But it is also much more than that: in talk and writing, in music and images, in film and television, genres actively generate and shape our knowledge of the world. Understanding genre as a dynamic process rather than a set of stable rules, this book explores:*the relation of simple to complex genres*the history of literary genre in theory*the generic organisation of implied meanings*the structuring of interpretation by genre*the uses of genre in teaching.John Frow’s lucid exploration of this fascinating concept will be essential reading for students of literary and cultural studies.

    Integrated central case studies woven throughout each chapter, use real-life stories to give you a tangible and engaging framework around which to learn and understand the science behind environmental issues. Printed on FSC (Forest Stewardship Council) certified paper, the newly revised Fourth Edition engages you through the addition of new EnvisionIt photo essays.

    Drawing upon new research in psychology, education, and cognitive science, the authors have demystified a complex topic into clear explanations of seven powerful learning principles. Full of great ideas and practical suggestions, all based on solid research evidence, this book is essential reading for instructors at all levels who wish to improve their students' learning." --Barbara Gross Davis, assistant vice chancellor for educational development, University of California, Berkeley, and author, Tools for Teaching"This book is a must-read for every instructor, new or experienced. Although I have been teaching for almost thirty years, as I read this book I found myself resonating with many of its ideas, and I discovered new ways of thinking about teaching." --Eugenia T. Paulus, professor of chemistry, North Hennepin Community College, and 2008 U.S. Community Colleges Professor of the Year from The Carnegie Foundation for the Advancement of Teaching and the Council for Advancement and Support of Education"Thank you Carnegie Mellon for making accessible what has previously been inaccessible to those of us who are not learning scientists. Your focus on the essence of learning combined with concrete examples of the daily challenges of teaching and clear tactical strategies for faculty to consider is a welcome work. I will recommend this book to all my colleagues." --Catherine M. Casserly, senior partner, The Carnegie Foundation for the Advancement of Teaching"As you read about each of the seven basic learning principles in this book, you will find advice that is grounded in learning theory, based on research evidence, relevant to college teaching, and easy to understand. The authors have extensive knowledge and experience in applying the science of learning to college teaching, and they graciously share it with you in this organized and readable book." --From the Foreword by Richard E. Mayer, professor of psychology, University of California, Santa Barbara; coauthor, e-Learning and the Science of Instruction; and author, Multimedia Learning

    The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and output, general statistics, graphics, and linear regression.Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you're a beginner, R Cookbook will help get you started. If you're an experienced data programmer, it will jog your memory and expand your horizons. You'll get the job done faster and learn more about R in the process.Create vectors, handle variables, and perform other basic functionsInput and output dataTackle data structures such as matrices, lists, factors, and data framesWork with probability, probability distributions, and random variablesCalculate statistics and confidence intervals, and perform statistical testsCreate a variety of graphic displaysBuild statistical models with linear regressions and analysis of variance (ANOVA)Explore advanced statistical techniques, such as finding clusters in your dataWonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language--one practical example at a time.--Jeffrey Ryan, software consultant and R package author

    His analysis explains not only the deficiencies of the self-regulating market, but the potentially dire social consequences of untempered market capitalism. New introductory material reveals the renewed importance of Polanyi's seminal analysis in an era of globalization and free trade.

    Offers students with the tools necessary to do ethical research in psychology and to understand the research they learn about in psychology courses and in the media.

    Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, recognize faces or spoken speech, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. "Introduction to Machine Learning" is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. It discusses many methods based in different fields, including statistics, pattern recognition, neural networks, artificial intelligence, signal processing, control, and data mining, in order to present a unified treatment of machine learning problems and solutions. All learning algorithms are explained so that the student can easily move from the equations in the book to a computer program. The book can be used by advanced undergraduates and graduate students who have completed courses in computer programming, probability, calculus, and linear algebra. It will also be of interest to engineers in the field who are concerned with the application of machine learning methods.After an introduction that defines machine learning and gives examples of machine learning applications, the book covers supervised learning, Bayesian decision theory, parametric methods, multivariate methods, dimensionality reduction, clustering, nonparametric methods, decision trees, linear discrimination, multilayer perceptrons, local models, hidden Markov models, assessing and comparing classification algorithms, combining multiple learners, and reinforcement learning.

    The result is a completely accessible introduction to the main themes of the philosophy of science. Intended for undergraduates and general readers with no prior background in philosophy, Theory and Reality covers logical positivism; the problems of induction and confirmation; Karl Popper's theory of science; Thomas Kuhn and "scientific revolutions"; the views of Imre Lakatos, Larry Laudan, and Paul Feyerabend; and challenges to the field from sociology of science, feminism, and science studies. The book then looks in more detail at some specific problems and theories, including scientific realism, the theory-ladeness of observation, scientific explanation, and Bayesianism. Finally, Godfrey-Smith defends a form of philosophical naturalism as the best way to solve the main problems in the field. Throughout the text he points out connections between philosophical debates and wider discussions about science in recent decades, such as the infamous "science wars." Examples and asides engage the beginning student; a glossary of terms explains key concepts; and suggestions for further reading are included at the end of each chapter. However, this is a textbook that doesn't feel like a textbook because it captures the historical drama of changes in how science has been conceived over the last one hundred years.Like no other text in this field, Theory and Reality combines a survey of recent history of the philosophy of science with current key debates in language that any beginning scholar or critical reader can follow.

    Peterson comes a creative guide to language construction for sci-fi and fantasy fans, writers, game creators, and language lovers. Peterson offers a captivating overview of language creation, covering its history from Tolkien’s creations and Klingon to today’s thriving global community of conlangers. He provides the essential tools necessary for inventing and evolving new languages, using examples from a variety of languages including his own creations, punctuated with references to everything from Star Wars to Michael Jackson. Along the way, behind-the-scenes stories lift the curtain on how he built languages like Dothraki for HBO’s Game of Thrones and Shiväisith for Marvel’s Thor: The Dark World, and an included phrasebook will start fans speaking Peterson’s constructed languages. The Art of Language Invention is an inside look at a fascinating culture and an engaging entry into a flourishing art form—and it might be the most fun you’ll ever have with linguistics.

    Illustrations and examples throughout show you how you can apply research to practice. Studying is made easy with a book-specific website that provides you with tutorial quizzes and links to additional related concepts. Outlines, introductions, boxes, chapter endings with main points, review questions and exercises, and internet exercises provide you with the information and practice you need to succeed in this course.

     Coauthored by the designer of the Scala language, this authoritative book will teach you, one step at a time, the Scala language and the ideas behind it. The book is carefully crafted to help you learn. The first few chapters will give you enough of the basics that you can already start using Scala for simple tasks. The entire book is organized so that each new concept builds on concepts that came before - a series of steps that promises to help you master the Scala language and the important ideas about programming that Scala embodies. A comprehensive tutorial and reference for Scala, this book covers the entire language and important libraries.

    Enhancements to this edition include a more thorough coverage of transport processes, plus new or expanded coverage of separation process applications, fluidized beds, non-Newtonian fluids, membrane separation processes and gas-membrane theory, and much more. The book contains 240+ example problems and 550+ homework problems.

    The guide includes information on aspects of the search that are common to all levels, with invaluable tips for those seeking their first or second faculty position. This new edition provides updated advice and addresses hot topics in the competitive job market of today, including the challenges faced by dual-career couples, job search issues for pregnant candidates, and advice on how to deal with gaps in a CV. The chapter on alternatives to academic jobs has been expanded, and sample resumes from individuals seeking nonfaculty positions are included.The book begins with an overview of the hiring process and a timetable for applying for academic positions. It then gives detailed information on application materials, interviewing, negotiating job offers, and starting the new job. Guidance throughout is aimed at all candidates, with frequent reference to the specifics of job searches in scientific and technical fields as well as those in the humanities and social sciences. Advice on seeking postdoctoral opportunities is also included.Perhaps the most significant contribution is the inclusion of sample vitas. "The Academic Job Search Handbook" describes the organization and content of the vita and includes samples from a variety of fields. In addition to CVs and research statements, new in this edition are a sample interview itinerary, a teaching portfolio, and a sample offer letter. The job search correspondence section has also been updated, and there is current information on Internet search methods and useful websites.

    Authors Juliet Corbin and the late Anselm Strauss (co-creator of Grounded Theory) present methods that enable researchers to analyze and interpret their data, and ultimately build theory from it. Highly accessible in their approach, Corbin and Strauss provide a step-by-step guide to the research act--from the formation of the research question through several approaches to coding and analysis, to reporting on the research. Full of definitions and illustrative examples, this book concludes with chapters that present criteria for evaluating a study, as well as responses to common questions posed by students of qualitative research. Significantly revised, Basics of Qualitative Research remains a landmark volume in the study of qualitative methods. Key Features of the Third Edition:Allows for students to develop their critical thinking skills in the "Critical Issues" section at the end of each chapter.Shows the actual steps involved in data analysis (from description to grounded theory) and data gathering by means of theoretical sampling.Provides exercises for thinking, writing and group discussion that reinforces material presented in the text.

    Based on B. P. Lathi's widely used book, Linear Systems and Signals, it features additional applications to communications, controls, and filtering as well as new chapters on analog and digital filters and digital signal processing. Lathi emphasizes the physical appreciation of concepts rather than the mere mathematical manipulation of symbols. Avoiding the tendency to treat engineering as a branch of applied mathematics, he uses mathematics to enhance physical and intuitive understanding of concepts, instead of employing it only to prove axiomatic theory. Theoretical results are supported by carefully chosen examples and analogies, allowing students to intuitively discover meaning for themselves.