Automatic Methods of Analysis
Automatic Methods of Analysis

Author: M. Valcárcel

Publisher: Elsevier

Published: 1988-08-01

Total Pages: 573

ISBN-13: 0080875572

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This new monograph provides a comprehensive overview of the state of the art of the automation of laboratory processes in analytical chemistry. The topics have been chosen according to such criteria as the degree of consolidation, scope of application and most promising trends.The first part of the book begins with the basic principles behind the automation of laboratory processes, then describes automatic systems for sampling and sample treatment. In the second part the principal types of analysers are discussed: continuous, batch and robotic. The third part is devoted to the automation of analytical instrumentation: spectroscopic, electroanalytical and chromatographic techniques and titrators. The last part presents some examples of the application of automation to clinical chemistry, environmental pollution monitoring and industrial process control.The text is supplemented by 290 figures and 800 literature references. It is written primarily for scientists directly involved in laboratory work and those responsible for industrial planning and control, research centres, etc. It will also be of interest to analytical chemists wishing to update their knowledge in this area, and will be of especial interest to scientists directly related to environmental sciences or clinical chemistry.

Text as Data
Text as Data

Author: Justin Grimmer

Publisher: Princeton University Press

Published: 2022-03-29

Total Pages: 0

ISBN-13: 0691207542

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A guide for using computational text analysis to learn about the social world From social media posts and text messages to digital government documents and archives, researchers are bombarded with a deluge of text reflecting the social world. This textual data gives unprecedented insights into fundamental questions in the social sciences, humanities, and industry. Meanwhile new machine learning tools are rapidly transforming the way science and business are conducted. Text as Data shows how to combine new sources of data, machine learning tools, and social science research design to develop and evaluate new insights. Text as Data is organized around the core tasks in research projects using text—representation, discovery, measurement, prediction, and causal inference. The authors offer a sequential, iterative, and inductive approach to research design. Each research task is presented complete with real-world applications, example methods, and a distinct style of task-focused research. Bridging many divides—computer science and social science, the qualitative and the quantitative, and industry and academia—Text as Data is an ideal resource for anyone wanting to analyze large collections of text in an era when data is abundant and computation is cheap, but the enduring challenges of social science remain. Overview of how to use text as data Research design for a world of data deluge Examples from across the social sciences and industry

Automatic Autocorrelation and Spectral Analysis
Automatic Autocorrelation and Spectral Analysis

Author: Piet M. T. Broersen

Publisher: Springer Science & Business Media

Published: 2006-04-20

Total Pages: 301

ISBN-13: 1846283280

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Spectral analysis requires subjective decisions which influence the final estimate and mean that different analysts can obtain different results from the same stationary stochastic observations. Statistical signal processing can overcome this difficulty, producing a unique solution for any set of observations but that is only acceptable if it is close to the best attainable accuracy for most types of stationary data. This book describes a method which fulfils the above near-optimal-solution criterion, taking advantage of greater computing power and robust algorithms to produce enough candidate models to be sure of providing a suitable candidate for given data.

Automated Machine Learning
Automated Machine Learning

Author: Frank Hutter

Publisher: Springer

Published: 2019-05-17

Total Pages: 223

ISBN-13: 3030053180

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This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.

Topics in Applied Multivariate Analysis
Topics in Applied Multivariate Analysis

Author: D. M. Hawkins

Publisher: Cambridge University Press

Published: 1982-04-22

Total Pages: 384

ISBN-13: 9780521243681

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Multivariate methods are employed widely in the analysis of experimental data but are poorly understood by those users who are not statisticians. This is because of the wide divergence between the theory and practice of multivariate methods. This book provides concise yet thorough surveys of developments in multivariate statistical analysis and gives statistically sound coverage of the subject. The contributors are all experienced in the theory and practice of multivariate methods and their aim has been to emphasize the major features from the point of view of applicability and to indicate the limitations and conditions of the techniques. Professional statisticians wanting to improve their background in applicable methods, users of high-level statistical methods wanting to improve their background in fundamentals, and graduate students of statistics will all find this volume of value and use.

Food Protein Analysis
Food Protein Analysis

Author: Richard Owusu-Apenten

Publisher: CRC Press

Published: 2002-05-24

Total Pages: 428

ISBN-13: 0824744675

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Ideal for planning, performing, and interpreting food protein analyses, especially as it relates to the effect of food processing on protei investigation results. Delineates basic research principles, practices, and anticipated outcomes in each of the illustrated protein assays.