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• Conceptual Modeling Methodology.- Conceptual Modeling and Requirements.- Foundations.- Conceptual Modeling in Specific Context.- Conceptual Modeling and Business Processes.- Model Efficiency.- Ontologies.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 35th International Conference on Conceptual Modeling, ER 2017, held in Valencia, Spain, in November 2017. The 28 full and 10 short papers presented together with 1 full 6 keynotes were carefully reviewed and selected from 153 submissions. This events covers a wide range of following topics: Conceptual Modeling Methodology, Conceptual Modeling and Requirements, Foundations, Conceptual Modeling in Specifi c Context, Conceptual Modeling and Business Processes, Model Efficiency, and Ontologies. .
(source: Nielsen Book Data)

This book constitutes the refereed proceedings of the First International Workshop on Connectomics in NeuroImaging, CNI 2017, held in conjunction with MICCAI 2017 in Quebec City, Canada, in September 2017. The 19 full papers presented were carefully reviewed and selected from 26 submissions. The papers deal with new advancements in network construction, analysis, and visualization techniques in connectomics and their use in clinical diagnosis and group comparison studies as well as in various neuroimaging applications.
(source: Nielsen Book Data)

• Towards a distributed data-sharing economy.- Modeling patient-centric healthcare using socially intelligent systems: the AVICENA experience.- `How did they know?' - Model-checking for analysis of information leakage in social networks.- A manifesto for conscientious design of hybrid online social systems.- Communication and shared mental models for teams performing interdependent tasks.- An empirical approach for relating environmental patterns with agent team compositions.- Monitoring opportunism in multi-agent systems.- The role of values.- On the minimal recognition of rights in holonic institutions. .
• (source: Nielsen Book Data)

This book constitutes the thoroughly refereed post-conference proceedings of the 12th International Workshops on Coordination, Organizations, Institutions and Norms in Agent Systems, COIN 2016. The workshop COIN@AAMAS 2016 was held in Singapore, Singapore, in May 2016, and the workshop COIN@ECAI 2016 was held in The Hague, The Netherlands, in August 2016. The 9 full papers were carefully reviewed and selected from 15 submissions for inclusion in this volume. They cover the following topics: Social Issues: The papers focus on the security of personal data, support for self-care for individuals with chronic conditions, analysis of the risk of information leakage in social networks, and an analysis of issues arising in the design of on-line environments whose participants are human and software. Teams: The papers consider different aspects of team working: what kinds of knowledge sharing best contribute to effective team performance and how to organize a tea m to function effectively in different kinds of scenarios. Rights and Values: The papers examine complementary issues that influence the effective design of normative systems, namely how to detect opportunism so that it may be discouraged, how individuals values influence (collective) decision-making processes and how rights and powers relate to value and conflict resolution in nested organizational structures.
(source: Nielsen Book Data)

• Cyber security.-Secure software development methodologies, formal methods semantics and verification of secure systems.-Fault tolerance, reliability, availability of distributed secure systems.- Game-theoretic approaches to secure computing.- Automatic recovery of self-stabilizing and self-organizing systems.- Communication, authentication and identification security.- Cyber security for mobile and Internet of things.- Cyber security of corporations.- Security and privacy for cloud, edge and fog computing.-Ccryptography.- Cryptographic implementation analysis and construction.- Secure multi-party computation.- Privacy-enhancing technologies and anonymity.- Post-quantum cryptography and security.- Machine learning and big data.- Anomaly detection and malware identification.- Business intelligence and security.- Digital forensics.- Digital rights management
• trust management and reputation systems.- Information retrieval, risk analysis, DoS.>.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the first International Symposium on Cyber Security Cryptography and Machine Learning, held in Beer-Sheva, Israel, in June 2017. The 17 full and 4 short papers presented include cyber security; secure software development methodologies, formal methods semantics and verification of secure systems; fault tolerance, reliability, availability of distributed secure systems; game-theoretic approaches to secure computing; automatic recovery of self-stabilizing and self-organizing systems; communication, authentication and identification security; cyber security for mobile and Internet of things; cyber security of corporations; security and privacy for cloud, edge and fog computing; cryptography; cryptographic implementation analysis and construction; secure multi-party computation; privacy-enhancing technologies and anonymity; post-quantum cryptography and security; machine learning and big data; anomaly detection and malware identification; business intelligence and security; digital forensics; digital rights management; trust management and reputation systems; information retrieval, risk analysis, DoS.
(source: Nielsen Book Data)

• Technology-Enhanced Learning.- Computer-assisted
• instruction.- Interactive learning
• environments.- Collaborative learning.- Learning management
• systems.- Distance learning.- E-Learning.- Data analytics.- Visual analytics.- Information visualization.- Online learning algorithms.- Machine learning.- Learning Anlaytics.- Recommender Systems.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 12th European Conference on Technology Enhanced Learning, EC-TEL 2017, held in Tallinn, Estonia, in September 2017. The 24 full papers, 23 short papers, 6 demo papers, and 22 poster papers presented in this volume were carefully reviewed and selected from 141 submissions. The theme for the 12th EC-TEL conference on Data Driven Approaches in Digital Education' aims to explore the multidisciplinary approaches thateectively illustrate how data-driven education combined with digital education systems can look like and what are the empirical evidences for the use of datadriven tools in educational practices.
(source: Nielsen Book Data)

• 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)

• 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)

• 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.
(source: Nielsen Book Data)

• 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.
• (source: Nielsen Book Data)

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. .
(source: Nielsen Book Data)

• Design and Usability.- Biomedical and Health Informatics.- Activity and Recognition.- Independent Living Technology.- Smart Home Technology.
• (source: Nielsen Book Data)

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.
(source: Nielsen Book Data)

• Intro
• Preface
• Organization
• CLEF Steering Committee
• Contents
• Full Papers
• A Pinch of Humor for Short-Text Conversation: An Information Retrieval Approach
• 1 Introduction
• 2 Related Work
• 3 Data
• 3.1 Joke Collection
• 3.2 Yahoo!Answers
• 4 Retrieval Models
• 4.1 BM25
• 4.2 Query Term Reweighting Model (QTR)
• 4.3 doc2vec
• 5 Evaluation
• 5.1 Yahoo!Answers
• 5.2 Lab Evaluation
• 6 Conclusion and Future Work
• References
• A Component-Level Analysis of an Academic Search Test Collection.
• 1 Introduction
• 2 Component-Level Evaluation in Academic Search

• 3 Study Configurations
• 3.1 Test Collection and Test IR System
• 3.2 Component-Level Configurations
• 3.3 Analysis Steps
• 4 Analyzing Component Performance
• 4.1 Document and Topic Structure
• 4.2 IR System Components
• 5 Conclusion
• References
• A Component-Level Analysis of an Academic Search Test Collection.
• 1 Introduction
• 2 Query Performance Prediction
• 3 Study Configurations
• 3.1 Test Collection and Test IR System
• 3.2 Analysis Steps
• 4 Analyzing Query Performance
• 4.1 Recall Base
• 4.2 Topic Specificity
• 4.3 Semantic Heterogeneity of Topic Terms

• 5 Conclusion
• References
• Improving the Reliability of Query Expansion for User-Generated Speech Retrieval Using Query Performance Prediction
• 1 Introduction
• 2 Previous Work on QE for Spoken Content
• 3 UGS Test Collection
• 3.1 UGS Document Set
• 3.2 Query and Relevance Sets
• 4 Initial Investigation of QE for UGS Retrieval
• 4.1 Retrieval Model
• 4.2 Query Expansion
• 4.3 Passage-Based QE
• 4.4 Experimental Results
• 5 Query Performance Prediction for QE
• 5.1 Query Performance Prediction Methods
• 5.2 Evaluation
• 6 Adaptive Passage-Based QE for UGS Retrieval

• 7 Conclusions and Further Studies
• References
• Optimized Convolutional Neural Network Ensembles for Medical Subfigure Classification
• 1 Introduction
• 2 Revisiting Participation at ImageCLEF 2016
• 3 Dataset Analysis
• 3.1 Data Generation Process
• 3.2 Problems of the Dataset
• 3.3 Suggestions for Future Datasets
• 4 Methodology
• 5 Evaluation
• 5.1 Results Without Additional Images from ImageCLEF 2013
• 5.2 Self-training Using a PubMedCentral Database Snapshot
• 6 Conclusion
• References
• IRIT-QFR: IRIT Query Feature Resource
• 1 Introduction
• 2 Query Features

• 2.1 Document Collection Independent Pre-retrieval Features: WordNet-Based and Other Linguistic Features
• 2.2 Document Collection Dependent Pre-retrieval Features
• 2.3 Post-retrieval Features
• 2.4 Collections for Which the Features Have Been Estimated
• 3 Analysis of the Resource
• 3.1 Descriptive Analysis
• 4 Applications
• 5 Conclusion
• References
• Evaluating and Improving the Extraction of Mathematical Identifier Definitions
• 1 Introduction
• 2 Related Work
• 2.1 Statistical Feature Analysis (ST)
• 2.2 Pattern Matching (PM)
• 2.3 Machine Learning
• 3 Methodology

This book constitutes the refereed proceedings of the 8th International Conference of the CLEF Initiative, CLEF 2017, held in Dublin, Ireland, in September 2017. The 7 full papers and 9 short papers presented together with 6 best of the labs papers were carefully reviewed and selected from 38 submissions. In addition, this volume contains the results of 10 benchmarking labs reporting their year long activities in overview talks and lab sessions. The papers address all aspects of information access in any modality and language and cover a broad range of topics in the field of multilingual and multimodal information access evaluation.
(source: Nielsen Book Data)

• International Workshop on Fetal and Infant Image Analysis, FIFI 2017:
• Template-Free Estimation of Intracranial Volume: A Preterm Birth Animal Model Study / Juan Eugenio Iglesias, Sebastiano Ferraris, Marc Modat, Willy Gsell, Jan Deprest, Johannes L. van der Merwe et al.
• Assessing Reorganisation of Functional Connectivity in the Infant Brain / Roxane Licandro, Karl-Heinz Nenning, Ernst Schwartz, Kathrin Kollndorfer, Lisa Bartha-Doering, Hesheng Liu et al.
• Fetal Skull Segmentation in 3D Ultrasound via Structured Geodesic Random Forest / Juan J. Cerrolaza, Ozan Oktay, Alberto Gomez, Jacqueline Matthew, Caroline Knight, Bernhard Kainz et al.
• Fast Registration of 3D Fetal Ultrasound Images Using Learned Corresponding Salient Points / Alberto Gomez, Kanwal Bhatia, Sarjana Tharin, James Housden, Nicolas Toussaint, Julia A. Schnabel
• Automatic Segmentation of the Intracranial Volume in Fetal MR Images / N. Khalili, P. Moeskops, N. H. P. Claessens, S. Scherpenzeel, E. Turk, R. de Heus et al.
• Abdomen Segmentation in 3D Fetal Ultrasound Using CNN-powered Deformable Models / Alexander Schmidt-Richberg, Tom Brosch, Nicole Schadewaldt, Tobias Klinder, Angelo Cavallaro, Ibtisam Salim et al.
• Multi-organ Detection in 3D Fetal Ultrasound with Machine Learning / Caroline Raynaud, Cybèle Ciofolo-Veit, Thierry Lefèvre, Roberto Ardon, Angelo Cavallaro, Ibtisam Salim et al.
• Robust Regression of Brain Maturation from 3D Fetal Neurosonography Using CRNs / Ana I. L. Namburete, Weidi Xie, J. Alison Noble
• 4th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2017:
• Segmentation of Retinal Blood Vessels Using Dictionary Learning Techniques / Taibou Birgui Sekou, Moncef Hidane, Julien Olivier, Hubert Cardot
• Detecting Early Choroidal Changes Using Piecewise Rigid Image Registration and Eye-Shape Adherent Regularization / Tiziano Ronchetti, Peter Maloca, Christoph Jud, Christoph Meier, Selim Orgül, Hendrik P. N. Scholl et al.
• Patch-Based Deep Convolutional Neural Network for Corneal Ulcer Area Segmentation / Qichao Sun, Lijie Deng, Jianwei Liu, Haixiang Huang, Jin Yuan, Xiaoying Tang
• Model-Driven 3-D Regularisation for Robust Segmentation of the Refractive Corneal Surfaces in Spiral OCT Scans / Joerg Wagner, Simon Pezold, Philippe C. Cattin
• Automatic Retinal Layer Segmentation Based on Live Wire for Central Serous Retinopathy / Dehui Xiang, Geng Chen, Fei Shi, Weifang Zhu, Xinjian Chen
• Retinal Image Quality Classification Using Fine-Tuned CNN / Jing Sun, Cheng Wan, Jun Cheng, Fengli Yu, Jiang Liu
• Optic Disc Detection via Deep Learning in Fundus Images / Peiyuan Xu, Cheng Wan, Jun Cheng, Di Niu, Jiang Liu
• 3D Choroid Neovascularization Growth Prediction with Combined Hyperelastic Biomechanical Model and Reaction-Diffusion Model / Chang Zuo, Fei Shi, Weifang Zhu, Haoyu Chen, Xinjian Chen
• Retinal Biomarker Discovery for Dementia in an Elderly Diabetic Population / Ahmed E. Fetit, Siyamalan Manivannan, Sarah McGrory, Lucia Ballerini, Alexander Doney, Thomas J. MacGillivray et al.
• Non-rigid Registration of Retinal OCT Images Using Conditional Correlation Ratio / Xueying Du, Lun Gong, Fei Shi, Xinjian Chen, Xiaodong Yang, Jian Zheng
• Joint Optic Disc and Cup Segmentation Using Fully Convolutional and Adversarial Networks / Sharath M. Shankaranarayana, Keerthi Ram, Kaushik Mitra, Mohanasankar Sivaprakasam
• Automated Segmentation of the Choroid in EDI-OCT Images with Retinal Pathology Using Convolution Neural Networks / Min Chen, Jiancong Wang, Ipek Oguz, Brian L. VanderBeek, James C. Gee
• Spatiotemporal Analysis of Structural Changes of the Lamina Cribrosa / Charly Girot, Hiroshi Ishikawa, James Fishbaugh, Gadi Wollstein, Joel Schuman, Guido Gerig
• Fast Blur Detection and Parametric Deconvolution of Retinal Fundus Images / Bryan M. Williams, Baidaa Al-Bander, Harry Pratt, Samuel Lawman, Yitian Zhao, Yalin Zheng et al.
• Towards Topological Correct Segmentation of Macular OCT from Cascaded FCNs / Yufan He, Aaron Carass, Yeyi Yun, Can Zhao, Bruno M. Jedynak, Sharon D. Solomon et al.
• Boosted Exudate Segmentation in Retinal Images Using Residual Nets / Samaneh Abbasi-Sureshjani, Behdad Dashtbozorg, Bart M. ter Haar Romeny, François Fleuret
• Development of Clinically Based Corneal Nerves Tortuosity Indexes / Fabio Scarpa, Alfredo Ruggeri
• A Comparative Study Towards the Establishment of an Automatic Retinal Vessel Width Measurement Technique / Fan Huang, Behdad Dashtbozorg, Alexander Ka Shing Yeung, Jiong Zhang, Tos T. J. M. Berendschot, Bart M. ter Haar Romeny
• Automatic Detection of Folds and Wrinkles Due to Swelling of the Optic Disc / Jason Agne, Jui-Kai Wang, Randy H. Kardon, Mona K. Garvin
• Representation Learning for Retinal Vasculature Embeddings / Luca Giancardo, Kirk Roberts, Zhongming Zhao.

This book constitutes the refereed joint proceedings of the International Workshop on Fetal and Infant Image Analysis, FIFI 2017, and the 6th International Workshop on Ophthalmic Medical Image Analysis, OMIA 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 8 full papers presented at FIFI 2017 and the 20 full papers presented at OMIA 2017 were carefully reviewed and selected. The FIFI papers feature research on advanced image analysis approaches focused on the analysis of growth and development in the fetal, infant and paediatric period. The OMIA papers cover various topics in the field of ophthalmic image analysis.
(source: Nielsen Book Data)

• Foundations of Flexible Querying.- Recommendation and Ranking.- Technologies for Flexible Representations and Querying.- Knowledge Discovery and Information/Data Retrieval.- Intuitionistic Sets.- Generalized Net Model.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 12th International Conference on Flexible Query Answering Systems, FQAS 2017, held in London, UK, in June 2017. The 21 full papers presented in this book together with 4 short papers were carefully reviewed and selected from 43 submissions. The papers cover the following topics: foundations of flexible querying; recommendation and ranking; technologies for flexible representations and querying; knowledge discovery and information/data retrieval; intuitionistic sets; and generalized net model.
(source: Nielsen Book Data)