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• Fundamentals of Multimedia Signal Processing and Information Hiding.- An Introduction to Intelligent Multimedia Data Hiding.- Advances in Multimedia Signal Processing.- Digital Video Coding - Techniques and Standards.- Advances of MPEG Scalable Video Coding Standard.- Various Data Hiding Techniques.- A Bit-Level Visual Secret Sharing Scheme for Multi-Secret Images Using Rotation and Reversion Operatations.- Adaptive Data Hiding Scheme for Palette Images.- GIS Watermarking: Hiding Data in 2D Vector Maps.- Adaptive Embedding and Detection for Improved Video Watermarking.- Steganographic Methods Focusing on BPCS Steganography.- Practical Applications of Intelligent Multimedia Signal Processing and Data Hiding Systems.- Intelligent Video Event Detection for Surveillance Systems.- Print-to-Web Linking Technology Using a Mobile Phone Camera and its Applications in Japan.- Multipurpose Image Watermarking Algorithms and Applications.- Tabu Search Based Multi-Watermarking over Lossy Networks.- Reversible Watermarking Techniques.
• (source: Nielsen Book Data)

This book lays out all the latest research in the area of multimedia data hiding. The book introduces multimedia signal processing and information hiding techniques. It includes multimedia representation, digital watermarking fundamentals and requirements of watermarking. It moves on to cover the recent advances in multimedia signal processing, before presenting information hiding techniques including steganography, secret sharing and watermarking. The final part of this book includes practical applications of intelligent multimedia signal processing and data hiding systems.
(source: Nielsen Book Data)

• An introduction to intelligent multimedia data hiding / Hsiang-Cheh Huang [and others]
• Digital video coding -- techniques and standards / Feng Pan
• Advances of MPEG scalable video coding standard / Wen-Hsiao Peng [and others]
• A bit-level visual secret sharing scheme for multi-secret images using rotation and reversion operations / Chin-Chen Chang, Tzu-Chuen Lu, Yi-Hsuan Fan
• Adaptive data hiding scheme for palette images / Chin-Chen Chang, Yu-Zheng Wang, Yu-Chen Hu
• GIS watermarking : hiding data in 2D vector maps / Xia-Mu Niu, Cheng-Yong Shao, Xiao-Tong Wang
• Adaptive embedding and detection for improved video watermarking / Isao Echizen [and others]
• Steganographic methods focusing on BPCS steganography / Hideki Noda, Michiharu Niimi, Eiji Kawaguchi
• Intelligent video event detection for surveillance systems / Hong-Yuan Mark Liao [and others]
• Print-to-Web linking technology using a mobile phone camera and its applications in Japan / Zheng Liu
• Multipurpose image watermarking algorithms and applications / Zhe-Ming Lu, Hans Burkhardt, Shu-Chuan Chu
• Tabu search based multi-watermarking over lossy networks / Hsiang-Cheh Huang [and others]
• Reversible watermarking techniques / Shao-Wei Weng, Yao Zhao, Jeng-Shyang Pan.

This book lays out all the latest research in the area of multimedia data hiding. The book introduces multimedia signal processing and information hiding techniques. It includes multimedia representation, digital watermarking fundamentals and requirements of watermarking. It moves on to cover the recent advances in multimedia signal processing, before presenting information hiding techniques including steganography, secret sharing and watermarking. The final part of this book includes practical applications of intelligent multimedia signal processing and data hiding systems.
(source: Nielsen Book Data)

• 1.
• Deep Learning for Innovative Medical Decision Support
• 2.
• Deep Learning and Image Analysis for Medical Decision Support
• 3.
• Deep Learning Oriented Systems for Medical Education
• 4.
• Hybrid Deep Systems for Medical Education and Decision Support
• 5.
• Deep Learning and Optimization for Medical Education and Decision Support 6.
• Deep Learning and Multimedia for Medical Education and Decision Support
• 7.
• Deep Learning and Traditional Methods for Medical Education and Decision Support.
• (source: Nielsen Book Data)

This book explores various applications of deep learning-oriented diagnosis leading to decision support, while also outlining the future face of medical decision support systems. Artificial intelligence has now become a ubiquitous aspect of modern life, and especially machine learning enjoysgreat popularity, since it offers techniques that are capable of learning from samples to solve newly encountered cases. Today, a recent form of machine learning, deep learning, is being widely used with large, complex quantities of data, because today's problems require detailed analyses of more data. This is critical, especially in fields such as medicine. Accordingly, the objective of this book is to provide the essentials of and highlight recent applications of deep learning architectures for medical decision support systems. The target audience includes scientists, experts, MSc and PhD students, postdocs, and any readers interested in the subjectsdiscussed. The book canbe used as a reference work to support courses on artificial intelligence, machine/deep learning, medical and biomedicaleducation. .
(source: Nielsen Book Data)

• Identification of the Conjugate Pair to Estimating Object Distance: An Application of the Ant Colony Algorithm.-Design of Palm Acupuncture Points Indicator.- Low-rank Representation and Locality-constrained Regression for Robust Low-Resolution Face Recognition.- Face Recognition Benchmark with ID Photos.- Scene Relighting using a Single Reference Image through Material Constrained Layer Decomposition.- Applying Adaptive Actor-critic Learning to Human Upper Lime Lifting Motion.- A Demand-based Allocation Mechanism for Virtual Machine.- A Joint Hierarchy Model for Action Recognition Using Kinect.- QoS-Based Medical Program Evolution.- An Improved 3D Surface Reconstruction Method based on Three Wavelength Phase Shift Profilometry.- The Research on the Lung Tumor Imaging based on the Electrical Impedance Tomography.- Combining CNN and MRF for Road Detection.- The Increasing of Discrimination Accuracy of Waxed Apples based on Hyperspectral Imaging Optimized by Spectral Correlation Analysis.- A Diffeomorphic Demons Approach to Statistical Shape Modeling.
• (source: Nielsen Book Data)

This book highlights selected papers presented at the 2nd International Symposium on Artificial Intelligence and Robotics 2017 (ISAIR2017), held in Nakamura Centenary Memorial Hall, Kitakyushu, Japan on November 25-26, 2017. Today, the integration of artificial intelligence and robotic technologies has become a topic of growing interest for both researchers and developers from academic fields and industries worldwide, and artificial intelligence is poised to become the main approach pursued in next-generation robotics research. The rapidly growing number of artificial intelligence algorithms and big data solutions has significantly extended the number of potential applications for robotic technologies. However, it also poses new challenges for the artificial intelligence community. The aim of this symposium is to provide a platform for young researchers to share the latest scientific achievements in this field, which are discussed in these proceedings.
(source: Nielsen Book Data)

• Identification of the Conjugate Pair to Estimating Object Distance: An Application of the Ant Colony Algorithm.-Design of Palm Acupuncture Points Indicator
• Low-rank Representation and Locality-constrained Regression for Robust Low-Resolution Face Recognition
• Face Recognition Benchmark with ID Photos
• Scene Relighting using a Single Reference Image through Material Constrained Layer Decomposition
• Applying Adaptive Actor-critic Learning to Human Upper Lime Lifting Motion
• A Demand-based Allocation Mechanism for Virtual Machine
• A Joint Hierarchy Model for Action Recognition Using Kinect
• QoS-Based Medical Program Evolution
• An Improved 3D Surface Reconstruction Method based on Three Wavelength Phase Shift Profilometry
• The Research on the Lung Tumor Imaging based on the Electrical Impedance Tomography
• Combining CNN and MRF for Road Detection
• The Increasing of Discrimination Accuracy of Waxed Apples based on Hyperspectral Imaging Optimized by Spectral Correlation Analysis
• A Diffeomorphic Demons Approach to Statistical Shape Modeling.

This book highlights selected papers presented at the 2nd International Symposium on Artificial Intelligence and Robotics 2017 (ISAIR2017), held in Nakamura Centenary Memorial Hall, Kitakyushu, Japan on November 25-26, 2017. Today, the integration of artificial intelligence and robotic technologies has become a topic of growing interest for both researchers and developers from academic fields and industries worldwide, and artificial intelligence is poised to become the main approach pursued in next-generation robotics research. The rapidly growing number of artificial intelligence algorithms and big data solutions has significantly extended the number of potential applications for robotic technologies. However, it also poses new challenges for the artificial intelligence community. The aim of this symposium is to provide a platform for young researchers to share the latest scientific achievements in this field, which are discussed in these proceedings.

• On the use of matrix Bloom filters in data leak protection.- A hybrid approach for the automatic extraction of causal relations from text.- Ambient Intelligence by ATML Rules in BackHome.- Dense Semantic Graph and its Application in Single Document Summarisation.- Web Architecture of a Web Portal for Reliability Diagnosis of Bus Regularity.- An approach to Knowledge Formalization.
• (source: Nielsen Book Data)

This book addresses new challenges and emerging ideas in Distributed Information Filtering and Retrieval. It gathers extended papers presented at DART 2013 (the 7th International Workshop on Information Filtering and Retrieval), held on December 6, 2013 in Turin, Italy, and co-hosted with the XIII International Conference of the Italian Association for Artificial Intelligence. The main focus of DART was to discuss and compare suitable novel solutions based on intelligent techniques and applied to real-world contexts. The papers presented here offer a comprehensive review of related work and state-of-the-art techniques. The authors - a mix of respected practitioners and researchers - share their findings on a range of topics, including data leak protection on text comparison, natural language processing, ambient intelligence, information retrieval and web portals, and knowledge management. All contributions were carefully reviewed by experts in the respective area, who also provided useful suggestions to improve the book's overall quality.
(source: Nielsen Book Data)

• Part I: Main Track.- Long distance in-links for ranking enhancement.- Concept Tracking and Adaptation for Drifting Data Streams under Extreme Verification Latency.- Adversarial Sample Crafting for Time Series Classification with Elastic Similarity Measures.- Slot Co-allocation Optimization in Distributed Computing with Heterogeneous Resources.- About Designing an Observer Pattern-Based Architecture for a Multi-Objective Metaheuristic Optimization Framework.- Scalable Inference of Gene Regulatory Networks with the Spark Distributed Computing Platform.- Finding Best Compiler Options for Critical Software Using Parallel Algorithms.- Drift Detection over Non-stationary Data Streams using Evolving Spiking Neural Networks.- Part II: Energy.- A Hybrid Ensemble of Heterogeneous Regressors for Wind Speed Estimation in Wind Farms.- Bio-inspired approximation to MPPT under real irradiation conditions.- Part III: Industry.- Decision Making in Industry 4.0 Scenarios supported by Imbalanced Data Classification.
• (source: Nielsen Book Data)

This book gathers a wealth of research contributions on recent advances in intelligent and distributed computing, and which present both architectural and algorithmic findings in these fields. A major focus is placed on new techniques and applications for evolutionary computation, swarm intelligence, multi-agent systems, multi-criteria optimization and Deep/Shallow machine learning models, all of which are approached as technological drivers to enable autonomous reasoning and decision-making in complex distributed environments. Part of the book is also devoted to new scheduling and resource allocation methods for distributed computing systems. The book represents the peer-reviewed proceedings of the 12th International Symposium on Intelligent Distributed Computing (IDC 2018), which was held in Bilbao, Spain, from October 15 to 17, 2018.
(source: Nielsen Book Data)

• Production and Economic Relations on the Internet: Another Level of Development of Economic Science.- Internet Economy: Existence from the Point of View of Micro-Economic Aspect.- Perspectives of Internet Economy Creation.- Modern Foundations of Internet Economy.
• (source: Nielsen Book Data)

This unique book adopts a problem approach to study the Internet economy, which consists in assessing its contradiction to classic economy, analyzing it, and describing how the Internet economy is developing in modern Russia. The authors study its sense and basic principles, identify the factors that influence its functioning and development, analyze the crisis of the Internet economy, and conduct a comparative analysis of the Internet economy and classic economy. The book is primarily intended for postgraduates, educators and researchers who study the foundations of the modern macro-economy. Based on the conclusions and results presented here, they will be able to create their own scientific studies. Further, problem analysis of the Internet economy and classic economy makes it possible to identify the peculiarities and prospects of development, and to form recommendations for the highly effective management of modern economic systems.
(source: Nielsen Book Data)

• Introduction.- Perceptual compression.- Predictive sampler design.- Perceptual deadzone for vector valued stimulus.- Temporal resolvability of kinesthetic stimuli.- Effect of rate of change of stimulus.- Dependence of deadzone on task specificity.- Sequential effect on kinesthetic perception.
• (source: Nielsen Book Data)

This book focuses on the study of possible adaptive sampling mechanisms for haptic data compression aimed at applications like tele-operations and tele-surgery. Demonstrating that the selection of the perceptual dead zones is a non-trivial problem, it presents an exposition of various issues that researchers must consider while designing compression algorithms based on just noticeable difference (JND). The book begins by identifying perceptually adaptive sampling strategies for 1-D haptic signals, and goes on to extend the findings on multidimensional signals to study directional sensitivity, if any. The book also discusses the effect of the rate of change of kinesthetic stimuli on the JND, temporal resolution for the perceivability of kinesthetic force stimuli, dependence of kinesthetic perception on the task being performed, the sequential effect on kinesthetic perception, and, correspondingly, on the perceptual dead zone. Offering a valuable resource for researchers, professionals, and graduate students working on haptics and machine perception studies, the book can also support interdisciplinary work focused on automation in surgery.
(source: Nielsen Book Data)

• Machine generated contents note: 1. Introduction
• 1.1. Basics of Haptics
• 1.1.1. Various Research Areas in Haptics
• 1.1.2. Possible Applications
• 1.2. Kinesthetic Perception
• 1.3. Perception: Aware Engineering Design
• 1.4.Organization of the Book
• References
• 2. Perceptual Deadzone
• 2.1. Haptic Data Compression
• 2.2. Perceptual Deadzone for Multidimensional Signals
• 2.3. Effect of Rate of Change of Kinesthetic Stimuli
• References
• 3. Predictive Sampler Design for Haptic Signals
• 3.1. Introduction
• 3.2. Experimental Setup
• 3.2.1. Device Setup
• 3.2.2. Signal Characteristics
• 3.2.3. Lag in User Response
• 3.2.4. Collected Data
• 3.3. Classification of Haptic Response
• 3.3.1. Performance Metric
• 3.3.2. Weber Classifier
• 3.3.3. Level Crossing Classifier
• 3.3.4. Classifiers Based on Decision Tree and Random Forests
• 3.3.5. Effect of Temporal Spacing
• 3.3.6. Significance Test for Classifiers
• 3.4. Applications in Adaptive Sampling
• References.

• Note continued: 4. Deadzone Analysis of 2-D Kinesthetic Perception
• 4.1. Introduction
• 4.2. Experimental Setup
• 4.2.1. Signal Characteristics and User Response
• 4.2.2. Data Statistics
• 4.3. Determination of Perceptual Deadzone
• 4.3.1. The Weber Classifier
• 4.3.2. Level Crossing Classifier
• 4.3.3. Elliptical Deadzone
• 4.3.4. Oriented Elliptical Deadzone
• References
• 5. Effect of Rate of Change of Stimulus
• 5.1. Introduction
• 5.2. Design of Experiment
• 5.2.1. Kinesthetic Force Stimulus
• 5.2.2. Data Collection
• 5.3. System Correction
• 5.4. Estimation of Decision Boundary
• 5.4.1. Parametric Decision Boundary
• 5.4.2. Nonparametric Decision Boundary
• 5.5. Analysis of Results
• References
• 6. Temporal Resolvability of Stimulus
• 6.1. Introduction
• 6.1.1. Motivation for the Study
• 6.1.2. Related Work
• 6.1.3. Our Approach
• 6.2. Experimental Setup
• 6.2.1. Signal Characteristics
• 6.2.2. Data Collection
• 6.3. Estimation of Temporal Resolution.

• Note continued: 6.4. Effect of Fatigue
• 6.5. Application in Data Communication
• References
• 7. Task Dependence of Perceptual Deadzone
• 7.1. Introduction
• 7.1.1. Objective of the Study
• 7.1.2. Prior Work
• 7.1.3. Our Approach
• 7.2. Design of Experiment
• 7.2.1. Kinesthetic Force Stimulus
• 7.2.2. Data Statistics
• 7.3. Estimation of Perceptual Deadzones
• References
• 8. Sequential Effect on Kinesthetic Perception
• 8.1. Introduction
• 8.2. Sequential Effect
• 8.3. Quantification of Sequential Effect
• 8.3.1. Logistic Regression
• 8.3.2. Description of the Regression Model
• 8.4. Analysis of Effect on Comparative Task
• 8.5. Analysis of Effect on Discriminative Task
• References
• 9. Conclusions.

This book focuses on the study of possible adaptive sampling mechanisms for haptic data compression aimed at applications like tele-operations and tele-surgery. Demonstrating that the selection of the perceptual dead zones is a non-trivial problem, it presents an exposition of various issues that researchers must consider while designing compression algorithms based on just noticeable difference (JND). The book begins by identifying perceptually adaptive sampling strategies for 1-D haptic signals, and goes on to extend the findings on multidimensional signals to study directional sensitivity, if any. The book also discusses the effect of the rate of change of kinesthetic stimuli on the JND, temporal resolution for the perceivability of kinesthetic force stimuli, dependence of kinesthetic perception on the task being performed, the sequential effect on kinesthetic perception, and, correspondingly, on the perceptual dead zone. Offering a valuable resource for researchers, professionals, and graduate students working on haptics and machine perception studies, the book can also support interdisciplinary work focused on automation in surgery.

• A Data Mining based Publish/Subscribe System over Structured Peer-to-Peer Networks.- Secure Identity Management System for Federated Cloud Environment.- Using Word N-Grams as Features in Arabic Text Classification.- Optimization of Emotional Learning Approach to Control Systems with Unstable Equilibrium.- An Evaluation of the MiDCoP Method for Imputing Allele Frequency in Genome Wide Association Studies.- An Approach to Construct Weighted Minimum Spanning Tree in Wireless Sensor Networks.- Elements of Difficulty Level in Mathematics.- Identify a Specified Fish Species by the Co-occurrence Matrix and AdaBoost.- Constraint-based Verification of Compositions in Safety-critical Component-based Systems.- A Polynomial-Time Algorithm for Checking the Equivalence of Deterministic Restricted One-Counter Transducers Which Accept by Final State.- An Unsupervised Ensemble Approach for Emotional Scene Detection from Lifelog Videos.- A Discovery Method of Anteroposterior Correlation for Big Data Era.- Increasing the Accuracy of Software Fault Prediction Using Majority Ranking Fuzzy Clustering.-.
• (source: Nielsen Book Data)

This edited book presents scientific results of 15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2014) held on June 30 - July 2, 2014 in Las Vegas Nevada, USA. The aim of this conference was to bring together scientists, engineers, computer users, and students to share their experiences and exchange new ideas, research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the 13 outstanding papers from those papers accepted for presentation at the conference.
(source: Nielsen Book Data)

• Advanced Optimization Methods and Their Applications. Solution Methods for General Quadratic Programming Problem with Continuous and Binary Variables: Overview / Nguyen Van Thoai
• Branch and Bound Algorithm Using Cutting Angle Method for Global Minimization of Increasing Positively Homogeneous Functions / Nguyen Van Thoai
• A DC Programming Framework for Portfolio Selection by Minimizing the Transaction Costs / Pham Viet-Nga, Hoai An Le Thi, Pham Dinh Tao
• Efficient Algorithms for Feature Selection in Multi-class Support Vector Machine / Hoai An Le Thi, Manh Cuong Nguyen
• Image Segmentation via Feature Weighted Fuzzy Clustering by a DCA Based Algorithm / Hoai Minh Le [and others]
• Clustering Data Streams over Sliding Windows by DCA / Ta Minh Thuy, Le Thi Hoai An, Lydia Boudjeloud-Assala
• A Column Generation Based Label Correcting Approach for the Sensor Management in an Information Collection Process / Duc Manh Nguyen [and others].

• Planning Sensors with Cost-Restricted Subprocess Calls: A Rare-Event Simulation Approach / Frédéric Dambreville
• Large Scale Image Classification with Many Classes, Multi-features and Very High-Dimensional Signatures / Thanh-Nghi Doan, Thanh-Nghi Do, François Poulet
• Partitioning Methods to Parallelize Constraint Programming Solver Using the Parallel Framework Bobpp / Tarek Menouer, Bertrand Le Cun, Pascal Vander-Swalmen
• Queueing Theory and Applications. Spectral Expansion Solution Methodology for QBD-M Processes and Applications in Future Internet Engineering / Tien Van Do, Ram Chakka, János Sztrik
• On the Properties of Generalised Markovian Queues with Heterogeneous Servers / Tien Van Do, Ram Chakka
• Performance Analysis of Edge Nodes with Multiple Path Routing / Hung Tuan Tran, Tien Van Do, Yeon-Mo Yang
• Computational Methods for Knowledge Engineering. Meta-concept and Intelligent Data Processing in the Geotechnical Fields / Chi Tran.

• Ekman Layers of Rotating Fluids with Vanishing Viscosity between Two Infinite Parallel Plates / Van-Sang Ngo
• Parallelization of the Fast Multipole Method for Molecular Dynamics Simulations on Multicore Computers / Nguyen Hai Chau
• An Adaptive Neuro-Fuzzy Inference System for Seasonal Forecasting of Tropical Cyclones Making Landfall along the Vietnam Coast / Trong Hai Duong [and others]
• An Application of Computational Collective Intelligence to Governance and Policy Modelling / Tien Van Do [and others]
• A Framework for Building Intelligent Tutoring Systems / Adrianna Kozierkiewicz-Hetmańska, Ngoc Thanh Nguyen
• A Review of AI-Supported Tutoring Approaches for Learning Programming / Nguyen-Thinh Le [and others]
• Supporting Career Counseling with User Modeling and Job Matching / Cuong Duc Nguyen, Khoi Duy Vo, Dung Tien Nguyen
• Knowledge Engineering with Cloud and Grid Computing.

• An Abstraction Model for High-Level Application Programming on the Cloud / Binh Minh Nguyen, Viet Tran, Ladislav Hluchy
• Agent Based Modeling of Ecodistricts with Smart Grid / Murat Ahat, Soufian Ben Amor, Alain Bui
• Cloud-Based Data Warehousing Application Framework for Modeling Global and Regional Data Management Systems / Thanh Binh Nguyen
• Logic Based Methods for Decision Making and Data Mining. A Tableau Method with Optimal Complexity for Deciding the Description Logic SHIQ / Linh Anh Nguyen
• An Approach to Semantic Indexing Based on Tolerance Rough Set Model / Sinh Hoa Nguyen, Hung Son Nguyen
• An Approach for Mining Concurrently Closed Itemsets and Generators / Anh Tran, Tin Truong, Bac Le
• An Efficient Algorithm for Mining Frequent Itemsets with Single Constraint / Hai Duong, Tin Truong, Bac Le
• Mining Frequent Weighted Closed Itemsets / Bay Vo, Nhu-Y Tran, Duong-Ha Ngo.

The book consists of 29 extended chapters which have been selected and invited from the submissions to the 1st International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA 2013) held on 9-10 May, 2013 in Warsaw, Poland. The book is organized into five parts, which are: Advanced Optimization Methods and Their Applications, Queuing Theory and Applications, Computational Methods for Knowledge Engineering, Knowledge Engineering with Cloud and Grid Computing, and Logic Based Methods for Decision Making and Data Mining, respectively. All chapters in the book discuss theoretical and practical issues connected with computational methods and optimization methods for knowledge engineering.
(source: Nielsen Book Data)

• Housing Prices Wavelet Entropy to Understand Macroeconomic States
• Myriam P. Sassano and Araceli N. Proto
• Dynamical Models for Representing and Building Consensus in Committees
• Antonio Maturo, Massimo Squillante and Aldo G.S. Ventre
• Financial Applications of Flow Network Theory
• Mario Eboli
• Networks of Financial Contagion
• Luisa Cutillo, Giuseppe De Marco and Chiara Donnini
• Rumour Propagation on Social Networks as a Function of Diversity
• Bernard Brooks
• Formal and Informal Networks in Organizations
• Silvana Stefani and Anna Torriero
• Assessing Consumer Credit Applications by a Genetic Programming Approach
• Salvatore Rampone, Franco Frattolillo and Federica Landolfi
• Towards a Human Consistent Analysis of Innovativeness via Linguistic Data Summaries and Their Protoforms
• Janusz Kacprzyk, Sławomir Zadrożny and Tadeusz Baczko
• An Investigation of Computational Complexity of the Method of Symbolic Images
• Giulia Rotundo
• Spatial Database Quality and the Potential Uncertainty Sources.

• Šárka Hošková-Mayerová, Václav Talhofer, Alois Hofmann and Petr Kubíček
• Mathematical Model Used in Decision-Making Process with Respect to the Reliability of Geodatabase
• Šárka Hošková-Mayerová, Václav Talhofer, Alois Hofmann and Petr Kubíček
• Complex Networks Topology: The Statistical Self-similarity Characteristics of the Average Overlapping Index
• Francisco O. Redelico and Araceli N. Proto
• Taxicab Non Symmetrical Correspondence Analysis for the Evaluation of the Passenger Satisfaction
• Biagio Simonetti and Antonio Lucadamo
• Simulation Study for PLS Path Modelling with High-Order Construct: A Job Satisfaction Model Evidence
• Enrico Ciavolino and Mariangela Nitti
• Log-Ratio and Parallel Factor Analysis: An Approach to Analyze Three-Way Compositional Data
• Michele Gallo
• Analyzing AHP Matrix by Robust Regression
• Gabriella Marcarelli, Biagio Simonetti and Viviana Ventre.

In this volume recent advances in the use of modern quantitative models for the analysis of various problems related to the dynamics of social and economic systems are presented. The majority of the chapters describe tools and techniques of broadly perceived computational intelligence, notably fuzzy logic, evolutionary computation, neural networks and some non-standard probabilistic and statistical analyses. Due to the high complexity of the systems and problems considered, in many situations it is necessary to consider at the same time analytic, topological and statistical aspects and apply appropriate procedures and algorithms. This volume is a direct result of vivid discussions held during the Fifth International Workshop on Dynamics of Social and Economical Systems (DYSES) which was held at Benevento, Italy September 20-25, 2010, as well as a couple of post-workshop meetings and consultations.

• New Trends in Web User Behaviour Analysis / Pablo E. Román, Juan D. Velásquez, Vasile Palade and Lakhmi C. Jain
• Web Usage Data Pre-processing / Gaston L'Huillier and Juan D. Velásquez
• Cognitive Science forWeb Usage Analysis / Pablo E. Román and Juan D. Velásquez
• Web Usage Mining: Discovering Usage Patterns for Web Applications / Giovanna Castellano, Anna M. Fanelli and Maria A. Torsello
• Web Opinion Mining and Sentimental Analysis / Edison Marrese Taylor, Cristián Rodríguez O., Juan D. Velásquez, Goldina Ghosh and Soumya Banerjee
• Web Usage Based Adaptive Systems / Pablo Loyola Heufemann, Jorge Gaete Villegas and In-Young Ko
• Recommender Systems: Sources of Knowledge and Evaluation Metrics / Denis Parra and Shaghayegh Sahebi.

This research volume focuses on analyzing the web user browsing behaviour and preferences in traditional web-based environments, social networks and web 2.0 applications, by using advanced techniques in data acquisition, data processing, pattern extraction and cognitive science for modeling the human actions. The book is directed to graduate students, researchers/scientists and engineers interested in updating their knowledge with the recent trends in web user analysis, for developing the next generation of web-based systems and applications.

• Helicopter Control Algorithms from the Set Orientation to the Set Geographical Location / Zygmunt Kuś and Sławomir Fraś
• The Control System for Autonomous Mobile Platform / Artur Babiarz, Krzysztof Jaskot and Przemysław Koralewicz
• Lyapunov Exponents for Discrete Time-Varying Systems / Adam Czornik, Aleksander Nawrat and Michał Niezabitowski
• Single DOF Powered Exoskeleton Control System, Algorithms and Signal Processing / Michał A. Mikulski
• Probabilistic Approach to Planning Collision Free Path of UAV / Krzysztof Skrzypczyk, Adam Gałuszka, Marcin Pacholczyk and Krzysztof Daniec
• Multi-robot Task Planning Problem with Uncertainty in Game Theoretic Framework / Krzysztof Skrzypczyk and Martin Mellado
• The Concept of Collision-Free Path Planning of UAV Objects / Artur Babiarz and Krzysztof Jaskot
• Planning as Artificial Intelligence Problem -- Short Introduction and Overview / Adam Gałuszka, Marcin Pacholczyk, Damian Bereska and Krzysztof Skrzypczyk.

• The Prototype of Gyro-Stabilized UAV Gimbal for Day-Night Surveillance / Karol Jędrasiak, Damian Bereska and Aleksander Nawrat
• The Comparison of Capabilities of Low Light Camera, Thermal Imaging Camera and Depth Map Camera for Night Time Surveillance Applications / Karol Jędrasiak and Aleksander Nawrat
• Object Detection Using IR Camera / Aleksander Nawrat, Krzysztof Daniec and Tomasz Warmuz
• Characterization of Hokuyo UTM-30LX Laser Range Finder for an Autonomous Mobile Robot / Piotr Demski, Michał Mikulski and Roman Koteras
• Direct Method of IMU Calibration / Witold Ilewicz and Aleksander Nawrat
• Main Aims and Objectives of an IT System in the Implementation of the Project: Design and Implementation of Innovative Unmanned Mobile Platforms for the Needs of Monitoring State Borders / Marcin Błaszczok, Arkadiusz Gwóźdź, Łukasz Hoppe and Krzysztof Skórka.

• Architecture and Functional Division of an IT System GRANICE / Marcin Śleziona
• Integration of IT Systems with the Use of Microsoft BizTalk Server Platform / Tomasz Krawczyk
• Tools and Methods Used to Ensure Security of Processing and Storing Information in Databases and IT Systems and Their Impact on System Performance / Łukasz Hoppe and Łukasz Wąsek
• TGIS Application for Monitoring and Control of Unmanned Flying Platforms / Marek Fischer
• Vision Object Access and Management with Usage of the In-Memory Databases / Aleksandra Werner, Małgorzata Bach and Adam Duszeńko
• SETh-Link the Distributed Management System for Unmanned Mobile Vehicles / Karol Jędrasiak, Aleksander Nawrat and Katarzyna Wydmańska
• Delays Models of Measurement and Control Data Transmission Network / Tadeusz Topór-Kamiński, Beata Krupanek and Jarosław Homa.

One of the world's leading problems in the field of national security is protection of borders and borderlands. This book addresses multiple issues on advanced innovative methods of multi-level control of both ground (UGVs) and aerial drones (UAVs). Those objects combined with innovative algorithms become autonomous objects capable of patrolling chosen borderland areas by themselves and automatically inform the operator of the system about potential place of detection of a specific incident. This is achieved by using sophisticatedmethods of generation of non-collision trajectory for those types of objects and enabling automatic integration of both ground and aerial unmanned vehicles. The topics included in this book also cover presentation of complete information and communication technology (ICT) systems capable of control, observation and detection of various types of incidents and threats. This book is a valuable source of information for constructors and developers of such solutions for uniformed services. Scientists and researchers involved in computer vision, image processing, data fusion, control algorithms or IC can find many valuable suggestions and solutions. Multiple challenges for such systems are also presented.

• Integrative Approaches for Drug Discovery -- PPAR Gamma as a Case Study / Meena Kishore Sakharkar
• Biomedical Informatics and the Future of Medicine / Jean-Pierre A. Kocher
• Inferring E. coli SOS Response Pathway from Gene Expression Data Using IST-DBN with Time Lag Estimation / Lian En Chai, Mohd Saberi Mohamad
• Framework for Biodiversity Information Retrieval in Malaysia / Sarinder K. Dhillon, Baldeve Paunoo
• Using Ant Colony Optimization (ACO) on Kinetic Modeling of the Acetoin Production in Lactococcus Lactis C7 / Nor Farhah Binti Saidin, Chuii Khim Chong
• Semantic Rule-Based Determination of Cancer Stages from Free-Text Radiology Reports / Sangsoo Nam, Heung-Seon Oh, Jong-Beom Kim
• Using Particle Swarm Optimization for Estimating Kinetics Parameters on Essential Amino Acid Production of Arabidopsis Thaliana / Siew Teng Ng, Chuii Khim Chong, Yee Wen Choon
• Content-Based and Similarity-Based Querying for Broad-Usage Medical Image Retrieval / Christopher Town
• Inferring Gene Networks from Gene Expression Data Using Dynamic Bayesian Network with Different Scoring Metric Approaches / Masarrah Abdul Mutalib, Lian En Chai
• Malaysian Parasite Database Infrastructure / Sarinder K. Dhillon, Nur-Imtiazah Shuhaimi
• Prediction of Vanillin Production in Yeast Using a Hybrid of Continuous Bees Algorithm and Flux Balance Analysis (CBAFBA) / Leang Huat Yin, Yee Wen Choon, Lian En Chai
• Identifying Gene Knockout Strategy Using Bees Hill Flux Balance Analysis (BHFBA) for Improving the Production of Ethanol in Bacillus Subtilis / Yee Wen Choon, Mohd Saberi Mohamad
• A Hybrid of Artificial Bee Colony and Flux Balance Analysis for Identifying Optimum Knockout Strategies for Producing High Yields of Lactate in Echerichia Coli / Seet Sun Lee, Yee Wen Choon, Lian En Chai.

Current Biomedical Databases are independently administered in geographically distinct locations, lending them almost ideally to adoption of intelligent data management approaches. This book focuses on research issues, problems and opportunities in Biomedical Data Infrastructure identifying new issues and directions for future research in Biomedical Data and Information Retrieval, Semantics in Biomedicine, and Biomedical Data Modeling and Analysis. The book will be a useful guide for researchers, practitioners, and graduate-level students interested in learning state-of-the-art development in biomedical data management.

• Curation in Chance Discovery / Akinori Abe
• Turning Down a Chance An Argument from Simplicity / Emanuele Bardone and Lorenzo Magnani
• A Chance Favors a Prepared Mind: Chance Discovery from Cognitive Psychology / Hitoshi Terai and Kazuhisa Miwa
• Chance Discovery with Self-Organizing Maps: Discovering Imbalances in Financial Networks / Peter Sarlin
• Map Interface for a Text Data Set by Recursive Clustering / Wataru Sunayama, Shuhei Hamaoka and Kiyoshi Okuda
• Multimodal Discussion Analysis Based on Temporal Sequence / Katsumi Nitta
• Framework of Early Adopters Roaming among Tribes for Discovering Innovative Creation / Mu-Hua Lin, Chao-Fu Hong, Hsiao-Fang Yang and Ai-Ling Wang
• Data-Driven Innovation Technologies for Smarter Business from Innovators' Market Game to iChance Creativity Support System / Hao Wang and Yukio Ohsawa.

• Paired Evaluators Method to Track Concept Drift: An Application in Finance / Masabumi Furuhata, Takanobu Mizuta and Jihei So
• Efficient Service Discovery among Heterogeneous Agents Using a Novel Agent Ranking Algorithm / Hao Lan Zhang, Clement H.C. Leung, Chaoyi Pang and Xijin Tang
• Discovering the Chances of Health Problems and Falls in the Elderly Using Data Mining / Bogdan Pogorelc and Matjaž Gams
• Temporal Logics Modeling Logical Uncertainty, Local and Global Chance Discovery / Vladimir Rybakov
• Discovering Probabilistic Models of Pilot Behavior from Aircraft Telemetry Data / Kirk Ogaard and Ronald Marsh
• Constructing Feature Set by Using Temporal Clustering of Term Usages in Document Categorization / Hidenao Abe and Shusaku Tsumoto
• Finding Rare Patterns with Weak Correlation Constraint: Progress in Indicative and Chance Patterns / Yoshiaki Okubo, Makoto Haraguchi and Takeshi Nakajima.

Since year 2000, scientists on artificial and natural intelligences started to study chance discovery - methods for discovering events/situations that significantly affect decision making. Partially because the editors Ohsawa and Abe are teaching at schools of Engineering and of Literature with sharing the interest in chance discovery, this book reflects interdisciplinary aspects of progress: First, as an interdisciplinary melting pot of cognitive science, computational intelligence, data mining/visualization, collective intelligence ... etc, chance discovery came to reach new application domains e.g. health care, aircraft control, energy plant, management of technologies, product designs, innovations, marketing, finance etc. Second, basic technologies and sciences including sensor technologies, medical sciences, communication technologies etc. joined this field and interacted with cognitive/computational scientists in workshops on chance discovery, to obtain breakthroughs by stimulating each other. Third, "time" came to be introduced explicitly as a significant variable ruling causalities - background situations causing chances and chances causing impacts on events and actions of humans in the future. Readers may urge us to list the fourth, fifth, sixth ... but let us stop here and open this book

• Machine Learning Applications in Cancer Informatics / Abdel-Badeeh M. Salem
• Methods for Interpretation of Data in Medical Informatics / Boris Mirkin
• Visual System of Sign Alphabet Learning for Poorly-Hearing Children / Margarita Favorskaya
• Decorrelation of Sequences of Medical CT Images Based on the Hierarchical Adaptive KLT / Roumen Kountchev, Peter Ivanov
• Compression with Adaptive Speckle Suppression for Ultrasound Medical Images / Roumen Kountchev, Vladimir Todorov
• Adaptive Approach for Enhancement the Visual Quality of Low-Contrast Medical Images / Vladimir Todorov, Roumiana Kountcheva
• An Adaptive Enhancement of X-Ray Images / Veska Georgieva, Roumen Kountchev
• Medical Images Transform by Multistage PCA-Based Algorithm / Ivo Draganov, Roumen Kountchev
• A New Histogram-Based Descriptor for Images Retrieval from Databases / Kidiyo Kpalma, Cong Bai
• Combining Features Evaluation Approach in Content-Based Image Search for Medical Applications / Antoaneta A. Popova, Nikolay N. Neshov
• Semi-automatic Ultrasound Medical Image Recognition for Diseases Classification in Neurology / Jiří Blahuta, Tomáš Soukup, Petr Čermák
• Classification and Detection of Diabetic Retinopathy / Ahmad Taher Azar, Valentina E. Balas
• Principal Component Analysis Used in Estimation of Human's Immune System, Suffered from Allergic Rhinosinusopathy Complicated with Clamidiosis or without It / Lyudmila Pokidysheva, Irina Ignatova
• Computer-Aided Diagnosis of Laryngopathies in the LabVIEW Environment: Exemplary Implementation / Dominika Gurdak, Krzysztof Pancerz
• Analysis and Development of Techniques and Methods in Medical Practice in Cochlear Implant Systems / Svetlin Antonov, Snejana Pleshkova-Bekiarska
• On Confidentially Connected-Free Graphs / Mihai Talmaciu, Elena Nechita
• Route Search Algorithm in Timetable Graphs and Extension for Block Agents / Ion Cozac
• From Individual EHR Maintenance to Generalised Findings: Experiments for Application of NLP to Patient-Related Texts / Galia Angelova, Dimitar Tcharaktchiev
• A Terminology Indexing Based on Heuristics Using Linguistic Resources for Medical Textual Corpus / Ali Benafia, Ramdane Maamri, Zaidi Sahnoun
• Architecture for Medical Image Processing / Rumen Mironov, Roumen Kountchev
• A New Generation of Biomedical Equipment: FPGA / Marius M. Balas.

This volume is a result of the fruitful and vivid discussions during the MedDecSup'2012 International Workshop bringing together a relevant body of knowledge, and new developments in the increasingly important field of medical informatics. This carefully edited book presents new ideas aimed at the development of intelligent processing of various kinds of medical information and the perfection of the contemporary computer systems for medical decision support. The book presents advances of the medical information systems for intelligent archiving, processing, analysis and search-by-content which will improve the quality of the medical services for every patient and of the global healthcare system. The book combines in a synergistic way theoretical developments with the practicability of the approaches developed and presents the last developments and achievements in medical informatics to a broad range of readers: engineers, mathematicians, physicians, and PhD students.

• Introduction to Intelligent Signal Processing and Data Mining / Lyudmila Mihaylova, Petia Georgieva and Lakhmi C. Jain
• Monte Carlo-Based Bayesian Group Object Tracking and Causal Reasoning / Avishy Y. Carmi, Lyudmila Mihaylova, Amadou Gning, Pini Gurfil and Simon J. Godsill
• A Sequential Monte Carlo Method for Multi-target Tracking with the Intensity Filter / Marek Schikora, Wolfgang Koch, Roy Streit and Daniel Cremers
• Sequential Monte Carlo Methods for Localization in Wireless Networks / Lyudmila Mihaylova, Donka Angelova and Anna Zvikhachevskaya
• A Sequential Monte Carlo Approach for Brain Source Localization / Petia Georgieva, Lyudmila Mihaylova, Filipe Silva, Mariofanna Milanova and Nuno Figueiredo, et al.
• Computational Intelligence in Automotive Applications / Yifei Wang, Naim Dahnoun and Alin Achim
• Detecting Anomalies in Sensor Signals Using Database Technology / Gereon Schüller, Andreas Behrend and Wolfgang Koch
• Hierarchical Clustering for Large Data Sets / Mark J. Embrechts, Christopher J. Gatti, Jonathan Linton and Badrinath Roysam
• A Novel Framework for Object Recognition under Severe Occlusion / Stamatia Giannarou and Tania Stathaki
• Historical Consistent Neural Networks: New Perspectives on Market Modeling, Forecasting and Risk Analysis / Hans-Georg Zimmermann, Christoph Tietz and Ralph Grothmann
• Reinforcement Learning with Neural Networks: Tricks of the Trade / Christopher J. Gatti and Mark J. Embrechts
• Sliding Empirical Mode Decomposition-Brain Status Data Analysis and Modeling / A. Zeiler, R. Faltermeier, A.M. Tomé, I.R. Keck and C. Puntonet, et al.

The book presents some of the most efficient statistical and deterministic methods for information processing and applications in order to extract targeted information and find hidden patterns. The techniques presented range from Bayesian approaches and their variations such as sequential Monte Carlo methods, Markov Chain Monte Carlo filters, Rao Blackwellization, to the biologically inspired paradigm of Neural Networks and decomposition techniques such as Empirical Mode Decomposition, Independent Component Analysis and Singular Spectrum Analysis. The book is directed to the research students, professors, researchers and practitioners interested in exploring the advanced techniques in intelligent signal processing and data mining paradigms.

• Data Mining, Classification and Queries
• A Bayesian Criterion for Evaluating the Robustness of Classification Rules in Binary Data Sets / Dominique Gay, Marc Boullé
• Mining Sequential Patterns: A Context-Aware Approach / Julien Rabatel, Sandra Bringay, Pascal Poncelet
• Comparison of Proximity Measures: A Topological Approach / Djamel Abdelkader Zighed, Rafik Abdesselam, Ahmed Bounekkar
• Comparing Two Discriminant Probabilistic Interestingness Measures for Association Rules / Israël César Lerman, Sylvie Guillaume
• A New Way for Hierarchical and Topological Clustering / Hanane Azzag, Mustapha Lebbah
• Summarizing and Querying Logs of OLAP Queries / Julien Aligon, Patrick Marcel, Elsa Negre
• Ontology and Semantic
• A Complete Life-Cycle for the Semantic Enrichment of Folksonomies / Freddy Limpens, Fabien Gandon, Michel Buffa
• Ontology-Based Formal Specifications for User-Friendly Geospatial Data Discovery / Ammar Mechouche, Nathalie Abadie, Emeric Prouteau, Sébastien Mustière
• Methods and Tools for Automatic Construction of Ontologies from Textual Resources: A Framework for Comparison and Its Application / Toader Gherasim, Mounira Harzallah, Giuseppe Berio, Pascale Kuntz
• User Centered Cognitive Maps / Lionel Chauvin, David Genest, Aymeric Le Dorze, Stéphane Loiseau.

The recent and novel research contributions collected in this book are extended and reworked versions of a selection of the best papers that were originally presented in French at the EGC'2011 Conference held in Brest, France, on January 2011. EGC stands for "Extraction et Gestion des connaissances" in French, and means "Knowledge Discovery and Management" or KDM. KDM is concerned with the works in computer science at the interface between data and knowledge; such as Data Mining, Knowledge Discovery, Business Intelligence, Knowledge Engineering and Semantic Web. This book is intended to be read by all researchers interested in these fields, including PhD or MSc students, and researchers from public or private laboratories. It concerns both theoretical and practical aspects of KDM. This book has been structured in two parts. The first part, entitled "Data Mining, classification and queries", deals with rule and pattern mining, with topological approaches and with OLAP. The second part of the book, entitled "Ontology and Semantic", is related to knowledge-based and user-centered approaches in KDM.
(source: Nielsen Book Data)