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• Life Science Data Modelling.- Analysing, Indexing, and Querying Life Sciences Datasets.- Annotating, Matching, and Sharing Life Sciences Datasets.- Privacy and Provenance of Life Sciences Datasets.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 12th International Conference on Data Integration in the Life Sciences, DILS 2017, held in Luxembourg, in November 2017. The 5 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 16 submissions. They cover topics such as: life science data modelling; analysing, indexing, and querying life sciences datasets; annotating, matching, and sharing life sciences datasets; privacy and provenance of life sciences datasets.
(source: Nielsen Book Data)

• Knowledge discovery of biomedical data.- Managing, querying and processing of medical image data.- Information extraction and data integration for biomedical data.- Health information systems.
• (source: Nielsen Book Data)

This book constitutes the thoroughly refereed post-conference proceedings of the Second International Workshop on Data Management and Analytics for Medicine and Healthcare, DMAH 2016, in New Delhi, India, in September 2016, held in conjunction with the 42nd International Conference on Very Large Data Bases, VLDB 2016. The 7 revised full papers presented together with 2 invited papers and 3 keynote abstracts were carefully reviewed and selected from 11 initial submissions. The papers are organized in topical sections on knowledge discovery of biomedical data; managing, querying and processing of medical image data; information extraction and data integration for biomedical data; and health information systems.
(source: Nielsen Book Data)

• Association Analysis.- A Process for Exploring Employees' Relationships via Social Network and Sentiment Analysis.- Mining Relationship between User Purposes and Product Features towards Purpose-Oriented Recommendation.- Finding Top-k Fuzzy Frequent Itemsets from Databases.- Association Rule Mining in Healthcare Analytics.- Does Student's Diligence to Study Relate to His/Her Academic Performance.- Correlation anaylsis of diesel engine performance testing data based on mixed-copula method.- Clustering.- Comparative Study of Apache Spark MLlib Clustering Algorithms.- l-DP algorithm: a hybrid density peaks clustering.- Prediction.- Incremental Adaptive Time Series Prediction for Power Demand Forecasting.- Food Sales Prediction with Meteorological Data { A Case Study of a Japanese Chain Supermarket.- Cascade Spatial Autoregression for Air Pollution Prediction.- Machine Learning Techniques for Prediction of Pre-fetched Objects in Handling Big Data Storage.- Classification.- Spectral-Spatial Mineral Classification Of Lunar Surface Using Band Parameters With Active Learning.- R2CEDM: A Rete-based RFID Complex Event Detection Method.- Learning Analytics for SNS-Integrated Virtual Learning Environment.- LBP vs. LBP Variance for Texture Classification.- A Decision Tree Of Ignition Point For Simple Inflammable Chemical Compounds.- Analyzing Consumption Behaviors of Pet Owners in a Veterinary Hospital.- Schedule and Sequence Analysis.- Modeling Inter-Country Connection from Geotagged News Reports: A Time-Series Analysis.- Mining Sequential Patterns of Students' Access on Learning Management System.- Design of a dynamic electricity trade scheduler based on genetic algorithms.- Increasing Coverage of Information Spreading in Social Networks with Supporting Seeding.- Big Data.- B-Learning and Big Data: Use in Training an Engineering Course.- Mapping Knowledge Domain Research in Big Data: From 2006 to 2016.- Template based Industrial Big Data Information Extraction and Query System.- Finding the Typical Communication Black Hole in Big Data Environment.- A Solution for Mining Big Data Based on Distributed Data Streams and Its Classifying Algorithms.- Data Analysis.- Design of a Quality-Aware Data Capture System.- Data Architecture for the Internet of Things and Industry 4.0.- Machine Learning in Data Lake for Combining Data Silos.- Development of 3D Earth Visualization for Taiwan Ocean Environment Demonstration.- Exploring Potential Use of Mobile Phone Data Resource to Analyze Inter-Regional Travel Patterns in Japan.- REBUILD:Graph Embedding Based Method for User Social Role Identity on Mobile Communication Network.- Study A Join Query Strategy over Data Stream Based on Sliding Windows.- Data Mining.- L2 Learners' Proficiency Evaluation Using Statistics Based on Relationship among CEFR Rating Scales.- Research Hotspots and Trends in Data Mining: From 1993 to 2016.- Proposal for a New Reduct Method for Decision Tables and an Improved STRIM.- Post-marketing Drug Safety Evaluation using Data Mining Based on FAERS.- Crowd density estimation from few RF tracking devices: I. Modelling Framework.- Text Mining.- Mining Textual Reviews with Hierarchical Latent Tree Analysis.- Extraction of Temporal Events from Clinical Text using Semi-Supervised Conditional Random Fields.- Characteristics of language usage in inquires asked to an online help desk.- Deep Learning.- A Novel Diagnosis Method for SZ by Deep Neural Networks.- A Novel Data-driven Fault Diagnosis Method Based on Deep Learning.- High Performance Computing.- Simulated Precipitation and Reservoir Inflow in the Chao Phraya River Basin by Multi-Model Ensemble CMIP3 & CMIP5.- An IDL-Based Parallel Model for Scientific Computations on Multi-Core Computers.- Accelerating Redis with RDMA over InfiniBand.- Knowledge Base and its Framework.- Application of Decision Trees in the Development of a Knowledge Base for a System of Support for Revitalization Processes.- ABC Metaheuristic Based Optimized Adaptation Planning Logic for Decision Making Intelligent Agents in Self Adaptive Software System.- A Knowledge-based Framework for Mitigating Hydro-Meteorological Disasters.- Fuzzy Control.- Improved Stability and Stabilization Criteria for T-S Fuzzy Systems with Distributed Time-Delay.- Adaptive Neuro-Fuzzy Inference System: Overview, Strengths, Limitations, and Solutions.- Acquisition of Knowledge in the Form of Fuzzy Rules for Cases Classification.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the Second International Conference on Data Mining and Big Data, DMBD 2017, held in Fukuoka, Japan, in July/August 2017. The 53 papers presented in this volume were carefully reviewed and selected from 96 submissions. They were organized in topical sections named: association analysis; clustering; prediction; classification; schedule and sequence analysis; big data; data analysis; data mining; text mining; deep learning; high performance computing; knowledge base and its framework; and fuzzy control. .
(source: Nielsen Book Data)

• Semantic Web and Semantics.- Graph Matching.- Data Modeling, Data Abstraction, and Uncertainty.- Preferences and Query Optimization.- Data Integration and RDF Matching.- Security and Privacy.- Web Search.- Data Clustering.- Top-K and Skyline Queries.- Data Mining and Big Data.- Service Computing.- Continuous and Temporal Data, and Continuous Query Language.- Text Processing and Semantic Search.- Indexing and Concurrency Control Methods.- Data Warehouse and Data Stream Warehouse.- Data Mining and Machine Learning.- Recommender Systems and Query Recommendation.- Graph Algorithms.- Semantic Clustering and Data Classification.
• (source: Nielsen Book Data)

This two volume set LNCS 10438 and LNCS 10439 constitutes the refereed proceedings of the 28th International Conference on Database and Expert Systems Applications, DEXA 2017, held in Lyon, France, August 2017. The 37 revised full papers presented together with 40 short papers were carefully reviewed and selected from 166 submissions. The papers discuss a range of topics including: Semantic Web and Semantics; Graph Matching; Data Modeling, Data Abstraction, and Uncertainty; Preferences and Query Optimization; Data Integration and RDF Matching; Security and Privacy; Web Search; Data Clustering; Top-K and Skyline Queries; Data Mining and Big Data; Service Computing; Continuous and Temporal Data, and Continuous Query Language; Text Processing and Semantic Search; Indexing and Concurrency Control Methods; Data Warehouse and Data Stream Warehouse; Data Mining and Machine Learning; Recommender Systems and Query Recommendation; Graph Algorithms; Semantic Clustering and Data Classific ation.
(source: Nielsen Book Data)

• Semantic web and knowledge management.- Indexing and distributed systems.- Network embedding.-Trajectory and time series data processing.- Data mining.- Query processing and optimization.-Text mining.-recommendation.- Security, privacy, senor and cloud.- Social network analytics.- Map matching and spatial keywords.- Query processing and optimization.- Search and information retrieval.- String and sequence processing.- Stream data processing.- Graph and network data processing.- Spatial databases.- Real time data processing.- Big data.- Social networks and graphs.
• (source: Nielsen Book Data)

This two volume set LNCS 10177 and 10178 constitutes the refereed proceedings of the 22nd International Conference on Database Systems for Advanced Applications, DASFAA 2017, held in Suzhou, China, in March 2017. The 73 full papers, 9 industry papers, 4 demo papers and 3 tutorials were carefully selected from a total of 300 submissions. The papers are organized around the following topics: semantic web and knowledge management; indexing and distributed systems; network embedding; trajectory and time series data processing; data mining; query processing and optimization; text mining; recommendation; security, privacy, senor and cloud; social network analytics; map matching and spatial keywords; query processing and optimization; search and information retrieval; string and sequence processing; stream date processing; graph and network data processing; spatial databases; real time data processing; big data; social networks and graphs.
(source: Nielsen Book Data)

• Semantic web and knowledge management.- Indexing and distributed systems.- Network embedding.-Trajectory and time series data processing.- Data mining.- Query processing and optimization.-Text mining.-recommendation.- Security, privacy, senor and cloud.- Social network analytics.- Map matching and spatial keywords.- Query processing and optimization.- Search and information retrieval.- String and sequence processing.- Stream data processing.- Graph and network data processing.- Spatial databases.- Real time data processing.- Big data.- Social networks and graphs.
• (source: Nielsen Book Data)

This two volume set LNCS 10177 and 10178 constitutes the refereed proceedings of the 22nd International Conference on Database Systems for Advanced Applications, DASFAA 2017, held in Suzhou, China, in March 2017. The 73 full papers, 9 industry papers, 4 demo papers and 3 tutorials were carefully selected from a total of 300 submissions. The papers are organized around the following topics: semantic web and knowledge management; indexing and distributed systems; network embedding; trajectory and time series data processing; data mining; query processing and optimization; text mining; recommendation; security, privacy, senor and cloud; social network analytics; map matching and spatial keywords; query processing and optimization; search and information retrieval; string and sequence processing; stream date processing; graph and network data processing; spatial databases; real time data processing; big data; social networks and graphs.
(source: Nielsen Book Data)

• Spatial databases.- Query processing.- Similarity search.- Data mining.- AI for big data.- Potpourri.- Demo papers.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 28th Australasian Database Conference, ADC 2017, held in Brisbane, QLD, Australia, in September 2017. The 20 full papers presented together with 2 demo papers were carefully reviewed and selected from 32 submissions. The mission of ADC is to share novel research solutions to problems of today's information society that fulfill the needs of heterogeneous applications and environments and to identify new issues and directions for future research and development work. The topics of the presented papers are related to all practical and theoretical aspects of advanced database theory and applications, as well as case studies and implementation experiences.
(source: Nielsen Book Data)

• Preface.- Introduction.- Tinnitus treatment as a problem area
• Recommender solutions overview.- Knowledge discovery approach for recommendation.- RECTIN system design.- Experiment 1: classifiers.- Experiment 2: diagnostic rules.- Experiment 3: treatment rules.- Experiment 4: treatment rules enhancement.- RECTIN implementation.- Final conclusions and future work.- References.
• (source: Nielsen Book Data)

The book presents a knowledge discovery based approach to build a recommender system supporting a physician in treating tinnitus patients with the highly successful method called Tinnitus Retraining Therapy. It describes experiments on extracting novel knowledge from the historical dataset of patients treated by Dr. P. Jastreboff so that to better understand factors behind therapy's effectiveness and better personalize treatments for different profiles of patients. The book is a response for a growing demand of an advanced data analytics in the healthcare industry in order to provide better care with the data driven decision-making solutions. The potential economic benefits of applying computerized clinical decision support systems include not only improved efficiency in health care delivery (by reducing costs, improving quality of care and patient safety), but also enhancement in treatment's standardization, objectivity and availability in places of scarce expert's knowledge on this difficult to treat hearing disorder. Furthermore, described approach could be used in assessment of the clinical effectiveness of evidence-based intervention of various proposed treatments for tinnitus.
(source: Nielsen Book Data)

• Third International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017:
• Simultaneous Multiple Surface Segmentation Using Deep Learning / Abhay Shah, Michael D. Abramoff, Xiaodong Wu
• A Deep Residual Inception Network for HEp-2 Cell Classification / Yuexiang Li, Linlin Shen
• Joint Segmentation of Multiple Thoracic Organs in CT Images with Two Collaborative Deep Architectures / Roger Trullo, Caroline Petitjean, Dong Nie, Dinggang Shen, Su Ruan
• Accelerated Magnetic Resonance Imaging by Adversarial Neural Network / Ohad Shitrit, Tammy Riklin Raviv
• Left Atrium Segmentation in CT Volumes with Fully Convolutional Networks / Honghui Liu, Jianjiang Feng, Zishun Feng, Jiwen Lu, Jie Zhou
• 3D Randomized Connection Network with Graph-Based Inference / Siqi Bao, Pei Wang, Albert C. S. Chung
• Adversarial Training and Dilated Convolutions for Brain MRI Segmentation / Pim Moeskops, Mitko Veta, Maxime W. Lafarge, Koen A. J. Eppenhof, Josien P. W. Pluim
• CNNs Enable Accurate and Fast Segmentation of Drusen in Optical Coherence Tomography / Shekoufeh Gorgi Zadeh, Maximilian W. M. Wintergerst, Vitalis Wiens, Sarah Thiele, Frank G. Holz, Robert P. Finger et al.
• Region-Aware Deep Localization Framework for Cervical Vertebrae in X-Ray Images / S. M. Masudur Rahman Al Arif, Karen Knapp, Greg Slabaugh
• Domain-Adversarial Neural Networks to Address the Appearance Variability of Histopathology Images / Maxime W. Lafarge, Josien P. W. Pluim, Koen A. J. Eppenhof, Pim Moeskops, Mitko Veta
• Accurate Lung Segmentation via Network-Wise Training of Convolutional Networks / Sangheum Hwang, Sunggyun Park
• Deep Residual Recurrent Neural Networks for Characterisation of Cardiac Cycle Phase from Echocardiograms / Fatemeh Taheri Dezaki, Neeraj Dhungel, Amir H. Abdi, Christina Luong, Teresa Tsang, John Jue et al.
• Computationally Efficient Cardiac Views Projection Using 3D Convolutional Neural Networks / Matthieu Le, Jesse Lieman-Sifry, Felix Lau, Sean Sall, Albert Hsiao, Daniel Golden
• Non-rigid Craniofacial 2D-3D Registration Using CNN-Based Regression / Yuru Pei, Yungeng Zhang, Haifang Qin, Gengyu Ma, Yuke Guo, Tianmin Xu et al.
• A Deep Level Set Method for Image Segmentation / Min Tang, Sepehr Valipour, Zichen Zhang, Dana Cobzas, Martin Jagersand
• Context-Based Normalization of Histological Stains Using Deep Convolutional Features / D. Bug, S. Schneider, A. Grote, E. Oswald, F. Feuerhake, J. Schüler et al.
• Transitioning Between Convolutional and Fully Connected Layers in Neural Networks / Shazia Akbar, Mohammad Peikari, Sherine Salama, Sharon Nofech-Mozes, Anne Martel
• Quantifying the Impact of Type 2 Diabetes on Brain Perfusion Using Deep Neural Networks / Behrouz Saghafi, Prabhat Garg, Benjamin C. Wagner, S. Carrie Smith, Jianzhao Xu, Ananth J. Madhuranthakam et al.
• Multi-stage Diagnosis of Alzheimer's Disease with Incomplete Multimodal Data via Multi-task Deep Learning / Kim-Han Thung, Pew-Thian Yap, Dinggang Shen
• A Multi-scale CNN and Curriculum Learning Strategy for Mammogram Classification / William Lotter, Greg Sorensen, David Cox
• Analyzing Microscopic Images of Peripheral Blood Smear Using Deep Learning / Dheeraj Mundhra, Bharath Cheluvaraju, Jaiprasad Rampure, Tathagato Rai Dastidar
• AGNet: Attention-Guided Network for Surgical Tool Presence Detection / Xiaowei Hu, Lequan Yu, Hao Chen, Jing Qin, Pheng-Ann Heng
• Pathological Pulmonary Lobe Segmentation from CT Images Using Progressive Holistically Nested Neural Networks and Random Walker / Kevin George, Adam P. Harrison, Dakai Jin, Ziyue Xu, Daniel J. Mollura
• End-to-End Unsupervised Deformable Image Registration with a Convolutional Neural Network / Bob D. de Vos, Floris F. Berendsen, Max A. Viergever, Marius Staring, Ivana Išgum
• Stain Colour Normalisation to Improve Mitosis Detection on Breast Histology Images / Azam Hamidinekoo, Reyer Zwiggelaar
• 3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation / Masahiro Oda, Natsuki Shimizu, Holger R. Roth, Ken'ichi Karasawa, Takayuki Kitasaka, Kazunari Misawa et al.
• A Unified Framework for Tumor Proliferation Score Prediction in Breast Histopathology / Kyunghyun Paeng, Sangheum Hwang, Sunggyun Park, Minsoo Kim
• Generalised Dice Overlap as a Deep Learning Loss Function for Highly Unbalanced Segmentations / Carole H. Sudre, Wenqi Li, Tom Vercauteren, Sebastien Ourselin, M. Jorge Cardoso
• ssEMnet: Serial-Section Electron Microscopy Image Registration Using a Spatial Transformer Network with Learned Features / Inwan Yoo, David G. C. Hildebrand, Willie F. Tobin, Wei-Chung Allen Lee, Won-Ki Jeong
• Fully Convolutional Regression Network for Accurate Detection of Measurement Points / Michal Sofka, Fausto Milletari, Jimmy Jia, Alex Rothberg
• Fast Predictive Simple Geodesic Regression / Zhipeng Ding, Greg Fleishman, Xiao Yang, Paul Thompson, Roland Kwitt, Marc Niethammer et al.
• Learning Spatio-Temporal Aggregation for Fetal Heart Analysis in Ultrasound Video / Arijit Patra, Weilin Huang, J. Alison Noble
• Fast, Simple Calcium Imaging Segmentation with Fully Convolutional Networks / Aleksander Klibisz, Derek Rose, Matthew Eicholtz, Jay Blundon, Stanislav Zakharenko
• Self-supervised Learning for Spinal MRIs / Amir Jamaludin, Timor Kadir, Andrew Zisserman
• Skin Lesion Segmentation via Deep RefineNet / Xinzi He, Zhen Yu, Tianfu Wang, Baiying Lei
• Multi-scale Networks for Segmentation of Brain Magnetic Resonance Images / Jie Wei, Yong Xia
• Deep Learning for Automatic Detection of Abnormal Findings in Breast Mammography / Ayelet Akselrod-Ballin, Leonid. Karlinsky, Alon Hazan, Ran Bakalo, Ami Ben Horesh, Yoel Shoshan et al.
• Grey Matter Segmentation in Spinal Cord MRIs via 3D Convolutional Encoder Networks with Shortcut Connections / Adam Porisky, Tom Brosch, Emil Ljungberg, Lisa Y. W. Tang, Youngjin Yoo, Benjamin De Leener et al.
• 7th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017:
• Mapping Multi-Modal Routine Imaging Data to a Single Reference via Multiple Templates / Johannes Hofmanninger, Bjoern Menze, Marc-André Weber, Georg Langs
• Automated Detection of Epileptogenic Cortical Malformations Using Multimodal MRI / Ravnoor S. Gill, Seok-Jun Hong, Fatemeh Fadaie, Benoit Caldairou, Boris Bernhardt, Neda Bernasconi et al.
• Prediction of Amyloidosis from Neuropsychological and MRI Data for Cost Effective Inclusion of Pre-symptomatic Subjects in Clinical Trials / Manon Ansart, Stéphane Epelbaum, Geoffroy Gagliardi, Olivier Colliot, Didier Dormont, Bruno Dubois et al.
• Automated Multimodal Breast CAD Based on Registration of MRI and Two View Mammography / T. Hopp, P. Cotic Smole, N. V. Ruiter
• EMR-Radiological Phenotypes in Diseases of the Optic Nerve and Their Association with Visual Function / Shikha Chaganti, Jamie R. Robinson, Camilo Bermudez, Thomas Lasko, Louise A. Mawn, Bennett A. Landman
• Erratum to: Fast Predictive Simple Geodesic Regression / Zhipeng Ding, Greg Fleishman, Xiao Yang, Paul Thompson, Roland Kwitt, Marc Niethammer et al.

This book constitutes the refereed joint proceedings of the Third International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017, and the 6th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 38 full papers presented at DLMIA 2017 and the 5 full papers presented at ML-CDS 2017 were carefully reviewed and selected. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.
(source: Nielsen Book Data)

• Preface.- Acknowledgements.- Chapte
• r1: Introduction.- Chapte
• r2: Selected topics in fuzzy systems designing.- Chapte
• r3: Introduction to fuzzy system interpretability.- Chapte
• r4: Improving fuzzy systems interpretability by appropriate selection of their structure.- Chapte
• r5: Interpretability of fuzzy systems designed in the process of gradient learning.- Chapte
• r6: Interpretability of fuzzy systems designed in the process of evolutionary learning.- Chapte
• r7: Case study: interpretability of fuzzy systems applied to nonlinear modelling and control.- Chapte
• r8: Case study: interpretability of fuzzy systems applied to identity verification.- Chapte
• r9: Concluding remarks and future perspectives.- Index.
• (source: Nielsen Book Data)

This book shows that the term "interpretability" goes far beyond the concept of readability of a fuzzy set and fuzzy rules. It focuses on novel and precise operators of aggregation, inference, and defuzzification leading to flexible Mamdani-type and logical-type systems that can achieve the required accuracy using a less complex rule base. The individual chapters describe various aspects of interpretability, including appropriate selection of the structure of a fuzzy system, focusing on improving the interpretability of fuzzy systems designed using both gradient-learning and evolutionary algorithms. It also demonstrates how to eliminate various system components, such as inputs, rules and fuzzy sets, whose reduction does not adversely affect system accuracy. It illustrates the performance of the developed algorithms and methods with commonly used benchmarks. The book provides valuable tools for possible applications in many fields including expert systems, automatic control and robotics.
(source: Nielsen Book Data)

• Intro; Preface; Contents; List of Figures; List of Tables; 1 On Using Fuzzy Logic to Control a Simulated Hexacopter Carrying an Attached Pendulum; 1.1 Introduction; 1.2 Description of the Controlled Plant: The Hexacopter; 1.3 Proposed Multi-layer Controller; 1.3.1 Pre-processing Phase; 1.3.2 Post-processing Phase; 1.4 The Fuzzy Controllers; 1.4.1 The Fuzzy Method; 1.4.2 Roll Stabilization; 1.4.3 Pitch Stabilization; 1.4.4 Heading to Goal (Yaw Controller); 1.4.5 The Horizontal Navigation; 1.4.6 The Vertical Navigation; 1.5 Experiment and Results; 1.5.1 Overview of the Experiment; 1.5.2 Results

• 1.5.3 Discussion1.6 Conclusions and Future Work; References; 2 Monocular Pose Estimation for an Unmanned Aerial Vehicle Using Spectral Features; 2.1 Introduction; 2.2 Homography-Based Pose Estimation; 2.2.1 Review of Plane-Induced Homography; 2.2.2 Homography Decomposition; 2.3 Spectral Features Correspondence; 2.3.1 Corresponding Points; 2.4 Implementation and Results; 2.4.1 Spectral Features Evaluation; 2.4.2 Pose Estimation in Simulated Quadcopter; 2.5 Conclusions; References; 3 Simultaneous Navigation and Mapping in an Autonomous Vehicle Based on Fuzzy Logic; 3.1 Introduction

• 3.2 Virtual Robot Experimentation Platform3.3 Autonomous Vehicle; 3.4 Navigation and Mapping; 3.4.1 Trajectory Planning; 3.4.2 Navigation; 3.4.3 Decision Tree; 3.5 Simulation; 3.6 Case Study; 3.7 Conclusions; References; 4 Fully Scalable Parallel Hardware for Wheeled Robot Navigation Using Fuzzy Control; 4.1 Introduction; 4.2 Fuzzy Controlllers; 4.3 Fuzzy Models for Wheeled Robot Navigation; 4.4 The Proposed Macro-architecture; 4.5 Micro-architecture of the Functional Units; 4.5.1 Membership Function Unit; 4.5.2 Membership Function Memory; 4.5.3 Fuzzification Unit; 4.5.4 Inference Unit

• 4.5.5 Defuzzification Unit4.6 Performance Results; 4.7 Conclusion; References; 5 Nonlinear Correction for an Energy Estimator Operating at Severe Pile-Up Conditions; 5.1 Introduction; 5.2 High-Energy Signal Pile-Up; 5.3 Online Linear Estimation; 5.3.1 Minimum Variance Linear Unbiased Estimator; 5.3.2 Maximum Likelihood Estimation; 5.4 Nonlinear Correction; 5.5 Performance Comparisons; 5.5.1 Data Set; 5.5.2 Nonlinear Corrector Design; 5.5.3 Efficiency Tests; 5.5.4 Bias and Linearity; 5.5.5 Performance at Different Occupancy Levels; 5.5.6 Exploring the ANN Generalization; 5.6 Conclusions

• 8 Human
• Machine Musical Composition in Real-Time Based on Emotions Through a Fuzzy Logic Approach

This book discusses a number of real-world applications of computational intelligence approaches. Using various examples, it demonstrates that computational intelligence has become a consolidated methodology for automatically creating new competitive solutions to complex real-world problems. It also presents a concise and efficient synthesis of different systems using computationally intelligent techniques.

• Advanced Classification of Remote Sensing High Resolution Imagery.- An Application for the Management of Natural Resources.- Analyzing the Impact of Strategic Performance Management Systems and Role Ambiguity on Performance: A Qualitative Approach.- Advanced Radial Approach to Resource Location Problems.- Verbal Decision Analysis Applied to the Prioritization of Influencing Factors in Distributed Software Development.- Agile Documentation Tool Concept.- Pervasive Business Intelligence: A Key Success Factor for Business.- Annotated Documents and Expanded CIDOC-CRM Ontology in the Automatic Construction of a Virtual Museum.
• (source: Nielsen Book Data)

This book primarily addresses Intelligent Information Systems (IIS) and the integration of artificial intelligence, intelligent systems and technologies, database technologies and information systems methodologies to create the next generation of information systems. It includes original and state-of-the-art research on theoretical and practical advances in IIS, system architectures, tools and techniques, as well as "success stories" in intelligent information systems. Intended as an interdisciplinary forum in which scientists and professionals could share their research results and report on new developments and advances in intelligent information systems, technologies and related areas - as well as their applications - , it offers a valuable resource for researchers and practitioners alike.
(source: Nielsen Book Data)

• From a Small Liberal Arts College to the World: Our Blended Courses, SPOC, and MOOCs in Italian Studies.- Giving Exible Learners a Head Start on Higher Education: Designing and Implementing a Pre-induction Socialization MOOC.- The E.M.M.A. Experience: Emerging Patterns and Factors for Success.- Mentoring Learners in MOOCs: a New Way to Improve Completion Rates.- Towards e-Presence at Distance as a Way to Reach and Share e-Quality: the Case of the ECO sMOOCs.- Additional Functionalities to Convert an xMOOC into an xLMOOC.- A Principled Approach to the Design of Collaborative MOOC Curricula.- Towards Full Engagement for Open Online Education. A Practical Experience for a MicroMaster.- From Low-Scale to Collaborative, Gamified and Massive-Scale Courses: Redesigning a MOOC.- Innovation in EU Communication: MOOCs from the European Committee of the Regions.- Does Gamification in MOOC Discussion Forums Work.- A MOOC-based Flipped Class: Lessons Learned from the Orchestration Perspective.- An International Collaboration in the Design Experience of a MOOC Series.- Measuring the Degree of Innovation in Education through the Implementation of an Indicator Based on Analyzing MOOC-related Activities.- Towards a Typology of MOOC Activity Patterns: Learners Who never Rest.- Improving MOOC Student Learning through Enhanced Peer-to-Peer Tasks.- Who Wants to Chat on a MOOC? Lessons from a Peer Recommender System.- Weekly Predicting the At-risk MOOC Learners Using Dominance-based Rough Set Approach.- MOOC Friends and Followers: An Analysis of Twitter Hashtag Networks.- Understanding Learning and Teaching in MOOCs from the Perspectives of Students and Instructors: a Review of Literature from 2014 to 2016.- Effect of Free Certificate Discontinuation in Completion Rates of MOOC.- Challenges of Identifying Second Language English Speakers in MOOCs.- MOOC Quality Evaluation System: Tomsk State University Experience.- The Drivers of Employer Support for Professional Skill Development in MOOCs.- To Change or not to Change? That's the Question on MOOC-Success, Barriers and Their Implications.- Follow-up of Learning Activities in Open edX: a Case Study at the University of Cauca.- Increasing Educational Value: the Transformation of MOOCs into Open Educational Resources.- Implementation Intention and How it Affects Goal Achievement in MOOCs.- A Social Learning Grid for MOOCs: Exploring a FutureLearn Case.- The Double Classroom: Design Patterns Using MOOCs in Teacher Education.- Early Prediction and Variable Importance of Certificate Accomplishment.- Types of Dropout in Adaptive Open Online Courses.- Exploring the Role of Assessment in Developing Learners' Critical Thinking in Massive Open Online Courses. .
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 5th European Conference, EMOOCs 2017, held in Leganes, Madrid, Spain, in May 2017. The 23 full and 10 short papers presented in this volume were carefully reviewed and selected from 53 submissions. Massive Open Online Courses (MOOCs) have marked a milestone in the use of technology for education. The reach, potential, and possibilities of EMOOCs are immense. But they are not only restricted to global outreach: the same technology can be used to improve teaching on campus and training inside companies and institutions. .
(source: Nielsen Book Data)

• Automatic Classification and Recommendation.- Cultural Heritage and Indigenous Knowledge.- Data Sharing and Retrieval.- Lexical and Discourse Analysis.- Mobile Applications.- Search Results Presentation and Visualization.- Social Media.- User Behaviors.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 19th International Conference on Asia-Pacific Digital Libraries, ICADL 2017, held in Bangkok, Thailand, in November 2017. The 21 full papers and 6 short papers presented in this book were carefully reviewed and selected from 51 submissions. The paper topics of ICADL 2017 covered a wide spectrum from various areas, including information visualization, data mining/extraction, cultural heritage preservation, personalized service and user modeling, novel library content and use environments, electronic publishing, preservation systems and algorithms, social networking and information systems, Internet of things, cloud computing and applications, mobile services, interoperability issues, open source tools and systems, security and privacy, multi-language support, metadata and cataloguing, search, retrieval and browsing interfaces to all forms of digital content, e-Science/e-Research data and knowledge management, and cooperative service and community service.
(source: Nielsen Book Data)

• Chapter 1: Requirements for Digital Preservation.-
• Chapter 2: Metadata in Long-term Digital Preservation.-
• Chapter 3: The CREDO Project.-
• Chapter 4: CREDO Repository Architecture.-
• Chapter 5: Information Processing in CREDO Long-term Archive.-
• Chapter 6: Metadata in CREDO Long-term Archive.-
• Chapter 7: Persistence Management in Long-term Digital Archive.-
• Chapter 8: Power Efficiency and Scheduling Access to the Archive.-
• Chapter 9: Information Management in Federated Digital Archives.
• (source: Nielsen Book Data)

This book addresses the process of maintaining digital objects through time to ensure continued access, an aspect that has become a crucial issue in recent years. It offers a concise yet comprehensive discussion of key concepts and requirements for long-term digital preservation, and presents a pioneering framework for digital repositories that enables the long-term archiving and metadata management for large volumes of digital resources based on a system that has already been completely designed and launched. In the framework, the reliability of information readouts is ensured by the repository with two-level data recording replication and monitoring mechanisms in the repository management system (RMS) and the file systems, and by the RMS's distributed nature. The advanced RMS allows operations on the archival storage to be scheduled, while also taking into account low energy consumption requirements. After presenting the framework in detail, the book assesses and demonstrates the approach's viability in terms of delivering accessibility, authenticity and usability. As such, the book offers a valuable resource for information technology (IT) researchers and practitioners, as well as archivists and librarians.
(source: Nielsen Book Data)

• Machine learning: online learning, regression, label classification, deep learning, feature selection, recommendation system.- Knowledge discovery: recommendation system, community detection, pattern mining, misc.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 20th International Conference on Discovery Science, DS 2017, held in Kyoto, Japan, in October 2017, co-located with the International Conference on Algorithmic Learning Theory, ALT 2017. The 18 revised full papers presented together with 6 short papers and 2 invited talks in this volume were carefully reviewed and selected from 42 submissions. The scope of the conference includes the development and analysis of methods for discovering scientific knowledge, coming from machine learning, data mining, intelligent data analysis, big data analysis as well as their application in various scientific domains. The papers are organized in topical sections on machine learning: online learning, regression, label classification, deep learning, feature selection, recommendation system; and knowledge discovery: recommendation system, community detection, pattern mining, misc.
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• Algorithms and models for computation with biomolecular systems.- Computational processes in vitro and in vivo.- Molecular motors and molecular robotics.- Studies of fault-tolerance and error correction.- Software tools for analysis, simulation, and design.- Synthetic biology and in vitro evolution.- Applications in engineering, physics, chemistry, biology, and medicine.
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This book constitutes the refereed proceedings of the 23th International Conference on DNA Computing and Molecular Programming, DNA 23, held Austin, TX, USA, in September 2017. The 16 full papers presented were carefully selected from 23 submissions. Research in DNA computing aims to draw together mathematics, computerscience, physics, chemistry, biology, and nanotechnology to address the analysis, design, and synthesis of information-based molecular systems. The papers address all areas related to biomolecular computing such as: algorithms and models for computation with biomolecular systems; computational processes in vitro and in vivo; molecular motors and molecular robotics; studies of fault-tolerance and error correction; software tools for analysis, simulation, and design; synthetic biology and in vitro evolution; applications in engineering, physics, chemistry, biology, and medicine. .
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• Emerging technologies for open access to education and learning.-Emerging technologies supported personalized and adaptive learning.-Emerging technologies support for intelligent tutoring.- Emerging technologies support for game-based and joyful learning.- Emerging technologies of pedagogical issues.- Emerging technologies for affective learning and emerging technologies for tangible learning.
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This book constitutes the thoroughly refereed post-workshop proceedings of the First International Symposium, SETE 2016, held in conjunction with ICWL 2016, Rome, Italy, in October 2016. The 81 revised papers, 59 full and 22 short ones, were carefully reviewed and selected from 139 submission. They cover latest findings in various areas, such as emerging technologies for open access to education and learning; emerging technologies supported personalized and adaptive learning; emerging technologies support for intelligent tutoring; emerging technologies support for game-based and joyful learning; emerging technologies of pedagogical issues; emerging technologies for affective learning and emerging technologies for tangible learning.
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• Design and Usability.- Biomedical and Health Informatics.- Activity and Recognition.- Independent Living Technology.- Smart Home Technology.
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This book constitutes the proceedings of the 15th International Conference on Smart Homes and Health Telematics, ICOST 2017, held in Paris, France, in August 2017. The 18 regular papers, 5 short papers together with 2 invited talks included in this volume were carefully reviewed and selected from numerous submissions. The conference features a dynamic program incorporating a range of design, development, deployment and evaluation of Smart Urban Environments, Assistive Technologies, Chronic Disease Management, Coaching and Health Telematics systems.
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• A Computational Study of Neighborhood Operators for Job-shop Scheduling Problems with Regular Objectives.- A Genetic Algorithm for Multi-Component Optimization Problems: the Case of the Travelling Thief Problem.- A Hybrid Feature Selection Algorithm Based on Large Neighborhood Search.- A Memetic Algorithm to Maximise the Employee Substitutability in Personnel Shift Scheduling.- Construct, Merge, Solve and Adapt versus Large Neighborhood Search for Solving the Multi-Dimensional Knapsack Problem: Which One Works Better When.- Decomposing SAT Instances with Pseudo Backbones.- Efficient Consideration of Soft Time Windows in a Large Neighborhood Search for the Districting and Routing Problem for Security Control.- Estimation of Distribution Algorithms for the Firefighter Problem.- LCS-Based Selective Route Exchange Crossover for the Pickup and Delivery Problem with Time Windows.- Multi-rendezvous Spacecraft Trajectory Optimization with Beam P-ACO.- Optimizing Charging Station Locations for Electric Car-Sharing Systems.- Selection of Auxiliary Objectives Using Landscape Features and Offline Learned Classifier.- Sparse, Continuous Policy Representations for Uniform Online Bin Packing via Regression of Interpolants.- The Weighted Independent Domination Problem: ILP Model and Algorithmic .
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This book constitutes the refereed proceedings of the 17th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2017, held in Amsterdam, The Netherlands, in April 2017, co-located with the Evo*2017 events EuroGP, EvoMUSART and EvoApplications. The 16 revised full papers presented were carefully reviewed and selected from 39 submissions. The papers cover both empirical and theoretical studies on a wide range of academic and real-world applications. The methods include evolutionary and memetic algorithms, large neighborhood search, estimation of distribution algorithms, beam search, ant colony optimization, hyper-heuristics and matheuristics. Applications include both traditional domains, such as knapsack problem, vehicle routing, scheduling problems and SAT; and newer domains such as the traveling thief problem, location planning for car-sharing systems and spacecraft trajectory optimization. Papers also study important concepts such as pseudo-backbones, phase transitions in local optima networks, and the analysis of operators. This wide range of topics makes the EvoCOP proceedings an important source for current research trends in combinatorial optimization.
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