Maintenance Manual For Lifelong Learning

Otolaryngology Lifelong Learning Manual, Third Edition is the AAO-HNSF's comprehensive guide for lifelong learning and for those taking certification and re-certification exams in otolaryngology-head and neck surgery. The book is divided into ten sections, each representing a subspecialty within otolaryngology-head and neck surgery, including: General, Facial Plastic and Reconstructive Surgery, Head and Neck, Laryngology and Bronchoesophagology, Otology and Neurotology, Pediatric Otolaryngology, Rhinology and Allergy. Key Features: Focuses on continuing professional development(CPD) and lifelong learning Covers the clinical fundamentals that all otolaryngologists must master Includes a new chapter on trauma written by the AAO-HNSF Trauma Committee which includes active duty military physicians This exam review book is an essential study guide for all residents in otolaryngology preparing for certification exams as well as practicing otolaryngologists preparing to take their re-certification exams.

There is a wealth of research and literature explaining suburban sprawl and the urgent need to retrofit suburbia. However, until now there has been no single guide that directly explains how to repair typical sprawl elements. The Sprawl Repair Manual demonstrates a step-by-step design process for the re-balancing and re-urbanization of suburbia into more sustainable, economical, energy- and resource-efficient patterns, from the region and the community to the block and the individual building. As Galina Tachieva asserts in this exceptionally useful book, sprawl repair will require a proactive and aggressive approach, focused on design, regulation and incentives. The Sprawl Repair Manual is a much-needed, single-volume reference for fixing sprawl, incorporating changes into the regulatory system, and implementing repairs through incentives and permitting strategies. This manual specifies the expertise that’s needed and details the techniques and algorithms of sprawl repair within the context of reducing the financial and ecological footprint of urban growth. The Sprawl Repair Manual draws on more than two decades of practical experience in the field of repairing and building communities to analyze the current pattern of sprawl development, disassemble it into its elemental components, and present a process for transforming them into human-scale, sustainable elements. The techniques are illustrated both two- and three-dimensionally, providing users with clear methodologies for the sprawl repair interventions, some of which are radical, but all of which will produce positive results.

This manual is intended primarily to support policymakers and managers in local education authorities (LEAs) in carrying out their duties under Britain's Further and Higher Education Act 1992 in the new context of collaborative planning as set out in the 1998 Green Paper, "Learning Is for Everyone." Section 1 provides a summary of the legislative background to the adequate provision of further education in Wales. Section 2 presents a framework for LEAs and their partners for defining adequacy at local level. Section 3 focuses on an essential ingredient in determining adequacy--to build a picture of current participation and provision. Section 4 focuses on needs assessment, which is critical to determining adequacy in the local area. Section 5 provides strategies for determining strategic priorities. It sets out a suggested list of six key roles for the LEA: providing a clear definition of adequacy, ensuring that participation is accurately monitored, ensuring that all stakeholders are involved in planning and delivery, identifying how LEA services contribute to adequacy, securing the contributions of other stakeholders to adequacy, and promoting stakeholder collaboration and cooperation. Section 6 considers strategies and approaches for the roles that deal with partnership in planning. Appendixes contain the following a description of an LEA project in Wales; Green Paper extracts; Swansea's Charter that commits it to becoming a city and county of learning; integrated summary of two assessment frameworks; example of community mapping exercise; two examples of auditing provisions; and examples of local functional partnerships. (YLB)

Lifelong Machine Learning, Second Edition is an introduction to an advanced machine learning paradigm that continuously learns by accumulating past knowledge that it then uses in future learning and problem solving. In contrast, the current dominant machine learning paradigm learns in isolation: given a training dataset, it runs a machine learning algorithm on the dataset to produce a model that is then used in its intended application. It makes no attempt to retain the learned knowledge and use it in subsequent learning. Unlike this isolated system, humans learn effectively with only a few examples precisely because our learning is very knowledge-driven: the knowledge learned in the past helps us learn new things with little data or effort. Lifelong learning aims to emulate this capability, because without it, an AI system cannot be considered truly intelligent. Research in lifelong learning has developed significantly in the relatively short time since the first edition of this book was published. The purpose of this second edition is to expand the definition of lifelong learning, update the content of several chapters, and add a new chapter about continual learning in deep neural networks—which has been actively researched over the past two or three years. A few chapters have also been reorganized to make each of them more coherent for the reader. Moreover, the authors want to propose a unified framework for the research area. Currently, there are several research topics in machine learning that are closely related to lifelong learning—most notably, multi-task learning, transfer learning, and meta-learning—because they also employ the idea of knowledge sharing and transfer. This book brings all these topics under one roof and discusses their similarities and differences. Its goal is to introduce this emerging machine learning paradigm and present a comprehensive survey and review of the important research results and latest ideas in the area. This book is thus suitable for students, researchers, and practitioners who are interested in machine learning, data mining, natural language processing, or pattern recognition. Lecturers can readily use the book for courses in any of these related fields.