This book provides a comprehensive overview on the theories, processes, and solutions relevant to effectively creating, using, and managing digital media in a variety of instructional settings. In the first section of the book, the authors provide an overview of the theories, development models, and principles of learning with digital media. In the second section, the authors detail various digital media solutions, including: Instructional Videos, Instructional Simulations and Games, Online Learning, Mobile Learning, and Emerging Learning Technologies. Overall, this book emphasizes the theoretical principles for learning with digital media and processes to design digital media solutions in various instructional settings. The readers are also provided with multiple case studies from real world projects in various instructional settings.

The institutions of the European Union employ hundreds of translators. Why? What do they do? What sort of translation problems do they have to tackle? Has the language policy of the European Union been affected by the recent inclusion of new Member States? This book answers all those questions. Written by three experienced translators from the European Commission, it aims to help general readers, translation students and freelance translators to understand the European Union institutions and their work. Although it deals with written rather than spoken translation, much of the information it gives will be of interest to interpreters too. This second edition has been updated to reflect the new composition of the EU and changes to recruitment procedures.

The institutions of the European Union employ hundreds of translators. Why? What do they do? What sort of translation problems do they have to tackle? Has the language policy of the European Union been affected by the recent inclusion of new Member States? This book answers all those questions. Written by three experienced translators from the European Commission, it aims to help general readers, translation students and freelance translators to understand the European Union institutions and their work. Although it deals with written rather than spoken translation, much of the information it gives will be of interest to interpreters too. This second edition has been updated to reflect the new composition of the EU and changes to recruitment procedures.

Battle is a practical and sometimes lasting way of solving man's problems. It relies on the strength of the combatants and ignores the truth of the dispute. Discussion face to face can dissolve attitudes which have incorrectly determined judgements. The most striking example of this that I know is a Battle in Ireland in the eleventh century, where the king of Leinster fought a Viking prince. The Icelanders had raided Ireland for several generations in search of women, which they lacked since most of the population of Iceland were men who had arrived there by rowing long-boats from Norway. The prince was leading such a raid for the first time. Standing in the prow of the leading boat he saw Irish cavalry galloping along the beach to meet them. As they approached the shore the Irish king rode out of the band to challenge single combat. The Icelander jumped into the surf to meet him. As they raised their swords each realized that the other's face was like his own. When the Irish king spoke the other recognized the language. It had been spoken in Iceland by his grandmother who had been captured and taken there from Ireland. Swords were dropped and replaced by drinking horns. It was soon established that they were cousins. The battle gave way to a life-time of close co-operation.

This important work describes recent theoretical advances in the study of artificial neural networks. It explores probabilistic models of supervised learning problems, and addresses the key statistical and computational questions. Chapters survey research on pattern classification with binary-output networks, including a discussion of the relevance of the Vapnik Chervonenkis dimension, and of estimates of the dimension for several neural network models. In addition, Anthony and Bartlett develop a model of classification by real-output networks, and demonstrate the usefulness of classification with a "large margin." The authors explain the role of scale-sensitive versions of the Vapnik Chervonenkis dimension in large margin classification, and in real prediction. Key chapters also discuss the computational complexity of neural network learning, describing a variety of hardness results, and outlining two efficient, constructive learning algorithms. The book is self-contained and accessible to researchers and graduate students in computer science, engineering, and mathematics.

This book examines case studies of North American Quaternary mammalian evolution within the larger domain of modern evolutionary theory. It presents previously unpublished studies of a variety of taxa (xenarthrans, rodents, carnivores, ungulates) examined over several temporal scales, from a few thousand years during the Holocene to millions of years of late Pliocene and Pleistocene time. Different organizational levels are represented, from mosaic population variation, to a synopsis of Quaternary evolution of an entire order (Rodentia). In addition to specific case histories, the book includes purely theoretical and methodological contributions, for example, on the statistical recognition of stasis in the fossil record, new ways to calculate evolutionary rates, and the use of digital image analysis in the study of dental ontogeny. Perhaps the most important aspect of the studies reported in this book is that they span the time between the "ecological moment" and "deep time." Modern taxa can be traced back into the fossil record, and variation among extant taxa can be used as a control against which variation in the extinct ones can be understood.

This book provides a comprehensive overview on the theories, processes, and solutions relevant to effectively creating, using, and managing digital media in a variety of instructional settings. In the first section of the book, the authors provide an overview of the theories, development models, and principles of learning with digital media. In the second section, the authors detail various digital media solutions, including: Instructional Videos, Instructional Simulations and Games, Online Learning, Mobile Learning, and Emerging Learning Technologies. Overall, this book emphasizes the theoretical principles for learning with digital media and processes to design digital media solutions in various instructional settings. The readers are also provided with multiple case studies from real world projects in various instructional settings.

This book examines case studies of North American Quaternary mammalian evolution within the larger domain of modern evolutionary theory. It presents previously unpublished studies of a variety of taxa (xenarthrans, rodents, carnivores, ungulates) examined over several temporal scales, from a few thousand years during the Holocene to millions of years of late Pliocene and Pleistocene time. Different organizational levels are represented, from mosaic population variation, to a synopsis of Quaternary evolution of an entire order (Rodentia). In addition to specific case histories, the book includes purely theoretical and methodological contributions, for example, on the statistical recognition of stasis in the fossil record, new ways to calculate evolutionary rates, and the use of digital image analysis in the study of dental ontogeny. Perhaps the most important aspect of the studies reported in this book is that they span the time between the "ecological moment" and "deep time." Modern taxa can be traced back into the fossil record, and variation among extant taxa can be used as a control against which variation in the extinct ones can be understood.

This important work describes recent theoretical advances in the study of artificial neural networks. It explores probabilistic models of supervised learning problems, and addresses the key statistical and computational questions. Chapters survey research on pattern classification with binary-output networks, including a discussion of the relevance of the Vapnik Chervonenkis dimension, and of estimates of the dimension for several neural network models. In addition, Anthony and Bartlett develop a model of classification by real-output networks, and demonstrate the usefulness of classification with a "large margin." The authors explain the role of scale-sensitive versions of the Vapnik Chervonenkis dimension in large margin classification, and in real prediction. Key chapters also discuss the computational complexity of neural network learning, describing a variety of hardness results, and outlining two efficient, constructive learning algorithms. The book is self-contained and accessible to researchers and graduate students in computer science, engineering, and mathematics.

Any student of linear algebra will welcome this textbook, which provides a thorough treatment of this key topic. Blending practice and theory, the book enables the reader to learn and comprehend the standard methods, with an emphasis on understanding how they actually work. At every stage, the authors are careful to ensure that the discussion is no more complicated or abstract than it needs to be, and focuses on the fundamental topics. The book is ideal as a course text or for self-study. Instructors can draw on the many examples and exercises to supplement their own assignments. End-of-chapter sections summarize the material to help students consolidate their learning as they progress through the book.

This monograph revolves around Daria Martin's new film "Sensorium Tests" (2011), which uses the recently diagnosed condition of mirror-touch synesthesia to explore how sensations are transmitted, shared and created in film--raising the question, can a spectator experience a bodily reaction to film? The publication includes related texts selected by Martin, by writers and thinkers from Mary Shelley to Maurice Merleau-Ponty.

Learn how to combine SQL Server's analytics with Azure's flexibility and hybrid connectivity to achieve industry-leading performance and manageability for your cloud database. Key Features Understand platform availability for SQL Server in Azure Explore the benefits and deployment choices offered by SQL IaaS Get to grips with deploying SQL Server on the Linux development ecosystem Book DescriptionDeploying SQL Server on Azure virtual machines allows you to work on full versions of SQL Server in the cloud without having to maintain on-premises hardware. The book begins by introducing you to the SQL portfolio in Azure and takes you through SQL Server IaaS scenarios, before explaining the factors that you need to consider while choosing an OS for SQL Server in Azure VMs. As you progress through the book, you'll explore different VM options and deployment choices for IaaS and understand platform availability, migration tools, and best practices in Azure. In later chapters, you'll learn how to configure storage to achieve optimized performance. Finally, you'll get to grips with the concept of Azure Hybrid Benefit and find out how you can use it to maximize the value of your existing on-premises SQL Server. By the end of this book, you'll be proficient in administering SQL Server on Microsoft Azure and leveraging the tools required for its deployment. What you will learn Choose an operating system for SQL Server in Azure VMs Use the Azure Management Portal to facilitate the deployment process Verify connectivity and network latency in cloud Configure storage for optimal performance and connectivity Explore various disaster recovery options for SQL Server in Azure Optimize SQL Server on Linux Discover how to back up databases to a URL Who this book is forSQL Server on Azure VMs is for you if you are a developer, data enthusiast, or anyone who wants to migrate SQL Server databases to Azure virtual machines. Basic familiarity with SQL Server and managed identities for Azure resources will be a plus.

Without expecting any particular background of the reader, this book covers graphs and relations, sequences and limits, partial derivatives, optimization, vectors, and matrix algebra. Throughout, the stress is firmly on how the mathematics relates to economics, and this is illustrated with copious examples and exercises that will foster depth of understanding.

This concise, readable book provides a sampling of the very large, active, and expanding field of artificial neural network theory. It considers select areas of discrete mathematics linking combinatorics and the theory of the simplest types of artificial neural networks. Neural networks have emerged as a key technology in many fields of application, and an understanding of the theories concerning what such systems can and cannot do is essential. The author discusses interesting connections between special types of Boolean functions and the simplest types of neural networks. Some classical results are presented with accessible proofs, together with some more recent perspectives, such as those obtained by considering decision lists. In addition, probabilistic models of neural network learning are discussed. Graph theory, some partially ordered set theory, computational complexity, and discrete probability are among the mathematical topics involved. Pointers to further reading and an extensive bibliography make this book a good starting point for research in discrete mathematics and neural networks.