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Presenting the science of statistical process control (SPC) and the related concepts of total quality management (TQM) and design of experiments (DOE), this remarkable reference demonstrates ways to track industrial processes and performance -- integrating related areas such as engineering process control, statistical reasoning in TQM, robust parameter design, control charts, multivariate process monitoring, capability indices, experimental design, empirical model building, and process optimization. Written by more than 25 renowned researchers with broad experience with on-the-job problem solving, Statistical Process Monitoring and Optimization showcases concepts such as "people-based management" and continuous improvement...examines leadership styles in European, American, and Asian companies...describes means of quantifying factors such as employee loyalty and customer satisfaction and their relation to profitability...explores multivariate diagnosis theory in application to multioperational and multi-index systems...assesses uses of Markov chains in relation to ARL and associated sampling distributions...explains statistical models for dynamic systems, change-point analysis, generalized linear models, and key algorithms...elucidates replication strategies and process capability...reviews the interplay of intraorganizational domains such as finance, marketing, resource allocation, software engineering, and strategic planning...and more. Containing over 1000 references, drawings, tables, and equations, Statistical Process Monitoring and Optimization is a must-read resource for applied statisticians; industrial, quality control, and management science engineers; and upper-level undergraduate and graduate students in these disciplines. Book jacket.
This book, which has been prepared by an international group of experts, provides comprehensive guidance for the design, planning and implementation of assessments and monitoring programmes for water bodies used for recreation. It addresses the wide range of hazards which may be encountered and emphasizes the importance of linking monitoring programmes to effective and feasible management actions to protect human health. It also provides details of sampling and analytical methods.
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.
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