The Principle of Normalization in Human Services
Author: Wolf Wolfensberger
Publisher:
Published: 1979
Total Pages: 258
ISBN-13:
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Normalization in World Politics
Author: Nicolas Lemay-Hebert
Publisher: University of Michigan Press
Published: 2022-02-08
Total Pages: 333
ISBN-13: 0472902814
DOWNLOAD EBOOKAs we face new challenges from climate change and the rise of populism in Western politics and beyond, there is little doubt that we are entering a new configuration of world politics. Driven by nostalgia for past certainties or fear of what is coming next, references to normalcy have been creeping into political discourse, with people either vying for a return to a past normalcy or coping with the new normal. This book traces main discourses and practices associated with normalcy in world politics. Visoka and Lemay-Hébert mostly focus on how dominant states and international organizations try to manage global affairs through imposing normalcy over fragile states, restoring normalcy over disaster-affected states, and accepting normalcy over suppressive states. They show how discourses and practices come together in constituting normalization interventions and how in turn they play in shaping the dynamics of continuity and change in world politics.
A Quarter-century of Normalization and Social Role Valorization
Author: Robert John Flynn
Publisher: University of Ottawa Press
Published: 1999
Total Pages: 586
ISBN-13: 0776604856
DOWNLOAD EBOOKDuring the late 1960s, Normalization and Social Role Valorization (SRV) enabled the widespread emergence of community residential options and then provided the philosophical climate within which educational integration, supported employment, and community participation were able to take firm root. This book is unique in tracing the evolution and impact of Normalization and SRV over the last quarter-century, with many of the chapter authors personally involved in a still-evolving international movement. Published in English.
Normalization of Multidimensional Data for Multi-Criteria Decision Making Problems
Author: Irik Z. Mukhametzyanov
Publisher: Springer Nature
Published: 2023-07-25
Total Pages: 314
ISBN-13: 3031338375
DOWNLOAD EBOOKThis book presents a systematic review of multidimensional normalization methods and addresses problems frequently encountered when using various methods and ways to eliminate them. The invariant properties of the linear normalization methods presented here can be used to eliminate simple problems and avoid obvious errors when choosing a normalization method. The book introduces valuable, novel techniques for the multistep normalization of multidimensional data. One of these methods involves inverting the normalized values of cost attributes into profit attributes based on the reverse sorting algorithm (ReS algorithm). Another approach presented is the IZ method, which addresses the issue of shift in normalized attribute values. Additionally, a new method for normalizing the decision matrix is proposed, called the MS method, which ensures the equalization of average values and variances of attributes. Featuring numerous illustrative examples throughout, the book helps readers to understand what difficulties can arise in multidimensional normalization, what to expect from such problems, and how to solve them. It is intended for academics and professionals in various areas of data science, computing in mathematics, and statistics, as well as decision-making and operations.
Normalization and "outsiderhood"
Author: Siv Fahlgren
Publisher: Bentham Science Publishers
Published: 2011
Total Pages: 130
ISBN-13: 1608052796
DOWNLOAD EBOOKThis volume presents an illuminating analysis of the ways in which normalization processes and practices operate in a welfare state in an age of neoliberalism. This informative book problematizes the meaning of the phrase 'normalization processes and prac
Normalization Techniques in Deep Learning
Author: Lei Huang
Publisher: Springer Nature
Published: 2022-10-08
Total Pages: 117
ISBN-13: 303114595X
DOWNLOAD EBOOKThis book presents and surveys normalization techniques with a deep analysis in training deep neural networks. In addition, the author provides technical details in designing new normalization methods and network architectures tailored to specific tasks. Normalization methods can improve the training stability, optimization efficiency, and generalization ability of deep neural networks (DNNs) and have become basic components in most state-of-the-art DNN architectures. The author provides guidelines for elaborating, understanding, and applying normalization methods. This book is ideal for readers working on the development of novel deep learning algorithms and/or their applications to solve practical problems in computer vision and machine learning tasks. The book also serves as a resource researchers, engineers, and students who are new to the field and need to understand and train DNNs.
Methods in Microarray Normalization
Author: Phillip Stafford
Publisher: CRC Press
Published: 2008-01-31
Total Pages: 322
ISBN-13: 1420052799
DOWNLOAD EBOOKThis organized text compiles, for the first time, the most useful normalization methods developed for interpreting microarray data. Experts examine the mathematical processes that are important in normalizing data and avoiding inherent systematic biases. They also review modern software, including discussions on key algorithms, comparative data, and download locations. The book contains the latest microarray innovations from companies such as Agilent, Affymetrix, and GeneGo as well as new, readily adaptable normalization methods for expression and CGH arrays. It also lists of open-source molecular profiling normalization algorithms available and where to access them.
Against Normalization
Author: Anthony O'Brien
Publisher: Duke University Press
Published: 2001-04-13
Total Pages: 356
ISBN-13: 9780822325710
DOWNLOAD EBOOKDIVA literary study of South African cultural changes since the end of apartheid from 1980 to present./div
Hands-On Machine Learning on Google Cloud Platform
Author: Giuseppe Ciaburro
Publisher: Packt Publishing Ltd
Published: 2018-04-30
Total Pages: 489
ISBN-13: 1788398874
DOWNLOAD EBOOKUnleash Google's Cloud Platform to build, train and optimize machine learning models Key Features Get well versed in GCP pre-existing services to build your own smart models A comprehensive guide covering aspects from data processing, analyzing to building and training ML models A practical approach to produce your trained ML models and port them to your mobile for easy access Book Description Google Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine learning models at scale but also host them in the cloud to make predictions. This book is focused on making the most of the Google Machine Learning Platform for large datasets and complex problems. You will learn from scratch how to create powerful machine learning based applications for a wide variety of problems by leveraging different data services from the Google Cloud Platform. Applications include NLP, Speech to text, Reinforcement learning, Time series, recommender systems, image classification, video content inference and many other. We will implement a wide variety of deep learning use cases and also make extensive use of data related services comprising the Google Cloud Platform ecosystem such as Firebase, Storage APIs, Datalab and so forth. This will enable you to integrate Machine Learning and data processing features into your web and mobile applications. By the end of this book, you will know the main difficulties that you may encounter and get appropriate strategies to overcome these difficulties and build efficient systems. What you will learn Use Google Cloud Platform to build data-based applications for dashboards, web, and mobile Create, train and optimize deep learning models for various data science problems on big data Learn how to leverage BigQuery to explore big datasets Use Google’s pre-trained TensorFlow models for NLP, image, video and much more Create models and architectures for Time series, Reinforcement Learning, and generative models Create, evaluate, and optimize TensorFlow and Keras models for a wide range of applications Who this book is for This book is for data scientists, machine learning developers and AI developers who want to learn Google Cloud Platform services to build machine learning applications. Since the interaction with the Google ML platform is mostly done via the command line, the reader is supposed to have some familiarity with the bash shell and Python scripting. Some understanding of machine learning and data science concepts will be handy
Information Systems Reengineering, Integration and Normalization
Author: Joseph Shi Piu Fong
Publisher: Springer
Published: 2015-02-09
Total Pages: 400
ISBN-13: 3319122959
DOWNLOAD EBOOKTaking a very practical approach, the author describes in detail database conversion techniques, reverse engineering, forward engineering and re-engineering methodologies for information systems, offering a systematic software engineering approach for reusing existing database systems built with “old” technology. He demonstrates how the existing systems can be transformed into the new technologies with the preservation of semantic constraints and without loss of information. In this third edition, with a new chapter on Data Normalization the author shows once the databases have been converted, how to integrate them for consolidating information, and how to normalize them so that they are efficient and user friendly. Many examples, illustrations and case studies together with questions and answers ensure that the methodology is easy to follow. Ideal as a textbook for students studying information systems theories, Information Systems Reengineering Integration and Normalization will also be a valuable management reference book for Information Technology Practitioners. Additional material is available on www.extramaterials/978-3-319-12294-6
