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When poet and essayist Kenneth Sherman was diagnosed with cancer, he began keeping a notebook of observations that blossomed into this powerful memoir. With incisive and evocative language, Sherman presents a clear-eyed view of what the cancer patient feels and thinks. His narrative voice is personal but not confessional, practical but not cold, thoughtful and searching but not self-pitying or self-absorbed. The author’s wait time for surgery on a malignant tumour was exceptionally long and riddled with bureaucratic bumbling; thus he asks our health-care providers and administrators if our system cannot be made efficient and more humane. While he is honest about what is good and bad in our system, he is not stridently political or given to directing blame. His narrative is interwoven with engaging ruminations on the meaning of illness in society, and is peppered with references to other writers’ thoughts on the subject. A widely published poet, Sherman helps the reader understand the deep connection between disease and creativity—the ways in which we write out of our suffering. Wait Time will be of special interest to anyone facing a serious illness as well as to health-care providers, social workers, and psychologists working in the field. Its thoughtful observations on health, life priorities, time, and mortality will make it of interest to all readers.
The report reviews a range of policies that countries have used to tackle waiting times for different services, including elective surgery and primary care consultations, but also cancer care and mental health services, with a focus on identifying the most successful ones.
This book constitutes the thoroughly refereed post-workshop proceedings of the 5th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP'99, held in San Juan, Puerto Rico, in April 1999, as a satelite meeting of IPPS/SPDP'99. The 12 revised full papers have been through an iterated reviewing process and present the state of the art in the area.
Describes nine different teaching strategies which have been proven to have positive effects on student learning and explains how those strategies can be incorporated into the classroom.
A new edition of a bestselling industrial and systems engineering reference, Handbook of Industrial and Systems Engineering, Second Edition provides students, researchers, and practitioners with easy access to a wide range of industrial engineering tools and techniques in a concise format. This edition expands the breadth and depth of coverage, emphasizing new systems engineering tools, techniques, and models. See What’s New in the Second Edition: Section covering safety, reliability, and quality Section on operations research, queuing, logistics, and scheduling Expanded appendix to include conversion factors and engineering, systems, and statistical formulae Topics such as control charts, engineering economy, health operational efficiency, healthcare systems, human systems integration, Lean systems, logistics transportation, manufacturing systems, material handling systems, process view of work, and Six Sigma techniques The premise of the handbook remains: to expand the breadth and depth of coverage beyond the traditional handbooks on industrial engineering. The book begins with a general introduction with specific reference to the origin of industrial engineering and the ties to the Industrial Revolution. It covers the fundamentals of industrial engineering and the fundamentals of systems engineering. Building on this foundation, it presents chapters on manufacturing, production systems, and ergonomics, then goes on to discuss economic and financial analysis, management, information engineering, and decision making. Two new sections examine safety, reliability, quality, operations research, queuing, logistics, and scheduling. The book provides an updated collation of the body of knowledge of industrial and systems engineering. The handbook has been substantively expanded from the 36 seminal chapters in the first edition to 56 landmark chapters in the second edition. In addition to the 20 new chapters, 11 of the chapters in the first edition have been updated with new materials. Filling the gap that exists between the traditional and modern practice of industrial and systems engineering, the handbook provides a one-stop resource for teaching, research, and practice.
The past decade has seen greatly increased interaction between theoretical work in neuroscience, cognitive science and information processing, and experimental work requiring sophisticated computational modeling. The 152 contributions in NIPS 8 focus on a wide variety of algorithms and architectures for both supervised and unsupervised learning. They are divided into nine parts: Cognitive Science, Neuroscience, Theory, Algorithms and Architectures, Implementations, Speech and Signal Processing, Vision, Applications, and Control. Chapters describe how neuroscientists and cognitive scientists use computational models of neural systems to test hypotheses and generate predictions to guide their work. This work includes models of how networks in the owl brainstem could be trained for complex localization function, how cellular activity may underlie rat navigation, how cholinergic modulation may regulate cortical reorganization, and how damage to parietal cortex may result in neglect. Additional work concerns development of theoretical techniques important for understanding the dynamics of neural systems, including formation of cortical maps, analysis of recurrent networks, and analysis of self- supervised learning. Chapters also describe how engineers and computer scientists have approached problems of pattern recognition or speech recognition using computational architectures inspired by the interaction of populations of neurons within the brain. Examples are new neural network models that have been applied to classical problems, including handwritten character recognition and object recognition, and exciting new work that focuses on building electronic hardware modeled after neural systems. A Bradford Book
Helps users of computerized statistical packages make correct statistical choices to match data they have collected, in cases of bivariate data analysis. Overviews popular statistical packages, then gives instructions on classifying data, frequency distributions, descriptive statistics, and hypothesis testing. Also covers Chi-square, t tests of two means, ANOVA, correlation, and testing scales. Includes exercises, answers, and a glossary.