Overview; 3.1 Intraflow Analysis; 3.2 Interflow Analysis; 3.3 Cluster Tracking; 4 Datasets; 5 Experimental Settings and Results; 6 Conclusion and Future Works; References; 360° Tracking Using a Virtual PTZ Camera; 1 Introduction; 2 Related Works; 2.1 360 Image Representation; 2.2 PTZ Tracking; 3 360 Camera Model; 3.1 Equirectangular Projection; 3.2 Equirectangular to Virtual Camera Plane Projection.

• 4 Tracking Model4.1 Tracking Algorithm; 5 Results; 6 Conclusions; References; Benchmarking Two Algorithms for People Detection from Top-View Depth Cameras; 1 Introduction; 2 Methods Considered for the Benchmarking; 2.1 WATERFILLING; 2.2 HOG-SVM; 3 The Adopted Dataset; 4 Experimental Analysis; 4.1 Performance Indices; 4.2 Training Procedure; 4.3 Analysis of the Experimental Results; 5 Conclusions and Future Work; References; Gesture Modelling and Recognition by Integrating Declarative Models and Pattern Recognition Algorithms; 1 Introduction; 2 Related Work.

• 2.1 Vision-Based Gesture Recognition Approaches2.2 Gesture Recognition: The Declarative Modelling Approach; 3 Combining the Two Approaches with DEICTIC; 4 Experiments and Preliminary Results; 5 Conclusions; References; How Far Can You Get by Combining Change Detection Algorithms?; 1 Introduction; 2 The Proposed Approach; 3 Experimental Setup; 4 Results; 5 Computational Time; 6 Conclusion; References; Robust Tracking of Walking Persons by Elite-Type Particle Filters and RGB-D Images; 1 Introduction; 2 Elite-Type Particle Filter; 2.1 Overall Structure of Tracking Algorithm.

The two-volume set LNCS 10484 and 10485 constitutes the refereed proceedings of the 19th International Conference on Image Analysis and Processing, ICIAP 2017, held in Catania, Italy, in September 2017. The 138 papers presented were carefully reviewed and selected from 229 submissions. The papers cover both classic and the most recent trends in image processing, computer vision, and pattern recognition, addressing both theoretical and applicative aspects. They are organized in the following topical sections: video analysis and understanding; pattern recognition and machine learning; multiview geometry and 3D computer vision; image analysis, detection and recognition; multimedia; biomedical and assistive technology; information forensics and security; imaging for cultural heritage and archaeology; and imaging solutions for improving the quality of life.
(source: Nielsen Book Data)

The two-volume set LNCS 10484 and 10485 constitutes the refereed proceedings of the 19th International Conference on Image Analysis and Processing, ICIAP 2017, held in Catania, Italy, in September 2017. The 138 papers presented were carefully reviewed and selected from 229 submissions. The papers cover both classic and the most recent trends in image processing, computer vision, and pattern recognition, addressing both theoretical and applicative aspects. They are organized in the following topical sections: video analysis and understanding; pattern recognition and machine learning; multiview geometry and 3D computer vision; image analysis, detection and recognition; multimedia; biomedical and assistive technology; information forensics and security; imaging for cultural heritage and archaeology; and imaging solutions for improving the quality of life.
(source: Nielsen Book Data)

• Machine learning in image recognition.- Machine learning for medical image computing.- Image enhancement and reconstruction.- Image segmentation.- Motion and tracking.- 3D computer vision.- Feature extraction.- Detection and classification.- Biomedical image analysis.- Image analysis in ophthalmology.- Remote sensing.- Applications.
• (source: Nielsen Book Data)

This book constitutes the thoroughly refereed proceedings of the 14th International Conference on Image Analysis and Recognition, ICIAR 2017, held in Montreal, QC, Canada, in July 2017. The 73 revised full papers presented were carefully reviewed and selected from 133 submissions. The papers are organized in the following topical sections: machine learning in image recognition; machine learning for medical image computing; image enhancement and reconstruction; image segmentation; motion and tracking; 3D computer vision; feature extraction; detection and classification; biomedical image analysis; image analysis in ophthalmology; remote sensing; applications.
(source: Nielsen Book Data)

• Predicate invention.- Graph-based learning.- Spatial learning.- Logical foundations.- Statistical relational learning.-Probabilistic ILP.- Implementation and scalability.- Applications in robotics, cyber security and games.
• (source: Nielsen Book Data)

This book constitutes the thoroughly refereed post-conference proceedings of the 26th International Conference on Inductive Logic Programming, ILP 2016, held in London, UK, in September 2016. The 10 full papers presented were carefully reviewed and selected from 29 submissions. The papers represent well the current breath of ILP research topics such as predicate invention; graph-based learning; spatial learning; logical foundations; statistical relational learning; probabilistic ILP; implementation and scalability; applications in robotics, cyber security and games.
(source: Nielsen Book Data)

• Scheduling.- Knowledge engineering.- Modeling, simulation and reconfiguration.- Energy systems.- MAS in various areas.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 8th International Conference on Industrial Applications of Holonic and Multi-Agent Systems, HoloMAS 2017, held in Lyon, France, in August 2017. The 19 revised full papers presented were carefully reviewed and selected from 27 submissions. The papers are organized in the following topical sections: scheduling; knowledge engineering; modeling, simulation and reconfiguration; energy systems; and MAS in various areas.
(source: Nielsen Book Data)

• Time Event Extraction to Boost an Information Retrieval System
• Interactive Text Categorisation: The Geometry of Likelihood Spaces
• Mining Movement Data to Extract Personal Points of Interest: A Feature Based Approach
• SABRE: a Sentiment Aspect-Based Retrieval Engine
• Monitoring and Supporting People that Need Assistance: the BackHome Experience
• The Relevance of Providing Useful and Personalized Information to Therapists and Caregivers in Tele*.

This book focuses on new research challenges in intelligent information filtering and retrieval. It collects invited chapters and extended research contributions from DART 2014 (the 8th International Workshop on Information Filtering and Retrieval), held in Pisa (Italy), on December 10, 2014, and co-hosted with the XIII AI*IA Symposium on Artificial Intelligence. The main focus of DART was to discuss and compare suitable novel solutions based on intelligent techniques and applied to real-world contexts. The chapters of this book present a comprehensive review of related works and the current state of the art. The contributions from both practitioners and researchers have been carefully reviewed by experts in the area, who also gave useful suggestions to improve the quality of the book.