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• 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)

• Data analytics and optimization for assessing a ride sharing system.- Constraint-Based Querying for Bayesian Network Exploration.- Efficient Model Selection for Regularized Classification by Exploiting Unlabeled Data.- Segregation Discovery in a Social Network of Companies.- A first+-order-logic based model for grounded language learning.- A parallel distributed processing algorithm for image feature extraction.- Modeling concept drift: A probabilistic graphical model based approach.- Diversity-driven Widening of Hierarchical Agglomerative Clustering.- Batch Steepest-Descent-Mildest-Ascent for Interactive Maximum Margin Clustering.- Time Series Classification with Representation Ensembles.- Simultaneous Clustering and Model Selection for Multinomial Distribution: A Comparative Study.- On Binary Reduction of Large-scale Multiclass Classification Problems.- Probabilistic Active Learning in Data Streams.- Implicitly Constrained Semi-Supervised Least Squares Classification.- Diagonal Co-clustering Algorithm for Document-Word Partitioning.- I-Louvain: an attributed graph clustering method.- Class-based outlier detection: staying zombies or awaiting for resurrection?.- Using Metalearning for Prediction of Taxi Trip Duration Using Different Granularity Levels.- Using entropy as a measure of acceptance for multi-label classification.- Investigation of Node Deletion Techniques for Clustering Applications of Growing Self Organizing Maps.- Exploratory topic modeling with distributional semantics.- Assigning Geo-Relevance of Sentiments Mined from Location-Based Social Media Posts.- Continuous and Discrete Deep Classifiers for Data Integration.- A Bayesian Approach for Identifying Multivariate Differences Between Groups.- Automatically Discovering Offensive Patterns in Soccer Match Data.- Fast Algorithm Selection using Learning Curves.- Optimally Weighted Cluster Kriging for Big Data Regression.- Slower can be faster: The iRetis incremental model tree learner.- VoQs: A Web Application for Visualization of Questionnaire Surveys.
• (source: Nielsen Book Data)

This book constitutes the refereed conference proceedings of the 14th International Conference on Intelligent Data Analysis, which was held in October 2015 in Saint Etienne. France. The 29 revised full papers were carefully reviewed and selected from 65 submissions. The traditional focus of the IDA symposium series is on end-to-end intelligent support for data analysis. The symposium aims to provide a forum for inspiring research contributions that might be considered preliminary in other leading conferences and journals, but that have a potentially dramatic impact. To facilitate this, IDA 2015 will feature two tracks: a regular "Proceedings" track, as well as a "Horizon" track for early-stage research of potentially ground-breaking nature.
(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)

• 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.

• Visualization and big data.- Machine learning and computer vision.- Computer graphics.- Virtual reality.
• (source: Nielsen Book Data)

This book constitute the refereed proceedings of the Fourth International Conference on Advances in Visual Informatics, IVIC 2015, held in Selangor, Malaysia, in November 2015. The five keynotes and 45 papers presented were carefully reviewed and selected from various submissions. The papers are organized in four tracks on visualization and big data; machine learning and computer vision; computer graphics; virtual reality.
(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)

• Plane and Planarity Thresholds for Random Geometric Graphs.- Connectivity of a dense mesh of randomly oriented directional antennas under a realistic fading model.- Maintaining Intruder Detection Capability in a Rectangular Domain with Sensors.- The Weakest Oracle for Symmetric Consensus in Population Protocols.- Exact and Approximation Algorithms for Data Mule Scheduling in a Sensor Network.- Limitations of Current Wireless Scheduling Algorithms.- Deterministic rendezvous with detection using beeps.- Minimizing total sensor movement for barrier coverage by non-uniform sensors on a line.- A comprehensive and lightweight security architecture to secure the IoT throughout the lifecycle of a device based on HIMMO.- Maximizing Throughput in Energy-Harvesting Sensor Nodes.- On verifying and maintaining connectivity of interval temporal networks.- Beachcombing on Strips and Islands.- Radio Aggregation Scheduling.- Gathering of Robots on Meeting-Points.- Mutual Visibility with an Optimal Number of Colors.- Mobile Agents Rendezvous in spite of a Malicious Agent.
• (source: Nielsen Book Data)

This book constitutes revised selected papers from the 11th International Symposium on Algorithms and Experiments for Wireless Sensor Networks, ALGOSENSORS 2015, held in Patras, Greece, in September 2015. The 16 full papers presented in this volume were carefully reviewed and selected from 30 submissions. The deal with algorithms analysis and problem complexity; computer communication networks; computation by abstract devices; and mathematics of computing.
(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)

• 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)

• Learning sequential data with the help of linear systems
• A spiking neural network for personalised modelling of Electrogastogrophy (EGG)
• Improving generalization abilities of maximal average margin classifiers
• Finding small sets of random Fourier features for shift-invariant kernel approximation
• Incremental construction of low-dimensional data representations
• Soft-constrained nonparametric density estimation with artificial neural networks
• Density based clustering via dominant sets
• Co-training with credal models
• Interpretable classifiers in precision medicine: feature selection and multi-class categorization
• On the evaluation of tensor-based representations for optimum-pathforest classification
• On the harmony search using quaternions
• Learning parameters in deep belief networks through firefly algorithm
• Towards effective classification of imbalanced data with convolutional neural networks
• On CPU performance optimization of restricted Boltzmann machine and convolutional RBM
• Comparing incremental learning strategies for convolutional neural networks
• Approximation of graph edit distance by means of a utility matrix
• Time series classification in reservoir- and model-space: a comparison
• Objectness scoring and detection proposals in forward-Looking sonar images with convolutional neural networks
• Background categorization for automatic animal detection in aerial videos using neural networks
• Predictive segmentation using multichannel neural networks in Arabic OCR system
• Quad-tree based image segmentation and feature extraction to recognize online handwritten Bangla characters
• A hybrid recurrent neural network/dynamic probabilistic graphical model predictor of the disulfide bonding state of cysteines from the primary structure of proteins
• Using radial basis function neural networks for continuous anddiscrete pain estimation from bio-physiological signals
• Active learning for speech event detection in HCI
• Emotion recognition in speech with deep learning architectures
• On gestures and postural behavior as a modality in ensemble methods
• Machine learning driven heart rate detection with camera photoplethysmography in time domain.

This book constitutes the refereed proceedings of the 7th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2016, held in Ulm, Germany, in September 2016. The 25 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 32 submissions for inclusion in this volume. The workshop will act as a major forum for international researchers and practitioners working in all areas of neural network- and machine learning-based pattern recognition to present and discuss the latest research, results, and ideas in these areas.

• 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)

• 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.

• 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)

• 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)

• 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)

• 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.

• Cognitive Radio Architecture
• Collaborative Adaptation
• Signaling Options
• Agent Communication Language
• An Example: Collaborative Link Adaptation
• Knowledge and Inference
• Cognitive Radio Ontology
• Implementation of Collaborative Link Optimization
• Evaluations.

This book provides an introduction to software-defined radio and cognitive radio, along with methodologies for applying knowledge representation, semantic web, logic reasoning and artificial intelligence to cognitive radio, enabling autonomous adaptation and flexible signaling. Readers from the wireless communications and software-defined radio communities will use this book as a reference to extend software-defined radio to cognitive radio, using the semantic technology described. Readers with a background in semantic web and artificial intelligence will find in this book the application of semantic web and artificial intelligence technologies to wireless communications. For readers in networks and network management, this book presents a new approach to enable interoperability, collaborative optimization and flexible adaptation of network components. Provides a comprehensive ontology covering the core concepts of wireless communications using a formal language; Presents the technical realization of using a formal language to exchange control messages, achieving autonomous adaptation of a communications link; Describes an architecture that enables radios to use a formal language to send inquiries and requests to other nodes, accept, interpret and execute such requests using their local policies and modify their own parameters.

• A Representational Analysis of the API4KP Metamodel
• Ontologies for Business Networks Identification
• Ontology Mapping in an E-Commerce Application
• Ontologies in the Realm of Enterprise Modeling
• a Reality Check
• Experience of Formal Application Ontology Development to Enhance User Understanding in a Geo Business Intelligence SaaS Platform
• An Ontology-Based Architecture for Storage Management
• Toward an Ontological Formalization of Technical Product for Design and Manufacturing
• Developing an Ontology for Joints in Furniture Design
• Created in Closed Interaction with the Industry: The Smart Appliances REFerence (SAREF) Ontology
• An Ontology for Global Production Network Design and Reconfiguration
• Ontology in Engineering Applications.

This book constitutes the proceedings of the 7th International Formal Ontologies Meet Industries Workshop held in Berlin, Germany, in August 2015. The 11 full research papers accepted for FOMI 2015 were selected from 18 submissions. The papers focus on theoretical studies of formal ontologies committed to provide a sound basis for industrial applications and to allow formal representation of corporate knowledge, and on business experiences in case studies that single out concrete problems and possible solutions in the creation and deployment of formal ontologies. Overall, they provide valuable insights into the current state of progress in supporting industrial information and knowledge sharing through the development of formal ontologies.

• Discrete-Time Signals and Circuits Fundamentals.- Introduction to Adaptive Signal Processing.- Optimal Linear Filter Theory.- Least Squares Method.- First Order Adaptive Algorithms.- Second Order Adaptive Algorithms.- Block and Transform Domain Algorithms.- Linear Prediction and Recursive Order Algorithms.- Discrete Space-Time Filtering.- Appendix A: Linear Algebra Foundation.- Appendix B: Non Linear Programming Fundamentals.-Appendix C: Random Variables, Stochastic Processes and Estimation Theory.
• (source: Nielsen Book Data)

This book is an accessible guide to adaptive signal processing methods that equips the reader with advanced theoretical and practical tools for the study and development of circuit structures and provides robust algorithms relevant to a wide variety of application scenarios. Examples include multimodal and multimedia communications, the biological and biomedical fields, economic models, environmental sciences, acoustics, telecommunications, remote sensing, monitoring and in general, the modeling and prediction of complex physical phenomena. The reader will learn not only how to design and implement the algorithms but also how to evaluate their performance for specific applications utilizing the tools provided. While using a simple mathematical language, the employed approach is very rigorous. The text will be of value both for research purposes and for courses of study.
(source: Nielsen Book Data)