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• 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)

• 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.

• 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.

• 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)

• 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)

• 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)

• 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)

• 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)

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)