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Annotation The Symposium series refers to all apects of theory, algorithm design, applications and emerging techniques related to computational intelligence.

• CHAPTER 1 Introduction
• CHAPTER 2 Accelerated Algorithms for Unconstrained Convex Optimization
• 1. Preliminaries
• 2. Accelerated Gradient Method for smooth optimization
• 3. Extension to the Composite Optimization
• 3.1. Nesterov's First Scheme
• 3.2. Nesterov's Second Scheme
• 3.2.1. A Primal Dual Perspective
• 3.3. Nesterov's Third Scheme
• 4. Inexact Proximal and Gradient Computing
• 4.1. Inexact Accelerated Gradient Descent
• 4.2. Inexact Accelerated Proximal Point Method
• 5. Restart
• 6. Smoothing for Nonsmooth Optimization
• 7. Higher Order Accelerated Method
• 8. Explanation: An Variational Perspective
• 8.1. Discretization
• CHAPTER 3 Accelerated Algorithms for Constrained Convex Optimization
• 1. Preliminaries
• 1.1. Case Study: Linear Equality Constraint
• 2. Accelerated Penalty Method
• 2.1. Non-strongly Convex Objectives
• 2.2. Strong Convex Objectives
• 3. Accelerated Lagrange Multiplier Method
• 3.1. Recovering the Primal Solution
• 3.2. Accelerated Augmented Lagrange Multiplier Method
• 4. Accelerated Alternating Direction Method of Multipliers
• 4.1. Non-strongly Convex and Non-smooth
• 4.2. Strongly Convex and Non-smooth
• 4.3. Non-strongly Convex and Smooth
• 4.4. Strongly Convex and Smooth
• 4.5. Non-ergodic Convergence Rate
• 4.5.1. Original ADMM
• 4.5.2. ADMM with Extrapolation and Increasing Penalty Parameter
• 5. Accelerated Primal Dual Method
• 5.1. Case 1
• 5.2. Case 2
• 5.3. Case 3
• 5.4. Case 4
• CHAPTER 4 Accelerated Algorithms for Nonconvex Optimization
• 1. Proximal Gradient with Momentum
• 1.1. Basic Assumptions
• 1.2. Convergence Theorem
• 1.3. Another Method: Monotone APG
• 2. AGD Achieves the Critical Points Quickly
• 2.1. AGD as a Convexity Monitor
• 2.2. Negative Curvature
• 2.3. Accelerating Nonconvex Optimization
• 3. AGD Escapes the Saddle Points Quickly
• 3.1. Almost Convex
• 3.2. Negative Curvature Descent
• 3.3. AGD for Non-Convex Problem
• 3.3.1. Locally Almost Convex! Globally Almost Convex
• 3.3.2. Outer Iterations
• 3.3.3. Inner Iterations
• CHAPTER 5 Accelerated Stochastic Algorithms
• 1. The Individual Convexity Case
• 1.1. Accelerated Stochastic Coordinate Descent
• 1.2. Background for Variance Reduction Methods
• 1.3. Accelerated Stochastic Variance Reduction Method
• 1.4. Black-Box Acceleration
• 2. The Individual Non-convexity Case
• 2.1. Individual Non-convex but Integrally Convex
• 3. The Non-Convexity Case
• 3.1. SPIDER
• 3.2. Momentum Acceleration
• 4. Constrained Problem
• 5. Infinity Case
• CHAPTER 6 Paralleling Algorithms
• 1. Accelerated Asynchronous Algorithms
• 1.1. Asynchronous Accelerated Gradient Descent
• 1.2. Asynchronous Accelerated Stochastic Coordinate Descent
• 2. Accelerated Distributed Algorithms
• 2.1. Centralized Topology
• 2.1.1. Large Mini-batch Algorithms
• 2.1.2. Dual Communication-Efficient Methods
• 2.2. Decentralized Topology
• CHAPTER 7 Conclusions
• APPENDIX Mathematical Preliminaries.
• (source: Nielsen Book Data)

This book on optimization includes forewords by Michael I. Jordan, Zongben Xu and Zhi-Quan Luo. Machine learning relies heavily on optimization to solve problems with its learning models, and first-order optimization algorithms are the mainstream approaches. The acceleration of first-order optimization algorithms is crucial for the efficiency of machine learning. Written by leading experts in the field, this book provides a comprehensive introduction to, and state-of-the-art review of accelerated first-order optimization algorithms for machine learning. It discusses a variety of methods, including deterministic and stochastic algorithms, where the algorithms can be synchronous or asynchronous, for unconstrained and constrained problems, which can be convex or non-convex. Offering a rich blend of ideas, theories and proofs, the book is up-to-date and self-contained. It is an excellent reference resource for users who are seeking faster optimization algorithms, as well as for graduate students and researchers wanting to grasp the frontiers of optimization in machine learning in a short time.
(source: Nielsen Book Data)

• Introduction.- Part 1:Background and Methodology.- Discrete Consensus Achievement in Artificial Systems.- Modular Design of Strategies for the Best-of-n Problem.- Part 2:Mathematical Modeling and Analysis.- Indirect Modulation of Majority-Based Decisions.- Direct Modulation of Voter-Based Decisions.- Direct Modulation of Majority-Based Decisions.- Part 3:Robot Experiments.- A Robot Experiment in Site Selection.- A Robot Experiment in Collective Perception.- Part 4:Discussion and Annexes.- Conclusions.- Background on Markov Chains.
• (source: Nielsen Book Data)

This book focuses on the design and analysis of collective decision-making strategies for the best-of-n problem. After providing a formalization of the structure of the best-of-n problem supported by a comprehensive survey of the swarm robotics literature, it introduces the functioning of a collective decision-making strategy and identifies a set of mechanisms that are essential for a strategy to solve the best-of-n problem. The best-of-n problem is an abstraction that captures the frequent requirement of a robot swarm to choose one option from of a finite set when optimizing benefits and costs. The book leverages the identification of these mechanisms to develop a modular and model-driven methodology to design collective decision-making strategies and to analyze their performance at different level of abstractions. Lastly, the author provides a series of case studies in which the proposed methodology is used to design different strategies, using robot experiments to show how the designed strategies can be ported to different application scenarios.
(source: Nielsen Book Data)

• Automating Inquiry Uncertainty Sampling Searching Through the Hypothesis Space Minimizing Expected Error and Variance Exploiting Structure in Data Theory Practical Considerations.
• (source: Nielsen Book Data)

The key idea behind active learning is that a machine learning algorithm can perform better with less training if it is allowed to choose the data from which it learns. An active learner may pose ""queries, "" usually in the form of unlabeled data instances to be labeled by an ""oracle"" (e.g., a human annotator) that already understands the nature of the problem. This sort of approach is well-motivated in many modern machine learning and data mining applications, where unlabeled data may be abundant or easy to come by, but training labels are difficult, time-consuming, or expensive to obtain. This book is a general introduction to active learning. It outlines several scenarios in which queries might be formulated, and details many query selection algorithms which have been organized into four broad categories, or ""query selection frameworks."" We also touch on some of the theoretical foundations of active learning, and conclude with an overview of the strengths and weaknesses of these approaches in practice, including a summary of ongoing work to address these open challenges and opportunities.
(source: Nielsen Book Data)

• Part I: Basics and Theory
• Photometry
• Geometry
• Sensors
• Light Sources
• Part II: Algorithms Photometric stereo
• Structured light
• Other shape reconstruction techniques
• Photometric estimation Part III: Applications
• Visualization, Augmented Reality, Virtual Reality, and Mixed Reality Systems
• Biomedical Applications
• E-Heritage
• Robot Vision, Autonomous Vehicles, and Humans.
• (source: Nielsen Book Data)

This book describes active illumination techniques in computer vision. We can classify computer vision techniques into two classes: passive and active techniques. Passive techniques observe the scene statically and analyse it as is. Active techniques give the scene some actions and try to facilitate the analysis. In particular, active illumination techniques project specific light, for which the characteristics are known beforehand, to a target scene to enable stable and accurate analysis of the scene. Traditional passive techniques have a fundamental limitation. The external world surrounding us is three-dimensional; the image projected on a retina or an imaging device is two-dimensional. That is, reduction of one dimension has occurred. Active illumination techniques compensate for the dimensional reduction by actively controlling the illumination. The demand for reliable vision sensors is rapidly increasing in many application areas, such as robotics and medical image analysis. This book explains this new endeavour to explore the augmentation of reduced dimensions in computer vision. This book consists of three parts: basic concepts, techniques, and applications. The first part explains the basic concepts for understanding active illumination techniques. In particular, the basic concepts of optics are explained so that researchers and engineers outside the field can understand the later chapters. The second part explains currently available active illumination techniques, covering many techniques developed by the authors. The final part shows how such active illumination techniques can be applied to various domains, describing the issue to be overcome by active illumination techniques and the advantages of using these techniques. This book is primarily aimed at 4th year undergraduate and 1st year graduate students, and will also help engineers from fields beyond computer vision to use active illumination techniques. Additionally, the book is suitable as course material for technical seminars.
(source: Nielsen Book Data)

• Cover; Title page; Preface; Acknowledgments; Contents; I. Data Collection; Toward Active Mining from On-line Scientific Text Abstracts Using Pre-existing Sources; Data Mining on the WAVEs
• Word-of-mouth-Assisting Virtual Environments; Immune Network-based Clustering for WWW Information Gathering/Visualization; Interactive Web Page Retrieval with Relational Learning-based Filtering Rules; Monitoring Partial Update of Web Pages by Interactive Relational Learning; Context-based Classification of Technical Terms Using Support Vector Machines.

Focusing on data mining, this work is a joint effort from researchers in Japan, and includes a report on the forefront of data collection, user-centred mining and user interaction/reaction. It offers an overview of modern solutions with real-world applications, sharing hard-learned experiences.

• Introduction.- RelatedWork and Background.- Theoretical Analysis of Differential Evolution.- Parameter Adaptive Differential Evolution.- Surrogate Model-based Differential Evolution.- Adaptive Multi-Objective Differential Evolution.- Application to Winner Determination Problems in Combinatorial Auctions.- Application to Flight Planning in Air Traffic Control Systems.- Application to the TPM Optimization in Credit Decision Making.- Conclusions and Future Work.
• (source: Nielsen Book Data)

Optimization problems are ubiquitous in academic research and real-world applications wherever such resources as space, time and cost are limited. Researchers and practitioners need to solve problems fundamental to their daily work which, however, may show a variety of challenging characteristics such as discontinuity, nonlinearity, nonconvexity, and multimodality. It is expected that solving a complex optimization problem itself should easy to use, reliable and efficient to achieve satisfactory solutions. Differential evolution is a recent branch of evolutionary algorithms that is capable of addressing a wide set of complex optimization problems in a relatively uniform and conceptually simple manner. For better performance, the control parameters of differential evolution need to be set appropriately as they have different effects on evolutionary search behaviours for various problems or at different optimization stages of a single problem. The fundamental theme of the book is theoretical study of differential evolution and algorithmic analysis of parameter adaptive schemes. Topics covered in this book include: Theoretical analysis of differential evolution and its control parameters Algorithmic design and comparative analysis of parameter adaptive schemes Scalability analysis of adaptive differential evolution Adaptive differential evolution for multi-objective optimization Incorporation of surrogate model for computationally expensive optimization Application to winner determination in combinatorial auctions of E-Commerce Application to flight route planning in Air Traffic Management Application to transition probability matrix optimization in credit-decision making.

• Adaptive Instruction Design and Authoring.- Interoperability and Standardization in Adaptive Instructional Systems.- Instructional Theories in Adaptive Instruction.- Learner Assessment and Modelling.- AI in Adaptive Instructional Systems, Conversational Tutors.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the First International Conference on Adaptive Instructional Systems, AIS 2019, held in July 2019 as part of HCI International 2019 in Orlando, FL, USA. HCII 2019 received a total of 5029 submissions, of which 1275 papers and 209 posters were accepted for publication after a careful reviewing process. The 50 papers presented in this volume are organized in topical sections named: Adaptive Instruction Design and Authoring, Interoperability and Standardization in Adaptive Instructional Systems, Instructional Theories in Adaptive Instruction, Learner Assessment and Modelling, AI in Adaptive Instructional Systems, Conversational Tutors.
(source: Nielsen Book Data)

• Designing and Developing Adaptive Instructional Systems.- Sensor-based Adaptive Instructional Systems in Live Simulation Training.- An Ambient & Pervasive Personalized Learning Ecosystem: "Smart Learning" in the Age of the Internet of Things.- Bridging Conceptual Models and Architectural Interchange for Adaptive Instructional Systems.- Dewey's Ethics of Moral Principles and Deliberation: Extending IEEE's Ethics Initiative for Adaptive Instructional Systems.- Realistic and Relevant Role-Players for Experiential Learning.- Learning Traces, Measurement and Assessment Templates for AIS Interoperability.- Supporting different Roles and Responsibilities in Developing and Using Context-based Adaptive Personalized Collaboration Environments Compliant to the Law.- Experiential Instruction of Metacognitive Strategies.- Falling Forward: Lessons Learned from Real-Life Implementation of Adaptive Learning Solutions.- Usability Dimensions of Simulated Trainers for Buried Explosives.- Toward Zero Authoring: Considering How to Maximize Courseware Quality and Affordability Simultaneously.- Agent-Based Methods in Support of Adaptive Instructional Decisions.- Representing Functional Relationships of Adaptive Instructional Systems in a Conceptual Model.- Knowledge-to-Information Translation Training (KITT): An Adaptive Approach to Explainable Artificial Intelligence.- User Rights and Adaptive A/IS - From Passive Interaction to Real Empowerment.- Supporting Metacognitive Learning Strategies through an Adaptive Application.- Towards Iteration by Design: An Interaction Design Concept for Safety Critical Systems.- Learner Modelling and Methods of Adaptation.- Bayesian Student Modelling in the AC&NL Tutor.- Nature at Your Service - Nature Inspired Representations Combined with Eye-gaze Features to Infer User Attention and Provide Contextualized Support.- Adapting Instruction by Measuring Engagement with Machine Learning in Virtual Reality Training.- Realizing the Promise of AI-Powered, Adaptive, Automated, Instant Feedback on Writing for Students in Grade 3-8 with an IEP.- Declarative Knowledge Extraction in the AC&NL Tutor.- On the Importance of Adaptive Operator Training in Human-Swarm Interaction.- The Mental Machine: Classifying Mental Workload State from Unobtrusive Heart Rate- measures Using Machine Learning.- Production Implementation of Recurrent Neural Networks in Adaptive Instructional Systems.- Pilot State Monitoring for Cursus Recommendation.- Experimental Evaluation of Heart-based Workload Measures as Related to Their Suitability for Real-time Applications.- EEG Covariance-based Estimation of Cooperative States in Teammates.- Adapting the Zone of Proximal Development to the Wicked Environments of Professional Practice.- An Adaptive Instructional System for the Retention of Complex Skills.- Learner Modeling in the Context of Caring Assessments.- Evaluating the Effectiveness of Adaptive Instructional Systems.- The Evolving Assessment Landscape and Adaptive Instructional Systems: Moving Beyond Good Intentions.- Contextual Barriers to Validity in Adaptive Instruction and Assessment.- Does Time Matter in Learning? A Computer Simulation of Carroll's Model of Learning.- Competency Development through Experiential Training: Mapping Scenarios with Assessments.- Does Gamification Work? Analyzing Effects of Game Features on Learning in an Adaptive Scenario-Based Trainer.- From "Knowing What" to "Knowing When": Exploring a Concept of Situation Awareness Synchrony for Evaluating SA Dynamics in Teams.- Exploring Video Engagement in an Intelligent Tutoring System.- Using a Non-Player Character to Improve Training Outcomes for Submarine Electronic Warfare Operators.- The Impact of Adaptive Activities in Acrobatiq Courseware: Investigating the Efficacy of Formative Adaptive Activities on Learning Estimates and Summative Assessment Scores.- A Mastery Approach to Flashcard-based Adaptive Training. .
• (source: Nielsen Book Data)

This volume constitutes the refereed proceedings of the Second International Conference on Adaptive Instructional Systems, AIS 2020, which was due to be held in July 2020 as part of HCI International 2020 in Copenhagen, Denmark. The conference was held virtually due to the COVID-19 pandemic. A total of 1439 papers and 238 posters have been accepted for publication in the HCII 2020 proceedings from a total of 6326 submissions. The 41 papers presented in this volume were organized in topical sections as follows: designing and developing adaptive instructional systems; learner modelling and methods of adaptation; evaluating the effectiveness of adaptive instructional systems. Chapter "Exploring Video Engagement in an Intelligent Tutoring System" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
(source: Nielsen Book Data)

• Part I Literature Review and State of the Art
• Part II Model for Adaptive Semantics Visualization
• Part III Proof of the Conceptual Model.

This book introduces a novel approach for intelligent visualizations that adapts the different visual variables and data processing to human's behavior and given tasks. Thereby a number of new algorithms and methods are introduced to satisfy the human need of information and knowledge and enable a usable and attractive way of information acquisition. Each method and algorithm is illustrated in a replicable way to enable the reproduction of the entire "SemaVis" system or parts of it. The introduced evaluation is scientifically well-designed and performed with more than enough participants to validate the benefits of the methods. Beside the introduced new approaches and algorithms, readers may find a sophisticated literature review in Information Visualization and Visual Analytics, Semantics and information extraction, and intelligent and adaptive systems. This book is based on an awarded and distinguished doctoral thesis in computer science

• 1st Workshop on Intelligent Data - From Data to Knowledge (DOING 2020).- 2nd Workshop on Modern Approaches in Data Engineering and Information System Design (MADEISD 2020).- 1st Workshop on Scientic Knowledge Graphs (SKG 2020).- 2nd Workshop of BI & Big Data Applications (BBIGAP 2020).- International Symposium on Data-Driven Process Discovery and Analysis (SIMPDA 2020).- The 1st International Workshop on Assessing Impact and Merit in Science (AIMinScience 2020).- Doctoral Consortium.
• (source: Nielsen Book Data)

This book constitutes thoroughly reviewed and selected papers presented at Workshops and Doctoral Consortium of the 24th East-European Conference on Advances in Databases and Information Systems, ADBIS 2020, the 24th International Conference on Theory and Practice of Digital Libraries, TPDL 2020, and the 16th Workshop on Business Intelligence and Big Data, EDA 2020, held in August 2020. Due to the COVID-19 the joint conference and satellite events were held online. The 26 full papers and 5 short papers were carefully reviewed and selected from 56 submissions. This volume presents the papers that have been accepted for the following satellite events: Workshop on Intelligent Data - From Data to Knowledge, DOING 2020; Workshop on Modern Approaches in Data Engineering and Information System Design, MADEISD 2020; Workshop on Scientic Knowledge Graphs, SKG 2020; Workshop of BI & Big Data Applications, BBIGAP 2020; International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2020; International Workshop on Assessing Impact and Merit in Science, AIMinScience 2020; Doctoral Consortium.
(source: Nielsen Book Data)

• Exploring Artificial Jabbering For Automatic Text Comprehension Question Generation.- Digital Value-Adding Chains in Vocational Education: Automatic Keyword Extraction from Learning Videos to Provide Learning Resource Recommendations.- Human-centered design of a dashboard on students' revisions during writing.- An operational Framework for Evaluating the Performance of Learning Record Stores.- Does an e-mail reminder intervention with learning analytics reduce procrastination in a blended university course.- Designing an Online Self-Assessment for Informed Study Decisions: The User Perspective.- What Teachers Need for Orchestrating Robotic Classrooms.- Assessing Teacher's Discourse Effect on Students' Learning: A Keyword Centrality Approach.- For learners, with learners: Identifying indicators for an academic advising dashboard for students.- Living with learning difficulties: Two case studies exploring the relationship between emotion and performance in students with learning difficulties.- Learnersourcing Quality Assessment of Explanations for Peer Instruction.- Using Diffusion Network Analytics to Examine and Support Knowledge Construction in CSCL Settings.- Supporting Second Language Learners' Development of Affective Self-Regulated Learning Skills through the Use and Design of Mobile Technology.- We Know What You Did Last Semester: Learners' Perspectives on Screen Recordings as a Long-Term Data Source for Learning Analytics.- Teaching Simulation Literacy with Evacuations: Concept, Technology, and Material for a Novel Approach.- Design of conversational agents for CSCL: comparing two types of agent intervention strategies in a university classroom.- Exploring Human-AI Control over Dynamic Transitions between Individual and Collaborative Learning.- Exploring Student-Controlled Social Comparison.- New Measures for Offline Evaluation of Learning Path Recommenders.- Assessing the Impact of the combination of Self-directed learning, Immediate feedback and Visualizations on Student Engagement in Online Learning.- CGVis: A Visualization-Based Learning Platform for Computational Geometry Algorithms.- How to Design Effective Learning Analytics Indicators? A Human-Centered Design Approach.- Emergency Remote Teaching: Capturing Teacher Experiences in Spain with SELFIE.- Utilising Learnersourcing to Inform Design Loop Adaptivity.- Fooling it - Student Attacks on Automatic Short Answer Grading.- Beyond indicators: A scoping review of the academic literature related to SDG4 and educational technology.- Pedagogical underpinnings of open science, citizen science and open innovation activities: a state-of-the-art analysis.- Knowledge-Driven Wikipedia Article Recommendation for Electronic Textbooks.- InfoBiTS: A mobile application to foster digital competencies of senior citizens.- Student Awareness and Privacy Perception of Learning Analytics in Higher Education.- User Assistance for Serious Games Using Hidden Markov Model.- Guiding Socio-technical Reflection of Ethical Principles in TEL Software Development: The SREP Framework.- Git4School: a Dashboard for Supporting Teacher Interventions in Software Engineering Courses.- Exploring the design and impact of online exercises for teacher training about dynamic models in mathematics.- Interactive Concept Cartoons: Exploring an Instrument for Developing Scientific Literacy.- Quality Evaluation of Open Educational Resources.- Designing Digital Activities to Screen Locomotor Skills in Developing Children.- Towards Adaptive Social Comparison for Education.- Simulation Based Assessment of Epistemological Beliefs about Science.- An Approach to Support Interactive Activities in Live Stream Lectures.- Educational Escape Games for Mixed Reality.- Measuring Learning Progress for serving Immediate Feedback needs: Learning Process Quantification Framework (LPQF).- Data-driven Game Design: The Case of Difficulty in Educational Games.- Extracting Topics from Open Educational Resources.- Supporting Gamification with an Interactive Gamification Analytics Tool (IGAT).- OpenLAIR an Open Learning Analytics Indicator Repository Dashboard.- CasualLearn: A smart application to learn History of Art.- Applying Instructional Design Principles on Augmented Reality Cards for Computer Science Education.- Extending Patient Education with CLAIRE: An Interactive Virtual Reality and Voice User Interface Application.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 15th European Conference on Technology Enhanced Learning, EC-TEL 2020, held in Heidelberg, Germany, in September 2020. The 24 research papers and 20 demo and 5 poster papers presented in this volume were carefully reviewed and selected from 91 submissions. The European Conference on Technology-Enhance Learning, which celebrates its 15th anniversary this year, is committed to address global challenges and quality education. The papers deal with the Sustainable Development Goals, particularly SDG 4 and SDG 10, to help to reduce the existing gaps and inequalities between countries and regions from around the world in terms of inclusiveness, equity, access, and quality of education. The chapters: "Designing an Online Self-Assessment for Informed Study Decisions: The User Perspective"; "Living with Learning Difficulties: Two Case Studies Exploring the Relationship Between Emotion and Performance in Students With Learning Difficulties"; "Applying Instructional Design Principles on Augmented Reality Cards for Computer Science Education"; and "Teaching Simulation Literacy With Evacuations - Concept, Technology, and Material for a Novel Approach" are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. Due to the Corona pandemic EC-TEL 2020 was held as an virtual event.
(source: Nielsen Book Data)

• Intro; Preface; Organization; Contents; Time Series Representation and Compression; Symbolic Representation of Time Series: A Hierarchical Coclustering Formalization; 1 Introduction; 2 Related Work; 3 Formalization of the SAXO Approach; 3.1 Prior Distribution of the SAXO Models; 3.2 Likelihood of Data Given a SAXO Model; 3.3 Evaluation Criterion; 4 Comparative Experiments on Real Datasets; 4.1 Coding Length Evaluation; 4.2 Supervised Learning Evaluation; 5 Conclusion and Perspectives; References; Dense Bag-of-Temporal-SIFT-Words for Time Series Classification; 1 Introduction; 2 Related Work

• 2.1 Distance-Based Time Series Classification2.2 Bag-of-Words for Time Series Classification; 2.3 Ensemble Classifiers for Time Series; 3 Bag-of-Temporal-SIFT-Words (BoTSW); 3.1 Keypoint Extraction in Time Series; 3.2 Description of the Extracted Keypoints; 3.3 Bag-of-Temporal-SIFT-Words for Time Series Classification; 4 Experiments and Results; 4.1 Experimental Setup; 4.2 Dense Extraction vs. Scale-Space Extrema Detection; 4.3 Impact of the BoW Normalization; 4.4 Comparison with State-of-the-Art Methods; 5 Conclusion; References

• Dimension Reduction in Dissimilarity Spaces for Time Series Classification1 Introduction; 2 Related Work; 3 Dissimilarity Representations of Time Series; 3.1 The Basic Idea; 3.2 Dynamic Time Warping Distance; 3.3 Dissimilarity Representations; 3.4 Learning Classifiers in Dissimilarity Space; 3.5 Prototype Dependent Kernels; 4 Experiments; 4.1 Data; 4.2 Classifiers; 4.3 Experimental Protocol; 4.4 Results; 5 Conclusion; A Performance Profiles; References; Time Series Classification and Clustering; Fuzzy Clustering of Series Using Quantile Autocovariances; 1 Introduction

• 2 A Dissimilarity Based on Quantile Autocovariances3 Fuzzy Clustering Based on Quantile Autocovariances; 4 Simulation Study; 5 A Case Study; 6 Concluding Remarks; References; A Reservoir Computing Approach for Balance Assessment; 1 Introduction; 2 Balance Assessment Using Reservoir Computing; 3 Experimental Results; 4 Conclusions; References; Learning Structures in Earth Observation Data with Gaussian Processes; 1 Introduction; 2 Gaussian Process Regression; 2.1 Gaussian Processes: A Gentle Introduction; 2.2 On the Model Selection; 2.3 On the Covariance Function

• 2.4 Gaussian Processes Exemplified3 Advances in Gaussian Process Regression; 3.1 Structured, Non-stationary and Multiscale; 3.2 Time-based Covariance for GPR; 3.3 Heteroscedastic GPR: Learning the Noise Model; 3.4 Warped GPR: Learning the Output Transformation; 3.5 Source Code and Toolboxes; 4 Analysis of Gaussian Process Models; 4.1 Ranking Features Through the ARD Covariance; 4.2 Uncertainty Intervals; 5 Conclusions and Further Work; References; Monitoring Short Term Changes of Infectious Diseases in Uganda with Gaussian Processes; 1 Introduction; 2 Methods Used

This book constitutes the refereed proceedings of the First ECML PKDD Workshop, AALTD 2015, held in Porto, Portugal, in September 2016. The 11 full papers presented were carefully reviewed and selected from 22 submissions. The first part focuses on learning new representations and embeddings for time series classification, clustering or for dimensionality reduction. The second part presents approaches on classification and clustering with challenging applications on medicine or earth observation data. These works show different ways to consider temporal dependency in clustering or classification processes. The last part of the book is dedicated to metric learning and time series comparison, it addresses the problem of speeding-up the dynamic time warping or dealing with multi-modal and multi-scale metric learning for time series classification and clustering.

• Robust Functional Regression for Outlier Detection
• Transform Learning Based Function Approximation for Regression and Forecasting
• Proactive Fiber Break Detection based on Quaternion Time Series and Automatic Variable Selection from Relational Data
• A fully automated periodicity detection in time series
• Conditional Forecasting of Water Level Time Series with RNNs
• Challenges and Limitations in Clustering Blood Donor Hemoglobin Trajectories
• Localized Random Shapelets
• Feature-Based Gait Pattern Classification for a Robotic Walking Frame
• How to detect novelty in textual data streams? A comparative study of existing methods
• Seq2VAR: multivariate time series representation with relational neural networks and linear autoregressive model
• Modelling Patient Sequences for Rare Disease Detection with Semi-supervised Generative Adversarial Nets
• Extended Kalman Filter for Large Scale Vessels Trajectory Tracking in Distributed Stream Processing Systems
• Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Datasets using Deep Learning
• Learning Stochastic Dynamical Systems via Bridge Sampling
• Quantifying Quality of Actions Using Wearable Sensor
• An Initial Study on Adapting DTW at Individual Query for Electrocardiogram Analysis.

This book constitutes the refereed proceedings of the 4th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2019, held in Würzburg, Germany, in September 2019. The 7 full papers presented together with 9 poster papers were carefully reviewed and selected from 31 submissions. The papers cover topics such as temporal data clustering; classification of univariate and multivariate time series; early classification of temporal data; deep learning and learning representations for temporal data; modeling temporal dependencies; advanced forecasting and prediction models; space-temporal statistical analysis; functional data analysis methods; temporal data streams; interpretable time-series analysis methods; dimensionality reduction, sparsity, algorithmic complexity and big data challenge; and bio-informatics, medical, energy consumption, on temporal data.

• Machine generated contents note: ch. 1 Introduction
• 1.1. Brief History of AI
• 1.2. Cognitive Issues of AI
• 1.3. Hierarchical Model of Thought
• 1.4. Symbolic Intelligence
• 1.5. Research Approaches of Artificial Intelligence
• 1.6. Automated Reasoning
• 1.7. Machine Learning
• 1.8. Distributed Artificial Intelligence
• 1.9. Artificial Thought Model
• 1.10. Knowledge Based Systems
• Exercises
• ch. 2 Logic Foundation of Artificial Intelligence
• 2.1. Introduction
• 2.2. Logic Programming
• 2.3. Nonmonotonic Logic
• 2.4. Closed World Assumption
• 2.5. Default Logic
• 2.6. Circumscription Logic
• 2.7. Nonmonotonic Logic NML
• 2.8. Autoepistemic Logic
• 2.9. Truth Maintenance System
• 2.10. Situation Calculus
• 2.11. Frame Problem
• 2.12. Dynamic Description Logic
• Exercises
• ch. 3 Constraint Reasoning
• 3.1. Introduction
• 3.2. Backtracking
• 3.3. Constraint Propagation
• 3.4. Constraint Propagation in Tree Search
• 3.5. Intelligent Backtracking and Truth Maintenance.

• 3.6. Variable Instantiation Ordering and Assignment Ordering
• 3.7. Local Revision Search
• 3.8. Graph-based Backjumping
• 3.9. Influence-based Backjumping
• 3.10. Constraint Relation Processing
• 3.11. Constraint Reasoning System COPS
• 3.12. ILOG Solver
• Exercise
• ch. 4 Qualitative Reasoning
• 4.1. Introduction
• 4.2. Basic approaches in qualitative reasoning
• 4.3. Qualitative Model
• 4.4. Qualitative Process
• 4.5. Qualitative Simulation Reasoning
• 4.6. Algebra Approach
• 4.7. Spatial Geometric Qualitative Reasoning
• Exercises
• ch. 5 Case-Based Reasoning
• 5.1. Overview
• 5.2. Basic Notations
• 5.3. Process Model
• 5.4. Case Representation
• 5.5. Case Indexing
• 5.6. Case Retrieval
• 5.7. Similarity Relations in CBR
• 5.8. Case Reuse
• 5.9. Case Retainion
• 5.10. Instance-Based Learning
• 5.11. Forecast System for Central Fishing Ground
• Exercises
• ch. 6 Probabilistic Reasoning
• 6.1. Introduction
• 6.2. Foundation of Bayesian Probability
• 6.3. Bayesian Problem Solving
• 6.4. Naive Bayesian Learning Model.

• 6.5. Construction of Bayesian Network
• 6.6. Bayesian Latent Semantic Model
• 6.7. Semi-supervised Text Mining Algorithms
• Exercises
• ch. 7 Inductive Learning
• 7.1. Introduction
• 7.2. Logic Foundation of Inductive Learning
• 7.3. Inductive Bias
• 7.4. Version Space
• 7.5. AQ Algorithm for Inductive Learning
• 7.6. Constructing Decision Trees
• 7.7. ID3 Learning Algorithm
• 7.8. Bias Shift Based Decision Tree Algorithm
• 7.9. Computational Theories of Inductive Learning
• Exercises
• ch. 8 Support Vector Machine
• 8.1. Statistical Learning Problem
• 8.2. Consistency of Learning Processes
• 8.3. Structural Risk Minimization Inductive Principle
• 8.4. Support Vector Machine
• 8.5. Kernel Function
• Exercises
• ch. 9 Explanation-Based Learning
• 9.1. Introduction
• 9.2. Model for EBL
• 9.3. Explanation-Based Generalization
• 9.4. Explanation Generalization using Global Substitutions
• 9.5. Explanation-Based Specialization
• 9.6. Logic Program of Explanation-Based Generalization
• 9.7. SOAR Based on Memory Chunks.

• 9.8. Operationalization
• 9.9. EBL with imperfect domain theory
• Exercises
• ch. 10 Reinforcement Learning
• 10.1. Introduction
• 10.2. Reinforcement Learning Model
• 10.3. Dynamic Programming
• 10.4. Monte Carlo Methods
• 10.5. Temporal-Difference Learning
• 10.6. Q-Learning
• 10.7. Function Approximation
• 10.8. Reinforcement Learning Applications
• Exercises
• ch. 11 Rough Set
• 11.1. Introduction
• 11.2. Reduction of Knowledge
• 11.3. Decision Logic
• 11.4. Reduction of Decision Tables
• 11.5. Extended Model of Rough Sets
• 11.6. Experimental Systems of Rough Sets
• 11.7. Granular Computing
• 11.8. Future Trends of Rough Set Theory
• Exercises
• ch. 12 Association Rules
• 12.1. Introduction
• 12.2. The Apriori Algorithm
• 12.3. FP-Growth Algorithm
• 12.4. CFP-Tree Algorithm
• 12.5. Mining General Fuzzy Association Rules
• 12.6. Distributed Mining Algorithm For Association Rules
• 12.7. Parallel Mining of Association Rules
• Exercises
• ch. 13 Evolutionary Computation
• 13.1. Introduction
• 13.2. Formal Model of Evolution System Theory.

• 13.3. Darwin's Evolutionary Algorithm
• 13.4. Classifier System
• 13.5. Bucket Brigade Algorithm
• 13.6. Genetic Algorithm
• 13.7. Parallel Genetic Algorithm
• 13.8. Classifier System Boole
• 13.9. Rule Discovery System
• 13.10. Evolutionary Strategy
• 13.11. Evolutionary Programming
• Exercises
• ch. 14 Distributed Intelligence
• 14.1. Introduction
• 14.2. The Essence of Agent
• 14.3. Agent Architecture
• 14.4. Agent Communication Language ACL
• 14.5. Coordination and Cooperation
• 14.6. Mobile Agent
• 14.7. Multi-Agent Environment MAGE
• 14.8. Agent Grid Intelligence Platform
• Exercises
• ch. 15 Artificial Life
• 15.1. Introduction
• 15.2. Exploration of Artificial Life
• 15.3. Artificial Life Model
• 15.4. Research Approach of Artificial Life
• 15.5. Cellular Automata
• 15.6. Morphogenesis Theory
• 15.7. Chaos Theories
• 15.8. Experimental Systems of Artificial Life
• Exercises.

Artificial intelligence is a branch of computer science and a discipline in the study of machine intelligence, that is, developing intelligent machines or intelligent systems imitating, extending and augmenting human intelligence through artificial means and techniques to realize intelligent behavior.Advanced Artificial Intelligence consists of 16 chapters. The content of the book is novel, reflects the research updates in this field, and especially summarizes the author's scientific efforts over many years. The book discusses the methods and key technology from theory, algorithm, system and applications related to artificial intelligence. This book can be regarded as a textbook for senior students or graduate students in the information field and related tertiary specialities. It is also suitable as a reference book for relevant scientific and technical personnel.
(source: Nielsen Book Data)

• Local Perturbation Analysis Of The Stochastic Matrix Riccati Equation With Applications In Finance.- An Embedded Compact Scheme For Biharmonic Problems In Irregular Domains.- Ant Colony Optimization Algorithm For 1D Cutting Stock Problem.- 2D Optimal Cutting Problem.- Error Estimate In The Iterative Numerical Method For Two-Dimensional Nonlinear Hammerstein-Fredholm Fuzzy Functional Integral Equations.- Noise Removal And Feature Extraction Of 2D CT Radiographic Images.- Representation Of Civilians And Police Officers By Generalized Nets For Describing Software Agents In The Case Of Protest.- Comparison Of NDT Techniques For Elastic Modulus Determination Of Laminated Composites.- Integer Codes For Flash Memories.- On The Strong Asymptotics Of Rows Of The Pade Table.- Total Phosphorus Removal In Horizontal Subsurface Flow Constructed Wetlands: A Computational Investigation For The Optimal Adsorption Model.- Some Results Involving Euler-Type Integrals And Dilogarithm Values.- Nonlinear Evolution Equation For Propagation Of Waves In An Artery With An Aneurysm: An Exact Solution Obtained By The Modified Method Of Simplest Equation.- Modelling Of Light Mg And Al Based Alloys As "In Situ" Composites.- Asymptotic Study Of The Nonlinear Velocity Problem For The Oscillatory Non-Newtonian Flow In A Straight Channel.- Competition For Resources And Space Contributes To The Emergence Of Drug Resistance In Cancer.- Efficient Error Based Metrics For Fuzzy-Neural Network Performance Evaluation.- Box Model Of Migration In Channels Of Migration Networks.- Modified Coordinates In Dynamics Simulation Of Multibody Systems With Elastic Bodies.
• (source: Nielsen Book Data)

This book presents recent research on Advanced Computing in Industrial Mathematics, which is one of the most prominent interdisciplinary areas, bringing together mathematics, computer science, scientific computations, engineering, physics, chemistry, medicine, etc. Further, the book presents the major tools used in Industrial Mathematics, which are based on mathematical models, and the corresponding computer codes, which are used to perform virtual experiments to obtain new data or to better understand previous experimental findings. The book gathers the peer-reviewed papers presented at the 11th Annual Meeting of the Bulgarian Section of SIAM (BGSIAM), from December 20 to 22, 2016 in Sofia, Bulgaria.
(source: Nielsen Book Data)

• Advanced Computing in Engineering.- Computer Supported Construction Management.- Life-Cycle Design Support.- Monitoring and Control Algorithms in Engineering.- BIM and Engineering Ontologies.
• (source: Nielsen Book Data)

This double volume set ( LNAI 10863-10864) constitutes the refereed proceedings of the 25th International Workshop, EG-ICE 2018, held in Lausanne, Switzerland, in June 2018. The 58 papers presented in this volume were carefully reviewed and selected from 108 submissions. The papers are organized in topical sections on Advanced Computing in Engineering, Computer Supported Construction Management, Life-Cycle Design Support, Monitoring and Control Algorithms in Engineering, and BIM and Engineering Ontologies.
(source: Nielsen Book Data)

• Advanced Computing in Engineering.- Computer Supported Construction Management.- Life-Cycle Design Support.- Monitoring and Control Algorithms in Engineering.- BIM and Engineering Ontologies.
• (source: Nielsen Book Data)

This double volume set ( LNAI 10863-10864) constitutes the refereed proceedings of the 25th International Workshop, EG-ICE 2018, held in Lausanne, Switzerland, in June 2018. The 58 papers presented in this volume were carefully reviewed and selected from 108 submissions. The papers are organized in topical sections on Advanced Computing in Engineering, Computer Supported Construction Management, Life-Cycle Design Support, Monitoring and Control Algorithms in Engineering, and BIM and Engineering Ontologies.
(source: Nielsen Book Data)

• Gradients versus Grey Values for Sparse Image Reconstruction and Inpainting-Based Compression
• Global Bilateral Symmetry Detection Using Multiscale Mirror Histograms
• Neural Network Boundary Detection for 3D Vessel Segmentation
• A Simple Human Activity Recognition Technique using DCT
• Hand Gesture Recognition using Infrared Imagery Provided by Leap Motion Controller
• Horizon line detection from fisheye images using color local image region descriptors and Bhattacharyya coefficient-based distance
• Joint Segmentation Of Myocardium On Multi State Spect Images
• Parallel Hough space image generation method for real time lane detection
• A Novel Decentralised System Architecture for Multi-Camera Target Tracking
• Intramolecular FRET efficiency measures for time-lapse fluorescence microscopy images
• Predicting Image Aesthetics with Deep Learning
• Automatic Image Splicing Detection Based On Noise Density Analysis In Raw Images
• Breast Shape Parametrization through Planar Projections
• Decreasing Time Consumption of Microscopy Image Segmentation through Parallel Processing on the GPU
• Coral reef fish detection and recognition in underwater videos by supervised machine learning : Comparison between Deep Learning and hog+svm methods
• A Real-time Eye Gesture Recognition System Based on Fuzzy Inference System for Mobile Devices Monitoring
• Spatially Varying Weighting Function-based Global and Local Statistical Active Contours. Application to X-ray Images
• Vegetation segmentation in cornfield images using bag of words
• Fast Traffic Sign Recognition Using Color Segmentation and Deep Convolutional Networks
• The Orlando Project: a 28 nm FDSOI Low Memory Embedded Neural Network ASIC
• Factor Analysis of Dynamic Sequence with Spatial Prior for 2D Cardiac Spect Sequences Analysis
• Soccer Player Detection with Only Color Features Selected Using Informed Haar-like Features
• Person Re-identification in frontal gait sequences via Histogram of Optic flow Energy Image
• A Bayesian approach to linear unmixing in the presence of highly mixed spectra
• Key frames extraction based on local features for efficient video summarization
• A simple evaluation procedure for range camera measurement quality
• Accordion Representation based Multi-scale Covariance Descriptor for Multi-shot Person Re-identification
• Jensen Shannon divergence as reduced reference measure for image denoising
• Visual Localization using Sequence Matching Based on Multi-feature Combination
• Towards Automated Drone Surveillance in Railways: State-of-the-Art and Future Directions
• Combining Stacked Denoising Autoencoders and Random Forests for Face Detection
• Multimodal Registration of PET/MR Brain Images based on Adaptive Mutual Information
• Aerial detection in maritime scenarios using convolutional neural networks
• R3P: Real-time RGB-D Registration Pipeline
• Vector Quantization Enhancement for Computer Vision Tasks
• Learning Approaches for Parking Lots Classification
• Video event detection based non-stationary Bayesian networks
• Optimized Connected Components Labeling with Pixel Prediction
• Hierarchical Fast Mean-Shift Segmentation in Depth Images
• Robust Color Watermarking Method Based On Clifford Transform
• Action-02MCF: A robust space-time Correlation Filter for Action Recognition in clutter and adverse lighting conditions
• An Image Quality Metric With Reference For Multiply Distorted Image
• 3D Planar RGB-D SLAM System
• Towards a generic m-svm parameters estimation using overlapping swarm intelligence for handwritten characters recognition
• Human Action Recognition Based on Temporal Pyramid of Key Poses Using RGB-D Sensors
• Multi-layer Dictionary Learning for Image Classification
• Intelligent Vision System for ASD Diagnosis and Assessment
• Visual Target Detection and Tracking in UAV EO/IR Videos by Moving Background Subtraction
• A Multiphase Level Set Method on Graphs for Hyperspectral Image Segmentation
• A Mobile Application for Leaf Detection in Complex Background using Saliency Maps
• Content-based mammogram retrieval using mixed kernel PCA and curvelet transform
• Combination of RGB-D Features for Head and Upper Body Orientation Classification
• A parametric algorithm for skyline extraction
• Quaternion linear color edge-glowing filter using genetic algorithm
• Scalable Vision System for Mouse Homecage Ethology
• Spatio-Temporal Features Learning with 3DPyraNet
• Automatic segmentation of tv news into stories using visual and temporal information
• Wavelet neural network initialization using LTS for DNA Sequence Classification
• Collection of Visual Data in Climbing Experiments for Addressing the Role of Multi-Modal Exploration in Motor Learning Efficiency
• Fog Augmentation of Road Images for Performance Analysis of Traffic Sign Detection Algorithms
• Statistical Modeling based Adaptive Parameter Setting for Random Walk Segmentation
• On-the-y Architecture Design and Implementation of a Real-Time Stereovision System
• Complex Image Processing Using Correlated Color Information
• Using PNU-based Techniques to Detect Alien Frames in Videos.

This book constitutes the refereed proceedings of the 17th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2016, held in Lecce, Italy, in October 2016. The 64 revised full papers presented in this volume were carefully selected from 137 submissions. They deal with classical low-level image processing techniques; image and video compression; 3D; security and forensics; and evaluation methodologies.

• Human-computer interaction.- Classification and recognition.- Navigation, mapping, robotics, and transports.- Video processing and retrieval.- Security, forensics, surveillance.- Image processing.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 18th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2017, held in Antwerp, Belgium, in September 2017. The 63 full papers presented in this volume were carefully selected from 134 submissions. They deal with human-computer interaction; classification and recognition; navigation, mapping, robotics, and transports; video processing and retrieval; security, forensics, surveillance; and image processing.
(source: Nielsen Book Data)

• Video Analysis.- Improving a Switched Vector Field Model for Pedestrian Motion Analysis.- Matrix Descriptor of Changes (MDC): Activity Recognition Based on
• Skeleton.- Person Re-identification with a Body Orientation-Specific Convolutional
• Neural Network.- Distributed Estimation of Vector Fields.- Clustering Based Reference Normal Pose for Improved Expression Recognition.- Detecting and Recognizing Salient Object in Videos.- Directional Beams of Dense Trajectories for Dynamic Texture Recognition.- Intrinsic Calibration of a Camera to a Line-Structured Light using a Single View of Two Spheres.- 3D Object-Camera and 3D Face-Camera Pose Estimation For Quadcopter Control: Application To Remote Labs.- Orthogonally-Divergent Fisheye Stereo.- Two-Camera Synchronization and Trajectory Reconstruction for a
• Touch Screen Usability Experiment.- Segmentation and classification.- Comparison of Co-segmentation Methods for Wildlife Photo-identification.- An Efficient Agglomerative Algorithm Cooperating with Louvain Method for Implementing Image Segmentation.- Robust Feature Descriptors For Object Segmentation Using Active Shape Models.- Foreground Background Segmentation in Front of Changing Footage on a Video Screen.- Multi-organ Segmentation of Chest CT Images in Radiation Oncology: Comparison of Standard and Dilated UNet.- Diffuse Low Grade Glioma NMR Assessment for Better Intra-operative Targeting Using Fuzzy Logic.- Identification of Saimaa rRnged Seal Individuals using Transfer Learning.- Remote sensing.- Enhanced Codebook Model and Fusion for Object Detection with Multispectral Images.- Unsupervised Perception Model for UAVs Landing Target Detection and Recognition.- Parallel and Distributed Local Fisher Discriminant Analysis to reduce Hyperspectral Images on Cloud Computing Architectures.- Bayesian Vehicle Detection using Optical Remote Sensing Images .- Integrating UAV in IoT for RoI Classification in Remote Images.- Biometrics.- Enhanced Line Local Binary Patterns (EL-LBP): An Efficient Image
• Representation for Face Recognition.- Single Sample Face Recognition by Sparse Recovery of Deep-learned Ida Features.- Recursive Chaining of Reversible Image-to-image Translators for Face
• Aging.- Automatically Selecting the Best Pictures for an Individualized Child Photo Album.- Face Detection in Painting using Deep Convolutional Neural Networks.- Robust Geodesic Skeleton Estimation from Body Single Depth.- Deep Learning.- Analysis of Neural Codes for Near-Duplicate Detection.- Optimum Network/Framework Selection from High-Level Specifications in Embedded Deep Learning Vision Applications.- Contour Propagation in CT scans with Convolutional Neural Networks.- Person Re-identification using Group Context.- Fingerprint Classification using Conic Radon Transform and Convolutional Neural Networks.- NoiseNet: Signal-dependent Noise Variance Estimation with Convolutional Neural Network.- Effective Training of Convolutional Neural Networks for Insect Image Recognition.- A Deep Learning Approach to Hair Segmentation and Color Extraction from Facial Images.- Learning Morphological Operators for Depth Completion.- Dealing with Topological Information within a Fully Convolutional Neural Network.- Coding and Compression.- L-infinite Predictive Coding of Depth.- An Application of Data Compression Models to Handwritten Digit Classification.- A Global Decoding Strategy with a Reduced-reference Metric Designed for the Wireless Transmission of JPWL .- Reconfigurable FPGA Implementation of the AVC Quantiser and Dequantiser Blocks.- Image Restauration and Reconstruction.- Large Parallax Image Stitching Using an Edge-Preserving Diffeomorphic Warping Process.- A Wavelet Based Image Fusion Method using Local Multiscale Image Regularity.- Optimising Data for Exemplar-based Inpainting.- Fast Light Field inpainting Propagation using Angular Warping and Color-guided Disparity Interpolation.- Fusing Omnidirectional Visual Data for Probability Matching Prediction.- Derivative Half Gaussian Kernels and Shock Filter.- Scanner Model Identification of Official Documents Using Noise Parameters Estimation in the Wavelet Domain.- Relocated Colour Contrast Occurrence Matrix and Adapted Similarity Measure for Colour Texture Retrieval.- I-HAZE: a Dehazing Benchmark with Real Hazy and Haze-free Indoor Images.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 19th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2018, held in Poitiers, France, in September 2018. The 52 full papers presented in this volume were carefully reviewed and selected from 91 submissions. They were organized in topical sections named: video analysis; segmentation and classification; remote sending; biometrics; deep learning; coding and compression; and image restauration and reconstruction.
(source: Nielsen Book Data)

This book constitutes the proceedings of the 12th International Conference on Advanced Data Mining and Applications, ADMA 2016, held in Gold Coast, Australia, in December 2016. The 70 papers presented in this volume were carefully reviewed and selected from 105 submissions. The selected papers covered a wide variety of important topics in the area of data mining, including parallel and distributed data mining algorithms, mining on data streams, graph mining, spatial data mining, multimedia data mining, Web mining, the Internet of Things, health informatics, and biomedical data mining.
(source: Nielsen Book Data)

• Database and Distributed Machine Learning.- Querying and Mining Strings Made Easy Distributed Training Large-Scale Deep Architectures.- Fault Detection and Localization in Distributed Systems using Recurrent Convolutional Neural Networks.- Discovering Group Skylines with Constraints by Early Candidate Pruning.- Comparing MapReduce-Based k-NN Similarity Joins On Hadoop For High-dimensional Data.- A Higher-Fidelity Frugal Quantile Estimator.- Recommender System.- Fair Recommendations Through Diversity Promotion.- A Hierarchical Bayesian Factorization Model for Implicit and Explicit Feedback Data.- Empirical Analysis of Factors Influencing Twitter Hashtag Recommendation on Detected Communities.- Group Recommender Model Based on Preference Interaction.- Identification of Grey Sheep Users By Histogram Inter
• section In Recommender Systems.- Social Network and Social Media.- A Feature-based Approach for the Redefined Link Prediction Problem in Signed Networks.- From Mutual Friends to Overlapping Community Detection: A Non-negative Matrix Factorization Approach.- Calling for Response: Automatically Distinguishing Situation-aware Tweets During Crises.- Efficient Revenue Maximization for Viral Marketing in Social Networks.- Generating Life Course Trajectory Sequences with Recurrent Neural Networks and Application to Early Detection on Social Disadvantage.- FRISK: A Multilingual Approach to Find twitteR InterestS via wiKipedia.- A Solution to Tweet-Based User Identification across Online Social Networks.- Machine Learning.- Supervised Feature Selection Algorithm Based on Low-Rank and Manifold Learning.- Mixed Membership Sparse Gaussian Conditional Random Fields.- Effects of Dynamic Subspacing in Random Forest.- Diversity and Locality in Multi-Component, Multi-Layer Predictive Systems: A Mutual Information Based Approach.- Hybrid Subspace Mixture Models For Prediction and Anomaly Detection in High Dimensions.- Classification and Clustering Methods.- StruClus: Scalable Structural Graph Set Clustering with Representative Sampling.- Employing Hierarchical Clustering and Reinforcement Learning for Attribute-based Zero-Shot Classification.- Environmental Sound Recognition using Masked Conditional Neural Networks.- Analyzing Performance of Classification Techniques in Detecting Epileptic Seizure.- A Framework for Clustering and Dynamic Maintenance of XML Documents.- Language-independent Twitter Classification using Character-based Convolutional Networks.- Behavior Modeling and User Profiling.- Modeling Check-in Behavior with Geographical Neighborhood Influence of Venues.- An empirical study on collective online behaviors of extremist supporters. -Your Moves, Your Device: Establishing Behavior Profiles using Tensors.- An Approach for Identifying Author Profiles of Blogs.- Generating Topics of Interests for Research Communities.- An Evolutionary Approach for Learning Conditional Preference Network from Inconsistent Examples.- Bioinformatic and Medical Data Analysis.- Predicting Clinical Outcomes of Alzheimer's Disease from Complex Brain Networks.- Doctoral Advisor or Medical Condition: Towards Entity-specific Rankings of Knowledge Base Properties.- Multiclass Lung Cancer Diagnosis by Gene Expression Programming and Microarray Datasets.- Drug-drug Interaction Extraction via Recurrent Neural Network with Multiple Attention Layers.- Spatio-temporal Data.- People-Centric Mobile Crowdsensing Platform for Urban Design.- Long-Term User Location Prediction Using Deep Learning and Periodic Pattern Mining.- An Intelligent Weighted Fuzzy Time Series Model Based on A Sine-Cosine Adaptive Human Learning Optimization Algorithm and Its Application to Financial Markets Forecasting.- Mobile Robot Scheduling with Multiple Trips and Time Windows.- Natural Language Processing and Text Mining.- Feature Analysis for Duplicate Detection in Programming QA Communities.- A Joint Human/Machine Process for Coding Events and Conflict Drivers.- Quality Prediction of Newly Proposed Questions in CQA by Leveraging Weakly Supervised Learning.- Improving Chinese Sentiment Analysis via Segmentation-based Representation Using Parallel CNN.- Entity Recognition by Distant Supervision with Soft List Constraint.- Structured Sentiment Analysis.- Data Mining Applications.- Improving Real-Time Bidding Using a Constrained Markov Decision Process.- PowerLSTM: Power Demand Forecasting Using Long Short-Term Memory Neural Network.- Identifying Unreliable Sensors Without a Knowledge of the Ground Truth in Deceptive Environments.- Color-sketch simulator: a guide for color-based visual known-item search.- Applications.- Making Use of External Company Data to Improve the Classification of Bank Transactions.- Mining Load Profile Patterns for Australian Electricity Consumers.- STA: a Spatio-temporal Thematic Analytics Framework for Urban Ground Sensing.- Privacy and Utility Preservation for Location Data Using Stay Region Analysis.- Location-aware Human Activity Recognition.- Demos.- SWYSWYK: a new Sharing Paradigm for the Personal Cloud.- Tools and Infrastructure for Supporting Enterprise Knowledge Graphs.- An Interactive Web-based Toolset for Knowledge Discovery from Short Text Log Data.- Carbon: Forecasting Civil Unrest Events by Monitoring News and Social Media.- A system for Querying and Analyzing Urban Regions.- Detect tracking behavior among trajectory data.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 13th International Conference on Advanced Data Mining and Applications, ADMA 2017, held in Singapore in November 2017. The 20 full and 38 short papers presented in this volume were carefully reviewed and selected from 118 submissions. The papers were organized in topical sections named: database and distributed machine learning; recommender system; social network and social media; machine learning; classification and clustering methods; behavior modeling and user profiling; bioinformatics and medical data analysis; spatio-temporal data; natural language processing and text mining; data mining applications; applications; and demos. .
(source: Nielsen Book Data)

• Information systems architecture.- Business process alignment.- User knowledge discovery.- Business process performance.- Big data exploration.- Process variability management.- Information systems transformation and evolution.- Business process modeling readability.- Business process adaption.- Data mining.- Process discovery.- Business process modeling notation.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 29th International Conference on Advanced Information Systems Engineering, CAiSE 2017, held in Essen, Germany, in June 2017. The 37 papers presented together with 3 keynote papers in this volume were carefully reviewed and selected from 175 submissions. The papers are organized in topical sections on information systems architecture; business process alignment; user knowledge discovery; business process performance; big data exploration; process variability management; information systems transformation and evolution; business process modeling readability; business process adaption; data mining; process discovery; business process modeling notation.
(source: Nielsen Book Data)

• Part 1 Intelligent computing theories and methodologies.

• Part 2 Intelligent computing theories and methodologies.

• Part 3 Advanced intelligent computing theories and applications.

This book - in conjunction with the double volume LNCS 9225-9226 - constitutes the refereed proceedings of the 11th International Conference on Intelligent Computing, ICIC 2015, held in Fuzhou, China, in August 2015. The 84 papers of this volume were carefully reviewed and selected from 671 submissions. Original contributions related to this theme were especially solicited, including theories, methodologies, and applications in science and technology. This year, the conference concentrated mainly on machine learning theory and methods, soft computing, image processing and computer vision, knowledge discovery and data mining, natural language processing and computational linguistics, intelligent control and automation, intelligent communication networks and web applications, bioinformatics theory and methods, healthcare and medical methods, and information security.
(source: Nielsen Book Data)

• Neural Networks.- Complex Functional Network Hebbian-Type Learning Algorithm and Convergence.- A New Intelligent Control Strategy of High-Voltage Power Supply for ECRH Based on CMAC Neural Network.- Self-configuration Using Artificial Neural Networks.- Evolutionary Learning and Genetic Algorithms.- An Improvement of AdaBoost for Face Detection with Random Forests.- Hybrid Good Point Set Evolutionary Strategy for Constrained Optimization.- Research of Modified Quantum Genetic Algorithm and It's Application in Collision Detection.- Granular Computing and Rough Sets.- A New Method of Attribute Reduction and Prediction in Fuzzy Decision System.- Particle Swarm Optimization and Niche Technology.- Development of Automatic Code Generation Tool for Condensation Algorithm.- Swarm Intelligence and Optimization.- A New Hybrid Multi-objective Pareto Archive PSO Algorithm for a Classic Job Shop Scheduling Problem with Ready Times.- Multi-objective Particle Swarm Optimization for Sequencing and Scheduling a Cellular Manufacturing System.- A Hybrid PSO Algorithm with Transposon for Multiobjective Optimization.- Independent Component Analysis and Blind Source Separation.- Joint Multichannel Blind Speech Separation and Dereverberation: A Real-Time Algorithmic Implementation.- An Efficient Pairwise Kurtosis Optimization Algorithm for Independent Component Analysis.- Combinatorial and Numerical Optimization.- The Mechanical Behavior of the Double Piece of Tape Spring.- Systems Biology and Computational Biology.- Cancer Immunoprevention: What Can We Learn from in Silico Models?.- Oscillatory Dynamics of Double Negative Feedback Loop Motif by MicroRNAs.- Neural Computing and Optimization.- Neural Network Approach for Greenery Warranty Systems.- Knowledge Discovery and Data Mining.- Comprehensive Evaluation of Effects of Naomaitong and Rhubarb Aglycone Combined with Bone Mesenchymal Stem Cells Transplantation on Brain in Rats with Cerebral Ischemia Based on Analytic Hierarchy Process.- Aggregating and Weighting Expert Knowledge in Group Decision Making.- A New Heuristic Feature Selection Algorithm Based on Rough Sets.- Developing a Procedure to Obtain Knowledge of Optimum Solutions in a Travelling Salesman Problem.- Trajectory Simplification and Classification for Moving Object with Road-Constraint.- Training a Pac-Man Player with Minimum Domain Knowledge and Basic Rationality.- Hybrid Self-Organizing Map and Neural Network Clustering Analysis for Technology Professionals Turnover Rate Forecasting.- Ensemble Methods.- A Study of Strength and Correlation in Random Forests.- Machine Learning Theory and Methods.- A Comparison Study of Conditional Random Fields Toolkits.- Robot Reinforcement Learning Based on Learning Classifier System.- Intelligent Computing in Bioinformatics.- Research of Marker Gene Selection for Tumor Classfication Based on Decision Forests.- Reverse Engineered Gene Networks Reveal Markers Predicting the Outcome of Breast Cancer.- New Tools for Expression Alternative Splicing Validation.- Intelligent Computing in Computational Biology and Drug Design.- Application for Artificial Bee Colony Algorithm in Migration of Mobile Agent.- Computational Genomics and Proteomics.- A Novel Tool for Assisted In-silico Cloning and Sequence Editing in Molecular Biology.- Intelligent Computing in Signal Processing.- A New Method Using Table to Sparse Representation in Pairs of Bases with Matching Pursuits.- Intelligent Computing in Pattern Recognition.- Palmprint Recognition Method Using WTA-ICA Based on 2DPCA.- Study of TCM Diagnosis of Syndromes of Acute Exacerbation of Chronic Obstructive Pulmonary Disease Based on Dynamic Fuzzy Kohonen Network.- Classification and Characteristics of TCM Syndromes of Chronic Respiratory Failure Based on Self-adaptive Fuzzy Inference System.- Implementation of the Pattern Matching System to Detect Flip Chip PCB Defects.- JPEG Steganalysis Using Estimated Image and Markov Model.- Applications of Two-Dimensional Heteroscedastic Discriminant Analysis in Face Recognition.- Intelligent Computing in Image Processing.- Multimodal Image Fusion Algorithm Using Dual-Tree Complex Wavelet Transform and Particle Swarm Optimization.- An Adaptive Method for Lane Marking Detection Based on HSI Color Model.- An Image Data Hiding Method Using Pixel-Based JND Model.- Intelligent Computing Applications Based on Eye Gaze: Their Role in Medical Image Interpretation.- Intelligent Computing in Communication and Computer Networks.- A Sequential Test Based Cooperative Spectrum Sensing Scheme Using Fuzzy Logic for Cognitive Radio Networks.- Solving Base Station Subsystem Assignment Problem in Mobile Communication Networks Using Hybridized Heuristic Algorithm.- A Sequential Cooperative Spectrum Sensing Scheme Based on Dempster Shafer Theory of Evidence.- High Resolution Direction Finding of Multiple Coherent Signals.- Extract and Maintain the Most Helpful Wavelet Coefficients for Continuous K-Nearest Neighbor Queries in Stream Processing.- A Neural Network-Based Cooperative Spectrum Sensing Scheme for Cognitive Radio Systems.- Intelligent Computing in Robotics.- Comparison of the Observability Indices for Robot Calibration considering Joint Stiffness Parameters.- Intelligent Computing in Computer Vision.- Human Computer Interaction Using Hand Gestures.- Smart Wheelchair Navigation Based on User's Gaze on Destination.- Entrance Detection of Building Component Based on Multiple Cues.- Intelligent Prediction and Time Series Analysis.- Developing an Evolutionary Neural Network Model for Stock Index Forecasting.- A Tower-Shadow Model for Wind Turbines Using a Wavelet-Prony Method.- Special Session on New Hand-Based Biometric Methods.- Contrast Enhancement and Metrics for Biometric Vein Pattern Recognition.- Feature Extraction Method for Contactless Palmprint Biometrics.- Special Session on Theories and Applications in Advanced Intelligent Computing.- Numerical Analysis for Stochastic Investment System with Poisson Jumps.- Quantum Collapsing Median Filter.- An Impulse C Application in the LDPC Decoding Algorithm.- Research on Algorithm of Parallel Garbage Collection Based on LISP 2 for Multi-core System.- Study on Anode Effect Prediction of Aluminium Reduction Applying Wavelet Packet Transform.- Rotating Machinery Fault Diagnosis Based on EMD-Approximate Entropy and LS-SVM.- Study of Applications Based on Measurement Technology in the Future Smart Grid.- Palm Line Extraction Using FRIT.- Fast ICA for Multi-speaker Recognition System.- Variable Universe Adaptive Fuzzy-PI Compound Control Applied in Maximum Power Point Tracking for Photovoltaic Energy Generation System.- Integrated and Automated Dielectric Measurement System at Millimeter Wavelengths.- Special Session on Search Based Software Engineering.- Software Security Testing of Web Applications Based on SSD.- Special Session on Bio-inspired Computing and Applications.- A Review of Bacterial Foraging Optimization Part I: Background and Development.- A Review of Bacterial Foraging Optimization Part II : Applications and Challenges.- Liquidity Risk Portfolio Optimization Using Swarm Intelligence.- Special Session on Advance in Dimensionality Reduction Methods and Its Applications.- Dimension Reduction with Semi-supervised Pairwise Covariance-Preserving Projection.- Special Session on Recent Advances in Medical Informatics.- Analysis of Impact Factors in Acupuncture for Patients with Migraine--Doubts on Prof. Andrew J Vickers' Conclusion.
• (source: Nielsen Book Data)

• Neural Networks.- Design of a Novel Six-Dimensional Force/Torque Sensor and Its Calibration Based on NN.- Incremental-Based Extreme Learning Machine Algorithms for Time-Variant Neural Networks.- Global Exponential Robust Stability of Hopfield Neural Networks with Reaction-Diffusion Terms.- Direct Inverse Model Control Based on a New Improved CMAC Neural Network.- Further Research on Extended Alternating Projection Neural Network.- Global Synchronization in an Array of Hybrid Coupling Neural Networks with Multiple Time-Delay Components.- Colour Image Segmentation Based on a Spiking Neural Network Model Inspired by the Visual System.- The White Noise Impact on the Optimal Performance of the Hopfield Neural Network.- The Study and Realization of Virtual Organization File System Based on DHT Technology.- Evolutionary Learning and Genetic Algorithms.- A Novel Quantum Genetic Algorithm for PID Controller.- Research on Hybrid Evolutionary Algorithms with Differential Evolution and GUO Tao Algorithm Based on Orthogonal Design.- An Improved Evolution Strategy for Constrained Circle Packing Problem.- Lecture Notes in Computer Science: Research on Multi-robot Avoidance Collision Planning Based on XCS.- Fuzzy Theory and Models.- An Integrated Method for the Construction of Compact Fuzzy Neural Models.- Scalarization of Type-1 Fuzzy Markov Chains.- Fuzzy Systems and Soft Computing.- Applying Fuzzy Differential Equations to the Performance Analysis of Service Composition.- Lattice Structures of Fuzzy Soft Sets.- A Predicate Formal System of Universal Logic with Projection Operator.- A Neuro-Evolutive Interval Type-2 TSK Fuzzy System for Volatile Weather Forecasting.- A Soft Computing Approach for Obtaining Transition Regions in Satellite Images.- Particle Swarm Optimization and Niche Technology.- Particle Swarm Optimization for Two-Stage Fuzzy Generalized Assignment Problem.- A Novel Cyclic Discrete Optimization Framework for Particle Swarm Optimization.- Economic Dispatch Considering Ancillary Service Based on Revised Particle Swarm Optimization Algorithm.- Particle Swarm Optimization-Based Extremum Seeking Control.- Image Contour Extraction Based on Ant Colony Algorithm and B-snake.- Supervised and Semi-supervised Learning.- An Improved Hidden Markov Model for Literature Metadata Extraction.- Discriminative Training of Subspace Gaussian Mixture Model for Pattern Classification.- Unsupervised and Reinforcement Learning.- A Stage by Stage Pruning Algorithm for Detecting the Number of Clusters in a Dataset.- Adaptive Independent Component Analysis by Modified Kernel Density Estimation.- Combinatorial and Numerical Optimization.- Cross System Bank Branch Evaluation Using Clustering and Data Envelopment Analysis.- He's Variational Iteration Method for Solving Convection Diffusion Equations.- GRASP for Low Autocorrelated Binary Sequences.- miRNA Target Prediction Method Based on the Combination of Multiple Algorithms.- Imperialistic Competitive Algorithm for Solving a Dynamic Cell Formation Problem with Production Planning.- Systems Biology and Computational Biology.- Genome-Wide DNA Methylation Profiling in 40 Breast Cancer Cell Lines.- GRIDUISS - A Grid Based Universal Immune System Simulator Framework.- Performance Comparison of Tumor Classification Based on Linear and Non-linear Dimensionality Reduction Methods.- Neural Computing and Optimization.- PH Optimal Control in the Clarifying Process of Sugar Cane Juice Based on DHP.- Nature Inspired Computing and Optimization.- Parameter-Free Deterministic Global Search with Simplified Central Force Optimization.- Comparison of Optimality and Robustness between SA, TS and GRASP Metaheuristics in FJSP Problem.- Hardware Emulation of Bacterial Quorum Sensing.- Knowledge Discovery and Data Mining.- Finding Research Community in Collaboration Network with Expertise Profiling.- The Ideal Data Representation for Feature Extraction of Traditional Malay Musical Instrument Sounds Classification.- Mining Reputation of Person/Product from Comment and Reply on UCC/Internet Article.- Interaction Analysis for Adaptive User Interfaces.- Unsupervised Subjectivity-Lexicon Generation Based on Vector Space Model for Multi-Dimensional Opinion Analysis in Blogosphere.- Enhancing Negation-Aware Sentiment Classification on Product Reviews via Multi-Unigram Feature Generation.- Building Associated Semantic Overlay for Discovering Associated Services.- Artificial Life and Artificial Immune Systems.- Immunity-Based Model for Malicious Code Detection.- Sparse Representation-Based Face Recognition for One Training Image per Person.- Semi-supervised Local Discriminant Embedding.- Orthogonal Discriminant Local Tangent Space Alignment.- Intelligent Computing in Image Processing.- Separating Pigment Components of Leaf Color Image Using FastICA.- Fast Algorithm for Multisource Image Registration Based on Geometric Feature of Corners.- Newborn Footprint Recognition Using Subspace Learning Methods.- Plant Classification Using Leaf Image Based on 2D Linear Discriminant Analysis.- Palmprint Recognition Combining LBP and Cellular Automata.- Dual Unsupervised Discriminant Projection for Face Recognition.- Applying Wikipedia-Based Explicit Semantic Analysis for Query-Biased Document Summarization.- Special Session on New Hand-Based Biometric Methods.- A New Approach for Vein Pattern-Based Recognition.- Study of Hand-Dorsa Vein Recognition.- DHV Image Registration Using Boundary Optimization.- Special Session on Recent Advances in Image Segmentation.- A Novel Level Set Model Based on Local Information.- A Multi-Descriptor, Multi-Nearest Neighbor Approach for Image Classification.- Orthogonal Locally Discriminant Projection for Palmprint Recognition.- Special Session on Theories and Applications in Advanced Intelligent Computing.- OPC UA Based Information Modeling for Distributed Industrial Systems.- Voting-Averaged Combination Method for Regressor Ensemble.- Face Recognition Using the Feature Fusion Technique Based on LNMF and NNSC Algorithms.- A PDOC Method for Topology Optimization Design.- Special Session on Search Based Software Engineering.- A Decision Support System Based on GIS for Grain Logistics Vehicle Routing Problem.- On Database Normalization Using User Interface Normal Form.- Special Session on Bio-inspired Computing and Applications.- Improved Particle Swarm Optimizers with Application on Constrained Portfolio Selection.- An Improved Image Rectification Algorithm Based on Particle Swarm Optimization.- Particle Swarm Optimizer Based on Small-World Topology and Comprehensive Learning.- Multi-Objective PSO Based on Evolutionary Programming.- Special Session on Advance in Dimensionality Reduction Methods and Its Applications.- Two-Dimensional Sparse Principal Component Analysis for Palmprint Recognition.- Discovery of Protein's Multifunction and Diversity of Information Transmission.- Special Session on Protein and Gene Bioinformatics: Methods and Applications.- Identification and Analysis of Binding Site Residues in Protein Complexes: Energy Based Approach.- Density Based Merging Search of Functional Modules in Protein-Protein Interaction (PPI) Networks.- Topology Prediction of ?-Helical and ?-Barrel Transmembrane Proteins Using RBF Networks.- Palmprint Recognition Based on Neighborhood Rough Set.- Increasing Reliability of Protein Interactome by Combining Heterogeneous Data Sources with Weighted Network Topological Metrics.- Predicting Protein Stability Change upon Double Mutation from Partial Sequence Information Using Data Mining Approach.- Inference of Gene Expression Regulation via microRNA Transfection.- A Residual Level Potential of Mean Force Based Approach to Predict Protein-Protein Interaction Affinity.
• (source: Nielsen Book Data)

The International Conference on Intelligent Computing (ICIC) was formed to provide an annual forum dedicated to the emerging and challenging topics in artificial intel- gence, machine learning, pattern recognition, image processing, bioinformatics, and computational biology. It aims to bring together researchers and practitioners from both academia and industry to share ideas, problems, and solutions related to the m- tifaceted aspects of intelligent computing. ICIC 2010, held in Changsha, China, August 18-21, 2010, constituted the 6th - ternational Conference on Intelligent Computing. It built upon the success of ICIC 2009, ICIC 2008, ICIC 2007, ICIC 2006, and ICIC 2005 that were held in Ulsan, Korea, Shanghai, Qingdao, Kunming and Hefei, China, respectively. This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications". Papers focusing on this theme were solicited, addressing theories, methodologies, and applications in science and technology.
(source: Nielsen Book Data)

• Evolutionary Computing and Genetic Algorithms
• Adaptive Routing Algorithm in Wireless Communication Networks Using Evolutionary Algorithm
• A New GA
• Based and Graph Theory Supported Distribution System Planning
• Sequencing Mixed-Model Assembly Lines with Limited Intermediate Buffers by a GA/SA-Based Algorithm
• Solving Vehicle Routing Problem Using Ant Colony and Genetic Algorithm
• Knowledge Discovery and Data Mining
• A Research on the Association of Pavement Surface Damages Using Data Mining
• An Integrated Method for GML Application Schema Match
• Application of Classification Methods for Forecasting Mid-Term Power Load Patterns
• Design of Fuzzy Entropy for Non Convex Membership Function
• Higher-Accuracy for Identifying Frequent Items over Real-Time Packet Streams
• Privacy Preserving Sequential Pattern Mining in Data Stream
• Methods of Computing Optimization
• A General k-Level Uncapacitated Facility Location Problem
• Fourier Series Chaotic Neural Networks
• Numerical Simulation and Experimental Study of Liquid-Solid Two-Phase Flow in Nozzle of DIA Jet
• Shape Matching Based on Ant Colony Optimization
• Fuzzy Systems and Soft Computing
• A Simulation Study on Fuzzy Markov Chains
• A Tentative Approach to Minimal Reducts by Combining Several Algorithms
• Ameliorating GM (1, 1) Model Based on the Structure of the Area under Trapezium
• Comparative Study with Fuzzy Entropy and Similarity Measure: One-to-One Correspondence
• Low Circle Fatigue Life Model Based on ANFIS
• New Structures of Intuitionistic Fuzzy Groups
• Intelligent Computing in Pattern Recognition
• An Illumination Independent Face Verification Based on Gabor Wavelet and Supported Vector Machine
• Hardware Deblocking Filter and Impact
• Medical Image Segmentation Using Anisotropic Filter, User Interaction and Fuzzy C-Mean (FCM)
• Medical Image Segmentation Using Fuzzy C-Mean (FCM), Learning Vector Quantization (LVQ) and User Interaction
• New Data Pre-processing on Assessing of Obstructive Sleep Apnea Syndrome: Line Based Normalization Method (LBNM)
• Recognition of Plant Leaves Using Support Vector Machine
• Region Segmentation of Outdoor Scene Using Multiple Features and Context Information
• Two-Dimensional Partial Least Squares and Its Application in Image Recognition
• Intelligent Computing in Bio/Cheminformatics
• A Novel Method of Creating Models for Finite Element Analysis Based on CT Scanning Images
• Accelerating Computation of DNA Sequence Alignment in Distributed Environment
• Predicting Protein Function by Genomic Data-Mining
• Tumor Classification Using Non-negative Matrix Factorization
• Intelligent Control and Automation
• A Visual Humanoid Teleoperation Control for Approaching Target Object
• An Intelligent Monitor System for Gearbox Test
• Development of Simulation Software for Coal-Fired Power Units Based on Matlab/Simulink
• Inconsistency Management
• Neural Network-Based Adaptive Optimal Controller
• A Continuous-Time Formulation
• On Improved Performance Index Function with Enhanced Generalization Ability and Simulation Research
• Intelligent Fault Diagnosis
• A Fault Diagnosis Approach for Rolling Bearings Based on EMD Method and Eigenvector Algorithm
• An Adaptive Fault-Tolerance Agent Running on Situation-Aware Environment
• Dynamic Neural Network-Based Pulsed Plasma Thruster (PPT) Fault Detection and Isolation for Formation Flying of Satellites
• Model-Based Neural Network and Wavelet Packets Decomposition on Damage Detecting of Composites
• Intelligent Computing in Communication
• A High Speed Mobile Courier Data Access System That Processes Database Queries in Real-Time
• A Scalable QoS-Aware VoD Resource Sharing Scheme for Next Generation Networks
• Brain Mechanisms for Making, Breaking, and Changing Rules
• Implementation of a Landscape Lighting System to Display Images
• Intelligent Sensor Networks
• Probability-Based Coverage Algorithm for 3D Wireless Sensor Networks
• Simulating an Adaptive Fault Tolerance for Situation-Aware Ubiquitous Computing
• A Hybrid CARV Architecture for Pervasive Computing Environments
• Intelligent Image/Document Retrievals
• Image and Its Semantic Role in Search Problem
• Color Image Watermarking Scheme Based on Efficient Preprocessing and Support Vector Machines
• Multiple Ranker Method in Document Retrieval
• Special Session on Image Processing, Analysis, and Vision Technology Based Intelligent Robot Systems
• An Elimination Method of Light Spot Based on Iris Image Fusion
• An Improved Model of Producing Saliency Map for Visual Attention System
• Multiple Classification of Plant Leaves Based on Gabor Transform and LBP Operator
• Research on License Plate Detection Based on Wavelet
• Stereo Correspondence Using Moment Invariants
• The Application of the Snake Model in Carcinoma Cell Image Segment
• Special Session on Data Mining and Fusion in Bioinformatics
• Data Clustering and Evolving Fuzzy Decision Tree for Data Base Classification Problems
• Multivariate Polynomials Estimation Based on GradientBoost in Multimodal Biometrics
• Special Session on Advances in Multidimensional Signal Processing
• An Introduction to Volterra Series and Its Application on Mechanical Systems
• Skin Detection from Different Color Spaces for Model-Based Face Detection
• Other Topics
• Applying Frequent Episode Algorithm to Masquerade Detection
• An Agent-Based Intelligent CAD Platform for Collaborative Design
• Design of a Reliable QoS Requirement Based on RCSM by Using MASQ Architecture
• Minimization of the Disagreements in Clustering Aggregation
• Prediction of Network Traffic Using Multiscale-Bilinear Recurrent Neural Network with Adaptive Learning
• Replay Attacks on Han et al.'s Chaotic Map Based Key Agreement Protocol Using Nonce
• The Short-Time Multifractal Formalism: Definition and Implement
• Modified Filled Function Method for Resolving Nonlinear Integer Programming Problem.

This book - in conjunction with the two volumes "LNCS 5226" and "LNAI 5227" - constitutes the refereed proceedings of the Fourth International Conference on Intelligent Computing, ICIC 2008, held in Shanghai, China in September 2008. The intelligent computing technology includes a range of techniques such as artificial intelligence, perceptual and pattern recognition, evolutionary and adaptive computing, informatics theories and applications, computational neuroscience and bioscience, soft computing, case based and constrained reasoning, agents, networking and computer supported co-operative working, human computer interface issues. ICIC theme unifies the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications.
(source: Nielsen Book Data)

• Neural Networks
• Neural Computing and Optimization
• Case Based Reasoning and Autonomy-Oriented Computing
• Knowledge Discovery and Data Mining
• Evolutionary Computing and Genetic Algorithms
• Fuzzy Systems and Soft Computing
• A4 Particle Swarm Optimization and Niche Technology
• Swarm Intelligence and Optimization
• Kernel Methods and Support Vector Machines
• Biological and Quantum Computing
• Intelligent Agent and Web Applications
• Intelligent Sensor Networks
• Intelligent Fault Diagnosis
• Intelligent Control and Automation
• Intelligent Data Fusion and Security
• Intelligent Prediction and Time Series Analysis
• Natural Language Processing and Expert Systems
• Intelligent Image/Document Retrievals
• Intelligent Computing in Bioinformatics
• Intelligent Computing in Signal Processing
• Intelligent Computing in Pattern Recognition
• Intelligent Computing in Commiuncation
• Special Session on Computational Intelligence Approaches and Methods for Security Engineering
• Special Session on Intelligent Human-Computer Interactions for Multi-modal and Autonomous Environment
• Special Session on Intelligent Robot Systems Based on Vision Technology
• Other Topics.

This volume, in conjunction with the two volumes LNCS 4681 and LNAI 4682, constitutes the refereed proceedings of the Third International Conference on Intelligent Computing held in Qingdao, China, in August 2007. The conference sought to establish contemporary intelligent computing techniques as an integral method that underscores trends in advanced computational intelligence and links theoretical research with applications.
(source: Nielsen Book Data)

• Table of Contents Preparing and Understanding Data Linear Regression Logistic Regression Advanced Feature Selection in Linear Models K-Nearest Neighbors and Support Vector Machines Tree-Based Classification Neural Networks and Deep Learning Creating Ensembles and Multiclass Methods Cluster Analysis Principal Component Analysis Association Analysis Time Series and Causality Text Mining Exploring the Machine Learning Landscape Predicting Employee Attrition Using Ensemble Models Implementing a Joke Recommendation Engine Sentiment Analysis of Amazon Reviews with NLP Customer Segmentation Using Wholesale Data Image Recognition Using Deep Neural Networks Credit Card Fraud Detection Using Autoencoders Automatic Prose Generation with Recurrent Neural Networks Winning the Casino Slot Machines with Reinforcement Learning.
• (source: Nielsen Book Data)

Master machine learning techniques with real-world projects that interface TensorFlow with R, H2O, MXNet, and other languages Key Features Gain expertise in machine learning, deep learning and other techniques Build intelligent end-to-end projects for finance, social media, and a variety of domains Implement multi-class classification, regression, and clustering Book DescriptionR is one of the most popular languages when it comes to exploring the mathematical side of machine learning and easily performing computational statistics. This Learning Path shows you how to leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization. You'll tackle realistic projects such as building powerful machine learning models with ensembles to predict employee attrition. You'll explore different clustering techniques to segment customers using wholesale data and use TensorFlow and Keras-R for performing advanced computations. You'll also be introduced to reinforcement learning along with its various use cases and models. Additionally, it shows you how some of these black-box models can be diagnosed and understood. By the end of this Learning Path, you'll be equipped with the skills you need to deploy machine learning techniques in your own projects. This Learning Path includes content from the following Packt products: R Machine Learning Projects by Dr. Sunil Kumar Chinnamgari Mastering Machine Learning with R - Third Edition by Cory Lesmeister What you will learn Develop a joke recommendation engine to recommend jokes that match users' tastes Build autoencoders for credit card fraud detection Work with image recognition and convolutional neural networks Make predictions for casino slot machine using reinforcement learning Implement NLP techniques for sentiment analysis and customer segmentation Produce simple and effective data visualizations for improved insights Use NLP to extract insights for text Implement tree-based classifiers including random forest and boosted tree Who this book is forIf you are a data analyst, data scientist, or machine learning developer this is an ideal Learning Path for you. Each project will help you test your skills in implementing machine learning algorithms and techniques. A basic understanding of machine learning and working knowledge of R programming is necessary to get the most out of this Learning Path.
(source: Nielsen Book Data)

• Effectiveness of graphical models including modeling. Reasoning, model selection
• Logic-probability relations
• Causality. Applying graphical models in real world settings
• Scalability
• Incremental learning.-Parallelization.

This volume constitutes the refereed proceedings of the Second International Workshop on Advanced Methodologies for Bayesian Networks, AMBN 2015, held in Yokohama, Japan, in November 2015. The 18 revised full papers and 6 invited abstracts presented were carefully reviewed and selected from numerous submissions. In the International Workshop on Advanced Methodologies for Bayesian Networks (AMBN), the researchers explore methodologies for enhancing the effectiveness of graphical models including modeling, reasoning, model selection, logic-probability relations, and causality. The exploration of methodologies is complemented discussions of practical considerations for applying graphical models in real world settings, covering concerns like scalability, incremental learning, parallelization, and so on.

• Introduction.- Respondent Privacy.- User Privacy.
• (source: Nielsen Book Data)

This book provides an overview of the research work on data privacy and privacy enhancing technologies carried by the participants of the ARES project. ARES (Advanced Research in Privacy an Security, CSD2007-00004) has been one of the most important research projects funded by the Spanish Government in the fields of computer security and privacy. It is part of the now extinct CONSOLIDER INGENIO 2010 program, a highly competitive program which aimed to advance knowledge and open new research lines among top Spanish research groups. The project started in 2007 and will finish this 2014. Composed by 6 research groups from 6 different institutions, it has gathered an important number of researchers during its lifetime. Among the work produced by the ARES project, one specific work package has been related to privacy. This books gathers works produced by members of the project related to data privacy and privacy enhancing technologies. The presented works not only summarize important research carried in the project but also serve as an overview of the state of the art in current research on data privacy and privacy enhancing technologies.
(source: Nielsen Book Data)

• 1. Speech hyphenation segmentation by means of blind source separation / Harold Szu and Charles Hsu
• 2. Higher-order moments based synthesis of supervised fourier demixing filter / Eiji Uchino, Noriaki Suetake, and Takeshi Yamakawa
• 3. Design and application of an acoustic database navigator for the intractive analysis of psychoacoustic sound archives and sound engineerint / Andreas Konig, Friedrich E. Blutner, Michael Eberhardt, and Robert Wenzel
• 4. Multilayer perceptron networks with adaptive centroid transformation / Mikko Lehtokangas
• 5. Identification and analysis for transiently evoked otoacoustic emission / Liming Li, Jinsen Lin, and Zhengguo Zhang
• 6. New reliability models based on imprecise probabilities / Lev V. Utkin and Sergey V. Gurov.

• 7. Multi-modular neural network for breast cancer detection / Huai Li and K.J. Ray Liu
• 8. Advanced neural nets for visual image communication / Harold Szu and Charles Hsu
• 9. Continuous valued techniques based on the Lagrangian method for the wire routing problem / Shakeel Ismail, Masahiro Nagamatu and Torao Yanaru
• 10. Chaotic neural networks for information processing / Charles Hsu and Harold Szu
• 11. Wavelet encoding for interactive genetic algorithm in emotional image retrieval / Joo-Young Lee and Sung-Bae Cho
• 12. Call admission control using interval arithmetic coulomb energy network / Won Don Lee, Kyunghee Lee and Hong-kee Kim.

This book presents worldwide outstanding research and recent progress in the applications of neural networks, fuzzy logic, chaos, independent component analysis, etc to fields related to speech recognition enhancement, supervised Fourier demixing noise elimination, acoustic databases, the human hearing system, cancer detection, image processing, and visual communications.
(source: Nielsen Book Data)

• Part I: From Machine Learning to Data Mining.- Analyzing Accident Prone Regions by Clustering.- Analyzing Life Insurance Data with Different Classification Techniques for Customers' Behavior Analysis.- Classification of Product Rating Using Data Mining Techniques.- MASS: a Semi-Supervised Multi-Label Classification Algorithm with Specific Feature.- Parallel Self-organizing Map Using Shared Virtual Memory Buffers.- Parametric Optimization of the Selected Classifiers in Binary Classification.- Prediction of Academic Performance During Adolescence Based on Socioeconomic, Psychological and Academic Factors.- A Super-Vector Deep Learning Coprocessor with High Performance-Power Ratio.- Part II: Big Data and Collaborative Decision Support Systems.- Bi-temporal Database Model for Legal Merger Transactions and Late-arriving Information Problem: the Case of Polish Merger Market.- Breathing Movement Analysis for Adjustment of Radiotherapy Planning.- Measuring Improvement in Access to Complete Data in Healthcare Collaborative Dabase Systems.- Rough Set Theory for Supporting Decision Making on Relevance in Browsing Multilingual Digital Resources.- The Social Influence on the Behavioral Intention to Use Mobile Electronic Medical Records.- Stock Prices Growth Pattern by the Emergency Demand After the Great East-Japan Earthquake.- Structure-Based Virtual Screening for Novel Modulators of Human Orexin 2 Receptor with Cloud Systems and Supercomputers.- Supply Chains of Cross-Border E-Commerce.- Towards Personalized Virtual Customer Experience.- Towards Big Management.- Part III: Computer Vision Analysis, Detection, Tracking and Recognition.- Combination of Collision Detection and Visibility Algorithms in Simulation of Effective Placement of Anti-Air Elements.- A Combination of Deep Learning and Hand-Designed Feature for Plant Identification based on Leaf and Flower Images.- An Efficient Defect Classification Algorithm for Ceramic Tiles.- Parking Assistant - Prediction of an Empty Parking Space in Time.- Recent Advances in the Field of Foreground Detection: An Overview.- Tracking of Bone Reparation Process with Using of Periosteal Callus Extraction based on Fuzzy C-Means Algorithm.- Part IV: Data-Intensive Text Processing.- Automatic Post-Editing of Kazakh Sentences Machine Translated from English.- Complex Technology of Machine Translation Resources Extension for the Kazakh Language.- Enhancing Latent Semantic Analysis by Embedding Tagging Algorithm in Retrieving Malay Text Documents.- Exploiting Distance Graph and Hidden Topic Models for Multi-label Text Classification.- Financial Reports and Financial News - An Information Content Gap Analysis.- The Great National Photocorpus of 20th-Century Vietnamese. Origins, assumptions and goals.- The Impact of User Sentiment Aroused by The-day-of-the-week on the Recommendation Effectiveness in Microblog.- Multi-Sentence Compression Using Word Graph and Integer Linear Programming.- A Performance Comparison of Feature Extraction Methods for Sentiment Analysis.- A Study of Plagiarism Checker System Based on Chinese Word Segmentation and SQL Intersection Operation Technique.- Text Summarization Based on Classification Using ANFIS.- Part V: Innovations in Web and Internet Technologies.- Analysis of Indoor Positioning Based on BLE.- A Fusion Technique of Schema and Syntax Rules for Validating Open Data.- Job Description Language for a Browser-Based Computing Platform - A Preliminary Report.- Measuring the Effectiveness of Knowledge Driven Web Applications.- Responsive Data Table Solution with New Scrolling Control Gesture for Better User Experience.- Part VI: New Methods and Applications in Software Engineering.- Adaptation of an ANN-Based Air Quality Forecasting Model to a New Application Area.- Checking Compliance of Program with SecureUML Model.- Generation of Test Data using Genetic Algorithm and Constraint Solver.- Investigating the Issues of using Agile Methods in Offshore Software Development in Sri Lanka.- A Method for Automated Test Cases Generation from UML Models with String ConstraintS.- Mobile Application for Calculation of Optimal Route Between Searched Points of Interest.- On Implementation of the Assumption Generation Method for Component-Based Software Verification.
• (source: Nielsen Book Data)

This book presents recent research in intelligent information and database systems. The carefully selected contributions were initially accepted for presentation as posters at the 9th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2017) held from to 5 April 2017 in Kanazawa, Japan. While the contributions are of an advanced scientific level, several are accessible for non-expert readers. The book brings together 47 chapters divided into six main parts: * Part I. From Machine Learning to Data Mining.* Part II. Big Data and Collaborative Decision Support Systems, * Part III. Computer Vision Analysis, Detection, Tracking and Recognition, * Part IV. Data-Intensive Text Processing, * Part V. Innovations in Web and Internet Technologies, and* Part VI. New Methods and Applications in Information and Software Engineering. The book is an excellent resource for researchers and those working in algorithmics, artificial and computational intelligence, collaborative systems, decision management and support systems, natural language processing, image and text processing, Internet technologies, and information and software engineering, as well as for students interested in such research areas.
(source: Nielsen Book Data)

• IVIS4BigData: A Reference Model for Advanced Visual Interfaces Supporting Big Data Analysis in Virtual Research Environments
• Engineering Study of Tidal Stream Renewable Energy Generation and Visualization: Issues of Process Modelling and Implementation
• Cost effective visualization of research data for cognitive development using mobile Augmented Reality
• Visualizing Next-Generation Sequencing Cancer Data Sets with Cloud Computing
• SenseCare: Towards an Experimental Platform for Home-Based, Visualisation of Emotional States of People with Dementia
• Toward Interactive Visualization of Results from Domain-Specific Text Analytics
• Towards Synchronizing Data Sources and Information Visualizations in Virtual Research Environments
• Visual analytics and mining over Big Data
• A Meta-design Approach to Support Information Access and Manipulation in Virtual Research Environments. <.

This book constitutes the thoroughly refereed post-workshop proceedings of the AVI 2016 Workshop on Road Mapping Infrastructures for Advanced Visual Interfaces Supporting Big Data Applications in Virtual Research Environments, AVI-BDA 2016, held in Bari, Italy, in June 2016. The 10 revised full papers in this volume present the elaborated outcome of the initial position papers capturing the results oft the roadmapping discussions in the workshop at which comments of several external reviewers for these full publications were also integrated.

• Foreword xix Introduction xxi Part I Measuring Success 1
• Chapter 1 Why Understanding Your Web Traffic Is Important to Your Business 3
• Chapter 2 Available Methodologies and Their Accuracy 23
• Chapter 3 Google Analytics Features, Benefits, and Limitations 53 Part II Using Google Analytics Reports 87
• Chapter 4 Using the Google Analytics Interface 89
• Chapter 5 Reports Explained 117 Part III Implementing Google Analytics 163
• Chapter 6 Getting Started: Initial Setup 165
• Chapter 7 Advanced Implementation 207
• Chapter 8 Best Practices Configuration Guide 267
• Chapter 9 Google Analytics Customizations 315 Part IV Using Visitor Data to Drive Website Improvement 357
• Chapter 10 Focusing on Key Performance Indicators 359
• Chapter 11 Real-World Tasks 417
• Chapter 12 Integrating Google Analytics with Third-Party Applications 503 Appendix A Regular Expression Overview 543 Appendix B Useful Tools 551 Appendix C Recommended Further Reading 557 Index 561.
• (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)
This book is intended for use by customers using Google Classic Analytics and does not cover the newer Google Universal Analytics or related Google Tag Manager. Google Analytics is the free tool used by millions of web site owners to assess the effectiveness of their efforts. Its revised interface and new features will offer even more ways to increase the value of your web site, and this book will teach you how to use each one to best advantage. Featuring new content based on reader and client requests, the book helps you implement new methods and concepts, track social and mobile visitors, use the new multichannel funnel reporting features, understand which filters to use, and much more. Gets you up and running with all the new tools in the revamped Google Analytics, and includes content requested by readers and users especially for new GA users Covers social media analytics features, advanced segmentation displays, multi-dashboard configurations, and using Top 20 reports Provides a detailed best-practices implementation guide covering advanced topics, such as how to set up GA to track dynamic web pages, banners, outgoing links, and contact forms Includes case studies and demonstrates how to optimize pay-per-click accounts, integrate AdSense, work with new reports and reporting tools, use ad version testing, and more Make your web site a more effective business tool with the detailed information and advice about Google Analytics in Advanced Web Metrics with Google Analytics, 3nd Edition.
(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)

• Remote Material Handling systems
• Industrial Robotics
• Mobile Robotics
• Adaptive control
• Vision system
• Smart materials
• Tele-operation.

This book constitutes the thoroughly refereed proceedings of the First International Conference of Advancements in Automation, Robotics and Sensing, ICAARS 2016, held in Coimbatore, India, in June 2016. The 83 revised selected papers were selected from 159 submissions and focus on industrial robotics, mobile robotics, adaptive control, vision system, smart materials, and teleoperation.

• Adaptive Sliding mode control of the Furuta pendulum
• Optimal Sliding and Decoupled Sliding Mode Tracking Control by Multi-objective Particle Swarm Optimization and Genetic Algorithms
• Robust Control of Robot Arms via Quasi Sliding Modes and Neural Networks
• A robust adaptive self-tuning sliding mode control for a hybrid actuator in camless internal combustion engines
• Sliding mode control of class of linear uncertain saturated systems
• Sliding mode control scheme of variable speed wind energy conversion system based on the PMSG for utility network connection
• Super-twisting Air/Fuel ratio control for spark ignition engines
• Robust Output Feedback Stabilization of a Magnetic Levitation System Using Higher Order Sliding Mode Control Strategy
• Design and Application of Discrete Sliding Mode Controller for TITO Process Control Systems
• Dynamic fuzzy sliding mode control of underwater vehicles
• An Indirect Adaptive Fuzzy Sliding Mode Power System Stabilizer for Single and Multi-Machine Power Systems
• Higher Order Sliding Mode Control of Uncertain Robot Manipulators
• Generalized H2 sliding mode control for a class of (TS) fuzzy descriptor systems with time-varying delay and nonlinear perturbations
• Rigid spacecraft fault-tolerant control using adaptive fast terminal sliding mode
• Sliding Modes for Fault Tolerant Control
• Transient Stability Enhancement of Power Systems using Observer-based Sliding Mode Control
• Switching Function Optimization of Sliding Mode Control to a Photovoltaic Pumping System
• Contribution to study Performance of the Induction Motor by Sliding Mode Control and Field Oriented Control.- Anti-Synchronization of Identical Chaotic Systems using Sliding Mode Control and an Application to Vaidyanathan-Madhavan Chaotic Systems
• Hybrid Synchronization of Identical Chaotic Systems using Sliding Mode Control and an Application to Vaidyanathan Chaotic Systems
• Global Chaos Control of a Novel Nine-Term Chaotic System via Sliding Mode Control.

This book describes the advances and applications in Sliding mode control (SMC) which is widely used as a powerful method to tackle uncertain nonlinear systems. The book is organized into 21 chapters which have been organised by the editors to reflect the various themes of sliding mode control. The book provides the reader with a broad range of material from first principles up to the current state of the art in the area of SMC and observation presented in a clear, matter-of-fact style. As such it is appropriate for graduate students with a basic knowledge of classical control theory and some knowledge of state-space methods and nonlinear systems. The resulting design procedures are emphasized using Matlab/Simulink software.

• Title page; AmI Revs Up; Introduction; Contents; Cyber Assist Project for Ambient Intelligence; Ambient Intelligence
• From Personal Assistance to Intelligent Megacities; Towards a Context Theory for Context-Aware Systems; An Active Classification System for Context Representation and Acquisition; Ambiance: A Mobile Agent Platform for End-User Programmable Ambient Systems; A Human Activity Aware Learning Mobile Music Player; Two Issues for an Ambient Reminding System: Context-Awareness and User Feedback; Help from Strangers
• Media Arts in Ambient Intelligence Research.

Contains contributions which provide a window into the visions and trends dominating the area of Ambient Intelligence. This book addresses the core technology of the field and provides an analysis of elements of the area which will demand special consideration during the future development of the area.

• Title page; Preface; Contents; Introduction: Aspects of Artificial General Intelligence; A Collection of Definitions of Intelligence; Four Contemporary AGI Designs: A Comparative Treatment; A Foundational Architecture for Artificial General Intelligence; A Working Hypothesis for General Intelligence; From NARS to a Thinking Machine; Adaptive Algorithmic Hybrids for Human-Level Artificial Intelligence; Cognitive Map Dimensions of the Human Value System Extracted from Natural Language; Program Evolution for General Intelligence.

Examines the creation of software programs displaying broad, deep, human-style general intelligence. This work features papers presented at the 2006 AGIRI (Artificial General Intelligence Research Institute) workshop, which illustrates that it is a fit and proper subject for serious science and engineering exploration.

• Knowledge Engineering.- Knowledge Representation and Reasoning under Uncertainty.- Multiagent Systems.- Game Theory and Economic Paradigms.- Game Playing and Interactive Entertainment.- Ambient Intelligence.- Machine Learning Applications.- Machine Learning Methods, Cognitive Modeling.- Cognitive Systems.- Planning and Scheduling.- Robotics.- Vision.- Natural Language Processing.- Human-Computer Interaction, AI in Education.- NLP and Knowledge Representation.- NLP and Machine Learning.- NLP and Text Mining.- Humans and AI.- Human-Aware AI.- General AI, Knowledge Engineering.- AI and the Web Applications.- Computational Sustainability and AI.- Heuristic Search and Optimization.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 16th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2018, held in Trujillo, Peru, in November 2018. The 41 papers presented were carefully reviewed and selected from 92 submissions. The papers are organized in the following topical sections: Knowledge Engineering, Knowledge Representation and Reasoning under Uncertainty., Multiagent Systems., Game Theory and Economic Paradigms, Game Playing and Interactive Entertainment, Ambient Intelligence, Machine Learning Methods, Cognitive Modeling, General AI, Knowledge Engineering, Computational Sustainability and AI, Heuristic Search and Optimization and much more.
(source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 16th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2015, held in Albacete, Spain, in November 2015. The 31 revised full papers presented were carefully selected from 175 submissions. The papers are organized in topical sections on Bayesian networks and uncertainty modeling; fuzzy logic and soft computing; knowledge representation, reasoning, and logic; intelligent systems and environment; intelligent Web and recommender systems; machine learning and data mining; metaheuristics and evolutionary computation; and social robotics.

• Image and video
• Classification
• Clustering
• Multiagent Systems
• Machine Learning
• Applications
• Evolutionary and Genetic Algorithms
• Metaheuristics
• Optimization
• Fuzzy Logic: Foundations and applications.

This book constitutes the refereed proceedings of the 16th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2016, held in Salamanca, Spain, in September 2016. The 47 revised full papers presented were carefully selected from 166 submissions. Apart from the presentation of technical full papers, the scientific program of CAEPIA 2016 included an App contest, a Doctoral Consortium and, as a follow-up to the success achieved in previously CAEPIA editions, a special session on outstanding recent papers (Key Works) already published in renowned journals or forums.

• Artificial Intelligence.- Fuzzy Sets and Systems.- Evolutionary Algorithms.- Data Mining.- Applications.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 18th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2018, held in Granada, Spain, in October 2018. The 36 full papers presented were carefully selected from 240 submissions. The Conference of the Spanish Association of Artificial Intelligence (CAEPIA) is a biennial forum open to researchers from all over the world to present and discuss their latest scientific and technological advances in Antificial Intelligence (AI). Authors are kindly requested to submit unpublished original papers describing relevant research on AI issues from all points of view: formal, methodological, technical or applied.
(source: Nielsen Book Data)

• Session
• 1. Agents.- Modeling Role-Based Agent Team.- Distributed Collaborative Filtering for Robust Recommendations Against Shilling Attacks.- Competition and Coordination in Stochastic Games.- Multiagent-Based Dynamic Deployment Planning in RTLS-Enabled Automotive Shipment Yard.- R-FRTDP: A Real-Time DP Algorithm with Tight Bounds for a Stochastic Resource Allocation Problem.- A Reorganization Strategy to Build Fault-Tolerant Multi-Agent Systems.- Session
• 2. Bioinformatics.- A Multi-site Subcellular Localizer for Fungal Proteins.- Selecting Genotyping Oligo Probes Via Logical Analysis of Data.- Session
• 3. Classification.- Learning the Semantic Meaning of a Concept from the Web.- On Combining Dissimilarity-Based Classifiers to Solve the Small Sample Size Problem for Appearance-Based Face Recognition.- A Novel Approach for Automatic Palmprint Recognition.- ICS: An Interactive Classification System.- Fast Most Similar Neighbor Classifier for Mixed Data.- Performance Measures in Classification of Human Communications.- Cost-Sensitive Decision Trees with Pre-pruning.- Probability Based Metrics for Locally Weighted Naive Bayes.- Recurrent Boosting for Classification of Natural and Synthetic Time-Series Data.- Pattern Classification in No-Limit Poker: A Head-Start Evolutionary Approach.- Session
• 4. Constraint Satisfaction.- Managing Conditional and Composite CSPs.- Multiagent Constraint Satisfaction with Multiply Sectioned Constraint Networks.- Session
• 5. Data Mining.- A Clustering Algorithm Based on Adaptive Subcluster Merging.- Efficient Algorithms for Video Association Mining.- Distributed Data Mining in a Ubiquitous Healthcare Framework.- Constructing a User Preference Ontology for Anti-spam Mail Systems.- Question Answering Summarization of Multiple Biomedical Documents.- A Profit-Based Business Model for Evaluating Rule Interestingness.- Session
• 6. Knowledge Representation and Reasoning.- Reasoning About Operations on Sets.- Analytic Results on the Hodgkin-Huxley Neural Network: Spikes Annihilation.- Improving Importance Sampling by Adaptive Split-Rejection Control in Bayesian Networks.- Adding Local Constraints to Bayesian Networks.- On the Use of Possibilistic Bases for Local Computations in Product-Based Possibilistic Networks.- Reasoning with Conditional Preferences Across Attributes.- Path Propagation for Inference in Bayesian Networks.- Problem-Solving Knowledge Mining from Users' Actions in an Intelligent Tutoring System.- Incremental Neighborhood Graphs Construction for Multidimensional Databases Indexing.- Session
• 7. Learning.- Learning Network Topology from Simple Sensor Data.- Reinforcement Learning in Nonstationary Environment Navigation Tasks.- On the Stability and Bias-Variance Analysis of Kernel Matrix Learning.- Session
• 8. Natural Language.- Query-Based Summarization of Customer Reviews.- Multi-state Directed Acyclic Graphs.- Fuzzy Clustering for Topic Analysis and Summarization of Document Collections.- Creating a Fuzzy Believer to Model Human Newspaper Readers.- Rethinking the Semantics of Complex Nominals.- A Hybrid Approach to Improving Automatic Speech Recognition Via NLP.- Session
• 9. Planning.- Planning in Multiagent Expedition with Collaborative Design Networks.- Hierarchical Shortest Pathfinding Applied to Route-Planning for Wheelchair Users.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 20th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2007, held in Montreal, Canada, in May 2007. The 46 revised full papers cover agents, bioinformatics, classification, constraint satisfaction, data mining, knowledge representation and reasoning, learning, natural language, and planning.
(source: Nielsen Book Data)

• Actions and Behaviours
• Audio and Visual Recognition
• Natural Language Processing
• Reasoning and Learning
• Streams and Distributed Computing.

This book constitutes the refereed proceedings of the 29th Canadian Conference on Artificial Intelligence, Canadian AI 2016, held in Victoria, BC, Canada, in May/June 2016. The 12 full papers and 27 short papers presented were carefully reviewed and selected from 97 submissions. The focus of the conference was on the following subjects: actions and behaviours, audio and visual recognition, natural language processing, reasoning and learning, streams and distributed computing.

• Data Mining and Machine Learning.- Planning and Combinatorial Optimization.- AI Applications.- Natural Language Processing.- Uncertainty and Preference Reasoning.- Agent Systems.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 30th Canadian Conference on Artificial Intelligence, Canadian AI 2017, held in Edmonton, AB, Canada, in May 2017. The 19 regular papers and 24 short papers presented together with 6 Graduate Student Symposium papers were carefully reviewed and selected from 62 submissions. The focus of the conference was on the following subjects: Data Mining and Machine Learning; Planning and Combinatorial Optimization; AI Applications; Natural Language Processing; Uncertainty and Preference Reasoning; and Agent Systems.
(source: Nielsen Book Data)

• Compressing Bayesian Networks: Swarm-Based Descent, Efficiency, and Posterior Accuracy.- De-Causalizing NAT-Modeled Bayesian Networks for Inference Efficiency.- A Novel Evaluation Methodology for Assessing Off-Policy Learning Methods in Contextual Bandits.- Synthesizing Controllers: On the Correspondence Between LTL Synthesis and Non-Deterministic Planning.- Logic-Based Benders Decomposition for Two-Stage Flexible Flow Shop Scheduling with Unrelated Parallel Machines.- Advice-Based Exploration in Model-Based Reinforcement Learning.- Deep Super Learner: A Deep Ensemble for Classification Problem.- One Single Deep Bidirectional LSTM Network for Word Sense Disambiguation of Text Data.- MedFact: Towards Improving Veracity of Medical Information in Social Media Using Applied Machine Learning.- Re-ranking Candidate Lists for Improved Lexical Induction.- Analysis of Social Media Posts for Early Detection of Mental Health Conditions.- Motor Bearing Fault diagnosis Using Deep Convolutional Neural Networks with 2D Analysis of Vibration Signal.- Mobile App for Detection of Counterfeit Banknotes.- A Multi-agent Framework for Understanding Addiction.- Infusing Domain Knowledge to Improve the Detection of Alzheimer's Disease from Everyday Motion Behavior.- An Incremental Machine Learning Algorithm for Nuclear Forensics.- MML-Based Approach for Determining the Number of Topics in EDCM Mixture Models.- Constrained Bayesian Optimization for Problems with Piece-wise Smooth Constraints.- Dimensionality Reduction and Visualization by Doubly Kernelized Unit Ball Embedding.- Accelerated Gradient and Block-wise Gradient Methods for Big Data Factorization.- Learning Belief Revision Operators.- Solving Constraint Satisfaction Problems Using Firey Algorithms.- An AI Planning-Based Approach to the Multi-Agent Plan Recognition Problem.- Predicting Transportation Modes of GPS Trajectories Using Feature Engineering and Noise Removal.- Prediction of Container Damage Insurance Claims for Optimized Maritime Port Operations.- Drug-Target Interaction Network Predictions for Drug Repurposing Using LASSO-based Regularized Linear Classification Model.- Optimal Scheduling for Smart Charging of Electric Vehicles Using Dynamic Programming.- Combining MCTS and A3C for Prediction of Spatially Spreading Processes in Forest Wildfire Settings.- Text-based Detection of Unauthorized Users of Social Media Accounts.- N-gram Based Approach for Automatic Prediction of Essay Rubric Marks.- Matching Resumes to Job Descriptions with Stacked Models.- Towards a Comprehensive Evaluation of Recommenders: A Cognition-based Approach.- A Sentence-level Sparse Gamma Topic Model for Sentiment Analysis.- Topic Detection and document Similarity on Financial News.- Software Defect Prediction from Code Quality Measurements via Machine Learning.- Automated Scheduling: Reinforcement Learning Approach to Algorithm Policy Learning.- Estimating Vineyard Grape Yield from Images.- Real-time Deep Learning Pedestrians Classification on a Micro-controller.- A Unified Evaluation Framework for Recommender Systems.- Early Detection of Alzheimer's Disease Using Deep Learning.- Learning with Prior Domain Knowledge and Insufficient Annotated Data.- Predicting Crime Using Spatial Features.- A Tool for Defining and Simulating Storage Strategies on the Smart Grid.- Decision Assist for Self-Driving Cars.- Rule Mining and Prediction Using the Flek Machine
• A New Machine Learning Engine.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 31th Canadian Conference on Artificial Intelligence, Canadian AI 2018, held in Toronto, ON, Canada, in May 2018. The 16 regular papers and 18 short papers presented together with 7 Graduate Student Symposium papers and 4 Industry Track papers were carefully reviewed and selected from 72 submissions. The focus of the conference was on artificial intelligence research and advanced information and communications technology.
(source: Nielsen Book Data)

• Intro; Preface; Conference Organization; Contents
• Part II; Contents
• Part I; Invited Papers; Measuring Non-compositionality of Verb-Noun Collocations Using Lexical Functions and WordNet Hypernyms; Abstract; 1 Introduction; 2 Related Work on Non-compositionality of Collocations; 3 Lexical Functions as a Concept of the Meaning-Text Theory; 3.1 Meaning-Text Theory (MTT); 3.2 Lexical Function; 3.3 Lexical Functions in Verb-Noun Collocations; 4 Non-compositionality in Terms of Lexical Function Detection Using WordNet Hypernyms; 5 Experiments; 6 Results and Discussion

• 7 Conclusions and Future WorkAcknowledgements; References; Fuzzy-Probabilistic Estimation of the Electric Vehicles Energy Consumption; Abstract; 1 Introduction; 2 Methodology; 2.1 Framework; 2.2 Fuzzy-Probabilistic Methodology; 3 Numerical Example; 4 Conclusions; References; Natural Language Processing Applications; Data-Driven Unsupervised Evaluation of Automatic Text Summarization Systems; Abstract; 1 Introduction; 2 Related Work; 3 Our Approach; 4 Data; 5 Experiments. Results. Discussion; 5.1 Experiment with Informants; 5.2 Preliminary Evaluation of the Summaries

• 5.3 Automatic Keywords Extraction5.4 Comparison of Keywords Given by Different Groups of Informants; 6 Conclusion and Future Work; Acknowledgements; References; Extractive Single-Document Summarization Based on Global-Best Harmony Search and a Greedy Local Optimizer; Abstract; 1 Introduction; 2 Problem Statement and Its Mathematical Formulation; 3 The Proposed Memetic Algorithm; 3.1 Greedy Local Optimizer; 4 Experiment and Evaluation; 4.1 Parameter Tuning; 4.2 Results; 5 Conclusions and Future Work; Acknowledgments; References; SVD-LDA: Topic Modeling for Full-Text Recommender Systems

• 1 Introduction2 LDA and sLDA; 2.1 Latent Dirichlet Allocation; 2.2 Supervised LDA; 3 SVD in Recommender Systems; 3.1 Basic SVD Model in Collaborative Filtering; 3.2 Cold Start, Additional Information, and Content; 4 SVD-LDA; 4.1 SVD-LDA: Exact Sampling; 4.2 SVD-LDA: First Order Approximation; 4.3 Variations of SVD-LDA; 5 Evaluation; 5.1 Dataset; 5.2 RMSE Improves with LDA Training; 5.3 SVD-LDA Recommends Better Than SVD; 5.4 Predictors for Demographic Clusters; 6 Conclusion; References; Movies Recommendation Based on Opinion Mining in Twitter; 1 Introduction

• 2 Classification Models for Opinion Mining2.1 Tokenization; 2.2 Pre-processing; 2.3 Classification Models; 3 Experimental Results; 3.1 Data Collection; 3.2 Tokenization Strategies; 3.3 Pre-processing Strategies; 3.4 Movies Recommendation; 4 Related Work; 5 Conclusions and Future Work; References; Inferring Sentiment-Based Priors in Topic Models; 1 Introduction; 2 Latent Dirichlet Allocation; 2.1 Notation and the Basic LDA Model; 2.2 LDA Extensions; 2.3 Topic Models for Sentiment Analysis; 3 Learning Sentiment Priors with the EM Algorithm; 4 Experimental Results; 5 Conclusion; References

The two volume set LNAI 9413 + 9414 constitutes the proceedings of the 14th Mexican International Conference on Artificial Intelligence, MICAI 2015, held in Cuernavaca, . Morelos, Mexico, in October 2015. The total of 98 papers presented in these proceedings was carefully reviewed and selected from 297 submissions. They were organized in topical sections named: natural language processing; logic and multi-agent systems; bioinspired algorithms; neural networks; evolutionary algorithms; fuzzy logic; machine learning and data mining; natural language processing applications; educational applications; biomedical applications; image processing and computer vision; search and optimization; forecasting; and intelligent applications.
(source: Nielsen Book Data)