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This book constitutes the refereed proceedings of the 9th International Conference on Reversible Computation, RC 2017, held in Kolkata, India, in July 2017. The 13 full and 5 short papers included in this volume together with one invited paper were carefully reviewed and selected from 47 submissions. The papers are organized in the following topical sections: foundations; reversible circuit synthesis; reversible circuit optimization; testing and fault tolerance; and quantum circuits.
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• Aerial Vehicles progress On Pico Air Vehicles.- Perception and Mapping.- Planning.- Systems and Integration.- Control.
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This volume presents a collection of papers presented at the 15th International Symposium of Robotic Research (ISRR). ISRR is the biennial meeting of the International Foundation of Robotic Research (IFRR) and its 15th edition took place in Flagstaff, Arizona on December 9 to December 12, 2011. As for the previous symposia, ISRR 2011 followed up on the successful concept of a mixture of invited contributions and open submissions. Therefore approximately half of the 37 contributions were invited contributions from outstanding researchers selected by the IFRR officers and the program committee, and the other half were chosen among the open submissions after peer review. This selection process resulted in a truly excellent technical program which featured some of the very best of robotic research. The program was organized around oral presentation in a single-track format and included for the first time a small number of interactive presentations. The symposium contributions contained in this volume report on a variety of new robotics research results covering a broad spectrum including perception, manipulation, grasping, vehicles and design, navigation, control and integration, estimation and SLAM. .
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• Part I Keynote Addresses: Robust Estimation of Heckman Model.- Part II Fundamental Theory: Sequential Monte Carlo Sampling for State Space Models.- Robustness as a Criterion for Selecting a Probability Distribution Under Uncertainty.- Why Cannot We Have a Strongly Consistent Family of Skew Normal (and Higher Order) Distributions.- Econometric Models of Probabilistic Choice: Beyond McFadden's Formulas.- How to Explain Ubiquity of Constant Elasticity of Substitution (CES) Production and Utility Functions Without Explicitly Postulating CES.- How to Make Plausibility-Based Forecasting More Accurate.- Structural Breaks of CAPM-type Market Model with Heteroskedasticity and Quantile Regression.- Weighted Least Squares and Adaptive Least Squares: Further Empirical Evidence.- Prior-free probabilistic inference for econometricians.- Robustness in Forecasting Future Liabilities in Insurance.- On Conditioning in Multidimensional Probabilistic Models.- New Estimation Method for Mixture of Normal Distributions.- EM Estimation for Multivariate Skew Slash Distribution.- Constructions of multivariate copulas.- Plausibility regions on the skewness parameter of skew normal distributions based on inferential models.- International Yield Curve Prediction with Common Functional Principal Component Analysis.- An alternative to p-values in hypothesis testing with applications in model selection of stock price data.- Confidence Intervals for the Common Mean of Several Normal Populations.- A generalized information theoretical approach to Non-linear time series model.- Predictive recursion maximum likelihood of Threshold Autoregressive model.- A multivariate generalized FGM copulas and its application to multiple regression.- Part III Applications: Key Economic Sectors and Their Transitions: Analysis of World Input-Output Network.- Natural Resources, Financial Development and Sectoral Value Added in a Resource Based Economy.- Can bagging improve the forecasting performance of tourism demand models?.- The Role of Asian Credit Default Swap Index in Portfolio Risk Management.- Chinese outbound tourism demand to Singapore, Malaysia and Thailand destinations: A study of political events and holiday impacts.- Forecasting Asian Credit Default Swap spreads: A comparison of multi-regime models.- Forecasting Asian Credit Default Swap spreads: A comparison of multi-regime models.- Effect of Helmet Use on Severity of Head Injuries Using Doubly Robust Estimators.- Forecasting cash holding with cash deposit using time series approaches.- Forecasting GDP Growth in Thailand with Different Leading Indicators using MIDAS regression models.- Testing the Validity of Economic Growth Theories Using Copula-based Seemingly Unrelated Quantile Kink Regression.- Analysis of Global Competitiveness Using Copula-based Stochastic Frontier Kink Model.- Gravity model of trade with Linear Quantile Mixed Models approach.- Stochastic Frontier Model in Financial Econometrics: A Copula-based Approach.- Quantile Forecasting of PM10 Data in Korea based on Time Series Models.- Do We Have Robust GARCH Models under Different Mean Equations: Evidence from Exchange Rates of Thailand?.- Joint Determinants of Foreign Direct Investment (FDI) Inflow in Cambodia: A Panel Co-integration Approach.- The Visitors' Attitudes and Perceived Value toward Rural Regeneration Community Development of Taiwan.- Analyzing the contribution of ASEAN stock markets to systemic risk.- Estimating Efficiency of Stock Return with Interval Data.- The impact of extreme events on portfolio in financial risk management.- Foreign Direct Investment, Exports and Economic Growth in ASEAN Region: Empirical Analysis from Panel Data.- Author Index.
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This book presents recent research on robustness in econometrics. Robust data processing techniques - i.e., techniques that yield results minimally affected by outliers - and their applications to real-life economic and financial situations are the main focus of this book. The book also discusses applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. In day-by-day data, we often encounter outliers that do not reflect the long-term economic trends, e.g., unexpected and abrupt fluctuations. As such, it is important to develop robust data processing techniques that can accommodate these fluctuations.
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• Opening the Black Box: Deriving Rules from Data.- The secret life of rules in Software Engineering.- Meta-Interpretive Learning: achievements and challenges.- Dischargeable Obligations in Abductive Logic Programming.- Using Rule-Based Reasoning for RDF Validation.- Three Methods for Revising Hybrid Knowledge Bases.- Can My Test Case Run on Your Test Plant? A Logic-Based Compliance Check and its Evaluation on Real Data.- Semantic DMN: Formalizing Decision Models with Domain Knowledge.- A set-theoretic approach to ABox reasoning services.- Verifying Controllability of Time-Aware Business Processes.- A Decidable Conuence Test for Cognitive Models in ACT-R.- On the Chase for All Provenance Paths With Existential Rules.- Rewriting Queries with Negated Atoms.- Fast ABox Consistency Checking using Incomplete Reasoning and Caching.- An Online Tool for Tuning Fuzzy Logic Programs.- Hybrid ASP-based Approach to Pattern Mining.- nconsistency-tolerant Instance Checking in Tractable Description Logics.- ArgQL: A Declarative Language for Querying Argumentative Dialogues.
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This book constitutes the proceedings of the International Joint Conference on Rules and Reasoning, RuleML+RR 2017, held in London, UK, during July 2017. This is the first conference of a new series, joining the efforts of two existing conference series, namely "RuleML" (International Web Rule Symposium) and "RR" (Web Reasoning and Rule Systems). The 16 regular papers presented together with 2 keynote abstracts were carefully reviewed and selected from 29 submissions. The RR conference series has been a forum for discussion and dissemination of new results on all topics concerning Web Reasoning and Rule Systems, with an emphasis on rule-based approaches and languages. The RuleML conference series has been devoted to disseminating research, applications, languages and standards for rule technologies, with attention to both theoretical and practical developments, to challenging new ideas and industrial applications. Both series of conferences aimed at building bridges between academia and industry in the field of rules and their applications. Therefore, RuleML+RR is expected to become a leading conference for all subjects concerning theoretical advances, novel technologies, and innovative applications about knowledge representation and reasoning with rules. This new joint conference provides a valuable forum for stimulating cooperation and cross-fertilization between the many different communities focused on the research, development and applications of rule-based systems. It provides the possibility to present and discuss applications of rules and reasoning in academia, industry, engineering, business, finance, healthcare and other application areas.
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• Invited papers.- Maximum likelihood estimation and coarse data.- Reasons and Means to Model Preferences as Incomplete.- Fuzzy Description Logics - A Survey.- Regular papers.- Using k-specificity for the management of count restrictions in flexible querying.- Comparing Machine Learning and Information Retrieval-based Approaches for Filtering Documents in a Parliamentary Setting.- Eliciting Implicit Evocations using Word Embeddings and Knowledge Representation.- K-nearest neighbour classification for interval-valued data.- Estimating Conditional Probabilities by Mixtures of Low Order Conditional Distributions.- Closed-Form Solutions in Learning Probabilistic Logic Programs by Exact Score Maximization.- Fault Tolerant Direct NAT Structure Extraction from Pairwise Causal Interaction Patterns.-The Altruistic Robot: do what I want, not just what I say.- Expressivity of possibilistic preference networks with constraints.- Assumption-Based Argumentation Equipped with Preferences and Constraints.- Semantic Change and Extension Enforcement in Abstract Argumentation.- Measuring Disagreement in Argumentation Graphs.- Belief in Attacks in Epistemic Probabilistic Argumentation.- A Parametrized Ranking-based Semantics for Persuasion.- A Probabilistic Programming Language for Influence Diagrams.- First-Order Typed Model Counting for Probabilistic Conditional Reasoning at Maximum Entropy.- Towards Statistical Reasoning in Description Logics over Finite Domains.- Bankruptcy Scenario Query: B-SQ.- A view of f-indexes of inclusion under different axiomatic definitions of fuzzy inclusion.- An integer 0-1 linear programming approach for computing inconsistency degree in product-based possibilistic DL-Lite.- A Semantic characterization for ASP base revision.- On Iterated Contraction: syntactic characterization, representation theorem and limitations of the Levi identity.- Handling Topical Metadata Regarding the Validity and Completeness of Multiple-Source Information: A possibilistic approach.- Aggregation of preferences on criteria importance expressed on various subsets by several decision makers.- Short papers.- Probabilistic local link prediction in complex networks.- A Fuzzy Ontology-based System for Gait Recognition using Kinect Sensor.- Evidential joint calibration of binary SVM classifiers using logistic regression.- Ad hoc metric for correspondences analysis between fuzzy partitions On Similarity-based Unfolding.- The Causality/Repair Connection in Databases: Causality-Programs. .
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This book constitutes the refereed proceedings of the 11th International Conference on Scalable Uncertainty Management, SUM 2017, which was held in Granada, Spain, in October 2017. The 24 full and 6 short papers presented in this volume were carefully reviewed and selected from 35 submissions. The book also contains 3 invited papers. Managing uncertainty and inconsistency has been extensively explored in Artificial Intelligence over a number of years. Now, with the advent of massive amounts of data and knowledge from distributed, heterogeneous, and potentially conflicting sources, there is interest in developing and applying formalisms for uncertainty and inconsistency in systems that need to better manage this data and knowledge. The International Conference on Scalable Uncertainty (SUM) aims to provide a forum for researchers who are working on uncertainty management, in different communities and with different uncertainty models, to meet and exchange ideas.
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• Search-Based Software Engineering.- Software testing.- Automated Program Repair.- Software Evolution.- Combinatorial Testing.- Software Requirements Analysis.- Software Configuration.- Multi-Objective Optimization.- Evolutionary computation.- Software Diversity.- Mutation Testing.
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This book constitutes the refereed proceedings of the 9th International Symposium on Search-Based Software Engineering, SSBSE 2017, held in Paderborn, Germany, in September 2017. The 7 full papers and 5 short papers presented together with 4 challenge track and 2 students student track papers were carefully reviewed and selected from 26 submissions. SSBSE welcomes not only applications from throughout the software engineering lifecycle but also a broad range of search methods ranging from exact Operational Research techniques to nature-inspired algorithms and simulated annealing.
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• Retrieval, Crawling and Fusion of Entity-centric Data on the Web.- Data Multiverse: The Uncertainty Challenge of Future Big Data Analytics.- Experiments with Document Retrieval from Small Text Collections using Latent Semantic Analysis or Term Similarity with Query Coordination and Automatic Relevance Feedback.- Unsupervised Extraction of Conceptual Keyphrases from Abstracts.- Back to the sketch-board: Integrating keyword search, semantics, and information retrieval.- Topic detection in multi-channel Italian newspapers.- Random Walks Analysis on Graph Modelled Multimodal Collections.- A software processing chain for evaluating thesaurus quality.- Comparison of Collaborative and Content-based Automatic Recommendation Approaches in a Digital Library of Serbian PhD Dissertations.- Keyword-based search on bilingual digital libraries.- Network-Enabled Keyword Extraction for Under-Resourced Languages.- Making sense of citations.- An Ontology-based Approach to Information Retrieval.- Game with a Purpose for Verification of Mappings Between Wikipedia and WordNet.- TB-Structure: Collective Intelligence for Exploratory Keyword Search.- Using Natural Language to Search Linked Data.- The Use of Semantics in the CrossCult H2020 Project.
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This book constitutes the thoroughly refereed post-conference proceedings of the Second COST Action IC1302 International KEYSTONE Conference on Semantic Keyword-Based Search on Structured Data Sources, IKC 2016, held in Cluj-Napoca, Romania, in September 2016. The 15 revised full papers and 2 invited papers are reviewed and selected from 18 initial submissions and cover the areas of keyword extraction, natural language searches, graph databases, information retrieval techniques for keyword search and document retrieval.
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• Research Track: Multi-Label Based Learning for Better Multi-Criteria Ranking of Ontology Reasoners.- The Efficacy of OWL and DL on User Understanding of Axioms and Their Entailments.- A Decidable Very Expressive Description Logic for Databases.- Improving Visual Relationship Detection using Semantic Modeling of Scene Descriptions.- An Empirical Study on How the Distribution of Ontologies Affects Reasoning on the Web.- Expressive Stream Reasoning with Laser.- Semantics and Validation of Shapes Schemas for RDF.- Temporal Query Answering in DL-Lite over Inconsistent Data.- Semantic Wide and Deep Learning for Detecting Crisis-Information Categories on Social Media.- Tractable Query Answering for Expressive Ontologies and Existential Rules.- Zooming in on Ontologies: Minimal Modules and Best Excerpts.- Global RDF Vector Space Embeddings.- LDScript: a Linked Data Script Language.- Practical Update Management in Ontology-based Data Access.- Computing Authoring Tests from Competency Questions: Experimental Validation.- Matching Web Tables with Knowledge Base Entities: From Entity Lookups to Entity Embeddings.- Learning Commonalities in SPARQL.- Meta Structures in Knowledge Graphs.- Challenges of source selection in the WoD.- AMUSE: Multilingual Semantic Parsing for Question Answering over Linked Data.- Computing FO-Rewritings in EL in Practice: from Atomic to Conjunctive Queries.- A Formal Framework for Comparing Linked Data Fragments.- Language-agnostic Relation Extraction from Wikipedia Abstracts.- Alignment Cubes: Towards Interactive Visual Exploration and Evaluation of Multiple Ontology Alignments.- Attributed Description Logics: Ontologies for Knowledge Graphs.- Reliable Granular References to Changing Linked Data.- Cost-Driven Ontology-Based Data Access.-The Odyssey Approach for Optimizing Federated SPARQL Queries.- Automated Fine-grained Trust Assessment in Federated Knowledge Bases.- Completeness-aware Rule Learning from Knowledge Graphs.- Entity Comparison in RDF Graphs.- Provenance Information in a Collaborative Knowledge Graph: an Evaluation of Wikidata External References.- Strider: A Hybrid Adaptive Distributed RDF Stream Processing Engine.- Mining Hypotheses from Data in OWL: Advanced Evaluation and Complete Construction.- Semantic Faceted Search with Aggregation and Recursion.- Investigating learnability, user performance, and preferences of the path query language SemwidgQL compared to SPARQL.- Cross-lingual Entity Alignment via Joint Attribute-Preserving Embedding.- Blockchain Enabled Privacy Audit Logs.- VICKEY: Mining Conditional Keys on RDF datasets.- Ontolex JeuxDeMots and Its Alignment to the Linguistic Linked Open Data Cloud.- Towards Holistic Concept Representations: Embedding Relational Knowledge, Visual Attributes, and Distributional Word Semantics.- An extension of SPARQL for expressing preferences.- Encoding Category Correlations into Bilingual Topic Modeling for Cross-Lingual Taxonomy Alignment.- Cross-lingual infobox alignment in Wikipedia using Entity-Attribute Factor Graph.
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The two-volume set LNCS 10587 + 10588 constitutes the refereed proceedings of the 16th International Semantic Web Conference, ISWC 2017, held in Vienna, Austria, in October 2017. ISWC 2017 is the premier international forum, for the Semantic Web / Linked Data Community. The total of 55 full and 21 short papers presented in this volume were carefully reviewed and selected from 300 submissions. They are organized according to the tracks that were held: Research Track; Resource Track; and In-Use Track.
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• Resource Track: Diefficiency Metrics: Measuring the Continuous Efficiency of Query Processing Approaches.- CodeOntology: RDF-ization of Source Code.- Linked Data Publication of Live Music Archives and Analysis.- The MedRed Ontology for Representing Clinical Data Acquisition Metadata.- Iguana : A Generic Framework for Benchmarking the Read-Write Performance of Triple Stores.- Ireland's Authoritative Geospatial Linked Data.- LOD-a-lot: A Queryable Dump of the LOD cloud.- IMGpedia: a Linked Dataset with Content-based Analysis of Wikimedia Images.- WIDOCO: A Wizard for Documenting Ontologies.- The CEDAR Workbench: An Ontology-Assisted Environment for Authoring Metadata that Describe Scientific Experiments.- WebIsALOD: Providing Hypernymy Relations extracted from the Web as Linked Open Data.- Ontology-Based Data Access to Slegge.- BiOnIC: A Catalog of User Interactions with Biomedical Ontologies.- Neural Embeddings for Populated Geonames Locations.- Distributed Semantic Analytics using the SANSA Stack.- The MIDI Linked Data Cloud.- SocialLink: Linking DBpedia Entities to Corresponding Twitter Accounts.- UNDO: the United Nations System Document Ontology.- One year of the OpenCitations Corpus - Releasing RDF-based scholarly citation data into the Public Domain.- An Entity Relatedness Test Dataset.- RSPLab, RDF Stream Processing Benchmarking made easy.- LC-QuAD: A Corpus for Complex Question Answering over Knowledge Graphs.- PDD Graph: Bridging Electronic Medical Records and Biomedical Knowledge Graphs via Entity Linking.- In-Use Track: A Controlled Crowdsourcing Platform for High-Quality Ontology Development and Data Annotation.- An Investigative Search Engine for the Human Trafficking Domain.- Lessons Learned in Building Linked Data for the American Art Collaborative.- Modeling and Using an Actor Ontology of Second World War Military Units and Personnel.- Sustainable Linked Data generation: the case of DBpedia.- Semantic Rule-Based Equipment Diagnostic.- Automatic Query-centric API for Routine Access to Linked Data.- Realizing an RDF-based Information Model for a Manufacturing Company - A Case Study.- Personalizing Actions in Context for Risk Management using Semantic Web Technologies.
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The two-volume set LNCS 10587 + 10588 constitutes the refereed proceedings of the 16th International Semantic Web Conference, ISWC 2017, held in Vienna, Austria, in October 2017. ISWC 2017 is the premier international forum, for the Semantic Web / Linked Data Community. The total of 55 full and 21 short papers presented in this volume were carefully reviewed and selected from 300 submissions. They are organized according to the tracks that were held: Research Track; Resource Track; and In-Use Track.
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• Intro
• Preface
• Organization
• Abstract of Keynotes
• Bringing Semantic Intelligence to Financial Markets
• Disrupting the Semantic Comfort Zone
• Semantic Web Technologies for Digital Archives
• Contents
• Part I
• Contents
• Part II
• Semantic Data Management, Big Data, and Scalability Track
• Traffic Analytics for Linked Data Publishers
• 1 Introduction
• 2 Related Work
• 3 System Overview
• 4 Traffic Metrics
• 4.1 Content Metrics Extraction
• 4.2 Protocol Metrics Extraction and SPARQL Queries Weight
• 4.3 Audience Metrics Extraction and Visitor Session Identification

• 5 Results
• 6 Conclusions and Future Work
• References
• Explaining Graph Navigational Queries
• 1 Introduction
• 2 Related Work
• 3 Building Query Explanations with GeL
• 3.1 Syntax of GeL
• 3.2 Semantics of GeL
• 4 Algorithms and Complexity
• 4.1 Translating GeL into SPARQL
• 5 Implementation and Evaluation
• 6 Concluding Remarks and Future Work
• References
• A SPARQL Extension for Generating RDF from Heterogeneous Formats
• 1 Introduction
• 2 Use-Cases and Requirements
• 3 Related Work
• 4 SPARQL-Generate Specification
• 4.1 SPARQL-Generate Concrete Syntax

• 4.2 Abstract Syntax
• 4.3 SPARQL-Generate Semantics
• 5 Implementation and Evaluation
• 5.1 Generic Approach
• 5.2 Implementation on Top of Apache Jena
• 5.3 Evaluation
• 6 Conclusion and Future Work
• References
• Linked Data Track
• Exploiting Source-Object Networks to Resolve Object Conflicts in Linked Data
• 1 Introduction
• 2 Preliminaries
• 2.1 Basic Definitions
• 2.2 Problem Analysis
• 3 ObResolution Method
• 3.1 Model Details
• 3.2 Inference Algorithms
• 3.3 Practical Issues
• 4 Evaluation
• 4.1 The Datasets
• 4.2 Comparative Methods and Metrics
• 4.3 Results

• 5 Related Work
• 6 Conclusion and Future Work
• References
• Methods for Intrinsic Evaluation of Links in the Web of Data
• 1 Introduction
• 2 Preliminaries
• 3 Principles for Data Interlinking in the Web of Data
• 4 Intrinsic Measures for Assessing the Quality of Links
• 4.1 Basic Descriptive Statistics
• 4.2 Principles-Based Measures
• 5 Empirical Analysis
• 5.1 Data
• 5.2 Methodology
• 5.3 Measure Validation
• 5.4 Results
• 6 Related Work
• 7 Conclusions and Future Work
• References
• Entity Deduplication on ScholarlyData
• 1 Introduction
• 2 Related Work
• 3 Deduplication

• 3.1 Blocking Strategies
• 3.2 Classification
• 3.3 URI Harmonisation
• 4 Experiments
• 4.1 The Train/test Dataset
• 4.2 Blocking
• 4.3 Classification
• 4.4 URI Harmonisation
• 5 Conclusions
• References
• Machine Learning Track
• WOMBAT
• A Generalization Approach for Automatic Link Discovery
• 1 Introduction
• 2 Preliminaries
• 3 Constructing and Traversing Link Specifications
• 3.1 Learning Atomic Specifications
• 3.2 Combining Atomic Specifications
• 4 The WOMBAT Algorithm
• 5 Evaluation
• 6 Related Work
• 7 Conclusions and Future Work
• References

The two volumes LNCS 10249 and 10250 constitute the refereed proceedings of the 14th International Semantic Web Conference, ESWC 2017, held in Portoroz, Slovenia. The 51 revised full papers presented were carefully reviewed and selected from 183 submissions. In addition, 10 PhD papers are included, selected out of 14 submissions. The papers are organized in the following tracks: semantic data management, big data, and scalability; linked data; machine learning; mobile web, sensors, and semantic streams; natural language processing and information retrieval; vocabularies, schemas, and ontologies; reasoning; social web and web science; semantic web and transparency; in use and industrial track; and PhD symposium. The paper 'Linked Data Notifications: A Resource-Centric Communication Protocol' is published open access under a CC BY 4.0 license at link.springer.com. .
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The two volumes LNCS 10249 and 10250 constitute the refereed proceedings of the 14th International Semantic Web Conference, ESWC 2017, held in Portoroz, Slovenia. The 51 revised full papers presented were carefully reviewed and selected from 183 submissions. In addition, 10 PhD papers are included, selected out of 14 submissions. The papers are organized in the following tracks: semantic data management, big data, and scalability; linked data; machine learning; mobile web, sensors, and semantic streams; natural language processing and information retrieval; vocabularies, schemas, and ontologies; reasoning; social web and web science; semantic web and transparency; in use and industrial track; and PhD symposium.
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• Vehicle Navigation Systems.- Localization and Mapping.- Path Planning.- Sensing and Tracking Systems.- Identification and Motion Control of Robotic Vehicles.- Coordinated and Cooperative Control of Multi-Vehicle Systems.
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This edited volume includes thoroughly collected on sensing and control for autonomous vehicles. Guidance, navigation and motion control systems for autonomous vehicles are increasingly important in land-based, marine and aerial operations. Autonomous underwater vehicles may be used for pipeline inspection, light intervention work, underwater survey and collection of oceanographic/biological data. Autonomous unmanned aerial systems can be used in a large number of applications such as inspection, monitoring, data collection, surveillance, etc. At present, vehicles operate with limited autonomy and a minimum of intelligence. There is a growing interest for cooperative and coordinated multi-vehicle systems, real-time re-planning, robust autonomous navigation systems and robust autonomous control of vehicles. Unmanned vehicles with high levels of autonomy may be used for safe and efficient collection of environmental data, for assimilation of climate and environmental models and to complement global satellite systems. The target audience primarily comprises research experts in the field of control theory, but the book may also be beneficial for graduate students. .
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• 1 High availability cloud manufacturing system integrating distributed MES agents.- 2Classification of cyber-physical systems developments: proposition of an analysis framework.- 3Formal Modelling of Distributed Automation CPS with CP-Agnostic Software.- 4Industrial Cyber Physical Systems Supported by Distributed Advanced Data Analytics.- 5 Gap analysis on Research and Innovation for Cyber-Physical Systems in Manufacturing.- 6 Redundant and Decentralised Directory Facilitator for Resilient Plug and Produce Cyber Physical Production Systems.- 7 Multi-Agent Systems for Industry and Service.- 8 A Self-Organisation Model for Mobile Robots in Large Structure Assembly using Multi-Agent Systems.- 9 Specifying Self-organising Logistics System: openness, intelligence, and decentralised control .- 10 A Generic Reconfigurable and Pluggable Material Handling System based on Genetic Algorithm.- 11 Smart condition based maintenance for a fleet of mobile entities.
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The book offers an integrated vision on Cloud and HPC, Big Data, Analytics and virtualization in computing-oriented manufacturing, combining information and communication technologies, service-oriented control of holonic architectures as well as enterprise integration solutions based on SOA principles. It is structured in eight parts, each one grouping research and trends in digital manufacturing and service oriented manufacturing control: Cloud and Cyber-Physical Systems for Smart Manufacturing, Reconfigurable and Self-organized Multi-Agent Systems for Industry and Service, Sustainability Issues in Intelligent Manufacturing Systems, Holonic and Multi-agent System Design for Industry and Service, Should Intelligent Manufacturing Systems be Dependable and Safe?, Service-oriented Management and Control of Manufacturing Systems, Engineering and Human Integration in Flexible and Reconfigurable Industrial Systems, Virtualization and Simulation in Computing-oriented Industry and Service.p>.
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• Adaptive Service-oriented and Cloud Applications.- IoT Systems Provisioning and Management in Cloud Computing.- Big Data Services and Computational Intelligence.- PhD Symposium.- Demonstration.
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This book constitutes the revised selected papers of the scientific satellite events that were held in conjunction with the 14th International Conference on Service-Oriented Computing, ICSOC 2016, held in Banff, AB, Canada, in October 2016. The ICSOC 2016 workshop track consisted of three workshops on a wide range of topics that fall into the general area of service computing: ASOCA 2016: The rst Workshop on Adaptive Service-oriented and Cloud Applications ISyCC 2016: The rst Workshop on IoT Systems Provisioning & Management in Cloud Computing BSCI 2016: The Second International Workshop on Big Data Services and Computational Intelligence.
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This book constitutes the refereed proceedings of the 10th International Conference on Similarity Search and Applications, SISAP 2017, held in Munich, Germany, in October 2017. The 23 full papers presented were carefully reviewed and selected from 53 submissions. The papers deal with issues surrounding the theory, design, analysis, practice, and application of content-based and feature-based similarity search. They are organized in the following topical sections: approximate similarity search; improving similarity search methods and applications; distances for complex objects; outlier detection; indexing and applications; and applications and specific domains. The paper 'A New Perspective on the Tree Edit Distance' is published open access under a CC BY 4.0 license at link.springer.com.
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• Evolutionary Optimisation.- Maximum Likelihood Estimation based on Random Subspace EDA: Application to Extrasolar Planet Detection.- Evolutionary Games Network Reconstruction by Memetic Algorithm with l1/2 Regularization.- A Simple Brain Storm Optimization Algorithm via Visualizing Confidence Intervals.- Simulated Annealing with a Time-slot Heuristic for Ready-mix Concrete Delivery.- A Sequential Learnable Evolutionary Algorithm with a Novel Knowledge Base Generation Method.- Using Parallel Strategies to Speed Up Pareto Local Search.- Differential evolution based hyper-heuristic for the flexible job-shop scheduling problem with fuzzy processing time.- ACO-iRBA: A Hybrid Approach to TSPN with Overlapping Neighborhoods.- An Evolutionary Algorithm with A New Coding Scheme for Multi-objective Portfolio Optimization.- Exact Approaches for the Travelling Thief Problem.- On the Use of Dynamic Reference Points in HypE.- Multi-Factorial Evolutionary Algorithm Based on M2M Decomposition.- An Efficient Local Search Algorithm for Minimum Weighted Vertex Cover on Massive Graphs.- Interactive Genetic Algorithm with Group Intelligence Articulated Possibilistic Condition Preference Model.- GP-Based Approach to Comprehensive Quality-Aware Automated Semantic Web Service Composition.- Matrix Factorization based Benchmark Set Analysis: A Case Study on HyFlex.-Learning to Describe Collective Search Behavior of Evolutionary Algorithms in Solution Space.- Evolutionary Multiobjective Optimisation.- A Hierarchical Decomposition-based Evolutionary Many-objective Algorithm.- Adjusting Parallel Coordinates for Investigating Multi-Objective Search.- An Elite Archive-based MOEA/D Algorithm.- A constraint partitioning method based on minimax strategy for constrained multiobjective optimization problems.- A Fast Objective Reduction Algorithm based on Dominance Structure for Many Objective Optimization.- A memetic algorithm based on decomposition and extended search for Multi-Objective Capacitated Arc Routing Problem.- Improvement of reference points for decomposition based multi-objective evolutionary algorithms.- Multi-Objective Evolutionary Optimization for Autonomous Intersection Management.- Study of an adaptive control of aggregate functions in MOEA/D.- Use of Inverted Triangular Weight Vectors in Decomposition-Based Many-Objective Algorithms.- Surrogate Model Assisted Multi-Objective Differential Evolution Algorithm for Performance Optimization at Software Architecture Level.- Normalized Ranking Based Particle Swarm Optimizer for Many Objective Optimization.- Evolutionary Machine Learning.- A Study on Pre-Training Deep Neural Networks Using Particle Swarm Optimisation.- Simple Linkage Identification Using Genetic Clustering.- Learning of Sparse Fuzzy Cognitive Maps Using Evolutionary Algorithm with Lasso Initialization.- A Bayesian Restarting Approach to Algorithm Selection.- Evolutionary Learning based Iterated Local Search for Google Machine Reassignment Problems.- Geometric Semantic Genetic Programming with Perpendicular Crossover and Random Segment Mutation for Symbolic Regression.- Constrained Dimensionally Aware Genetic Programming for Evolving Interpretable Dispatching Rules in Dynamic Job Shop Scheduling.- Visualisation and Optimisation of Learning Classifier Systems for Multiple Domain Learning.- Adaptive Memetic Algorithm Based Evolutionary Multi-tasking Single-objective Optimization.- Effective Policy Gradient Search for Reinforcement Learning through NEAT based Feature Extraction.- Generalized Hybrid Evolutionary Algorithm Framework with a Mutation Operator Requiring no Adaptation.- A Multitree Genetic Programming Representation for Automatically Evolving Texture Image Descriptors.- Theoretical Developments.- Running-time Analysis of Particle Swarm Optimization with a Single Particle Based on Average Gain.- Evolutionary Computation Theory for Remote Sensing Image Clustering: A Survey.- Feature Selection and Dimensionality Reduction.- New Representations in Genetic Programming for Feature Construction in k-means Clustering.- Transductive Transfer Learning in Genetic Programming for Document Classification.- Automatic Feature Construction for Network Intrusion Detection.- A Feature Subset Evaluation Method based on Multi-objective Optimization.- A Hybrid GA-GP Method for Feature Reduction in Classification.- Kernel Construction and Feature Subset Selection in Support Vector Machines.- KW-Race and Fast KW-Race: Racing-based Frameworks for Tuning Parameters of Evolutionary Algorithms on Black-box Optimization Problems.- Dynamic and Uncertain Environments.- A Probabilistic Learning Algorithm for the Shortest Path Problem.- A first-order difference model-based evolutionary dynamic multiobjective optimization.- A Construction Graph-based Evolutionary Algorithm For Traveling Salesman Problem.- Real-world Applications.- Bi-objective water cycle algorithm for solving remanufacturing rescheduling problem.- A New Method for Constructing Ensemble Classifier in Privacy-Preserving Distributed Environment.- Greedy based Pareto Local Search for Bi-objective Robust Airport Gate Assignment Problem.- Multi-neighbourhood Great Deluge for Google Machine Reassignment Problem.- Evolutionary Optimization of Airport Security Inspection Allocation.- Evolving Directional Changes Trading Strategies with a New Event-based Indicator.- Constrained Differential Evolution for Cost and Energy Efficiency Optimization in 5G Wireless Networks.- Evolutionary Computation to Determine Product Builds in Open Pit Mining.- An Evolutionary Vulnerability Detection Method for HFSWR Ship Tracking Algorithm.- Genetic Programming for Lifetime Maximization in Wireless Sensor Networks with Mobile Sink.- Unsupervised Change Detection for Remote Sensing Images Based on Principal Component Analysis and Differential Evolution.- Parallel particle swarm optimization for community detection in large-scale networks.- Multi-objective memetic algorithm based on three-dimentional request prediction for dynamic pickup-and-delivery problem with time windows.- Optimization of Spectrum-Energy Efficiency in Heterogeneous Communication Network.- Large scale WSN deployment based on an improved cooperative coevolutionary PSO with global differential grouping.- Adaptive Systems.- Learning Fuzzy Cognitive Maps Using a Genetic Algorithm with Decision-making Trial and Evaluation.- Dynamic and Adaptive Threshold for DNN Compression from Scratch.- Cooperative Design of Two Level Fuzzy Logic Controllers for Medium Access Control in Wireless Body Area Networks.- Statistical Analysis of Social Coding in GitHub Hypernetwork.- Swarm Intelligence.- Sparse Restricted Boltzmann Machine Based on Multiobjective Optimization.- A Knee Point Driven Particle Swarm Optimization Algorithm for Sparse Reconstruction.- Multivariant optimization algorithm with bimodal-gauss.- Enhanced Comprehensive Learning Particle Swarm Optimization with Exemplar Evolution.- Recommending PSO variants using meta-learning framework for global optimization.- Augmented Brain Storm Optimization with Mutation Strategies.- A new precedence-based Ant Colony Optimization for permutation problems.- A general swarm intelligence model for continuous function optimization.- A Hybrid Particle Swarm Optimization for High-Dimensional Dynamic Optimization.- Visualizing the Search Dynamics in a High-dimensional Space for a Particle Swarm Optimizer.- Particle Swarm Optimization with Winning Score Assignment for Multi-objective Portfolio Optimization.- Conservatism and Adventurism in Particle Swarm Optimization Algorithm.- A competitive social spider optimization with learning strategy for PID controller optimization. .
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 11th International Conference on Simulated Evolution and Learning, SEAL 2017, held in Shenzhen, China, in November 2017. The 85 papers presented in this volume were carefully reviewed and selected from 145 submissions. They were organized in topical sections named: evolutionary optimisation; evolutionary multiobjective optimisation; evolutionary machine learning; theoretical developments; feature selection and dimensionality reduction; dynamic and uncertain environments; real-world applications; adaptive systems; and swarm intelligence.
(source: Nielsen Book Data)

This book constitutes the refereed proceedings of the Second International Workshop on Simulation and Synthesis in Medical Imaging, held in conjunction with MICCAI 2017, in Quebec City, Canada, in September 2017. The 11 revised full papers presented were carefully reviewed and selected from 14 submissions. The contributions span the following broad categories: cross modality (PET/MR, PET/CT, CT/MR, etc.) image synthesis, simulation and synthesis from large-scale image databases, automated techniques for quality assessment images, and several applications of image synthesis and simulation in medical imaging such as image interpolation and segmentation, image reconstruction, cell imaging, and blood flow.
(source: Nielsen Book Data)

• A Robust and Lightweight Protocol over Long Range (LoRa) Technology for Applications in Smart Cities.- A sustainable bi-objective approach for the minimum latency problem.- Cities as Enterprises: A comparison of Smart City Frameworks based on Enterprise Architecture requirements.- Comparative study of artificial neural network models for forecasting the indoor temperature in smart buildings.- Considering Congestion Costs and Driver Behaviour into Route Optimisation Algorithms in Smart Cities.- Distributed Genetic Algorithms on Portable Devices for Smart Cities.- Existing approaches to smart parking: An overview.- Impact of protests in the number of smart devices in streets: A new approach to analyze protesters behavior.- Logistics Support Approach for drone delivery.- Policy Recommendations Supporting Smart City Strategies: Towards a New Methodological Tool.- Predicting Car Park Occupancy Rates in Smart Cities.- Predicting Individual Trip Destinations With Artificial Potential Fields.- Robust Bi-objective Shortest Path Problem in Real Road Networks.- Smart urban mobility from expert stakeholders' narratives.- Simulation Model of Trafic in Smart Cities for Decision-Making Support: Case Study in Tudela (Navarre, Spain).- Virtual Development of a Presence Sensor Network Using 3D Simulations.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the second International Conference on Smart Cities, Smart-CT 2017, held in Malaga, Spain, in June 2017. The 16 papers presented in this volume were carefully reviewed and selected from 21 submissions. The topics covered include studies and tools to improve road traffic, energy consumption, logistics, frameworks to provide new services and take decisions in a holistic way, driving assistance, electric vehicles, public transport, and surveys on smart city concepts.
(source: Nielsen Book Data)

• Behavioral and social sciences ; Inferring follower preferences in the 2016 U.S. presidential primaries with sparse learning / Yu Wang, Yang Feng, Xiyang Zhang, and Jiebo Luo
• Detection and analysis of 2016 US presidential election related rumors on twitter / Zhiwei Jin, Juan Cao, Han Guo, Yongdong Zhang, Yu Wang, and Jiebo Luo
• How emotional support and informational support relate to linguistic alignment / Yafei Wang, David Reitter, and John Yen
• Gender politics in the 2016 U.S. presidential election : a computer vision approach / Yu Wang, Yang Feng, and Jiebo Luo
• Agent-based modeling approach in understanding behavior during disasters : measuring response and rescue in 'eBayanihan' disaster management platform / Maria Regina Justina E. Estuar, Rey C. Rodrigueza, John Noel C. Victorino, Marcella Claudette V. Sevilla, Marlene M. De Leon, and John Clifford S. Rosales
• An agent-based model of posting behavior during times of societal unrest / Krishna C. Bathina, Aruna Jammalamadaka, Jiejun Xu, and Tsai-Ching Lu
• 'They all look the same to me.' An agent based simulation of out-group homogeneity / Ansgar E. Depping, Nathaniel Osgood, and Kurt Kreuger
• Cultural dimension theory based simulations for US army personnel / Brian An, Donald E. Brown, Riannon Hazell, and Peter Grazaitis
• Socio-cultural cognitive mapping / Geoffrey P. Morgan, Joel Levine, and Kathleen M. Carley

• Cyber and intelligence applications ; A cognitive model of feature selection and categorization for autonomous systems / Michael Martin, Christian Lebiere, Maryanne Fields, and Craig Lennon
• ENWalk : learning network features for spam detection in Twitter / K. C. Santosh, Suman Kalyan Maity, and Arjun Mukherjee
• Understanding Russian information operations using unsupervised multilingual topic modeling / Peter A. Chew and Jessica G. Turnley
• Social cyber forensics approach to study Twitter's and blogs' influence on propaganda campaigns / Samer Al-khateeb, Muhammad Nihal Hussain, and Nitin Agarwal
• From cyber space opinion leaders and the diffusion of anti-vaccine extremism to physical space disease outbreaks / Xiaoyi Yuan and Andrew Crooks
• Event-based model simulating the change in DDoS attack trends after P/DIME events / Adam Tse and Kathleen M. Carley
• Using a real-time cybersecurity exercise case study to understand temporal characteristics of cyberattacks / Aunshul Rege, Zoran Obradovic, Nima Asadi, Edward Parker, Nicholas Masceri, Brian Singer, and Rohan Pandit
• Hybrid modeling of cyber adversary behavior / Amy Sliva, Sean Guarino, Peter Weyhrauch, Peter Galvin, Daniel Mitchell, Joseph Campolongo, and Jason Taylor
• Cyber-FIT : an agent-based modelling approach to simulating cyber warfare / Geoffrey B. Dobson and Kathleen M. Carley

• Information, systems, and network sciences ; Large-scale sleep condition analysis using selfies from social media / Xuefeng Peng, Jiebo Luo, Catherine Glenn, Jingyao Zhan, and Yuhan Liu
• Modeling the co-evolution of culture, signs and network structure / Peter Revay and Claudio Cioffi-Revilla
• Simulating population behavior : transportation mode, green technology, and climate change / Nasrin Khansari, John B. Waldt, Barry G. Silverman, Willian W. Braham, Karen Shen, and Jae Min Lee
• A parametric study of opinion progression in a divided society / Farshad Salimi Naneh Karan and Subhadeep Chakraborty
• Integrating simulation and signal processing with stochastic social kinetic model / Fan Yang and Wen Dong
• Learning network dynamics from Tumblr® : a search for influential users / Steven Munn, Kang-Yu Ni, and Jiejun Xu
• Modeling the impact of protraction on refugee identity / Erika Frydenlund and José J. Padilla
• Linking Twitter sentiment and event data to monitor public opinion of geopolitical developments and trends / Lucas A. Overbey, Scott C. Batson, Jamie Lyle, Christopher Williams, Robert Regal, and Lakeisha Williams
• Identifying smoking from smartphone sensor data and multivariate hidden Markov models / Yang Qin, Weicheng Qian, Narjes Shojaati, and Nathaniel Osgood
• Is word adoption a grassroots process? An analysis of Reddit communities / Jeremy R. Cole, Moojan Ghafurian, and David Reitter
• Understanding discourse acts : political campaign messages classification on Facebook and Twitter / Feifei Zhang, Jennifer Stromer-Galley, Sikana Tanupabrungsun, Yatish Hegde, Nancy McCracken, and Jeff Hemsley
• Improving the efficiency of allocating crowd donations with agent-based simulation model / Chi-Hsien Yen, Yi-Chieh Lee, and Wai-Tat Fu
• Temporal analysis of influence to predict users' adoption in online social networks / Ericsson Marin, Ruocheng Guo, and Paulo Shakarian
• Ideology detection for Twitter users via link analysis / Yupeng Gu, Ting Chen, Yizhou Sun, and Bingyu Wang

• Methodology ; Spread of pathogens in the patient transfer network of US hospitals / Juan Fernández-Gracia, Jukka-Pekka Onnela, Michael L. Barnett, Víctor M. Eguíluz, and Nicholas A. Christakis
• On predicting geolocation of Tweets using convolutional neural networks / Binxuan Huang and Kathleen M. Carley
• Stigmergy-based modeling to discover urban activity patterns from positioning data / Antonio Luca Alfeo, Mario Giovanni C. A. Cimino, Sara Egidi, Bruno Lepri, Alex Pentland, and Gigliola Vaglini
• Prospective detection of foodborne illness outbreaks using machine learning approaches / Aydin Teyhouee, Sara McPhee-Knowles, Chryl Waldner, and Nathaniel Osgood
• Mitigating the risks of financial exclusion : predicting illiteracy with standard mobile phone logs / Pål Sundsøy
• Multi-layer network composition under a unified dynamical process / Xiaoran Yan, Shang-Hua Teng, and Kristina Lerman
• Extracting information from negative interactions in multiplex networks using mutual information / Alireza Hajibagheri, Gita Sukthankar, and Kiran Lakkaraju
• A blockchain-enabled participatory decision support framework / Marek Laskowski
• Hyperparameter optimization for predicting the tolerance level of religious discourse / Donald E. Brown, Hope McIntyre, Peter J. Grazaitis, Riannon M. Hazell, and Nicholas Venuti
• APART : automatic political actor recommendation in real-time / Mohiuddin Solaimani, Sayeed Salam, Latifur Khan, Patrick T. Brandt, and Vito D'Orazio
• Measuring perceived causal relationships between narrative events with a crowdsourcing application on Mturk / Dian Hu and David A. Broniatowski.

This book constitutes the refereed proceedings of the 10th International Conference on Social, Cultural, and Behavioral Modeling & Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2017, held in Washington, DC, USA, in July 2017.The 16 full papers and 27 short papers presented were carefully reviewed and selected from 79 submissions. Owing to its strong multi-disciplinary heritage, the papers represent a large range of disciplines including computer science, psychology, sociology, communication science, public health, bioinformatics, political science, and organizational science and use numerous types of computational methods such as machine learning, language technology, social network analysis and visualization, agent-based simulation, and statistics. They are organized in the following topical sections: behavioral and social sciences; cyber and intelligence applications; information, systems, and network sciences; and methodology.
(source: Nielsen Book Data)

• Economics, science of success, and education.- Network science.- News, misinformation, and collective sensemaking.- Opinions, behavior, and social media mining.- Proximity, location, mobility, and urban analytics.- Security, privacy, and trust.- Tools and methods.- Health and behaviour.
• (source: Nielsen Book Data)

The two-volume set LNCS 10539 and 10540 constitutes the proceedings of the 9th International Conference on Social Informatics, SocInfo 2017, held in Oxford, UK, in September 2017.The 37 full papers and 43 poster papers presented in this volume were carefully reviewed and selected from 142 submissions. The papers are organized in topical sections named: economics, science of success, and education; network science; news, misinformation, and collective sensemaking; opinions, behavior, and social media mining; proximity, location, mobility, and urban analytics; security, privacy, and trust; tools and methods; and health and behaviour.
(source: Nielsen Book Data)

• Economics, science of success, and education.- Network science.- News, misinformation, and collective sensemaking.- Opinions, behavior, and social media mining.- Proximity, location, mobility, and urban analytics.- Security, privacy, and trust.- Tools and methods.- Health and behaviour.
• (source: Nielsen Book Data)

The two-volume set LNCS 10539 and 10540 constitutes the proceedings of the 9th International Conference on Social Informatics, SocInfo 2017, held in Oxford, UK, in September 2017. The 37 full papers and 43 poster papers presented in this volume were carefully reviewed and selected from 142 submissions. The papers are organized in topical sections named: economics, science of success, and education; network science; news, misinformation, and collective sensemaking; opinions, behavior, and social media mining; proximity, location, mobility, and urban analytics; security, privacy, and trust; tools and methods; and health and behaviour.
(source: Nielsen Book Data)

• Dependable and Optimal Cyber-Physical Systems.- Verifying Parametric Thread Creation.- Network Constructors: A Model for Programmable Matter.- Logical characterisations and compositionality of input-output conformance simulation.- A Linear-Time Branching-Time Spectrum of Behavioral Specification Theories.- Symbolic semantics for multiparty interactions in the link-calculus.- Different Speeds Suffice for Rendezvous of Two Agents on Arbitrary Graphs.- Deciding structural liveness of Petri nets.- Distributed Network Generation based on Preferential Attachment in ABS.- Completeness of Hoare Logic Relative to the Standard Model.- Configuration- and Residual-Based Transition Systems for Event Structures with Asymmetric Conflict.- Hardness of deriving invertible sequences from finite state machines.- A Graph-theoretical Characterisation of State Separation.- Selfish Transportation Games.- Decomposable Relaxation for Concurrent Data Structures.- Sufficient Conditions for a Connected Graph to have a Hamiltonian Path.- Enumerating Minimal Tropical Connected Sets.- Bamboo Garden Trimming Problem (Perpetual maintenance of machines with different attendance urgency factors).- Exact quantum query complexity of EXACT_{k, l}^n.- Adjacent vertices can be hard to find by quantum walks.- Matrix semigroup freeness problems in SL(2, Z).- Order-preserving 1-string representations of planar graphs.- How to Draw a Planarization.- Finding Largest Common Substructures of Molecules in Quadratic Time.- Lower Bounds for On-line Interval Coloring with Vector and Cardinality Constraints.- Parameterized and Exact Algorithms for Class Domination Coloring.- The Approximability of Partial Vertex Covers in Trees.- Longest Common Subsequence in at Least k Length Order-isomorphic Substrings.- Computing longest single-arm-gapped palindromes in a string.- Edit-Distance between Visibly Pushdown Languages.- Trends and Challenges in Predictive Analytics.- Model-driven Development in Practice: From Requirements to Code.- Webpage Menu Detection Based on DOM.- A Hybrid Model for Linking Multiple Social Identities across Heterogeneous Online Social Networks.- Eco Data Warehouse Design Through Logical Variability.- On Featured Transition Systems.- Domain-Specific Languages: A Systematic Mapping Study.- Characterising Malicious Software with High-Level Behavioural Patterns.- AErlang at work.- Software Systems Migration towards Cloud-native Architectures for SME-sized Software Vendors.- Using n-grams for the Automated Clustering of Structural Models.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 43rd International Conference on Current Trends in Theory and Practice of Computer Science, SOFSEM 2017, held in Limerick, Ireland, in January 2017. The 34 papers presented in this volume were carefully reviewed and selected from 41 submissions. They were organized in topical sections named: foundations in computer science; semantics, specification and compositionality; theory of mobile and distributed systems; verification and automated system analysis; petri nets, games and relaxed data structures; graph theory and scheduling algorithms; quantum and matrix algorithms; planar and molecular graphs; coloring and vertex covers; algorithms for strings and formal languages; data, information and knowledge engineering; and software engineering: methods, tools, applications.
(source: Nielsen Book Data)

• Optimal Group Decision Making Can Help Decrease Poverty, Inequality, and Discrimination.- An Overview and Re-Interpretation of Paradoxes of Responsiveness.- Veto in Yes-no and Yes-no-abstain Voting Systems.- Power Indices for Finance.- The binomial decomposition of the single parameter family of GB welfare functions.- The logic of information and processes in the system-of-systems applications.- Decision-making Process using Hyperstructures and Fuzzy Structures in the Social Sciences.- Social Preferences through Riesz Spaces: A First Approach.- Coherent conditional plausibility: a tool for handling fuzziness and uncertainty under partial information.- Intuitionistic fuzzy interpretations of some formulas for estimation of preference degree.- Fuzzified Likert Scales in Group Multiple-criteria Evaluation.- Maximal Entropy and Minimal Variability OWA Operator Weights: A Short Survey of Recent Developments.
• (source: Nielsen Book Data)

This book offers a concise introduction and comprehensive overview of the state of the art in the field of decision-making and consensus modeling, with a special emphasis on fuzzy methods. It consists of a collection of authoritative contributions reporting on the decision-making process from different perspectives: from psychology to social and political sciences, from decision sciences to data mining, and from computational sciences in general, to artificial and computational intelligence and systems. Written as a homage to Mario Fedrizzi for his scholarly achievements, creative ideas and long lasting services to different scientific communities, it introduces key theoretical concepts, describes new models and methods, and discusses a range of promising real-world applications in the field of decision-making science. It is a timely reference guide and a source of inspiration for advanced students and researchers.
(source: Nielsen Book Data)

• A Review of Soft Computing Techniques in Maritime Logistics and its Related Fields.- Intelligent Data Analysis, Soft Computing and Imperfect Data.- Soft Computing Methods in Transport and Logistics.- Applications of Soft Computing in Intelligent Transportation Systems.- Fuzzy Cognitive Maps based Models for Pattern Classification: Advances and Challenges.- A proposal of on-line detection of new faults and automatic learning in fault diagnosis.- Fuzzy Portfolio Selection Models for dealing with Investor's Preferences.- Gradual numbers and fuzzy solutions to fuzzy optimization problems.- A modal account of preference in a fuzzy setting.- The single parameter family of Gini Bonferroni welfare functions and the binomial decomposition, transfer sensitivity and positional transfer sensitivity.
• (source: Nielsen Book Data)

This book offers a timely snapshot of current soft-computing research and solutions to decision-making and optimization problems, which are ubiquitous in the current social and technological context, addressing fields including logistics, transportation and data analysis. Written by leading international experts from the United States, Brazil and Cuba, as well as the United Kingdom, France, Finland and Spain, it discusses theoretical developments in and practical applications of soft computing in fields where these methods are crucial to obtaining better models, including: intelligent transportation systems, maritime logistics, portfolio selection, decision- making, fuzzy cognitive maps, and fault detection. The book is dedicated to Professor Jose L. Verdegay, a pioneer who has been actively pursuing research in fuzzy sets theory and soft computing since 1982, in honor of his 65th birthday.
(source: Nielsen Book Data)

• Soft Computing techniques and Sustainability Science, an introduction.- Vessels Fuel Consumption: a Data Analytics Perspective to Sustainability.- FuzzyCovering: a Spatial Decision Support System for solving fuzzy covering location problems.- A Fuzzy Location Problem based upon Georeferenced Data.- A review of the application to emergent subfields in viticulture of local reflectance and interactance spectroscopy combined with soft computing and multivariate analysis.- Consumer segmentation through multi-instance clustering time-series energy data from smart meters.- A multicriteria group decision model for ranking technology packages in agriculture.- A Linguistic 2-tuple based Environmental Impact Assessment for Maritime Port Projects: Application to Moa Port. .
• (source: Nielsen Book Data)

This book offers a timely snapshot of soft computing methodologies and their applications to various problems related to sustainability, including electric energy consumption; fault diagnosis; vessel fuel consumption; determining the best sites for new malls; maritime port projects; and ad-hoc vehicular networks. Further, it demonstrates how metaheuristics and machine learning methods, fuzzy linear programming, neural networks, computing with words, linguistic models and other soft computing methods can be efficiently used to solve real-world problems. Intended as a practice-oriented guide for students, researchers, and professionals working at the interface between computer science, industrial engineering, naval engineering, agriculture, and sustainable development / climate change research, it provides readers with a set of intelligent solutions, helping them answer a range of emerging questions related to sustainability. .
(source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 15th International Conference on Software Engineering and Formal Methods, SEFM 2017, held in Trento, Italy, in September 2017. The 17 full papers and 6 short papers presented were carefully reviewed and selected from 102 submissions. The papers deal with a large range of topics in the following research areas: new frontiers in software architecture; software verification and testing; software development methods; application and technology transfer; security and safety; and design principles. .
(source: Nielsen Book Data)

• Sequence Classification based on Active Learning.- Using MongoDB Databases For Training and Combining Intrusion Detection Datasets.- Service Oriented Network Management with Knowledge-Based Network Management System in Fluctuating Environment.- A Topic Structuration Method on Time Series for a Meeting from Text Data.- Joint Embedding of Hierarchical Structure and Context for Entity Disambiguation.- Automatic Optimization of OpenCL-Based Stencil Codes for FPGAs.- Should Duration and Team Size be Used for Effort Estimation?.- A Lifelog Data Portfolio for Privacy Protection based on Dynamic Data Attributes in a Lifelog Service.- Estimation of Emotional Scene from Lifelog Videos in Consideration of Intensity of Various Facial Expressions.- Developing a Framework to Support Designing of Active Learning Class.- Where Do Drivers Look When Driving in a Foreign Country?.- On Password Strength: A Survey and Analysis.- Probabilistic Model-Based Multistep Crossover Considering Dependency between Nodes in Tree Optimization.- Digital Watermark Design for Two-dimensional Codes Displayed on Smart Phone Screen Using Multi-Objective Optimization and Optical Simulation.
• (source: Nielsen Book Data)

This book gathers 14 of the most promising papers presented at the 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2017), which was held on June 26-28, 2017 in Kanazawa, Japan. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the various fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. The book presents research findings concerning all aspects (theory, applications and tools) of computer and information science, and discusses the practical challenges encountered along the way, as well as the solutions adopted to solve them.
(source: Nielsen Book Data)

• Modeling and specification.- Safety and security.- Fault tolerance, resilience and robustness software.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the International Workshop on Software Engineering for Resilient Systems, SERENE 2017, held in Geneva; Switzerland, in September 2017. The 11 papers presented together with 2 invited talks were carefully reviewed and selected from 16 submissions. They cover the following areas: modeling and specification; safety and security; fault tolerance, resilience and robustness software.
(source: Nielsen Book Data)

• Agile Web Development Methodologies: A Survey and Evaluation.- Load Experiment of the vDACS Scheme in case of Increasing the simultaneous connection for the DACS SV.- Blind Channel Estimation Using Novel Independent Component Analysis with Pulse Shaping for Interference Cancellation.- Anticipated Test Design and its Application to Evaluate and Select Embedded Libraries.- Improving Web Application Reliablilty and Testing Using Accurate Usage Models.- C-PLAD-SM: Extending Component Requirements with Use Cases and State Machines.- A Structural Rule-Based Approach for Design Patterns Recovery.- DRSS: Distributed RDF SPARQL Streaming.- An Efficient Approach for Real-Time Processing of RDSZ-Based Compressed RDF Streams.- Energy Efficiency Cluster Head Election Using Fuzzy Logic Method for Wireless Sensor Networks.- Enabling GSD Task Allocation via Cloud-based Software Processes.- Composite Event Handling over a Distributed Event-Based System.
• (source: Nielsen Book Data)

This book gathers 12 of the most promising papers presented at the 15th International Conference on Software Engineering, Artificial Intelligence Research, Management and Applications (SERA 2017) held on June 7-9, 2017 at the University of Greenwich, London, UK. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science, to share their experiences and to exchange new ideas and information in a meaningful way. The book also presents research findings regarding all aspects (theory, applications and tools) of computer and information science, and discusses the practical challenges encountered along the way and the solutions adopted to solve them.
(source: Nielsen Book Data)

• Recognition.- Synthesis.- Understanding.- Signal processing.- Language and text processing.- Computational paralinguistics.- Multi-modal speech processing.- Human-computer interaction.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 19th International Conference on Speech and Computer, SPECOM 2017, held in Hatfield, UK, in September 2017. The 80 papers presented in this volume were carefully reviewed and selected from 150 submissions. The papers present current research in the area of computer speech processing (recognition, synthesis, understanding etc.) and related domains (including signal processing, language and text processing, computational paralinguistics, multi-modal speech processing, human-computer interaction).
(source: Nielsen Book Data)

• Proof-Labeling Schemes: Broadcast, Unicast and in Between.- Self-Stabilizing Rendezvous of Synchronous Mobile Agents in Graphs.- The Dynamics and Stability of Probabilistic Population Processes.- Self-stabilizing Distributed Stable Marriage.- Computing the Fault-Containment Time of Self-Stabilizing Algorithms Using Markov Chains and Lumping.- Self-Tuning Eventually-Consistent Data Stores.- An Efficient Silent Self-Stabilizing 1-Maximal Matching Algorithm under Distributed Daemon for Arbitrary Networks.- An Improved Approximate Agreement Algorithm in the Presence of
• Mobile Byzantine Faults.- Fault-Induced Dynamics of Oblivious Robots on a Line.- Relaxed Data Types as Consistency Conditions.- Ant-Inspired Dynamic Task Allocation via Gossiping.- Self-stabilizing Localization of the Middle Point of a Line Segment by an Oblivious Robot with Limited visibility.- Robust Routing Made Easy.- Generalized Paxos Made Byzantine (and Less Complex).- ASSESS: A Tool for Automated Synthesis of Distributed Self-Stabilizing Algorithms.- How to Simulate Message-passing Algorithms in mobile agent systems with faults.- A Self-Stabilizing General De Bruijn Graph.- Constant-Time Complete Visibility for Asynchronous Robots with Lights.- On Security Analysis of Proof-of-Elapsed-Time (PoET).- Brief Announcement: Federated Code Auditing and Delivery for MPC.- Brief Announcement: Reduced Space Self-stabilizing Center Finding Algorithms in Chains and Trees.- A Fully Asynchronous and Fault Tolerant Distributed Algorithm to Compute a Minimum Graph Orientation.- Universally Optimal Gathering under Limited Visibility.- Optimum Algorithm for Mutual Visibility among Asynchronous Robots with Lights.- Brief Announcement: ZeroBlock: Timestamp-Free Prevention of Block-Withholding Attack in Bitcoin.- Scalable Funding of Bitcoin Micropayment Channel Networks.- Brief Announcement: A Self-stabilizing Algorithm for the Minimal Generalized Dominating Set Problem.- Space-Optimal Proportion Consensus with Population Protocols.- Brief Announcement: Asynchronous, Distributed Optical Mutual Exclusion.- Brief Announcement: Passive and Active Attacks on Audience Response Systems Using Software Defined Radios.- Cryptocurrency Smart Contracts for Distributed Consensus of Public Randomness.- TorBricks: Blocking-Resistant Tor Bridge Distribution.- Cover Time in Edge-Uniform Stochastically-Evolving Graphs.- Bitcoin a Distributed Shared Register.- Broadcast Encryption with Both Temporary and Permanent Revocation.- Brief Announcement: Optimal Asynchronous Rendezvous for Mobile Robots with Lights.- Brief Announcement: Space-efficient Uniform Deployment of Mobile Agents in Asynchronous Unidirectional Rings. .
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 19th International Symposium on Stabilization, Safety, and Security of Distributed Systems, SSS 2017, held in Boston, MA, USA, in November 2017. The 29 revised full papers presented together with 8 revised short papers were carefully reviewed and selected from 68 initial submissions. This year the Symposium was organized into three tracks reflecting major trends related to self-* systems: Stabilizing Systems: Theory and Practice: Distributed Computing and Communication Networks; and Computer Security and Information Privacy.
(source: Nielsen Book Data)

• Language and information extraction.- Post-processing and applications of automatic transcriptions.- Speech paralinguistics and synthesis.- Speech recognition: modeling and resources.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 5th International Conference on Statistical Language and Speech Processing, SLSP 2017, held in Le Mans, France, in October 2017. The 21 full papers presented were carefully reviewed and selected from 39 submissions. The papers cover topics such as anaphora and conference resolution; authorship identification, plagiarism and spam filtering; computer-aided translation; corpora and language resources; data mining and semanticweb; information extraction; information retrieval; knowledge representation and ontologies; lexicons and dictionaries; machine translation; multimodal technologies; natural language understanding; neural representation of speech and language; opinion mining and sentiment analysis; parsing; part-of-speech tagging; question and answering systems; semantic role labeling; speaker identification and verification; speech and language generation; speech recognition; speech synthesis; speech transcription; speech correction; spoken dialogue systems; term extraction; text categorization; test summarization; user modeling. They are organized in the following sections: language and information extraction; post-processing and applications of automatic transcriptions; speech paralinguistics and synthesis; speech recognition: modeling and resources.
(source: Nielsen Book Data)

• Greedy shortest common superstring approximation in compact space.- Longest common factor after one edit operation.- Distinct squares in circular words.- LZ78 Compression in Low Main Memory Space.- On Two LZ78-style Grammars: Compression Bounds and Compressed-Space Computation.-On suffix tree breadth.- Pattern Matching on Elastic-Degenerate Text with Errors.- Succint Partial Sums and Fenwick Trees.- Tight Bounds for Top Tree Compression.- Efficient Compression and Indexing of Trajectories.- Fast Construction of Compressed Web Graphs.- Constructing a Consensus Phylogeny from a Leaf-Removal Distance.- Listing Maximal Independent Sets with Minimal Space and Bounded Delay.- Fast label extraction in the CDAWG.- Lightweight BWT and LCP Merging via the Gap algorithm.- Practical Evaluation of Lempel-Ziv-78 and Lempel-Ziv-Welch Tries.- Regular Abelian periods and longest common Abelian factors on run-length encoded strings.-Mining bit-parallel LCS-length algorithms.- Practical Implementation of Space-Efficient Dynamic Keyword Dictionaries.- Faster Practical Block Compression for Rank/Select Dictionaries.- Optimal Skeleton Huffman Trees.- Detecting Unary Patterns.- Order preserving pattern matching on trees and DAGs.- A Self-Index on Block Trees.- Counting Palindromes in Substrings.- linear-size CDAWG: new repetition-aware indexing and grammar compression. .
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 24th International Symposium on String Processing and Information Retrieval, SPIRE 2017, held in Palermo, Italy, in September 2017. The 26 papers presented in this volume were carefully reviewed and selected from 71 submissions. They focus on fundamental studies on string processing and information retrieval, as well as on computational biology. .
(source: Nielsen Book Data)

• Modeling and Specification.- Orchestration Combinators in Apla+ Language.- On Termination and Boundedness of Nested Updatable Timed Automata.- Instant-based and State-based Analysis of Infinite Logical Clock.- Animation and Prototyping.- Automated Safety Analysis on Scenario-based Requirements for Train Control System.- A Case Study of a GUI-Aided Approach to Constructing Formal Specifications.- Formal Development of Linear Structure Reusable Components in PAR Platform.- Verification and Validation.- E-SSL:An SSL Security-Enhanced Method for Bypassing MITM Attacks in Mobile Internet.- A Proof System for MSVL Programs in Coq.- Runtime Verification Monitor Construction for Three-valued PPTL.- Applying SOFL to a Railway Interlocking System in Industry. .
• (source: Nielsen Book Data)

This book constitutes revised selected papers from the 6th International Workshop on Structures Object-Oriented Formal Language and Method, SOFL+MSVL 2016, held in Tokyo, Japan, in November 2016. The 13 papers presented in this volume were carefully reviewed and selected from 26 submissions. They are organized in topical sections named: modeling and specification; animation and prototyping; verification and validation; and model checking. .
(source: Nielsen Book Data)

• Introduction to Swarm Search.- Cooperative "Swarm Cleaning" of Stationary Domains.- Swarm Search of Expanding Regions in Grids: Lower Bounds.- Swarm Search of Expanding Regions in Grids: Upper Bounds.- The Search Complexity of Collaborative Swarms Expanding Z2 Grid Regions.
• (source: Nielsen Book Data)

This book offers a comprehensive analysis of the theory and tools needed for the development of an efficient and robust infrastructure for the design of collaborative patrolling unmanned aerial vehicle (UAV) swarms, focusing on its applications for tactical intelligence drones. It discusses frameworks for robustly and near-optimally analyzing flocks of semi-autonomous vehicles designed to efficiently perform the ongoing dynamic patrolling and scanning of pre-defined "search regions". It discusses the theoretical limitations of such systems, as well as the trade-offs between the systems' various economic and operational parameters. Current UAV systems rely mainly on human operators for the design and adaptation of drones' flying routes. However, recent technological advances have introduced new systems, comprised of a small number of self-organizing vehicles, manually guided at the swarm level by a human operator. With the growing complexity of such man-supervised architectures, it is becoming increasingly harder to guarantee a pre-defined level of performance. The use of large scale swarms of UAVs as a combat and reconnaissance platform therefore necessitates the development of an efficient optimization mechanism of their utilization, specifically in the design and maintenance of their patrolling routes. The book is intended for researchers and engineers in the fields of swarms systems and autonomous drones. .
(source: Nielsen Book Data)

This book is published open access under a CC BY license. This book constitutes the proceedings of the 5th International Workshop on Symbiotic Interaction, Symbiotic 2016, held in Padua, Italy, in October 2016. The 12 full papers and 3 short papers presented in this volume were carefully reviewed and selected from 23 submissions. The idea of symbiotic systems put forward in this workshop capitalizes on the computers' ability to implicitly detect the users goals, preferences or/and psycho-physiological states and thereby enhancing human-computer interaction (HCI). The papers present an overview of the symbiotic relationships between humans and computers with emphasis on user-driven research on symbiotic systems, adaptive systems, implicit input data, physiological computing and BCI, but also on understanding the nature of the interdependence and agency between computers and humans more broadly.
(source: Nielsen Book Data)

• Analogical reasoning.- Argumentation.- Bayesian networks.- Belief functions.- Conditionals.- Credal sets, credal networks.- Decision theory, decision making and reasoning under uncertainty.- Fuzzy sets, fuzzy logic.- Logics.-Orthopairs.- Possibilistic networks.- Probabilistic logics, probabilistic reasoning.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 14th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2017, held in Lugano, Switzerland, in July 2017. The 44 revised full papers presented together with 5 abstracts of invited talks were carefully reviewed and selected from 63 submissions and cover topics on analogical reasoning; argumentation; Bayesian networks; belief functions; conditionals; credal sets, credal networks; decision theory, decision making and reasoning under uncertainty; fuzzy sets, fuzzy logic; logics; orthopairs; possibilistic networks; and probabilistic logics, probabilistic reasoning.
(source: Nielsen Book Data)

• Abstraction Refinement for the Analysis of Software Product Lines.- Hybrid Information Flow Analysis for Real-World C Code.- Symbolic Execution of Transition Systems with Function Summaries.- Unit Testing of Database-Driven Java Enterprise Edition Applications.- Model-Based Testing of Probabilistic Systems with Stochastic Time.- Test Suite Reduction in Idempotence Testing of Infrastructure as Code.- Checking UML and OCL Model Behavior with Filmstripping and Classifying Terms.- Skolem Function Continuation for Quantified Boolean Formulas.- WSCLim: A Tool for Model-Based Testing of WS-BPEL Compositions under Load Conditions.- Testing a Saturation-Based Theorem Prover: Experiences and Challenges. .
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 11th International Conference on Tests and Proofs, TAP 2017, held as part of STAF 2017, in Marburg, Germany, in July 2017. The 9 full papers and 1 invited paper presented in this volume were carefully reviewed and selected from 16 submissions. The TAP conference promotes research in verification and formal methods that targets the interplay of proofs and testing: the advancement of techniques of each kind and their combination, with the ultimate goal of improving software and system dependability.
(source: Nielsen Book Data)

This volume constitutes the refereed post-conference proceedings of the International Conference on Theoretical Computer Science and Discrete Mathematics, held in Krishnankoil, India, in December 2016. The 57 revised full papers were carefully reviewed and selected from 210 submissions. The papers cover a broad range of topics such as line graphs and its generalizations, large graphs of given degree and diameter, graphoidal covers, adjacency spectrum, distance spectrum, b-coloring, separation dimension of graphs and hypergraphs, domination in graphs, graph labeling problems, subsequences of words and Parike matrices, lambda-design conjecture, graph algorithms and interference model for wireless sensor networks. .
(source: Nielsen Book Data)

• Computability.- Computer science logic.- Complexity.- Algorithms.- Models of computation and systems theory.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 14th Annual Conference on Theory and Applications of Models of Computation, TAMC 2017, held in Bern, Switzerland, in April 2017. The 45 revised full papers presented together with 4 invited papers were carefully reviewed and selected from 103 submissions. The main themes of TAMC 2017 have been computability, computer science logic, complexity, algorithms, and models of computation and systems theory.
(source: Nielsen Book Data)

• Introduction to fuzzy sets.- Introduction to fuzzy systems.- Ordered fuzzy numbers: sources and intuitions.- Ordered fuzzy numbers: definitions and operations.- Processing the direction with ordered fuzzy numbers.- Some cases of comparing fuzzy numbers using defuzzificators on the catalog of OFN shapes.- Two approaches to fuzzy implication.- The approach to capital budgeting under uncertainty and risk based on Ordered Fuzzy Numbers.- Input-Output Model Based on Ordered Fuzzy Numbers.- Ordered Fuzzy Candlesticks - financial data representation and analysis using Ordered Fuzzy Numbers.- Application of Ordered Fuzzy Numbers to detect trends in the Nasdaq composite index.- The OFNAnt method based on Ant Colony Optimization used to solve the TSP.- A new OFNBee method as an example of fuzzy observance applied for ABC optimization.- Fuzzy observation of DDoS attack.- Fuzzy control for secure TCP transfer.- Fuzzy Numbers applied to a heat furnace control.- Traditional vs OFN-based analysis of temporo-spatial gait parameters.- OFN-based brain function modeling.
• (source: Nielsen Book Data)

This book is open access under a CC BY 4.0 license. This open access book offers comprehensive coverage on Ordered Fuzzy Numbers, providing readers with both the basic information and the necessary expertise to use them in a variety of real-world applications. The respective chapters, written by leading researchers, discuss the main techniques and applications, together with the advantages and shortcomings of these tools in comparison to other fuzzy number representation models. Primarily intended for engineers and researchers in the field of fuzzy arithmetic, the book also offers a valuable source of basic information on fuzzy models and an easy-to-understand reference guide to their applications for advanced undergraduate students, operations researchers, modelers and managers alike.
(source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 20th International Conference on Theory and Applications of Satisfiability Testing, SAT 2017, held in Melbourne, Australia, in August/September 2017. The 22 revised full papers, 5 short papers, and 3 tool papers were carefully reviewed and selected from 64 submissions. The papers are organized in the following topical sections: algorithms, complexity, and lower bounds; clause learning and symmetry handling; maximum satisfiability and minimal correction sets; parallel SAT solving; quantified Boolean formulas; satisfiability modulo theories; and SAT encodings.
(source: Nielsen Book Data)

• Computer-aided human centric cyber situation awareness.- Computer and information science aspects of the recent advances in cyber situation awareness.- Learning and decision making aspects of the recent advances in cyber situation awareness.- Cognitive science aspects of the recent advances in cyber situation awareness.
• (source: Nielsen Book Data)

Today, when a security incident happens, the top three questions a cyber operation center would ask are: What has happened? Why did it happen? What should I do? Answers to the first two questions form the core of Cyber Situation Awareness (SA). Whether the last question can be satisfactorily addressed is largely dependent upon the cyber situation awareness capability of an enterprise. The goal of this book is to present a summary of recent research advances in the development of highly desirable Cyber Situation Awareness capabilities. The 8 invited full papers presented in this volume are organized around the following topics: computer-aided human centric cyber situation awareness; computer and information science aspects of the recent advances in cyber situation awareness; learning and decision making aspects of the recent advances in cyber situation awareness; cognitive science aspects of the recent advances in cyber situation awareness.
(source: Nielsen Book Data)

• Part 1: Historical Review of Professor Zdzislaw Pawlak and Rough Set.- The Born and Growing of Chinese Rough Set Community with Help of Professor Zdzislaw Pawlak.- Zdzislaw Pawlak as I Saw Him and Remember Him Now.- Recent Development of Rough Computing: A Scientometrics View.-
• Part 2: Review of Rough Set Research.- Rough Sets, Rough Mereology and Uncertainty.- Rough Sets in Machine Learning: A Review.- Application of Tolerance Rough Sets in Structured and Unstructured Text Categorization: A Survey.- Medical Diagnosis: Rough Set View.- Rough Set Analysis of Imprecise Classes.- Pawlak's Many Valued Information System, Non-deterministic Information System, and a Proposal of New Topics on Information Incompleteness Toward the Actual Application.-
• Part 3: Rough Set Theory.- From Information Systems to Interactive Information Systems.- Back to the Beginnings: Pawlak's Definitions of the Terms Information System and Rough Set.- Knowledge and Consequence in AC Semantics for General Rough Sets.- Measuring Soft Roughness of Soft Rough Sets Induced by Covering.- Rough search of vague knowledge.- Vagueness and Uncertainty: An F-Rough Set Perspective.- Directions of Use of the Pawlak's Approach to Conflict Analysis.- Lattice Structure of Variable Precision Rough Sets.-
• Part 4: Rough Set Based Data Mining.- Mining for Actionable Knowledge in Tinnitus Datasets.- Rough-Granular Computing for Relational Data.- The Boosting and Bootstrap Ensembles for the Pair Classifier Based on the Dual Indiscernibility Matrix.
• (source: Nielsen Book Data)

This special book is dedicated to the memory of Professor Zdzislaw Pawlak, the father of rough set theory, in order to commemorate both the 10th anniversary of his passing and 35 years of rough set theory. The book consists of 20 chapters distributed into four sections, which focus in turn on a historical review of Professor Zdzislaw Pawlak and rough set theory; a review of the theory of rough sets; the state of the art of rough set theory; and major developments in rough set based data mining approaches. Apart from Professor Pawlak's contributions to rough set theory, other areas he was interested in are also included. Moreover, recent theoretical studies and advances in applications are also presented. The book will offer a useful guide for researchers in Knowledge Engineering and Data Mining by suggesting new approaches to solving the problems they encounter.
(source: Nielsen Book Data)

• Temporal Costs of Computing Unit Redundancy in Steady and Transient State.- SIPE: A Domain-Specific Language for Specifying Interactive Programming Exercises.- Managing Software Complexity by Exploiting Software Similarity Patterns.- A Prototype Tool for Semantic Validation of UML class Diagrams with the Use of Domain Ontologies Expressed in OWL 2.- Ensuring the Strong Exception Safety.- Efficient Testing of Time-dependent, Asynchronous Code.
• (source: Nielsen Book Data)

This book reports on recent advances in software engineering research and practice. Divided into 15 chapters, it addresses: languages and tools; development processes; modelling, simulation and verification; and education. In the first category, the book includes chapters on domain-specific languages, software complexity, testing and tools. In the second, it reports on test-driven development, processing of business rules, and software management. In turn, subsequent chapters address modelling, simulation and verification of real-time systems, mobile systems and computer networks, and a scrum-based framework. The book was written by researchers and practitioners, the goal being to achieve a synergistic combination of research results achieved in academia and best practices used in the industry, and to provide a valuable reference guide for both groups.
(source: Nielsen Book Data)

• Swarm and multi-robotic systems.- Human-robot interaction.- Robotic learning and imitation.- Robot navigation, planning and safety.- Humanoid and bio-inspired robots.- Mobile robots and vehicles.- Robot testing and design.- Detection and recognition.- Learning and adaptive behaviours.- Interaction.- Soft and reconfigurable robots.- Service and industrial robots.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 18th Annual Conference on Towards Autonomous Robotics, TAROS 2017, held in Guildford, UK, in July 2017. The 43 revised full papers presented together with 13 short papers were carefully reviewed and selected from 66 submissions. The papers discuss robotics research drawn from a wide and diverse range of topics, such as swarm and multi-robotic systems; human-robot interaction; robotic learning and imitation; robot navigation, planning and safety; humanoid and bio-inspired robots; mobile robots and vehicles; robot testing and design; detection and recognition; learning and adaptive behaviours; interaction; soft and reconfigurable robots; and service and industrial robots.
(source: Nielsen Book Data)

• Towards integrative Machine Learning & Knowledge Extraction.- Machine Learning and Knowledge Extraction in Digital Pathology needs an integrative approach.- Comparison of Public-Domain Software and Services for Probabilistic Record Linkage and Address Standardization.- Better Interpretable Models for Proteomics Data Analysis Using rule-based Mining.- Probabilistic Logic Programming in Action.- Persistent topology for natural data analysis - A survey.- Predictive Models for Differentiation between Normal and Abnormal EEG through Cross-Correlation and Machine Learning Techniques.- A Brief Philosophical Note on Information.- Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline.- A Fast Semi-Automatic Segmentation Tool for Processing Brain Tumor Images.- Topological characteristics of oil and gas reservoirs and their applications.- Convolutional and Recurrent Neural Networks for Activity Recognition in Smart Environment.
• (source: Nielsen Book Data)

The BIRS Workshop "Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets" (15w2181), held in July 2015 in Banff, Canada, was dedicated to stimulating a cross-domain integrative machine-learning approach and appraisal of "hot topics" toward tackling the grand challenge of reaching a level of useful and useable computational intelligence with a focus on real-world problems, such as in the health domain. This encompasses learning from prior data, extracting and discovering knowledge, generalizing the results, fighting the curse of dimensionality, and ultimately disentangling the underlying explanatory factors in complex data, i.e., to make sense of data within the context of the application domain. The workshop aimed to contribute advancements in promising novel areas such as at the intersection of machine learning and topological data analysis. History has shown that most often the overlapping areas at intersections of seemingly disparate fields are key for the stimulation of new insights and further advances. This is particularly true for the extremely broad field of machine learning.
(source: Nielsen Book Data)

These transactions publish research in computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as the semantic Web, social networks, and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood as the form of intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies, such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc., aims to support human and other collective intelligence and to create new forms of CCI in natural and/or artificial systems. This twenty-sixth issue is a special issue with selected papers from the First International KEYSTONE Conference 2015 (IKC 2015), part of the keystone COST Action IC1302.
(source: Nielsen Book Data)

• Exact Detection of Information Leakage: Decidability and Complexity.- Binary Shapelet Transform for Multiclass Time Series Classification.- DAAR: A Discrimination-Aware Association Rule Classifier for Decision Support.- New Word Detection and Tagging on Chinese Twitter Stream.- On-Demand Snapshot Maintenance in Data Warehouses Using Incremental ETL Pipeline.
• (source: Nielsen Book Data)

• Lightweight Metric Computation for Distributed Massive Data Streams.- Performance Analysis of Object Store Systems in a Fog and Edge Computing Infrastructure.- Scientific Workflow Scheduling with Provenance Data in a Multisite Cloud.- Cost Optimization of Data Flows Based on Task Re-ordering.- Fusion Strategies for Large-Scale Multi-Modal Image Retrieval.
• (source: Nielsen Book Data)

The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This, the 33rd issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains five revised selected regular papers. Topics covered include distributed massive data streams, storage systems, scientific workflow scheduling, cost optimization of data flows, and fusion strategies.
(source: Nielsen Book Data)
The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This volume, the 32nd issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, focuses on Big Data Analytics and Knowledge Discovery, and contains extended and revised versions of five papers selected from the 17th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2015, held in Valencia, Spain, during September 1-4, 2015. The five papers focus on the exact detection of information leakage, the binary shapelet transform for multiclass time series classification, a discrimination-aware association rule classifier for decision support (DAAR), new word detection and tagging on Chinese Twitter, and on-demand snapshot maintenance in data warehouses using incremental ETL pipelines, respectively. discovery, ="" contains="" extended="" revised="" versions="" five="" papers="" selected="" from="" 17th="" international="" conference="" discovery="" (dawak="" 2015), ="" held="" in="" valencia, ="" spain, ="" during="" september="" 1-4, ="" 2015.="" focus="" exact="" detection="" information="" leakage, ="" binary="" shapelet="" transform="" for="" multiclass="" time="" series="" classification, ="" a="" discrimination-aware="" association="" rule="" classifier="" decision="" support="" (daar), ="" new="" word="" tagging="" chinese="" twitter, ="" on-demand="" snapshot="" maintenance="" warehouses="" using="" incremental="" etl="" pipelines, ="" respectively.
(source: Nielsen Book Data)

• Lightweight Metric Computation for Distributed Massive Data Streams.- Performance Analysis of Object Store Systems in a Fog and Edge Computing Infrastructure.- Scientific Workflow Scheduling with Provenance Data in a Multisite Cloud.- Cost Optimization of Data Flows Based on Task Re-ordering.- Fusion Strategies for Large-Scale Multi-Modal Image Retrieval.
• (source: Nielsen Book Data)

The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This, the 33rd issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains five revised selected regular papers. Topics covered include distributed massive data streams, storage systems, scientific workflow scheduling, cost optimization of data flows, and fusion strategies.
(source: Nielsen Book Data)

• Early Classification of Multivariate Time Series on Distributed and In-Memory Platforms.- Behavior Classification of Dairy Cows fitted with GPS collars.- Dynamic Real-time Segmentation and Recongnition of Activities using a Multi-feature Windowing Approach.- Feature Extraction from EEG data for a P300 Based Brain-computer Interface.- Thermal Stratification Prediction at Lake Trevallyn.- Development of a Software Vulnerability Prediction Web Service based on Artificial Neural Networks
• Diversification Heuristics in Bees Swarm Optimization for Association Rules Mining.- Improved CFDP Algorithms Based on Shared Nearest Neighbors and Transitive Closure.- CNN-based Sequence Labeling for Fine-grained Opinion Mining of Microblogs.- A Genetic Algorithm for Interpretable Model Extraction from Decision Tree Ensembles.- Self-Adaptive Weighted Extreme Learning Machine for Imbalanced Classification Problems.- Estimating Word Probabilities with Neural Networks in Latent Dirichlet Allocation.- GA-Apriori: Combining Apriori Heuristic and Genetic Algorithms for Solving the Frequent Itemsets Mining Problem.- Shelf Time Analysis in CTP Insurance Claims Processing.- Automated Product-Attribute Mapping.- A Novel Extreme Learning Machine-based Classification Algorithm for Uncertain Data.- SPGLAD: A Self-Paced Learning-based Crowdsourcing Classification Model.
• (source: Nielsen Book Data)

This book constitutes the thoroughly refereed post-workshop proceedings at PAKDD Workshops 2017, held in conjunction with PAKDD, the 21st Pacific-Asia Conference on Knowledge Discovery and Data Mining in May 2017 in Jeju, South Korea. The 17 revised papers presented were carefully reviewed and selected from 38 submissions. The workshops affiliated with PAKDD 2017 include: Workshop on Machine Learning for Sensory Data Analysis (MLSDA), Workshop on Biologically Inspired Data Mining Techniques (BDM), Pacific Asia Workshop on Intelligence and Security Informatics (PAISI), and Workshop on Data Mining in Business Process Management (DM-BPM).
(source: Nielsen Book Data)

• E-health mining.- Image, information and intelligent applications--.- Artificial intelligence for educational applications.- Artificial intelligence for tourism.-Emphatic computing.- Artificial intelligence and applications.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 14th Pacific Rim Collocated PRICAI 2016 Workshops on Artificial Intelligence, held in Phuket, Thailand, in August 2016.The 16 full papers presented in this volume were carefully reviewed and selected from 46 submissions. The are organized around the following topics: e-health mining; image, information and intelligent applications; artificial intelligence for educational applications; artificial intelligence for tourism; emphatic computing; artificial intelligence and applications.
(source: Nielsen Book Data)

• Introduction.- Generalized Eigenvalue Proximal Support Vector Machines.- Twin Support Vector Machines (TWSVM) for Classification.- TWSVR: Twin Support Vector Machine Based Regression.- Variants of Twin Support Vector Machines: Some More Formulations.- TWSVM for Unsupervised and Semi-Supervised Learning.- Some Additional Topics.- Applications Based on TWSVM.- References.
• (source: Nielsen Book Data)

This book provides a systematic and focused study of the various aspects of twin support vector machines (TWSVM) and related developments for classification and regression. In addition to presenting most of the basic models of TWSVM and twin support vector regression (TWSVR) available in the literature, it also discusses the important and challenging applications of this new machine learning methodology. A chapter on "Additional Topics" has been included to discuss kernel optimization and support tensor machine topics, which are comparatively new but have great potential in applications. It is primarily written for graduate students and researchers in the area of machine learning and related topics in computer science, mathematics, electrical engineering, management science and finance.
(source: Nielsen Book Data)

• Preface.- MapReduce: From Elementary Circuits to Cloud.- On the Helmholtz Principle for Data Mining.- A method of introducing weights into OWA operators and other symmetric functions.- Uncertainty Management: Probability, Possibility, Entropy, and Other Paradigms- Relationships between fuzziness, partial truth and probability in the case of repetitive events.- Using extended tree kernels to recognize metalanguage in text.- Relationships between Probability and Possibility Theories.- Modeling extremal events is not easy: why the Extreme Value Theorem cannot be as general as the Central Limit Theorem.- Information quality and uncertainty.- Applying anomalous cluster approach to spatial clustering.- Why is linear quantile regression empirically successful: a possible explanation.- A Rapid Soft Computing Approach to Dimensionality Reduction in Model Construction.- Physics Of The Mind, Dynamic Logic, and Monotone Boolean Functions.- Fuzzy arithmetic type 1 without extension principle and vertical membership functions.- Copula as a bridge between probability theory and fuzzy logic.- Note to the polemics surrounding the second Goedel's theorem.- Ontological Data Mining.
• (source: Nielsen Book Data)

This book commemorates the 65th birthday of Dr. Boris Kovalerchuk, and reflects many of the research areas covered by his work. It focuses on data processing under uncertainty, especially fuzzy data processing, when uncertainty comes from the imprecision of expert opinions. The book includes 17 authoritative contributions by leading experts.
(source: Nielsen Book Data)

• Distributed computing models.- Formal languages and automata theory.- Concurrency.- Probabilistic computation.- Timed and hybrid models.- Formal software verification.- Model verification and validation.- Performance evaluation.- Control methods.- Modeling methodologies.- Model development and analysis.- Modeling and simulation.- Formal mehods.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 11th International Conference International Conference on Verification and Evaluation of Computer and Communication Systems ( VECoS 2017 ), held at Concordia University, Montreal, Canada, in August 2017. The 13 full papers, together with 3 abstracts in this volume were carefully reviewed and selected from 35 submissions. The aim of the VECoS conference is to bring together researchers and practitioners in the areas of verification, control, performance and dependability evalu-ation in order to discuss state-of-the-art and challenges in modern computer and communication systems in which functional and extra-functional properties are strongly interrelated. Thus, the main motivation for VECoS is to encourage the cross-fertilization between various formal verification and evaluation approaches, methods and techniques, and especially those developed for concurrent and dis-tributed hardware/software systems.
(source: Nielsen Book Data)

• Person Re-Identification Dataset with RGB-D Camera in a Top-View Configuration.- Pervasive System for Consumer Behaviour Analysis in Retail Environments.- Estimation of task difficulty and habituation effect while visual manipulation using pupillary response.- Robust Probabilistic Logo Detection in Broadcast Videos for Audience Measurement.- Saliency Prediction for Visual Regions of Interest with Applications in Advertising.- Person Invariant Classification of Subtle Facial Expressions using Coded Movement Direction of Keypoints.- A Two-directional Two-Dimensional PCA Correlation Filter in the Phase Only Spectrum for Face Recognition in Video.- End to End Deep Learning for Single Step Real-time Facial Expression Recognition.- Comparative Study of Human Age Estimation Based on Hand-crafted and Deep Face Features.- Pose-Selective Max Pooling for Measuring Similarity.- Complementing SRCNN by Transformed Self-Exemplars. -Human Head Pose Estimation on SASE database using Random Hough Regression Forests.- Spatio-Temporal Pain Recognition in CNN-based Super-Resolved Facial Images.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the Third Workshop on Video Analytics for Audience Measurement, VAAM 2016, and the Second International Workshop on Face and Facial Expression Recognition from Real World Videos, FFER 2016, held at the 23rd International Conference on Pattern Recognition, ICPR 2016, in Cancun, Mexico, in December 2016. The 11 papers presented in this volume were carefully reviewed and selected from 13 submissions. They deal with: re-identification; consumer behavior analysis; utilizing pupillary response for task difficulty measurement; logo detection; saliency prediction; classification of facial expressions; face recognition; face verification; age estimation; super resolution; pose estimation; and pain recognition. .
(source: Nielsen Book Data)

• Spatial data processing and data quality.- Graph data processing.- Data mining, privacy and semantic analysis.- Text and log data management.-Social networks.- Data mining and data streams.- Query processing.- Topic modeling.- Machine learning.- Recommendation systems.- Distributed data processing and applications.- Machine learning and optimization.
• (source: Nielsen Book Data)

This two -volume set, LNCS 10366 and 10367, constitutes the thoroughly refereed proceedings of the First International Joint Conference, APWeb-WAIM 2017, held in Beijing, China in July 2017. The 44 full papers presented together with 32 short papers and 10 demonstrations papers were carefully reviewed and selected from 240 submissions. The papers are organized around the following topics: spatial data processing and data quality; graph data processing; data mining, privacy and semantic analysis; text and log data management; social networks; data mining and data streams; query processing; topic modeling; machine learning; recommendation systems; distributed data processing and applications; machine learning and optimization.
(source: Nielsen Book Data)

• Spatial data processing and data quality.- Graph data processing.- Data mining, privacy and semantic analysis.- Text and log data management.-Social networks.- Data mining and data streams.- Query processing.- Topic modeling.- Machine learning.- Recommendation systems.- Distributed data processing and applications.- Machine learning and optimization. .
• (source: Nielsen Book Data)

This two -volume set, LNCS 10366 and 10367, constitutes the thoroughly refereed proceedings of the First International Joint Conference, APWeb-WAIM 2017, held in Beijing, China in July 2017. The 44 full papers presented together with 32 short papers and 10 demonstrations papers were carefully reviewed and selected from 240 submissions. The papers are organized around the following topics: spatial data processing and data quality; graph data processing; data mining, privacy and semantic analysis; text and log data management; social networks; data mining and data streams; query processing; topic modeling; machine learning; recommendation systems; distributed data processing and applications; machine learning and optimization.
(source: Nielsen Book Data)

• Intro
• Preface
• Organization
• Contents
• Technical Research Papers
• Evaluating Knowledge Anchors in Data Graphs Against Basic Level Objects
• Abstract
• 1 Introduction
• 2 Related Work
• 3 Identifying Knowledge Anchors in Data Graphs
• 4 Identifying Basic Level Objects Over Data Graphs
• 4.1 Cognitive Science Experimental Approaches for Deriving BLO
• 4.2 Algorithm for Identifying BLO Over Data Graphs
• 4.3 Application Contexts Used for Experimental Evaluation
• 5 MusicPinta: Evaluating KADG Against BLO
• 5.1 Obtaining BLO
• 5.2 Evaluating KADG Against BLO

• 6 L4All: Evaluating KADG Against BLO
• 6.1 Obtaining BLO
• 6.2 Evaluating KADG Against BLO
• 7 Discussion
• 8 Conclusion and Future Work
• Acknowledgements
• References
• Decentralized Evolution and Consolidation of RDF Graphs
• 1 Introduction
• 2 Related Work
• 3 Preliminaries
• 4 Operations
• 4.1 Merge Different Branches
• 4.2 Revert a Commit
• 5 Merge Strategies
• 6 Evaluation
• 6.1 Correctness of Version Tracking
• 6.2 Performance
• 6.3 Correctness of the Merge Method
• 7 Conclusion and Future Work
• References

• The BigDataEurope Platform
• Supporting the Variety Dimension of Big Data
• 1 Introduction
• 2 Platform Overview
• 3 Semantic Layer
• 3.1 Semantic Data Lake
• 3.2 Big Data Analytics for RDF
• 3.3 Semagrow Query Federation
• 4 BDE Platform Showcases
• 4.1 SC1 Health, Demographic Change and Wellbeing
• 4.2 SC7: Secure Societies
• 5 Discussion and Conclusions
• References
• Spatially Cohesive Service Discovery and Dynamic Service Handover for Distributed IoT Environments
• Abstract
• 1 Introduction
• 2 Related Work

• 3 Spatially Cohesive Service Discovery and Dynamic Service Handover
• 3.1 Problem Definition
• 3.2 Discovery Plan Generation
• 3.3 Spatio-Cohesive Service Discovery and Handover
• 4 Evaluation
• 4.1 Evaluation Setting
• 4.2 Evaluation Results
• 4.3 Threats to Validity
• 5 Testbed Implementation
• 6 Conclusion
• Acknowledgment
• References
• ALMOsT.js: An Agile Model to Model and Model to Text Transformation Framework
• 1 Introduction
• 2 Related Work
• 3 The ALMOsT.js Framework
• 3.1 Requirements
• 3.2 Architecture
• 3.3 Data Model
• 3.4 Transformation Rules
• 3.5 Model Editor

• 3.6 Case Study: IFMLEdit.org
• 3.7 Extending ALMOsT.js
• 3.8 Discussion and Limitations
• 4 Conclusions and Future Work
• References
• A Big Data Analysis Framework for Model-Based Web User Behavior Analytics
• 1 Introduction
• 2 MDD of User Interaction with IFML and WebRatio
• 2.1 The IFML Language
• 2.2 WebRatio Implementation of IFML
• 3 Modeling, Integration, Analysis, and Visualization
• 3.1 Application Modeling and Generation
• 3.2 Analysis
• 3.3 Visualization
• 4 Case Study
• 4.1 Navigation-Based Statistics
• 4.2 Content-Based Statistics
• 4.3 Visualization

This book constitutes the refereed proceedings of the 17th International Conference on Web Engineering, ICWE 2017, held in Rome, Italy, in June 2017. The 20 full research papers and 12 short papers presented together with 6 application papers, 6 demonstration papers, and 6 contributions to the PhD Symposium, were carefully reviewed and selected from 139 submissions. The papers cover research areas such as Web application modeling and engineering, human computation and crowdsourcing applications, Web applications composition and mashup, Social Web applications, Semantic Web applications, Web of Things applications, and big data.
(source: Nielsen Book Data)

• Paper Sessions Applications 1.- Artificial Intelligence Systems in Micromechanics.- Integrating Two Artificial Intelligence Theories in a Medical Diagnosis Application.- Artificial Intelligence and Law.- Virtual Market Environment for Trade.- Neural Networks and Fuzzy Systems.- An Artificial Neural Networks Approach to the Estimation of Physical Stellar Parameters.- Evolutionary Robot Behaviors Based on Natural Selection and Neural Network.- Control of Overhead Crane by Fuzzy-Pid with Genetic Optimisation.- Creative Design of Fuzzy Logic Controller.- On-Line Extraction of Fuzzy rules in a Wastewater Treatment Plant.- Agents.- An Autonomous Intelligent Agent Architecture Based on Constructivist AI.- Finding Manufacturing Expertise Using Ontologies and Cooperative Agents.- Using Agents in the Exchange of Product Data.- Applications 2.- A Pervasive Identification and Adaptation System for the Smart House.- Deductive Diagnosis of Digital Circuits.- Verification of NASA Emergent Systems.- Theory.- Knowledge Base Structure.- Learning Bayesian Metanetworks from Data with Multilevel Uncertainty.- Using Organizational Structures Emergence for Maintaining Functional Integrity in Embedded Systems Networks.- Efficient Attribute Reduction Algorithm.- Using Relative Logic for Pattern Recognition.- Intelligent Tutoring and Collaboration.- Mathtutor: A Multi-Agent Intelligent Tutoring System.- Analysis and Intelligent Support of Learning Communities in Semi-Structured Discussion Environments.- An Adaptive Assessment System to Evaluate Student Ability Level.- Forming the Optimal Team of Experts for Collaborative Work.- Internet.- Impact on Performance of Hypertext Classification of Selective Rich HTML Capture.- Introducing a Star Topology into Latent Class Models for Collaborative Filtering.- Dialoguing with an Online Assistant in a Financial Domain: The VIP-Advisor Approach.- An Agency for Semantic-Based Automatic Discovery of Web-Services.- Genetic Algorithms.- GESOS: A Multi-Objective Genetic Tool for Project Management Considering Technical and Non-Technical Constraints.- Using Genetic Algorithms and Tabu Search Parallel Models to Solve the Scheduling Problem.- Modelling Document Categories by Evolutionary Learning of Text Centroids.- Ontologies and Data Mining.- ODEval: A Tool for Evaluating RDF(S), DAML+OIL, and OWL Concept Taxonomies.- Air - A Platform for Intelligent Systems.- Swissanalyst.- Data Mining by MOUCLAS Algorithm for Petroleum Reservoir Characterization from Well Logging Data.- Reasoning and Scheduling.- Verification of Procedural Reasoning System (PRS) Programs Using Coloured Petri Nets (CPN).- On-Line Possibilistic Diagnosis Based on Expert Knowledge for Engine Dyno Test Benches.- CBR and Micro-Architecture Anti-Patterns Based Software Design Improvement.- A Decision Support System (DSS) for the Railway Scheduling Problem.- An Interactive Multicriteria Optimisation Approach to Scheduling.
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Artificial Intelligence and Innovations (AIAI) will interest researchers, IT professionals and consultants by examining technologies and applications of demonstrable value. The conference focused on profitable intelligent systems and technologies. AIAI focuses on real world applications; therefore authors should highlight the benefits of AI technology for industry and services. Novel approaches solving business and industrial problems, using AI, will emerge from this conference.
(source: Nielsen Book Data)

• Table of Contents A Gentle Introduction to Machine Learning Important Elements in Machine Learning Feature Selection and Feature Engineering Regression Algorithms Linear Classification Algorithms Naive Bayes and Discriminant Analysis Support Vector Machines Decision Trees and Ensemble Learning Clustering Fundamentals Advanced Clustering Hierarchical Clustering Introducing Recommendation Systems Introducing Natural Language Processing Topic Modeling and Sentiment Analysis in NLP Introducing Neural Networks Advanced Deep Learning Models Creating a Machine Learning Architecture.
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An easy-to-follow, step-by-step guide for getting to grips with the real-world application of machine learning algorithms Key Features Explore statistics and complex mathematics for data-intensive applications Discover new developments in EM algorithm, PCA, and bayesian regression Study patterns and make predictions across various datasets Book DescriptionMachine learning has gained tremendous popularity for its powerful and fast predictions with large datasets. However, the true forces behind its powerful output are the complex algorithms involving substantial statistical analysis that churn large datasets and generate substantial insight. This second edition of Machine Learning Algorithms walks you through prominent development outcomes that have taken place relating to machine learning algorithms, which constitute major contributions to the machine learning process and help you to strengthen and master statistical interpretation across the areas of supervised, semi-supervised, and reinforcement learning. Once the core concepts of an algorithm have been covered, you'll explore real-world examples based on the most diffused libraries, such as scikit-learn, NLTK, TensorFlow, and Keras. You will discover new topics such as principal component analysis (PCA), independent component analysis (ICA), Bayesian regression, discriminant analysis, advanced clustering, and gaussian mixture. By the end of this book, you will have studied machine learning algorithms and be able to put them into production to make your machine learning applications more innovative. What you will learn Study feature selection and the feature engineering process Assess performance and error trade-offs for linear regression Build a data model and understand how it works by using different types of algorithm Learn to tune the parameters of Support Vector Machines (SVM) Explore the concept of natural language processing (NLP) and recommendation systems Create a machine learning architecture from scratch Who this book is forMachine Learning Algorithms is for you if you are a machine learning engineer, data engineer, or junior data scientist who wants to advance in the field of predictive analytics and machine learning. Familiarity with R and Python will be an added advantage for getting the best from this book.
(source: Nielsen Book Data)

• Table of Contents Machine Learning Model Fundamentals Introduction to Semi-Supervised Learning Graph-based Semi-Supervised Learning Bayesian Networks and Hidden Markov Models EM algorithm and applications Hebbian Learning Advanced Clustering and Feature Extraction Ensemble Learning Neural Networks for Machine Learning Advanced Neural Models Auto-Encoders Generative Adversarial Networks Deep Belief Networks Introduction to Reinforcement Learning Policy estimation algorithms.
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Explore and master the most important algorithms for solving complex machine learning problems. Key Features Discover high-performing machine learning algorithms and understand how they work in depth. One-stop solution to mastering supervised, unsupervised, and semi-supervised machine learning algorithms and their implementation. Master concepts related to algorithm tuning, parameter optimization, and more Book DescriptionMachine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines. However, with the advancement in the technology and requirements of data, machines will have to be smarter than they are today to meet the overwhelming data needs; mastering these algorithms and using them optimally is the need of the hour. Mastering Machine Learning Algorithms is your complete guide to quickly getting to grips with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and will learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this book will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries such as scikit-learn. You will also learn how to use Keras and TensorFlow to train effective neural networks. If you are looking for a single resource to study, implement, and solve end-to-end machine learning problems and use-cases, this is the book you need. What you will learn Explore how a ML model can be trained, optimized, and evaluated Understand how to create and learn static and dynamic probabilistic models Successfully cluster high-dimensional data and evaluate model accuracy Discover how artificial neural networks work and how to train, optimize, and validate them Work with Autoencoders and Generative Adversarial Networks Apply label spreading and propagation to large datasets Explore the most important Reinforcement Learning techniques Who this book is forThis book is an ideal and relevant source of content for data science professionals who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. A basic knowledge of machine learning is preferred to get the best out of this guide.
(source: Nielsen Book Data)

• Frontmatter
• CONTENTS
• PREFACE
• WHAT IS THIS BOOK ABOUT, ACCORDING TO AI?
• INTRODUCTION: TECHNOLOGY MOVES FASTER THAN JOURNALISTIC STANDARDS
• 1. THE PROBLEM: A JOURNALISTIC MODEL IN TRANSITION
• 2. ENABLERS: THE AI TECHNOLOGIES DRIVING JOURNALISTIC CHANGE
• 3. WORKFLOW: A SCALABLE PROCESS FOR NEWSROOM TRANSFORMATION
• CONCLUSION
• ACKNOWLEDGMENTS
• NOTES
• BIBLIOGRAPHY
• INDEX

Will the use of artificial intelligence (AI), algorithms, and smart machines be the end of journalism as we know it-or its savior? In Newsmakers, Francesco Marconi, who has led the development of the Associated Press and Wall Street Journal's use of AI in journalism, offers a new perspective on the potential of these technologies. He explains how reporters, editors, and newsrooms of all sizes can take advantage of the possibilities they provide to develop new ways of telling stories and connecting with readers. Marconi analyzes the challenges and opportunities of AI through case studies ranging from financial publications using algorithms to write earnings reports to investigative reporters analyzing large data sets to outlets determining the distribution of news on social media. Newsmakers contends that AI can augment-not automate-the industry, allowing journalists to break more news more quickly while simultaneously freeing up their time for deeper analysis. Marshaling insights drawn from firsthand experience, Marconi maps a media landscape transformed by artificial intelligence for the better. In addition to considering the benefits of these new technologies, Marconi stresses the continuing need for editorial and institutional oversight. Newsmakers outlines the important questions that journalists and media organizations should consider when integrating AI and algorithms into their workflow. For journalism students as well as seasoned media professionals, Marconi's insights provide much-needed clarity and a practical roadmap for how AI can best serve journalism.
(source: Nielsen Book Data)

• Table of Contents Recognizing traffic signs using Convnets Annotating Images with Object Detection API Caption generation for images Building GANs for Conditional Image Creation Stock Price Prediction with LSTM Create & Train Machine Translation Systems Train and set up a Chatbot, able to discuss like a human Detecting Duplicate Quora Questions Building a TensorFlow Recommender Systems Video Games by Reinforcement learning.
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Leverage the power of Tensorflow to design deep learning systems for a variety of real-world scenarios Key Features Build efficient deep learning pipelines using the popular Tensorflow framework Train neural networks such as ConvNets, generative models, and LSTMs Includes projects related to Computer Vision, stock prediction, chatbots and more Book DescriptionTensorFlow is one of the most popular frameworks used for machine learning and, more recently, deep learning. It provides a fast and efficient framework for training different kinds of deep learning models, with very high accuracy. This book is your guide to master deep learning with TensorFlow with the help of 10 real-world projects. TensorFlow Deep Learning Projects starts with setting up the right TensorFlow environment for deep learning. Learn to train different types of deep learning models using TensorFlow, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and Generative Adversarial Networks. While doing so, you will build end-to-end deep learning solutions to tackle different real-world problems in image processing, recommendation systems, stock prediction, and building chatbots, to name a few. You will also develop systems that perform machine translation, and use reinforcement learning techniques to play games. By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow, and will be able to build and train your own deep learning models with TensorFlow confidently. What you will learn Set up the TensorFlow environment for deep learning Construct your own ConvNets for effective image processing Use LSTMs for image caption generation Forecast stock prediction accurately with an LSTM architecture Learn what semantic matching is by detecting duplicate Quora questions Set up an AWS instance with TensorFlow to train GANs Train and set up a chatbot to understand and interpret human input Build an AI capable of playing a video game by itself -and win it! Who this book is forThis book is for data scientists, machine learning developers as well as deep learning practitioners, who want to build interesting deep learning projects that leverage the power of Tensorflow. Some understanding of machine learning and deep learning, and familiarity with the TensorFlow framework is all you need to get started with this book.
(source: Nielsen Book Data)

• Table of Contents Data science: Bird's-eye view Data Modeling in Action - The Titanic Example Feature Engineering and Model Complexity - The Titanic Example Revisited Get Up and Running with TensorFlow Tensorflow in Action - Some Basic Examples Deep Feed-forward Neural Networks - Implementing Digit Classification Introduction to Convolutional Neural Networks Object Detection - CIFAR-10 Example Object Detection - Transfer Learning with CNNs Recurrent-Type Neural Networks - Language modeling Representation Learning - Implementing Word Embeddings Neural sentiment Analysis Autoencoders - Feature Extraction and Denoising Generative Adversarial Networks in Action - Generating New Images Face Generation and Handling Missing Labels Appendix - Implementing Fish Recognition.
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Grasp the fundamental concepts of deep learning using Tensorflow in a hands-on manner Key Features Get a first-hand experience of the deep learning concepts and techniques with this easy-to-follow guide Train different types of neural networks using Tensorflow for real-world problems in language processing, computer vision, transfer learning, and more Designed for those who believe in the concept of 'learn by doing', this book is a perfect blend of theory and code examples Book DescriptionDeep learning is a popular subset of machine learning, and it allows you to build complex models that are faster and give more accurate predictions. This book is your companion to take your first steps into the world of deep learning, with hands-on examples to boost your understanding of the topic. This book starts with a quick overview of the essential concepts of data science and machine learning which are required to get started with deep learning. It introduces you to Tensorflow, the most widely used machine learning library for training deep learning models. You will then work on your first deep learning problem by training a deep feed-forward neural network for digit classification, and move on to tackle other real-world problems in computer vision, language processing, sentiment analysis, and more. Advanced deep learning models such as generative adversarial networks and their applications are also covered in this book. By the end of this book, you will have a solid understanding of all the essential concepts in deep learning. With the help of the examples and code provided in this book, you will be equipped to train your own deep learning models with more confidence. What you will learn Understand the fundamentals of deep learning and how it is different from machine learning Get familiarized with Tensorflow, one of the most popular libraries for advanced machine learning Increase the predictive power of your model using feature engineering Understand the basics of deep learning by solving a digit classification problem of MNIST Demonstrate face generation based on the CelebA database, a promising application of generative models Apply deep learning to other domains like language modeling, sentiment analysis, and machine translation Who this book is forThis book targets data scientists and machine learning developers who wish to get started with deep learning. If you know what deep learning is but are not quite sure of how to use it, this book will help you as well. An understanding of statistics and data science concepts is required. Some familiarity with Python programming will also be beneficial.
(source: Nielsen Book Data)

• Advanced Computing in Engineering.- Computer Supported Construction Management.- Life-Cycle Design Support.- Monitoring and Control Algorithms in Engineering.- BIM and Engineering Ontologies.
• (source: Nielsen Book Data)

This double volume set ( LNAI 10863-10864) constitutes the refereed proceedings of the 25th International Workshop, EG-ICE 2018, held in Lausanne, Switzerland, in June 2018. The 58 papers presented in this volume were carefully reviewed and selected from 108 submissions. The papers are organized in topical sections on Advanced Computing in Engineering, Computer Supported Construction Management, Life-Cycle Design Support, Monitoring and Control Algorithms in Engineering, and BIM and Engineering Ontologies.
(source: Nielsen Book Data)

• Human-computer interaction.- Classification and recognition.- Navigation, mapping, robotics, and transports.- Video processing and retrieval.- Security, forensics, surveillance.- Image processing.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 18th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2017, held in Antwerp, Belgium, in September 2017. The 63 full papers presented in this volume were carefully selected from 134 submissions. They deal with human-computer interaction; classification and recognition; navigation, mapping, robotics, and transports; video processing and retrieval; security, forensics, surveillance; and image processing.
(source: Nielsen Book Data)

• Video Analysis.- Improving a Switched Vector Field Model for Pedestrian Motion Analysis.- Matrix Descriptor of Changes (MDC): Activity Recognition Based on
• Skeleton.- Person Re-identification with a Body Orientation-Specific Convolutional
• Neural Network.- Distributed Estimation of Vector Fields.- Clustering Based Reference Normal Pose for Improved Expression Recognition.- Detecting and Recognizing Salient Object in Videos.- Directional Beams of Dense Trajectories for Dynamic Texture Recognition.- Intrinsic Calibration of a Camera to a Line-Structured Light using a Single View of Two Spheres.- 3D Object-Camera and 3D Face-Camera Pose Estimation For Quadcopter Control: Application To Remote Labs.- Orthogonally-Divergent Fisheye Stereo.- Two-Camera Synchronization and Trajectory Reconstruction for a
• Touch Screen Usability Experiment.- Segmentation and classification.- Comparison of Co-segmentation Methods for Wildlife Photo-identification.- An Efficient Agglomerative Algorithm Cooperating with Louvain Method for Implementing Image Segmentation.- Robust Feature Descriptors For Object Segmentation Using Active Shape Models.- Foreground Background Segmentation in Front of Changing Footage on a Video Screen.- Multi-organ Segmentation of Chest CT Images in Radiation Oncology: Comparison of Standard and Dilated UNet.- Diffuse Low Grade Glioma NMR Assessment for Better Intra-operative Targeting Using Fuzzy Logic.- Identification of Saimaa rRnged Seal Individuals using Transfer Learning.- Remote sensing.- Enhanced Codebook Model and Fusion for Object Detection with Multispectral Images.- Unsupervised Perception Model for UAVs Landing Target Detection and Recognition.- Parallel and Distributed Local Fisher Discriminant Analysis to reduce Hyperspectral Images on Cloud Computing Architectures.- Bayesian Vehicle Detection using Optical Remote Sensing Images .- Integrating UAV in IoT for RoI Classification in Remote Images.- Biometrics.- Enhanced Line Local Binary Patterns (EL-LBP): An Efficient Image
• Representation for Face Recognition.- Single Sample Face Recognition by Sparse Recovery of Deep-learned Ida Features.- Recursive Chaining of Reversible Image-to-image Translators for Face
• Aging.- Automatically Selecting the Best Pictures for an Individualized Child Photo Album.- Face Detection in Painting using Deep Convolutional Neural Networks.- Robust Geodesic Skeleton Estimation from Body Single Depth.- Deep Learning.- Analysis of Neural Codes for Near-Duplicate Detection.- Optimum Network/Framework Selection from High-Level Specifications in Embedded Deep Learning Vision Applications.- Contour Propagation in CT scans with Convolutional Neural Networks.- Person Re-identification using Group Context.- Fingerprint Classification using Conic Radon Transform and Convolutional Neural Networks.- NoiseNet: Signal-dependent Noise Variance Estimation with Convolutional Neural Network.- Effective Training of Convolutional Neural Networks for Insect Image Recognition.- A Deep Learning Approach to Hair Segmentation and Color Extraction from Facial Images.- Learning Morphological Operators for Depth Completion.- Dealing with Topological Information within a Fully Convolutional Neural Network.- Coding and Compression.- L-infinite Predictive Coding of Depth.- An Application of Data Compression Models to Handwritten Digit Classification.- A Global Decoding Strategy with a Reduced-reference Metric Designed for the Wireless Transmission of JPWL .- Reconfigurable FPGA Implementation of the AVC Quantiser and Dequantiser Blocks.- Image Restauration and Reconstruction.- Large Parallax Image Stitching Using an Edge-Preserving Diffeomorphic Warping Process.- A Wavelet Based Image Fusion Method using Local Multiscale Image Regularity.- Optimising Data for Exemplar-based Inpainting.- Fast Light Field inpainting Propagation using Angular Warping and Color-guided Disparity Interpolation.- Fusing Omnidirectional Visual Data for Probability Matching Prediction.- Derivative Half Gaussian Kernels and Shock Filter.- Scanner Model Identification of Official Documents Using Noise Parameters Estimation in the Wavelet Domain.- Relocated Colour Contrast Occurrence Matrix and Adapted Similarity Measure for Colour Texture Retrieval.- I-HAZE: a Dehazing Benchmark with Real Hazy and Haze-free Indoor Images.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 19th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2018, held in Poitiers, France, in September 2018. The 52 full papers presented in this volume were carefully reviewed and selected from 91 submissions. They were organized in topical sections named: video analysis; segmentation and classification; remote sending; biometrics; deep learning; coding and compression; and image restauration and reconstruction.
(source: Nielsen Book Data)

• Knowledge Engineering.- Knowledge Representation and Reasoning under Uncertainty.- Multiagent Systems.- Game Theory and Economic Paradigms.- Game Playing and Interactive Entertainment.- Ambient Intelligence.- Machine Learning Applications.- Machine Learning Methods, Cognitive Modeling.- Cognitive Systems.- Planning and Scheduling.- Robotics.- Vision.- Natural Language Processing.- Human-Computer Interaction, AI in Education.- NLP and Knowledge Representation.- NLP and Machine Learning.- NLP and Text Mining.- Humans and AI.- Human-Aware AI.- General AI, Knowledge Engineering.- AI and the Web Applications.- Computational Sustainability and AI.- Heuristic Search and Optimization.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 16th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2018, held in Trujillo, Peru, in November 2018. The 41 papers presented were carefully reviewed and selected from 92 submissions. The papers are organized in the following topical sections: Knowledge Engineering, Knowledge Representation and Reasoning under Uncertainty., Multiagent Systems., Game Theory and Economic Paradigms, Game Playing and Interactive Entertainment, Ambient Intelligence, Machine Learning Methods, Cognitive Modeling, General AI, Knowledge Engineering, Computational Sustainability and AI, Heuristic Search and Optimization and much more.
(source: Nielsen Book Data)

• Artificial Intelligence.- Fuzzy Sets and Systems.- Evolutionary Algorithms.- Data Mining.- Applications.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 18th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2018, held in Granada, Spain, in October 2018. The 36 full papers presented were carefully selected from 240 submissions. The Conference of the Spanish Association of Artificial Intelligence (CAEPIA) is a biennial forum open to researchers from all over the world to present and discuss their latest scientific and technological advances in Antificial Intelligence (AI). Authors are kindly requested to submit unpublished original papers describing relevant research on AI issues from all points of view: formal, methodological, technical or applied.
(source: Nielsen Book Data)

• Compressing Bayesian Networks: Swarm-Based Descent, Efficiency, and Posterior Accuracy.- De-Causalizing NAT-Modeled Bayesian Networks for Inference Efficiency.- A Novel Evaluation Methodology for Assessing Off-Policy Learning Methods in Contextual Bandits.- Synthesizing Controllers: On the Correspondence Between LTL Synthesis and Non-Deterministic Planning.- Logic-Based Benders Decomposition for Two-Stage Flexible Flow Shop Scheduling with Unrelated Parallel Machines.- Advice-Based Exploration in Model-Based Reinforcement Learning.- Deep Super Learner: A Deep Ensemble for Classification Problem.- One Single Deep Bidirectional LSTM Network for Word Sense Disambiguation of Text Data.- MedFact: Towards Improving Veracity of Medical Information in Social Media Using Applied Machine Learning.- Re-ranking Candidate Lists for Improved Lexical Induction.- Analysis of Social Media Posts for Early Detection of Mental Health Conditions.- Motor Bearing Fault diagnosis Using Deep Convolutional Neural Networks with 2D Analysis of Vibration Signal.- Mobile App for Detection of Counterfeit Banknotes.- A Multi-agent Framework for Understanding Addiction.- Infusing Domain Knowledge to Improve the Detection of Alzheimer's Disease from Everyday Motion Behavior.- An Incremental Machine Learning Algorithm for Nuclear Forensics.- MML-Based Approach for Determining the Number of Topics in EDCM Mixture Models.- Constrained Bayesian Optimization for Problems with Piece-wise Smooth Constraints.- Dimensionality Reduction and Visualization by Doubly Kernelized Unit Ball Embedding.- Accelerated Gradient and Block-wise Gradient Methods for Big Data Factorization.- Learning Belief Revision Operators.- Solving Constraint Satisfaction Problems Using Firey Algorithms.- An AI Planning-Based Approach to the Multi-Agent Plan Recognition Problem.- Predicting Transportation Modes of GPS Trajectories Using Feature Engineering and Noise Removal.- Prediction of Container Damage Insurance Claims for Optimized Maritime Port Operations.- Drug-Target Interaction Network Predictions for Drug Repurposing Using LASSO-based Regularized Linear Classification Model.- Optimal Scheduling for Smart Charging of Electric Vehicles Using Dynamic Programming.- Combining MCTS and A3C for Prediction of Spatially Spreading Processes in Forest Wildfire Settings.- Text-based Detection of Unauthorized Users of Social Media Accounts.- N-gram Based Approach for Automatic Prediction of Essay Rubric Marks.- Matching Resumes to Job Descriptions with Stacked Models.- Towards a Comprehensive Evaluation of Recommenders: A Cognition-based Approach.- A Sentence-level Sparse Gamma Topic Model for Sentiment Analysis.- Topic Detection and document Similarity on Financial News.- Software Defect Prediction from Code Quality Measurements via Machine Learning.- Automated Scheduling: Reinforcement Learning Approach to Algorithm Policy Learning.- Estimating Vineyard Grape Yield from Images.- Real-time Deep Learning Pedestrians Classification on a Micro-controller.- A Unified Evaluation Framework for Recommender Systems.- Early Detection of Alzheimer's Disease Using Deep Learning.- Learning with Prior Domain Knowledge and Insufficient Annotated Data.- Predicting Crime Using Spatial Features.- A Tool for Defining and Simulating Storage Strategies on the Smart Grid.- Decision Assist for Self-Driving Cars.- Rule Mining and Prediction Using the Flek Machine
• A New Machine Learning Engine.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 31th Canadian Conference on Artificial Intelligence, Canadian AI 2018, held in Toronto, ON, Canada, in May 2018. The 16 regular papers and 18 short papers presented together with 7 Graduate Student Symposium papers and 4 Industry Track papers were carefully reviewed and selected from 72 submissions. The focus of the conference was on artificial intelligence research and advanced information and communications technology.
(source: Nielsen Book Data)

• Sorting -Permutations by -Operations.- Super Short Reversals on Both Gene Order and Intergenic Sizes.- Identifying Maximal Perfect Haplotype Blocks.- Sorting by Weighted Reversals and Transpositions.- Graph databases in Molecular Biology.- ViMT - Development of a Web-based Vivarium Management Tool.- An argumentation theory-based multiagent model to annotate proteins.- AutoModel: a client-server tool for intuitive and interactive homology modeling of protein-ligand complexes.- Detecting Acute Lymphoblastic Leukemia in Down Syndrome Patients using Convolutional Neural Networks on Preprocessed Mutated Datasets.- S2FS: Single score feature selection applied to the problem of distinguishing long non-coding RNAs from protein coding transcripts.- A Genetic Algorithm for Character State Live Phylogeny.- A workflow for predicting microRNAs targets via accessibility in Flavivirus genomes.- Parallel solution based on collective communication operations for phylogenetic bootstrapping in PhyML 3.0.
• (source: Nielsen Book Data)

• Sorting λ-Permutations by λ-Operations.- Super Short Reversals on Both Gene Order and Intergenic Sizes.- Identifying Maximal Perfect Haplotype Blocks.- Sorting by Weighted Reversals and Transpositions.- Graph databases in Molecular Biology.- ViMT
• Development of a Web-based Vivarium Management Tool.- An argumentation theory-based multiagent model to annotate proteins.- AutoModel: a client-server tool for intuitive and interactive homology modeling of protein-ligand complexes.- Detecting Acute Lymphoblastic Leukemia in Down Syndrome Patients using Convolutional Neural Networks on Preprocessed Mutated Datasets.- S2FS: Single score feature selection applied to the problem of distinguishing long non-coding RNAs from protein coding transcripts.- A Genetic Algorithm for Character State Live Phylogeny.- A workflow for predicting microRNAs targets via accessibility in Flavivirus genomes.- Parallel solution based on collective communication operations for phylogenetic bootstrapping in PhyML 3.0.

This book constitutes the refereed proceedings of the 11th Brazilian Symposium on Bioinformatics, BSB 2018, held in Rio de Janeiro, Brazil, in October/November 2018. The 13 revised full papers presented were carefully reviewed and selected from 26 submissions. The papers cover all aspects of bioinformatics and computational biology.
(source: Nielsen Book Data)

• Neural Computation.- Style Neutralization Generative Adversarial Classifier.- How Good a Shadow Neural Network is for Solving Non-linear Decision Making Problems.- Predicting Seminal Quality using Back-Propagation Neural Networks with Optimal Feature Subsets.- Deep Learning based Recommendation Algorithm in Online Medical Platform.- The Prediction Model of Saccade Target Based on LSTM-CRF for Chinese Reading.- Visual Cognition Inspired Vehicle Re-identification via Correlative Sparse Ranking with Multi-view Deep Features.- Fully Automatic Synaptic Cleft Detection and Segmentation From EM Images based on Deep Learning.- Deep Background Subtraction of Thermal and Visible Imagery for Pedestrian Detection in Videos.- Recent Advances in Deep Learning for Single Image Super-Resolution.- Using GAN to augment the synthesizing images from 3D models.- Deep Learning Based Single Image Super-resolution: A Survey.- DAU-GAN: Unsupervised object transfiguration via Deep Attention Unit.- Gravitational Search Optimized Hyperspectral Image Classification with Multilayer Perceptron.- 3-D Gabor Convolutional Neural Network for Damage Mapping from Post-earthquake High Resolution Images.- Biologically Inspired Systems.- A study of the role of attention in classifying covert and overt motor activities.- Attend to Knowledge: Memory-enhanced Attention Network for Image Captioning.- Direction Guided Cooperative Coevolutionary Differential Evolution Algorithm for Cognitive Modelling of Ray Tracing in Separable High Dimensional Space.- P300 brain waves instigated semi supervised video surveillance for inclusive security systems.- Motor Imagery EEG Recognition Based on FBCSP and PCA.- A Hybrid Brain-Computer Interface System Based on Motor Imageries and Eye-blinking.- Goal-directed behavior control based on the mechanism of neuromodulation.- Automated analysis of chest radiographs for cystic fibrosis scoring.- Mismatching Elimination Algorithm in SIFT Based on Function Fitting.- Novel Group Variable Selection for Salient Skull Region Selection and Sex Determination.- AFSnet: Fixation Prediction in Movie Scenes with Auxiliary Facial Saliency.- A Visual Attention Model based on Human Visual Cognition.- An Extended Common Spatial Pattern Framework for EEG-Based Emotion Classification.- CSA-DE/EDA: A Clonal Selection Algorithm Using Differential Evolution and Estimation of Distribution Algorithm.- Early Identification of Alzheimer's Disease Using An Ensemble of 3D Convolutional Neural Networks and Magnetic Resonance Imaging.- Image Recognition: Detection, Tracking and Classification.- A Novel Semi-Supervised Classification Method Based on Class Certainty of Samples.- Texture Profiles and Composite Kernel Frame for Hyperspectral Image Classification.- High-resolution Image Classification using the Dynamic Differential Evolutionary Algorithm Optimized Multi-Scale Kernel Support Vector Machine Method.- Eigenface Algorithm-Based Facial Expression Recognition in Conversations - An Experimental Study.- Unsupervised Hyperspectral Band Selection Based on maximum Information Entropy and Determinantal Point Process.- Dense Pyramid Network for Semantic Segmentation of High Resolution Aerial Imagery.- Gaussian-Staple for Robust Visual Object Real-Time Tracking.- Saliency-Weighted Global-Local Fusion for Person Re-identification.- Spectral and Spatial Kernel Extreme Learning Machine for Hyperspectral Image Classification.- Local-Global Extraction Unit for Person Re-Identification.- Robust image corner detection based on maximum point-to-chord distance.- Fabric Defect Detection based on Sparse Representation Image Decomposition.- Salient Superpixel Visual Tracking with Coarse-to-Fine Segmentation and Manifold Ranking.- A Regenerated Feature Extraction Method for Cross-modal Image Registration.- Bottom-up Saliency Prediction by Simulating End-stopping with Log-Gabor.- Learning Collaborative Sparse Correlation Filter for Real-time Multispectral Object Tracking.- Saliency Detection via Multi-view Synchronized Manifold Ranking.- Robust Visual Tracking via Sparse Feature Selection and Weight Dictionary Update.- Saliency Detection via Bidirectional Absorbing Markov Chain.- Pedestrian Detection Based on HOG, LBP Features and Visual Saliency.- Data Analysis and Natural Language Processing.- Hadoop Massive Small File Merging Technology Based on Visiting Hot-spot and Associated File Optimization.- A Reversible Data Hiding Scheme Using Compressive Sensing and Random Embedding.- An Abnormal Behavior Clustering Algorithm Based on K-means.- Manifold-regularized Adaptive Lasso.- SentiALG: Automated Corpus Annotation for Algerian Sentiment Analysis.- Self-Validated Story Segmentation of Chinese Broadcast News.- Improved Big Data Analytics Solution Using Deep Learning Model and Real-Time Sentiment Data Analysis Approach.- A Semi-Supervised Corpus Annotation for Saudi Sentiment Analysis using Twitter.- Exploiting Deep Learning for Persian Sentiment Analysis.- Big Data Analytics and Mining for Crime Data Analysis, Visualization and Prediction.- Comparison of Sentiment analysis approaches using modern Arabic and Sudanese Dialect.- An Intelligent Question Answering System for University Courses Based on BiLSTM and Keywords Similarity.- A Method for Calculating Patent Similarity Using Patent Model Tree Based on Neural Network.- An Optimal Solution of Storing and Processing Small Image Files on Hadoop.- A Big Data Analytics Platform for Information Sharing in the Connection between Administrative Law and Criminal Justice.- Applications.- RST I Invariant W Watermarking S Scheme Using Genetic Algorithm and DWT-SVD.- Application of VPN Based on L2TP and User's Access Rights in Campus Network.- Improved reversible data hiding in JPEG images based on interval correlation.- Representing RCPBAC(Role-Involved Conditional Purpose-based Access Control) in Ontology and SWRL.- Real-time Image Deformation Using Locally-weighted Moving Least Squares.- Machine-learning-based Malware Detection for Virtual Machine by Analyzing Opcode Sequence.- A Trusted Connection Authentication Reinforced By Bayes Algorithm.- A Proactive Caching Strategy Based on Deep Learning in EPC of 5G.- Dynamic Hybrid Approaching for Robust Hand-Eye Calibration.- Statistical Analysis Driven Optimized Deep Learning System for Intrusion Detection.- Comparing Event Related Arousal-Valence and Focus among Different Viewing Perspectives in VR gaming.- A Novel Loop Subdivision for Continuity Surface.- Making Industrial Robots Smarter with Adaptive Reasoning and Autonomous Thinking for Real-Time Tasks in Dynamic Environments: A Case Study.- Shading Structure-Guided Depth Image Restoration.- Machine Learning for Muon Imaging.- Night View Road Scene Enhancement based on Mixed Multi-Scale Retinex and Fractional differentiation.- Traffic Image defogging based on Bit-plane Decomposition.- The Simulation of Non-Gaussian Scattering on Rough Sea Surface.- Distributed Multi-node of Fuzzy Control Considering Adjacent Node Effect for Temperature Control.- An Improved Tentative Q learning Algorithm for Robot Learning.
• .
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 9th International Conference on Advances in Brain Inspired Cognitive Systems, BICS 2018, held in Xi'an, China, in July 2018. The 83 papers presented in this volume were carefully reviewed and selected from 137 submissions. The papers were organized in topical sections named: neural computation; biologically inspired systems; image recognition: detection, tracking and classification; data analysis and natural language processing; and applications.
(source: Nielsen Book Data)

This book constitutes the refereed conference proceedings of the 14th International Conference on Advances in Computer Entertainment Technology, ACE 2017, held in London, UK, in December 2017. The 59 full papers presented were selected from a total of 229 submissions. ACE is by nature a multi-disciplinary conference, therefore attracting people across a wide spectrum of interests and disciplines including computer science, design, arts, sociology, anthropology, psychology, and marketing. The main goal is to stimulate discussion in the development of new and compelling entertainment computing and interactive art concepts and applications. The chapter 'eSport vs irlSport' is open access under a CC BY 4.0 license via link.springer.com.
(source: Nielsen Book Data)

• Analytical Solution for "EinStein wurfelt nicht!" with One Stone.- Toward Solving EinStein wurfelt nicht!.- Analysis of Fred Horn's Gloop Puzzle.- Set Matching: An Enhancement of the Hales-Jewett Pairing Strategy Playing Hanabi Near-Optimally Optimal Play of the Farkle Dice GameDeep df-pn and its Efficient Implementations.- Improved Policy Networks for Computer Go.- Exploring Positional Linear Go.- Influence of Search Depth on Position Evaluation.- Evaluating Chess-like Games Using Generated Natural Language Descriptions.- Machine Learning in the Game of Breakthrough.- A Curling Agent Based on the Monte-Carlo Tree Search Considering the Similarity of the Best Action among Similar States.- Exploration Bonuses Based on Upper Confidence Bounds for Sparse Developing a 2048 Player with Backward Temporal Coherence Learning and Restart.- A Little Bit of Frustration Can Go a Long Way.- Automated Adaptation and Assessment in Serious Games: A Portable Tool for Supporting Learning.- An Analysis of Majority Voting in Homogeneous Groups for Checkers: Understanding Group Performance through Unbalance.- Yasol: An Open Source Solver for Quantified Mixed Integer Programs.
• (source: Nielsen Book Data)

• Analytical Solution for EinStein w⦥lt nicht!" with One Stone
• Toward Solving EinStein w⦥lt nicht!
• Analysis of Fred Horn's Gloop Puzzle
• Set Matching: An Enhancement of the Hales-Jewett Pairing Strategy Playing Hanabi Near-Optimally Optimal Play of the Farkle Dice GameDeep df-pn and its Efficient Implementations
• Improved Policy Networks for Computer Go
• Exploring Positional Linear Go
• Influence of Search Depth on Position Evaluation
• Evaluating Chess-like Games Using Generated Natural Language Descriptions
• Machine Learning in the Game of Breakthrough
• A Curling Agent Based on the Monte-Carlo Tree Search Considering the Similarity of the Best Action among Similar States
• Exploration Bonuses Based on Upper Confidence Bounds for Sparse Developing a 2048 Player with Backward Temporal Coherence Learning and Restart
• A Little Bit of Frustration Can Go a Long Way
• Automated Adaptation and Assessment in Serious Games: A Portable Tool for Supporting Learning
• An Analysis of Majority Voting in Homogeneous Groups for Checkers: Understanding Group Performance through Unbalance
• Yasol: An Open Source Solver for Quantified Mixed Integer Programs.

This book constitutes the refereed conference proceedings of the 15th International Conference, ACG 2017, held in Leiden, The Netherlands, in July 2017.The 19 revised full papers were selected from 23 submissions and cover a wide range of computer games. They are grouped in four classes according to the order of publication: games and puzzles, go and chess, machine learning and MCTS, and gaming.
(source: Nielsen Book Data)

• Secure messaging.- Implementations and physical attacks prevention.- Authenticated and format-preserving encryption.- Cryptoanalysis.- Searchable encryption and differential privacy.- Secret sharing.- Encryption.- Symmetric cryptography.- Proofs of work and proofs of Stake.- Proof tools.- Key exchange.- Symmetric cryptoanalysis.- Hashes and random oracles.- Trapdoor functions.- Round optimal MPC.- Foundations.- Lattices.- Lattice-based ZK.- Efficient MPC.- Quantum cryptography.- MPC.- Garbling.- Information-theoretic MPC.- Oblivious transfer.- Non-malleable codes.- Zero knowledge.- Obfuscation.
• (source: Nielsen Book Data)

The three volume-set, LNCS 10991, LNCS 10992, and LNCS 10993, constitutes the refereed proceedings of the 38th Annual International Cryptology Conference, CRYPTO 2018, held in Santa Barbara, CA, USA, in August 2018. The 79 revised full papers presented were carefully reviewed and selected from 351 submissions. The papers are organized in the following topical sections: secure messaging; implementations and physical attacks prevention; authenticated and format-preserving encryption; cryptoanalysis; searchable encryption and differential privacy; secret sharing; encryption; symmetric cryptography; proofs of work and proofs of stake; proof tools; key exchange; symmetric cryptoanalysis; hashes and random oracles; trapdoor functions; round optimal MPC; foundations; lattices; lattice-based ZK; efficient MPC; quantum cryptography; MPC; garbling; information-theoretic MPC; oblivious transfer; non-malleable codes; zero knowledge; and obfuscation.
(source: Nielsen Book Data)

The three volumes LNCS 10820, 10821, and 10822 constitute the thoroughly refereed proceedings of the 37th Annual International Conference on the Theory and Applications of Cryptographic Techniques, EUROCRYPT 2018, held in Tel Aviv, Israel, in April/May 2018. The 69 full papers presented were carefully reviewed and selected from 294 submissions. The papers are organized into the following topical sections: foundations; lattices; random oracle model; fully homomorphic encryption; permutations; galois counter mode; attribute-based encryption; secret sharing; blockchain; multi-collision resistance; signatures; private simultaneous messages; masking; theoretical multiparty computation; obfuscation; symmetric cryptanalysis; zero-knowledge; implementing multiparty computation; non-interactive zero-knowledge; anonymous communication; isogeny; leakage; key exchange; quantum; non-malleable codes; and provable symmetric cryptography. .
(source: Nielsen Book Data)

The three volumes LNCS 10820, 10821, and 10822 constitute the thoroughly refereed proceedings of the 37th Annual International Conference on the Theory and Applications of Cryptographic Techniques, EUROCRYPT 2018, held in Tel Aviv, Israel, in April/May 2018. The 69 full papers presented were carefully reviewed and selected from 294 submissions. The papers are organized into the following topical sections: foundations; lattices; random oracle model; fully homomorphic encryption; permutations; galois counter mode; attribute-based encryption; secret sharing; blockchain; multi-collision resistance; signatures; private simultaneous messages; masking; theoretical multiparty computation; obfuscation; symmetric cryptanalysis; zero-knowledge; implementing multiparty computation; non-interactive zero-knowledge; anonymous communication; isogeny; leakage; key exchange; quantum; non-malleable codes; and provable symmetric cyptography. .
(source: Nielsen Book Data)

The three volumes LNCS 10820, 10821, and 10822 constitute the thoroughly refereed proceedings of the 37th Annual International Conference on the Theory and Applications of Cryptographic Techniques, EUROCRYPT 2018, held in Tel Aviv, Israel, in April/May 2018. The 69 full papers presented were carefully reviewed and selected from 294 submissions. The papers are organized into the following topical sections: foundations; lattices; random oracle model; fully homomorphic encryption; permutations; galois counter mode; attribute-based encryption; secret sharing; blockchain; multi-collision resistance; signatures; private simultaneous messages; masking; theoretical multiparty computation; obfuscation; symmetric cryptanalysis; zero-knowledge; implementing multiparty computation; non-interactive zero-knowledge; anonymous communication; isogeny; leakage; key exchange; quantum; non-malleable codes; and provable symmetric cyptography. .
(source: Nielsen Book Data)

• Invited Papers.- Information extraction and Integration.- Data Mining and Knowledge Discovery.- Indexing, Query Processing and Optimization.- Data Quality and Data Cleansing.- Distributed Data Platforms, Including Cloud Data Systems, Key-Value Stores, and Big Data Systems.- Streaming Data Analysis.- Web, XML and Semi-Structured Databases.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 22nd European Conference on Advances in Databases and Information Systems, ADBIS 2018, held in Budapest, Hungary, in September 2018.The 17 regular papers presented together with two invited papers were carefully selected and reviewed from numerous submissions. The papers are organized in topical sections such as information extraction and integration; data mining and knowledge discovery; indexing, query processing and optimization; data quality and data cleansing; distributed data platforms, including cloud data systems, key-value stores, and big data systems; and streaming data analysis; web, XML and semi-structured databases.
(source: Nielsen Book Data)

• Topic Modelling.- Health Applications.- Deep Learning.- Evulations and user behavoir.- Representation.- Recommendation.- Retrieval.- Learning and Classification.- Microblogs. .
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 40th European Conference on IR Research, ECIR 2018, held in Grenoble, France, in March 2018. The 39 full papers and 39 short papers presented together with 6 demos, 5 workshops and 3 tutorials, were carefully reviewed and selected from 303 submissions. Accepted papers cover the state of the art in information retrieval including topics such as: topic modeling, deep learning, evaluation, user behavior, document representation, recommendation systems, retrieval methods, learning and classication, and micro-blogs.
(source: Nielsen Book Data)

• Intro
• PC Chairs' Preface
• General Chairs' Preface
• Organization
• Contents
• Part I
• Classification and Supervised Machine Learning
• Classifier Risk Estimation Under Limited Labeling Resources
• 1 Introduction
• 2 Problem Formulation
• 3 Estimation Methods
• 3.1 Simple Random Sampling
• 3.2 Stratified Sampling
• 3.3 Allocation Methods for Stratified Sampling
• 3.4 Comparison of Variances
• 3.5 Stratification Methods
• 4 Experiments and Results
• 4.1 Proportional and Equal Allocation
• 4.2 Optimal Allocation
• 4.3 Dependence on True Accuracy

• 5 Discussions and Conclusions
• References
• Social Stream Classification with Emerging New Labels
• 1 Introduction
• 2 Related Work
• 3 Preliminaries
• 4 The Proposed Framework
• 4.1 NL-Forest: Training Process
• 4.2 NL-Forest: Deployment
• 4.3 NL-Forest: Model Update
• 4.4 Model Complexity
• 5 Experiment
• 5.1 Experimental Setup
• 5.2 Simulated Data Stream
• 5.3 Real Data Stream
• 5.4 Sensitivity of Parameters
• 6 Conclusion
• References
• Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules
• 1 Introduction
• 2 Preliminaries

• 2.1 Multi-label Rule Learning
• 2.2 Bipartition Evaluation Functions
• 3 Properties of Multi-label Evaluation Measures
• 4 Algorithm for Learning Multi-label Head Rules
• 5 Evaluation
• 6 Related Work
• 7 Conclusions
• References
• Modeling Label Interactions in Multi-label Classification: A Multi-structure SVM Perspective
• 1 Introduction
• 2 A Quick Review of Existing Work
• 3 Multi-structure SVM
• 4 Dual MSSVM and an Efficient Optimization Algorithm
• 5 Experiments
• 6 Conclusion
• References
• Sentiment Classification Using Neural Networks with Sentiment Centroids

• 1 Introduction
• 2 Related Work
• 2.1 Sentiment Features Learning
• 2.2 Neural Networks for Sentiment Classification
• 3 Our Approach
• 3.1 Text Sequence Encoder Models
• 3.2 Sentiment Centriods Constraint
• 4 Experiments
• 4.1 Datasets
• 4.2 Evaluation Metrics
• 4.3 Training Settings
• 4.4 Sentence-Level Classification
• 4.5 Document-Level Classification
• 4.6 The Effect of Sentiment Centroids
• 5 Conclusion and Future Work
• References
• Random Pairwise Shapelets Forest
• 1 Introduction
• 2 Random Pairwise Shapelets Forest
• 2.1 Providing More Information by Combination

• 2.2 Proposed Algorithm
• 3 Decomposed Mean Decrease Impurity
• 4 Experiment and Evaluation
• 4.1 Experimental Setup
• 4.2 Predictive Performance
• 4.3 Computational Performance
• 5 Case Studies
• 5.1 GunPoint
• 5.2 ArrowHead
• 6 Conclusion
• References
• A Locally Adaptive Multi-Label k-Nearest Neighbor Algorithm
• 1 Introduction
• 1.1 Background
• 1.2 Motivation
• 1.3 Paper Organization
• 2 Related Work
• 3 Methodology
• 4 Experiment
• 4.1 Experiment Setup
• 4.2 Results
• 5 Conclusion
• References
• Classification with Reject Option Using Conformal Prediction

This three-volume set, LNAI 10937, 10938, and 10939, constitutes the thoroughly refereed proceedings of the 22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018, held in Melbourne, VIC, Australia, in June 2018. The 164 full papers were carefully reviewed and selected from 592 submissions. The volumes present papers focusing on new ideas, original research results and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems and the emerging applications. .
(source: Nielsen Book Data)

This three-volume set, LNAI 10937, 10938, and 10939, constitutes the thoroughly refereed proceedings of the 22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018, held in Melbourne, VIC, Australia, in June 2018. The 164 full papers were carefully reviewed and selected from 592 submissions. The volumes present papers focusing on new ideas, original research results and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems and the emerging applications. .
(source: Nielsen Book Data)

• Intro
• PC Chairs' Preface
• General Chairs' Preface
• Organization
• Contents
• Part III
• Feature Learning and Data Mining Process
• Discovering High Utility Itemsets Based on the Artificial Bee Colony Algorithm
• Abstract
• 1 Introduction
• 2 Preliminaries
• 2.1 Problem of HUI Mining
• 2.2 ABC Algorithm
• 3 Mining HUIs Using the ABC
• 3.1 Bitmap Item Information Representation
• 3.2 Modeling HUI Discovery Using the ABC
• 3.3 Direct Nectar Source Generation for Scout Bees
• 3.4 Algorithm Description
• 4 Performance Evaluation
• 4.1 Experimental Environment and Datasets

• 4.2 Running Time
• 4.3 Number of Discovered HUIs
• 4.4 Convergence
• 5 Conclusions
• Acknowledgments
• References
• A Scalable and Efficient Subgroup Blocking Scheme for Multidatabase Record Linkage
• 1 Introduction
• 2 Related Work
• 3 Subgroup Blocking Process
• 3.1 Potential Candidate Grouping
• 3.2 Candidate Graph Construction
• 3.3 Subgroup Candidate Generation
• 4 Analysis of Subgroup Blocking
• 5 Experiments and Discussion
• 6 Conclusions and Future Work
• References
• Efficient Feature Selection Framework for Digital Marketing Applications
• 1 Introduction

• 2 Related Work
• 3 Overall Framework
• 4 Feature Exploration Using Semantic Ranking and Generative Filtering
• 4.1 The Semantic Ranking Guided Feature Selection Algorithm
• 4.2 Combining with Generative Filtering for Better Performance
• 5 Progressive Sampling and Feature Selection Framework
• 5.1 Coarse to Fine Implementation
• 5.2 Time and Space Reduction Through Progressive Sampling
• 6 Experiments and Discussion
• 7 Conclusion
• References
• Dynamic Feature Selection Algorithm Based on Minimum Vertex Cover of Hypergraph
• 1 Introduction
• 2 Preliminaries

• 3 Dynamic Feature Selection Algorithm Based on Minimum Vertex Cover of Hypergraph
• 3.1 The Induced Hypergraph
• 3.2 Updating Minimum Vertex Cover of Hypergraph
• 3.3 Dynamic Feature Selection Algorithm
• 4 Experimental Analysis
• 5 Conclusions
• References
• Feature Selection for Multiclass Binary Data
• 1 Introduction
• 2 Related Work
• 3 Preliminary Concepts
• 4 Problem Formulation
• 5 Our Approach
• 5.1 Measuring the Sparse Value Distribution
• 5.2 New Feature Selection Objective
• 5.3 A Greedy Feature Selection Approach
• 6 Evaluation
• 6.1 Experimental Results

• 6.2 Evaluation Insights
• 7 Conclusion
• References
• Scalable Model-Based Cascaded Imputation of Missing Data
• 1 Introduction
• 2 Related Work
• 3 Proposed Method
• 4 Methodology
• 5 Discussion of Experimental Results
• 6 Conclusions
• References
• On Reducing Dimensionality of Labeled Data Efficiently
• 1 Introduction
• 2 Related Work
• 2.1 Metric Learning
• 2.2 Nonlinear Algorithms for Collapsing Classes
• 2.3 Parametric Embedding
• 3 Nonlinear Parametric Embedding
• 4 Evaluation
• 4.1 Experiment Settings
• 4.2 Results
• 5 Conclusion
• References

This three-volume set, LNAI 10937, 10938, and 10939, constitutes the thoroughly refereed proceedings of the 22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018, held in Melbourne, VIC, Australia, in June 2018. The 164 full papers were carefully reviewed and selected from 592 submissions. The volumes present papers focusing on new ideas, original research results and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems and the emerging applications. .
(source: Nielsen Book Data)

• Introduction.- The metaheuristic algorithm of the social-spider.- Calibration of Fractional Fuzzy Controllers by using the Social-spider method.- The metaheuristic algorithm of the Locust-search.- Identification of fractional chaotic systems by using the Locust Search Algorithm.- The States of Matter Search (SMS).- Multimodal States of Matter search.- Metaheuristic algorithms based on Fuzzy Logic.
• (source: Nielsen Book Data)

This book explores new alternative metaheuristic developments that have proved to be effective in their application to several complex problems. Though most of the new metaheuristic algorithms considered offer promising results, they are nevertheless still in their infancy. To grow and attain their full potential, new metaheuristic methods must be applied in a great variety of problems and contexts, so that they not only perform well in their reported sets of optimization problems, but also in new complex formulations. The only way to accomplish this is to disseminate these methods in various technical areas as optimization tools. In general, once a scientist, engineer or practitioner recognizes a problem as a particular instance of a more generic class, he/she can select one of several metaheuristic algorithms that guarantee an expected optimization performance. Unfortunately, the set of options are concentrated on algorithms whose popularity and high proliferation outstrip those of the new developments. This structure is important, because the authors recognize this methodology as the best way to help researchers, lecturers, engineers and practitioners solve their own optimization problems.
(source: Nielsen Book Data)

• Best Paper Candidate.- Video Coding.- Image Super-resolution, Debluring, and Dehazing.- Person Identity and Emotion.- Tracking and Action Recognition.- Detection and Classification.- Multimedia Signal Reconstruction and Recovery.- Text and Line Detection/Recognition.- Social Media.- 3D and Panoramic Vision.- Deep Learning for Signal Processing and Understanding.- Large-Scale Multimedia Affective Computing.- Sensor-enhanced Multimedia Systems.- Content Analysis.- Coding, Compression, Transmission, and Processing.
• (source: Nielsen Book Data)

The two-volume set LNCS 10735 and 10736 constitutes the thoroughly refereed proceedings of the 18th Pacific-Rim Conference on Multimedia, PCM 2017, held in Harbin, China, in September 2017. The 184 full papers presented were carefully reviewed and selected from 264 submissions. The papers are organized in topical sections on: Best Paper Candidate; Video Coding; Image Super-resolution, Debluring, and Dehazing; Person Identity and Emotion; Tracking and Action Recognition; Detection and Classification; Multimedia Signal Reconstruction and Recovery; Text and Line Detection/Recognition; Social Media; 3D and Panoramic Vision; Deep Learning for Signal Processing and Understanding; Large-Scale Multimedia Affective Computing; Sensor-enhanced Multimedia Systems; Content Analysis; Coding, Compression, Transmission, and Processing.
(source: Nielsen Book Data)

• Best Paper Candidate.- Video Coding.- Image Super-resolution, Debluring, and Dehazing.- Person Identity and Emotion.- Tracking and Action Recognition.- Detection and Classification.- Multimedia Signal Reconstruction and Recovery.- Text and Line Detection/Recognition.- Social Media.- 3D and Panoramic Vision.- Deep Learning for Signal Processing and Understanding.- Large-Scale Multimedia Affective Computing.- Sensor-enhanced Multimedia Systems.- Content Analysis.- Coding, Compression, Transmission, and Processing.
• (source: Nielsen Book Data)

The two-volume set LNCS 10735 and 10736 constitutes the thoroughly refereed proceedings of the 18th Pacific-Rim Conference on Multimedia, PCM 2017, held in Harbin, China, in September 2017. The 184 full papers presented were carefully reviewed and selected from 264 submissions. The papers are organized in topical sections on: Best Paper Candidate; Video Coding; Image Super-resolution, Debluring, and Dehazing; Person Identity and Emotion; Tracking and Action Recognition; Detection and Classification; Multimedia Signal Reconstruction and Recovery; Text and Line Detection/Recognition; Social Media; 3D and Panoramic Vision; Deep Learning for Signal Processing and Understanding; Large-Scale Multimedia Affective Computing; Sensor-enhanced Multimedia Systems; Content Analysis; Coding, Compression, Transmission, and Processing.
(source: Nielsen Book Data)

• Multimedia content analysis.- Multimedia signal processing and communications.- Multimedia applications and services.
• (source: Nielsen Book Data)

The three-volume set LNCS 101164, 11165, and 11166 constitutes the refereed proceedings of the 19th Pacific-Rim Conference on Multimedia, PCM 2018, held in Hefei, China, in September 2018. The 209 regular papers presented together with 20 special session papers were carefully reviewed and selected from 452 submissions. The papers cover topics such as: multimedia content analysis; multimedia signal processing and communications; and multimedia applications and services.
(source: Nielsen Book Data)

• Multimedia content analysis.- Multimedia signal processing and communications.- Multimedia applications and services.
• (source: Nielsen Book Data)

The three-volume set LNCS 101164, 11165, and 11166 constitutes the refereed proceedings of the 19th Pacific-Rim Conference on Multimedia, PCM 2018, held in Hefei, China, in September 2018. The 209 regular papers presented together with 20 special session papers were carefully reviewed and selected from 452 submissions. The papers cover topics such as: multimedia content analysis; multimedia signal processing and communications; and multimedia applications and services.
(source: Nielsen Book Data)

• Multimedia content analysis.- Multimedia signal processing and communications.- Multimedia applications and services.
• (source: Nielsen Book Data)

The three-volume set LNCS 101164, 11165, and 11166 constitutes the refereed proceedings of the 19th Pacific-Rim Conference on Multimedia, PCM 2018, held in Hefei, China, in September 2018. The 209 regular papers presented together with 20 special session papers were carefully reviewed and selected from 452 submissions. The papers cover topics such as: multimedia content analysis; multimedia signal processing and communications; and multimedia applications and services.
(source: Nielsen Book Data)

• Cognition computation.- Models, methods and algorithms.- Clustering, classifiation, learning, and forecasting.- Neurodynamics, complex systems, and chaos.- Multi-agent systems and game theory.- Signal, image and video processing.- Intelligent control, robotics and hardware.- Bio-signal, bioinformatics and biomedical engineering.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 15th International Symposium on Neural Networks, ISNN 2018, held in Minsk, Belarus in June 2018.The 98 revised regular papers presented in this volume were carefully reviewed and selected from 214 submissions. The papers cover many topics of neural network-related research including intelligent control, neurodynamic analysis, bio-signal, bioinformatics and biomedical engineering, clustering, classification, forecasting, models, algorithms, cognitive computation, machine learning, and optimization. .
(source: Nielsen Book Data)

• Hammer or Tongs: How Best to Build Agent-Based Models.- Towards Autonomous AI Systems for Resource Management: Applications in Industry and Lessons Learned.- A Holonic Multi-Agent Based Diagnostic Decision Support System for Computer-Aided History and Physical Examination.- A Resilient Agent-Based Re-Organizing Traffic Network for Urban Evacuations.- Coping with Bad Agent Interaction Protocols when Monitoring Partially Observable Multiagent Systems.- SimFI: a Transmission Agent-Based Model of Two Interacting Pathogens.- Electric vehicles fleet for frequency regulation using multi-agent system.- Using Run-Time Biofeedback during Virtual Agent-Based Aggression De-escalation Training.- Multi-Agent Systems and Blockchain: Results from a Systematic Literature Review.- A Model and Platform for Building Agent-Based Pervasive Mixed Reality Systems.- Classification of Spatio-temporal Trajectories based on Support Vector Machines.- A Cooperative Multi-Agent System for Wind Power Forecasting.- Cooperative agents for discovering Pareto-optimal classifiers under dynamic costs.- Unemployment expectations in an agent-based model with education.- Towards reducing complexity of multi-agent simulations by applying model-driven techniques.- Environment for identification of significant subjects on information portals.- Evaluation of Multi-Agent Coordination on Embedded Systems.- AgentUD
• E17: A Genetic Algorithm to Optimize the Parameters of an Electricity Tariff in a Smart Grid Environment.- A first step towards a general-purpose distributed cyberdefense system.- A Network-Oriented Adaptive Agent Model for Learning Regulation of a Highly Sensitive Person's Response.- SAIL: a Social Artificial Intelligence Layer for Human-Machine Teaming.- Agent-Based Model of Smart Social Networking-Driven Recommendations System for Internet of Vehicles.- MAXIM-GPRT: A Simulator of local Schedulers, Negotiations, and Communication for Multi-Agent Systems in General-Purpose and Real-Time Scenarios. -Managing Bad AIPs with RIVERtools.- Developing Agent-Based Pervasive Mixed Reality Systems: the MiRAgE Framework.- Generating unemployment expectations of the "man in the street".- MASAP: Multi-Agent Simulation of Air Pollution.- Analysis of Agent-Based Parallelism for Use in Clustering and Classification Applications.- HVUAN - A rapid-development framework for Spanish-speaking virtual humans.- ATHOS - A domain-specific language for multi-agent simulations.- MASEV: A MAS for the Analysis of Electric Vehicle Charging Stations Location.- On the way of protecting MANETs against security threats: a proactive approach.- Coordinated UAV Search and Rescue Application with JaCaMo.- AgentOil: a multi-agent-based simulation of the drilling process in oilfields.- A social robot assisting in cognitive stimulation therapy.- Swarm of Satellites: Multi-Agent Mission Scheduler for Constellation of Earth Remote Sensing Satellites.- Demonstration of Tools Control Center for Multi-Agent Energy Systems Simulation.- MATISSE 3
• .0: A Large-Scale Multi-Agent Simulation System for Intelligent Transportation Systems.- The SAIL Framework for Implementing Human-Machine Teaming Concepts.- A novel web services infrastructure leveraging agent oriented middleware environment for realizing agent oriented information system models.- A Demonstration of Simulation Modeling for SIoV Recommendations System.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 16th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2018, held in Toledo, Spain, in June 2018. The 20 regular and 19 demo papers presented in this volume were carefully reviewed and selected from 57 submissions. They deal with the application and validation of agent-based models, methods, and technologies in a number of key applications areas, such as: energy and security; engineering and tools; evaluation and ethics; negotiation and organisations; personalization and learning; simulation applications; simulation platforms; social networks and humans. The book also contains two invited talks in full paper length. .
(source: Nielsen Book Data)

• Theories and models of swarm intelligence.- ant colony optimization
• particle swarm optimization.- artificial bee colony algorithms.- genetic algorithms.- differential evolution.- fireworks algorithms.- bacterial foraging optimization.- artificial immune system.- hydrologic cycle optimization.- other swarm-based optimization algorithms.- hybrid optimization algorithms.- multi-objective optimization.- large-scale global optimization.- multi-agent systems.- swarm robotics
• fuzzy logic approaches.- planning and routing problems.- recommendation in social media.- prediction.- classification.- finding patterns.- image enhancement.- deep learning.
• (source: Nielsen Book Data)

The two-volume set of LNCS 10941 and 10942 constitutes the proceedings of the 9th International Conference on Advances in Swarm Intelligence, ICSI 2018, held in Shanghai, China, in June 2018. The total of 113 papers presented in these volumes was carefully reviewed and selected from 197 submissions. The papers were organized in topical sections as follows: theories and models of swarm intelligence; ant colony optimization; particle swarm optimization; artificial bee colony algorithms; genetic algorithms; differential evolution; fireworks algorithms; bacterial foraging optimization; artificial immune system; hydrologic cycle optimization; other swarm-based optimization algorithms; hybrid optimization algorithms; multi-objective optimization; large-scale global optimization; multi-agent systems; swarm robotics; fuzzy logic approaches; planning and routing problems; recommendation in social media; prediction, classification; finding patterns; image enhancement; deep learning. .
(source: Nielsen Book Data)

• ST : computational bioimaging ; Automatic registration of serial cerebral angiography : a comparative review / Alice Tang, Zhiyuan Zhang, and Fabien Scalzo
• Skull stripping using confidence segmentation convolution neural network / Kaiyuan Chen, Jingyue Shen, and Fabien Scalzo
• Skin cancer segmentation using a unified Markov random field / Omran Salih and Serestina Viriri
• Heart modeling by convexity preserving segmentation and convex shape decomposition / Xue Shi, Lijun Tang, Shaoxiang Zhang, and Chunming Li
• Computer graphics I ; PSO-based Newton-like method and iteration processes in the generation of artistic patterns / Ireneusz Gościniak and Krzysztof Gdawiec
• An evaluation of smoothing and remeshing techniques to represent the evolution of real-world phenomena / José Duarte, Paulo Dias, and José Moreira
• Biomimetic perception learning for human sensorimotor control / Masaki Nakada, Honglin Chen, and Demetri Terzopoulos
• Porous structure design in tissue engineering using anisotropic radial basis functions / Ye Guo, Ke Liu, and Zeyun Yu

• Visual surveillance ; Accurate and efficient non-parametric background detection for video surveillance / William Porr, James Easton, Alireza Tavakkoli, Donald Loffredo, and Sean Simmons
• A low-power neuromorphic system for real-time visual activity recognition / Deepak Khosla, Ryan Uhlenbrock, and Yang Chen
• Video-based human action recognition using kernel relevance analysis / Jorge Fernández-Ramírez, Andrés Álvarez-Meza, and Álvaro Orozco-Gutiérrez
• Robust incremental hidden conditional random fields for human action recognition / Michalis Vrigkas, Ermioni Mastora, Christophoros Nikou, and Ioannis A. Kakadiaris
• Pattern recognition ; Rotation symmetry object classification using structure constrained convolutional neural network / Seunghwa Yu and Seugnkyu Lee
• A Hough space feature for vehicle detection / Chunling Tu and Shengzhi Du
• Gender classification based on facial shape and texture features / Mayibongwe H. Bayana, Serestina Viriri, and Raphael Angulu
• Authentication-based on biomechanics of finger movements captured using optical motion-capture / Brittany Lewis, Christopher J. Nycz, Gregory S. Fischer, and Krishna K. Venkatasubramanian
• Specific document sign location detection based on point matching and clustering / Huaixin Xiong

• Virtual reality I ; Training in virtual environments for hybrid power plant / Max G. Chiluisa, Rubén D. Mullo, and Víctor H. Andaluz
• Visualizing viewpoint movement on driving by space information rendering / Satoru Morita
• Virtual reality system for children lower limb strengthening with the use of electromyographic sensors / Eddie E. Galarza, Marco Pilatasig, Eddie D. Galarza, Victoria M. López, Pablo A. Zambrano, Jorge Buele, and Jhon Espinoza
• A comparative study of virtual UI for risk assessment and evaluation / Naila Bushra, Daniel Carruth, and Shuchisnigdha Deb
• Sensory fusion and intent recognition for accurate gesture recognition in virtual environments / Sean Simmons, Kevin Clark, Alireza Tavakkoli, and Donald Loffredo
• Deep learning I ; Accuracy of a driver-assistance system in a collision scenario / Waqar Khan and Reinhard Klette
• Classify broiler viscera using an iterative approach on noisy labeled training data / Anders Jørgensen, Jens Fagertun, and Thomas B. Moeslund
• Instance-level object recognition using deep temporal coherence / Miguel Lagunes-Fortiz, Dima Damen, and Walterio Mayol-Cuevas
• DUPL-VR : deep unsupervised progressive learning for vehicle re-identification / Raja Muhammad Saad Bashir, Muhammad Shahzad, and Muhammad Moazam Fraz

• Motion and tracking ; Particle filter based tracking and mapping / Nils Höhner, Anna Katharina Hebborn, and Stefan Müller
• Multi-branch Siamese networks with online selection for object tracking / Zhenxi Li, Guillaume-Alexandre Bilodeau, and Wassim Bouachir
• Deep convolutional correlation filters for forward-backward visual tracking / Yong Wang, Robert Laganière, Daniel Laroche, Ali Osman Ors, Xiaoyin Xu, and Changyun Zhu
• The bird gets caught by the WORM : tracking multiple deformable objects in noisy environments using weight ORdered logic maps / Debajyoti Karmaker, Ingo Schiffner, Michael Wilson, and Mandyam V. Srinivasan
• A Mumford Shah style unified framework for layering : pitfalls and solutions / Fareed ud din Mehmood Jafri, Martin Fritz Mueller, and Anthony Joseph Yezzi
• Visualization ; Visualization of parameter sensitivity of 2D time-dependent flow / Karsten Hanser, Ole Klein, Bastian Rieck, Bettina Wiebe, Tobias Selz, Marian Piatkowski, Antoni Sagristá, Boyan Zheng, Mária Lucácová-Medvidová, George Craig, Heike Leitte, and Filip Sadlo
• Non-stationary generalized Wishart processes for enhancing resolution over diffusion tensor fields / Jhon F. Cuellar-Fierro, Hernán Darío Vargas-Cardona, Andrés M. Álvarez, Álvaro A. Orozco, and Mauricio A. Álvarez
• Reduced-reference image quality assessment based on improved local binary pattern / Xi-kui Miao, Dah-Jye Lee, Xiang-zheng Cheng, and Xiao-yu Yang
• Web system for visualization of weather data of the hydrometeorological network of Tungurahua, Ecuador / Jaime Santana, Fernando A. Chicaiza, Víctor H. Andaluz, and Patrick Reuter
• Analysis and visualization of sports performance anxiety in tennis matches / Shiraj Pokharel and Ying Zhu

• Object detection and recognition ; Detailed sentence generation architecture for image semantics description / Imran Khurram, Muhammad Moazam Fraz, and Muhammad Shahzad
• Pupil localization using geodesic distance / Radovan Fusek
• Parallel curves detection using multi-agent system / Shengzhi Du and Chunling Tu
• Can deep learning learn the principle of closed contour detection? / Xinhua Zhang, Yijing Watkins, and Garrett T. Kenyon
• Deep learning II ; DensSiam : end-to-end densely-Siamese network with self-attention model for object tracking / Mohamed H. Abdelpakey, Mohamed S. Shehata, and Mostafa M. Mohamed
• Convolutional adaptive particle filter with multiple models for visual tracking / Reza Jalil Mozhdehi, Yevgeniy Reznichenko, Abubakar Siddique, and Henry Medeiros
• Scale-aware RPN for vehicle detection / Lu Ding, Yong Wang, Robert Laganière, Xinbin Luo, and Shan Fu
• Object detection to assist visually impaired people : a deep neural network adventure / Fereshteh S. Bashiri, Eric LaRose, Jonathan C. Badger, Roshan M. D'Souza, Zeyun Yu, and Peggy Peissig
• Large scale application response time measurement using image recognition and deep learning / Lan Vu, Uday Kurkure, Hari Sivaraman, and Aravind Bappanadu

• Applications I ; Vision-depth landmarks and inertial fusion for navigation in degraded visual environments / Shehryar Khattak, Christos Papachristos, and Kostas Alexis
• Efficient nearest neighbors search for large-scale landmark recognition / Federico Magliani, Tomaso Fontanini, and Andrea Prati
• Patient's body motion study using multimodal RGBDT videos / Mohammad A. Haque, Simon S. Kjeldsen, Federico G. Arguissain, Iris Brunner, Kamal Nasrollahi, Ole Kæseler Andersen, Jørgen F. Nielsen, Thomas B. Moeslund, and Anders Jørgensen
• Marker based thermal-inertial localization for aerial robots in obscurant filled environments / Shehryar Khattak, Christos Papachristos, and Kostas Alexis
• Shape-based smoothing of binary digital objects using signed distance transform / Xiaoliu Zhang, Cheng Chen, Gregory Chang, and Punam K. Saha
• Segmentation ; Patch-based potentials for interactive contour extraction / Thoraya Ben Chattah, Sébastien Bougleux, Olivier Lézoray, and Atef Hamouda
• A new algorithm for local blur-scale computation and edge detection / Indranil Guha and Punam K. Saha
• Semantic segmentation by integrating classifiers for different difficulty levels / Daisuke Matsuzuki and Kazuhiro Hotta

• Applications II ; Fast image dehazing methods for real-time video processing / Yang Chen and Deepak Khosla
• GPU accelerated non-parametric background subtraction / William Porr, James Easton, Alireza Tavakkoli, Donald Loffredo, and Sean Simmons
• Budget-constrained online video summarisation of egocentric video using control charts / Paria Yousefi, Clare E. Matthews, and Ludmila I. Kuncheva
• [Italic]p-Laplacian regularization of signals on directed graphs / Zeina Abu Aisheh, Sébastien Bougleux, and Olivier Lézoray
• A dense-depth representation for VLAD descriptors in content-based image retrieval / Federico Magliani, Tomaso Fontanini, and Andrea Prati
• Virtual reality II ; Augmented reality system for training and assistance in the management of industrial equipment and instruments / Edison A. Chicaiza, Edgar I. De la Cruz, and Víctor H. Andaluz
• Alternative treatment of psychological disorders such as spider phobia through virtual reality environments / Joseph Armas and Víctor H. Andaluz
• The skyline as a marker for augmented reality in urban context / Mehdi Ayadi, Leo Valque, Mihaela Scuturici, Serge Miguet, and Chokri Ben Amar
• Oil processes VR training / Víctor H. Andaluz, José L. Amaquiña, Washington X. Quevedo, Jorge Mora-Aguilar, Daniel Castillo-Carrión, Roberto J. Miranda, and María G. Pérez
• ST : intelligent transportation systems ; Multiple object tracking in urban traffic scenes with a multiclass object detector / Hui-Lee Ooi, Guillaume-Alexandre Bilodeau, Nicolas Saunier, and David-Alexandre Beaupré
• Autonomous bus boarding robotic wheelchair using bidirectional sensing systems / Shamim Al Mamun, Hisato Fukuda, Antony Lam, Yoshinori Kobayashi, and Yoshinori Kuno
• Road user abnormal trajectory detection using a deep autoencoder / Pankaj Raj Roy and Guillaume-Alexandre Bilodeau
• Traffic flow classification using traffic cameras / Mohammad Shokrolah Shirazi and Brendan Morris.

This book constitutes the refereed proceedings of the 13th International Symposium on Visual Computing, ISVC 2018, held in Las Vegas, NV, USA in November 2018. The total of 66 papers presented in this volume was carefully reviewed and selected from 91 submissions. The papers are organized in topical sections named: ST: computational bioimaging; computer graphics; visual surveillance; pattern recognition; vitrual reality; deep learning; motion and tracking; visualization; object detection and recognition; applications; segmentation; and ST: intelligent transportation systems. .
(source: Nielsen Book Data)

• Visualization and Data Driven Technology.- Engineering and Data Driven Innovation.- Data Driven Societal Well-being and Applications.- Data Driven Cyber Security.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 5th International Conference on Advances in Visual Informatics, IVIC 2017, held in Bangi, Malaysia, in November 2017. The keynote and 72 papers presented were carefully reviewed and selected from 130 submissions. The papers are organized in the following topics: Visualization and Data Driven Technology; Engineering and Data Driven Innovation; Data Driven Societal Well-being and Applications; and Data Driven Cyber Security.
(source: Nielsen Book Data)

• Automata and Formal Languages.- Algorithmics.- Computer Science Education.
• (source: Nielsen Book Data)

This Festschrift volume is published in honor of Juraj Hromkovic on the occasion of his 60th birthday. Juraj Hromkovic is a leading expert in the areas of automata and complexity theory, algorithms for hard problems, and computer science education. The contributions in this volume reflect the breadth and impact of his work. The volume contains 35 full papers related to Juraj Hromkovic's research. They deal with various aspects of the complexity of finite automata, the information content of online problems, stability of approximation algorithms, reoptimization algorithms, computer science education, and many other topics within the fields of algorithmics and complexity theory. Moreover, the volume contains a prologue and an epilogue of laudatios from several collaborators, colleagues, and friends.
(source: Nielsen Book Data)

• A Description Logic Based Knowledge Representation Model for Concept Understanding.- Reasoning for Autonomous Agents in Dynamic Domains: Towards Automatic Satisfaction of the Module Property.- Chest X-Ray Image Analysis - A Vision of Logic Programming.- Text Classification and Transfer Learning based on Character-level Deep Convolutional Neural Networks.- A Hierarchical Playscript Representation of Distributed Words for Effective Semantic Clustering and Search.- Data Harvesting and Event Detection from Czech Twitter.- Variants of Independence Detection in SAT-based Optimal Multi-Agent Path Finding.- -Strong Privacy Preserving Multi-agent Planning.- A Quantitative Assessment of the JADEL Programming Language.- Analogical Reasoning in Clinical Practice with Description Logic ELH.- Advanced User Interfaces for Semantic Annotation of Complex Relations in Text.
• (source: Nielsen Book Data)

• A Description Logic Based Knowledge Representation Model for Concept Understanding
• Reasoning for Autonomous Agents in Dynamic Domains: Towards Automatic Satisfaction of the Module Property
• Chest X-Ray Image Analysis
• A Vision of Logic Programming
• Text Classification and Transfer Learning based on Character-level Deep Convolutional Neural Networks
• A Hierarchical Playscript Representation of Distributed Words for Effective Semantic Clustering and Search
• Data Harvesting and Event Detection from Czech Twitter
• Variants of Independence Detection in SAT-based Optimal Multi-Agent Path Finding
• ε-Strong Privacy Preserving Multi-agent Planning
• A Quantitative Assessment of the JADEL Programming Language
• Analogical Reasoning in Clinical Practice with Description Logic ELH
• Advanced User Interfaces for Semantic Annotation of Complex Relations in Text.

This book contains the revised and extended versions of selected papers from the 9th International Conference, ICAART 2017, held in Porto, Portugal, in February 24-26, 2017.The 11 full papers were carefully reviewed and selected from 158 initial submissions. The papers are organized in two tracks. The first focuses on agents, multi-agent systems, software platforms, distributed problem solving and distributed AI in general. The second track focuses mainly on artificial intelligence, knowledge representation, planning, learning, scheduling, perception, reactive AI systems, evolutionary computing, and other topics related to intelligent systems and computer intelligence.
(source: Nielsen Book Data)

This book contains revised and extended selected papers from two workshops: the 10th International Workshop on Agents Applied in Health Care, A2HC 2017, held at the 16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017, held in Sao Paulo, Brazil, in May 2017, and the International Workshop on Agents and Multi-Agent Systems for AAL and e-Health, A-HEALTH 2017, held at the 15th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2017, in Porto, Portugal, in June 2017. The 9 revised full papers were carefully reviewed and selected from 16 submissions. They feature current research topics such as personalised health systems for remote and autonomous tele-assistance, communication and co-operation between distributed intelligent agents to manage patient care, information agents that retrieve medical information from distributed repositories, intelligent and distributed data mining, and multi-agent systems that assist the doctors in the tasks of monitoring, decision support and diagnosis. .
(source: Nielsen Book Data)

• Introduction : legal and ethical dimensions of AI, NorMAS, and the web of data
• Legal philosophy, conceptual analysis, and epistemic approaches
• Rules and norms analysis and representation
• Legal vocabularies and natural language processing
• Legal ontologies and semantic annotation
• Legal argumentation
• Courts, adjudication and dispute resolution.

This book includes revised selected papers from five International Workshops on Artificial Intelligence Approaches to the Complexity of Legal Systems, AICOL VI to AICOL X, held during 2015-2017: AICOL VI in Braga, Portugal, in December 2015 as part of JURIX 2015; AICOL VII at EKAW 2016 in Bologna, Italy, in November 2016; AICOL VIII in Sophia Antipolis, France, in December 2016; AICOL IX at ICAIL 2017 in London, UK, in June 2017; and AICOL X as part of JURIX 2017 in Luxembourg, in December 2017. The 37 revised full papers included in this volume were carefully reviewed and selected form 69 submissions. They represent a comprehensive picture of the state of the art in legal informatics. The papers are organized in six main sections: legal philosophy, conceptual analysis, and epistemic approaches; rules and norms analysis and representation; legal vocabularies and natural language processing; legal ontologies and semantic annotation; legal argumentation; and courts, adjudication and dispute resolution.
(source: Nielsen Book Data)

• Introduction
• e-Learning so far
• MOOCs, Crowdsourcing and Social Networks
• User Profiling and Personalisation
• Personal Learning Networks, Portfolios and Environments
• Customised e-Learning
• Looking Ahead.

This book reviews a blend of artificial intelligence (AI) approaches that can take e-learning to the next level by adding value through customization. It investigates three methods: crowdsourcing via social networks; user profiling through machine learning techniques, and personal learning portfolios using learning analytics. Technology and education have drawn closer together over the years as they complement each other within the domain of e-learning, and different generations of online education reflect the evolution of new technologies as researcher and developers continuously seek to optimize the electronic medium to enhance the effectiveness of e-learning. Artificial intelligence (AI) for e-learning promises personalized online education through a combination of different intelligent techniques that are grounded in established learning theories while at the same time addressing a number of common e-learning issues. This book is intended for education technologists and e-learning researchers as well as for a general readership interested in the evolution of online education based on techniques like machine learning, crowdsourcing, and learner profiling that can be merged to characterize the future of personalized e-learning.
(source: Nielsen Book Data)