Shiyu Zhou's Books

Industrial Data Analytics for Diagnosis and Prognosis

A Random Effects Modelling Approach

By: Shiyu Zhou,Yong Chen

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Industrial Data Analytics for Diagnosis and Prognosis

A Random Effects Modelling Approach

By: Shiyu Zhou,Yong Chen

Discover data analytics methodologies for the diagnosis and prognosis of industrial systems under a unified random effects model In Industrial Data Analytics for Diagnosis and Prognosis - A Random Effects Modelling Approach, distinguished engineers Shiyu Zhou and Yong Chen deliver a rigorous and practical introduction to the random effects modeling approach for industrial system diagnosis and prognosis. In the book’s two parts, general statistical concepts and useful theory are described and explained, as are industrial diagnosis and prognosis methods. The accomplished authors describe and model fixed effects, random effects, and variation in univariate and multivariate datasets and cover the application of the random effects approach to diagnosis of variation sources in industrial processes. They offer a detailed performance comparison of different diagnosis methods before moving on to the application of the random effects approach to failure prognosis in industrial processes and systems. In addition to presenting the joint prognosis model, which integrates the survival regression model with the mixed effects regression model, the book also offers readers: A thorough introduction to describing variation of industrial data, including univariate and multivariate random variables and probability distributions Rigorous treatments of the diagnosis of variation sources using PCA pattern matching and the random effects model An exploration of extended mixed effects model, including mixture prior and Kalman filtering approach, for real time prognosis A detailed presentation of Gaussian process model as a flexible approach for the prediction of temporal degradation signals Ideal for senior year undergraduate students and postgraduate students in industrial, manufacturing, mechanical, and electrical engineering, Industrial Data Analytics for Diagnosis and Prognosis is also an indispensable guide for researchers and engineers interested in data analytics methods for system diagnosis and prognosis.

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Page Count

356

Publisher

John Wiley & Sons

Published Date

ISBN 10

1119666309

ISBN 13

9781119666301

Graphene Field-Effect Transistor Biosensors

By: Shiyu Wang,Zakir Hossain,Yan Zhao,Tao Han

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Graphene Field-Effect Transistor Biosensors

By: Shiyu Wang,Zakir Hossain,Yan Zhao,Tao Han

In this monograph, the graphene-based field-effect transistor (FET) biosensors are shown to be an emerging sensing platform. Divided into two parts the first set of chapters are devoted to basic knowledge of graphene, graphene FET and its biosensing. In the second part of this book the applications of graphene FET biosensors combined with various biotechnologies are presented. As well as discussing the existing technologies the authors also introduce their own ideas and concepts. Finally the remaining problems in graphene FET biosensors are discussed, along with proposed solutions and prospects for future applications. This monograph allows readers to grasp the basic knowledge and future direction of graphene-based FET biosensors.

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