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Features are a central concept in linguistic analysis. They are the basic building blocks of linguistic units, such as words. For many linguists they offer the most revealing way to explore the nature of language. Familiar features are Number (singular, plural, dual, ...), Person (1st, 2nd, 3rd) and Tense (present, past, ...). Features have a major role in contemporary linguistics, from the most abstract theorizing to the most applied computational applications, yet little is firmly established about their status. They are used, but are little discussed and poorly understood. In this unique work, Corbett brings together two lines of research: how features vary between languages and how they work. As a result, the book is of great value to the broad range of perspectives of those who are interested in language.
The book is the complete introduction and applications guide to this new technology. This book introduces the reader to features and gives an overview of geometric modeling techniques, discusses the conceptual development of features as modeling entities, illustrates the use of features for a variety of engineering design applications, and develops a set of broad functional requirements and addresses high level design issues.
"Introduction to landforms and bodies of water using simple text, illustrations, and photos. Features include puzzles and games, fun facts, a resource list, and an index"--Provided by publisher.
Examines unusual animal facial features and how they help the animals survive.
Nicky Haslam has always been at the centre of things wherever he is - at parties, opening nights, royal weddings - and has stories to tell of crossing paths, and more, with the cultural icons of our time: Cecil Beaton, Francis Bacon, Diana Cooper, Lucian Freud, David Hockney, Andy Warhol, Jack Kennedy and Marilyn Monroe to name but a few. Redeeming Features is an exuberantly told and stunningly crafted memoir: a compelling and wholly singular document of our times.
A proposal that person features do not have inherent content but are used to navigate a “person space” at the heart of every pronominal expression. This book offers a significant reconceptualization of the person system in natural language. The authors, leading scholars in syntax and its interfaces, propose that person features do not have inherent content but are used to navigate a “person space” at the heart of every pronominal expression. They map the journey of person features in grammar, from semantics through syntax to the system of morphological realization. Such an in-depth cross-modular study allows the development of a theory in which assumptions made about the behavior of a given feature in one module bear on possible assumptions about its behavior in other modules. The authors' new theory of person, built on a sparse set of two privative person features, delivers a typologically adequate inventory of persons; captures the semantics of personal pronouns, impersonal pronouns, and R-expressions; accounts for aspects of their syntactic behavior; and explains patterns of person-related syncretism in the realization of pronouns and inflectional endings. The authors discuss numerous observations from the literature, defend a number of theoretical choices that are either new or not generally accepted, and present novel empirical findings regarding phenomena as different as honorifics, number marking, and unagreement.
Wh-movement and the theory of feature-checking argues that cross-linguistic variation in wh-constructions reduces to the availability of different lexical instantiations of a +wh C0 both across languages and within a single language, and the way in which such lexical elements are syntactically identified, either via movement or base-generation. Evidence from a wide range of patterns including wh-expletive questions leads to the conclusion that wh-feature checking may sometimes be effected non-locally and 'at a distance' (long-distance wh-agreement), and that movement in general takes place for two related but discrete reasons: both to identify and activate an underspecified licensing head and in order for an element to occur in the checking domain projected by its relevant licensing head. Developing and generalizing the proposals beyond wh-phenomena, the study also goes on to argue for a Minimalist model of syntax in which feature-dependencies are in fact all licensed in the overt syntax and where there is no need for any further level of LF.
Well known researchers in all areas related to featured based manufacturing have contributed chapters to this book. Some of the chapters are surveys, while others review a specific technique. All contributions, including those from the editors, were thoroughly refereed. The goal of the book is to provide a comprehensive picture of the present stage of development of Features Technology from the point of view of applications in manufacturing. The book is aimed at several audiences. Firstly, it provides the research community with an overview of the present state-of-the-art features in manufacturing, along with references in the literature. Secondly, the book will be useful as supporting material for a graduate-level course on product modeling and realization. Finally, the book will also be valuable to industrial companies who are assessing the significance of features for their business.
This book offers a comprehensive overview of ensemble learning in the field of feature selection (FS), which consists of combining the output of multiple methods to obtain better results than any single method. It reviews various techniques for combining partial results, measuring diversity and evaluating ensemble performance. With the advent of Big Data, feature selection (FS) has become more necessary than ever to achieve dimensionality reduction. With so many methods available, it is difficult to choose the most appropriate one for a given setting, thus making the ensemble paradigm an interesting alternative. The authors first focus on the foundations of ensemble learning and classical approaches, before diving into the specific aspects of ensembles for FS, such as combining partial results, measuring diversity and evaluating ensemble performance. Lastly, the book shows examples of successful applications of ensembles for FS and introduces the new challenges that researchers now face. As such, the book offers a valuable guide for all practitioners, researchers and graduate students in the areas of machine learning and data mining.