Volume I is the first of two volumes that document the three components of the CHILDES Project. It is divided into two parts which provide an introduction to the use of computational tools for studying language learning. The first part is the CHAT manual, which describes the conventions and principles of CHAT transcription and recommends specific methods for data collection and digitization. The second part is the CLAN manual, which describes the uses of the editor, sonic CHAT, and the various analytic commands. The book will be useful for both novice and experienced users of the CHILDES tools, as well as instructors and students working with transcripts of child language.
Volume II describes in detail all of the corpora included in the CHILDES database. The conversational interactions in the corpora come from monolingual children and their caregivers and siblings, as well as bilingual children, older school-aged children, adult second-language learners, children with various types of language disabilities, and aphasic recovering from language loss. The database includes transcripts in 26 different languages.
The CD-ROM that accompanies these volumes includes the transcript files described in Volume II. It runs on both Windows and Macintosh platforms. For more information or updates to the files, visit the CHILDES website at http: //childes.psy.cmu.edu

How do preprocessing steps such as tokenization, stemming, and removing stop words affect predictive models? Build beginning-to-end workflows for predictive modeling using text as features Compare traditional machine learning methods and deep learning methods for text data

Blockchain technology (BT) is quietly transforming the world, from financial infrastructure, to the internet-of-things, to healthcare applications. With increasing penetration of BT into various areas of our daily lives, the need arises for better awareness and greater knowledge about the capabilities, benefits, risks, and alternatives to distributed ledger applications. It is hoped that current book will be one of the pioneering collections focusing on blockchain implementations in the area of healthcare, with specific aim to present content in an easy-to-understand and readily accessible way for typical end-users of blockchain-based applications. There are important areas within the fabric of modern healthcare that stand to benefit from implementations of BT. These areas include electronic medical records, quality control, patient safety, finance, device tracking, biostamping/biocertification, redundant storage of critical data, health and liability insurance, medication utilization tracking (including opioid and antibiotic misuse), financial transactions, academics/education, asset tokenization, public health and pandemics, healthcare provider credentialing, and many other potential applications. The ultimate goal of the proposed book would be to provide an integrative, easy-to-understand, and comprehensive picture of the current state of blockchain use in healthcare while actively engaging the reader in a forward-looking, exploratory approach toward future developments in this space. To accomplish this goal, an expert panel of contributors has been assembled, featuring scholars from top global universities and think-tanks.

The development of a methodology for using logic databases is essential if new users are to be able to use these systems effectively to solve their problems, and this remains a largely unrealized goal. A workshop was organized in conjunction with the ILPS '93 Conference in Vancouver in October 1993 to provide a forum for users and implementors of deductive systems to share their experience. The emphasis was on the use of deductive systems. In addition to paper presentations, a number of systems were demonstrated. The papers of this book were drawn largely from the papers presented at the workshop, which have been extended and revised for inclusion here, and also include some papers describing interesting applications that were not discussed at the workshop. The applications described here should be seen as a starting point: a number of promising application domains are identified, and several interesting application packages are described, which provide the inspiration for further development. Declarative rule-based database systems hold a lot of promise in a wide range of application domains, and we need a continued stream of application development to better understand this potential and how to use it effectively. This book contains the broadest collection to date of papers describing implemented, significant applications of logic databases, and database systems as well as potential database users in such areas as scientific data management and complex decision support.

Written by leading industry experts, the Data Management Handbook is a comprehensive, single-volume guide to the most innovative ideas on ho w to plan, develop, and run a powerful data management function - as w ell as handle day-to-day operations. The book provides practical, hand s-on guidance on the strategic, tactical, and technical aspects of dat a management, offering an inside look at how leading companies in vari ous industries meet the challenges of moving to a data-sharing environ ment.

Topics covered include: The fundamentals of business process modeling, including workflow patterns, an in-depth treatment of process flexibility, including approaches to dealing with on-the-fly changes, unexpected exceptions, and constraint-based processes, Technological aspects of a modern BPM environment, including its architecture, process design environment, process engine, resource handler and other support services, a comparative insight into current approaches to business process modeling and execution such as BPMN, EPCs, BPEL, jBPM, OpenWFE, and Enhydra Shark, process mining, verification, integration and configuration; and case studies in health care and screen business.

This book provides a comprehensive treatment of the field of Business Process Management (BPM) with a focus on Business Process Automation. It achieves this by covering a wide range of topics, both introductory and advanced, illustrated through and grounded in the YAWL (Yet Another Workflow Language) language and corresponding open-source support environment. In doing so it provides the reader with a deep, timeless, and vendor-independent understanding of the essential ingredients of business process automation.

The BPM field is in a continual state of flux and is subject to both the ongoing proposal of new standards and the introduction of new tools and technology. Its fundamentals however are relatively stable and this book aims to equip the reader with both a thorough understanding of them and the ability to apply them to better understand, assess and utilize new developments in the BPM field.

As a consequence of its topic-based format and the inclusion of a broad range of exercises, the book is eminently suitable for use in tertiary education, both at the undergraduate and the postgraduate level, for students of computer science and information systems. BPM researchers and practitioners will also find it a valuable resource. The book serves as a unique reference to a varied and comprehensive collection of topics that are relevant to the business process life-cycle.

Soft Computing Applications for Database Technologies: Techniques and Issues treats the new, emerging discipline of soft computing, which exploits this data through tolerance for imprecision and uncertainty to achieve solutions for complex problems. Soft computing methodologies include fuzzy sets, neural networks, genetic algorithms, Bayesian belief networks and rough sets, which are explored in detail through case studies and in-depth research. The advent of soft computing marks a significant paradigm shift in computing, with a wide range of applications and techniques which are presented and discussed in the chapters of this book.

Most applications generate large datasets, like social networking and social influence programs, smart cities applications, smart house environments, Cloud applications, public web sites, scientific experiments and simulations, data warehouse, monitoring platforms, and e-government services. Data grows rapidly, since applications produce continuously increasing volumes of both unstructured and structured data. Large-scale interconnected systems aim to aggregate and efficiently exploit the power of widely distributed resources. In this context, major solutions for scalability, mobility, reliability, fault tolerance and security are required to achieve high performance and to create a smart environment. The impact on data processing, transfer and storage is the need to re-evaluate the approaches and solutions to better answer the user needs. A variety of solutions for specific applications and platforms exist so a thorough and systematic analysis of existing solutions for data science, data analytics, methods and algorithms used in Big Data processing and storage environments is significant in designing and implementing a smart environment. Fundamental issues pertaining to smart environments (smart cities, ambient assisted leaving, smart houses, green houses, cyber physical systems, etc.) are reviewed. Most of the current efforts still do not adequately address the heterogeneity of different distributed systems, the interoperability between them, and the systems resilience. This book will primarily encompass practical approaches that promote research in all aspects of data processing, data analytics, data processing in different type of systems: Cluster Computing, Grid Computing, Peer-to-Peer, Cloud/Edge/Fog Computing, all involving elements of heterogeneity, having a large variety of tools and software to manage them. The main role of resource management techniques in this domain is to create the suitable frameworks for development of applications and deployment in smart environments, with respect to high performance. The book focuses on topics covering algorithms, architectures, management models, high performance computing techniques and large-scale distributed systems.

The history of the computer, and of the industry it spawned, is the latest entrant into the field of historical studies. Scholars beginning to turn their attention to the subject of computing need James Cortada's "Archives of Data Procesing History" as a brief introduction to sources immediately available for investigation. Each essay provides an overview of a major government, academic, or industrial archival collection dealing with the history of computing, the industry, and its leaders and is written by the archivist/historian who has worked with or is responsible for the collection.

The archives give practical information on hours, organization, contacts, telephone numbers, survey of contents, and assessments of the historical significance of the collections and their institutions. Reference and business librarians will definitely want to add this volume to their collections. Those interested in the history of technology, the business history of the industry, and the history of major institutions will want to consult it.

The key competing texts are practitioner-focused 'how to' guides, whilst our book combines rigorous theory with practical insight and examples, with authors from both the academic and business world, making it more adoptable as a student text; Unlike other books on the subject, this has a customer focus and an exploration of how big data can add value to customers as well as organisations; Enables readers to move from "big data" to "big solutions" by demonstrating how to integrate data analytics into specific goals and processes for implementation; Highly successful and well regarded both for students and practitioners

Grid computing promises to transform the way organizations and individuals compute, communicate, and collaborate. Computational and Data Grids: Principles, Applications and Design offers critical perspectives on theoretical frameworks, methodologies, implementations, and cutting edge research in grid computing, bridging the gap between academia and the latest achievements of the computer industry. Useful for professionals and students involved or interested in the study, use, design, and development of grid computing, this book highlights both the basics of the field and in depth analyses of grid networks.

This book introduces the quantum mechanical framework to information retrieval scientists seeking a new perspective on foundational problems. As such, it concentrates on the main notions of the quantum mechanical framework and describes an innovative range of concepts and tools for modeling information representation and retrieval processes. The book is divided into four chapters. Chapter 1 illustrates the main modeling concepts for information retrieval (including Boolean logic, vector spaces, probabilistic models, and machine-learning based approaches), which will be examined further in subsequent chapters. Next, chapter 2 briefly explains the main concepts of the quantum mechanical framework, focusing on approaches linked to information retrieval such as interference, superposition and entanglement. Chapter 3 then reviews the research conducted at the intersection between information retrieval and the quantum mechanical framework. The chapter is subdivided into a number of topics, and each description ends with a section suggesting the most important reference resources. Lastly, chapter 4 offers suggestions for future research, briefly outlining the most essential and promising research directions to fully leverage the quantum mechanical framework for effective and efficient information retrieval systems. This book is especially intended for researchers working in information retrieval, database systems and machine learning who want to acquire a clear picture of the potential offered by the quantum mechanical framework in their own research area. Above all, the book offers clear guidance on whether, why and when to effectively use the mathematical formalism and the concepts of the quantum mechanical framework to address various foundational issues in information retrieval.

In recent years, cryptographic techniques for protecting and hiding secret information have been included in directions of research on intelligent information management. Data can be managed securely due to the use of algorithms for ensuring the confidentiality of data, information splitting techniques as well as protocols for sharing information and methods of its reconstruction. This is why techniques of advanced splitting and reconstruction of information form the primary subject of Secure Information Management Using Linguistic Threshold Approach, whose main purpose is to discuss the so-called linguistic threshold schemes for information sharing. An attempt is also made to describe the opportunities of using these techniques to create new models of managing strategic information shared within a commercial organisation or a state institution. Such information is specially protected, and its contents are used only if the authorised users are enabled to access it. This monograph attempts to define a model structure of information flow and for assigning information shares to particular groups of individuals concerned. The proposed information flow model can be integrated into practical solutions within any organisation or institution, improving the functionality of its legacy information systems. The use of strong mathematical cryptographic models to manage information constitutes a scientific innovation and a demonstration of the methods and opportunities of using advanced techniques for confidentially exchanging information in tasks supporting data flow within a commercial organisation. The interdisciplinary nature of the solutions proposed means that the subject of linguistic threshold schemes forming part of intelligent information management becomes a new challenge for the research and application work carried out. The authors of this monograph hope that it will guide readers on an interesting journey through the cutting edge solution in the field of secure information management.

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you will learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available in the framework of the data engineering lifecycle. Authors Joe Reis and Matt Housley walk you through the data engineering lifecycle and show you how to stitch together a variety of cloud technologies to serve the needs of downstream data consumers. You will understand how to apply the concepts of data generation, ingestion, orchestration, transformation, storage, governance, and deployment that are critical in any data environment regardless of the underlying technology. This book will help you: Assess data engineering problems using an end-to-end data framework of best practices Cut through marketing hype when choosing data technologies, architecture, and processes Use the data engineering lifecycle to design and build a robust architecture Incorporate data governance and security across the data engineering lifecycle

Statistical and machine learning methods have many applications in the environmental sciences, including prediction and data analysis in meteorology, hydrology and oceanography, pattern recognition for satellite images from remote sensing, management of agriculture and forests, assessment of climate change, and much more. With rapid advances in machine learning in the last decade, this book provides an urgently needed, comprehensive guide to machine learning and statistics for students and researchers interested in environmental data science. It includes intuitive explanations covering the relevant background mathematics, with examples drawn from the environmental sciences. A broad range of topics are covered, including correlation, regression, classification, clustering, neural networks, random forests, boosting, kernel methods, evolutionary algorithms, and deep learning, as well as the recent merging of machine learning and physics. End-of-chapter exercises allow readers to develop their problem-solving skills and online data sets allow readers to practise analysis of real data.

This book aims to help the reader better understand the importance of data analysis in project management. Moreover, it provides guidance by showing tools, methods, techniques and lessons learned on how to better utilize the data gathered from the projects. First and foremost, insight into the bridge between data analytics and project management aids practitioners looking for ways to maximize the practical value of data procured. The book equips organizations with the know-how necessary to adapt to a changing workplace dynamic through key lessons learned from past ventures. The book's integrated approach to investigating both fields enhances the value of research findings.

First book to examine game analysis, modern didactic reflections on learning, and big data in a key topic in science and society today. Provides understanding on how to use game analysis when applied to different sports and how to use the approach for video, event and positional data. Presents translational work that has implications for academics, programmers and applied practitioners.

A timely survey of the field from the point of view of some of the subject's most active researchers. Divided into several parts organized by theme, the book first covers the underlying methodology regarding active rules, followed by formal specification, rule analysis, performance analysis, and support tools. It then moves on to the implementation of active rules in a number of commercial systems, before concluding with applications and future directions for research. All researchers in databases will find this a valuable overview of the topic.

Advanced Signature Indexing for Multimedia and Web Applications presents the latest research developments in signature-based indexing and query processing, specifically in multimedia and Web domains. These domains now demand a different designation of hashing information in bit-strings (i.e., signatures), and new indexes and query processing methods. The book provides solutions to these issues and addresses the resulting requirements, which are not adequately handled by existing approaches. Examples of these applications include: searching for similar images, representing multi-theme layers in maps, recommending products to Web-clients, and indexing large Web-log files. Special emphasis is given to structure description, implementation techniques and clear evaluation of operations performed (from a performance perspective).

Advanced Signature Indexing for Multimedia and Web Applications is an excellent reference for professionals involved in the development of applications in multimedia databases or the Web and may also serve as a textbook for advanced level courses in database and information retrieval systems.

Requiring heterogeneous information systems to cooperate and communicate has now become crucial, especially in application areas like e-business, Web-based mash-ups and the life sciences. Such cooperating systems have to automatically and efficiently match, exchange, transform and integrate large data sets from different sources and of different structure in order to enable seamless data exchange and transformation.

The book edited by Bellahsene, Bonifati and Rahm provides an overview of the ways in which the schema and ontology matching and mapping tools have addressed the above requirements and points to the open technical challenges. The contributions from leading experts are structured into three parts: large-scale and knowledge-driven schema matching, quality-driven schema mapping and evolution, and evaluation and tuning of matching tasks. The authors describe the state of the art by discussing the latest achievements such as more effective methods for matching data, mapping transformation verification, adaptation to the context and size of the matching and mapping tasks, mapping-driven schema evolution and merging, and mapping evaluation and tuning. The overall result is a coherent, comprehensive picture of the field.

With this book, the editors introduce graduate students and advanced professionals to this exciting field. For researchers, they provide an up-to-date source of reference about schema and ontology matching, schema and ontology evolution, and schema merging.

Time is ubiquitous in information systems. Almost every enterprise faces the problem of its data becoming out of date. However, such data is often valu able, so it should be archived and some means to access it should be provided. Also, some data may be inherently historical, e.g., medical, cadastral, or ju dicial records. Temporal databases provide a uniform and systematic way of dealing with historical data. Many languages have been proposed for tem poral databases, among others temporal logic. Temporal logic combines ab stract, formal semantics with the amenability to efficient implementation. This chapter shows how temporal logic can be used in temporal database applica tions. Rather than presenting new results, we report on recent developments and survey the field in a systematic way using a unified formal framework [GHR94; Ch094]. The handbook [GHR94] is a comprehensive reference on mathematical foundations of temporal logic. In this chapter we study how temporal logic is used as a query and integrity constraint language. Consequently, model-theoretic notions, particularly for mula satisfaction, are of primary interest. Axiomatic systems and proof meth ods for temporal logic [GHR94] have found so far relatively few applications in the context of information systems. Moreover, one needs to bear in mind that for the standard linearly-ordered time domains temporal logic is not re cursively axiomatizable [GHR94]' so recursive axiomatizations are by necessity incomplete.

CHARM '97 is the ninth in a series of working conferences devoted to the development and use of formal techniques in digital hardware design and verification. This series is held in collaboration with IFIP WG 10.5. Previous meetings were held in Europe every other year.

The subject of error-control coding bridges several disciplines, in particular mathematics, electrical engineering and computer science. The theory of error-control codes is often described abstractly in mathematical terms only, for the benefit of other coding specialists. Such a theoretical approach to coding makes it difficult for engineers to understand the underlying concepts of error correction, the design of digital error-control systems, and the quantitative behavior of such systems. In this book only a minimal amount of mathematics is introduced in order to describe the many, sometimes mathematical, aspects of error-control coding. The concepts of error correction and detection are in many cases sufficiently straightforward to avoid highly theoretical algebraic constructions. The reader will find that the primary emphasis of the book is on practical matters, not on theoretical problems. In fact, much of the material covered is summarized by examples of real developments, and almost all of the error-correction and detection codes introduced are attached to related practical applications. Error-Control Coding for Data Networks takes a structured approach to channel-coding, starting with the basic coding concepts and working gradually towards the most sophisticated coding systems. The most popular applications are described throughout the book. These applications include the channel-coding techniques used in mobile communication systems, such as: the global system for mobile communications (GSM) and the code-division multiple-access (CDMA) system, coding schemes for High-Definition TeleVision (HDTV) system, the Compact Disk (CD), and Digital Video Disk (DVD), as well as theerror-control protocols for the data-link layers of networks, and much more. The book is compiled carefully to bring engineers, coding specialists, and students up to date in the important modern coding technologies. Both electrical engineering students and communication engineers will benefit from the information in this largely self-contained text on error-control system engineering.