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

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

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

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

• Introduction.- Problem Description.- Background.- Related Work.- The PLASTIC Algorithms.- Theoretical Analysis of PLASTIC.- Empirical Evaluation.- Discussion and Conclusion.
• (source: Nielsen Book Data)

This book is devoted to the encounter and interaction of agents such as robots with other agents and describes how they cooperate with their previously unknown teammates, forming an Ad Hoc team. It presents a new algorithm, PLASTIC, that allows agents to quickly adapt to new teammates by reusing knowledge learned from previous teammates. PLASTIC is instantiated in both a model-based approach, PLASTIC-Model and a policy-based approach, PLASTIC-Policy. In addition to reusing knowledge learned from previous teammates, PLASTIC also allows users to provide expert-knowledge and can use transfer learning (such as the new Two Stage Transfer algorithm) to quickly create models of new teammates when it has some information about its new teammates. The effectiveness of the algorithm is demonstrated on three domains, ranging from multi-armed bandits to simulated robot soccer games.
(source: Nielsen Book Data)

• Pattern Recognition and Machine Learning
• Spatiotemporal Stacked Sequential Learning for Pedestrian Detection
• Social Signaling Descriptor for Group Behaviour Analysis
• A New Smoothing Method for Lexicon-Based Handwritten Text Keyword Spotting
• Empirical Evaluation of Different Feature Representations for Social Circles Detection
• Source-Target-Source Classification Using Stacked Denoising Autoencoders
• On the Impact of Distance Metrics in Instance-Based Learning Algorithms
• Multi-class Boosting for Imbalanced Data
• Computer Vision
• Object Discovery Using CNN Features in Egocentric Videos
• Prototype Generation on Structural Data Using Dissimilarity Space Representation: A Case of Study
• Estimation and Tracking of Partial Planar Templates to Improve VSLAM
• Human Centered Scene Understanding Based on 3D Long-Term Tracking Data
• Fast Head Pose Estimation for Human-Computer Interaction
• Structured Light System Calibration for Perception in Underwater Tanks
• Dense 3D SLAM in Dynamic Scenes Using Kinect
• Scene Recognition Invariant to Symmetrical Reflections and Illumination Conditions in Robotics
• System for Medical Mask Detection in the Operating Room Through Facial Attributes
• Image and Signal Processing
• New Method for Obtaining Optimal Polygonal Approximations
• Noise Decomposition Using Polynomial Approximation
• Color Correction for Image Stitching by Monotone Cubic Spline Interpolation
• Structured Output Prediction with Hierarchical Loss Functions for Seafloor Imagery Taxonomic Categorization
• Escaping Path Approach with Extended Neighborhood for Speckle Noise Reduction
• Adaptive Line Matching for Low-Textured Images
• Unsupervised Approximation of Digital Planar Curves
• On the Modification of Binarization Algorithms to Retain Grayscale Information for Handwritten Text Recognition
• Applications
• Improving the Minimum Description Length Inference of Phrase-Based Translation Models
• A Kinect-Based System to Assess Lymphedema Impairments in Breast Cancer Patients
• Arabic Writer Identification Using Local Binary Patterns (LBP) of Handwritten Fragments
• A Fuzzy C-Means Algorithm for Fingerprint Segmentation
• Word-Graph Based Applications for Handwriting Documents: Impact of Word-Graph Size on Their Performances
• Temporal Segmentation of Digital Colposcopies
• Goal-Driven Phenotyping Through Spectral Imaging for Grape Aromatic Ripeness Assessment
• Medical Image
• Robust 3D Active Shape Model for the Segmentation of the Left Ventricle in MRI
• Kernel-Based Feature Relevance Analysis for ECG Beat Classification
• Spatial-Dependent Similarity Metric Supporting Multi-atlas MRI Segmentation
• Color Detection in Dermoscopy Images Based on Scarce Annotations
• Pattern Recognition and Machine Learning
• Spectral Clustering Using Friendship Path Similarity
• R-Clustering for Egocentric Video Segmentation
• Applying Basic Features from Sentiment Analysis for Automatic Irony Detection
• Exploiting the Bin-Class Histograms for Feature Selection on Discrete Data
• Time-Series Prediction Based on Kernel Adaptive Filtering with Cyclostationary Codebooks
• Latent Topic Encoding for Content-Based Retrieval
• Dissimilarity-Based Learning from Imbalanced Data with Small Disjuncts and Noise
• Binary and Multi-class Parkinsonian Disorders Classification Using Support Vector Machines
• Peripheral Nerve Segmentation Using Speckle Removal and Bayesian Shape Models
• Measuring Scene Detection Performance
• Threshold of Graph-Based Volumetric Segmentation
• Brain Neural Data Analysis with Feature Space Defined by Descriptive Statistics
• Extremely Overlapping Vehicle Counting
• Sentence Clustering Using Continuous Vector Space Representation
• Online Learning of Stochastic Bi-automaton to Model Dialogues
• Single-Channel Separation Between Stationary and Non-stationary Signals Using Relevant Information
• Computer Vision
• A New Trajectory Based Motion Segmentation Benchmark Dataset (UdG-MS15)
• Escritoire: A Multi-touch Desk with e-Pen Input for Capture, Management and Multimodal Interactive Transcription of Handwritten Documents
• Person Enrollment by Face-Gait Fusion
• Homographic Class Template for Logo Localization and Recognition
• Multimodal Object Recognition Using Random Clustering Trees
• Videogrammetry System for Wind Turbine Vibration Monitoring
• Canonical Views for Scene Recognition in Mobile Robotics
• Crater Detection in Multi-ring Basins of Mercury
• Iterative Versus Voting Method to Reach Consensus Given Multiple Correspondences of Two Sets
• Extracting Categories by Hierarchical Clustering Using Global Relational Features
• A Calibration Algorithm for Multi-camera Visual Surveillance Systems Based on Single-View Metrology
• 3D-Guided Multiscale Sliding Window for Pedestrian Detection
• A Feature-Based Gaze Estimation Algorithm for Natural Light Scenarios
• Image and Signal Processing
• Fast Simple Linear Iterative Clustering by Early Candidate Cluster Elimination
• Pectoral Muscle Segmentation in Mammograms Based on Cartoon-Texture Decomposition
• PPG Beat Reconstruction Based on Shape Models and Probabilistic Templates for Signals Acquired with Conventional Smartphones
• Peripheral Nerves Segmentation in Ultrasound Images Using Non-linear Wavelets and Gaussian Processes
• Improving Diffusion Tensor Estimation Using Adaptive and Optimized Filtering Based on Local Similarity
• Dimension Reduction of Hyperspectral Image with Rare Event Preserving
• Applications
• Clustering of Strokes from Pen-Based Music Notation: An Experimental Study
• Image Analysis-Based Automatic Detection of Transmission Towers Using Aerial Imagery
• A Sliding Window Framework for Word Spotting Based on Word Attributes
• Combining Statistical and Semantic Knowledge for Sarcasm Detection in Online Dialogues
• Estimating Fuel Consumption from GPS Data
• A Bag-of-phonemes Model for Homeplace Classification of Mandarin Speakers
• A Gaussian Process Emulator for Estimating the Volume of Tissue Activated During Deep Brain Stimulation
• Genetic Seam Carving: A Genetic Algorithm Approach for Content-Aware Image Retargeting
• Analysis of Expressiveness of Portuguese Sign Language Speakers
• Automatic Eye Localization; Multi-block LBP vs. Pyramidal LBP Three-Levels Image Decomposition for Eye Visual Appearance Description
• Clinical Evaluation of an Automatic Method for Segmentation and Characterization of the Thoracic Aorta with and Without Aneurysm Patients
• Combined MPEG7 Color Descriptors for Image Classification: Bypassing the Training Phase
• A Multi-platform Graphical Software for Determining Reproductive Parameters in Fishes Using Histological Image Analysis.

This book constitutes the proceedings of the 6th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2015, held in Warsaw, Poland, in June/July 2015. The total of 53 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 90 submissions. They were organized in topical sections named: foundations of machine learning; image processing; image retrieval; image tracking; pattern recognition; data mining techniques for large scale data; fuzzy computing; rough sets; bioinformatics; and applications of artificial intelligence.

• Vocabularies, Schemas, Ontologies
• Requirements for and Evaluation of User Support for Large-Scale Ontology Alignment
• RODI: A Benchmark for Automatic Mapping Generation in Relational-to-Ontology Data Integration
• VocBench: a Web Application for Collaborative Development of Multilingual Thesauri
• Leveraging and Balancing Heterogeneous Sources of Evidence in Ontology Learning
• Reasoning
• A Context-Based Semantics for SPARQL Property Paths over the Web
• Distributed and Scalable OWL EL Reasoning
• Large scale rule-based Reasoning using a Laptop
• RDF Digest: Efficient Summarization of RDF/S KBs
• Linked Data
• A Comparison of Data Structures to Manage URIs on the Web of Data
• Heuristics for Fixing Common Errors in Deployed schema.org Microdata
• Semantic Web and Web Science
• LOD-based Disambiguation of Named Entities in @tweets through Context enrichment
• Knowledge Enabled Approach to Predict the Location of Twitter Users
• Semantic Data Management, Big data, Scalability
• A Compact In-Memory Dictionary for RDF data
• Quality Assessment of Linked Datasets using Probabilistic Approximations
• Cooperative Techniques for SPARQL Query Relaxation in RDF Databases
• HDT-MR: A Scalable Solution for RDF Compression with HDT and MapReduce
• Processing Aggregate Queries in a Federation of SPARQL Endpoints
• A survey of HTTP caching implementations on the open Semantic Web
• Query Execution Optimization for Clients of Triple Pattern Fragments
• Natural Language Processing and Information Retrieval LIME: the Metadata Module for OntoLex
• Learning a Cross-Lingual Semantic Representation of Relations Expressed in Text
• HAWK Hybrid Question Answering using Linked Data
• Machine Learning
• Automating RDF Dataset Transformation and Enrichment
• Semi-supervised Instance Matching Using Boosted Classifiers
• Assigning Semantic Labels to Data Sources
• Inductive Classification through Evidence-based Models and their Ensembles
• Mobile Web, Internet of Things and Semantic Streams
• Standardized and Efficient RDF Encoding for Constrained Embedded Networks
• Services, Web APIs, and the Web of Things SPSC: Efficient Composition of Semantic Services in Unstructured P2P Networks
• Data as a Service: The Semantic Web Redeployed
• Cognition and Semantic Web
• On Coherent Indented Tree Visualization of RDF Graphs
• Gagg: A Graph Aggregation Operator
• FrameBase: Representing N-ary Relations using Semantic Frames
• Human Computation and Crowdsourcing
• Towards hybrid NER: a study of content and crowdsourcing-related performance factors
• Ranking Entities in the Age of Two Webs, An Application to Semantic Snippets
• In-Use Industrial Track
• Troubleshooting and Optimizing Named Entity Resolution Systems in the Industry
• Using Ontologies For Modeling Virtual Reality Scenarios
• Supporting Open Collaboration in Science through Explicit and Linked Semantic Description of Processes
• Crowdmapping Digital Social Innovation with Linked data
• Desperately searching for travel offers? Formulate better queries with some help from Linked Data
• Towards the Linked Russian Heritage Cloud: Data enrichment and Publishing
• From Symptoms to Diseases
• Creating the Missing Link
• Using semantic web technologies for enterprise architecture analysis
• PADTUN
• Using Semantic Technologies in Tunnel Diagnosis and Maintenance Domain.

This book constitutes the refereed proceedings of the 12th Extended Semantic Web Conference, ESWC 2014, held in Anissaras, Portoroz, Slovenia, in May/June 2015. The 43 revised full papers presented together with three invited talks were carefully reviewed and selected from 164 submissions. This program was completed by a demonstration and poster session, in which researchers had the chance to present their latest results and advances in the form of live demos. In addition, the PhD Symposium program included 12 contributions, selected out of 16 submissions. The core tracks of the research conference were complemented with new tracks focusing on linking machine and human computation at web scale (cognition and Semantic Web, Human Computation and Crowdsourcing) beside the following subjects Vocabularies, Schemas, Ontologies, Reasoning, Linked Data, Semantic Web and Web Science, Semantic Data Management, Big data, Scalability, Natural Language Processing and Information Retrieval, Machine Learning, Mobile Web, Internet of Things and Semantic Streams, Services, Web APIs, and the Web of Things, Cognition and Semantic Web, Human Computation and Crowdsourcing, and In-Use Industrial Track as well.

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

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

• Introduction.- Background and Literature Survey.- VLSI Architecture for Fast Three Step Search Algorithm.- Parallel Architecture for Successive Elimination Block Matching Algorithm.- Fast One-Bit Transformation Architectures.- Efficient Pixel Truncation Algorithm and Architecture.- Introduction to Scalable Image and Video Coding.- Forward Plans.- 8 Forward Plans.- A Matlab Programs.- B Verilog Modules.
• (source: Nielsen Book Data)

The need of video compression in the modern age of visual communication cannot be over-emphasized. This monograph will provide useful information to the postgraduate students and researchers who wish to work in the domain of VLSI design for video processing applications. In this book, one can find an in-depth discussion of several motion estimation algorithms and their VLSI implementation as conceived and developed by the authors. It records an account of research done involving fast three step search, successive elimination, one-bit transformation and its effective combination with diamond search and dynamic pixel truncation techniques. Two appendices provide a number of instances of proof of concept through Matlab and Verilog program segments. In this aspect, the book can be considered as first of its kind. The architectures have been developed with an eye to their applicability in everyday low-power handheld appliances including video camcorders and smartphones.
(source: Nielsen Book Data)

• Features, Learning, and Classifiers. Toward Computer-Aided Interpretation of Situations / Juliusz L. Kulikowski
• Classification of Multi-dimensional Distributions Using Order Statistics Criteria / A. Thomas, B. John Oommen
• Knowledge Extraction from Graph-Based Structures in Conceptual Design / Grażyna Ślusarczyk
• Estimation of the Relations of: Equivalence, Tolerance and Preference on the Basis of Pairwise Comparisons / Leszek Klukowski
• Generalized Constraint Design of Linear-Phase FIR Digital Filters / Norbert Henzel, Jacek M. Leski
• Reduced Kernel Extreme Learning Machine / Wanyu Deng, Qinghua Zheng, Kai Zhang
• Using Positional Information in Modeling Inflorescence Discs / Malgorzata Prolejko
• A New Method for Random Initialization of the EM Algorithm for Multivariate Gaussian Mixture Learning / Wojciech Kwedlo
• Heuristic Optimization Algorithms for a Tree-Based Image Dissimilarity Measure / Bartłomiej Zieliński, Marcin Iwanowski.

• Model of Syntactic Recognition of Distorted String Patterns with the Help of GDPLL(k)-Based Automata / Janusz Jurek, Tomasz Peszek
• Decision Rules in Simple Decision Systems over Ontological Graphs / Krzysztof Pancerz
• Nonlinear Extension of the IRLS Classifier Using Clustering with Pairs of Prototypes / Michal Jezewski, Jacek M. Leski
• Separable Linearization of Learning Sets by Ranked Layer of Radial Binary Classifiers / Leon Bobrowski, Magdalena Topczewska
• Hidden Markov Models For Two-Dimensional Data / Janusz Bobulski
• Methods of Learning Classifier Competence Applied to the Dynamic Ensemble Selection / Maciej Krysmann, Marek Kurzynski
• The Method of Improving the Structure of the Decision Tree Given by the Experts / Robert Burduk
• Biometrics. Face Detection and Recognition under Heterogeneous Database Based on Fusion of Catadioptric and PTZ Vision Sensors / Aditya Raj [and others]
• Eigenfaces, Fisherfaces, Laplacianfaces, Marginfaces -- How to Face the Face Verification Task / Maciej Smiatacz.

• A Content Based Feature Combination Method for Face Recognition / Madeena Sultana, Marina Gavrilova
• Face Recognition Based on Sequence of Images / Jacek Komorowski, Przemyslaw Rokita
• Statistical Analysis in Signature Recognition System Based on Levenshtein Distance / Malgorzata Palys, Rafal Doroz, Piotr Porwik
• A Computational Assessment of a Blood Vessel's Roughness / Tomasz Wesolowski, Krzysztof Wrobel
• Performance Benchmarking of Different Binarization Techniques for Fingerprint-Based Biometric Authentication / Soharab Hossain Shaikh, Khalid Saeed, Nabendu Chaki
• Biometric Features Selection with k-Nearest Neighbours Technique and Hotelling Adaptation Method / Piotr Porwik, Rafal Doroz
• Data Stream Classification and Big Data Analytics. Predictive Regional Trees to Supplement Geo-Physical Random Fields / Annalisa Appice, Sonja Pravilovic, Donato Malerba
• Extending Bagging for Imbalanced Data / Jerzy Błaszczyński, Jerzy Stefanowski, Łukasz Idkowiak.

• Rule Chains for Visualizing Evolving Fuzzy Rule-Based Systems / Sascha Henzgen, Marc Strickert, Eyke Hüllermeier
• Recovery Analysis for Adaptive Learning from Non-stationary Data Streams / Ammar Shaker, Eyke Hüllermeier
• Analysis of Roles and Groups in Blogosphere / Bogdan Gliwa, Anna Zygmunt, Jarosław Koźlak
• Knowledge Generalization from Long Sequence of Execution Scenarios / Radosław Z. Ziembiński
• Incremental Learning and Forgetting in One-Class Classifiers for Data Streams / Bartosz Krawczyk, Michał Woźniak
• Comparable Study of Statistical Tests for Virtual Concept Drift Detection / Piotr Sobolewski, Michał Woźniak
• Image Processing and Computer Vision. An Experimental Comparison of Fourier-Based Shape Descriptors in the General Shape Analysis Problem / Katarzyna Gościewska, Dariusz Frejlichowski
• Extraction of the Foreground Regions by Means of the Adaptive Background Modelling Based on Various Colour Components for a Visual Surveillance System / Dariusz Frejlichowski [and others].

• Repeatability Measurements for 2D Interest Point Detectors on 3D Models / Simon R. Lang, Martin H. Luerssen, David M.W. Powers
• Extended Investigations on Skeleton Graph Matching for Object Recognition / Jens Hedrich [and others]
• Low-Level Image Features for Stamps Detection and Classification / Paweł Forczmański, Andrzej Markiewicz
• Stochastic Approximation to Reconstruction of Vector-Valued Images / Dariusz Borkowski
• Image Segmentation with Use of Cross-Entropy Clustering / Marek Śmieja, Jacek Tabor
• Detection of Disk-Like Particles in Electron Microscopy Images / P. Spurek, J. Tabor, E. Zając
• A GPU Accelerated Local Polynomial Approximation Algorithm for Efficient Denoising of MR Images / Artur Klepaczko
• Altair: Automatic Image Analyzer to Assess Retinal Vessel Caliber / Gabino Verde [and others]
• Real-Time Wrist Localization in Hand Silhouettes / Tomasz Grzejszczak, Jakub Nalepa, Michal Kawulok
• An s-layered Grade Decomposition of Images / Maria Grzegorek.

• System-Level Hardware Implementation of Simplified Low-Level Color Image Descriptor / Paweł Forczmański, Piotr Dziurzański
• Reconstruction of Head Surface Model from Single Scan / Krzysztof Skabek, Dawid Łapczynski
• The Effectiveness of Matching Methods for Rectified Images / Pawel Popielski, Zygmunt Wrobel, Robert Koprowski
• The Print-Scan Problem in Printed Steganography of Face Images / Włodzimierz Kasprzak, Maciej Stefańczyk, Jan Popiołkiewicz
• Phototool Geometry Verification / Jarosław Zdrojewski, Adam Marchewka
• Structure from Motion in Three -- Dimensional Modeling of Human Head / Anna Wójcicka, Zygmunt Wróbel
• A Short Overview of Feature Extractors for Knuckle Biometrics / Michał Choraś
• Three-Stage Method of Text Region Extraction from Diagram Raster Images / Jerzy Sas, Andrzej Zolnierek
• Medical Applications. Time Series of Fuzzy Sets in Classification of Electrocardiographic Signals / Jacek M. Leski, Norbert Henzel.

• Interpolation Procedure in Filtered Backprojection Algorithm for the Limited-Angle Tomography / Aleksander Denisiuk
• Classification of Uterine Electrical Activity Patterns for Early Detection of Preterm Birth / Janusz Jezewski [and others]
• Diagnosis of Bipolar Disorder Based on Principal Component Analysis and SVM / M. Termenon [and others]
• Genetic Algorithms in EEG Feature Selection for the Classification of Movements of the Left and Right Hand / Izabela Rejer
• On the Use of Programmed Automata for a Verification of ECG Diagnoses / Mariusz Flasiński, Piotr Flasiński, Ewa Konduracka
• Blood Flow Modeling in a Synthetic Cylindrical Vessel for Validating Methods of Vessel Segmentation in MRA Images / Grzegorz Dwojakowski, Artur Klepaczko, Andrzej Materka
• Swarm Optimization and Multi-level Thresholding of Cytological Images for Breast Cancer Diagnosis / Marek Kowal [and others]
• Detecting Overlapped Nuclei Regions in the Feulgen-Stained Cytological Smears / Bogusław D. Piętka, Annamonika Dulewicz.

• Density Invariant Detection of Osteoporosis Using Growing Neural Gas / Igor T. Podolak, Stanisław K. Jastrzębski
• Cost Sensitive Hierarchical Classifiers for Non-invasive Recognition of Liver Fibrosis Stage / Bartosz Krawczyk [and others]
• Miscellaneous Applications. A Blinking Measurement Method for Driver Drowsiness Detection / Belhassen Akrout, Walid Mahdi
• Description of Human Activity Using Behavioral Primitives / Piotr Augustyniak
• How to Become Famous? Motives in Scientific Social Networks / Adam Matusiak, Mikołaj Morzy
• AdaBoost for Parking Lot Occupation Detection / Radovan Fusek [and others]
• Blink Detection Based on the Weighted Gradient Descriptor / Krystian Radlak, Bogdan Smolka
• Touchless Input Interface for Disabled / Adam Nowosielski, Łukasz Chodyła
• Architecture of the Semantically Enhanced Intellectual Property Protection System / Dariusz Ceglarek
• Validation of Clustering Techniques for User Group Modeling / Danuta Zakrzewska.

• Parking Lot Occupancy Detection Using Computational Fluid Dynamics / Tomas Fabian
• Human Fall Detection Using Kinect Sensor / Michal Kepski, Bogdan Kwolek
• Evaluation of Various Techniques for SQL Injection Attack Detection / Michał Choraś, Rafał Kozik
• Task Allocation in Distributed Mesh-Connected Machine Learning System: Simplified Busy List Algorithm with Q-Learning Based Queuing / Agnieszka Majkowska, Dawid Zydek, Leszek Koszałka
• Power Saving Algorithms for Mobile Networks Using Classifiers Ensemble / Rafal Lysiak, Marek Kurzynski
• Hardware Implementation of Fourier Transform for Real Time EMG Signals Recognition / Andrzej R. Wolczowski [and others]
• Data Preprocessing with GPU for DBSCAN Algorithm / Piotr Cal, Michał Woźniak
• Pattern Recognition and Image Processing in Robotics. Structured Light Techniques for 3D Surface Reconstruction in Robotic Tasks / M. Rodrigues [and others]
• Multi-modal People Detection from Aerial Video / Helen Flynn, Stephen Cameron.

• The Classification of the Terrain by a Hexapod Robot / Adam Schmidt, Krzysztof Walas
• Robust Registration of Kinect Range Data for Sensor Motion Estimation / Michał Nowicki, Piotr Skrzypczyński
• Utilization of Depth and Color Information in Mobile Robotics / Maciej Stefańczyk, Konrad Bojar, Włodzimierz Kasprzak
• Speech and Word Recognition. Texture-Based Text Detection in Digital Images with Wavelet Features and Support Vector Machines / Marcin Grzegorzek [and others]
• Automatic Disordered Syllables Repetition Recognition in Continuous Speech Using CWT and Correlation / Ireneusz Codello [and others]
• Evaluation of the Document Classification Approaches / Michal Hrala, Pavel Král
• The Prolongation-Type Speech Non-fluency Detection Based on the Linear Prediction Coefficients and the Neural Networks / Adam Kobus [and others].

This book is a study of computer recognition systems. It contains articles contributed by experts of pattern recognition, and reports on current research with respect to both methodology and applications. Topics include: biometrics; data stream classification and big data analytics; features, learning, and classifiers; image processing and computer vision; medical applications; pattern recognition and image processing in robotics; speech and word recognition.

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

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

• Multilevel Analysis of Attributed Graphs for Explicit Graph Embedding in Vector Spaces / Muhammad Muzzamil Luqman, Jean-Yves Ramel and Josep Lladós
• Feature Grouping and Selection Over an Undirected Graph / Sen Yang, Lei Yuan, Ying-Cheng Lai, Xiaotong Shen and Peter Wonka, et al.
• Median Graph Computation by Means of Graph Embedding into Vector Spaces / Miquel Ferrer, Itziar Bardají, Ernest Valveny, Dimosthenis Karatzas and Horst Bunke
• Patch Alignment for Graph Embedding / Yong Luo, Dacheng Tao and Chao Xu
• Improving Classifications Through Graph Embeddings / Anirban Chatterjee, Sanjukta Bhowmick and Padma Raghavan
• Learning with ℓ1-Graph for High Dimensional Data Analysis / Jianchao Yang, Bin Cheng, Shuicheng Yan, Yun Fu and Thomas Huang
• Graph-Embedding Discriminant Analysis on Riemannian Manifolds for Visual Recognition / Sareh Shirazi, Azadeh Alavi, Mehrtash T. Harandi and Brian C. Lovell
• A Flexible and Effective Linearization Method for Subspace Learning / Feiping Nie, Dong Xu, Ivor W. Tsang and Changshui Zhang
• A Multi-graph Spectral Framework for Mining Multi-source Anomalies / Jing Gao, Nan Du, Wei Fan, Deepak Turaga and Srinivasan Parthasarathy, et al.
• Graph Embedding for Speaker Recognition / Z.N. Karam and W.M. Campbell.₉

Graph Embedding for Pattern Analysis covers theory methods, computation, and applications widely used in statistics, machine learning, image processing, and computer vision. This book presents the latest advances in graph embedding theories, such as nonlinear manifold graph, linearization method, graph based subspace analysis, L1 graph, hypergraph, undirected graph, and graph in vector spaces. Real-world applications of these theories are spanned broadly in dimensionality reduction, subspace learning, manifold learning, clustering, classification, and feature selection. A selective group of experts contribute to different chapters of this book which provides a comprehensive perspective of this field.

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

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