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• Introduction Rational Agents Strategic Games Coordination Partial Observability Mechanism Design Learning.
• (source: Nielsen Book Data)

Multiagent systems is an expanding field that blends classical fields like game theory and decentralized control with modern fields like computer science and machine learning. This monograph provides a concise introduction to the subject, covering the theoretical foundations as well as more recent developments in a coherent and readable manner. The text is centered on the concept of an agent as decision maker. Chapter 1 is a short introduction to the field of multiagent systems. Chapter 2 covers the basic theory of singleagent decision making under uncertainty. Chapter 3 is a brief introduction to game theory, explaining classical concepts like Nash equilibrium. Chapter 4 deals with the fundamental problem of coordinating a team of collaborative agents. Chapter 5 studies the problem of multiagent reasoning and decision making under partial observability. Chapter 6 focuses on the design of protocols that are stable against manipulations by self-interested agents. Chapter 7 provides a short introduction to the rapidly expanding field of multiagent reinforcement learning. The material can be used for teaching a half-semester course on multiagent systems covering, roughly, one chapter per lecture.
(source: Nielsen Book Data)

• Frontmatter
• Preface
• Contents
• List of Contributors
• 1. Feature selection in biomedical signal classification process and current software implementations / Jovic, Alan
• 2. An overview of skin lesion segmentation, features engineering, and classification / Sabri, My Abdelouahed / Filali, Youssef / Ennouni, Assia / Yahyaouy, Ali / Aarab, Abdellah
• 3. Brain tumor image segmentation and classification using SVM, CLAHE, and ARKFCM / Ishita, Banerjee / Madhumathy, P. / Kavitha, N.
• 4. Coronary Heart Disease prediction using genetic algorithm based decision tree / Sivaranjani, Reddi / Naresh, Vankamamidi S. / Murthy, Nistala V.E.S.
• 5. Intelligent approach for retinal disease identification / Rajyaguru, Vipul C. / Vithalani, Chandresh H. / Thanki, Rohit M.
• 6. Speech separation for interactive voice systems / Wiem, Belhedi / Anouar, Ben Messaoud Mohamed / Aïcha, Bouzid
• 7. Machine vision for human-machine interaction using hand gesture recognition / Verma, Varnita / Rajput, Anshuman / Chauhan, Piyush / Rathore, Harshit / Goyal, Piyush / Gupta, Mukul Kumar
• Index

Intelligent prediction and decision support systems are based on signal processing, computer vision (CV), machine learning (ML), software engineering (SE), knowledge based systems (KBS), data mining, artificial intelligence (AI) and include several systems developed from the study of expert systems (ES), genetic algorithms (GA), artificial neural networks (ANN) and fuzzy-logic systems The use of automatic decision support systems in design and manufacturing industry, healthcare and commercial software development systems has the following benifits: Cost savings in companies, due to employment of expert system technology. Fast decision making, completion of projects in time and development of new products. Improvement in decision making capability and quality. Usage of Knowledge database and Preservation of expertise of individuals Eases complex decision problems. Ex: Diagnosis in Healthcare To address the issues and challenges related to development, implementation and application of automatic and intelligent prediction and decision support systems in domains such as manufacturing, healthcare and software product design, development and optimization, this book aims to collect and publish wide ranges of quality articles such as original research contributions, methodological reviews, survey papers, case studies and/or reports covering intelligent systems, expert prediction systems, evaluation models, decision support systems and Computer Aided Diagnosis (CAD).
(source: Nielsen Book Data)

• Chapter 1 Memristor Emulators A Note on Modeling.-
• Chapter 2 A Simple Oscillator using Memristor.-
• Chapter 3 A Hyperjerk Memristive System with Hidden Attractors.-
• Chapter 4 A Memristive System with Hidden Attractors and its Engineering Application.-
• Chapter 5 Adaptive Control, Synchronization and Circuit Simulation of a Memristor-Based.-
• Chapter 6 Modern System Design using Memristors.-
• Chapter 7 RF/Microwave Applications of Memristors.-
• Chapter 8 Theory, Modeling and Design of Memristor-Based Min-Max Circuits.-
• Chapter 9 Analysis of a 4-D Hyperchaotic Fractional-Order Memristive System with Hidden Attractors.-
• Chapter 10 Adaptive Control and Synchronization of a Memristor-Based Shinriki's System.
• (source: Nielsen Book Data)

This book reports on the latest advances in and applications of memristors, memristive devices and systems. It gathers 20 contributed chapters by subject experts, including pioneers in the field such as Leon Chua (UC Berkeley, USA) and R.S. Williams (HP Labs, USA), who are specialized in the various topics addressed in this book, and covers broad areas of memristors and memristive devices such as: memristor emulators, oscillators, chaotic and hyperchaotic memristive systems, control of memristive systems, memristor-based min-max circuits, canonic memristors, memristive-based neuromorphic applications, implementation of memristor-based chaotic oscillators, inverse memristors, linear memristor devices, delayed memristive systems, flux-controlled memristive emulators, etc. Throughout the book, special emphasis is given to papers offering practical solutions and design, modeling, and implementation insights to address current research problems in memristors, memristive devices and systems. As such, it offers a valuable reference book on memristors and memristive devices for graduate students and researchers with a basic knowledge of electrical and control systems engineering.
(source: Nielsen Book Data)

• Multi-Message Broadcast in Dynamic Radio Networks.- Global Synchronization and Consensus Using Beeps in a Fault-Prone MAC 16.- Vertex Coloring with Communication and Local Memory Constraints in Synchronous Broadcast Networks.- A New Kind of Selectors, and Their Applications to Conflict Resolution in Wireless Multi-channels Networks.- The Impact of the Gabriel Sub-graph of the Visibility Graph on the Gathering of Mobile Autonomous Robots.- Search-and-Fetch with One Robot on a Disk.- A 2-Approximation Algorithm for Barrier Coverage by Weighted Non-uniform Sensors on a Line.- Flexible Cell Selection in Cellular Networks.- The Euclidean k-Supplier Problem in IR2.
• (source: Nielsen Book Data)

This book constitutes revised selected papers from the 12th International Symposium on Algorithms and Experiments for Wireless Sensor Networks, ALGOSENSORS 2016, held in Aarhus, Denmark, in August 2016. The 9 full papers presented in this volume were carefully reviewed and selected from 19 submissions. This year papers were solicited into three tracks: Distributed and Mobile, Experiments and Applications, and Wireless and Geometry.
(source: Nielsen Book Data)

• Discrete geometry and topology.- Tilings and patterns.- Grammars, models and other technical tools for image analysis.- Image segmentation.- Classification.- Reconstruction.- Compression.- Texture analysis.-Bioimaging.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 18th International Workshop on Combinatorial Image Analysis, IWCIA 2017, held in Plovdiv, Bulgaria, in June 2017. The 27 revised full papers presented were carefully reviewed and selected from 47 submissions. The workshop is organized in topical sections of theoretical foundations and theory of applications, namely: discrete geometry and topology; tilings and patterns; grammars, models and other technical tools for image analysis; image segmentation, classification; reconstruction; compression; texture analysis; bioimaging.
(source: Nielsen Book Data)

• Algorithms.- Biometrics and pattern recognition applications.- Data analysis and information retrieval.-Engineering of enterprise software products.- Industrial management and other applications.- Modelling and optimization.- Various aspects of computer security.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 16th IFIP TC8 International Conference on Computer Information Systems and Industrial Management, CISIM 2017, held in Bialystok, Poland, in June 2017. The 60 regular papers presented together with 5 keynotes were carefully reviewed and Selected from 85 submissions. They are organized in the following topical sections: algorithms; biometrics and pattern recognition applications; data analysis and information retrieval; engineering of enterprise software products; industrial management and other applications; modelling and optimization; various aspects of computer security.
(source: Nielsen Book Data)

• Segmentation and Classification.- Segmentation and Semantic Segmentation.- Dictionary Learning, Retrieval, and Clustering.- Deep Learning.- People Tracking and Action Recognition.- People and Actions.- Faces.- Computational Photography.- Face and Gestures.- Image Alignment.- Computational Photography and Image Processing.- Language and Video.- 3D Computer Vision.- Image Attributes, Language, and Recognition.- Video Understanding.- 3D Vision.
• (source: Nielsen Book Data)

The five-volume set LNCS 10111-10115 constitutes the thoroughly refereed post-conference proceedings of the 13th Asian Conference on Computer Vision, ACCV 2016, held in Taipei, Taiwan, in November 2016. The total of 143 contributions presented in these volumes was carefully reviewed and selected from 479 submissions. The papers are organized in topical sections on Segmentation and Classification; Segmentation and Semantic Segmentation; Dictionary Learning, Retrieval, and Clustering; Deep Learning; People Tracking and Action Recognition; People and Actions; Faces; Computational Photography; Face and Gestures; Image Alignment; Computational Photography and Image Processing; Language and Video; 3D Computer Vision; Image Attributes, Language, and Recognition; Video Understanding; and 3D Vision.
(source: Nielsen Book Data)

• Segmentation and Classification.- Segmentation and Semantic Segmentation.- Dictionary Learning, Retrieval, and Clustering.- Deep Learning.- People Tracking and Action Recognition.- People and Actions.- Faces.- Computational Photography.- Face and Gestures.- Image Alignment.- Computational Photography and Image Processing.- Language and Video.- 3D Computer Vision.- Image Attributes, Language, and Recognition.- Video Understanding.- 3D Vision.
• (source: Nielsen Book Data)

The five-volume set LNCS 10111-10115 constitutes the thoroughly refereed post-conference proceedings of the 13th Asian Conference on Computer Vision, ACCV 2016, held in Taipei, Taiwan, in November 2016. The total of 143 contributions presented in these volumes was carefully reviewed and selected from 479 submissions. The papers are organized in topical sections on Segmentation and Classification; Segmentation and Semantic Segmentation; Dictionary Learning, Retrieval, and Clustering; Deep Learning; People Tracking and Action Recognition; People and Actions; Faces; Computational Photography; Face and Gestures; Image Alignment; Computational Photography and Image Processing; Language and Video; 3D Computer Vision; Image Attributes, Language, and Recognition; Video Understanding; and 3D Vision.
(source: Nielsen Book Data)

• Segmentation and Classification.- Segmentation and Semantic Segmentation.- Dictionary Learning, Retrieval, and Clustering.- Deep Learning.- People Tracking and Action Recognition.- People and Actions.- Faces.- Computational Photography.- Face and Gestures.- Image Alignment.- Computational Photography and Image Processing.- Language and Video.- 3D Computer Vision.- Image Attributes, Language, and Recognition.- Video Understanding.- 3D Vision.
• (source: Nielsen Book Data)

The five-volume set LNCS 10111-10115 constitutes the thoroughly refereed post-conference proceedings of the 13th Asian Conference on Computer Vision, ACCV 2016, held in Taipei, Taiwan, in November 2016. The total of 143 contributions presented in these volumes was carefully reviewed and selected from 479 submissions. The papers are organized in topical sections on Segmentation and Classification; Segmentation and Semantic Segmentation; Dictionary Learning, Retrieval, and Clustering; Deep Learning; People Tracking and Action Recognition; People and Actions; Faces; Computational Photography; Face and Gestures; Image Alignment; Computational Photography and Image Processing; Language and Video; 3D Computer Vision; Image Attributes, Language, and Recognition; Video Understanding; and 3D Vision.
(source: Nielsen Book Data)

• Segmentation and Classification.- Segmentation and Semantic Segmentation.- Dictionary Learning, Retrieval, and Clustering.- Deep Learning.- People Tracking and Action Recognition.- People and Actions.- Faces.- Computational Photography.- Face and Gestures.- Image Alignment.- Computational Photography and Image Processing.- Language and Video.- 3D Computer Vision.- Image Attributes, Language, and Recognition.- Video Understanding.- 3D Vision.
• (source: Nielsen Book Data)

The five-volume set LNCS 10111-10115 constitutes the thoroughly refereed post-conference proceedings of the 13th Asian Conference on Computer Vision, ACCV 2016, held in Taipei, Taiwan, in November 2016. The total of 143 contributions presented in these volumes was carefully reviewed and selected from 479 submissions. The papers are organized in topical sections on Segmentation and Classification; Segmentation and Semantic Segmentation; Dictionary Learning, Retrieval, and Clustering; Deep Learning; People Tracking and Action Recognition; People and Actions; Faces; Computational Photography; Face and Gestures; Image Alignment; Computational Photography and Image Processing; Language and Video; 3D Computer Vision; Image Attributes, Language, and Recognition; Video Understanding; and 3D Vision.
(source: Nielsen Book Data)

• New Trends in Image Restoration and Enhancement (NTIRE).- Workshop on Assistive Vision.- Hyperspectral Image and Signal Processing.- Computer Vision Technologies for Smart Vehicle.- Spontaneous Facial Behavior Analysis.- 3D Modelling and Applications.
• (source: Nielsen Book Data)

The three-volume set, consisting of LNCS 10116, 10117, and 10118, contains carefully reviewed and selected papers presented at 17 workshops held in conjunction with the 13th Asian Conference on Computer Vision, ACCV 2016, in Taipei, Taiwan in November 2016. The 134 full papers presented were selected from 223 submissions. LNCS 10116 contains the papers selected .
(source: Nielsen Book Data)

• New Trends in Image Restoration and Enhancement (NTIRE).- Workshop on Assistive Vision.- Hyperspectral Image and Signal Processing.- Computer Vision Technologies for Smart Vehicle.- Spontaneous Facial Behavior Analysis.- 3D Modelling and Applications.
• (source: Nielsen Book Data)

The three-volume set, consisting of LNCS 10116, 10117, and 10118, contains carefully reviewed and selected papers presented at 17 workshops held in conjunction with the 13th Asian Conference on Computer Vision, ACCV 2016, in Taipei, Taiwan in November 2016. The 134 full papers presented were selected from 223 submissions. LNCS 10116 contains the papers selected .
(source: Nielsen Book Data)

• New Trends in Image Restoration and Enhancement (NTIRE).- Workshop on Assistive Vision.- Hyperspectral Image and Signal Processing.- Computer Vision Technologies for Smart Vehicle.- Spontaneous Facial Behavior Analysis.- 3D Modelling and Applications.
• (source: Nielsen Book Data)

The three-volume set, consisting of LNCS 10116, 10117, and 10118, contains carefully reviewed and selected papers presented at 17 workshops held in conjunction with the 13th Asian Conference on Computer Vision, ACCV 2016, in Taipei, Taiwan in November 2016. The 134 full papers presented were selected from 223 submissions. LNCS 10116 contains the papers selected .
(source: Nielsen Book Data)

• 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.
• (source: Nielsen Book Data)

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)

• Next generation community engagement.- Online policy, politics and co-creation.- Understanding and empowering digital citizens.- Data-driven research and design.- Social media and online interaction.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 4th International Conference on Internet Science held in Thessaloniki, Greece, in November 2017. The 34 papers presented were carefully reviewed and selected for inclusion in this volume. They were organized in topical sections named: next generation community engagement; online policy, politics and co-creation; understanding and empowering digital citizens; data-driven research and design; social media and online interaction.
(source: Nielsen Book Data)

• Algebraic Theory, Max-Plus and Max-Min Mathematics.- Discrete Geometry and Discrete Topology.- Watershed and Graph-based Segmentation.- Trees and Hierarchies.- Topological and Graph-based Clustering, Classification and Filtering.- Connected Operators and Attribute Filters.- PDE-based Morphology.- Scale-Space Representations and Nonlinear Decompositions.- Computational Morphology.- Object Detection.- Biomedical, Material Science and Physical Applications.
• (source: Nielsen Book Data)

This book contains the refereed proceedings of the 13th International Symposium on Mathematical Morphology, ISMM 2017, held in Fontainebleau, France, in May 2017. The 36 revised full papers presented together with 4 short papers were carefully reviewed and selected from 53 submissions. The papers are organized in topical sections on algebraic theory, max-plus and max-min mathematics; discrete geometry and discrete topology; watershed and graph-based segmentation; trees and hierarchies; topological and graph-based clustering, classification and filtering; connected operators and attribute filters; PDE-based morphology; scale-space representations and nonlinear decompositions; computational morphology; object detection; and biomedical, material science and physical applications.
(source: Nielsen Book Data)

• OnTheMove 2017 Keynotes.- International Conference on Cooperative Information Systems (CoopIS) 2017.- Cloud and Trusted Computing (C&TC) 2017.- International Conference on Ontologies, DataBases, and Applications of Semantics (ODBASE) 2017.
• (source: Nielsen Book Data)

This double volumes LNCS 10573-10574 constitutes the refereed proceedings of the Confederated International Conferences: Cooperative Information Systems, CoopIS 2017, Ontologies, Databases, and Applications of Semantics, ODBASE 2017, and Cloud and Trusted Computing, C&TC, held as part of OTM 2017 in October 2017 in Rhodes, Greece. The 61 full papers presented together with 19 short papers were carefully reviewed and selected from 180 submissions. The OTM program every year covers data and Web semantics, distributed objects, Web services, databases, information systems, enterprise workflow and collaboration, ubiquity, interoperability, mobility, grid and high-performance computing.
(source: Nielsen Book Data)

• OnTheMove 2017 Keynotes.- International Conference on Cooperative Information Systems (CoopIS) 2017.- Cloud and Trusted Computing (C&TC) 2017.- International Conference on Ontologies, DataBases, and Applications of Semantics (ODBASE) 2017.
• (source: Nielsen Book Data)

This double volumes LNCS 10573-10574 constitutes the refereed proceedings of the Confederated International Conferences: Cooperative Information Systems, CoopIS 2017, Ontologies, Databases, and Applications of Semantics, ODBASE 2017, and Cloud and Trusted Computing, C&TC, held as part of OTM 2017 in October 2017 in Rhodes, Greece. The 61 full papers presented together with 19 short papers were carefully reviewed and selected from 180 submissions. The OTM program every year covers data and Web semantics, distributed objects, Web services, databases, information systems, enterprise workflow and collaboration, ubiquity, interoperability, mobility, grid and high-performance computing.
(source: Nielsen Book Data)

• Pattern recognition and artificial intelligence techniques.- Image processing and analysis.- Robotics and remote sensing.- Natural language processing and recognition.- Applications of pattern recognition.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 9th Mexican Conference on Pattern Recognition, MCPR 2017, held in Huatulco, Mexico, in June 2017. The 29 revised full papers presented were carefully reviewed and selected from 55 submissions. The papers are organized in topical sections on pattern recognition and artificial intelligence techniques, image processing and analysis, robotics and remote sensing, natural language processing and recognition, applications of pattern recognition.
(source: Nielsen Book Data)

• Pattern Recognition and Machine Learning.- Computer Vision.- Image and Signal Processing.- Medical Image.-Applications.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 8th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2017, held in Faro, Portugal, in June 2017. The 60 regular papers presented in this volume were carefully reviewed and selected from 86 submissions. They are organized in topical sections named: Pattern Recognition and Machine Learning; Computer Vision; Image and Signal Processing; Medical Image; and Applications.
(source: Nielsen Book Data)

• Pattern recognition algorithms.- Reproducible research frameworks.- Reproducible research results.- Previous works on reproducible research.
• (source: Nielsen Book Data)

This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Reproducible Research in Pattern Recognition, RRPR 2016, held in Cancun, Mexico, in December 2016. The 12 revised full papers, among them 2 invited talks, presented were carefully reviewed and selected from 16 submissions. They focus on pattern recognition algorithms; reproducible research frameworks; reproducible research results, previous works on reproducible research.
(source: Nielsen Book Data)

• Aerial Vehicles progress On Pico Air Vehicles.- Perception and Mapping.- Planning.- Systems and Integration.- Control.
• (source: Nielsen Book Data)

This volume presents a collection of papers presented at the 15th International Symposium of Robotic Research (ISRR). ISRR is the biennial meeting of the International Foundation of Robotic Research (IFRR) and its 15th edition took place in Flagstaff, Arizona on December 9 to December 12, 2011. As for the previous symposia, ISRR 2011 followed up on the successful concept of a mixture of invited contributions and open submissions. Therefore approximately half of the 37 contributions were invited contributions from outstanding researchers selected by the IFRR officers and the program committee, and the other half were chosen among the open submissions after peer review. This selection process resulted in a truly excellent technical program which featured some of the very best of robotic research. The program was organized around oral presentation in a single-track format and included for the first time a small number of interactive presentations. The symposium contributions contained in this volume report on a variety of new robotics research results covering a broad spectrum including perception, manipulation, grasping, vehicles and design, navigation, control and integration, estimation and SLAM. .
(source: Nielsen Book Data)

• Swarm and multi-robotic systems.- Human-robot interaction.- Robotic learning and imitation.- Robot navigation, planning and safety.- Humanoid and bio-inspired robots.- Mobile robots and vehicles.- Robot testing and design.- Detection and recognition.- Learning and adaptive behaviours.- Interaction.- Soft and reconfigurable robots.- Service and industrial robots.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 18th Annual Conference on Towards Autonomous Robotics, TAROS 2017, held in Guildford, UK, in July 2017. The 43 revised full papers presented together with 13 short papers were carefully reviewed and selected from 66 submissions. The papers discuss robotics research drawn from a wide and diverse range of topics, such as swarm and multi-robotic systems; human-robot interaction; robotic learning and imitation; robot navigation, planning and safety; humanoid and bio-inspired robots; mobile robots and vehicles; robot testing and design; detection and recognition; learning and adaptive behaviours; interaction; soft and reconfigurable robots; and service and industrial robots.
(source: Nielsen Book Data)

• Intro
• Preface
• Organization
• Contents
• Mammographic Mass Segmentation Using Fuzzy C-means and Decision Trees
• 1 Introduction
• 2 Segmentation of Masses in Mammograms Using Fuzzy C-means and Decision Trees
• 2.1 Fuzzy C-means Based on Gray Levels Histogram
• 2.2 Reduction of False Positive ROIs
• 2.3 Feature Extraction
• 2.4 Binary Decision Tree
• 3 Experimentation
• 3.1 Results and Discussion
• 4 Conclusions
• References
• Refining the Pose: Training and Use of Deep Recurrent Autoencoders for Improving Human Pose Estimation
• 1 Introduction

• 2 Deep Architecture for 3D Human Pose Refinement
• 2.1 Denoising Recurrent Autoencoder
• 2.2 Convolutional Network for Pose Prediction
• 2.3 Pose Refinement Training
• 2.4 Cost Function
• 3 Experiments
• 3.1 Evaluation on HumanEva-I
• 3.2 Evaluation on Human 3.6 Million
• 3.3 Ablation Experiments
• 3.4 Conclusions
• References
• How Can Deep Neural Networks Be Generated Efficiently for Devices with Limited Resources?
• 1 Introduction
• 2 Background
• 3 Parameter Pruning
• 4 Quantization
• 5 Low-Rank Factorization
• 6 Compact Network Design
• 7 Neural Model Deployment

• 7.1 Compact Network Design
• 7.2 Training and Pruning
• 7.3 Quantize Model
• 7.4 Inference Optimization
• 8 Conclusion
• References
• Controlling a Smartphone with Brain-Computer Interfaces: A Preliminary Study
• 1 Introduction
• 2 Subjects and Methods
• 2.1 Acquisition
• 2.2 Processing
• 2.3 Application
• 2.4 Evaluation Procedure
• 3 Results
• 4 Discussion
• 5 Conclusion
• References
• Capturing Industrial Machinery into Virtual Reality
• 1 Introduction
• 2 Related Work
• 3 System Design
• 3.1 Initialisation
• 3.2 Capturing Images
• 3.3 Calibration
• 3.4 Visualisation

• 4 Results
• 5 Conclusion
• References
• Leishmaniasis Parasite Segmentation and Classification Using Deep Learning
• 1 Introduction
• 2 Data
• 3 Method
• 4 Results
• 5 Conclusions
• References
• Robust Pedestrian Detection for Semi-automatic Construction of a Crowded Person Re-Identification Dataset
• 1 Introduction
• 2 The JNU Dataset
• 3 Automatic Pedestrian Detection
• 4 Automatic Data Association
• 5 Evaluation
• 6 Conclusion
• References
• Shape and Appearance Based Sequenced Convnets to Detect Real-Time Face Attributes on Mobile Devices
• 1 Introduction
• 2 Related Work

• 3 Datasets and Data Preparation
• 3.1 FER-2013 and FER+ Datasets
• 3.2 Data Preprocessing
• 4 Proposed CNN Architecture
• 4.1 Sequenced CNN Models
• 4.2 Face Heatmap Image Construction
• 4.3 CNN Models
• 4.4 Learning with a Shape Heatmap Image
• 5 Results and Applications
• 5.1 Effects of Data Preparation and Alignment
• 5.2 Combining Face Shape and Appearance with VGG
• 5.3 Combining Face Shape and Appearance with Mobilenet
• 5.4 Implementation
• 6 Conclusions
• References
• Image Colorization Using Generative Adversarial Networks
• 1 Introduction

This book constitutes the refereed proceedings of the 10th International Conference on Articulated Motion and Deformable Objects, AMDO 2018, held in Palma de Mallorca, Spain, in July 2018. The 12 papers presented were carefully reviewed and selected from 26 submissions. The papers address the following topics: advanced computer graphics and immersive videogames; human modeling and animation; human motion analysis and tracking; 3D human reconstruction and recognition; multimodal user interaction and applications; ubiquitous and social computing; design tools; input technology; programming user interfaces; 3D medical deformable models and visualization; deep learning methods for computer vision and graphics; and multibiometric.
(source: Nielsen Book Data)

• Intro
• Preface
• Organization
• Contents
• Invited Papers
• What's Wrong with Computer Vision?
• 1 Introduction
• 2 Top Ten Questions a Theory on Vision Should Address
• 3 Hierarchical Description of Visual Tasks
• 3.1 Pixel-Wise and Abstract Visual Interpretations
• 3.2 The Interwound Story of Vision and Language
• 3.3 When Vision Collapses to Classification
• 4 Conclusions
• References
• Deep Learning in the Wild
• 1 Introduction
• 2 Face Matching
• 3 Print Media Monitoring
• 4 Visual Quality Control
• 5 Music Scanning
• 6 Game Playing
• 7 Automated Machine Learning

• 8 Conclusions
• References
• Learning Algorithms and Architectures
• Effect of Equality Constraints to Unconstrained Large Margin Distribution Machines
• 1 Introduction
• 2 Least Squares Support Vector Machines
• 3 Large Margin Distribution Machines and Their Variants
• 3.1 Large Margin Distribution Machines
• 3.2 Least Squares Large Margin Distribution Machines
• 3.3 Unconstrained Large Margin Distribution Machines
• 4 Performance Evaluation
• 4.1 Conditions for Experiment
• 4.2 Results for Two-Class Problems
• 5 Conclusions
• References
• DLL: A Fast Deep Neural Network Library

• 1 Introduction
• 2 DLL: Deep Learning Library
• 2.1 Performance
• 2.2 Example
• 3 Experimental Evaluation
• 4 MNIST
• 4.1 Fully-Connected Neural Network
• 4.2 Convolutional Neural Network
• 5 CIFAR-10
• 6 ImageNet
• 7 Conclusion and Future Work
• References
• Selecting Features from Foreign Classes
• 1 Introduction
• 2 Methods
• 2.1 Learning from Context Classes
• 2.2 Foreign Class Combinations
• 3 Experiments
• 3.1 Datasets
• 4 Results
• 5 Discussion and Conclusion
• References
• A Refinement Algorithm for Deep Learning via Error-Driven Propagation of Target Outputs

• 1 Introduction
• 2 Error-Driven Target Propagation: Formalization of the Algorithms
• 2.1 The Inversion Net
• 2.2 Refinement of Deep Learning via Target Propagation
• 3 Experiments
• 4 Conclusions
• References
• Combining Deep Learning and Symbolic Processing for Extracting Knowledge from Raw Text
• 1 Introduction
• 2 Model
• 2.1 Semantic Features
• 2.2 Logic Constraints
• 2.3 Segmentation
• 3 Experiments
• 4 Conclusions
• References
• SeNA-CNN: Overcoming Catastrophic Forgetting in Convolutional Neural Networks by Selective Network Augmentation
• 1 Introduction
• 2 Related Work

• 3 Proposed Method
• 4 Experiments
• 4.1 Network Architecture
• 4.2 Training Methodology
• 4.3 Isolated Learning
• 4.4 Adding New Tasks to the Models
• 4.5 Three Tasks Scenario
• 5 Conclusion
• References
• Classification Uncertainty of Deep Neural Networks Based on Gradient Information
• 1 Introduction
• 2 Entropy, Softmax Baseline and Gradient Metrics
• 3 Meta Classification
• A Benchmark Between Maximum Softmax Probability and Gradient Metrics
• 4 Recognition of Unlearned Concepts
• 5 Meta Classification with Known Unknowns
• 6 Conclusion and Outlook
• References

This book constitutes the refereed proceedings of the 8th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2018, held in Siena, Italy, in September 2018. The 29 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 35 submissions. The papers present and discuss the latest research in all areas of neural network- and machine learning-based pattern recognition. They are organized in two sections: learning algorithms and architectures, and applications. Chapter "Bounded Rational Decision-Making with Adaptive Neural Network Priors" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
(source: Nielsen Book Data)

• Cyber Physical Systems Security.-Risk Management for CPS Security.-Wireless Sensor Network Security for Cyber Physical Systems.-WSN Security mechanisms for CPS.- ICS/SCADA System Security for CPS.-Embedded Systems Security for Cyber Physical Systems.-Distributed Control Systems Security for CPS.-Standards for CPS.
• (source: Nielsen Book Data)

This book is a pioneering yet primary general reference resource on cyber physical systems and their security concerns. Providing a fundamental theoretical background, and a clear and comprehensive overview of security issues in the domain of cyber physical systems, it is useful for students in the fields of information technology, computer science, or computer engineering where this topic is a substantial emerging area of study. .
(source: Nielsen Book Data)

• The DARPA Robotics Challenge Finals: Results and Perspectives.- Robot System of DRC-HUBO+ and Control Strategy of Team KAIST in DARPA Robotics Challenge Finals.- Team IHMC's Lessons Learned from the DARPA Robotics Challenge: Finding Data in the Rubble.- Developing a Robust Disaster Response Robot: CHIMP and the Robotics Challenge.- DRC Team NimbRo Rescue: Perception and Control for Centaur-like Mobile Manipulation Robot Momaro.- Team RoboSimian: Semi-autonomous Mobile Manipulation at the 2015 DARPA Robotics Challenge Finals.- Director: A User Interface Designed for Robot Operation with Shared Autonomy.- Achieving Reliable Humanoid Robot Operations in the DARPA Robotics Challenge: Team WPI-CMU's Approach.- Team DRC-Hubo@UNLV in 2015 DARPA Robotics Challenge Finals.- Team SNU's Control Strategies to Enhancing Robot's Capability: Lessons from the DARPA Robotics Challenge Finals 2015.- Team THOR's Entry in the DARPA Robotics Challenge Finals 2015.- Collaborative Autonomy Between High-level Behaviors and Human Operators for Control of Complex Tasks with Different Humanoid Robots.- WALK-MAN Humanoid Platform.- An Architecture for Human-Guided Autonomy: Team TROOPER at the DARPA Robotics Challenge Finals.- Team VALOR's ESCHER: A Novel Electromechanical Biped for the DARPA Robotics Challenge.- Perspectives on Human-Robot Team Performance from an Evaluation of the DARPA Robotics Challenge.- What Happened at the DARPA Robotics Challenge Finals.
• (source: Nielsen Book Data)

The DARPA Robotics Challenge was a robotics competition that took place in Pomona, California USA in June 2015. The competition was the culmination of 33 months of demanding work by 23 teams and required humanoid robots to perform challenging locomotion and manipulation tasks in a mock disaster site. The challenge was conceived as a response to the Japanese Fukushima nuclear disaster of March 2011. The Fukushima disaster was seen as an ideal candidate for robotic intervention since the risk of exposure to radiation prevented human responders from accessing the site. This volume, edited by Matthew Spenko, Stephen Buerger, and Karl Iagnemma, includes commentary by the organizers, overall analysis of the results, and documentation of the technical efforts of 15 competing teams. The book provides an important record of the successes and failures involved in the DARPA Robotics Challenge and provides guidance for future needs to be addressed by policy makers, funding agencies, and the robotics research community. Many of the papers in this volume were initially published in a series of special issues of the Journal of Field Robotics. We have proudly collected versions of those papers in this STAR volume. .
(source: Nielsen Book Data)

• Clustering and Quantum Methods.- Motion and Tracking.- Image Processing and Segmentation.- Color, Shading and Reflectance of Light.- Propagation and Time-evolution.- Inference, Labeling, and Relaxation.
• (source: Nielsen Book Data)

This volume constitutes the refereed proceedings of the 11th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2017, held in Venice, Italy, in October/November 2017. The 37 revised full papers were carefully reviewed and selected from 51 submissions. The papers are organized in topical sections on Clustering and Quantum Methods; Motion and Tracking; Image Processing and Segmentation; Color, Shading and Reflectance of Light; Propagation and Time-evolution; and Inference, Labeling, and Relaxation.
(source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 15th International Conference on Simulation of Adaptive Behavior, SAB 2018, held in Frankfurt/Main, Germany, in August 2018.The 21 papers presented were carefully reviewed and selected from 39 submissions. They cover the main areas in animat research, including the animat approach and methodology, perception and motor control, action selection and navigation, learning and adaptation, and collective and social behavior.
(source: Nielsen Book Data)

• Multi-agent Systems and Distributed Control.- Human-Machine Interaction.- Rehabilitation Robotics.- Industrial Robot and Robot Manufacturing.- Sensors and Actuators.- Robot Grasping and Control.- Mobile Robotics and Path Planning.- Robotic Vision, Recognition and Reconstruction.- Robot Intelligence and Learning.
• (source: Nielsen Book Data)

The two volume set LNAI 10984 and LNAI 10985 constitutes the refereed proceedings of the 11th International Conference on Intelligent Robotics and Applications, ICIRA 2018, held in Newcastle, NSW, Australia, in August 2018. The 81 papers presented in the two volumes were carefully reviewed and selected from 129 submissions. The papers in the first volume of the set are organized in topical sections on multi-agent systems and distributed control; human-machine interaction; rehabilitation robotics; sensors and actuators; and industrial robot and robot manufacturing. The papers in the second volume of the set are organized in topical sections on robot grasping and control; mobile robotics and path planning; robotic vision, recognition and reconstruction; and robot intelligence and learning.
(source: Nielsen Book Data)

This book constitutes the proceedings of the 11th International Conference on Internet and Distributed Computing Systems, IDCS 2018, held in Tokyo, Japan, in October 2018. The 21 full papers presented together with 5 poster and 2 short papers in this volume were carefully reviewed and selected from 40 submissions. This conference desired to look for inspiration in diverse areas (e.g., infrastructure and system design, software development, big data, control theory, artificial intelligence, IoT, self-adaptation, emerging models, paradigms, applications and technologies related to Internet-based distributed systems) to develop new ways to design and mange such complex and adaptive computation resources. .
(source: Nielsen Book Data)

• Risks on the Internet: Detecting Harmful Content and Discussing Regulation.- Methodologies for Studies of Online Audiences.- Online Media and Public Issues.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 5th International Conference on Internet Science held in St. Petersburg, Russia, in October 2018. The 23 papers presented were carefully reviewed and selected for inclusion in this volume. They were organized in topical sections named: risks on the Internet: detecting harmful content and discussing regulation; methodologies for studies of online audiences; and online media and public issues.
(source: Nielsen Book Data)

• Awareness Platform.- Aalto Observatory on Digital Valuation Systems.- A Novel Lexicon-Based Approach in Determining Sentiment in Financial Data Using Learning Automata.- A Hybrid Recommendation System Based on Density-Based Clustering.- Computing Platform for Virtual Economic Activities Index.- Data Based Stock Portfolio Construction Using Computational Intelligence.- YourDataStories: Transparency and Corruption Fighting Through Data Interlinking and Visual Exploration.- The Maker Movement and the Disruption of the Producer-Consumer Relation.- Open Data: Creating Communities and Practices for a New Common.- The Case for Collaborative Policy Experimentation Using Advanced Geospatial Data Analytics and Visualisation.- An Engagement-Related Behaviour Change Approach for SavingFood in Greece.- Developing a Social Innovation Methodology in the Web 2.0 Era.- Code Hunting Games: a Mixed Reality Multiplayer Treasure Hunt Through a Conversational Interface.- Politician - an Imitation Game.- Towards Open Domain Chatbots - a GRU Architecture for Data Driven Conversations.- Creating Dialogues Using Argumentation and Social Practices.- An Overview of Open-Source Chatbots Social Skills.
• (source: Nielsen Book Data)

This book constitutes the refereed post-conference proceedings of 4 workshops, held at the 4th International Conference on Internet Science, Thessaloniki, Greece, in November 2017: the Second International Workshop on the Internet for Financial Collective Awareness and Intelligence, IFIN 2017, the International Workshop on Data Economy 2017, the International Workshop on Digital Technology to Support Social Innovation, DSI 2017, and the International Workshop on Chatbot Research and Design, CONVERSATIONS 2017. The 17 full papers presented together with one short paper were carefully reviewed and selected from 27 submissions. The contributions of the IFIN workshop focus on a multidisciplinary dialogue on how to use the internet to promote financial awareness and capability among citizens whereas the papers of the Data Economy workshop show how online data change economy and business. The aim of the DSI workshop was to collect the lessons learned from different platforms and settings, and to understand the requirements and challenges for building and using digital platforms to effectively engage broad participation in the social innovation process. The papers of the Conversations workshop explore the brave new world of human-computer communication through natural language, gathering latest developments in chatbots research and design.
(source: Nielsen Book Data)

• Structured Tensor Decompositions and Applications.- Matrix and Tensor Factorizations.- ICA Methods.- Nonlinear Mixtures.- Audio Data and Methods.- Signal Separation Evaluation Campaign.- Deep Learning and Data-driven Methods.- Advances in Phase Retrieval and Applications.- Sparsity-Related Methods.- Biomedical Data and Methods.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 14th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2018, held in Guildford, UK, in July 2018.The 52 full papers were carefully reviewed and selected from 62 initial submissions. As research topics the papers encompass a wide range of general mixtures of latent variables models but also theories and tools drawn from a great variety of disciplines such as structured tensor decompositions and applications; matrix and tensor factorizations; ICA methods; nonlinear mixtures; audio data and methods; signal separation evaluation campaign; deep learning and data-driven methods; advances in phase retrieval and applications; sparsity-related methods; and biomedical data and methods.
(source: Nielsen Book Data)

• Full Papers.- Time-Based Maintenance Models under Uncertainty.- Markov Automata on Discount.- Markov Analysis for Optimum Caching as an Alternative to Belady's Algorithm.- Intrusion Detection for Sequence-based Attacks with Reduced Traffic Models.- Hidden Storage in Data Centers: Gaining Flexibility Through Cooling Systems.- Performance Benchmarking of Network Function Chain Placement Algorithms.- Towards Optimal Placement of Monitoring Units in Time-varying Networks under Centralized Control.- Estimating the Flow Rule Installation Time of SDN Switches when Facing Control Plane Delay.- Dynamic Control of Running Servers.- On the Value of Service Demand Estimation for Auto-Scaling.- Evaluating a Single-Server Queue with Asynchronous Speed Scaling.- Active Queue Management Based on Congestion Policing (CP-AQM).- Deficit Round Robin with Limited Deficit Savings (DRR-LDS) for Fairness among TCP Users.- Modeling the Performance of ARQ Error Control in an LTE Transmission System.- Catching Corner Cases in Network Calculus { Flow Segregation Can Improve Accuracy.- QoE Analysis of the Setup of Different Internet Services for FIFO Server Systems.- Industrial, Practical Experience and PhD Track Papers.- VirtuWind - An SDN- and NFV-based Architecture for Softwarized Industrial Networks.- A Modular Environment to Test SCADA Solutions for Wind Parks.- Evaluation of Single-Hop Beaconing with Congestion Control in IEEE WAVE and ETSI ITS-G5.- Practical QoE Evaluation of Adaptive Video Streaming.- Tool Papers.- A Domain-Specific Language and Toolchain for Performance Evaluation based on Measurements.- SLA Tool.- A Tool for Generating Automata of IEC60870-5-104 Implementations.- A Software Tool for the Compact Solution of the Chemical Master Equation.- Logical PetriNet - A Tool to Model Digital Circuit Petri Nets and Transform them into Digital Circuits.- ClassCast: A Tool for Class-Based Forecasting.- Collider - Parallel Experiments in Silico.- FunSpec4DTMC { A Tool for Modelling Discrete-Time Markov Chains Using Functional Specifications.- Model-based System Design and Evaluation of Image Processing Architectures with SimTAny Framework.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 19th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems, MMB 2018, held in Erlangen, Germany, in February 2018. The 16 full papers, 4 PhD track papers, and 9 tool papers presented in this volume were carefully reviewed and selected from 42 submissions. They are dealing with performance and dependability evaluation techniques for computer and communication systems and its related fields. .
(source: Nielsen Book Data)

• Motivation.- Closing the Loop: Placing Ontology Usage Analysis in the Ontology Development and Deployment Lifecycle.- Ontology Usage Analysis Framework (OUSAF).- Identification Phase : Ontology Usage Network Analysis Framework (OUN-AF).- Investigation Phase: Empirical Analysis of Domain Ontology Usage (EMP-AF).
• (source: Nielsen Book Data)

This unique book succinctly summarizes the need to measure how ontologies (one of the building blocks of the Semantic Web) are currently being utilized, providing insights for various stakeholders. Where possible it improves and reuses terms in existing vocabularies/ontologies, as recommended by the Linked Data community. Recent advances in the Semantic Web have led to a proliferation of Resource Description Framework (RDF) data, which employ ontologies to semantically describe the information on the Web making it equally understandable for both humans and machines. However, to create a network effect, it is important that selective ontologies are used by more data publishers to improve the value of that ontology. For this to happen, it is vital to discover what is being used from an ontology to semantically annotate the information on the Web specific to a given domain. Answers to such basic but crucial questions can only be achieved by ascertaining how ontologies in the current semantic web are being utilized and adopted. The proposed frameworks to obtain such insights are explained with real-world examples to provide a clear and detailed description of ontology usage analysis. Both theoretical and practical, the book is of value to academics and professionals working in industry. Specifically, it is of primary interest to researchers, graduate students and practitioners in the area of the Semantic Web and its various real-world applications.
(source: Nielsen Book Data)

• Information Systems Applications (incl.
• Internet).- Information Storage and Retrieval.- Software Engineering Artificial Intelligence (incl. Robotics).- Systems and Data Security.- Computer Appl. in Administrative Data
• Processing Ontologies.- Databases.- Semantics.- Cooperative Information Systems.-Cloud Computing.- Trust, Security, Privacy And Risk
• Management.
• (source: Nielsen Book Data)

This double volumes LNCS 11229-11230 constitutes the refereed proceedings of the Confederated International Conferences: Cooperative Information Systems, CoopIS 2018, Ontologies, Databases, and Applications of Semantics, ODBASE 2018, and Cloud and Trusted Computing, C&TC, held as part of OTM 2018 in October 2018 in Valletta, Malta. The 64 full papers presented together with 22 short papers were carefully reviewed and selected from 173 submissions. The OTM program every year covers data and Web semantics, distributed objects, Web services, databases, informationsystems, enterprise workflow and collaboration, ubiquity, interoperability, mobility, grid and high-performance computing.
(source: Nielsen Book Data)

• Pattern Recognition Principles.- Patterns of Go gaming by Ising model.- A Novel Criterion to Obtain the Best Feature Subset from Filter Ranking Methods.- Class-specific Reducts vs. Classic Reducts in a Rule-based Classifier: A Case Study.- On the Construction of a Specific Algebra for Composing Tonal Counterpoint.- The Impact of Basic Matrix Dimension on the Performance of Algorithms for Computing Typical Testors.- Fast Convex Hull by a Geometric Approach.- An Experimental Study on Ant Colony Optimization Hyper-heuristics for Solving the Knapsack Problem.- A Linear Time Algorithm for Computing #2SAT for Outerplanar 2-CNF Formulas.- Improving the List of Clustered Permutation on Metric Spaces for Similarity Searching on Secondary Memory.- Modelling 3-Coloring of Polygonal Trees via Incremental Satisfiability.- Deep Learning, Neural Networks and Associative Memories.- Performance Analysis of Deep Neural Networks for Classification of Gene-Expression Microarrays.- Extreme Points of Convex Polytopes Derived from Lattice Autoassociative Memories.- A Comparison of Deep Neural Network Algorithms for Recognition of EEG Motor Imagery Signals.- Learning Word and Sentence Embeddings using a Generative Convolutional Network.- Dense Captioning of Natural Scenes in Spanish.- Automated Detection of Hummingbirds in Images: a Deep Learning Approach.- Data Mining.- Patterns in Poor Learning Engagement in Students While They are Solving Mathematics Exercises in an Affective Tutoring System Related to Frustration.- Pattern Discovery in Mixed Data Bases.- Image Clustering based on Frequent Approximate Subgraph Mining.- Validation of Semantic Relation of Synonymy in Domain Ontologies using Lexico-Syntactic Patterns and Acronyms.- Computer Vision.- Scene Text Segmentation Based on Local Image Phase Information and MSER Method.- A Lightweight Library for Augmented Reality Applications.- Point Set Matching with Order Type.- Including Foreground and Background Information in Maya Hieroglyph Representation.- A Fast Algorithm for Robot Localization using Multiple Sensing Units.- Improving Breast Mass Classification through Kernel Methods and the Fusion of Clinical Data and Image Descriptors.- An Improved Stroke Width Transform to Detect Race Bib Numbers.- Scaled CCR Histogram for Scale-invariant Texture Classification.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 10th Mexican Conference on Pattern Recognition, MCPR 2018, held in Puebla, Mexico, in June 2018. The 28 papers presented in this volume were carefully reviewed and selected from 44 submissions. They were organized in topical sections named: pattern recognition principles; deep learning, neural networks and associative memories; data mining; and computer vision. .
(source: Nielsen Book Data)

• Biometrics.- Computer Vision Application.- Deep Learning.- Document Analysis.- Face Recognition and Analysis.- Feature Extraction and Selection.- Machine Learning.- Object Detection and Tracking.- Performance Evaluation and Database.- Remote Sensing.
• (source: Nielsen Book Data)

The four-volume set LNCS 11056, 110257, 11258, and 11073 constitutes the refereed proceedings of the First Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2018, held in Guangzhou, China, in November 2018. The 179 revised full papers presented were carefully reviewed and selected from 399 submissions. The papers have been organized in the following topical sections: Part I: Biometrics, Computer Vision Application. Part II: Deep Learning. Part III: Document Analysis, Face Recognition and Analysis, Feature Extraction and Selection, Machine Learning. Part IV: Object Detection and Tracking, Performance Evaluation and Database, Remote Sensing.
(source: Nielsen Book Data)

• Biometrics.- Computer Vision Application.- Deep Learning.- Document Analysis.- Face Recognition and Analysis.- Feature Extraction and Selection.- Machine Learning.- Object Detection and Tracking.- Performance Evaluation and Database.- Remote Sensing.
• (source: Nielsen Book Data)

The four-volume set LNCS 11056, 110257, 11258, and 11073 constitutes the refereed proceedings of the First Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2018, held in Guangzhou, China, in November 2018. The 179 revised full papers presented were carefully reviewed and selected from 399 submissions. The papers have been organized in the following topical sections: Part I: Biometrics, Computer Vision Application. Part II: Deep Learning. Part III: Document Analysis, Face Recognition and Analysis, Feature Extraction and Selection, Machine Learning. Part IV: Object Detection and Tracking, Performance Evaluation and Database, Remote Sensing.
(source: Nielsen Book Data)

• Biometrics.- Computer Vision Application.- Deep Learning.- Document Analysis.- Face Recognition and Analysis.- Feature Extraction and Selection.- Machine Learning.- Object Detection and Tracking.- Performance Evaluation and Database.- Remote Sensing.
• (source: Nielsen Book Data)

The four-volume set LNCS 11056, 110257, 11258, and 11073 constitutes the refereed proceedings of the First Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2018, held in Guangzhou, China, in November 2018. The 179 revised full papers presented were carefully reviewed and selected from 399 submissions. The papers have been organized in the following topical sections: Part I: Biometrics, Computer Vision Application. Part II: Deep Learning. Part III: Document Analysis, Face Recognition and Analysis, Feature Extraction and Selection, Machine Learning. Part IV: Object Detection and Tracking, Performance Evaluation and Database, Remote Sensing.
(source: Nielsen Book Data)

• Biometrics.- Computer Vision Application.- Deep Learning.- Document Analysis.- Face Recognition and Analysis.- Feature Extraction and Selection.- Machine Learning.- Object Detection and Tracking.- Performance Evaluation and Database.- Remote Sensing.
• (source: Nielsen Book Data)

The four-volume set LNCS 11056, 110257, 11258, and 11073 constitutes the refereed proceedings of the First Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2018, held in Guangzhou, China, in November 2018. The 179 revised full papers presented were carefully reviewed and selected from 399 submissions. The papers have been organized in the following topical sections: Part I: Biometrics, Computer Vision Application. Part II: Deep Learning. Part III: Document Analysis, Face Recognition and Analysis, Feature Extraction and Selection, Machine Learning. Part IV: Object Detection and Tracking, Performance Evaluation and Database, Remote Sensing.
(source: Nielsen Book Data)

• Queueing Models with Retrials.- Queueing Models with Variants of Service.- Queueing Models for Cloud Computing.- Queueing Models for Wireless Communication.- Optimization in Queueing Models.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 13th International Conference on Queueing Theory and Network Applications, QTNA 2018, held in Tsukuba, Japan in July 2018.The 8 full papers together with 10 short papers included in this volume were carefully reviewed and selected from 57 initial submissions. All the papers to be presented disseminate the latest results covering up-to-date research fields such as performance modeling and analysis of telecommunication systems, retrial and vacation queueing models, optimization of queueing systems, modeling of social systems, application of machine learning in queueing models.
(source: Nielsen Book Data)

• Robotics.- Artificial intelligence.- Environment perception.- State estimation.- Pattern recognition.- Sensor fusion.- Action planning.- Control theory.- Robot learning.- Human-robot interaction.- Multi-agent systems.- Simultaneous localization and mapping.- Object manipulation.- Locomotion.- RoboCup.- Robot competition. .
• (source: Nielsen Book Data)

This book includes the post-conference proceedings of the 20th RoboCup International Symposium, held in Leipzig, Germany, in July 2016. In addition to the 38 contributions to the symposium, selected from 63 submissions, the book also contains 15 champion papers of teams winning individual leagues of the RoboCup 2016 competition, the Amazon Picking Challenge, and the Harting Open Source Award. The papers present current research in the fields of robotics and artificial intelligence with a special focus to robot hardware and software, environment perception, action planning and control, robot learning, multi-robot systems, and human-robot interaction.
(source: Nielsen Book Data)

• Part I Global Robot Path Planning
• 1.
• Introduction to Mobile Robot Path Planning
• 2.
• Background on Artificial Intelligence Algorithms for Global Path Planning
• 3.
• Design and Evaluation of Intelligent Global Path Planning Algorithms 4.
• Integration of Global Path Planners in ROS
• 5.
• Robot Path Planning using Cloud Computing for Large Grid Maps
• Part II Multi-Robot Task Allocation
• 6.
• General Background on Multi-Robot Task Allocation
• 7.
• Different Approaches to Solve the MRTA Problem
• 8.
• Performance Analysis of the MRTA Approaches for Autonomous Mobile Robot .
• (source: Nielsen Book Data)

This book presents extensive research on two main problems in robotics: the path planning problem and the multi-robot task allocation problem. It is the first book to provide a comprehensive solution for using these techniques in large-scale environments containing randomly scattered obstacles. The research conducted resulted in tangible results both in theory and in practice. For path planning, new algorithms for large-scale problems are devised and implemented and integrated into the Robot Operating System (ROS). The book also discusses the parallelism advantage of cloud computing techniques to solve the path planning problem, and, for multi-robot task allocation, it addresses the task assignment problem and the multiple traveling salesman problem for mobile robots applications. In addition, four new algorithms have been devised to investigate the cooperation issues with extensive simulations and comparative performance evaluation. The algorithms are implemented and simulated in MATLAB and Webots.
(source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 15th International Semantic Web Conference, ESWC 2018, held in Heraklion, Crete, Greece. The 48 revised full papers presented were carefully reviewed and selected from 179 submissions. The papers cover a large range of topics such as logical modelling and reasoning, natural language processing, databases and data storage and access, machine learning, distributed systems, information retrieval and data mining, social networks, and Web science and Web engineering. .
(source: Nielsen Book Data)

• Poster and Demo Papers.- Finding Unexplainable Triples in an RDF Graph.- ATU-DSS: Knowledge-Driven Data Integration and Reasoning for Sustainable Subsurface Inter-Asset Management.- Deep Learning and Sentiment Analysis for Human-Robot Interaction.- Pseudo-Random ALC Syntax Generation.- A Protege Plugin for Annotating OWL Ontologies with OPLa.- An Editor that Uses a Block Metaphor for Representing Semantic Mappings in Linked Data.- A Diagrammatic Approach for Visual Question Answering Over Knowledge Graphs.- Simplified SPARQL REST API - CRUD on JSON Object Graphs via URI Paths.- Hate Speech Detection on Twitter: Feature Engineering v.s. Feature Selection.- Incremental Data Partitioning of RDF Data in SPARK.- Developing an Ontology for Curriculum & Syllabus.- Computer-assisted Ontology Construction System: Focus on Bootstrapping Capabilities.- Matching Offerings and Queries on an Internet of Things Marketplace.- Exploiting Equivalence to Infer Type Subsumption in Linked Graphs.- Speleothem - An Information System for Caves Based on Semantic Web Technologies.- M-CREAM: A Tool for Creative Modeling of Emergency Scenarios in Smart Cities.- Context Spaces as the Cornerstone of a Near-Transparent & Self-Reorganizing Semantic Desktop.- SeGoFlow: A Semantic Governance Workflow Tool.- Image User Profiling with Knowledge Graph and Computer Vision.- reboting.com: Towards geo-search and visualization of Austrian Open Data.- Demoing Platypus - a Multilingual Question Answering Platform for Wikidata.- Knowledge Graph Embeddings with node2vec for Item Recommendation.- REDI: A Linked Data-powered Research Networking Platform.- Combining P-Plan and the REPRODUCE-ME Ontology to Achieve Semantic Enrichment of Scientific Experiments using Interactive Notebooks.- A Scalable Consent, Transparency and Compliance Architecture.- Enabling Conversational Tourism Assistants through Schema.org Mapping.- A Workflow for generation of LDP.- Supporting sustainable publishing and consuming of live Linked Time Series Streams.- TagTheWeb: Using Wikipedia Categories to Automatically Classify Resources on the Web.- ViziQuer: a Web-based Tool for Visual Diagrammatic Queries over RDF Data.- EventKG+TL: Creating Cross-Lingual Timelines from an Event-Centric Knowledge Graph.- ABSTAT 1
• .0: Compute, Manage and Share Semantic Profiles of RDF Knowledge Graphs.- Entity Linking in 40 Languages using MAG.- Ulysses: an Intelligent client for replicated Triple Pattern Fragments.- Bridging Web APIs and Linked Data with SPARQL Micro-Services.- Grasping Metaphors: Lexical Semantics in Metaphor Analysis.- The Unified Code for Units of Measure in RDF: cdt:ucum and other UCUM Datatypes.- Deep Linking Desktop Resources.- VocRec: An Automated Vocabulary Recommender Tool.- Declarative Rules for Linked Data Generation at your Fingertips.- Modeling and Reasoning over Data Licenses.- PhD Symposium Track.- Recommending spatial classes for entity interlinking in the Web of Data.- Ontology ABox Comparison.- Modeling and Querying Versioned Source Code in RDF.- Linkflows: enabling a web of linked semantic publishing workflows.- Adaptive anomaly detection and root cause analysis by fusing semantics and machine learning.- Question Answering over Knowledge Bases.- Semantic Query Federation for Scalable Security Log Analysis.- Assessing the Quality of owl:sameAs Links.- SHARK: A Test-driven Framework for Design and Evolution of Ontologies.- 3rd Workshop on Geospatial Linked Data.- Using Linked Open Geo Boundaries for Adaptive Delineation of Functional Urban Areas.- 4th Workshop on Sentic Computing, Sentiment Analysis, Opinion Mining, and Emotion Detection.- A Study of the Similarities of Entity Embeddings Learned from Different Aspects of a Knowledge Base for Item Recommendations.- 2nd Workshop on Querying the Web of Data.- MAS: A Corpus of Tweets for Marketing in Spanish.- 4th Workshop on Social Media World Sensors.- Benchmarking Commercial RDF Stores with Publications Office Dataset.- 1st Workshop on Semantic Web of Things for Industry 4.0.- Such a wonderful Place: extracting sense of place from Twitter.- 3rd Workshop on Semantic Web for Cultural Heritage.- IoT Semantic Interoperability With Device Description Shapes.- Exploring Linked Data For The Automatic Enrichment of Historical Archives.- 4th Workshop on Managing the Evolution and Preservation of the Data Web.- nlGis: A Use Case in Linked Historic Geodata.- 2nd Semantic Web solutions for large-scale biomedical data analytics.- Distributed RDF archives Querying with Spark.- 1st Workshop on Deep Learning for Knowledge Graphs and Semantic Technologies.- Assessing FAIR Data Principles against the 5-Star Open Data Principles.- Translational Models for Item Recommendation.
• (source: Nielsen Book Data)

This book constitutes the thoroughly refereed post-conference proceedings of the Satellite Events of the 15th Extended Semantic Web Conference, ESWC 2018, held in Heraklion, Crete, Greece, in June 2018.The volume contains 41 poster and demonstration papers, 11 invited workshop papers, and 9 full papers, selected out of a total of 70 submissions. They deal with all areas of semantic web research, semantic technologies on the Web and Linked Data. .
(source: Nielsen Book Data)

• Online Learning of Human Navigational Intentions.- Autonomous Assistance Control based on Inattention of the Driver when Driving a Truck Tract.- The Robotic Archetype: Character Animation and Social Robotics.- A proposed Wizard of OZ architecture for a Human-Robot Collaborative drawing task.- Factors and Development of Cognitive and Affective Trust on Social Robots.- Smiles of Children with ASD May Facilitate Helping Behaviors to the Robot.- If drones could see: investigating evaluations of a drone with eyes.- Validation of the Design of a Robot to Study the Thermo-Emotional Expression.- Training Autistic Children on Joint Attention Skills with a Robot.- Robotic Understanding of Scene Contents and Spatial Constraints.- Social Robots and Wearable Sensors for Mitigating Meltdowns in Autism - A Pilot Test.- Autonomous Control through the Level of Fatigue Applied to the Control of Autonomous Vehicles.- Dialogue Models for Socially Intelligent Robots.- Composable Multimodal Dialogues based on Communicative Acts.- How Should a Robot Interrupt a Conversation between Multiple Humans.- Grasping novel objects with real-time obstacle avoidance.- Augmenting Robot Knowledge Consultants with Distributed Short Term Memory.- 3D Virtual Path Planning for People with Amyotrophic Lateral Sclerosis through Standing Wheelchair.- Physiological differences depending on task performed in a 5-day interaction scenario designed for the elderly: a pilot study.- Character Design and Validation on Aerial Robotic Platforms Using Laban Movement Analysis.- Social Robots in Public Spaces: A Meta-Review.- On the Design of a Full-actuated Robot Hand with Target Sensing Self-adaption and Slider Crank Mechanism.- Towards Dialogue-based Navigation with Multivariate Adaptation driven by Intention and Politeness for Social Robots.- Design and Implementation of Shoulder Exoskeleton Robot.- Cooperative Control of Sliding Mode for Multi-Mobile Manipulators.- When Should a Robot Apologize? Understanding how Timing Affects Human-Robot Trust Repair.- "Let There be Intelligence!"- A Novel Cognitive Architecture for Teaching Assistant Social Robots.- Virtual Social Toys: A Novel Concept to Bring Inanimate Dolls to Life
• Modular Robotic System for Nuclear Decommissioning.- A new model to enhance robot-patient communication: Applying insights from the medical world
• Towards Crossmodal Learning for SmoothMultimodal Attention Orientation.- A Two-step Framework for Novelty Detection in Activities of Daily Living.- Design of Robotic System for the Mannequin-Based Disinfection Training.- Learning to Win Games in a Few Examples: Using Game-Theory and Demonstrations to Learn the Win Conditions of a Connect Four Game.- Semantics Comprehension of Entities in Dictionary Corpora for Robot Scene Understanding.- The CPS-triangle: a suggested framework for evaluating robots in relation to everyday life.- Feature-based Monocular Dynamic 3D Object Reconstruction.- Adaptive Control of Human-interacted Mobile Robots with Velocity Constraint.- Attributing human-likeness to an avatar: the role of time and space in the perception of biological motion.- Dancing Droids: An Expressive Layer for Mobile Robots Developed Within Choreographic Practice.- Semantic-based interaction for teaching robot behavior compositions using spoken language.- Comfortable Passing Distances for Robots.- Reduced Sense of Agency in Human-Robot interaction.- Comparing the Effects of Social Robots and Virtual Agents on Exercising Motivation.- The Relevance of Social Cues in Assistive Training with a Social Robot.- Attitudes of Heads of Education and Directors of Research towards the Need for Social Robotics Education in Universities
• Coordinated and Cooperative Control of Heterogeneous Mobile Manipulators.- Robotic Healthcare Service System to Serve Multiple Patients with Multiple Robots.- Perception of Control in Artificial and Human Systems: A Study of Embodied Performance Interactions.- A Robotic Brush with Surface Tracing Motion Applied to the Face.- MagicHand: In-Hand Perception of Object Characteristics for Dexterous Manipulation.- Robots and Human Touch in Care: Desirable and Non-Desirable Robot Assistance.- The Effects of Gaze Following Behaviours of Driving Agents on Human-Autonomous Car Interaction.- Virtual Reality Social Robot Platform: A Case Study on Arash Social Robot.- Novel Siamese Robot Platform for Multi-Human Robot Interaction.- An Attention-aware Model for Human Action Recognition on Tree-based Skeleton Sequences.- Predicting the Target in Human-Robot Manipulation Tasks.- Imitating Human Movement Using a Measure of Verticality to Animate Low Degree-of-Freedom Non-humanoid Virtual Characters.- Adaptive Neural Control for Robotic Manipulators Under Constrained Task Space.- Multi-pose face registration method for social robot.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 10th International Conference on Social Robotics, ICSR 2018, held in Qingdao, China, in November 2018.The 60 full papers presented were carefully reviewed and selected from 79 submissions. The theme of the 2018 conference is: Social Robotics and AI. In addition to the technical sessions, ICSR 2018 included 2 workshops:Smart Sensing Systems: Towards Safe Navigation and Social Human-Robot Interaction of Service Robots.
(source: Nielsen Book Data)

• Learning Affordances for Assistive Robots.- Initial Design, Implementation and Technical Evaluation of a Context-aware Proxemics Planner for a Social Robot.- An Image based Non-verbal Behaviour analysis of HRI.- Do Social Rewards from Robots Enhance Offline Improvements in Motor Skills?.- How the Timing and Magnitude of Robot Errors Influence Peoples' Trust of Robots in an Emergency Scenarios.- The Iterative Development of the Humanoid Robot Kaspar: An Assistive Robot for Children with Autism.- The Interaction Between Voice and Appearance in the Embodiment of a Robot Tutor.- Shape It - The Influence of Robot Body Shape on Gender Perception in Robots.- A Telepresence Robot in Residential Care: Family Increasingly Present, Personnel Worried about Privacy.- Influence of Robot's Interaction Style on Performance in a Stroop Task.- `Autistic Robots' for Embodied Emulation of Behaviors Typically Seen in Children with Different Autism Severities.- Learning Relationships between Objects and Places by Multimodal Spatial Concept with Bag of Objects.- There once was a Robot Storyteller: Measuring the Effects of Emotion and non-verbal Behaviour.- Field testing of the influence of assistive wear on the physical fitness of nursing-care workers.- Developing Interaction Scenarios with a Humanoid Robot to Encourage Visual Perspective Taking Skills in Children with Autism - Preliminary Proof of Concept Tests.- Human-like Hand Reaching by Motion Prediction using Long Short-Term Memory.- User's Personality and Activity Influence on HRI Comfortable Distances.- A Need for Service Robots among Health Care Professionals in Hospitals and Housing Services.- Do you think I approve of that? Designing facial expressions for a robot.- Robotic Device to Mediate Human-Human Hug-Driven Remote Communication.- RoMa: A Hi-tech Robotic Mannequin for the Fashion Industry.- Walk the talk: Gestures in mobile interaction.- Gaze Behavioral Adaptation towards Group Members for Providing Effective Recommendations.- Subtle Reaction and Response Time Effects in Human-Robot Touch Interaction.- Young EFL learners' attitude towards RALL: an observational study focusing on motivation, anxiety, and interaction.- Design of a Cloud-Based Robotic Platform for Accompanying and Interacting with Humans.- Influence of Environmental Context on Recognition Rates.- Creating lively behaviors in social robots.- What Went Wrong and Why? Diagnosing Situated Interaction Failures in the Wild.- Toward 3D Printed Prosthetic Hands that can Satisfy Psychosocial Needs: Grasping Force Comparisons between a Prosthetic Hand and Human Hands.- Integrating a Humanoid Robot into ECHONET-based Smart Home Environments.- A Robot that Encourages Self-Disclosure by Hug.- Hand Gestures and Verbal Acknowledgments Improve Human-Robot Rapport.- Do Audio-Visual Stimuli Change Hug Impressions?.- Impact of Tutoring Strategies in Grounded Lexicon Learning.- Yes, Of Course? An Investigation on Obedience and Feelings of Shame towards a Robot.- Dance with me! Child-robot interaction in the wild.- Rethinking the Why of Socially Assistive Robotics through Design.- Role-oriented Designing: A Methodology to Designing for Appearance and Interaction Ways of Customized Professional Social Robots
• Exploring Users' Reactions Towards Tangible Implicit Probes for Measuring Human-Robot Engagement.- Gaze-Based Hints During Child - Robot GamePlay.- Gender Difference in Expectation for Domestic Robots: A Survey in Japan.- Motor Actions Predictions and Controls for the NAO Robot when Playing Hand Clapping Games.- The importance of mutual gaze in human-robot interaction.- About Decisions During Human-Robot Shared Plan Achievement: Who Should Act and How?.- Improving User's Performance by Motivation: Matching Robot Interaction Strategy with User's Regulatory State.- Social group motion in robots.- Shopping Mall Robots - Opportunities and Constraints from the Retailer and Manager Perspective.- Dynamic Gesture Recognition for Social Robots.- Embodiment, Privacy and Social Robots: May I remember you?.- A TV Chat Robot with Time-Shifting Function for Daily-Use Communication.- Naturalistic Conversational Gaze Control for Humanoid Robots - A First Step.- Design and Implementation of a Device Management System for Healthcare Assistive Robots: Sensor Manager System Version 2.- Dialogue Design for a Robot-Based Face-Mirroring Game to Engage Autistic Children with Emotional Expressions.- Look but Don't Stare: Mutual Gaze Interaction in Social Robots.- Recognition of Gestural Behaviors Expressed by a Humanoid Robotic Platform for Teaching Affect Recognition to Children with Autism - A Healthy Subjects Pilot Study.- A Visual Environment for Reactive Robot Programming of Macro-level Behaviors.- Hand in Hand with Robots: Differences between Experienced and Naive Users in Human-Robot Handover Scenarios.- Subjective Stress in Hybrid Collaboration.- Development of Control Mechanism for Safety Enhancement in Bilateral Control Robot Applications.- Understanding anthropomorphism: Anthropomorphism is not a reverse process of dehumanization.- An Evaluation Tool of the Effect of Robots in Eldercare on the Sense of Safety and Security.- Becoming Real: An Anthropological Approach to Evaluating Robots in the Real World.- Human Perceptions of the Severity of Domestic Robot Errors.- What Can We Learn from the Long-Term Users of a Social Robot?.- Adaptive Emotional Chatting Behavior to Increase the Sociability of Robots.- Measuring Children's Perceptions of Robots' Social Competence: Design and Validation.- Rule Extraction Method Considering Reliability for Synchronized Behavior of Group Robots in Multi-party Conversations.- Omnidirectional Traveling Instruction for Behavior Navigation.- News Application Adaptation based on User Sensory Profile.- Robot Compliant Behaviour with Mixed-Initiative Interaction in an Obstacle Avoidance Scenario.- "Xylotism": A Tablet-Based Application to Teach Music to Children with Autism.- Starting a Conversation by Multi-Robot Cooperative Behavior.- Adaptive Strategies for Multi-Party Interactions with Robots in Public Spaces.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 9th International Conference on Social Robotics, ICSR 2016, held in Tsukuba, Japan, in November 2017.The 74 revised full papers presented were carefully reviewed and selected from 110 submissions. The theme of the 2017 conference is: Embodied Interactive Robots. In addition to the technical sessions, ICSR 2017 included four workshops: 1) Social Robot Intelligence for Social Human-Robot Interaction of Service Robots; 2) Human Safety and Comfort in Human-Robot Interactive Social Environments; 3) Modes of Interaction for Social Robots (MISR 2017): Postures, Gestures and Microinteractions; and 4) Religion in Robotics.
(source: Nielsen Book Data)

This book constitutes the refereed post-conference proceedings of the 11th International Seminar on Speech Production, ISSP 2017, held in Tianjin, China, In October 2017. The 20 revised full papers included in this volume were carefully reviewed and selected from 68 submissions. They cover a wide range of speech science fields including phonology, phonetics, prosody, mechanics, acoustics, physiology, motor control, neuroscience, computer science and human interaction. The papers are organized in the following topical sections: emotional speech analysis and recognition; articulatory speech synthesis; speech acquisition; phonetics; speech planning and comprehension, and speech disorder.
(source: Nielsen Book Data)

• Object manipulation and locomotion.- Soft and bioinspired robotics.- Path planning and autonomous vehicles.- Robotics vision and teleoperation.- HRI, assistive and medical robotics.- Swarm robotics.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 19th Annual Conference on Towards Autonomous Robotics, TAROS 2018, held in Bristol, UK, in July 2018. The 38 full papers presented together with 14 short papers were carefully reviewed and selected from 68 submissions. The papers focus on presentation and discussion of the latest results and methods in autonomous robotics research and applications. The conference offers a friendly environment for robotics researchers and industry to take stock and plan future progress.
(source: Nielsen Book Data)

• Behavior Analysis.- Human Motion Recognition.- Application Datasets.
• (source: Nielsen Book Data)

This book constitutes the revised selected papers of the Second International Workshop on Understanding Human Activities through 3D Sensors, UHA3DS 2016, that was held in conjunction with the 23rd International Conference on Pattern Recognition, ICPR 2016, held in Cancun, Mexico, in December 2016. The 9 revised full papers were carefully reviewed and selected from 12 submissions. The papers are organized in topical sections on Behavior Analysis, Human Motion Recognition, and Application Datasets.
(source: Nielsen Book Data)

• Modelling of Underwater Robots.- Dynamic Control of 6-DOF AUVs.- Fault Detection/Tolerance Strategies for AUVs and ROVs.- Experiments of Dynamic Control of a 6-DOF AUV.- Kinematic Control of UVMSs.- Dynamic Control of UVMSs.- Interaction Control of UVMSs.- Dynamic Control of 6-DOF AUVs.- Fault Detection/Tolerance Strategies for AUVs and ROVs.- Experiments of Dynamic Control of a 6-DOF AUV.- Kinematic Control of UVMSs.- Dynamic Control of UVMSs.- Interaction Control of UVMSs.
• (source: Nielsen Book Data)

A classic in underwater robotics. One of the first volumes in the "Springer Tracts in Advanced Robotics" series, it has been a bestseller through the previous three editions. Fifteen years after the publication of the first edition, the fourth edition comes to print. The book addresses the main control aspects in underwater manipulation tasks. With respect to the third edition, it has been revised, extended and some concepts better clustered. The mathematical model with significant impact on the control strategy is discussed. The problem of controlling a 6-degrees-of-freedoms autonomous underwater vehicle is investigated and a survey of fault detection/tolerant strategies for unmanned underwater vehicles is provided. Inverse kinematics, dynamic and interaction control for underwater vehicle-manipulator systems are then discussed. The code used to generate most of the numerical simulations is made available and briefly discussed.
(source: Nielsen Book Data)

• Mobile web data analytics.- Big spatial data and urban computing.- Graph data management and analytics.- Mobility analytics from spatial and social data.
• (source: Nielsen Book Data)

This book constitutes the thoroughly refereed post-conference proceedings of the First APWeb-WAIM 2017 Workshops, held jointly with the First International Joint Conference APWeb-WAIM 2017, held in Beijing, China, in July 2017. The 25 full papers presented were carefully reviewed and selected from 40 submissions. The papers originating from six workshops present cutting-edge ideas, results, experiences, techniques, and tools from all aspects of web data management with the focus on mobile web data analytics; big spatial data and urban computing; graph data management and analytics; mobility analytics from spatial and social data.
(source: Nielsen Book Data)

• Theoretical computer science.- Artificial intelligence.- Microeconomics.- Problems at the intersection of computation, game theory and economics. .
• (source: Nielsen Book Data)

This book constitutes the thoroughly refereed proceedings of the 13th International Conference on Web and Internet Economics, WINE 2017, held in Bangalore, India, in December 2017. The 28 full and 6 short papers presented were carefully reviewed and selected from 89 submissions. The papers reflect the work of researchers in theoretical computer science, artificial intelligence, and microeconomics who have joined forces to tackle problems at the intersection of computation, game theory and economics. .
(source: Nielsen Book Data)

• A Study of Energy Reduction Strategies in Renewable Hybrid Grid.- Classification and Watermarking of Brain Tumor using Artificial and Convolutional Neural Networks.- A Proposal for a Deep Learning Model to Enhance Student Guidance and Reduce Dropout.- EduBot: An Unsupervised Domain-Specific Chatbot for Educational Institutions.- SQL Generation from Natural Language using Supervised Learning and Recurrent Neural Networks.- Toward Intelligent Solution to Identify Learner Attitude from Source Code.
• (source: Nielsen Book Data)

This book gathers selected papers from Artificial Intelligence and Industrial Applications (A2IA'2020), the first installment of an annual international conference organized by ENSAM-Meknes at Moulay Ismail University, Morocco. The 29 papers presented here were carefully reviewed and selected from 141 submissions by an international scientific committee. They address various aspects of artificial intelligence such as digital twin, multiagent systems, deep learning, image processing and analysis, control, prediction, modeling, optimization and design, as well as AI applications in industry, health, energy, agriculture, and education. The book is intended for AI experts, offering them a valuable overview and global outlook for the future, and highlights a wealth of innovative ideas and recent, important advances in AI applications, both of a foundational and practical nature. It will also appeal to non-experts who are curious about this timely and important subject.
(source: Nielsen Book Data)

• A Fuzzy Ontology Based Approach To Support Product Eco-Design.-
• A Genetic-based SVM Approach for Quality Data Classification.- Towards a platform to implement an intelligent and predictive maintenance in the context of industry.- Towards a Prediction Analysis in an Industrial Context.- Methodology for Implementation of Industry . Technologies in Supply Chain for SMEs.- A Deep Reinforcement Learning DRL Decision Model For Heating Process Parameters Identification In Automotive Glass Manufacturing
• Analytic Hierarchy Process AHP for supply chain . risks management.- SmartDFRelevance: a Holonic Agent based System for Engineering Industrial Projects in Concurrent Engineering Context.- A Cyber-Physical Warehouse Management System Architecture in an.- Industry . context.- PLM and Smart technologies for product and supply chain design.- Production systems simulation considering Non-Productive Times and Human Factors.- Distributed and Embedded System to Control Traffic Collision Based on Artificial Intelligence.- The Emergence and Decision Support in Complex System with Fuzzy Logic Control.- Markov Decision Processes with Discounted Costs over a Finite Horizon: Action Elimination.- Robust adaptive fuzzy path tracking control of Differential Wheeled Mobile Robot.- Deep Learning approach for Automated Guided Vehicle System.- Path Planning Using Particle Swarm Optimization And Fuzzy Logic
• Prediction of Robot localization states using Hidden Markov Models.- A New Approach for Multi-Agent Reinforcement Learning.- Recommender System for Most Relevant k Pick-Up Points.- Feature Detection and Tracking for Visual Effects: Augmented Reality and Video Stabilization.- Spectral image recognition using artificial dynamic neural network in information resonance mode.- U-Net Based Model for Obfuscated Human Faces Reconstruction.- A Machine Learning Assistant for Choosing Operators and Tuning Their Parameters in Image Processing Tasks.- Convergence and parameters setting of continuous Hopfield neural networks applied to image restoration problem.- The Ibn Battouta Air Traffic Control Corpus with Real Life ADS-B and METAR data.- Weed Recognition System For Low-Land Rice Precision Farming Using Deep Learning Approach.- A Comparative Study Between Mixture and Stepwise Regression to Model The Parameters Of The Composting Process.- Deep Learning Based Sponge Gourd Diseases Recognition For Commercial Cultivation in Bangladesh.- Exploitation of vegetation indices and Random Forest for cartography of rosemary cover: application to Gourrama region, Morocco.
• (source: Nielsen Book Data)

This book gathers the refereed proceedings of the Artificial Intelligence and Industrial Applications (A2IA'2020), the first installment of an annual international conference organized by the ENSAM-Meknes at Moulay Ismail University, Morocco. The 30 papers presented here were carefully reviewed and selected from 141 submissions by an international scientific committee. They address various aspects of artificial intelligence such as smart manufacturing, smart maintenance, smart supply chain management, supervised learning, unsupervised learning, reinforcement learning, graph-based and semi-supervised learning, neural networks, deep learning, planning and optimization, and other AI applications. The book is intended for AI experts, offering them a valuable overview of the status quo and a global outlook for the future, with many new and innovative ideas and recent important developments in AI applications, both of a foundational and practical nature. It will also appeal to non-experts who are curious about this timely and important subject.
(source: Nielsen Book Data)

• Introduction
• Monitoring of Weld Pool Surface with Active Vision
• Visual Sensing of 3D Weld Pool Geometry with Passive Vision Image
• Penetration prediction with machine learning models
• Penetration Control for Bead-on plate welding
• Penetration Detection of narrow U-groove welding
• Lack of fusion detection inside narrow U-groove
• Conclustions and recommendations.

This book describes the application of vision-sensing technologies in welding processes, one of the key technologies in intelligent welding manufacturing. Gas tungsten arc welding (GTAW) is one of the main welding techniques and has a wide range of applications in the manufacturing industry. As such, the book also explores the application of AI technologies, such as vision sensing and machine learning, in GTAW process sensing and feature extraction and monitoring, and presents the state-of-the-art in computer vision, image processing and machine learning to detect welding defects using non-destructive methods in order to improve welding productivity. Featuring the latest research from ORNL (Oak Ridge National Laboratory) using digital image correlation technology, this book will appeal to researchers, scientists and engineers in the field of advanced manufacturing.
(source: Nielsen Book Data)

• Introduction
• Kinematic Geometry of the PnP Robots
• Differential Kinematics of the Robots
• Kinematic Performance Criteria
• Elastostatics and Stiffness
• Rigid Multibody Dynamics
• Robot Elastodynamics
• Design optimization of parallel PnP Robots.

This book discusses the parametric modeling, performance evaluation, design optimization and comparative study of the high-speed, parallel pick-and-place robots. It collects the modeling methodology, evaluation criteria and design guidelines for parallel PnP robots to provide a systematic analysis method for robotic developers. Furthermore, it gathers the research results previously scattered in many prestigious international journals and conference proceedings and methodically edits them and presents them in a unified form. The book is of interest to researchers, R&D engineers and graduate students in industrial parallel robotics who wish to learn the core principles, methods, algorithms, and applications.
(source: Nielsen Book Data)

• Development of an Industry 4.0 demonstrator using Sequence Planner and ROS2.- ROS2 for ROS1 users.- Multi-Robot SLAM framework for ROS with Efficient Information Sharing.- Agile experimentation of robot swarms in large scale.- Lessons learned building a self-driving car on top of ROS.- Landing a UAV on a moving platform using a front facing camera.- Integrating the Functional Mock-up Interface with ROS and Gazebo.- An ARVA sensor simulator.- ROS Implementation for Untethered Microrobot Manipulation.- ClegS: A package to develop C-legged robots.- Video frames selection method for 3D Reconstruction depending on ROS-based monocular SLAM.- ROS Rescue: Fault Tolerance System for ROS.
• (source: Nielsen Book Data)

This book is the fifth volume in the successful book series Robot Operating System: The Complete Reference. The objective of the book is to provide the reader with comprehensive coverage on the Robot Operating System (ROS), which is currently considered to be the primary development framework for robotics applications, and the latest trends and contributing systems. The content is divided into six parts. Pat I presents for the first time the emerging ROS 2.0 framework, while Part II focuses on multi-robot systems, namely on SLAM and Swarm coordination. Part III provides two chapters on autonomous systems, namely self-driving cars and unmanned aerial systems. In turn, Part IV addresses the contributions of simulation frameworks for ROS. In Part V, two chapters explore robotic manipulators and legged robots. Finally, Part VI presents emerging topics in monocular SLAM and a chapter on fault tolerance systems for ROS. Given its scope, the book will offer a valuable companion for ROS users and developers, helping them deepen their knowledge of ROS capabilities and features. .
(source: Nielsen Book Data)

• Intro
• Preface
• Introduction
• Contents
• 1 Safety the Basis for Future Mobility
• 1.1 Safety is Much More Than Safety Engineering
• 1.2 Safety as a Social Right
• 1.3 Legal Basis for "Auto-Mobility"
• 1.3.1 The German Road Traffic Act (StVG)
• 1.3.2 Origin of the German Road Traffic Act
• 1.3.3 Adaptation of the Traffic Right for the Globalisation Trend
• 1.3.4 Activities in Germany for Future Mobility Solutions
• 1.3.5 Genevan and Viennese Convention
• 1.4 European Union (EU) and Legislation
• 1.4.1 EU Directives Related to Road Traffic
• 1.4.2 European Vehicle Class

• 1.4.3 EU Directive for Future Mobility
• 1.5 Licensing Act
• 1.6 US Road Traffic Regulations
• 1.7 UNECE
• 1.8 Legal View on Future Mobility
• 1.8.1 New Licensing Approach for Automated Vehicles
• 1.8.2 ITS Law
• 1.8.3 ETSI-European Telecommunications Standards Institute
• 1.8.4 OECD, Organisation for Economic Co-operation and Development
• 1.8.5 ETSC European Transport Safety Council
• 1.8.6 IT Security Act
• 1.9 Product Liability
• 1.10 Common Law and Civil Law
• 1.11 Legal Regulation in China
• 1.12 Insurance
• 2 Risk Management
• 2.1 Risk Management Cycle

• 2.1.1 Development of the Context
• 2.1.2 Identification of Risk
• 2.1.3 Assessment of the Risk in the Target Context
• 2.1.4 Development of a Strategy and Treatment of Potential Risk
• 2.1.5 Development and Defining of Activities and Their Objectives
• 2.1.6 Development of an Implementation and Realisation Strategy
• 2.1.7 Review and Evaluation of the Plan
• 2.2 Technical Risk
• 2.3 Risk in Road Traffic
• 2.3.1 Causes of Technical Risk
• 2.3.2 Control of Technical Risk
• 2.4 Standardisation of Safety for Road Vehicles
• 2.4.1 Risk and Integrity Definition from the IEC 61508

• 2.4.2 Risk According to ISO 26262
• 2.5 Critical Infrastructure
• 2.5.1 Organisation for Critical Infrastructure
• 2.5.2 Cloud Computing
• 2.5.3 Transport and Traffic and Critical Infrastructure
• 3 Automation in Mobility
• 3.1 Human Driving: a Closed-Loop Control System
• 3.2 Human Driving
• 3.2.1 Driver's HMI
• 3.2.2 Driver in the Loop
• 3.2.3 Human Driving Journey
• 3.3 Human Control Mechanism
• 3.4 Human Behaviour and Context
• 3.4.1 Observer of the Observer
• 3.4.2 Industry Automation
• 3.4.3 Multiple Contexts for Different Layers of Abstraction

• 3.5 Communication and Interfaces
• 3.6 Human Driver as a Control System
• 3.6.1 Human Communication
• 3.6.2 Human Perception
• 3.6.3 Technical Control System Comparison
• 3.6.4 Control System Architecture in Comparison with the Human Control System
• 3.7 Cyclic Data Processing Versus Distributed Event-Driven Data Processing
• 3.7.1 Distributed Control
• 3.7.2 Configuration of Human Control System
• 3.8 Cybernetics and Control
• 3.8.1 Digital Twin
• 3.8.2 Cybernetics About Behaviour and Control
• 3.8.3 Cybernetics and Sufficiently Perceiving the Environment

The book provides background information about technical solutions, processes and methodology to develop future automated mobility solutions. Beginning from the legal requirements as the minimum tolerable risk level of the society, the book provides state-of-the-art risk-management methodologies. The system engineering approach based on todays engineering best practices enhanced by principles derived from cybernetics. The approach derived from the typical behaviour of a human driver in public road traffic to a cybernetical based system engineering approach. Beyond the system engineering approach, a common behaviour model for the operational domain will show aspects how to extend the system engineering model with principles of cybernetics. The role and the human factors of road traffic participants and drivers of motor vehicles are identified and several viewpoints for different observers show how such mixed traffic scenarios could be assessed and optimised. The influence of the changing mobility demands of the society and the resulting changes to the origination of producer, owner, driver and supplier show aspects for future liability and risk share option for new supply chains. Examples from various industries provide some well-proven engineering principles how to adapt those for the future mobility for the benefit of the users. The aim of the book is to raise awareness that the safety provided by a product, a means of transport or a system up to an entire traffic system depends on the capabilities of the various actors. In addition to the driver and passengers, there are also other road users, maintenance personnel and service providers, who must have certain abilities to act safely in traffic. These are also the capabilities of the organisation, not only the organisation that develops or brings the product to market, but also the organisation that is responsible for the operation and the whole lifecycle of the products. The book is for people who want to get invo lved in the mobility of the future. People, that have ideas to become a player who want to help shape the future mobility of society and who want to bring responsible solutions for users into the market.

• Quality Aspects in Machine Learning, AI and Data Analytics.- Evidence-Based Software Quality Engineering.- Human and Artificial Intelligences for Software Evolution.- Process Modeling, Improvement and Assessment.- Software Quality Education and Training.- Quality Aspects in Quantum Computing.- Safety, Security and Privacy.- ICT Verification and Validation.- RE, MDD and Agile.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 13th International Conference on the Quality of Information and Communications Technology, QUATIC 2020, held in Faro, Portugal*, in September 2020. The 27 full papers and 12 short papers were carefully reviewed and selected from 81 submissions. The papers are organized in topical sections: quality aspects in machine learning, AI and data analytics; evidence-based software quality engineering; human and artificial intelligences for software evolution; process modeling, improvement and assessment; software quality education and training; quality aspects in quantum computing; safety, security and privacy; ICT verification and validation; RE, MDD and agile. *The conference was held virtually due to the COVID-19 pandemic.
(source: Nielsen Book Data)

• 1. A Comprehensive Introduction to Photometric 3D-Reconstruction.-
• 2. Perspective Shape from Shading an Exposition on Recent Works with New Experiments.-
• 3. RGBD-Fusion: Depth Refinement for Diffuse and Specular Objects.-
• 4. Non-Rigid Structure from Motion and Shading.-
• 5. On the Well-Posedness of Uncalibrated Photometric Stereo Under General Lighting.-
• 6. Recent Progress in Shape from Polarization.-
• 7. Estimating Facial Aging using Light Scattering Photometry.
• (source: Nielsen Book Data)

This book presents the latest advances in photometric 3D reconstruction. It provides the reader with an overview of the state of the art in the field, and of the latest research into both the theoretical foundations of photometric 3D reconstruction and its practical application in several fields (including security, medicine, cultural heritage and archiving, and engineering). These techniques play a crucial role within such emerging technologies as 3D printing, since they permit the direct conversion of an image into a solid object. The book covers both theoretical analysis and real-world applications, highlighting the importance of deepening interdisciplinary skills, and as such will be of interest to both academic researchers and practitioners from the computer vision and mathematical 3D modeling communities, as well as engineers involved in 3D printing. No prior background is required beyond a general knowledge of classical computer vision models, numerical methods for optimization, and partial differential equations. .
(source: Nielsen Book Data)

• World Wide Web.- Recommendation.- Query Processing and Algorithm.- Natural Language Processing.- Machine Learning.- Graph Query.- Edge Computing and Data Mining.- Data Privacy and Security.- Blockchain.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 17th International Conference on Web Information Systems and Applications, WISA 2020, held in Guangzhou, China, in September 2020. The 42 full papers and 16 short papers presented were carefully reviewed and selected from 165 submissions. The papers are grouped in topical sections on world wide web, recommendation, query processing and algorithm, natural language processing, machine learning, graph query, edge computing and data mining, data privacy and security, and blockchain.
(source: Nielsen Book Data)

• Advanced Modelling, Simulation and Data Analytics in Production and Supply Networks.- A Robust Multi-Commodity Rebalancing Process in Humanitarian Logistics.- Towards a unified reliability-centered information logistics model for production assets.- Characterization of energy consumers in production systems with renewable on-site power generation.- A simulation model supporting the production optimization for high-precision machines assembly.- Agent-Based Modeling and Analysis of Dynamic Slab Yard Management in a Steel Factory.- A Simulation Analysis of Part Feeding to Assembly Stations with Vertical Robotic Storage and Retrieval.- Process Mining in Manufacturing: Goals, Techniques and Applications.- Bayesian Modelling for Product Testing and Release.- Advanced, Digital and Smart Manufacturing.- The Use of Organizational Innovation Concepts in Manufacturing Companies.- Systems Engineering Approach to Identify Requirements for Digital Twins Development.- Manufacturing Operations Management for Smart Manufacturing - A Case Study.- Industry 4.0 on demand: a value driven methodology to implement Industry 4.0.- Gamification of Operational Tasks in Manufacturing - A Literature Review.- Technology Adoption in the Industry 4.0 Era: Empirical Evidence from Manufacturing Companies.- Towards the definition of an Impact Level factor of SME features over Digital Transformation.- Industry 4
• .0: maturity of automotive companies in Brazil for the digitization of processes.- General readiness assessment of Industry 4
• .0: Evidence from Serbian manufacturing industry.- Digital and Virtual Quality Management Systems.- Assembly issue resolution system using machine learning in aero engine manufacturing.- Introduction to Material Feeding 4
• .0: strategic, tactical, and operational impact.- Cloud-Manufacturing.- Cycle Time Estimation Model for Hybrid Assembly Stations based on Digital Twin Concept.- Cyber-Physical Production Systems and Digital Twins.- Digital Shadows as an enabler for the internet of production.- The transformation towards smart(er) factories: integration requirements of the digital twin.- IIOT Interoperability.- Towards inter-operable enterprise systems - graph-based validation of a context-driven approach for message profiling.- Supply Chain Planning and Optimization.- Software-based Assistance System for Decision Support on Supply Chain Level.- Integration of triple sustainable management by considering multi-period supply chain for next-generation fuel.- Potential benefits of Reverse Blending in the fertilizer industry.- Effectiveness of Vendor Managed Inventory [VMI] in Explosive Inventory Management.- Value chain integration - a framework for assessment.- A dynamic hybrid Berth Allocation Problem with routing constraints in bulk ports.- Blockchain-based secured collaborative model for supply chain resource sharing and visibility.- Gripper types and components in robotic bin picking.- A stochastic model for a two-level disassembly lot-sizing problem under random lead time.- Digital and Smart Supply Chain Management.- ERP in Industry 4.0 Context.- Identifying the opportunities for enhancing the digital readiness level of the supply chain.- Intelligent Logistics Networks Management.- The Role of Last-Mile Delivery in the Future of E-commerce.- Production-storage and transport integratedplanning for a multi-site mining industry.- Artificial Intelligence and Blockchain Technologies in Logistics and DSN.- Evaluating a Blockchain-based supply chain purchasing process through simulation.- Questionnaire model for paraconsistent quality assessment of software developed in Sales Force.- Novel Production Planning & Control Approaches.- Supporting the Decision of the Order Processing Strategy by using Logistic Models: A Case Study.- Order acceptance and scheduling with a throughput diagram.- Machine Learning and Artificial Intelligence.- Machine Learning-Supported Planning of Lead Times in Job Shop Manufacturing.- Connected, Smart Factories of the Future.- Identifying Key Business Processes that Can Benefit from Industry 4.0 in the Gas Sector, The Public Gas Distribution Networks Case in Greece.- The impact of Industry 4.0 connectivity on the collaboration along Brazilian automotive supply chain.- Manufacturing Systems Engineering: Agile, Flexible, Reconfigurable.- Towards a reference model for configuration of reconfigurable manufacturing system (RMS).- Automatic Design of Dispatching Rules with Genetic Programming for Dynamic Job Shop Scheduling.- A Literature review on the Level of Automation and new approach proposal.- De-risking investments in industrial systems using Real Options Analysis: Case of chemical industry.- Data-driven Replenishment Method Choice in a Picking System.- Business Process Management for Manufacturing Execution System deployment: some lessons from a bearings manufacturer experience.- An Application of a DSML in Industry 4.0 Production Processes.- Towards an Industry-Applicable Design Methodology for Developing Reconfigurable Manufacturing.- Reconfigurable Manufacturing: Lesson Learnt from the COVID-19 Outbreak.- Digital Assistance Systems: Augmented Reality and Virtual Reality.- Virtual and Augmented reality as a digital support to HR systems in production management.- Application of Virtual Reality Technologies for Achieving Energy Efficient Manufacturing: Literature Analysis and Findings.- Smart Products in Smart Manufacturing Systems: An Opportunity to Utilize AR?.- Evaluation of Augmented Reality in Industry.- Circular Products Design and Engineering.- Finding and Capturing Value in e-Waste for Refrigerators Manufacturers and Recyclers.- Circular, Green, Sustainable Manufacturing.- Sustainable Business Model Innovation in Furniture Supply Chain: A Case Study.- A basic study on scheduling method for electric power saving of production machine.- Sustainability in fabric chains and garments for a circular economy.- Planning environments of hospital laboratories: An exploratory study.- Knowledge and practices towards sustainability and circular economy transitions: A Norwegian manufacturing perspective.- A methodology to integrate sustainability evaluations into vendor rating.- Environmental and Social Lifecycle Assessments.- Travel-Times Analysis and Passenger Transport Disutilities in Congested American Cities: Los Angeles, New York, Atlanta, Austin, and Chicago.- Socio-Cultural Aspects in Production Systems.- The interdependencies of Quality Management, Knowledge Management and Innovation Performance. A literature review.- Insights from a top-down lean subprogram deployment in a corporate group: The use of deployment tactics.- Tools for Evaluating Human Factor Aspects in Production and Logistics System.- Economy and its symbiosis with Circularity.- Data-driven Manufacturing and Services Operations Management.- First Steps to the Digital Shadow of Maintenance Services' Value Contribution.- Reshoring of service operations: evidence from a Delphi study.- Digital and physical testbed for production logistics operations.- Principles and Research Agenda for Sustainable, Data-Driven Food Production Planning and Control.- Product-Service Systems in DSN.- Agile guideline for development of smart services in manufacturing enterprises with support of artificial intelligence.- Collaborative Design and Engineering.- Framework for identifying gripper requirements for collaborative applications in manufacturing.- A novel value driven co-creation framework.- Autonomous mobile robots in hospital logistics.- Interorganizational learning in manufacturing industry.
• (source: Nielsen Book Data)

The two-volume set IFIP AICT 591 and 592 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2020, held in Novi Sad, Serbia, in August/September 2020.The 164 papers presented were carefully reviewed and selected from 199 submissions. They discuss globally pressing issues in smart manufacturing, operations management, supply chain management, and Industry 4.0. The papers are organized in the following topical sections: Part I: advanced modelling, simulation and data analytics in production and supply networks; advanced, digital and smart manufacturing; digital and virtual quality management systems; cloud-manufacturing; cyber-physical production systems and digital twins; IIOT interoperability; supply chain planning and optimization; digital and smart supply chain management; intelligent logistics networks management; artificial intelligence and blockchain technologies in logistics and DSN; novel production planning and control approaches; machine learning and artificial intelligence; connected, smart factories of the future; manufacturing systems engineering: agile, flexible, reconfigurable; digital assistance systems: augmented reality and virtual reality; circular products design and engineering; circular, green, sustainable manufacturing; environmental and social lifecycle assessments; socio-cultural aspects in production systems; data-driven manufacturing and services operations management; product-service systems in DSN; and collaborative design and engineering Part II: the Operator 4.0: new physical and cognitive evolutionary paths; digital transformation approaches in production management; digital transformation for more sustainable supply chains; data-driven applications in smart manufacturing and logistics systems; data-driven services: characteristics, trends and applications; the future of lean thinking and practice; digital lean manufacturing and its emerging practices; new reconfigurable, flexible or agile production systems in the era of industry 4.0; operations management in engineer-to-order manufacturing; production management in food supply chains; gastronomic service system design; product and asset life cycle management in the circular economy; and production ramp-up strategies for product.
(source: Nielsen Book Data)

• The Operator 4
• .0: New Physical and Cognitive Evolutionary Paths.- Facilitating Operator Participation in Continuous Improvement: An Investigation of Organizational Factors.- Improving the Safety of Using Didactic Setups by Augmented Reality.- Production Management as-a-Service: A Softbot Approach.- Knowledge Strategies for Organisation 4.0.- Challenges for the Operator 3.0 Addressed Through the Enabling Technologies of the Operator 4.0.- Agent- and Skill-based Process Interoperability for Socio-Technical Production Systems-of-Systems.- Digital Transformation Approaches in Production Management.- Challenges in Data Life Cycle Management for Sustainable Cyber-Physical Production Systems.- Explainable AI in Manufacturing: A Predictive Maintenance Case Study.- Retrofit Concept for Textile Production.- Organizational enablers for digitalization in manufacturing industry.- Concept of PLM application integration with VR and AR techniques.- The big potential of Big Data in manufacturing: evidence from emerging economies.- A conceptual model for deploying digitalization in SMEs through capability building.- The Potential of Game Development Platforms for Digital Twins and Virtual Labs: Case Study of an Energy.- The Application of ICT Software Solutions in Manufacturing Sector in Serbia.- Achieving Business Model Innovation with the Personalized Product Business Model Radar Template.- Integrating electronic components into 3D printed parts to develop a digital manufacturing approach.- Digital transformation and its potential effects on future management: Insights from an ETO context.- Applying contextualization for data-driven transformation in manufacturing.- Digital Transformation for more Sustainable Supply Chains.- Smart contract-based blockchain solution to reduce supply chain risks.- Towards sustainability: The manufacturers' perspective.- Data-Driven Applications in Smart Manufacturing and Logistics Systems.- Smart Factory Competitiveness based on real time Monitoring and Quality predictive model applied to multi-stages Production lines.- A New Application of Coordination Contracts for Supplier Selection in a Cloud Environment.- Workforce Assignment with a Different Skill Level for Automotive Parts Assembly Lines.- A framework of data-driven dynamic optimisation for smart production logistics.- Decentralized Industrial IoT Data Management Based on Blockchain and IPFS.- Integrated Platform and Digital Twin Application for Global Automotive Part Suppliers.- Analyzing the Characteristics of Digital Twin and Discrete Event Simulation in Cyber Physical Systems.- Streaming Analytics in Edge-Cloud Environment for Logistics Processes.- An Improvement in Master Surgical Scheduling using Artificial Neural Network and Fuzzy Programming.- SKOS Tool: A Tool for Creating Knowledge Graphs to Support Semantic Text Classification.- Data-Driven Services: Characteristics, Trends and Applications.- The successful commercialization of a digital twin in an industrial product service system.- Using Service Dominant logic to assess the value co-creation of Smart Services.- Engineering of data-driven Service Systems for Smart Living: Application and Challenges.- The role of service business models in the manufacturing of transition economies.- System architecture analysis with network index in MBSE approach -Application to smart interactive service with digital health modeling.- The Data-Driven Product-Service Systems Design and Delivery (4DPSS) methodology.- Data-driven maintenance delivery framework: test in an Italian company.- Towards a Comparative Data Value Assessment Framework for Smart Product Service Systems.- Impact of platform openness on ecosystems and value streams in Platform-based PSS exemplified using RAMI 4.0.- Industry 4.0 data-related technologies and servitization: a systematic literature review.- A framework to support value co-creation in PSS development.- The Future of Lean Thinking and Practice.- Utilizing Lean Thinking as a Means to Digital Transformation in Service Organizations.- On the Need of Functional Priority and Failure Risk Assessment to Optimize Human Resource Allocation in Public Service Organizations.- Assessing the Value of Process Improvement Suggestions.- On the Necessity for Identifying Waste in Knowledge Work Dominated Projects: A Case Study from Oil and Gas-Related Product Development Projects.- Lean Thinking: from the shop floor to an organizational culture.- Digital Lean Manufacturing and its Emerging Practices.- A Learning Roadmap for Digital Lean Manufacturing.- Investigating the Challenges and Opportunities for Production Planning and Control in Digital Lean Manufacturing.- New Forms of Gemba Walks and their Digital Tools in the Digital Lean Manufacturing World.- New Reconfigurable, Flexible or Agile Production Systems in the Era of Industry 4.0.- A computational method for identifying the optimum buffer size in the era of Zero Defect Manufacturing.- A Bi-objective Scheduling Model for Additive Manufacturing with Multiple Materials and Sequence-dependent Setup Time.- Dynamic Distributed Job-Shop Scheduling Problem Consisting of Reconfigurable Machine Tools.- Towards a Non-Disruptive System for Dynamic Orchestration of the Shop Floor.- Assembly process design: performance evaluation under ergonomics consideration using several robot collaboration modes.- A Method of Distributed Production Management for Highly-Distributed Flexible Job Shops.- A Digital Twin modular framework for Reconfigurable Manufacturing Systems.- Reconfigurable Digitalized and Servitized Production Systems: Requirements and Challenges.- The impact of dynamic tasks assignment in paced mixed-model assembly line with moving workers.- Balancing and configuration planning of RMS to minimize energy cost.- Operations Management in Engineer-to-Order Manufacturing.- Factors affecting shipyard operations and logistics: A framework and comparison of shipbuilding approaches.- Using the Smartphone as an Augmented Reality Device in ETO Industry.- Exploring the Path Towards Construction 4
• .0: Collaborative Networks & Enterprise Architecture Views.- The Potential for Purchasing function to Enhance Circular Economy Business Models for ETO production.- Planning procurement activities in ETO projects.- Maturity model for successful cost transformation in ETO companies.- Backlog Oriented Bottleneck Management - Practical Guide for Production Managers.- Cross-functional coordination before and after the CODP: an empirical study in the machinery industry.- Production Management in Food Supply Chains.- Food Bank: A Proposal for Short Agri-Food Chains.- The New Frontiers in World Soybean Production: An Analysis of Savanna in Piaui, Brazil.- Prediction of cold chain transport conditions using data mining.- Environmental impact classification of perishable on-road transport using data mining.- Economic and Environmental Perfomance in Coffee Supply Chains: A Brazilian Case Study.- Managing Perishable Multi-Product Inventory with Supplier Fill-Rate, Price Reduction and Substitution.- Digital Technology Enablers for Resilient and Customer Driven Food Value Chains.- Gastronomic Service System Design.- Human-Robot Hybrid Service System Introduction for Enhancing Labor and Robot Productivity.- Forecasting Customers Visiting using Machine Learning and Characteristics Analysis with Low Forecasting Accuracy Days.- A study on menu planning method for managed meal -Consideration of the cost of ordering ingredients.- Service system design considering employee satisfaction.- Product and Asset Life Cycle Management in the Circular Economy.- Exploring synergies between Circular Economy and Asset Management.- Information flows supporting Circular Economy adoption in the manufacturing sector.- A conceptual model of the IT ecosystem for Asset Management in the global manufacturing context.- Production Ramp-up Strategies for Product.- Part Selection for Freeform Injection Molding: framework for development of a unique methodology.- A Model for Cost-Benefit Analysis of Production Ramp-up Strategies.- Key factors on utilizing the production system design phase for increasing operational performance.- Business Model Development for a Dynamic Production Network Platform.- Changeable Closed-Loop Manufacturing Systems: A Case Study of Challenges in Product Take-Back.
• (source: Nielsen Book Data)

The two-volume set IFIP AICT 591 and 592 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2020, held in Novi Sad, Serbia, in August/September 2020. The 164 papers presented were carefully reviewed and selected from 199 submissions. They discuss globally pressing issues in smart manufacturing, operations management, supply chain management, and Industry 4.0. The papers are organized in the following topical sections: Part I: advanced modelling, simulation and data analytics in production and supply networks; advanced, digital and smart manufacturing; digital and virtual quality management systems; cloud-manufacturing; cyber-physical production systems and digital twins; IIOT interoperability; supply chain planning and optimization; digital and smart supply chain management; intelligent logistics networks management; artificial intelligence and blockchain technologies in logistics and DSN; novel production planning and control approaches; machine learning and artificial intelligence; connected, smart factories of the future; manufacturing systems engineering: agile, flexible, reconfigurable; digital assistance systems: augmented reality and virtual reality; circular products design and engineering; circular, green, sustainable manufacturing; environmental and social lifecycle assessments; socio-cultural aspects in production systems; data-driven manufacturing and services operations management; product-service systems in DSN; and collaborative design and engineering Part II: the Operator 4.0: new physical and cognitive evolutionary paths; digital transformation approaches in production management; digital transformation for more sustainable supply chains; data-driven applications in smart manufacturing and logistics systems; data-driven services: characteristics, trends and applications; the future of lean thinking and practice; digital lean manufacturing and its emerging practices; new reconfigurable, flexible or agile production systems in the era of industry 4.0; operations management in engineer-to-order manufacturing; production management in food supply chains; gastronomic service system design; product and asset life cycle management in the circular economy; and production ramp-up strategies for product.
(source: Nielsen Book Data)

• Deep Learning Methods for Image Guidance in Radiation Therapy Intentional Image Similarity Search.- Sttructured (De)composable Representations Trained with Neural Networks.- Long Distance Relationships without Time Travel: Boosting the Performance of a Sparse Predictive Autoencoder in Sequence Modeling.- Improving Accuracy and Efficiency of Object Detection Algorithms using Multiscale Feature Aggregation Plugins.- Abstract Echo State Networks.- Minimal Complexity Support Vector Machines.- Named Entity Disambiguation at Scale.- Geometric Attention for Prediction of Differential Properties in 3D Point Clouds.- How (Not) to Measure Bias in Face Recognition Networks.-Feature Extraction: A Time Window Analysis based on the X-ITE Pain Database.- Pain Intensity Recognition - An Analysis of Short-Time Sequences in a Real-World Scenario.- A deep learning approach for efficient registration of dual view mammography.- Deep Transfer Learning for Texture Classification in Colorectal Cancer Histology.- Applications of Generative Adversarial Networks to Dermatologic Imaging.- Typing Plasmids with Distributed Sequence Representation.- KP-YOLO: a modification of YOLO algorithm for the keypoint-based detection of QR Codes.- Using Mask R-CNN for Image-Based Wear Classification of Solid Carbide Milling and Drilling Tools.- A Hybrid Deep Learning Approach For Forecasting Air Temperature.- Using CNNs to optimize numerical simulations in geotechnical engineering.- Going for 2D or 3D? Investigating various Machine Learning Approaches for Peach Variety Identification.- A Transfer Learning End-to-End Arabic Text-To-Speech (TTS) Deep Architecture.- ML-Based Trading Models: An investigation during COVID-19 pandemic crisis.- iNNvestigate-GUI - Explaining Neural Networks Through an Interactive Visualization Tool.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 9th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2020, held in Winterthur, Switzerland, in September 2020. The conference was held virtually due to the COVID-19 pandemic. The 22 revised full papers presented were carefully reviewed and selected from 34 submissions. The papers present and discuss the latest research in all areas of neural network-and machine learning-based pattern recognition. They are organized in two sections: learning algorithms and architectures, and applications.
(source: Nielsen Book Data)

• Facial Age Estimation Using Compact Facial Features.- A Vision Based Hardware-Software Real-Time Control System for the Autonomous Landing of an UAV.- Exploration of Ear Biometrics with Deep Learning.- Does Randomness in the Random Visual Cryptography Protocol Depend on the Period of Pseudorandom Number Generators.- Software for CT-Image Analysis to Assist the Choice of Mechanical-Ventilation Settings in Acute Respiratory Distress Syndrome.- Edge-Aware Color Image Manipulation by Combination of Low-pass Linear Filter and Morphological Processing of its Residuals.- On the Effect of DCE MRI Slice Thickness and Noise on Estimated Pharmacokinetic Biomarkers a Simulation Study.- A New Sport Teams Logo Dataset for Detection Tasks.- Scene Recognition Using AlexNet to Recognize Significant Events within Cricket Game Footage.- Biologically Inspired Modelling of Flowers.- Tuberculosis Abnormality Detection in Chest X-Rays: A Deep Learning Approach.- Dynamic Local Ternary Patterns for Gender Identification using Facial Components.- Depth Perception Tendencies in the 3-D Environment of Virtual Reality.- Optimisation of a Siamese Neural Network for Real-Time Energy Efficient Object Tracking.- Nuclei Detection with Local Threshold Processing in DAB&H Stained Breast Cancer Biopsy Images.- Video Footage Highlight Detection in Formula 1 Through Vehicle Recognition with Faster R-CNN Trained On Game Footage.- Performance Evaluation of Selected Detector-Descriptor Combinations.- Watermarking Method for Video Authentication with Tamper Localization.- RGB-D and Lidar Calibration Supported by GPU.- Video-Surveillance Tools for Monitoring Social Responsibility Under Covid-19 Restrictions.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the International Conference on Computer Vision and Graphics, ICCVG 2020, held in Warsaw, Poland, in September 2020. The 20 full papers were selected from 49 submissions. The contributions cover topics such as: modelling of human visual perception; computational geometry; geometrical models of objects and scenes; illumination and reflection models and methods; image formation; image and video coding; image filtering and enhancement; biomedical image processing; biomedical graphics; colour image processing; multispectral image processing; pattern recognition in image processing; scene understanding; motion analysis, visual navigation and active vision; human motion detection and analysis; visualisation and graphical data presentation; hardware and architectures for image processing; computer-aided graphic design; 3D imaging, shading and rendering; computer animation; graphics for internet and mobile systems; virtual reality; image and video databases; digital watermarking; multimedia applications; and computer art. Due to the Corona pandemic ICCVG 2020 was held as a virtual event.
(source: Nielsen Book Data)

• Character and text recognition.- Document image processing.- Segmentation and layout analysis.- Word embedding and spotting.- Text detection.- Font design and classification.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 14th IAPR International Workshop on Document Analysis Systems, DAS 2020, held in Wuhan, China, in July 2020. The 40 full papers presented in this book were carefully reviewed and selected from 57 submissions. The papers are grouped in the following topical sections: character and text recognition; document image processing; segmentation and layout analysis; word embedding and spotting; text detection; and font design and classification. Due to the Corona pandemic the conference was held as a virtual event .
(source: Nielsen Book Data)

• Part 1: Preparing for the Future of Work
• Chapter 1: Will Robots Replace You?
• Chapter 2: Technology Definitions
• Part 2: Robots are Working
• Chapter 3: Robotic Process Automation
• Chapter 4: Robots in Teams
• Chapter 5: Robots Without Arms
• Part 3: Making Sense for Robots and Society
• Chapter 6: Robots in a World of Data
• Chapter 7: Robots in Society
• Chapter 8: Work in the Future.

Understand the current and future research into technologies that underpin the increasing capabilities of automation technologies and their impact on the working world of the future. Rapid advances in automation and robotics technologies are often reported in the trade and general media, often relying on scary headlines such as "Jobs Lost to Robots." It is certainly true that work will change with the advent of smarter and faster automated workers; however, the scope and scale of the changes is still unknown. Automation may seem to be here already, but we are only at the early stages. Automation and Collaborative Robotics explores the output of current research projects that are improving the building blocks of an automated world. Research into collaborative robotics (cobotics) is merging digital, audio, and visual data to generate a commonly held view between cobots and their human collaborators. Low-power machine learning at the edge of the network can deliver decision making on cobots or to their manipulations. Topics covered in this book include: Robotic process automation, chatbots, and their impact in the near future The hype of automation and headlines leading to concerns over the future of work Component technologies that are still in the research labs Foundational technologies and collaboration that will enable many tasks to be automated with human workers being re-skilled and displaced rather than replaced What You Will Learn Be aware of the technologies currently being researched to improve or deliver automation Understand the impact of robotics, other automation technologies, and the impact of AI on automation Get an idea of how far we are from implementation of an automated future Know what work will look like in the future with the deployment of these technologies Who This Book Is For Technical and business managers interested in the future of automation and robotics, and the impact it will have on their organizations, customers, and the business world in general.
(source: Nielsen Book Data)

• Machine Learning
• Medical Image and Analysis
• Analysis of Histopathology Images
• Diagnosis and Screening of Ophthalmic Diseases
• Grand Challenge on Automatic Lung Cancer Patient Management.

This two-volume set LNCS 12131 and LNCS 12132 constitutes the refereed proceedings of the 17th International Conference on Image Analysis and Recognition, ICIAR 2020, held in Póvoa de Varzim, Portugal, in June 2020. The 54 full papers presented together with 15 short papers were carefully reviewed and selected from 123 submissions. The papers are organized in the following topical sections: image processing and analysis; video analysis; computer vision; 3D computer vision; machine learning; medical image and analysis; analysis of histopathology images; diagnosis and screening of ophthalmic diseases; and grand challenge on automatic lung cancer patient management. Due to the corona pandemic, ICIAR 2020 was held virtually only.

• Pattern Recognition Techniques.- Image Processing and Analysis.- Computer Vision.- Industrial and Medical Applications of Pattern Recognition.- Natural Language Processing and Recognition.- Artificial Intelligence Techniques and Recognition.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 12th Mexican Conference on Pattern Recognition, MCPR 2020, which was due to be held in Morelia, Mexico, in June 2020. The conference was held virtually due to the COVID-19 pandemic. The 31 papers presented in this volume were carefully reviewed and selected from 67 submissions. They were organized in the following topical sections: pattern recognition techniques; image processing and analysis; computer vision; industrial and medical applications of pattern recognition; natural language processing and recognition; artificial intelligence techniques and recognition.
(source: Nielsen Book Data)

• Real time Implementation of Articial Neural Network in FPGA Platform.- Design of a 0,18um CMOS Inductor - based Bandpass Microwave Active Filter.- Improvement of the Authentication on in-Vehicle Controller Area Networks.- Comparative Evaluation of Speech Recognition systems Based on Different Toolkits.- Stability Analysis and H Performance for Nonlinear Fuzzy Networked Control Systems with Time-Varying Delay.- Driver Behavior assistance in Road Intersections.- Performance of CE-OFDM System over AWGN and Frequency-Selective Channels.- Towards a Dynamical Adaptive Finite Volume Core for Urban Flow Simulations.- An Efficiency Study of Adaptive Median Filtering for Image Denoising, Based on A Hardware Implementation.- Processing Time and Computing Resources Optimization in a Mobile Edge Computing Node.- Viscous Dissipation and Heat Source/Sink Effects on Convection Heat Transfer in a Saturated Porous Medium.- Fast and Efficient Decoding Algorithm Developed From Concatenation between A Symbol-By-Symbol Decoder and A Decoder Based On Syndrome Computing and Hash Techniques.- SWIMAC: An Ultra-Low Power Consumption MAC Protocol for IR-UWB based WSN.- An Optimal Design of a Short-Channel RF Low Noise Amplifier Using a Swarm Intelligence Techniques.
• (source: Nielsen Book Data)

• 4 Conclusion
• References
• Design of a 0.18 μm CMOS Inductor-Based Bandpass Microwave Active Filter
• 1 Introduction
• 2 Synthesis of a Grounded CMOS Active Inductor
• 3 Procedure of Designing Chebyshev Microwave Bandpass Filters
• 4 Example of a Third-Order Chebyshev Bandpass Filter
• 5 Conclusion
• References
• Improvement of the Authentication on In-Vehicle Controller Area Networks
• 1 Introduction
• 2 Development of an Authentication Method
• 2.1 Principles
• 2.2 Current Technique
• 2.3 Proposed Improvements
• 3 Hash Algorithm
• 4 Conclusion
• References

This book gathers selected research papers presented at the First International Conference on Embedded Systems and Artificial Intelligence (ESAI 2019), held at Sidi Mohamed Ben Abdellah University, Fez, Morocco, on 2-3 May 2019. Highlighting the latest innovations in Computer Science, Artificial Intelligence, Information Technologies, and Embedded Systems, the respective papers will encourage and inspire researchers, industry professionals, and policymakers to put these methods into practice.
(source: Nielsen Book Data)

• Network and Computing Technologies
• Wireless Networks and Internet of Things (IoT)
• Futuristic Computing Technologies
• Communication Technologies, Security and Privacy.

This book constitutes the refereed proceedings of the Second International Conference on Futuristic Trends in Network and Communication Technologies, FTNCT 2019, held in Chandigarh, India, in November 2019. The 49 revised full papers and 6 short papers presented were carefully reviewed and selected from 226 submissions. The prime aim of the conference is to invite researchers from different domains of network and communication technologies to a single platform to showcase their research ideas. The selected papers are organized in topical sections on network and computing technologies; wireless networks and Internet of Things (IoT); futuristic computing technologies; communication technologies, security and privacy.

• 1. Introduction.-
• 2. Machine Learning Methods for Spatial and Temporal Parameter Estimation.-
• 3. Deep Learning for Hyperspectral Image Analysis, Part I: Theory and Algorithms.-
• 4. Deep Learning for Hyperspectral Image Analysis, Part II: Applications to Remote Sensing and Biomedicine.-
• 5. Advances in Deep Learning for Hyperspectral Image Analysis - Addressing Challenges Arising in Practical Imaging Scenarios.-
• 6. Addressing the Inevitable Imprecision: Multiple Instance Learning for Hyperspectral Image Analysis.-
• 7. Supervised, Semi Supervised and Unsupervised Learning for Hyperspectral Regression.-
• 8. Sparsity-based Methods for Classification.-
• 9. Multiple Kernel Learning for Hyperspectral Image Classification.-
• 10. Low Dimensional Manifold Model in Hyperspectral Image Reconstruction.-
• 11. Deep Sprase Band Selection for Hyperspectral Face Recognition.-
• 12. Detection of Large-Scale and Anomalous Changes.-
• 13. Recent Advances in Hyperspectral Unmixing Using Sparse Techniques and Deep Learning.-
• 14. Chapter Hyperspectral-Multispectral Image Fusion Enhancement Based on Deep Learning.-
• 15. Automatic Target Detection for Sparse Hyperspectral Images.
• (source: Nielsen Book Data)

This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas of image analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful. .
(source: Nielsen Book Data)

• Chapter 1. Introduction.-
• Chapter 2. Sparse Linear Model.-
• Chapter 3. Blind Demixing.-
• Chapter 4. Sparse Blind Demixing.-
• Chapter 5. Shuffled Linear Regression.-
• Chapter 6. Learning Augmented Methods.-
• Chapter 7. Conclusions and Discussions.-
• Chapter 8. Appendix. .
• (source: Nielsen Book Data)

• 4.5.1 Optimization on Product Manifolds
• 4.5.2 Smoothed Riemannian Optimization
• 4.5.3 Simulation Results
• 4.6 Summary
• References
• 5 Shuffled Linear Regression
• 5.1 Joint Data Decoding and Device Identification
• 5.2 Problem Formulation
• 5.3 Maximum Likelihood Estimation Based Approaches
• 5.3.1 Sorting Based Algorithms
• 5.3.2 Approximation Algorithm
• 5.4 Algebraic-Geometric Approach
• 5.4.1 Eliminating Π via Symmetric Polynomials
• 5.4.2 Theoretical Analysis
• 5.4.2.1 Exact Data
• 5.4.2.2 Corrupted Data
• 5.4.3 Algebraically Initialized Expectation-Maximization

The recent developments in wireless communications, networking, and embedded systems have driven various innovative Internet of Things (IoT) applications, e.g., smart cities, mobile healthcare, autonomous driving and drones. A common feature of these applications is the stringent requirements for low-latency communications. Considering the typical small payload size of IoT applications, it is of critical importance to reduce the size of the overhead message, e.g., identification information, pilot symbols for channel estimation, and control data. Such low-overhead communications also help to improve the energy efficiency of IoT devices. Recently, structured signal processing techniques have been introduced and developed to reduce the overheads for key design problems in IoT networks, such as channel estimation, device identification, and message decoding. By utilizing underlying system structures, including sparsity and low rank, these methods can achieve significant performance gains. This book provides an overview of four general structured signal processing models: a sparse linear model, a blind demixing model, a sparse blind demixing model, and a shuffled linear model, and discusses their applications in enabling low-overhead communications in IoT networks. Further, it presents practical algorithms based on both convex and nonconvex optimization approaches, as well as theoretical analyses that use various mathematical tools.
(source: Nielsen Book Data)

• Conversational Agents in Healthcare: Using QCA to Explain Patients Resistance to Chatbots for Medication
• An Approach for Ex-Post-Facto Analysis of Knowledge Graph-Driven Chatbots
• the DBpedia Chatbot
• Privacy Concerns in Chatbot Interactions
• Creating Humanlike Chatbots: What Chatbot Developers Could Learn from Webcare Employees in Adopting a Conversational Human Voice
• The Conversational Agent "Emoty" Perceived by People with Neurodevelopmental Disorders: Is It a Human or a Machine
• Gender Bias in Chatbot Design
• Conversational Web Interaction: Proposal of a Dialog-Based Natural Language Interaction Paradigm for the Web
• Designing Chatbots for Guiding Online Peer Support Conversations for Adults with ADHD
• Towards Chatbots to Support Bibliotherapy Preparation and Delivery
• CivicBots
• Chatbots for Supporting Youth in Societal Participation
• Using Theory of Mind to Assess Users Sense of Agency in Social Chatbots
• Exploring Age Differences in Motivations for and Acceptance of Chatbot Communication in a Customer Service Context
• Improving Conversations: Lessons Learnt from Manual Analysis of Chatbot Dialogues
• Conversational Repair in Chatbots for Customer Service: The Effect of Expressing Uncertainty and Suggesting Alternatives
• Working Together with Conversational Agents: The Relationship of Perceived Cooperation with Service Performance Evaluation
• Chatbots for the Information Acquisition at Universities
• A Students View on the Application Area
• A Configurable Agent to Advance Peers Productive Dialogue in MOOCs
• Small Talk Conversations and the Long-Term Use of Chatbots in Educational Settings
• Experiences from a Field Study.

This book constitutes the refereed proceedings of the Third International Workshop on Chatbot Research and Design, CONVERSATIONS 2019, held in Amsterdam, The Netherlands, in November 2019. The 18 revised full papers presented in this volume were carefully reviewed and selected from 31 submissions. The papers are grouped in the following topical sections: user and communication studies user experience and design, chatbots for collaboration, chatbots for customer service, and chatbots in education.

Extract patterns and knowledge from your data in easy way using MATLAB About This Book * Get your first steps into machine learning with the help of this easy-to-follow guide * Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB * Understand how your data works and identify hidden layers in the data with the power of machine learning. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well. What You Will Learn * Learn the introductory concepts of machine learning. * Discover different ways to transform data using SAS XPORT, import and export tools, * Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data. * Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment. * Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures. * Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox. * Learn feature selection and extraction for dimensionality reduction leading to improved performance. In Detail MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners. You'll start by getting your system ready with t he MATLAB environment for machine learning and you'll see how to easily interact with the Matlab workspace. We'll then move on to data cleansing, mining and analyzing various data types in machine learning and you'll see how to display data values on a plot. Next, you'll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You'll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you'll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB. Style and approach The book takes a very comprehensive approach to enhance your understanding of machine learning using MATLAB. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work.
(source: Nielsen Book Data)

• The Two-point Fano and Ideal Binary Clutters.- On Scheduling Coflows.- Integrality Gaps of Integer Knapsack Problems.- An Improved Integrality Gap for the Calinescu-Karloff-Rabani Relaxation for Multiway Cut.- Approximation of Corner Polyhedra with Families of Intersection Cuts.- The Structure of the Infinite Models in Integer Programming.- Mixed-integer Linear Representability, Disjunctions, and Variable Elimination.- Deterministic Fully Dynamic Approximate Vertex Cover and Fractional Matching in O(1) Amortized Update Time.- Cutting Planes from Wide Split Disjunctions.- The Salesman's Improved Tours for Fundamental Classes.- The Heterogeneous Capacitated k-Center Problem.- Local Guarantees in Graph Cuts and Clustering.- Verifying Integer Programming Results.- Long term Behavior of Dynamic Equilibria in uid Queuing Networks.- A 4/5 - Approximation Algorithm for the Maximum Traveling Salesman Problem.- Minimizing Multimodular Functions and Allocating Capacity in Bike-sharing Systems.- Compact, Provably-Good LPs for Orienteering and Regret-Bounded Vehicle Routing.- Discrete Newton's Algorithm for Parametric Submodular Function Minimization.- Stochastic Online Scheduling on Unrelated Machines.- Online Matroid Intersection: Beating Half for Random Arrival.- Number Balancing is as Hard as Minkowski's Theorem and Shortest Vector.- An Improved Deterministic Rescaling for Linear Programming Algorithms.- Min-Max Theorems for Packing and Covering Odd (u
• v)-trails.- Breaking 1 - 1/e Barrier for Non-preemptive Throughput Maximization.- A Quasi-Polynomial Approximation for the Restricted Assignment Problem.- Adaptive Submodular Ranking.- On the Notions of Facets, Weak Facets, and Extreme Functions of the Gomory-Johnson Infinite Group Problem.- Minimum Birkhoff-von Neumann Decomposition.- Maximum Matching in the Online Batch-Arrival Model.- Budget Feasible Mechanisms on Matroids.- Deterministic Discrepancy Minimization Via the Multiplicative Weight Update Method.- Mixed-integer Convex Representability.- High Degree Sum of Squares Proofs, Bienstock-Zuckerberg Hierarchy and Chvatal-Gomory Cuts.- Enumeration of Integer Points in Projections of Unbounded Polyhedral.- Excluded t-factors in Bipartite Graphs: A Unified Framework for Nonbipartite Matchings and Restricted 2-matchings.- Equilibrium Computation in Atomic Splittable Singleton Congestion Games. .
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 19th International Conference on Integer Programming and Combinatorial Optimization, IPCO 2017, held in Waterloo, IN, Canada, in June 2017. The 36 full papers presented were carefully reviewed and selected from 125 submissions. The conference is a forum for researchers and practitioners working on various aspects of integer programming and combinatorial optimization. The aim is to present recent developments in theory, computation, and applications in these areas. The scope of IPCO is viewed in a broad sense, to include algorithmic and structural results in integer programming and combinatorial optimization as well as revealing computational studies and novel applications of discrete optimization to practical problems.
(source: Nielsen Book Data)

• Rol based on MATLAB and the real-time controller
• Design and Analysis of Motor Control System for Drilling Fluid Continuous Wave Generator Based on Improved Active Disturbance Rejection Control and Hysteresis Current Control
• Trajectory Planning based on Optimal Control and Exact Derivatives
• Co-simulation Based on ADAMS and Simulink for Direct Yaw Moment Control System of 4WD-EV
• LI Zhanfeng, Du Shuang. Simulation Analysis of PID Closed-Loop Control of Current of SBW
• Characteristic Analysis and Disturbance Control of Hydraulic Transmission System for Driving Torque Extraction Electric Power Generation in Coal Sampling Robot
• Appearance-Based Gaze Tracking: A Brief Review
• Language and Robotics: Complex Sentence Understanding
• Dynamic Motion Planning Algorithm in Human-Robot Collision Avoidance
• Dynamics modeling of a 2-DOFs mechanism with rigid joint and flexible joint
• Haptic Joystick Impedance Control with Gravity Compensation
• Landmark-Based Virtual Path Estimation for Assisted UAV FPV Tele-Operation with Augmented Reality
• Concurrent Probabilistic Motion Primitives for Obstacle Avoidance and Human-Robot Collaboration e System of the Assistive Gait Training Robot
• A Noninvasive Calibration-free and Model-free Surgical Robot for Automatic Fracture Reduction
• Force Modeling of Tool-tissue Interaction Force during Suturing
• Minimally invasive instrument joint design based on variable stiffness of transmission efficiency
• An improved arti cial potential eld method for mobile robots using environmental information
• Towards End-to-End Speech Recognition with Deep Multipath Convolutional Neural Networks
• Robot Intelligent Trajectory Planning based on PCM guided Reinforcement Learning
• Fast Robot Motor Skill Acquisition Based on Bayesian inspired Policy Improvement
• Control of Nameplate Pasting Robot for Sand Mold Based on Deep Reinforcement Learning
• Robot Intelligent Trajectory Planning based on PCM guided Reinforcement Learning
• Way-Point Tracking Control of Underactuated USV Based on GPC Path Planning
• Neural Networks-Based PID Precision Motion Control of a Piezo-Actuated Microinjector
• Force/Motion Hybrid Control of Three Link Constrained Manipulator Using Sliding Mode
• Development of workshop management system for assembly production process
• Dynamic Scheduling of Dual-Resource Constrained Blocking Job Shop
• Study on No-wait Flexible Flow Shop Scheduling with Multi-Objective
• Dynamic Behavior Analysis and Multi-sensor Modal Information Fusion for Robotic Milling System
• Adaptive Impedance Control for Robotic Polishing with an Intelligent Digital Compliant Grinder
• Path Planning of UAV-UGV Heterogeneous Robot System in Road Network
• Automatic programming for dual robots to grinding intersecting curve
• A HoloLens Based Augmented Reality Navigation System for Minimally Invasive Total Knee Arthroplasty
• R-3RPS robot-based mathematical modeling for a military flight simulator
• Innovation Ability Cultivation Quality Evaluation Model of Machinery Postgraduate by Mechatronics Engineering
• DOREP: an educational experiment platform for robot cont.

The volume set LNAI 11740 until LNAI 11745 constitutes the proceedings of the 12th International Conference on Intelligent Robotics and Applications, ICIRA 2019, held in Shenyang, China, in August 2019. The total of 378 full and 25 short papers presented in these proceedings was carefully reviewed and selected from 522 submissions. The papers are organized in topical sections as follows: Part I: collective and social robots; human biomechanics and human-centered robotics; robotics for cell manipulation and characterization; field robots; compliant mechanisms; robotic grasping and manipulation with incomplete information and strong disturbance; human-centered robotics; development of high-performance joint drive for robots; modular robots and other mechatronic systems; compliant manipulation learning and control for lightweight robot. Part II: power-assisted system and control; bio-inspired wall climbing robot; underwater acoustic and optical signal processing for environmental cognition; piezoelectric actuators and micro-nano manipulations; robot vision and scene understanding; visual and motional learning in robotics; signal processing and underwater bionic robots; soft locomotion robot; teleoperation robot; autonomous control of unmanned aircraft systems. Part III: marine bio-inspired robotics and soft robotics: materials, mechanisms, modelling, and control; robot intelligence technologies and system integration; continuum mechanisms and robots; unmanned underwater vehicles; intelligent robots for environment detection or fine manipulation; parallel robotics; human-robot collaboration; swarm intelligence and multi-robot cooperation; adaptive and learning control system; wearable and assistive devices and robots for healthcare; nonlinear systems and control. Part IV: swarm intelligence unmanned system; computational intelligence inspired robot navigation and SLAM; fuzzy modelling for automation, control, and robotics; development of ultra-thin-film, flexible sensor s, and tactile sensation; robotic technology for deep space exploration; wearable sensing based limb motor function rehabilitation; pattern recognition and machine learning; navigation/localization. Part V: robot legged locomotion; advanced measurement and machine vision system; man-machine interactions; fault detection, testing and diagnosis; estimation and identification; mobile robots and intelligent autonomous systems; robotic vision, recognition and reconstruction; robot mechanism and design. Part VI: robot motion analysis and planning; robot design, development and control; medical robot; robot intelligence, learning and linguistics; motion control; computer integrated manufacturing; robot cooperation; virtual and augmented reality; education in mechatronics engineering; robotic drilling and sampling technology; automotive systems; mechatronics in energy systems; human-robot interaction.

• Pattern Recognition and Artificial Intelligent Techniques.- Image Processing and Analysis.- Robotics and Computer Vision.- Natural Language Processing and Recognition.- Applications of Pattern Recognition.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 7th Mexican Conference on Pattern Recognition, MCPR 2015, held in Mexico City Mexico, in June 2015. The 30 revised full papers presented were carefully reviewed and selected from 63 submissions. The papers are organized in topical sections on pattern recognition and artificial intelligence; image processing and analysis; robotics and computer vision; natural language processing and recognition; and applications of pattern recognition.
(source: Nielsen Book Data)

• Pattern recognition and machine learning.- Signal and image processing.- Computer vision and video processing.- Soft and natural computing.- Speech and natural language processing.- Bioinformatics and computational biology.- Data mining and big data analytics.- Deep learning.- Spatial data science and engineering.- Applications of pattern recognition and machine intelligence.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 7th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2017, held in Kolkata, India, in December 2017. The total of 86 full papers presented in this volume were carefully reviewed and selected from 293 submissions. They were organized in topical sections named: pattern recognition and machine learning; signal and image processing; computer vision and video processing; soft and natural computing; speech and natural language processing; bioinformatics and computational biology; data mining and big data analytics; deep learning; spatial data science and engineering; and applications of pattern recognition and machine intelligence.
(source: Nielsen Book Data)

• Communication in Soccer Simulation: On the Use of Wiretapping Opponent Teams.- Multi-Robot Fast-Paced Coordination With Leader Election.- Visual SLAM-Based Localization and Navigation for Service Robots: The Pepper Case.- Visual Mesh: Real-time Object Detection Using Constant Sample Density.- Fast Multi-Scale fHOG Feature Extraction Using Histogram Downsampling.- Combining Simulations and Real-Robot Experiments for Bayesian Optimization of Bipedal Gait Stabilization.- Learning Skills for Small Size League RoboCup.- Real-time Scene Understanding Using Deep Neural Networks for RoboCup SPL.- Training a RoboCup Striker Agent via Transferred Reinforcement Learning.- Playing Soccer Without Colors in the SPL: A Convolutional Neural Network.- End-to-End Deep Imitation Learning: Robot Soccer Case Study.- Designing Convolutional Neural Networks Using a Genetic Approach for Ball Detection.- ImageTagger: An Open Source Online Platform for Collaborative Image Labeling.- Mimicking an Expert Team Through the Learning of Evaluation Functions from Action Sequences.- Jetson, Where Is the Ball? Using Neural Networks for Ball Detection at RoboCup 2017.- Bridging the Gap - On a Humanoid Robotics Rookie League.- Context Aware Robot Architecture, Application to the Robocup@Home Challenge.- From Commands to Goal-based Dialogs: A Roadmap to Achieve Natural Language Interaction in RoboCup@Home.-RoboCupSimData: Software and Data for Machine Learning from RoboCup Simulation League.- Generation of Laser-Quality 2D Navigation Maps from RGB-D Sensors.- Towards Long-Term Memory for Social Robots: Proposing a New Challenge for the RoboCup@Home.- eEVA: Real-Time Web-Based Affective Agents for Human-Robot Interface.- Evaluation of Situations in RoboCup 2D Simulations Using Soccer Field Images.- Near Real-Time Object Recognition for Pepper Based on Deep Neural Networks Running on a Backpack.- Multimodal Movement Activity Recognition Using a Robot's Proprioceptive Sensors.- Survey of Rescue Competitions and Proposal of New Standard Task from Ordinary Tasks.- Adjusted Bounded Weighted Policy Learner.- Towards Real-Time Ball Localization Using CNNs.- Deep Learning for Semantic Segmentation on Minimal Hardware.- RoboCup Junior in the Hunter Region: Driving the Future of Robotic STEM Education Distributed Circumnavigation Control with Dynamic Spacings for a Heterogeneous Multi-Robot System.- Prediction of a Ball Trajectory for the Humanoid Robots: A Friction-Based Study.- RoboCup SSL 2018 Champion Team Paper.- Tech United Eindhoven Middle Size League Winner 2018.- Ichiro Robots Winning RoboCup 2018 Humanoid TeenSize Soccer Competitions.- NimbRo Robots Winning RoboCup 2018 Humanoid AdultSize Soccer Competitions.- HELIO
• S2018: RoboCup 2018 Soccer Simulation 2D League Champion.- UT Austin Villa: RoboCup 2018 3D Simulation League Champions.- Integrating the Latest Artificial Intelligence Algorithms in the RoboCup Rescue Simulation framework.- Robust and Flexible System Architecture for Facing the RoboCup Logistics League Challenge.- RoboCup@Work 2018 Team AutonOHM.- homer@UniKoblenz: Winning Team of the RoboCup@Home Open Platform League 2018.- ToBI - Team of Bielefeld: Enhancing the Robot Capabilities of the Social Standard Platform Pepper. .
• (source: Nielsen Book Data)

This book includes the post-conference proceedings of the 22nd RoboCup International Symposium, held in Montreal, QC, Canada, in June 2018. The 32 full revised papers and 11 papers from the winning teams presented were carefully reviewed and selected from 51 submissions. This book highlights the approaches of champion teams from the competitions and documents the proceedings of the 22nd annual RoboCup International Symposium. Due to the complex research challenges set by the RoboCup initiative, the RoboCup International Symposium offers a unique perspective for exploring scientific and engineering principles underlying advanced robotic and AI systems.
(source: Nielsen Book Data)

• to Pattern Recognition and Classification in Medical and Astrophysical Images.- Image Standardization and Enhancement.- Intensity and Region-Based Feature Recognition in Solar Images.- Advanced Feature Recognition and Classification Using Artificial Intelligence Paradigms.- Feature Recognition and Classification Using Spectral Methods.
• (source: Nielsen Book Data)

This book presents innovative techniques in recognition and classification of astrophysical and medical images. Coverage includes: image standardization and enhancement; region-based methods for pattern recognition in medical and astrophysical images; advanced information processing using statistical methods; and feature recognition and classification using spectral method.
(source: Nielsen Book Data)

• Chapter 1: Installation and Environment Setup
• Chapter Goal: Making System Ready for Image Processing and Analysis
• No of pages 20
• Sub -Topics (Top 2)
• 1.
• Installing Jupyter Notebook
• 2.
• Installing OpenCV and other Image Analysis dependencies
• 3.
• Installing Neural Network Dependencies
• Chapter 2: Introduction to Python and Image Processing
• Chapter Goal: Introduction to different concepts of Python and Image processing Application on it.
• No of pages: 50
• Sub - Topics (Top 2)
• 1. Essentials of Python
• 2. Terminologies related to Image Analysis
• Chapter 3: Advanced Image Processing using OpenCV
• Chapter Goal: Understanding Algorithms and their applications using Python
• No of pages: 100
• Sub - Topics (Top 2):
• 1.
• Operations on Images
• 2.
• Image Transformations
• Chapter 4: Machine Learning Approaches in Image Processing
• Chapter Goal: Basic Implementation of Machine and Deep Learning Models, which takes care of Image Processing, before applications in real-time scenario
• No of pages: 100
• Sub - Topics (Top 2):
• 1.
• Image Classification and Segmentation
• 2.
• Applying Supervised and Unsupervised Learning approaches on Images using Python
• Chapter 5: Real Time Use Cases
• Chapter Goal: Working on 5 projects using Python, applying all the concepts learned in this book
• No of pages: 100
• Sub - Topics (Top 5):
• 1. Facial Detection
• 2. Facial Recognition
• 3. Hand Gesture Movement Recognition
• 4. Self-Driving Cars Conceptualization: Advanced Lane Finding
• 5. Self-Driving Cars Conceptualization: Traffic Signs Detection
• Chapter 6: Appendix A
• Chapter Goal: Advanced concepts Introduction
• No of pages: 50
• Sub - Topics (Top 2):
• 1. AdaBoost and XGBoost
• 2. Pulse Coupled Neural Networks.
• (source: Nielsen Book Data)

Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You'll see the OpenCV algorithms and how to use them for image processing. The next section looks at advanced machine learning and deep learning methods for image processing and classification. You'll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you'll explore how models are made in real time and then deployed using various DevOps tools. All the concepts in Practical Machine Learning and Image Processing are explained using real-life scenarios. After reading this book you will be able to apply image processing techniques and make machine learning models for customized application. What You Will Learn Discover image-processing algorithms and their applications using Python Explore image processing using the OpenCV library Use TensorFlow, scikit-learn, NumPy, and other libraries Work with machine learning and deep learning algorithms for image processing Apply image-processing techniques to five real-time projects Who This Book Is For Data scientists and software developers interested in image processing and computer vision.
(source: Nielsen Book Data)

• Foreword. Introduction. Part I: Measuring Success. 1 Why Understanding Your Web Traffic Is Important to Your Business. 2 Available Methodologies. 3 Where Google Analytics Fits. Part II: Using Google Analytics Reports. 4 Using the Google Analytics Interface. 5 Top 10 Reports Explained Part III: Implementing Google Analytics. 6 Getting Started. 7 Advanced Implementation. 8 Best Practices Configuration Guide. 9 Google Analytics Hacks. Part IV: Using Visitor Data to Drive Website Improvement. 10 Focusing on Key Performance Indicators. 11 Real-World Tasks. 12 Integrating Google Analytics Data with Third-Party Systems. Appendix A Regular Expression Overview. Understanding the Fundamentals. Regex Examples. Appendix B Useful Tools. Tools to Audit Your GATC Deployment. Firefox Add-ons. Desktop Helper Applications. Appendix C Recommended Further Reading. Books on Web Analytics and Related Areas. Web Resources. Blog Roll for Web Analytics. Index.
• (source: Nielsen Book Data)

Packed with insider tips and tricks, this how-to guide is fully revised to cover the latest version of Google Analytics and shows you how to implement proven Web analytics methods and concepts. This second edition of the bestselling Advanced Web Metrics with Google Analytics is the perfect book for marketers, vendors, consultants, and Webmasters who want to learn the installation, configuration, tracking techniques, and best practices of Google Analytics.* Google Analytics is a free tool that measures Web site effectiveness and helps users better understand how web site performance; this book is a detailed usage guide written by one of the software's original creators* Explains what filters keep data accurate, how to measure Flash usage and tag for e-mail marketing, and what visitor segmentation provides the most useful feedback* Examines principles and practices of Web analytics, then shows how to use GA's reports and how to track dynamic Web pages, banners, outgoing links, and contact forms* Discusses advanced setups for configuring goals and filters, how to integrate GA with third-party systems, and how to leverage the new API Advanced Web Metrics with Google Analytics, Second Edition is valuable for both novice and experienced users of Google Analytics.
(source: Nielsen Book Data)

• Introduction Motivation Shape recognition Proposed method Objectives Assumptions and input data Book organization
• Preliminary knowledge Statistics Probability Random variable Expected value Variance and deviation Covariance and correlation Moment-generating function Fourier transform Structural and syntactic pattern recognition Introduction Grammar-based passing method Graph-based matching methods Neural network Architecture Learning process Summary
• Review of shape recognition techniques 2D shape recognition Shape representation Shape recognition approaches Logo recognition Statistical approach Syntactic/structural approach Neural network Hybrid approach Polygonal approximation Indexing Matching Distance measure Hausdorff distance Summary
• System overview Preprocessing Polygonal approximation Indexing Matching
• Polygonal approximation Feature point detection overview Dynamic two-strip algorithm The proposed method Results Comparison with other methods Summary
• Logo indexing Normalization Indexing Reference angle indexing (filter 1) Line orientation indexing (filters 2 and 3) Experimental results Summary
• Logo matching Hausdorff distance Modified LHD (MLHD) Experimental results Matching results Degradation analysis Results analysis with respect to the LHD and the MHD Discussion and comparison with other methods Summary
• Applications Mobile visual search with GetFugu Using logo recognition for anti-phishing and Internet brand monitoring The LogoTrace library Real-time vehicle logo recognition Summary
• Conclusion Book summary Contribution Future work Book conclusion References
• Appendix Test images Appendix Results of feature point detection
• Index.
• (source: Nielsen Book Data)

Used by companies, organizations, and even individuals to promote recognition of their brand, logos can also act as a valuable means of identifying the source of a document. E-business applications can retrieve and catalog products according to their logos. Governmental agencies can easily inspect goods using smart mobile devices that use logo recognition techniques. However, because logos are two-dimensional shapes of varying complexity, the recognition process can be challenging. Although promising results have been found for clean logos, they have not been as robust for noisy logos. Logo Recognition: Theory and Practice is the first book to focus on logo recognition, especially under noisy conditions. Beginning with an introduction to fundamental concepts and methods in pattern and shape recognition, it surveys advances in logo recognition. The authors also propose a new logo recognition system that can be used under adverse conditions such as broken lines, added noise, and occlusion. The proposed system introduces a novel polygonal approximation, a robust indexing scheme, and a new line segment Hausdorff distance (LHD) matching method that can handle more distortion and transformation types than previous techniques. In the first stage, raw logos are transformed into normalized line segment maps. In the second stage, effective line pattern features are used to index the database to generate a moderate number of likely models. In the third stage, an improved LHD measure screens and generates the best matches. A comprehensive overview of logo recognition, the book also presents successful applications of the technology and suggests directions for future research.
(source: Nielsen Book Data)

Extract patterns and knowledge from your data in easy way using MATLAB About This Book * Get your first steps into machine learning with the help of this easy-to-follow guide * Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB * Understand how your data works and identify hidden layers in the data with the power of machine learning. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well. What You Will Learn * Learn the introductory concepts of machine learning. * Discover different ways to transform data using SAS XPORT, import and export tools, * Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data. * Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment. * Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures. * Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox. * Learn feature selection and extraction for dimensionality reduction leading to improved performance. In Detail MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners. You'll start by getting your system ready with t he MATLAB environment for machine learning and you'll see how to easily interact with the Matlab workspace. We'll then move on to data cleansing, mining and analyzing various data types in machine learning and you'll see how to display data values on a plot. Next, you'll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You'll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you'll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB. Style and approach The book takes a very comprehensive approach to enhance your understanding of machine learning using MATLAB. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work.
(source: Nielsen Book Data)

• Foreword
• 1. The Semantic Web
• 2. Web Knowledge
• 3. Reactive Agents
• 4. Practical Reasoning and Deductive Agents
• 5. Reasoning on the Web
• 6. Agent Communication
• 7. Semantic Web Services
• 8. Conclusions
• Index.
• (source: Nielsen Book Data)

This highly topical text considers the construction of the next generation of the Web, called the Semantic Web. This will enable computers to automatically consume Web-based information, overcoming the human-centric focus of the Web as it stands at present, and expediting the construction of a whole new class of knowledge-based applications that will intelligently utilise Web content. The text is structured into three main sections on knowledge representation techniques, reasoning with multi-agent systems, and knowledge services. For each of these topics, the text provides an overview of the state-of-the-art techniques and the popular standards that have been defined. Numerous small programming examples are given, which demonstrate how the benefits of the Semantic Web technologies can be realised at the present time. The main theoretical results underlying each of the technologies are presented, and the main problems and research issues which remain are summarised. Based on a course on 'Multi-Agent Systems and the Semantic Web' taught at the University of Edinburgh, this text is ideal for final-year undergraduate and graduate students in Mathematics, Computer Science, Artificial Intelligence, and Logic and researchers interested in Multi-Agent Systems and the Semantic Web.
(source: Nielsen Book Data)

• 1. Introduction
• 2. Clusters and robots
• 3. Cluster programming
• 4. Robot motion
• 5. Sensors
• 6. Mapping and localization
• 7. Vision and tracking
• 8. Learning landmarks
• 9. Robot architectures
• Appendix I: Summary of OpenMPI man page for mpirun
• Appendix II: MPI datatypes
• Appendix III: MPI reduction operations
• Appendix IV: MPI application programmer interface.

In this book, we look at how cluster technology can be leveraged to build better robots. Algorithms and approaches in key areas of robotics and computer vision, such as map building, target tracking, action selection and landmark learning, are reviewed and cluster implementations for these are presented.The objective of the book is to give professionals working in the beowulf cluster or robotics and computer vision fields a concrete view of the strong synergy between the areas as well as to spur further fruitful exploitation of this connection. The book is written at a level appropriate for an advanced undergraduate or graduate student. The key concepts in robotics, computer vision and cluster computing are introduced before being used to make the text useful to a wide audience in these fields.
(source: Nielsen Book Data)

• Introduction, C.H. Chen
• combined neural-net/knowledge-based adaptive systems for large scale dynamic control, A.D.C. Holden and S.C. Suddarth
• a connectionist incremental expert system combining production systems and associative memory, H.F. Yin and P. Liang
• optimal hidden units for two-layer nonlinear feedforward networks, T.D. Sanger
• an incremental fine adjustment algorithm for the design of optimal interpolating networks, S.K. Sin and R.J.P. deFigueiredo
• on the asymptotic properties of recurrent neural networks for optimization, J. Wang
• a real-time image segmentation system using a connectionist classifier architecture, W.E. Blanz and S.L. Gish
• segmentation of ultrasonic images with neural network technology's on automatic active sonar classifier development, T.B. Haley
• on the relationships between statistical pattern recognition and artificial neural networks, C.H. Chen.
• (source: Nielsen Book Data)

The revitalization of neural network research in the past few years has already had a great impact on research and development in pattern recognition and artificial intelligence. Although neural network functions are not limited to pattern recognition, there is no doubt that a renewed progress in pattern recognition and its applications now critically depends on neural networks. This volume specially brings together outstanding original research papers in the area and aims to help the continued progress in pattern recognition and its applications.
(source: Nielsen Book Data)

• Preface
• Special Topics in Pattern Recognition with Applications in Nonprofileration
• Manufacturing Feature Recognition for Mould & Die Designs: Current Status & Future Directions
• Pattern-Recognition Receptors of Oral Epithelia
• Generating-Kernel Based Nonlinear Feature Extraction Methods
• Damage Assessment Based on Pattern Recognition
• Artificial Intelligence Techniques for Assisting the Decision of Making or Postponing the Embryo Transfer
• New Perspectives on a Pattern Recognition Algorithm Based on Haken's Synergetic Computer Network- With a Comment on Artificial Intelligence & Physical Intelligence
• Active Contours for Real Time Applications
• Class Distribution Estimation in Imprecise Domains Based on Supervised Learning
• Quantitative Bioimage Analysis Using Pattern Recognition
• Advances in Mining Emerging Patterns for Supervised Classification
• On the Geometrical Aspect of Biometric Authentication
• Pattern Recognition as a New Method of Numerical Research of the Concrete Dynamic System
• Pattern Recognition from ICA Mixture Modeling
• Index.
• (source: Nielsen Book Data)

Pattern recognition involves tasks such as pattern identification, feature extraction from them and pattern classification in categories, based on the extracted features. This book presents topical research in the study of pattern recognition, including pattern recognition applications in non-proliferation; pattern recognition of machine feature identifications; pattern recognition receptors of oral epithelia; construction damage assessment based on pattern recognition; Haken's pattern recognition algorithm as applied in engineering sciences; active contours for real time applications and quantitative bioimage analysis using pattern recognition.
(source: Nielsen Book Data)

• Title page; Preface; Contents; Part I: General Purpose Applications of AI; Supervised Machine Learning: A Review of Classification Techniques; Dimension Reduction and Data Visualization Using Neural Networks; Recommender System Technologies Based on Argumentation; Knowledge Modelling Using UML Profile for Knowledge-Based Systems Development; A Semantic-Based Navigation Approach for Information Retrieval in the Semantic Web; Ontology-Based Management of Pervasive Systems; A DIYD (Do It Yourself Design) e-Commerce System for Vehicle Design Based on Ontologies and 3D Visualization.

Provides insights on how computer engineers can implement artificial intelligence (AI) in real world applications. This book presents practical applications of AI.

• 1. The vision of sociable robots
• 2. Robot in society: a question of interface
• 3. Insights from developmental psychology
• 4. Designing sociable robots
• 5. The physical robot
• 6. The vision system
• 7. The auditory system
• 8. The motivation system
• 9. The behavior system
• 10. Facial animation and expression
• 11. Expressive vocalization system
• 12. Social constraints on animate vision
• 13. Grand challenges of building sociable robots.

Cynthia Breazeal here presents her vision of the sociable robot of the future, a synthetic creature and not merely a sophisticated tool. A sociable robot will be able to understand us, to communicate and interact with us, to learn from us and grow with us. It will be socially intelligent in a humanlike way. Eventually sociable robots will assist us in our daily lives, as collaborators and companions. Because the most successful sociable robots will share our social characteristics, the effort to make sociable robots is also a means for exploring human social intelligence and even what it means to be human. Breazeal defines the key components of social intelligence for these machines and offers a framework and set of design issues for their realization. Much of the book focuses on a nascent sociable robot she designed named Kismet. Breazeal offers a concrete implementation for Kismet, incorporating insights from the scientific study of animals and people, as well as from artistic disciplines such as classical animation. This blending of science, engineering, and art creates a lifelike quality that encourages people to treat Kismet as a social creature rather than just a machine. The book includes a CD-ROM that shows Kismet in action.
(source: Nielsen Book Data)

• Cover; Title page; Preface; Contents;
• 1. Introduction to Neural Networks for Instrumentation, Measurement, and Industrial Applications;
• 2. The Fundamentals of Measurement Techniques;
• 3. Neural Networks in Intelligent Sensors and Measurement Systems for Industrial Applications;
• 4. Neural Networks in System Identification;
• 5. Neural Techniques in Control;
• 6. Neural Networks for Signal Processing in Measurement Analysis and Industrial Applications: the Case of Chaotic Signal Processing.

This work aims to disseminate theoretical and practical knowledge about neural networks in measurement, instrumentation and the related industrial applications. It also creates a consciousness about the effectiveness of these techniques as well as the measurement problems in industrial environments.

• pt. I. Technology. Robust layered control system for a mobile robot
• Robot that walks: emergent behaviors from a carefully evolved network
• Learning a distributed map representation based on navigation behaviors
• New approaches to robotics. pt. II. Philosophy. Intelligence without representation
• Planning is just a way of avoiding figuring out what to do next
• Elephants don't play chess
• Intelligence without reason.

Until the mid-1980s, AI researchers assumed that an intelligent system doing high-level reasoning was necessary for the coupling of perception and action. In this traditional model, cognition mediates between perception and plans of action. Realizing that this core AI, as it was known, was illusory, Rodney A. Brooks turned the field of AI on its head by introducing the behavior-based approach to robotics. The cornerstone of behavior-based robotics is the realization that the coupling of perception and action gives rise to all the power of intelligence and that cognition is only in the eye of an observer. Behavior-based robotics has been the basis of successful applications in entertainment, service industries, agriculture, mining, and the home. It has given rise to both autonomous mobile robots and more recent humanoid robots such as Brooks' Cog. This book represents Brooks' initial formulation of and contributions to the development of the behavior-based approach to robotics. It presents all of the key philosophical and technical ideas that put this "bottom-up" approach at the forefront of current research in not only AI but all of cognitive science.
(source: Nielsen Book Data)

• PREFACE. NOTATION.
• 1 Introduction. 1.1 Learning and Statistical Estimation. 1.2 Statistical Dependency and Causality. 1.3 Characterization of Variables. 1.4 Characterization of Uncertainty. 1.5 Predictive Learning versus Other Data Analytical Methodologies.
• 2 Problem Statement, Classical Approaches, and Adaptive Learning. 2.1 Formulation of the Learning Problem. 2.1.1 Objective of Learning. 2.1.2 Common Learning Tasks. 2.1.3 Scope of the Learning Problem Formulation. 2.2 Classical Approaches. 2.2.1 Density Estimation. 2.2.2 Classification. 2.2.3 Regression. 2.2.4 Solving Problems with Finite Data. 2.2.5 Nonparametric Methods. 2.2.6 Stochastic Approximation. 2.3 Adaptive Learning: Concepts and Inductive Principles. 2.3.1 Philosophy, Major Concepts, and Issues. 2.3.2 A Priori Knowledge and Model Complexity. 2.3.3 Inductive Principles. 2.3.4 Alternative Learning Formulations. 2.4 Summary.
• 3 Regularization Framework. 3.1 Curse and Complexity of Dimensionality. 3.2 Function Approximation and Characterization of Complexity. 3.3 Penalization. 3.3.1 Parametric Penalties. 3.3.2 Nonparametric Penalties. 3.4 Model Selection (Complexity Control). 3.4.1 Analytical Model Selection Criteria. 3.4.2 Model Selection via Resampling. 3.4.3 Bias-Variance Tradeoff. 3.4.4 Example of Model Selection. 3.4.5 Function Approximation versus Predictive Learning. 3.5 Summary.
• 4 Statistical Learning Theory. 4.1 Conditions for Consistency and Convergence of ERM. 4.2 Growth Function and VC Dimension. 4.2.1 VC Dimension for Classification and Regression Problems. 4.2.2 Examples of Calculating VC Dimension. 4.3 Bounds on the Generalization. 4.3.1 Classification. 4.3.2 Regression. 4.3.3 Generalization Bounds and Sampling Theorem. 4.4 Structural Risk Minimization. 4.4.1 Dictionary Representation. 4.4.2 Feature Selection. 4.4.3 Penalization Formulation. 4.4.4 Input Preprocessing. 4.4.5 Initial Conditions for Training Algorithm. 4.5 Comparisons of Model Selection for Regression. 4.5.1 Model Selection for Linear Estimators. 4.5.2 Model Selection for k-Nearest-Neighbor Regression. 4.5.3 Model Selection for Linear Subset Regression. 4.5.4 Discussion. 4.6 Measuring the VC Dimension. 4.7 VC Dimension, Occam's Razor, and Popper's Falsifiability. 4.8 Summary and Discussion.
• 5 Nonlinear Optimization Strategies. 5.1 Stochastic Approximation Methods. 5.1.1 Linear Parameter Estimation. 5.1.2 Backpropagation Training of MLP Networks. 5.2 Iterative Methods. 5.2.1 EM Methods for Density Estimation. 5.2.2 Generalized Inverse Training of MLP Networks. 5.3 Greedy Optimization. 5.3.1 Neural Network Construction Algorithms. 5.3.2 Classification and Regression Trees. 5.4 Feature Selection, Optimization, and Statistical Learning Theory. 5.5 Summary.
• 6 Methods for Data Reduction and Dimensionality Reduction. 6.1 Vector Quantization and Clustering. 6.1.1 Optimal Source Coding in Vector Quantization. 6.1.2 Generalized Lloyd Algorithm. 6.1.3 Clustering. 6.1.4 EM Algorithm for VQ and Clustering. 6.1.5 Fuzzy Clustering. 6.2 Dimensionality Reduction: Statistical Methods. 6.2.1 Linear Principal Components. 6.2.2 Principal Curves and Surfaces. 6.2.3 Multidimensional Scaling. 6.3 Dimensionality Reduction: Neural Network Methods. 6.3.1 Discrete Principal Curves and Self-Organizing Map Algorithm. 6.3.2 Statistical Interpretation of the SOM Method. 6.3.3 Flow-Through Version of the SOM and Learning Rate Schedules. 6.3.4 SOM Applications and Modifications. 6.3.5 Self-Supervised MLP. 6.4 Methods for Multivariate Data Analysis. 6.4.1 Factor Analysis. 6.4.2 Independent Component Analysis. 6.5 Summary.
• 7 Methods for Regression. 7.1 Taxonomy: Dictionary versus Kernel Representation. 7.2 Linear Estimators. 7.2.1 Estimation of Linear Models and Equivalence of Representations. 7.2.2 Analytic Form of Cross-Validation. 7.2.3 Estimating Complexity of Penalized Linear Models. 7.2.4 Nonadaptive Methods. 7.3 Adaptive Dictionary Methods. 7.3.1 Additive Methods and Projection Pursuit Regression. 7.3.2 Multilayer Perceptrons and Backpropagation. 7.3.3 Multivariate Adaptive Regression Splines. 7.3.4 Orthogonal Basis Functions and Wavelet Signal Denoising. 7.4 Adaptive Kernel Methods and Local Risk Minimization. 7.4.1 Generalized Memory-Based Learning. 7.4.2 Constrained Topological Mapping. 7.5 Empirical Studies. 7.5.1 Predicting Net Asset Value (NAV) of Mutual Funds. 7.5.2 Comparison of Adaptive Methods for Regression. 7.6 Combining Predictive Models. 7.7 Summary.
• 8 Classification. 8.1 Statistical Learning Theory Formulation. 8.2 Classical Formulation. 8.2.1 Statistical Decision Theory. 8.2.2 Fisher's Linear Discriminant Analysis. 8.3 Methods for Classification. 8.3.1 Regression-Based Methods. 8.3.2 Tree-Based Methods. 8.3.3 Nearest-Neighbor and Prototype Methods. 8.3.4 Empirical Comparisons. 8.4 Combining Methods and Boosting. 8.4.1 Boosting as an Additive Model. 8.4.2 Boosting for Regression Problems. 8.5 Summary.
• 9 Support Vector Machines. 9.1 Motivation for Margin-Based Loss. 9.2 Margin-Based Loss, Robustness, and Complexity Control. 9.3 Optimal Separating Hyperplane. 9.4 High-Dimensional Mapping and Inner Product Kernels. 9.5 Support Vector Machine for Classification. 9.6 Support Vector Implementations. 9.7 Support Vector Regression. 9.8 SVM Model Selection. 9.9 Support Vector Machines and Regularization. 9.10 Single-Class SVM and Novelty Detection. 9.11 Summary and Discussion.
• 10 Noninductive Inference and Alternative Learning Formulations. 10.1 Sparse High-Dimensional Data. 10.2 Transduction. 10.3 Inference Through Contradictions. 10.4 Multiple-Model Estimation. 10.5 Summary.
• 11 Concluding Remarks. Appendix A: Review of Nonlinear Optimization. Appendix B: Eigenvalues and Singular Value Decomposition. References. Index.
• (source: Nielsen Book Data)

An interdisciplinary framework for learning methodologies-covering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be applied-showing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science. Complete with over one hundred illustrations, case studies, and examples making this an invaluable text.
(source: Nielsen Book Data)

• Low-level preprocessing, surveillance systems
• Tracking, robotics
• Identification, detection, recognition
• Behavior, activities, crowd analysis.

This book constitutes the refereed proceedings of the 4th Chinese Conference, IVS 2016, held in Beijing, China, in October 2016. The 19 revised full papers presented were carefully reviewed and selected from 45 submissions. The papers are organized in topical sections on low-level preprocessing, surveillance systems; tracking, robotics; identification, detection, recognition; behavior, activities, crowd analysis.

• Computer graphics.-Applications
• Visual Surveillance
• Virtual Reality.

The two volume set LNCS 10072 and LNCS 10073 constitutes the refereed proceedings of the 12th International Symposium on Visual Computing, ISVC 2016, held in Las Vegas, NV, USA in December 2016. The 102 revised full papers and 34 poster papers presented in this book were carefully reviewed and selected from 220 submissions. The papers are organized in topical sections: Part I (LNCS 10072) comprises computational bioimaging; computer graphics; motion and tracking; segmentation; pattern recognition; visualization; 3D mapping; modeling and surface reconstruction; advancing autonomy for aerial robotics; medical imaging; virtual reality; computer vision as a service; visual perception and robotic systems; and biometrics. Part II (LNCS 9475): applications; visual surveillance; computer graphics; and virtual reality.