This book begins with an introduction of pragmatic cluster randomized trials (PCTs) and reviews various pragmatic issues that need to be addressed by statisticians at the design stage. It discusses the advantages and disadvantages of each type of PCT, and provides sample size formulas, sensitivity analyses, and examples for sample size calculation. The generalized estimating equation (GEE) method will be employed to derive sample size formulas for various types of outcomes from the exponential family, including continuous, binary, and count variables. Experimental designs that have been frequently employed in PCTs will be discussed, including cluster randomized designs, matched-pair cluster randomized design, stratified cluster randomized design, stepped-wedge cluster randomized design, longitudinal cluster randomized design, and crossover cluster randomized design. It demonstrates that the GEE approach is flexible to accommodate pragmatic issues such as hierarchical correlation structures, different missing data patterns, randomly varying cluster sizes, etc. It has been reported that the GEE approach leads to under-estimated variance with limited numbers of clusters. The remedy for this limitation is investigated for the design of PCTs. This book can assist practitioners in the design of PCTs by providing a description of the advantages and disadvantages of various PCTs and sample size formulas that address various pragmatic issues, facilitating the proper implementation of PCTs to improve health care. It can also serve as a textbook for biostatistics students at the graduate level to enhance their knowledge or skill in clinical trial design. Key Features: Discuss the advantages and disadvantages of each type of PCTs, and provide sample size formulas, sensitivity analyses, and examples. Address an unmet need for guidance books on sample size calculations for PCTs; A wide variety of experimental designs adopted by PCTs are covered; The sample size solutions can be readily implemented due to the accommodation of common pragmatic issues encountered in real-world practice; Useful to both academic and industrial biostatisticians involved in clinical trial design; Can be used as a textbook for graduate students majoring in statistics and biostatistics.

Accurate sample size calculation ensures that clinical studies have adequate power to detect clinically meaningful effects. This results in the efficient use of resources and avoids exposing a disproportionate number of patients to experimental treatments caused by an overpowered study. Sample Size Calculations for Clustered and Longitudinal Outcomes in Clinical Research explains how to determine sample size for studies with correlated outcomes, which are widely implemented in medical, epidemiological, and behavioral studies. The book focuses on issues specific to the two types of correlated outcomes: longitudinal and clustered. For clustered studies, the authors provide sample size formulas that accommodate variable cluster sizes and within-cluster correlation. For longitudinal studies, they present sample size formulas to account for within-subject correlation among repeated measurements and various missing data patterns. For multiple levels of clustering, the level at which to perform randomization actually becomes a design parameter. The authors show how this can greatly impact trial administration, analysis, and sample size requirement. Addressing the overarching theme of sample size determination for correlated outcomes, this book provides a useful resource for biostatisticians, clinical investigators, epidemiologists, and social scientists whose research involves trials with correlated outcomes. Each chapter is self-contained so readers can explore topics relevant to their research projects without having to refer to other chapters.

Digital fringe projection (DFP) techniques are used for non-contact shape measurement of 3D images. In the rapidly expanding field of 3D high-speed imaging, the demand for DFP continues to grow due to the technology's fast speed, flexibility, low cost, and high accuracy. High-Speed 3D Imaging with Digital Fringe Projection Techniques discusses the generation of digital fringe with digital video projection devices, covering a variety of core technical aspects. The book begins by establishing the theoretical foundations of fringe pattern analysis, reviewing various 3D imaging techniques while highlighting the advantages of DFP. The author then: Describes the differences between digital light processing (DLP), liquid crystal display (LCD), and liquid crystal on silicon (LCoS) Explains how to unwrap phase maps temporally and spatially Shows how to generate fringe patterns with video projectors Demonstrates how to convert phase to coordinates through system calibrations Provides a detailed example of a built-from-scratch 3D imaging system Incorporating valuable insights gained during the author's 15+ years of 3D imaging research, High-Speed 3D Imaging with Digital Fringe Projection Techniques illuminates the pathway to advancement in high-speed 3D optical imaging using DFP.

Accurate sample size calculation ensures that clinical studies have adequate power to detect clinically meaningful effects. This results in the efficient use of resources and avoids exposing a disproportionate number of patients to experimental treatments caused by an overpowered study. Sample Size Calculations for Clustered and Longitudinal Outcomes in Clinical Research explains how to determine sample size for studies with correlated outcomes, which are widely implemented in medical, epidemiological, and behavioral studies. The book focuses on issues specific to the two types of correlated outcomes: longitudinal and clustered. For clustered studies, the authors provide sample size formulas that accommodate variable cluster sizes and within-cluster correlation. For longitudinal studies, they present sample size formulas to account for within-subject correlation among repeated measurements and various missing data patterns. For multiple levels of clustering, the level at which to perform randomization actually becomes a design parameter. The authors show how this can greatly impact trial administration, analysis, and sample size requirement. Addressing the overarching theme of sample size determination for correlated outcomes, this book provides a useful resource for biostatisticians, clinical investigators, epidemiologists, and social scientists whose research involves trials with correlated outcomes. Each chapter is self-contained so readers can explore topics relevant to their research projects without having to refer to other chapters.

With the ongoing release of 3D movies and the emergence of 3D TVs, 3D imaging technologies have penetrated our daily lives. Yet choosing from the numerous 3D vision methods available can be frustrating for scientists and engineers, especially without a comprehensive resource to consult. Filling this gap, Handbook of 3D Machine Vision: Optical Metrology and Imaging gives an extensive, in-depth look at the most popular 3D imaging techniques. It focuses on noninvasive, noncontact optical methods (optical metrology and imaging).

The handbook begins with the well-studied method of stereo vision and explains how random speckle patterns or space-time varying patterns substantially improve the results of stereo vision. It then discusses stereo particle image velocimetry as a major experimental means in fluid dynamics, the robust and easy-to-implement structured-light technique for computer science applications, digital holography for performing micro- to nanoscale measurements, and grating, interferometry, and fringe projection techniques for precisely measuring dynamically deformable natural objects.

The book goes on to describe techniques that do not require triangulation to recover a 3D shape, including time-of-flight techniques and uniaxial 3D shape measurement, as well as 3D measurement techniques that are not restricted to surface capture, such as 3D ultrasound, optical coherence tomography, and 3D endoscopy. The book also explores how novel 3D imaging techniques are being applied in the promising field of biometrics which may prove essential to security and public safety.

Written by key players in the field and inventors of important imaging technologies, this authoritative, state-of-the-art handbook helps you understand the core of 3D imaging technology and choose the proper 3D imaging technique for your needs. For each technique, the book provides its mathematical foundations, summarizes its successful applications, and discusses its limitations. "

With the ongoing release of 3D movies and the emergence of 3D TVs, 3D imaging technologies have penetrated our daily lives. Yet choosing from the numerous 3D vision methods available can be frustrating for scientists and engineers, especially without a comprehensive resource to consult. Filling this gap, Handbook of 3D Machine Vision: Optical Metrology and Imaging gives an extensive, in-depth look at the most popular 3D imaging techniques. It focuses on noninvasive, noncontact optical methods (optical metrology and imaging). The handbook begins with the well-studied method of stereo vision and explains how random speckle patterns or space-time varying patterns substantially improve the results of stereo vision. It then discusses stereo particle image velocimetry as a major experimental means in fluid dynamics, the robust and easy-to-implement structured-light technique for computer science applications, digital holography for performing micro- to nanoscale measurements, and grating, interferometry, and fringe projection techniques for precisely measuring dynamically deformable natural objects. The book goes on to describe techniques that do not require triangulation to recover a 3D shape, including time-of-flight techniques and uniaxial 3D shape measurement, as well as 3D measurement techniques that are not restricted to surface capture, such as 3D ultrasound, optical coherence tomography, and 3D endoscopy. The book also explores how novel 3D imaging techniques are being applied in the promising field of biometrics-which may prove essential to security and public safety. Written by key players in the field and inventors of important imaging technologies, this authoritative, state-of-the-art handbook helps you understand the core of 3D imaging technology and choose the proper 3D imaging technique for your needs. For each technique, the book provides its mathematical foundations, summarizes its successful applications, and discusses its limitations.

Digital fringe projection (DFP) techniques are used for non-contact shape measurement of 3D images. In the rapidly expanding field of 3D high-speed imaging, the demand for DFP continues to grow due to the technology's fast speed, flexibility, low cost, and high accuracy. High-Speed 3D Imaging with Digital Fringe Projection Techniques discusses the generation of digital fringe with digital video projection devices, covering a variety of core technical aspects. The book begins by establishing the theoretical foundations of fringe pattern analysis, reviewing various 3D imaging techniques while highlighting the advantages of DFP. The author then: Describes the differences between digital light processing (DLP), liquid crystal display (LCD), and liquid crystal on silicon (LCoS) Explains how to unwrap phase maps temporally and spatially Shows how to generate fringe patterns with video projectors Demonstrates how to convert phase to coordinates through system calibrations Provides a detailed example of a built-from-scratch 3D imaging system Incorporating valuable insights gained during the author's 15+ years of 3D imaging research, High-Speed 3D Imaging with Digital Fringe Projection Techniques illuminates the pathway to advancement in high-speed 3D optical imaging using DFP.

This book systematically introduces the clinical and imaging characteristics of mediastinal diseases, with emphasis on the essential relationship between clinical diseases and imaging, and on imaging diagnosis and differential diagnosis. This book systematically expounds the etiology, clinical and imaging manifestations, diagnosis, differential diagnosis and treatment of diseases, supplemented by a large number of cases to focus on analysis, focus on clinical thinking, and strive to combine theory with practice, so that readers have a systematic and in-depth understanding of diagnosis and treatment and differential diagnosis of related diseases.

Variational inequalities (VIs) arise from a wide range of application areas, like mechanics, control theory, engineering, and finance. One of the emerging applications of variational inequalities in finance is valuation of American-style options. An option is a derivative contract where the future payoffs to the buyer and seller of the contract are determined by the price of another security, such as a common stock or a basket of stocks. American option pricing can be formulated as an obstacle problem, a particular example of VIs. To solve time dependent variational inequalities numerically, we employ the explicit or implicit Euler method for time-discretization and the finite element method (FEM) for space-discretization with adaptive time-space mesh refinement techniques. Adaptive mesh refinement is an important tool to deal with multiscale phenomena and to reduce the size of the linear systems that arise from the discretization.