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Designed as a handbook, this text provides media, speech (public speaking, interpersonal, small group, and organizational communication), and theatre educators with both the theoretical and practical ammunition to fight the assessment battles on their campuses. The philosophical implications of accountability are balanced with concrete, specific, and usable assessment strategies. Stressing student, faculty, course, program, department, and institutional assessment, this book's aim is to provide, in one place, information that will help diverse and complex communication programs face the growing challenges in assessment. The book is divided into three sections: background and foundational information for assessment; broad assessment strategies that apply to a variety of media, "speech," and theatre courses and programs; and context-specific assessment strategies. While covering a host of topics, it: * provides an overview of assessment and suggests how it might impact communication education, * discusses the elements of program assessment and how linkage of mission statements with outcomes can lead to strong, innovative programs, * compares and contrasts regional association requirements and presents a specific how-to strategy for writing outcome statements, * discusses teaching evaluation and argues that we need to identify the "what" of teaching before we try to measure the "how," * looks at creative ways for formative and summative course evaluation that starts with the creation of an explicit syllabus, * discusses the use of capstone courses as a way of evaluating not only their major but also how students have integrated their "total" educational experience, * suggests the variety of ways that interpersonal communication can be assessed and calls for future research that stresses the "knowledge" component of learning, * reports on a strategy for developing small group communication assessment measures, and * provides media, speech, and theatre faculty and administrators with the background, understanding and tools to build stonger programs and develop better courses and educational experiences for their students.
With continuous improvement (kaizen) and Total Quality Control (TQC) becoming increasingly important to world class companies, there's an urgent need to build quality into every management decision. The tools presented in this book allow you to do just that. They represent the most important advance in quality deployment and project management in recent years. Unlike the seven traditional QC tools, which measure quality problems that already exist and are used by quality circles, these seven new QC tools make it possible for managers to plan wide-ranging and detailed TQC objectives throughout the entire organization. These tools, some borrowed from other disciplines and others developed specifically for quality management, include the relations diagram, the KJ method (affinity diagram), the systematic diagram, the matrix diagram, matrix data analysis, the process decision program chart (PDPC), and the arrow diagram. Together they will help you to: Expand the scope of quality efforts company-wide. Set up and manage the systems necessary to resolve major quality problems. Anticipate potential quality problems and actually eliminate defects before they happen. Never before available in English, Management for Quality Improvement is absolutely essential reading if you are in any area of project management, quality assurance, MIS, or TQC.
Modern Petrochemical Technology A text that explores the essence of petrochemicals and petrochemical technology Modern Petrochemical Technology: Methods, Manufacturing and Applications is a comprehensive resource that provides an overview of the uses for common petrochemical building blocks, a review of the marketplaces, and offers a survey of the technology used to make the key petrochemical building blocks. The book contains both critical information the technologies used to produce petrochemicals, how the various petrochemicals are applied in industry, and provides illustrative examples and problems designed to reinforce the learning about the basic science, engineering, and use of petrochemicals. The book explores three seprate petrochemical building block—olefin complexes, aromatic complexes and synthesis gas complexes—and examines the “interconnected” nature of these building blocks. The authors also include information on the olefins productions using steam cracking, paraffin dehydrogenation, and methanol to olefins technologies and describes various methods, commercial processes to produce aromatics such as benzene, toluene and xylene, and much more. This important book: Offers a guide to the critical information on petrochemical producing technologies Includes material on various petrochemicals from the industrial point-of-view Explores the separation processes, membrane technology, absorption technology, liquid-liquid extraction, and more Contains material from a team of noted experts Provides a survey of examples of commercialization applications of petrochemicals Written for chemical engineers, chemists in industry, membrane scientists, and process engineers, Modern Petrochemical Technology provides an overview of markets and uses for common petrochemical building blocks as well as includes a survey of the technology used to make the key petrochemical building blocks.
This monograph proposes a comprehensive and fully automatic approach to designing text analysis pipelines for arbitrary information needs that are optimal in terms of run-time efficiency and that robustly mine relevant information from text of any kind. Based on state-of-the-art techniques from machine learning and other areas of artificial intelligence, novel pipeline construction and execution algorithms are developed and implemented in prototypical software. Formal analyses of the algorithms and extensive empirical experiments underline that the proposed approach represents an essential step towards the ad-hoc use of text mining in web search and big data analytics. Both web search and big data analytics aim to fulfill peoples’ needs for information in an adhoc manner. The information sought for is often hidden in large amounts of natural language text. Instead of simply returning links to potentially relevant texts, leading search and analytics engines have started to directly mine relevant information from the texts. To this end, they execute text analysis pipelines that may consist of several complex information-extraction and text-classification stages. Due to practical requirements of efficiency and robustness, however, the use of text mining has so far been limited to anticipated information needs that can be fulfilled with rather simple, manually constructed pipelines.
The book describes the most important quality management tools (e.g. QFD, Kano model), methods (e.g. FMEA, Six Sig-ma) and standards (e.g. IS0 9001, ISO 14001, ISO 27001, ISO 45001, SA8000). It reflects recent developments in the field. It is considered a must-read for students, academics, and practitioners.
Neuro-symbolic AI is an emerging subfield of Artificial Intelligence that brings together two hitherto distinct approaches. ”Neuro” refers to the artificial neural networks prominent in machine learning, ”symbolic” refers to algorithmic processing on the level of meaningful symbols, prominent in knowledge representation. In the past, these two fields of AI have been largely separate, with very little crossover, but the so-called “third wave” of AI is now bringing them together. This book, Neuro-Symbolic Artificial Intelligence: The State of the Art, provides an overview of this development in AI. The two approaches differ significantly in terms of their strengths and weaknesses and, from a cognitive-science perspective, there is a question as to how a neural system can perform symbol manipulation, and how the representational differences between these two approaches can be bridged. The book presents 17 overview papers, all by authors who have made significant contributions in the past few years and starting with a historic overview first seen in 2016. With just seven months elapsed from invitation to authors to final copy, the book is as up-to-date as a published overview of this subject can be. Based on the editors’ own desire to understand the current state of the art, this book reflects the breadth and depth of the latest developments in neuro-symbolic AI, and will be of interest to students, researchers, and all those working in the field of Artificial Intelligence.