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• Frontmatter
• Preface
• Contents
• List of Contributors
• 1. Feature selection in biomedical signal classification process and current software implementations / Jovic, Alan
• 2. An overview of skin lesion segmentation, features engineering, and classification / Sabri, My Abdelouahed / Filali, Youssef / Ennouni, Assia / Yahyaouy, Ali / Aarab, Abdellah
• 3. Brain tumor image segmentation and classification using SVM, CLAHE, and ARKFCM / Ishita, Banerjee / Madhumathy, P. / Kavitha, N.
• 4. Coronary Heart Disease prediction using genetic algorithm based decision tree / Sivaranjani, Reddi / Naresh, Vankamamidi S. / Murthy, Nistala V.E.S.
• 5. Intelligent approach for retinal disease identification / Rajyaguru, Vipul C. / Vithalani, Chandresh H. / Thanki, Rohit M.
• 6. Speech separation for interactive voice systems / Wiem, Belhedi / Anouar, Ben Messaoud Mohamed / Aïcha, Bouzid
• 7. Machine vision for human-machine interaction using hand gesture recognition / Verma, Varnita / Rajput, Anshuman / Chauhan, Piyush / Rathore, Harshit / Goyal, Piyush / Gupta, Mukul Kumar
• Index

Intelligent prediction and decision support systems are based on signal processing, computer vision (CV), machine learning (ML), software engineering (SE), knowledge based systems (KBS), data mining, artificial intelligence (AI) and include several systems developed from the study of expert systems (ES), genetic algorithms (GA), artificial neural networks (ANN) and fuzzy-logic systems The use of automatic decision support systems in design and manufacturing industry, healthcare and commercial software development systems has the following benifits: Cost savings in companies, due to employment of expert system technology. Fast decision making, completion of projects in time and development of new products. Improvement in decision making capability and quality. Usage of Knowledge database and Preservation of expertise of individuals Eases complex decision problems. Ex: Diagnosis in Healthcare To address the issues and challenges related to development, implementation and application of automatic and intelligent prediction and decision support systems in domains such as manufacturing, healthcare and software product design, development and optimization, this book aims to collect and publish wide ranges of quality articles such as original research contributions, methodological reviews, survey papers, case studies and/or reports covering intelligent systems, expert prediction systems, evaluation models, decision support systems and Computer Aided Diagnosis (CAD).
(source: Nielsen Book Data)

• Intro
• Preface
• Organization
• Contents
• Mammographic Mass Segmentation Using Fuzzy C-means and Decision Trees
• 1 Introduction
• 2 Segmentation of Masses in Mammograms Using Fuzzy C-means and Decision Trees
• 2.1 Fuzzy C-means Based on Gray Levels Histogram
• 2.2 Reduction of False Positive ROIs
• 2.3 Feature Extraction
• 2.4 Binary Decision Tree
• 3 Experimentation
• 3.1 Results and Discussion
• 4 Conclusions
• References
• Refining the Pose: Training and Use of Deep Recurrent Autoencoders for Improving Human Pose Estimation
• 1 Introduction

• 2 Deep Architecture for 3D Human Pose Refinement
• 2.1 Denoising Recurrent Autoencoder
• 2.2 Convolutional Network for Pose Prediction
• 2.3 Pose Refinement Training
• 2.4 Cost Function
• 3 Experiments
• 3.1 Evaluation on HumanEva-I
• 3.2 Evaluation on Human 3.6 Million
• 3.3 Ablation Experiments
• 3.4 Conclusions
• References
• How Can Deep Neural Networks Be Generated Efficiently for Devices with Limited Resources?
• 1 Introduction
• 2 Background
• 3 Parameter Pruning
• 4 Quantization
• 5 Low-Rank Factorization
• 6 Compact Network Design
• 7 Neural Model Deployment

• 7.1 Compact Network Design
• 7.2 Training and Pruning
• 7.3 Quantize Model
• 7.4 Inference Optimization
• 8 Conclusion
• References
• Controlling a Smartphone with Brain-Computer Interfaces: A Preliminary Study
• 1 Introduction
• 2 Subjects and Methods
• 2.1 Acquisition
• 2.2 Processing
• 2.3 Application
• 2.4 Evaluation Procedure
• 3 Results
• 4 Discussion
• 5 Conclusion
• References
• Capturing Industrial Machinery into Virtual Reality
• 1 Introduction
• 2 Related Work
• 3 System Design
• 3.1 Initialisation
• 3.2 Capturing Images
• 3.3 Calibration
• 3.4 Visualisation

• 4 Results
• 5 Conclusion
• References
• Leishmaniasis Parasite Segmentation and Classification Using Deep Learning
• 1 Introduction
• 2 Data
• 3 Method
• 4 Results
• 5 Conclusions
• References
• Robust Pedestrian Detection for Semi-automatic Construction of a Crowded Person Re-Identification Dataset
• 1 Introduction
• 2 The JNU Dataset
• 3 Automatic Pedestrian Detection
• 4 Automatic Data Association
• 5 Evaluation
• 6 Conclusion
• References
• Shape and Appearance Based Sequenced Convnets to Detect Real-Time Face Attributes on Mobile Devices
• 1 Introduction
• 2 Related Work

• 3 Datasets and Data Preparation
• 3.1 FER-2013 and FER+ Datasets
• 3.2 Data Preprocessing
• 4 Proposed CNN Architecture
• 4.1 Sequenced CNN Models
• 4.2 Face Heatmap Image Construction
• 4.3 CNN Models
• 4.4 Learning with a Shape Heatmap Image
• 5 Results and Applications
• 5.1 Effects of Data Preparation and Alignment
• 5.2 Combining Face Shape and Appearance with VGG
• 5.3 Combining Face Shape and Appearance with Mobilenet
• 5.4 Implementation
• 6 Conclusions
• References
• Image Colorization Using Generative Adversarial Networks
• 1 Introduction

This book constitutes the refereed proceedings of the 10th International Conference on Articulated Motion and Deformable Objects, AMDO 2018, held in Palma de Mallorca, Spain, in July 2018. The 12 papers presented were carefully reviewed and selected from 26 submissions. The papers address the following topics: advanced computer graphics and immersive videogames; human modeling and animation; human motion analysis and tracking; 3D human reconstruction and recognition; multimodal user interaction and applications; ubiquitous and social computing; design tools; input technology; programming user interfaces; 3D medical deformable models and visualization; deep learning methods for computer vision and graphics; and multibiometric.
(source: Nielsen Book Data)

• Queueing Models with Retrials.- Queueing Models with Variants of Service.- Queueing Models for Cloud Computing.- Queueing Models for Wireless Communication.- Optimization in Queueing Models.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 13th International Conference on Queueing Theory and Network Applications, QTNA 2018, held in Tsukuba, Japan in July 2018.The 8 full papers together with 10 short papers included in this volume were carefully reviewed and selected from 57 initial submissions. All the papers to be presented disseminate the latest results covering up-to-date research fields such as performance modeling and analysis of telecommunication systems, retrial and vacation queueing models, optimization of queueing systems, modeling of social systems, application of machine learning in queueing models.
(source: Nielsen Book Data)

• Quality Aspects in Machine Learning, AI and Data Analytics.- Evidence-Based Software Quality Engineering.- Human and Artificial Intelligences for Software Evolution.- Process Modeling, Improvement and Assessment.- Software Quality Education and Training.- Quality Aspects in Quantum Computing.- Safety, Security and Privacy.- ICT Verification and Validation.- RE, MDD and Agile.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 13th International Conference on the Quality of Information and Communications Technology, QUATIC 2020, held in Faro, Portugal*, in September 2020. The 27 full papers and 12 short papers were carefully reviewed and selected from 81 submissions. The papers are organized in topical sections: quality aspects in machine learning, AI and data analytics; evidence-based software quality engineering; human and artificial intelligences for software evolution; process modeling, improvement and assessment; software quality education and training; quality aspects in quantum computing; safety, security and privacy; ICT verification and validation; RE, MDD and agile. *The conference was held virtually due to the COVID-19 pandemic.
(source: Nielsen Book Data)

• The Two-point Fano and Ideal Binary Clutters.- On Scheduling Coflows.- Integrality Gaps of Integer Knapsack Problems.- An Improved Integrality Gap for the Calinescu-Karloff-Rabani Relaxation for Multiway Cut.- Approximation of Corner Polyhedra with Families of Intersection Cuts.- The Structure of the Infinite Models in Integer Programming.- Mixed-integer Linear Representability, Disjunctions, and Variable Elimination.- Deterministic Fully Dynamic Approximate Vertex Cover and Fractional Matching in O(1) Amortized Update Time.- Cutting Planes from Wide Split Disjunctions.- The Salesman's Improved Tours for Fundamental Classes.- The Heterogeneous Capacitated k-Center Problem.- Local Guarantees in Graph Cuts and Clustering.- Verifying Integer Programming Results.- Long term Behavior of Dynamic Equilibria in uid Queuing Networks.- A 4/5 - Approximation Algorithm for the Maximum Traveling Salesman Problem.- Minimizing Multimodular Functions and Allocating Capacity in Bike-sharing Systems.- Compact, Provably-Good LPs for Orienteering and Regret-Bounded Vehicle Routing.- Discrete Newton's Algorithm for Parametric Submodular Function Minimization.- Stochastic Online Scheduling on Unrelated Machines.- Online Matroid Intersection: Beating Half for Random Arrival.- Number Balancing is as Hard as Minkowski's Theorem and Shortest Vector.- An Improved Deterministic Rescaling for Linear Programming Algorithms.- Min-Max Theorems for Packing and Covering Odd (u
• v)-trails.- Breaking 1 - 1/e Barrier for Non-preemptive Throughput Maximization.- A Quasi-Polynomial Approximation for the Restricted Assignment Problem.- Adaptive Submodular Ranking.- On the Notions of Facets, Weak Facets, and Extreme Functions of the Gomory-Johnson Infinite Group Problem.- Minimum Birkhoff-von Neumann Decomposition.- Maximum Matching in the Online Batch-Arrival Model.- Budget Feasible Mechanisms on Matroids.- Deterministic Discrepancy Minimization Via the Multiplicative Weight Update Method.- Mixed-integer Convex Representability.- High Degree Sum of Squares Proofs, Bienstock-Zuckerberg Hierarchy and Chvatal-Gomory Cuts.- Enumeration of Integer Points in Projections of Unbounded Polyhedral.- Excluded t-factors in Bipartite Graphs: A Unified Framework for Nonbipartite Matchings and Restricted 2-matchings.- Equilibrium Computation in Atomic Splittable Singleton Congestion Games. .
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 19th International Conference on Integer Programming and Combinatorial Optimization, IPCO 2017, held in Waterloo, IN, Canada, in June 2017. The 36 full papers presented were carefully reviewed and selected from 125 submissions. The conference is a forum for researchers and practitioners working on various aspects of integer programming and combinatorial optimization. The aim is to present recent developments in theory, computation, and applications in these areas. The scope of IPCO is viewed in a broad sense, to include algorithmic and structural results in integer programming and combinatorial optimization as well as revealing computational studies and novel applications of discrete optimization to practical problems.
(source: Nielsen Book Data)

• Cover; Title page; Preface; Contents;
• 1. Introduction to Neural Networks for Instrumentation, Measurement, and Industrial Applications;
• 2. The Fundamentals of Measurement Techniques;
• 3. Neural Networks in Intelligent Sensors and Measurement Systems for Industrial Applications;
• 4. Neural Networks in System Identification;
• 5. Neural Techniques in Control;
• 6. Neural Networks for Signal Processing in Measurement Analysis and Industrial Applications: the Case of Chaotic Signal Processing.

This work aims to disseminate theoretical and practical knowledge about neural networks in measurement, instrumentation and the related industrial applications. It also creates a consciousness about the effectiveness of these techniques as well as the measurement problems in industrial environments.

• Big and Smart Data
• A Parallel Approach for Decision Trees Learning from Big Data Streams
• Industry 4.0
• Potentials for Creating Smart Products: Empirical Research Results
• Evaluating New Approaches of Big Data Analytics Frameworks
• Automated Equation Formulation for Causal Loop Diagrams
• An Empirical Study on Spreadsheet Shortcomings from an Information Systems Perspective
• A Mark Based-Temporal Conceptual Graphs for Enhancing Big Data Management and Attack Scenario Reconstruction
• Semantic Technologies
• Ontology-Based Creation of 3D Content in a Service-Oriented Environment
• Modeling and Querying Sensor Services Using Ontologies
• Validation and Calibration of Dietary Intake in Chronic Kidney Disease: An Ontological Approach
• Content Retrieval and Filtering
• Evaluation of the Dynamic Construct Competition Miner for an eHealth System
• Dynamic Reconfiguration of Composite Convergent Services Supported by Multimodal Search
• On Extracting Information from Semi-structured Deep Web Documents
• A Novel Approach to Web Information Extraction
• Business Process Management and Mining
• Mining Multi-variant Process Models from Low-Level Logs
• On Improving the Maintainability of Compliance Rules for Business Processes
• Evolutionary Computation Based Discovery of Hierarchical Business Process Models
• Collaboration
• Empowering End-Users to Collaboratively Structure Processes for Knowledge Work
• Social Collaboration Solutions as a Catalyst of Consumer Trust in Service Management Platforms
• A Research Study
• The Relative Advantage of Collaborative Virtual Environments and Two-Dimensional Websites in Multichannel Retail
• Enterprise Architecture and Business-IT-Alignment
• Combining Business Processes and Cloud Services: A Marketplace for Processlets
• The Nature and a Process for Development of Enterprise Architecture Principles
• Interrelations Between Enterprise Modeling Focal Areas and Business and IT Alignment Domains
• Specific BIS Applications
• Multi-dimensional Performance Measurement in Complex Networks
• Model and Integration for Logistics Chain Management
• Engaging Facebook Users in Brand Pages: Different Posts of Marketing-Mix Information
• Context Variation for Service Self-contextualization in Cyber-Physical Systems
• EPOs, an Early Warning System for Post-merger IS Integration
• Open Data for BIS
• The Adoption of Open Data and Open API Telecommunication Functions by Software Developers
• The Use of Open API in Travel Planning Application
• Tap & Plan Use Case.

This book contains the refereed proceedings of the 18th International Conference on Business Information Systems, BIS 2015, held in Poznań, Poland, in June 2015. The BIS conference series follows trends in academic and business research; thus, the theme of the BIS 2015 conference was "Making Big Data Smarter." Big data is now a fairly mature concept, recognized and widely used by professionals in both research and industry. Together, they work on developing more adequate and efficient tools for data processing and analyzing, thus turning "big data" into "smart data." The 26 revised full papers were carefully reviewed and selected from 70 submissions. In addition, two invited papers are included in this book. They are grouped into sections on big and smart data, semantic technologies, content retrieval and filtering, business process management and mining, collaboration, enterprise architecture and business−IT alignment, specific BIS applications, and open data for BIS.