Information theory Books

Book SynopsisThis book constitutes the refereed post-conference proceedings of the 13th International Conference on Ad Hoc Networks, ADHOCNETS 2021, held in December 2021, and the 16th International Conference on Tools for Design, Implementation and Verification of Emerging Information Technologies, TRIDENTCOM 2021, held in November 2021. Both conferences were held virtually due to COVID 19 pandemic. The 15 full papers of ADHOCNETS 2021 were selected from 29 submissions and cover a variety of network paradigms including ad hoc networks (MANETs), wireless sensor networks (WSNs), vehicular ad hoc networks (Vanets), airborne networks, underwater networks, underground networks, personal area networks, and home networks, etc. It promises a wide range of applications in civilian, commercial, and military areas. The 18 full papers were selected from 47 submissions and deal the emerging technologies such as Industry 4.0, blockchain, deep learning, cloud/edge/fog computing, cyber physical systems, cybersecurity and computer communications.Table of ContentsNetwork Routing.- Analysis of Routing Attacks in FANET.- Context-Aware Routing and Forwarding Model for NDN-based VANET.- A Novel Adaptive Hello Mechanism based Geographic Routing Protocol for FANETs.- Network Security 4 Evaluation of Denial of Service Attacks in Software Defined-Cognitive Radio Networks.- The Evaluation of the Two Detection Algorithms for Distributed Denial of Service Attack.- Investigating the effectiveness of Spectrum Sensing Data Falsification Attacks Defense Mechanisms in Cognitive Radio Ad hoc Networks.- Active attack that exploits biometric similarity difference and basic countermeasures.- Network Protocols.- LEACH-S enhancement to ensure WSN stability.- M-ODD: A Standard Protocol for Reporting MANET Related Models, Simulations, and Findings.- Frame Design for Adaptability in Long-range Underwater Communication.- Adaptive Data Rate Based Congestion Control in Vehicular Ad Hoc Networks (VANET).- Network Applications.- Analyzing Aggregate User Behavior on a Large Multi-platform Content Distribution Service.- An AI-based Transmission Power-control Certificate Omission in Vehicular Ad-Hoc Networks.- Dynamic Ephemeral and Session Key Generation Protocol for Next Generation Smart Grids.- A Blockchain-Based Data-Sharing Scheme for Inter[1]Vehicular Safety Applications.- A Trust-based and Secure Real-Time Traffic Information Sharing Scheme.- TuneIn: Framework Design and Implementation for Education Using Dynamic Difficulty Adjustment Based on Deep Reinforcement Learning and Mathematical Approach.- P-sharding: Streamline emergency medical transactions via priority sharding.- BiDKT: Deep Knowledge Tracing with BERT.- Vision - An innovative management system based on private DLT.- Value-aware Collaborative Data Pricing for Federated Learning in Vehicular Networks.- Dual Scheme Privacy-Preserving Approach for Location[1]Aware Application in Edge Computing.- Survey on Bridge Discovery in Tor.

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Book SynopsisObject-oriented databases were originally developed as an alternative to relational database technology for the representation, storage, and access of non-traditional data forms that were increasingly found in advanced applications of database technology. After much debate regarding object-oriented versus relational database technology, object-oriented extensions were eventually incorporated into relational technology to create object-relational databases. Both object-oriented databases and object-relational databases, collectively known as object databases, provide inherent support for object features, such as object identity, classes, inheritance hierarchies, and associations between classes using object references. This monograph presents the fundamentals of object databases, with a specific focus on conceptual modeling of object database designs. After an introduction to the fundamental concepts of object-oriented data, the monograph provides a review of object-oriented conceptual modeling techniques using side-by-side Enhanced Entity Relationship diagrams and Unified Modeling Language conceptual class diagrams that feature class hierarchies with specialization constraints and object associations. These object-oriented conceptual models provide the basis for introducing case studies that illustrate the use of object features within the design of object-oriented and object-relational databases. For the object-oriented database perspective, the Object Data Management Group data definition language provides a portable, language-independent specification of an object schema, together with an SQL-like object query language. LINQ (Language INtegrated Query) is presented as a case study of an object query language together with its use in the db4o open-source object-oriented database. For the object-relational perspective, the object-relational features of the SQL standard are presented together with an accompanying case study of the object-relational features of Oracle. For completeness of coverage, an appendix provides a mapping of object-oriented conceptual designs to the relational model and its associated constraints. Table of Contents: List of Figures / List of Tables / Introduction to Object Databases / Object-Oriented Databases / Object-Relational DatabasesTable of ContentsList of Figures.- List of Tables.- Introduction to Object Databases.- Object-Oriented Databases.- Object-Relational Databases.

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Book SynopsisIn the 1980s, traditional Business Intelligence (BI) systems focused on the delivery of reports that describe the state of business activities in the past, such as for questions like "How did our sales perform during the last quarter?" A decade later, there was a shift to more interactive content that presented how the business was performing at the present time, answering questions like "How are we doing right now?" Today the focus of BI users are looking into the future. "Given what I did before and how I am currently doing this quarter, how will I do next quarter?" Furthermore, fuelled by the demands of Big Data, BI systems are going through a time of incredible change. Predictive analytics, high volume data, unstructured data, social data, mobile, consumable analytics, and data visualization are all examples of demands and capabilities that have become critical within just the past few years, and are growing at an unprecedented pace. This book introduces research problems and solutions on various aspects central to next-generation BI systems. It begins with a chapter on an industry perspective on how BI has evolved, and discusses how game-changing trends have drastically reshaped the landscape of BI. One of the game changers is the shift toward the consumerization of BI tools. As a result, for BI tools to be successfully used by business users (rather than IT departments), the tools need a business model, rather than a data model. One chapter of the book surveys four different types of business modeling. However, even with the existence of a business model for users to express queries, the data that can meet the needs are still captured within a data model. The next chapter on vivification addresses the problem of closing the gap, which is often significant, between the business and the data models. Moreover, Big Data forces BI systems to integrate and consolidate multiple, and often wildly different, data sources. One chapter gives an overview of several integration architectures for dealing with the challenges that need to be overcome. While the book so far focuses on the usual structured relational data, the remaining chapters turn to unstructured data, an ever-increasing and important component of Big Data. One chapter on information extraction describes methods for dealing with the extraction of relations from free text and the web. Finally, BI users need tools to visualize and interpret new and complex types of information in a way that is compelling, intuitive, but accurate. The last chapter gives an overview of information visualization for decision support and text.Table of ContentsIntroduction and the Changing Landscape of Business Intelligence.- BI Game Changers: an Industry Viewpoint.- Business Modeling for BI.- Vivification in BI.- Information Integration in BI.- Information Extraction for BI.- Information Visualization for BI.

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Book SynopsisRoughly a decade ago, power consumption and heat dissipation concerns forced the semiconductor industry to radically change its course, shifting from sequential to parallel computing. Unfortunately, improving performance of applications has now become much more difficult than in the good old days of frequency scaling. This is also affecting databases and data processing applications in general, and has led to the popularity of so-called data appliances—specialized data processing engines, where software and hardware are sold together in a closed box. Field-programmable gate arrays (FPGAs) increasingly play an important role in such systems. FPGAs are attractive because the performance gains of specialized hardware can be significant, while power consumption is much less than that of commodity processors. On the other hand, FPGAs are way more flexible than hard-wired circuits (ASICs) and can be integrated into complex systems in many different ways, e.g., directly in the network for a high-frequency trading application. This book gives an introduction to FPGA technology targeted at a database audience. In the first few chapters, we explain in detail the inner workings of FPGAs. Then we discuss techniques and design patterns that help mapping algorithms to FPGA hardware so that the inherent parallelism of these devices can be leveraged in an optimal way. Finally, the book will illustrate a number of concrete examples that exploit different advantages of FPGAs for data processing. Table of Contents: Preface / Introduction / A Primer in Hardware Design / FPGAs / FPGA Programming Models / Data Stream Processing / Accelerated DB Operators / Secure Data Processing / Conclusions / Bibliography / Authors' Biographies / IndexTable of ContentsPreface.- Introduction.- A Primer in Hardware Design.- FPGAs.- FPGA Programming Models.- Data Stream Processing.- Accelerated DB Operators.- Secure Data Processing.- Conclusions.- Bibliography.- Authors' Biographies.- Index.

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Book SynopsisResearch on social networks has exploded over the last decade. To a large extent, this has been fueled by the spectacular growth of social media and online social networking sites, which continue growing at a very fast pace, as well as by the increasing availability of very large social network datasets for purposes of research. A rich body of this research has been devoted to the analysis of the propagation of information, influence, innovations, infections, practices and customs through networks. Can we build models to explain the way these propagations occur? How can we validate our models against any available real datasets consisting of a social network and propagation traces that occurred in the past? These are just some questions studied by researchers in this area. Information propagation models find applications in viral marketing, outbreak detection, finding key blog posts to read in order to catch important stories, finding leaders or trendsetters, information feed ranking, etc. A number of algorithmic problems arising in these applications have been abstracted and studied extensively by researchers under the garb of influence maximization. This book starts with a detailed description of well-established diffusion models, including the independent cascade model and the linear threshold model, that have been successful at explaining propagation phenomena. We describe their properties as well as numerous extensions to them, introducing aspects such as competition, budget, and time-criticality, among many others. We delve deep into the key problem of influence maximization, which selects key individuals to activate in order to influence a large fraction of a network. Influence maximization in classic diffusion models including both the independent cascade and the linear threshold models is computationally intractable, more precisely #P-hard, and we describe several approximation algorithms and scalable heuristics that have been proposed in the literature. Finally, we also deal with key issues that need to be tackled in order to turn this research into practice, such as learning the strength with which individuals in a network influence each other, as well as the practical aspects of this research including the availability of datasets and software tools for facilitating research. We conclude with a discussion of various research problems that remain open, both from a technical perspective and from the viewpoint of transferring the results of research into industry strength applications.Table of ContentsAcknowledgments.- Introduction.- Stochastic Diffusion Models.- Influence Maximization.- Extensions to Diffusion Modeling and Influence Maximization.- Learning Propagation Models.- Data and Software for Information/Influence: Propagation Research.- Conclusion and Challenges.- Bibliography.- Authors' Biographies.- Index.

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Book SynopsisState-of-the-art database systems manage and process a variety of complex objects, including strings and trees. For such objects equality comparisons are often not meaningful and must be replaced by similarity comparisons. This book describes the concepts and techniques to incorporate similarity into database systems. We start out by discussing the properties of strings and trees, and identify the edit distance as the de facto standard for comparing complex objects. Since the edit distance is computationally expensive, token-based distances have been introduced to speed up edit distance computations. The basic idea is to decompose complex objects into sets of tokens that can be compared efficiently. Token-based distances are used to compute an approximation of the edit distance and prune expensive edit distance calculations. A key observation when computing similarity joins is that many of the object pairs, for which the similarity is computed, are very different from each other. Filters exploit this property to improve the performance of similarity joins. A filter preprocesses the input data sets and produces a set of candidate pairs. The distance function is evaluated on the candidate pairs only. We describe the essential query processing techniques for filters based on lower and upper bounds. For token equality joins we describe prefix, size, positional and partitioning filters, which can be used to avoid the computation of small intersections that are not needed since the similarity would be too low.Table of ContentsPreface.- Acknowledgments.- Introduction.- Data Types.- Edit-Based Distances.- Token-Based Distances.- Query Processing Techniques.- Filters for Token Equality Joins.- Conclusion.- Bibliography.- Authors' Biographies.- Index.

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Book SynopsisOn the Web, a massive amount of user-generated content is available through various channels (e.g., texts, tweets, Web tables, databases, multimedia-sharing platforms, etc.). Conflicting information, rumors, erroneous and fake content can be easily spread across multiple sources, making it hard to distinguish between what is true and what is not. This book gives an overview of fundamental issues and recent contributions for ascertaining the veracity of data in the era of Big Data. The text is organized into six chapters, focusing on structured data extracted from texts. Chapter 1 introduces the problem of ascertaining the veracity of data in a multi-source and evolving context. Issues related to information extraction are presented in Chapter 2. Current truth discovery computation algorithms are presented in details in Chapter 3. It is followed by practical techniques for evaluating data source reputation and authoritativeness in Chapter 4. The theoretical foundations and various approaches for modeling diffusion phenomenon of misinformation spreading in networked systems are studied in Chapter 5. Finally, truth discovery computation from extracted data in a dynamic context of misinformation propagation raises interesting challenges that are explored in Chapter 6. This text is intended for a seminar course at the graduate level. It is also to serve as a useful resource for researchers and practitioners who are interested in the study of fact-checking, truth discovery, or rumor spreading.Table of ContentsIntroduction to Data Veracity.- Information Extraction.- Truth Discovery Computation.- Trust Computation.- Misinformation Dynamics.- Transdisciplinary Challenges of Truth Discovery.- Bibliography.- Authors' Biographies.

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Book SynopsisTraditional theory and practice of write-ahead logging and of database recovery focus on three failure classes: transaction failures (typically due to deadlocks) resolved by transaction rollback; system failures (typically power or software faults) resolved by restart with log analysis, "redo," and "undo" phases; and media failures (typically hardware faults) resolved by restore operations that combine multiple types of backups and log replay. The recent addition of single-page failures and single-page recovery has opened new opportunities far beyond the original aim of immediate, lossless repair of single-page wear-out in novel or traditional storage hardware. In the contexts of system and media failures, efficient single-page recovery enables on-demand incremental "redo" and "undo" as part of system restart or media restore operations. This can give the illusion of practically instantaneous restart and restore: instant restart permits processing new queries and updates seconds after system reboot and instant restore permits resuming queries and updates on empty replacement media as if those were already fully recovered. In the context of node and network failures, instant restart and instant restore combine to enable practically instant failover from a failing database node to one holding merely an out-of-date backup and a log archive, yet without loss of data, updates, or transactional integrity. In addition to these instant recovery techniques, the discussion introduces self-repairing indexes and much faster offline restore operations, which impose no slowdown in backup operations and hardly any slowdown in log archiving operations. The new restore techniques also render differential and incremental backups obsolete, complete backup commands on a database server practically instantly, and even permit taking full up-to-date backups without imposing any load on the database server. Compared to the first version of this book, this second edition adds sections on applications of single-page repair, instant restart, single-pass restore, and instant restore. Moreover, it adds sections on instant failover among nodes in a cluster, applications of instant failover, recovery for file systems and data files, and the performance of instant restart and instant restore.Table of ContentsPreface.- Acknowledgments.- Introduction.- Related Prior Work.- Single-Page Recovery.- Applications of Single-Page Recovery.- Instant Restart after a System Failure.- Applications of Instant Restart.- Single-Pass Restore.- Applications of Single-Pass Restore.- Instant Restore after a Media Failure.- Applications of Instant Restore.- Multiple Pate, System and Media Failures.- Instant Failover.- Applications of Instant Failover.- File Systems and Data Files.- Performance and Scalability.- Conclusions.- References.- Author Biographies .

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Book SynopsisData management systems enable various influential applications from high-performance online services (e.g., social networks like Twitter and Facebook or financial markets) to big data analytics (e.g., scientific exploration, sensor networks, business intelligence). As a result, data management systems have been one of the main drivers for innovations in the database and computer architecture communities for several decades. Recent hardware trends require software to take advantage of the abundant parallelism existing in modern and future hardware. The traditional design of the data management systems, however, faces inherent scalability problems due to its tightly coupled components. In addition, it cannot exploit the full capability of the aggressive micro-architectural features of modern processors. As a result, today's most commonly used server types remain largely underutilized leading to a huge waste of hardware resources and energy. In this book, we shed light on the challenges present while running DBMS on modern multicore hardware. We divide the material into two dimensions of scalability: implicit/vertical and explicit/horizontal. The first part of the book focuses on the vertical dimension: it describes the instruction- and data-level parallelism opportunities in a core coming from the hardware and software side. In addition, it examines the sources of under-utilization in a modern processor and presents insights and hardware/software techniques to better exploit the microarchitectural resources of a processor by improving cache locality at the right level of the memory hierarchy. The second part focuses on the horizontal dimension, i.e., scalability bottlenecks of database applications at the level of multicore and multisocket multicore architectures. It first presents a systematic way of eliminating such bottlenecks in online transaction processing workloads, which is based on minimizing unbounded communication, and shows several techniques that minimize bottlenecks in major components of database management systems. Then, it demonstrates the data and work sharing opportunities for analytical workloads, and reviews advanced scheduling mechanisms that are aware of nonuniform memory accesses and alleviate bandwidth saturation.Table of ContentsIntroduction.- Exploiting Resources of a Processor Core.- Minimizing Memory Stalls.- Scaling-up OLTP.- Scaling-up OLAP Workloads.- Outlook.- Summary.- Bibliography.- Authors' Biographies.

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Book SynopsisThe topic of using views to answer queries has been popular for a few decades now, as it cuts across domains such as query optimization, information integration, data warehousing, website design and, recently, database-as-a-service and data placement in cloud systems. This book assembles foundational work on answering queries using views in a self-contained manner, with an effort to choose material that constitutes the backbone of the research. It presents efficient algorithms and covers the following problems: query containment; rewriting queries using views in various logical languages; equivalent rewritings and maximally contained rewritings; and computing certain answers in the data-integration and data-exchange settings. Query languages that are considered are fragments of SQL, in particular select-project-join queries, also called conjunctive queries (with or without arithmetic comparisons or negation), and aggregate SQL queries. This second edition includes two new chapters that refer to tree-like data and respective query languages. Chapter 8 presents the data model for XML documents and the XPath query language, and Chapter 9 provides a theoretical presentation of tree-like data model and query language where the tuples of a relation share a tree-structured schema for that relation and the query language is a dialect of SQL with evaluation techniques appropriately modified to fit the richer schema.Table of ContentsPreface to the First Edition.- Preface to the Second Edition.- Acknowledgments.- Queries and Views.- Query Containment and Equivalence.- Finding Equivalent Rewritings.- Maximally Contained Rewritings (MCRs).- Answering Queries in Presence of Dependencies.- Answering Queries in Data Exchange.- Answering Queries Using Views.- XPath Queries and Views.- Tree-Structured Records Queried with SQL Dialect.- Bibliographical Notes for Chapters 1--7.- Conclusion for Chapters 1--7.- Bibliography.- Authors' Biographies.

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Book SynopsisSince the introduction of Bitcoin—the first widespread application driven by blockchain—the interest of the public and private sectors in blockchain has skyrocketed. In recent years, blockchain-based fabrics have been used to address challenges in diverse fields such as trade, food production, property rights, identity-management, aid delivery, health care, and fraud prevention. This widespread interest follows from fundamental concepts on which blockchains are built that together embed the notion of trust, upon which blockchains are built. 1. Blockchains provide data transparancy. Data in a blockchain is stored in the form of a ledger, which contains an ordered history of all the transactions. This facilitates oversight and auditing. 2. Blockchains ensure data integrity by using strong cryptographic primitives. This guarantees that transactions accepted by the blockchain are authenticated by its issuer, are immutable, and cannot be repudiated by the issuer. This ensures accountability. 3. Blockchains are decentralized, democratic, and resilient. They use consensus-based replication to decentralize the ledger among many independent participants. Thus, it can operate completely decentralized and does not require trust in a single authority. Additions to the chain are performed by consensus, in which all participants have a democratic voice in maintaining the integrity of the blockchain. Due to the usage of replication and consensus, blockchains are also highly resilient to malicious attacks even when a significant portion of the participants are malicious. It further increases the opportunity for fairness and equity through democratization. These fundamental concepts and the technologies behind them—a generic ledger-based data model, cryptographically ensured data integrity, and consensus-based replication—prove to be a powerful and inspiring combination, a catalyst to promote computational trust. In this book, we present an in-depth study of blockchain, unraveling its revolutionary promise to instill computational trust in society, all carefully tailored to a broad audience including students, researchers, and practitioners. We offer a comprehensive overview of theoretical limitations and practical usability of consensus protocols while examining the diverse landscape of how blockchains are manifested in their permissioned and permissionless forms.Table of ContentsPreface.- Introduction.- Practical Byzantine Fault-Tolerant Consensus.- Beyond the Design of PBFT.- Toward Scalable Blockchains.- Permissioned Blockchains.- Permissionless Blockchains.- Bibliography.- Authors' Biographies.

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Book SynopsisProbabilistic databases are databases where the value of some attributes or the presence of some records are uncertain and known only with some probability. Applications in many areas such as information extraction, RFID and scientific data management, data cleaning, data integration, and financial risk assessment produce large volumes of uncertain data, which are best modeled and processed by a probabilistic database. This book presents the state of the art in representation formalisms and query processing techniques for probabilistic data. It starts by discussing the basic principles for representing large probabilistic databases, by decomposing them into tuple-independent tables, block-independent-disjoint tables, or U-databases. Then it discusses two classes of techniques for query evaluation on probabilistic databases. In extensional query evaluation, the entire probabilistic inference can be pushed into the database engine and, therefore, processed as effectively as the evaluation of standard SQL queries. The relational queries that can be evaluated this way are called safe queries. In intensional query evaluation, the probabilistic inference is performed over a propositional formula called lineage expression: every relational query can be evaluated this way, but the data complexity dramatically depends on the query being evaluated, and can be #P-hard. The book also discusses some advanced topics in probabilistic data management such as top-k query processing, sequential probabilistic databases, indexing and materialized views, and Monte Carlo databases. Table of Contents: Overview / Data and Query Model / The Query Evaluation Problem / Extensional Query Evaluation / Intensional Query Evaluation / Advanced TechniquesTable of ContentsOverview.- Data and Query Model.- The Query Evaluation Problem.- Extensional Query Evaluation.- Intensional Query Evaluation.- Advanced Techniques.

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Book SynopsisDue to the Internet Revolution, human conversational data -- in written forms -- are accumulating at a phenomenal rate. At the same time, improvements in speech technology enable many spoken conversations to be transcribed. Individuals and organizations engage in email exchanges, face-to-face meetings, blogging, texting and other social media activities. The advances in natural language processing provide ample opportunities for these "informal documents" to be analyzed and mined, thus creating numerous new and valuable applications. This book presents a set of computational methods to extract information from conversational data, and to provide natural language summaries of the data. The book begins with an overview of basic concepts, such as the differences between extractive and abstractive summaries, and metrics for evaluating the effectiveness of summarization and various extraction tasks. It also describes some of the benchmark corpora used in the literature. The book introduces extraction and mining methods for performing subjectivity and sentiment detection, topic segmentation and modeling, and the extraction of conversational structure. It also describes frameworks for conducting dialogue act recognition, decision and action item detection, and extraction of thread structure. There is a specific focus on performing all these tasks on conversational data, such as meeting transcripts (which exemplify synchronous conversations) and emails (which exemplify asynchronous conversations). Very recent approaches to deal with blogs, discussion forums and microblogs (e.g., Twitter) are also discussed. The second half of this book focuses on natural language summarization of conversational data. It gives an overview of several extractive and abstractive summarizers developed for emails, meetings, blogs and forums. It also describes attempts for building multi-modal summarizers. Last but not least, the book concludes with thoughts on topics for further development. Table of Contents: Introduction / Background: Corpora and Evaluation Methods / Mining Text Conversations / Summarizing Text Conversations / Conclusions / Final ThoughtsTable of ContentsIntroduction.- Background: Corpora and Evaluation Methods.- Mining Text Conversations.- Summarizing Text Conversations.- Conclusions.- Final Thoughts.

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Book SynopsisQuery compilation is the problem of translating user requests formulated over purely conceptual and domain specific ways of understanding data, commonly called logical designs, to efficient executable programs called query plans. Such plans access various concrete data sources through their low-level often iterator-based interfaces. An appreciation of the concrete data sources, their interfaces and how such capabilities relate to logical design is commonly called a physical design. This book is an introduction to the fundamental methods underlying database technology that solves the problem of query compilation. The methods are presented in terms of first-order logic which serves as the vehicle for specifying physical design, expressing user requests and query plans, and understanding how query plans implement user requests. Table of Contents: Introduction / Logical Design and User Queries / Basic Physical Design and Query Plans / On Practical Physical Design / Query Compilation and Plan Synthesis / Updating DataTable of ContentsIntroduction.- Logical Design and User Queries.- Basic Physical Design and Query Plans.- On Practical Physical Design.- Query Compilation and Plan Synthesis.- Updating Data.

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Book SynopsisWith the proliferation of citizen reporting, smart mobile devices, and social media, an increasing number of people are beginning to generate information about events they observe and participate in. A significant fraction of this information contains multimedia data to share the experience with their audience. A systematic information modeling and management framework is necessary to capture this widely heterogeneous, schemaless, potentially humongous information produced by many different people. This book is an attempt to examine the modeling, storage, querying, and applications of such an event management system in a holistic manner. It uses a semantic-web style graph-based view of events, and shows how this event model, together with its query facility, can be used toward emerging applications like semi-automated storytelling. Table of Contents: Introduction / Event Data Models / Implementing an Event Data Model / Querying Events / Storytelling with Events / An Emerging Application / ConclusionTable of ContentsIntroduction.- Event Data Models.- Implementing an Event Data Model.- Querying Events.- Storytelling with Events.- An Emerging Application.- Conclusion.

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Book SynopsisIntegrity constraints are semantic conditions that a database should satisfy in order to be an appropriate model of external reality. In practice, and for many reasons, a database may not satisfy those integrity constraints, and for that reason it is said to be inconsistent. However, and most likely, a large portion of the database is still semantically correct, in a sense that has to be made precise. After having provided a formal characterization of consistent data in an inconsistent database, the natural problem emerges of extracting that semantically correct data, as query answers. The consistent data in an inconsistent database is usually characterized as the data that persists across all the database instances that are consistent and minimally differ from the inconsistent instance. Those are the so-called repairs of the database. In particular, the consistent answers to a query posed to the inconsistent database are those answers that can be simultaneously obtained from all the database repairs. As expected, the notion of repair requires an adequate notion of distance that allows for the comparison of databases with respect to how much they differ from the inconsistent instance. On this basis, the minimality condition on repairs can be properly formulated. In this monograph we present and discuss these fundamental concepts, different repair semantics, algorithms for computing consistent answers to queries, and also complexity-theoretic results related to the computation of repairs and doing consistent query answering. Table of Contents: Introduction / The Notions of Repair and Consistent Answer / Tractable CQA and Query Rewriting / Logically Specifying Repairs / Decision Problems in CQA: Complexity and Algorithms / Repairs and Data CleaningTable of ContentsIntroduction.- The Notions of Repair and Consistent Answer.- Tractable CQA and Query Rewriting.- Logically Specifying Repairs.- Decision Problems in CQA: Complexity and Algorithms.- Repairs and Data Cleaning.

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Book SynopsisSpatial database management deals with the storage, indexing, and querying of data with spatial features, such as location and geometric extent. Many applications require the efficient management of spatial data, including Geographic Information Systems, Computer Aided Design, and Location Based Services. The goal of this book is to provide the reader with an overview of spatial data management technology, with an emphasis on indexing and search techniques. It first introduces spatial data models and queries and discusses the main issues of extending a database system to support spatial data. It presents indexing approaches for spatial data, with a focus on the R-tree. Query evaluation and optimization techniques for the most popular spatial query types (selections, nearest neighbor search, and spatial joins) are portrayed for data in Euclidean spaces and spatial networks. The book concludes by demonstrating the ample application of spatial data management technology on a wide range of related application domains: management of spatio-temporal data and high-dimensional feature vectors, multi-criteria ranking, data mining and OLAP, privacy-preserving data publishing, and spatial keyword search. Table of Contents: Introduction / Spatial Data / Indexing / Spatial Query Evaluation / Spatial Networks / Applications of Spatial Data Management TechnologyTable of ContentsIntroduction.- Spatial Data.- Indexing.- Spatial Query Evaluation.- Spatial Networks.- Applications of Spatial Data Management Technology.

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Book SynopsisIn data publishing, the owner delegates the role of satisfying user queries to a third-party publisher. As the servers of the publisher may be untrusted or susceptible to attacks, we cannot assume that they would always process queries correctly, hence there is a need for users to authenticate their query answers. This book introduces various notions that the research community has studied for defining the correctness of a query answer. In particular, it is important to guarantee the completeness, authenticity and minimality of the answer, as well as its freshness. We present authentication mechanisms for a wide variety of queries in the context of relational and spatial databases, text retrieval, and data streams. We also explain the cryptographic protocols from which the authentication mechanisms derive their security properties. Table of Contents: Introduction / Cryptography Foundation / Relational Queries / Spatial Queries / Text Search Queries / Data Streams / ConclusionTable of ContentsIntroduction.- Cryptography Foundation.- Relational Queries.- Spatial Queries.- Text Search Queries.- Data Streams.- Conclusion.

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Book SynopsisAs an alternative to traditional client-server systems, Peer-to-Peer (P2P) systems provide major advantages in terms of scalability, autonomy and dynamic behavior of peers, and decentralization of control. Thus, they are well suited for large-scale data sharing in distributed environments. Most of the existing P2P approaches for data sharing rely on either structured networks (e.g., DHTs) for efficient indexing, or unstructured networks for ease of deployment, or some combination. However, these approaches have some limitations, such as lack of freedom for data placement in DHTs, and high latency and high network traffic in unstructured networks. To address these limitations, gossip protocols which are easy to deploy and scale well, can be exploited. In this book, we will give an overview of these different P2P techniques and architectures, discuss their trade-offs, and illustrate their use for decentralizing several large-scale data sharing applications. Table of Contents: P2P Overlays, Query Routing, and Gossiping / Content Distribution in P2P Systems / Recommendation Systems / Top-k Query Processing in P2P SystemsTable of ContentsP2P Overlays, Query Routing, and Gossiping.- Content Distribution in P2P Systems.- Recommendation Systems.- Top-k Query Processing in P2P Systems.

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Book SynopsisThere are millions of searchable data sources on the Web and to a large extent their contents can only be reached through their own query interfaces. There is an enormous interest in making the data in these sources easily accessible. There are primarily two general approaches to achieve this objective. The first is to surface the contents of these sources from the deep Web and add the contents to the index of regular search engines. The second is to integrate the searching capabilities of these sources and support integrated access to them. In this book, we introduce the state-of-the-art techniques for extracting, understanding, and integrating the query interfaces of deep Web data sources. These techniques are critical for producing an integrated query interface for each domain. The interface serves as the mediator for searching all data sources in the concerned domain. While query interface integration is only relevant for the deep Web integration approach, the extraction and understanding of query interfaces are critical for both deep Web exploration approaches. This book aims to provide in-depth and comprehensive coverage of the key technologies needed to create high quality integrated query interfaces automatically. The following technical issues are discussed in detail in this book: query interface modeling, query interface extraction, query interface clustering, query interface matching, query interface attribute integration, and query interface integration. Table of Contents: Introduction / Query Interface Representation and Extraction / Query Interface Clustering and Categorization / Query Interface Matching / Query Interface Attribute Integration / Query Interface Integration / Summary and Future ResearchTable of ContentsIntroduction.- Query Interface Representation and Extraction.- Query Interface Clustering and Categorization.- Query Interface Matching.- Query Interface Attribute Integration.- Query Interface Integration.- Summary and Future Research.

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Book SynopsisWhile classic data management focuses on the data itself, research on Business Processes also considers the context in which this data is generated and manipulated, namely the processes, users, and goals that this data serves. This provides the analysts a better perspective of the organizational needs centered around the data. As such, this research is of fundamental importance. Much of the success of database systems in the last decade is due to the beauty and elegance of the relational model and its declarative query languages, combined with a rich spectrum of underlying evaluation and optimization techniques, and efficient implementations. Much like the case for traditional database research, elegant modeling and rich underlying technology are likely to be highly beneficiary for the Business Process owners and their users; both can benefit from easy formulation and analysis of the processes. While there have been many important advances in this research in recent years, there is still much to be desired: specifically, there have been many works that focus on the processes behavior (flow), and many that focus on its data, but only very few works have dealt with both the state-of-the-art in a database approach to Business Process modeling and analysis, the progress towards a holistic flow-and-data framework for these tasks, and highlight the current gaps and research directions. Table of Contents: Introduction / Modeling / Querying Business Processes / Other Issues / ConclusionTable of ContentsIntroduction.- Modeling.- Querying Business Processes.- Other Issues.- Conclusion.

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Book SynopsisData quality is one of the most important problems in data management. A database system typically aims to support the creation, maintenance, and use of large amount of data, focusing on the quantity of data. However, real-life data are often dirty: inconsistent, duplicated, inaccurate, incomplete, or stale. Dirty data in a database routinely generate misleading or biased analytical results and decisions, and lead to loss of revenues, credibility and customers. With this comes the need for data quality management. In contrast to traditional data management tasks, data quality management enables the detection and correction of errors in the data, syntactic or semantic, in order to improve the quality of the data and hence, add value to business processes. While data quality has been a longstanding problem for decades, the prevalent use of the Web has increased the risks, on an unprecedented scale, of creating and propagating dirty data. This monograph gives an overview of fundamental issues underlying central aspects of data quality, namely, data consistency, data deduplication, data accuracy, data currency, and information completeness. We promote a uniform logical framework for dealing with these issues, based on data quality rules. The text is organized into seven chapters, focusing on relational data. Chapter One introduces data quality issues. A conditional dependency theory is developed in Chapter Two, for capturing data inconsistencies. It is followed by practical techniques in Chapter 2b for discovering conditional dependencies, and for detecting inconsistencies and repairing data based on conditional dependencies. Matching dependencies are introduced in Chapter Three, as matching rules for data deduplication. A theory of relative information completeness is studied in Chapter Four, revising the classical Closed World Assumption and the Open World Assumption, to characterize incomplete information in the real world. A data currency model is presented in Chapter Five, to identify the current values of entities in a database and to answer queries with the current values, in the absence of reliable timestamps. Finally, interactions between these data quality issues are explored in Chapter Six. Important theoretical results and practical algorithms are covered, but formal proofs are omitted. The bibliographical notes contain pointers to papers in which the results were presented and proven, as well as references to materials for further reading. This text is intended for a seminar course at the graduate level. It is also to serve as a useful resource for researchers and practitioners who are interested in the study of data quality. The fundamental research on data quality draws on several areas, including mathematical logic, computational complexity and database theory. It has raised as many questions as it has answered, and is a rich source of questions and vitality. Table of Contents: Data Quality: An Overview / Conditional Dependencies / Cleaning Data with Conditional Dependencies / Data Deduplication / Information Completeness / Data Currency / Interactions between Data Quality IssuesTable of ContentsData Quality: An Overview.- Conditional Dependencies.- Cleaning Data with Conditional Dependencies.- Data Deduplication.- Information Completeness.- Data Currency.- Interactions between Data Quality Issues.

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Book SynopsisThe chase has long been used as a central tool to analyze dependencies and their effect on queries. It has been applied to different relevant problems in database theory such as query optimization, query containment and equivalence, dependency implication, and database schema design. Recent years have seen a renewed interest in the chase as an important tool in several database applications, such as data exchange and integration, query answering in incomplete data, and many others. It is well known that the chase algorithm might be non-terminating and thus, in order for it to find practical applicability, it is crucial to identify cases where its termination is guaranteed. Another important aspect to consider when dealing with the chase is that it can introduce null values into the database, thereby leading to incomplete data. Thus, in several scenarios where the chase is used the problem of dealing with data dependencies and incomplete data arises. This book discusses fundamental issues concerning data dependencies and incomplete data with a particular focus on the chase and its applications in different database areas. We report recent results about the crucial issue of identifying conditions that guarantee the chase termination. Different database applications where the chase is a central tool are discussed with particular attention devoted to query answering in the presence of data dependencies and database schema design. Table of Contents: Introduction / Relational Databases / Incomplete Databases / The Chase Algorithm / Chase Termination / Data Dependencies and Normal Forms / Universal Repairs / Chase and Database ApplicationsTable of ContentsIntroduction.- Relational Databases.- Incomplete Databases.- The Chase Algorithm.- Chase Termination.- Data Dependencies and Normal Forms.- Universal Repairs.- Chase and Database Applications.

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Book SynopsisAfter the traditional document-centric Web 1.0 and user-generated content focused Web 2.0, Web 3.0 has become a repository of an ever growing variety of Web resources that include data and services associated with enterprises, social networks, sensors, cloud, as well as mobile and other devices that constitute the Internet of Things. These pose unprecedented challenges in terms of heterogeneity (variety), scale (volume), and continuous changes (velocity), as well as present corresponding opportunities if they can be exploited. Just as semantics has played a critical role in dealing with data heterogeneity in the past to provide interoperability and integration, it is playing an even more critical role in dealing with the challenges and helping users and applications exploit all forms of Web 3.0 data. This book presents a unified approach to harness and exploit all forms of contemporary Web resources using the core principles of ability to associate meaning with data through conceptual or domain models and semantic descriptions including annotations, and through advanced semantic techniques for search, integration, and analysis. It discusses the use of Semantic Web standards and techniques when appropriate, but also advocates the use of lighter weight, easier to use, and more scalable options when they are more suitable. The authors' extensive experience spanning research and prototypes to development of operational applications and commercial technologies and products guide the treatment of the material. Table of Contents: Role of Semantics and Metadata / Types and Models of Semantics / Annotation -- Adding Semantics to Data / Semantics for Enterprise Data / Semantics for Services / Semantics for Sensor Data / Semantics for Social Data / Semantics for Cloud Computing / Semantics for Advanced ApplicationsTable of ContentsRole of Semantics and Metadata.- Types and Models of Semantics.- Annotation -- Adding Semantics to Data.- Semantics for Enterprise Data.- Semantics for Services.- Semantics for Sensor Data.- Semantics for Social Data.- Semantics for Cloud Computing.- Semantics for Advanced Applications.

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Book SynopsisCloud computing has emerged as a successful paradigm of service-oriented computing and has revolutionized the way computing infrastructure is used. This success has seen a proliferation in the number of applications that are being deployed in various cloud platforms. There has also been an increase in the scale of the data generated as well as consumed by such applications. Scalable database management systems form a critical part of the cloud infrastructure. The attempt to address the challenges posed by the management of big data has led to a plethora of systems. This book aims to clarify some of the important concepts in the design space of scalable data management in cloud computing infrastructures. Some of the questions that this book aims to answer are: the appropriate systems for a specific set of application requirements, the research challenges in data management for the cloud, and what is novel in the cloud for database researchers? We also aim to address one basic question: whether cloud computing poses new challenges in scalable data management or it is just a reincarnation of old problems? We provide a comprehensive background study of state-of-the-art systems for scalable data management and analysis. We also identify important aspects in the design of different systems and the applicability and scope of these systems. A thorough understanding of current solutions and a precise characterization of the design space are essential for clearing the "cloudy skies of data management" and ensuring the success of DBMSs in the cloud, thus emulating the success enjoyed by relational databases in traditional enterprise settings. Table of Contents: Introduction / Distributed Data Management / Cloud Data Management: Early Trends / Transactions on Co-located Data / Transactions on Distributed Data / Multi-tenant Database Systems / Concluding RemarksTable of ContentsIntroduction.- Distributed Data Management.- Cloud Data Management: Early Trends.- Transactions on Co-located Data.- Transactions on Distributed Data.- Multi-tenant Database Systems.- Concluding Remarks.

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Book SynopsisMobile agent computing is being used in fields as diverse as artificial intelligence, computational economics and robotics. Agents' ability to adapt dynamically and execute asynchronously and autonomously brings potential advantages in terms of fault-tolerance, flexibility and simplicity. This monograph focuses on studying mobile agents as modelled in distributed systems research and in particular within the framework of research performed in the distributed algorithms community. It studies the fundamental question of how to achieve rendezvous, the gathering of two or more agents at the same node of a network. Like leader election, such an operation is a useful subroutine in more general computations that may require the agents to synchronize, share information, divide up chores, etc. The work provides an introduction to the algorithmic issues raised by the rendezvous problem in the distributed computing setting. For the most part our investigation concentrates on the simplest case of two agents attempting to rendezvous on a ring network. Other situations including multiple agents, faulty nodes and other topologies are also examined. An extensive bibliography provides many pointers to related work not covered in the text. The presentation has a distinctly algorithmic, rigorous, distributed computing flavor and most results should be easily accessible to advanced undergraduate and graduate students in computer science and mathematics departments. Table of Contents: Models for Mobile Agent Computing / Deterministic Rendezvous in a Ring / Multiple Agent Rendezvous in a Ring / Randomized Rendezvous in a Ring / Other Models / Other TopologiesTable of ContentsModels for Mobile Agent Computing.- Deterministic Rendezvous in a Ring.- Multiple Agent Rendezvous in a Ring.- Randomized Rendezvous in a Ring.- Other Models.- Other Topologies.

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Book SynopsisUnderstanding distributed computing is not an easy task. This is due to the many facets of uncertainty one has to cope with and master in order to produce correct distributed software. Considering the uncertainty created by asynchrony and process crash failures in the context of message-passing systems, the book focuses on the main abstractions that one has to understand and master in order to be able to produce software with guaranteed properties. These fundamental abstractions are communication abstractions that allow the processes to communicate consistently (namely the register abstraction and the reliable broadcast abstraction), and the consensus agreement abstractions that allows them to cooperate despite failures. As they give a precise meaning to the words "communicate" and "agree" despite asynchrony and failures, these abstractions allow distributed programs to be designed with properties that can be stated and proved. Impossibility results are associated with these abstractions. Hence, in order to circumvent these impossibilities, the book relies on the failure detector approach, and, consequently, that approach to fault-tolerance is central to the book. Table of Contents: List of Figures / The Atomic Register Abstraction / Implementing an Atomic Register in a Crash-Prone Asynchronous System / The Uniform Reliable Broadcast Abstraction / Uniform Reliable Broadcast Abstraction Despite Unreliable Channels / The Consensus Abstraction / Consensus Algorithms for Asynchronous Systems Enriched with Various Failure Detectors / Constructing Failure DetectorsTable of ContentsList of Figures.- The Atomic Register Abstraction.- Implementing an Atomic Register in a Crash-Prone Asynchronous System.- The Uniform Reliable Broadcast Abstraction.- Uniform Reliable Broadcast Abstraction Despite Unreliable Channels.- The Consensus Abstraction.- Consensus Algorithms for Asynchronous Systems Enriched with Various Failure Detectors.- Constructing Failure Detectors.

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Book SynopsisUnderstanding distributed computing is not an easy task. This is due to the many facets of uncertainty one has to cope with and master in order to produce correct distributed software. A previous book Communication and Agreement Abstraction for Fault-tolerant Asynchronous Distributed Systems (published by Morgan & Claypool, 2010) was devoted to the problems created by crash failures in asynchronous message-passing systems. The present book focuses on the way to cope with the uncertainty created by process failures (crash, omission failures and Byzantine behavior) in synchronous message-passing systems (i.e., systems whose progress is governed by the passage of time). To that end, the book considers fundamental problems that distributed synchronous processes have to solve. These fundamental problems concern agreement among processes (if processes are unable to agree in one way or another in presence of failures, no non-trivial problem can be solved). They are consensus, interactive consistency, k-set agreement and non-blocking atomic commit. Being able to solve these basic problems efficiently with provable guarantees allows applications designers to give a precise meaning to the words ""cooperate"" and ""agree"" despite failures, and write distributed synchronous programs with properties that can be stated and proved. Hence, the aim of the book is to present a comprehensive view of agreement problems, algorithms that solve them and associated computability bounds in synchronous message-passing distributed systems. Table of Contents: List of Figures / Synchronous Model, Failure Models, and Agreement Problems / Consensus and Interactive Consistency in the Crash Failure Model / Expedite Decision in the Crash Failure Model / Simultaneous Consensus Despite Crash Failures / From Consensus to k-Set Agreement / Non-Blocking Atomic Commit in Presence of Crash Failures / k-Set Agreement Despite Omission Failures / Consensus Despite Byzantine Failures / Byzantine Consensus in Enriched ModelsTable of ContentsList of Figures.- Synchronous Model, Failure Models, and Agreement Problems.- Consensus and Interactive Consistency in the Crash Failure Model.- Expedite Decision in the Crash Failure Model.- Simultaneous Consensus Despite Crash Failures.- From Consensus to k-Set Agreement.- Non-Blocking Atomic Commit in Presence of Crash Failures.- k-Set Agreement Despite Omission Failures.- Consensus Despite Byzantine Failures.- Byzantine Consensus in Enriched Models.

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Book SynopsisWireless sensor networks are about to be part of everyday life. Homes and workplaces capable of self-controlling and adapting air-conditioning for different temperature and humidity levels, sleepless forests ready to detect and react in case of a fire, vehicles able to avoid sudden obstacles or possibly able to self-organize routes to avoid congestion, and so on, will probably be commonplace in the very near future. Mobility plays a central role in such systems and so does passive mobility, that is, mobility of the network stemming from the environment itself. The population protocol model was an intellectual invention aiming to describe such systems in a minimalistic and analysis-friendly way. Having as a starting-point the inherent limitations but also the fundamental establishments of the population protocol model, we try in this monograph to present some realistic and practical enhancements that give birth to some new and surprisingly powerful (for these kind of systems) computational models. Table of Contents: Population Protocols / The Computational Power of Population Protocols / Enhancing the model / Mediated Population Protocols and Symmetry / Passively Mobile Machines that Use Restricted Space / Conclusions and Open Research Directions / Acronyms / Authors' BiographiesTable of ContentsPopulation Protocols.- The Computational Power of Population Protocols.- Enhancing the model.- Mediated Population Protocols and Symmetry.- Passively Mobile Machines that Use Restricted Space.- Conclusions and Open Research Directions.- Acronyms.- Authors' Biographies.

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Book SynopsisCooperative network supercomputing is becoming increasingly popular for harnessing the power of the global Internet computing platform. A typical Internet supercomputer consists of a master computer or server and a large number of computers called workers, performing computation on behalf of the master. Despite the simplicity and benefits of a single master approach, as the scale of such computing environments grows, it becomes unrealistic to assume the existence of the infallible master that is able to coordinate the activities of multitudes of workers. Large-scale distributed systems are inherently dynamic and are subject to perturbations, such as failures of computers and network links, thus it is also necessary to consider fully distributed peer-to-peer solutions. We present a study of cooperative computing with the focus on modeling distributed computing settings, algorithmic techniques enabling one to combine efficiency and fault-tolerance in distributed systems, and the exposition of trade-offs between efficiency and fault-tolerance for robust cooperative computing. The focus of the exposition is on the abstract problem, called Do-All, and formulated in terms of a system of cooperating processors that together need to perform a collection of tasks in the presence of adversity. Our presentation deals with models, algorithmic techniques, and analysis. Our goal is to present the most interesting approaches to algorithm design and analysis leading to many fundamental results in cooperative distributed computing. The algorithms selected for inclusion are among the most efficient that additionally serve as good pedagogical examples. Each chapter concludes with exercises and bibliographic notes that include a wealth of references to related work and relevant advanced results. Table of Contents: Introduction / Distributed Cooperation and Adversity / Paradigms and Techniques / Shared-Memory Algorithms / Message-Passing Algorithms / The Do-All Problem in Other Settings / Bibliography / Authors' BiographiesTable of ContentsIntroduction.- Distributed Cooperation and Adversity.- Paradigms and Techniques.- Shared-Memory Algorithms.- Message-Passing Algorithms.- The Do-All Problem in Other Settings.- Bibliography.- Authors' Biographies.

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Book SynopsisLink reversal is a versatile algorithm design technique that has been used in numerous distributed algorithms for a variety of problems. The common thread in these algorithms is that the distributed system is viewed as a graph, with vertices representing the computing nodes and edges representing some other feature of the system (for instance, point-to-point communication channels or a conflict relationship). Each algorithm assigns a virtual direction to the edges of the graph, producing a directed version of the original graph. As the algorithm proceeds, the virtual directions of some of the links in the graph change in order to accomplish some algorithm-specific goal. The criterion for changing link directions is based on information that is local to a node (such as the node having no outgoing links) and thus this approach scales well, a feature that is desirable for distributed algorithms. This monograph presents, in a tutorial way, a representative sampling of the work on link-reversal-based distributed algorithms. The algorithms considered solve routing, leader election, mutual exclusion, distributed queueing, scheduling, and resource allocation. The algorithms can be roughly divided into two types, those that assume a more abstract graph model of the networks, and those that take into account more realistic details of the system. In particular, these more realistic details include the communication between nodes, which may be through asynchronous message passing, and possible changes in the graph, for instance, due to movement of the nodes. We have not attempted to provide a comprehensive survey of all the literature on these topics. Instead, we have focused in depth on a smaller number of fundamental papers, whose common thread is that link reversal provides a way for nodes in the system to observe their local neighborhoods, take only local actions, and yet cause global problems to be solved. We conjecture that future interesting uses of link reversal are yet to be discovered. Table of Contents: Introduction / Routing in a Graph: Correctness / Routing in a Graph: Complexity / Routing and Leader Election in a Distributed System / Mutual Exclusion in a Distributed System / Distributed Queueing / Scheduling in a Graph / Resource Allocation in a Distributed System / ConclusionTable of ContentsIntroduction.- Routing in a Graph: Correctness.- Routing in a Graph: Complexity.- Routing and Leader Election in a Distributed System.- Mutual Exclusion in a Distributed System.- Distributed Queueing.- Scheduling in a Graph.- Resource Allocation in a Distributed System.- Conclusion.

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Book SynopsisA quorum system is a collection of subsets of nodes, called quorums, with the property that each pair of quorums have a non-empty intersection. Quorum systems are the key mathematical abstraction for ensuring consistency in fault-tolerant and highly available distributed computing. Critical for many applications since the early days of distributed computing, quorum systems have evolved from simple majorities of a set of processes to complex hierarchical collections of sets, tailored for general adversarial structures. The initial non-empty intersection property has been refined many times to account for, e.g., stronger (Byzantine) adversarial model, latency considerations or better availability. This monograph is an overview of the evolution and refinement of quorum systems, with emphasis on their role in two fundamental applications: distributed read/write storage and consensus. Table of Contents: Introduction / Preliminaries / Classical Quorum Systems / Classical Quorum-Based Emulations / Byzantine Quorum Systems / Latency-efficient Quorum Systems / Probabilistic Quorum SystemsTable of ContentsIntroduction.- Preliminaries.- Classical Quorum Systems.- Classical Quorum-Based Emulations.- Byzantine Quorum Systems.- Latency-efficient Quorum Systems.- Probabilistic Quorum Systems.

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Book SynopsisThe study of what can be computed by a team of autonomous mobile robots, originally started in robotics and AI, has become increasingly popular in theoretical computer science (especially in distributed computing), where it is now an integral part of the investigations on computability by mobile entities. The robots are identical computational entities located and able to move in a spatial universe; they operate without explicit communication and are usually unable to remember the past; they are extremely simple, with limited resources, and individually quite weak. However, collectively the robots are capable of performing complex tasks, and form a system with desirable fault-tolerant and self-stabilizing properties. The research has been concerned with the computational aspects of such systems. In particular, the focus has been on the minimal capabilities that the robots should have in order to solve a problem. This book focuses on the recent algorithmic results in the field of distributed computing by oblivious mobile robots (unable to remember the past). After introducing the computational model with its nuances, we focus on basic coordination problems: pattern formation, gathering, scattering, leader election, as well as on dynamic tasks such as flocking. For each of these problems, we provide a snapshot of the state of the art, reviewing the existing algorithmic results. In doing so, we outline solution techniques, and we analyze the impact of the different assumptions on the robots' computability power. Table of Contents: Introduction / Computational Models / Gathering and Convergence / Pattern Formation / Scatterings and Coverings / Flocking / Other DirectionsTable of ContentsIntroduction.- Computational Models.- Gathering and Convergence.- Pattern Formation.- Scatterings and Coverings.- Flocking.- Other Directions.

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Book SynopsisThe focus of this monograph is on symmetry breaking problems in the message-passing model of distributed computing. In this model a communication network is represented by a n-vertex graph G = (V,E), whose vertices host autonomous processors. The processors communicate over the edges of G in discrete rounds. The goal is to devise algorithms that use as few rounds as possible. A typical symmetry-breaking problem is the problem of graph coloring. Denote by ? the maximum degree of G. While coloring G with ? + 1 colors is trivial in the centralized setting, the problem becomes much more challenging in the distributed one. One can also compromise on the number of colors, if this allows for more efficient algorithms. Other typical symmetry-breaking problems are the problems of computing a maximal independent set (MIS) and a maximal matching (MM). The study of these problems dates back to the very early days of distributed computing. The founding fathers of distributed computing laid firm foundations for the area of distributed symmetry breaking already in the eighties. In particular, they showed that all these problems can be solved in randomized logarithmic time. Also, Linial showed that an O(?2)-coloring can be solved very efficiently deterministically. However, fundamental questions were left open for decades. In particular, it is not known if the MIS or the (? + 1)-coloring can be solved in deterministic polylogarithmic time. Moreover, until recently it was not known if in deterministic polylogarithmic time one can color a graph with significantly fewer than ?2 colors. Additionally, it was open (and still open to some extent) if one can have sublogarithmic randomized algorithms for the symmetry breaking problems. Recently, significant progress was achieved in the study of these questions. More efficient deterministic and randomized (? + 1)-coloring algorithms were achieved. Deterministic ?1 + o(1)-coloring algorithms with polylogarithmic running time were devised. Improved (and often sublogarithmic-time) randomized algorithms were devised. Drastically improved lower bounds were given. Wide families of graphs in which these problems are solvable much faster than on general graphs were identified. The objective of our monograph is to cover most of these developments, and as a result to provide a treatise on theoretical foundations of distributed symmetry breaking in the message-passing model. We hope that our monograph will stimulate further progress in this exciting area.Table of ContentsAcknowledgments.- Introduction.- Basics of Graph Theory.- Basic Distributed Graph Coloring Algorithns.- Lower Bounds.- Forest-Decomposition Algorithms and Applications.- Defective Coloring.- Arbdefective Coloring.- Edge-Coloring and Maximal Matching.- Network Decompositions.- Introduction to Distributed Randomized Algorithms.- Conclusion and Open Questions.- Bibliography.- Authors' Biographies.

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Book SynopsisPrevalent types of data in scientific visualization are volumetric data, vector field data, and particle-based data. Particle data typically originates from measurements and simulations in various fields, such as life sciences or physics. The particles are often visualized directly, that is, by simple representants like spheres. Interactive rendering facilitates the exploration and visual analysis of the data. With increasing data set sizes in terms of particle numbers, interactive high-quality visualization is a challenging task. This is especially true for dynamic data or abstract representations that are based on the raw particle data. This book covers direct particle visualization using simple glyphs as well as abstractions that are application-driven such as clustering and aggregation. It targets visualization researchers and developers who are interested in visualization techniques for large, dynamic particle-based data. Its explanations focus on GPU-accelerated algorithms for high-performance rendering and data processing that run in real-time on modern desktop hardware. Consequently, the implementation of said algorithms and the required data structures to make use of the capabilities of modern graphics APIs are discussed in detail. Furthermore, it covers GPU-accelerated methods for the generation of application-dependent abstract representations. This includes various representations commonly used in application areas such as structural biology, systems biology, thermodynamics, and astrophysics.Table of ContentsAcknowledgments.- Figure Credits.- Introduction.- History.- GPU-based Glyph Ray Casting.- Acceleration Strategies.- Data Structures.- Efficient Nearest Neighbor Search on the GPU.- Improved Visual Quality.- Application-driven Abstractions.- Summary and Outlook.- Bibliography.- Authors' Biographies.

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Book SynopsisThis book constitutes the refereed proceedings of the 4th International Conference on HCI for Cybersecurity, Privacy and Trust, HCI-CPT 2022, held as part of the 23rd International Conference, HCI International 2022, which was held virtually in June/July 2022. The total of 1271 papers and 275 posters included in the HCII 2022 proceedings was carefully reviewed and selected from 5487 submissions. The HCI-CPT 2022 proceedings focuses on to user privacy and data protection, trustworthiness and User Experience in cybersecurity, multi-faceted authentication methods and tools, HCI in cyber defense and protection, studies on usable security in Intelligent Environments, as well as the impact of the Covid-19 pandemic on cybersecurityTable of ContentsUser Privacy and Data Protection.- Trustworthiness and User Experience in Cybersecurity.- Multi-faceted Authentication Methods and Tools.- HCI in Cyber Defense and Protection.- Studies on Usable Security in Intelligent Environments.- The Impact of the Covid-19 Pandemic on Cybersecurity.

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Book SynopsisThis book constitutes the refereed proceedings of the 20th International Conference on Artificial Intelligence in Medicine, AIME 2022, held in Halifax, NS, Canada, in June 2022. The 39 full papers presented together with 7 short papers were selected from 113 submissions. The papers are grouped in topical sections on knowledge-based system; machine learning; medical image processing; predictive modeling; natural language processing.Table of ContentsKnowledge-Based Systems Explainable Decision Support Using Task Network Models in Notation.- Computerizing Lipid Management Clinical Guidelines as Interactive Task Networks.- Towards an AI planning-based pipeline for the management of multimorbid patients.- A Knowledge Graph Completion Method Applied to Literature-Based Discovery for Predicting Missing Links Targeting Cancer Drug Repurposing.- Ontological Representation of Causal Relations for a Deep Understanding of Associations between Variables in Epidemiology.- Explainable Clinical Decision Support: Towards Patient-Facing Explanations for Education and Long-term Behavior Change.- Machine Learning Assessing Knee Biomechanical Osteoarthritis Severity and Biomechanical Changes After Total Knee Arthroplasty Using Self-Organizing Maps.- NeuralSympCheck: A Symptom Checking and Disease Diagnostic Neural Model with Extracting Surrogate Decision Trees from Black-box Models to Explain the Temporal Importance of Clinical Features in Predicting Kidney Graft Survival.- Recurrence and Self-Attention vs the Transformer for Time-Series Classification: A Comparative Study.- Integrating Graph Convolutional Neural Networks and Long Short-Term Memory for Efficient Diagnosis of Autism.- Hierarchical Deep Multi-task learning for Classification of Patient Diagnoses.- TTS-GAN: A Transformer-based Time-Series Generative Adversarial Network.- Predicting Next Kidney Offer for Transplant Candidate Declining Current One.- Wrist Ultrasound Segmentation by Deep Learning.- Early Detection and Classification of Patient-Ventilator Asynchrony using Machine Learning.- On graph construction for classification of clinical trials protocols using Graph Neural Networks.- Medical Image Processing Malignant Mesothelioma Subtyping of Tissue Images via Sampling Driven Multiple Instance Prediction.- Calibrating Histopathology Image Classifiers using Label Smoothing.- InvUNET: Involuted UNET for Breast Tumor Segmentation from Ultrasound.- MRI reconstruction with LassoNet and compressed sensing.- Predictive Modeling A 3-window-based framework for the discovery of predictive functional dependencies from clinical data.- When can I expect the mHealth user to return? Prediction meets time series with gaps.- A novel survival analysis approach to predict the need for intubation in intensive care units.- Awareness of being tested and its effect on reading behaviour.- Natural Language Processing Generating extremely short summaries from the scientific literature to support decisions in primary healthcare: a human evaluation study.- A Russian Medical Language Understanding Benchmark.- Biomedical Semantic Textual Similarity: Evaluation of Sentence Representations Enhanced With Principal Component Reduction and Word Frequency Weighting.

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Book SynopsisThis book constitutes the refereed proceedings of the Third International Conference on Next Generation Arithmetic, CoNGA 2022, which was held in Singapore, during March 1–3, 2022. The 8 full papers included in this book were carefully reviewed and selected from 12 submissions. They deal with emerging technologies for computer arithmetic focusing on the demands of both AI and high-performance computing. Table of ContentsOn the Implementation of Edge Detection Algorithms with SORN Arithmetic.- A Posit8 Decompression Operator for Deep Neural Network Inference.- Qtorch+: Next Generation Arithmetic for Pytorch Machine Learning.- ACTION: Automated Hardware-Software Codesign Framework for Low-precision Numerical Format SelecTION in TinyML.- MultiPosits: Universal Coding of Rn.- Comparing Different Decodings for Posit Arithmetic.- Universal⋆: Reliable, Reproducible, and Energy-Efficient Numerics.- Small reals representations for Deep Learning at the edge: a comparison.

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Book SynopsisThis book constitutes the refereed proceedings of the 20th International Conference on Software Engineering and Formal Methods, SEFM 2022, which took place in Berlin, Germany, in September 2022. The 19 full and 3 short papers included in this book were carefully reviewed and selected from 62 submissions. They were organized in topical sections as follows: software verification; program analysis; verifier technology; formal methods for intelligent and learning systems; specification and contracts; program synthesis; temporal logic; and runtime methods.

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Book SynopsisThis book constitutes thoroughly refereed and revised selected papers from the proceedings of 19th European Conference on Multi-Agent Systems, EUMAS 2022, held in Düsseldorf, Germany, during September 14–16, 2022.The 23 full papers included in this book were carefully reviewed and selected from 36 submissions. The book also contains 6 short summaries of talks from PhD students at the PhD day. The papers deal with current topics in the research and development of multi-agent systems.Table of ContentsEUMAS 2022 Papers.- Iterative Goal-Based Approval Voting.- Mind the Gap! Runtime Verification of Partially Observable MASs with Probabilistic Trace Expressions.- Advising Agent for Service-Providing Live-Chat Operators.- Initial Conditions Sensitivity Analysis of a Two-Species Butterfly-Effect Agent-Based Model.- Proxy Manipulation for Better Outcomes.- The Spread of Opinions via Boolean Networks.- Robustness of Greedy Approval Rules.- Using Multiwinner Voting to Search for Movies.- Allocating Teams to Tasks: An Anytime Heuristic Competence-Based Approach.- Collaborative Decision Making for Lane-Free Autonomous Driving in the Presence of Uncertainty.- Maximin Shares under Cardinality Constraints.- Welfare Effects of Strategic Voting under Scoring Rules.- Preserving Consistency for Liquid Knapsack Voting.- Strategic Nominee Selection in Tournament Solutions.- Sybil-Resilient Social Choice with Low Voter Turnout.- A Survey of Ad Hoc Teamwork Research.- Combining Theory of Mind and Abduction for Cooperation under Imperfect Information.- A Modular Architecture for Integrating Normative Advisors in MAS.- Participatory Budgeting with Multiple Resources.- A Methodology for Formalizing Different Types of Norms.- Explainability in Mechanism Design: Recent Advances and the Road Ahead.- Integrating Quantitative and Qualitative Reasoning for Value Alignment.- Resource Allocation to Agents with Restrictions: Maximizing Likelihood with Minimum Compromise.- PhD Day Short Papers.- Proactivity in Intelligent Personal Assistants: A Simulation-based Approach.- Stability, Fairness, and Altruism in Coalition Formation.- Pro-Social Autonomous Agents.- Axiomatic and Algorithmic Study on Different Areas of Collective Decision Making.- Participatory Budgeting: Fairness and Welfare Maximization.- Human Consideration in Analysis and Algorithms for Mechanism Design.

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Book SynopsisThis book constitutes the proceedings of the Third International Conference on Microelectronic Devices, Circuits and Systems, ICMDCS 2022, was held in Vellore, India, in August 2022.The 9 full papers and 5 short paper presented in this volume were carefully reviewed and selected from 84 submissions. The papers are organized in the following topical sections: System Level Design; Digital Design; Analog, Mixed-Signal and RF Design; and Emerging Technologies.Table of Contents​System Level Design.- Tapered Fed Modified Patch Antenna for SWB Communications using DGS.- Design of Hardware Accelerator for Facial Recognition System using Convolutional Neural Networks based on FPGA.- Digital Design.- Advanced TSV-BIST Repair Technique to target the Yield and Test challenges in 3-D Stacked IC’s.- Redundancy allocation problem evaluation using interval-based GA and PSO for multi-core system consisting of one instruction cores.- Design of Low Powered and High Speed Compressor based Multiplier.-A Route Planning for Idyllic Coverage in Sensor Networks with Efficient Area Coverage.- Low Power Mod 2 Synchronous Counter Design using Modified Gate Diffusion Input Technique.- Analog, Mixed-Signal and RF Design.- A novel blind zone free, low power phase frequency detector for fast locking of charge pump phase locked loops.- Performance Improvement of H-Shaped Antenna for Wireless Local Area Networks.- Emerging Technologies.- Real-Time Rainfall Prediction System using IoT and Machine Learning.- Performance Analysis of Image Caption Generation using Deep Learning Techniques.- The Heroes and Villains of the Mix Zone: The Preservation and Leaking of User’s Privacy in Future Vehicles.- Analysis and Design of High Speed and Low Power Finite Impulse Response Filter using Different Types of Multipliers.- MPPT using P&O algorithm for Solar-Battery powered Electric Vehicle.

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Book SynopsisThis book constitutes the refereed proceedings of the 8th International Conference on Modelling and Development of Intelligent Systems, MDIS 2022, held in Sibiu, Romania, during October 28–30, 2022.The 21 papers included in this book were carefully reviewed and selected from 48 submissions. They were organized in the following topical sections as follows: intelligent systems for decision support; machine learning; mathematical models for development of intelligent systems; and modelling and optimization of dynamic systems.Table of ContentsIntelligent Systems for Decision Support.- Effective LSTM Neural Network with Adam Optimizer for Improving Frost Prediction in Agriculture Data Stream.- Gaze Tracking: A Survey of Devices, Libraries and Applications.- Group Decision-Making Involving Competence of Experts in Relation to Evaluation Criteria: Case Study for e-Commerce Platform Selection.- Transparency and Traceability for AI-based Defect Detection in PCB Production.- Tasks Management Using Modern Devices.- Machine Learning.- A Method for Target Localization by Multistatic Radars.- Intrusion Detection by XGBoost Model Tuned by Improved Social Network Search Algorithm.- Bridging the Resource Gap in Cross-lingual Embedding Space.- Classification of Microstructure Images of Metals using Transfer Learning.- Generating Jigsaw Puzzles and an AI Powered Solver.- Morphology of Convolutional Neural Network with Diagonalized Pooling.- Challenges and Opportunities in Deep Learning Driven Fashion Design and Textiles Patterns Development.- Feature Selection and Extreme Learning Machine Tuning by Hybrid Sand Cat Optimization Algorithm for Diabetes Classification.- Enriching SQL-Driven Data Exploration With Different Machine Learning Models.- Mathematical Models for Development of Intelligent Systems.- Analytical Solution of the Simplest Entropiece Inversion Problem.- Latent Semantic Structure in Malicious Programs.- Innovative Lattice Sequences Based on Component by Component Construction Method for Multidimensional Sensitivity Analysis.- On an Optimization of the Lattice Sequence for the Multidimensional Integrals Connected with Bayesian Statistics.- Modelling and Optimization of Dynamic Systems.- Numerical Optimization Identification of a Keller-Segel Model for Thermoregulation in Honey Bee Colonies in Winter.- Gradient Optimization in Reconstruction of the Diffusion Coefficient in a Time Fractional Integro-Differential Equation of Pollution in Porous Media.- Flash Flood Simulation Between Slănic and Vărbilău Rivers in Vărbilău Village, Prahova County, Romania, Using Hydraulic Modeling and GIS Techniques.

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Book SynopsisThis book constitutes the proceedings of the 18th International Workshop on Algorithms and Models for the Web Graph, WAW 2023, held in Toronto, Canada, in May 23–26, 2023.The 12 Papers presented in this volume were carefully reviewed and selected from 21 submissions. The aim of the workshop was understanding of graphs that arise from the Web and various user activities on the Web, and stimulate the development of high-performance algorithms and applications that exploit these graphs.Table of ContentsCorrecting for Granularity Bias in Modularity-Based Community Detection Methods.- The emergence of a giant component in one-dimensional inhomogeneous networks with long-range effects.- Unsupervised Framework for Evaluating Structural Node Embeddings of Graphs.- Modularity Based Community Detection in Hypergraphs.- Establishing Herd Immunity is Hard Even in Simple Geometric Networks.- Multilayer hypergraph clustering using the aggregate similarity matrix.- The Myth of the Robust-Yet-Fragile Nature of Scale-Free Networks: An Empirical Analysis.- A Random Graph Model for Clustering Graphs.- Topological Analysis of Temporal Hypergraphs.- PageRank Nibble on the sparse directed stochastic block model.- A simple model of influence.- The Iterated Local Transitivity Model for Tournaments.

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Book SynopsisThis book constitutes the refereed proceedings of the 22nd International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2023, held in Ekaterinburg, Russia, during July 2–8, 2023. The 28 full papers and 1 short paper included in this book were carefully reviewed and selected from 89 submissions. They were organized in topical sections as follows: Mathematical programming and applications; discrete and combinatorial optimization; stochastic optimization; scheduling; game theory; and optimal control and mathematical economics. The book also contains one invited talk in full paper length. Table of Contents​Invited papers.- General equilibrium models in production networks with substitution of inputs.- Mathematical programming and applications.- On decentralized nonsmooth optimization.- Byzantine-robust loopless stochastic variance-reduced gradient.- Semi-supervised k-means clustering via DC programming approach.- On the uniqueness of identification the thermal conductivity and heat capacit of substance.- On the uniqueness of identification the thermal conductivity and heat capacity of substance.- Discrete and combinatorial optimization.- Constant-factor approximation algorithms for some maximin multiclustering problems.- Aggregation tree construction using hierarchical structures.- Enumeration and unimodular equivalence of empty delta-modular simplices.- PTAS for p-means q-medoids r-given clustering problem.- Nested (2,3)-instances of the Cutting Stock Problem.- Stochastic optimization.- On the resource allocation problem to increase reliability of transport systems.- Distributionally robust optimization by probability criterion for estimating a bounded signal.- Scheduling.- Approximation algorithms for two-machine proportionate routing open shop on a tree.- MIP heuristics for a resource constrained project scheduling problem with workload stability constraints.- Hybrid evolutionary algorithm with optimized operators for total weighted tardiness problem.- Game theory.- Equilibrium arrivals to preemptive queueing system with fixed reward for completing request.- On optimal positional strategies in fractional optimal control problems.- On a single-type differential game of retention in a ring.- Harmonic numbers in Gambler’s Ruin Problem.- Exploitation and recovery periods in dynamic resource management problem.- Trade-off mechanism to sustain cooperation in pollution reduction.- Communication restriction-based characteristic function in differential games on networks.- Optimal control and mathematical economics.- Guaranteed expectation of the flock position with random distribution of items.- Method for solving a differential inclusion with a subdifferentiable support function of the right-hand side.- Approximate solution of small-time control synthesis problem based on linearization.- A Priori Estimates of the Objective Function in the Speed-in-Action Problem for a Linear Two-Dimensional Discrete-Time System.- An approach to solving input reconstruction problems in stochastic differential equations: dynamic algorithms and tuning their parameters.- Mathematical modeling of the household behavior on the labor market.- Visual positioning of a moving object using multi-objective control algorithm.

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Book SynopsisThis book constitutes the proceedings of the 21st International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2023, held in Guimaraes, Portugal, in July 2023.The 32 full papers in this book were reviewed and selected from 70 submissions. 5 demonstration papers are also included in this volume. The papers deal with the application and validation of agent-based models, methods, and technologies in a number of key applications areas, including: advanced models and learning, agent-based programming, decision-making, education and social interactions, formal and theoretic models, health and safety, mobility and the city, swarms and task allocation.Table of Contents​PAAMS 2023 - MAIN TRACK.- Brain waves classification using a single-channel dry EEG headset: an application for controlling an intelligent wheelchair.- AJAN: An Engineering Framework for Semantic Web-Enabled Agents and Multi-Agent Systems.- Adaptive consumption by continuous negotiation.- When Extrinsic Payoffs meet Intrinsic Expectations.- Multi-Agent Reinforcement Learning for Structured Symbolic Music Generation.- A multi-level density-based crowd simulation architecture.- Resolving the Dilemma of Responsibility in Multi-Agent Flow Networks.- Lessons Learned on the Design of a Predictive Agent for LoRaWAN Network Planning.- A solution concept with an exploration bias for repeated stochastic coalitional games.- Governing online forum interactions with multi-agent system: A Reddit use case with the JaCaMo platform.- Fuzzy Hyperplane based Twin-KSVC and Its Applications to Stock Price Movement Direction Prediction Based on News Articles.- Enhancing Safety Checking Coverage with Multi-swarm Particle Swarm Optimization.- A Decentralized Resource Allocation Protocol in Social Networks.- Multi-agent learning of causal networks in the Internet of Things.- Investigation of Integrating Solution Techniques for Lifelong MAPD Problem Considering Endpoints.- Towards Norm Entrepreneurship in Agent Societies.- Velluscinum: A Middleware for Using Digital Assets in Multi-Agent Systems.- Parking Problem with Multiple Gates.- UAV Swarm Control and Coordination Using Jason BDI Agents on top of ROS.- Traffic Assignment Optimization using Flow-based Multi-Maps.- A Monitoring Agent for Advancing Elderly Care through Mobile Health Technology.- Extrinsic Emotion Regulation by Intelligent Agents: A computational model based on Arousal-Valence dimensions.- Optimization of Complex Systems in Photonics by Multi-Agent Robotic Control.- GTG-CoL: A new Decentralized Federated Learning based on Consenssus for dynamic networks.- A novel framework for multi-agent knowledge-based federated learning systems.- Exploring Planner-Guided Swarms Running on Real Robots.- Integrating Policy Summaries with Reward Decomposition for Explaining Reinforcement Learning Agents.- A Multi-Agent Based Dynamic Network Slice Tarification Framework.- An IDE to Support the Development of Embedded Multi-Agent Systems. Bioinspired Artificial Cockroach Colony Strategy combined with 2-type Fuzzy Logic for the Priority-Based Sanitization of Railway Stations.- Embedding Autonomous Agents into Low-Power Wireless Sensor Networks.- Safe Autonomous Decision-Making with vGOAL.- PAAMS 2023 - DEMONSTRATIONS.- Towards Exception Handling in the SARL Agent Platform.- Multi-Agent Path Finding for Indoor Quadcopters.- Energy community integration of a smart home based on an open source multiagent system.- Cognitive Assistant for Enhanced eHealth Monitoring.- Extended Green Cloud - Modeling Cloud Infrastructure with Green Energy Sources.

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Book SynopsisThis volume set constitutes the refereed proceedings of the 16th International Conference on Knowledge Science, Engineering and Management, KSEM 2023, which was held in Guangzhou, China, during August 16–18, 2023. The 114 full papers and 30 short papers included in this book were carefully reviewed and selected from 395 submissions. They were organized in topical sections as follows: knowledge science with learning and AI; knowledge engineering research and applications; knowledge management systems; and emerging technologies for knowledge science, engineering and management. Table of ContentsKnowledge Engineering Research and Applications.- Knowing before Seeing: Incorporating Post-Retrieval Information into Pre-Retrieval Query Intention Classification.- LSRN: Live-Streaming Identification Based on Reasoning Network with Core Traffic Set.- Implicit Offensive Speech Detection Based on Multi-feature Fusion.- SIE-YOLOv5: Improved YOLOv5 for Small Object Detection in Drone-Captured-Scenarios.- Learning-based Dichotomy Graph Sketch for Summarizing Graph Streams with High Accuracy.- SNAFA-Net: Squared Normalization Attention and Feature Alignment for Visible-Infrared Person Re-identification.- A comparative study of chatbot response generation: traditional approaches versus large language models.- Investigating the Impact of Product Contours on User Perception of Product Attributes.- Conf-UNet: A model for speculation on unknown Oracle Bone Characters.- An Efficient One-Shot Network and Robust Data Associations in Multi-Pedestrian Tracking.- Sampling Spatial-Temporal Attention Network for Traffic Forecasting.- ST-MAN: Spatio-Temporal Multimodal Attention Network for Traffic Prediction.- Sparse-view CT Reconstruction via Implicit Neural Intensity Functions.- Tennis action recognition based on multi-branch mixed attention.- Cascade Sampling via Dual Uncertainty for Active Entity Alignment.- Template Shift and Background Suppression for Visual Object Tracking.- Reversible Data Hiding in Encrypted Images Based on A Multi-Granularity Adaptive Classification Mechanism.- Enhanced Entity Interaction Modeling for Multi-modal Entity Alignment.- Monte Carlo Medical Volume Rendering Denoising via Auxiliary Feature Guided Self-Attention and Convolution Integrated.- View Distribution Alignment with Progressive Adversarial Learning for UAV Visual Geo-Localization.- HBay: Predicting Human Mobility via Hyperspherical Bayesian Learning.- Spatial-Temporal Diffusion Probabilistic Learning for Crime Prediction.- DBA: An Efficient Approach to Boost Transfer-based Adversarial Attack Performance through Information Deletion.- A Graph Partitioning Algorithm Based on Graph Structure and Label Propagation for Citation Network Prediction.- Hybrid Heterogeneous Graph Neural Networks for Fund Performance Prediction.- WGCN: A Novel Wavelet Graph Neural Network for Metro Ridership Prediction.- GMiRec: A Multi-image Visual Recommendation Model based on a Gated Neural Network.- Semi-supervised entity alignment via noisy student-based self training.- Modeling Chinese Ancient Book Catalog.- JOINT EXTRACTION OF NESTED ENTITIES AND RELATIONS BASED ON MULTI-TASK LEARNING.- A Grasping System with Structured Light 3D Machine Vision Guided Strategy Optimization.- A Cognitive Knowledge Enriched Joint Framework for Social Emotion and Cause Mining.- TKSP: Long-term Stance Prediction for Social Media Users by Fusing Time Series Features and Event Dynamic Evolution Knowledge.- A Cross-Document Coreference Resolution Approach to Low-Resource Languages.- Network Flow Based IoT Anomaly Detection Using Graph Neural Network.- Disentangled Multi-factor Graph Neural Network for Non-coding RNA-drug Resistance Association Prediction.

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Book SynopsisThis book constitutes the refereed conference proceedings of the 14th International Conference on Bio-inspired Information and Communications Technologies, held in Okinawa, Japan, during April 11-12, 2023. The 17 full papers were carefully reviewed and selected from 33 submissions. The papers focus on the latest research that leverages the understanding of key principles, processes, and mechanisms in biological systems for development of novel information and communications technologies (bio-inspired ICT). BICT 2023 will also highlight innovative research and technologies being developed for biomedicine that are inspired by ICT (ICT-inspired biomedicine).Table of ContentsElectromagnetic-induced Calcium signal with network coding for molecular communications.- Smart Farm Teaching Aids based on STEM concepts.- Reinforcement Learning for Multifocal Tumour Targeting.- Automatic Soil Testing Device for Agriculture.- A Novel Visualization Method of Vessel Network for tumour Targeting: A Vessel Matrix Approach.- Heterogeneous Group of Fish Response to Escape Reaction.- Modeling and Simulation of a Bio-inspired Nanorobotic Drug Delivery System.- Cooperative Relaying in Multi-Hop Mobile Molecular Communication via Diffusion.- Covid-19 Versus Monkeypox-2022: The Silent Struggle of Global Pandemics.- Monte Carlo Simulation of Arbitrium and the Probabilistic Behavior of Bacteriophages.- Instant Messaging Application for 5G Core Network.- Genetic Algorithm-based Fair Order Assignment Optimization of Food Delivery Platform.- Preliminary Considerations on Non-Invasive Home-Based Bone Fracture Healing Monitoring.- Features of Audio Frequency Content of Respiration to Distinguish Inhalation from Exhalation.- Management of the medical file in case of emergency.- A Novel Durable Fat Tissue Phantom for Microwave Based Medical Monitoring Applications.- ISI Mitigation with Molecular Degradation in Molecular Communication.- Signal Transmission Through Human Body Via Human Oxygen Saturation Detection.- Simple ISI-Avoiding and Rate-Increasing Modulation for Diffusion-base Molecular Communications.- Range Expansion in Neuro-spike Synaptic Communication: Error Performance Analysis.- [Extended Abstract] Collective Bio-nanomachine Rotation via Chemical and Physical Interactions: A Three- dimensional Model.- Wearable Vibration Device to Assist with Ambulation for the Visually Impaired.- Development of Capacitive Sensors to Detect and Quantify Fluids in the Adult Diaper.- Energy Cyber Attacks to Smart Healthcare Devices: A Testbed.- [Extended Abstract] Wet-laboratory Experiments and Computer Simulation of Interacting Cell Spheroids.- Ensembles of Heuristics and Computational Optimisation In Highly Flexible Manufacturing System.- A Intelligent Nanorobots Fish Swarm Strategy for Tumor Targetting.- [Extended abstract] Design and Implementation of A General-purpose Multicellular Molecular Communication Simulator.

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Book SynopsisThis book constitutes the refereed proceedings of the 27th International Conference on Linking Theory and Practice of Digital Libraries, TPDL 2023, held in Zadar, Croatia, during September 26–29, 2023.The 13 full papers and 17 short papers included in this book were carefully reviewed and selected from 69 submissions. They were organized in topical sections as follows: Applications and digital library systems; data citation and citation analysis; discovering science, monitoring and publishing science; knowledge creation; Human-Computer Interaction; digital humanities; and digital cultural heritage. Table of ContentsApplications and Digital Library Systems.- Human-in-the-loop Latent Space Learning for Bibrecord-based Literature Management.- Holistic Graph-based Document Representation and Management for Open Science.- A Multilingual Dashboard To Analyse Intercultural Knowledge Circulation.- Applications and Digital Library Systems.- Known by the Company it Keeps: Proximity-Based Indexing for Physical Content in Archival Repositories.- Aspect-Driven Structuring of Historical Dutch Newspaper Archives.- PreprintResolver: Improving Citation Quality by Resolving Published Versions of ArXiv Preprints using Literature Databases.- Data Citation and Citation Analysis.- How to Cite a Web Ranking and Make it FAIR.- Tracing Data Footprints: Formal and Informal Data Citations in the Scientific Literature.- Non-citable but not uncited: a large-scale citation analysis of editorials.- BIP! NDR (NoDoiRefs): A Dataset of Citations From Papers Without DOIs in Computer Science Conferences and Workshops.- Investigating the Relation between Authors’ Academic Age and their Citations.- Discovering science.- On Retraction Cascade? Citation Intention Analysis as a Quality Control Mechanism in Digital Libraries.- Using Semi-Automatic Annotation Platform to create Corpus for Argumentative Zoning.- CORE-GPT: Combining Open Access research and large language models for credible, trustworthy question answering.- A Robust Approach for Hybrid Personalized Recommender Systems.- Readability Measures as Predictors of Understandability and Engagement in Searching to Learn.- Classification of Visualization Types and Perspectives in Patents.- Monitoring and Publishing science.- It’s Not Just GitHub: Identifying Data and Software Sources Included in Publications.- A Graph Neural Network Approach for Evaluating Correctness of Groups of Duplicates.- Synthesizing Web Archive Collections Into Big Data: Lessons From Mining Data From Web Archives.- A Comparison of Automated Journal Recommender Systems.- Making PDFs Accessible for Visually Impaired Users (and Findable for Everybody Else).- Knowledge creation.- Multi-view Graph-based Text Representations for Imbalanced Classification.- Large Synthetic Data from the arχiv for OCR Post Correction of Historic Scientific Articles.- Human-Computer Interaction.- From textual to visual image searching: User experience of advanced image search tool.- Ranking for Learning: Studying Users’ Perceptions of Relevance, Understandability, and Engagement.- Digital Humanities.- Image Modification Modeled as a Storytelling Process.- From ISAD(G) to Linked Data Archival Descriptions.- Detection of Redacted Text in Legal Documents.- The First Tile for the Digital Onomastic Repertoire of the French Medieval Romance: Problems and Perspectives.- Digital Cultural Heritage.- Digital Cultural Heritage.- Persistent identifier usage by cultural heritage institutions: a study on the Europeana.eu dataset.- Real Experienced Needs for Accessible and Inclusive Cultural Heritage – First Results in MuseIT.

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