Listen to Coronavirus Patient Zero
Preface. Acknowledgements. Part 1: Introduction. A. Scope of the subject. B. Description of the research program. C. Outline of the monograph. Part 2: An Introduction to Mathematical and Physical Modelling of Microwave Scattering and Polarimetric Remote Sensing. 1. Introduction to Inverse Radar Scattering Problems. 1.1. Theoretical aspects. 1.2. Pattern recognition and evaluation parameters. 1.3. Conditions for implementing inverse scattering techniques. 1.4. Polarimetric radar. 2. Description of Remote Sensing by Radar Polarimetry. 2.1. Physical process of encoding/decoding of polarimetric data. 2.2. Physical realization of a polarimetric radar. 2.3. Methods of measurements of polarimetric data. 2.4. Radar techniques for polarimetric remote sensing. 3. Physical and Mathematical Modelling. 3.1. Physical modelling. 3.2. Mathematical modelling. 4. Summary of Available Scattering Methods. 4.1. Introduction. 4.2. Transport theory: radiative transfer equation. Part 3: Diagnostics of the Earth s Environment Using Polarimetric Radar Monitoring: Formulation and Potential Applications. 5. Basic Mathematical Modelling for Random Environments. 5.1. Introduction. 5.2. Space spectrum method. 5.3. Solutions. 5.4. Conclusions and applications. 6. Review of Vegetation Models. 6.1. Introduction. 6.2. Biometrical characteristics of vegetation. 6.3. Electrophysical characteristics of vegetation. 6.4. Electrodynamic model of vegetation. 6.5. Determination of biometrical characteristics of vegetation from radar remote sensing data. 6.6. Classification of vegetation. 6.7. Conclusions and applications. 7. Electrodynamic and Physical Characteristics of Earth Surfaces. 7.1. Introduction. 7.2. Complex permittivity. 7.3. Dielectric and physical parameters. 7.4. Interrelations between dielectric and physical characteristics. 7.5. Conclusions and applications. 8. Reflection of Electromagnetic Waves from Non-Uniform Layered Structures. 8.1. Introduction 8.2. Deterministic approach. 8.3. Stochastic case of three layers with flat boundaries. 8.4. Conclusions and applications. 9. Radiowave Reflection from Structures with Internal Ruptures. 9.1. Introduction. 9.2. Reflection from a symmetrical wedge-shaped fracture. 9.3. Reflection from an asymmetric wedge-shaped fracture. 9.4. Reflection from a pit with spherical form. 9.5. Reflection from a rectangular pit with finite depth. 9.6. Antenna pattern and fracture filling effects. 9.7. Combined model. 9.8. Conclusions and applications. 10. Scattering of Waves by a Layer with a Rough Boundary. 10.1. Introduction. 10.2. Initial equations and solutions. 10.3. Model parameters of an ensemble of co-directional cylinders. 10.4. Conclusions and applications. 11. Polarimetric Methods for Measuring Permittivity Characteristics of the Earth's Surface. 11.1. Introduction. 11.2. Determination of the complex permittivity. 11.3. The KLL sphere. 11.4. Conclusions and applications. 12. Implementing Solutions to Inverse Scattering Problems: Signal Processing and Applications. 12.1. Introduction. 12.2. Radar imaging. 12.3. Synthetic Aperture Radar (SAR). 12.4. Radar altimeter. 12.5. Tropospheric-scatter radar. 12.6. Atmospheric monitoring with polarimetry. Part 4: Concluding Remarks. 13. Review of Potential Applications of Radar Polarimetry. 13.1. Introduction. 13.2. Results of polarimetric remote sensing. 13.3. Comparison-review of the inverse scattering models analyzed. 14. Historical Development of Radar Polarimetry in Russia. 14.1. Introduction. 14.2. General theory of polarization of radiowaves. 14.3. The polarization theory of the radar targets. 14.4. Polarization selection. 14.5. Development of algorithms for the reception of polarized signals. 14.6.Polarization modulation. 14.7. The polarization analysis of scattered and reflected radiowaves for studying the environment. 14.8. Applications of radar-polarimetry in remote sensing systems. Appendix A. Appendix B. Appendix C. Appendix D. Appendix E. Appendix F. References.
The first comprehensive guide to all surface and dermal sampling methods. Written by one of the nation's foremost sampling experts, this authoritative guide offers an integrated approach that combines surface and dermal sampling methods with air and biological monitoring techniques.
The approach taken in this book is to studies monitored over time, what the Central Limit Theorem is to studies with only one analysis. Just as the Central Limit Theorem shows that test statistics involving very different types of clinical trial outcomes are asymptotically normal, this book shows that the joint distribution of the test statistics at different analysis times is asymptotically multivariate normal with the correlation structure of Brownian motion ( the B-value ) irrespective of the test statistic. The so-called B-value approach to monitoring allows us to use, for different types of trials, the same boundaries and the same simple formula for computing conditional power. Although Brownian motion may sound complicated, the authors make the approach easy by starting with a simple example and building on it, one piece at a time, ultimately showing that Brownian motion works for many different types of clinical trials.
The book will be very valuable to statisticians involved in clinical trials. The main body of the chapters is accessible to anyone with knowledge of a standard mathematical statistics text. More mathematically advanced readers will find rigorous developments in appendices at the end of chapters. Reading the book will develop insight into not only monitoring, but power, survival analysis, safety, and other statistical issues germane to clinical trials.
Michael Proschan, Gordon Lan, and Janet Wittes are elected Fellows of the American Statistical Association. All have spent formative years in the Biostatistics Research Branch of the National Heart, Lung, and Blood Institute (NHLBI/NIH). While there, they were intimately involved in the design and statistical monitoring of large-scale randomized clinical trials, developing methodology to aid in their monitoring. For example, Lan developed, with DeMets, the now widely-used spending function approach to group sequential designs, whose properties were further investigated by Proschan. The B-value approach used in the book was introduced in a very influential paper by Lan and Wittes. The statistical theory behind conditional power was developed by Lan, along with Simon and Halperin, and was the cornerstone for the conditional error approach to adaptive clinical trials introduced by Proschan and Hunsberger. All three authors have expertise in adaptive methodology for clinical trials.
Michael Proschan is a Mathematical Statistician at the National Institutes of Health; Gordon Lan is Senior Director of Biometrics at Johnson & Johnson Pharmaceutical Research and Development, L.L.C.; Janet Wittes is President of Statistics Collaborative, a statistical consulting company she founded in 1990."
Deepwater Horizon Articles
Deepwater Horizon Books