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| back ups 600 apc manual: McWp 3-35.3 - Military Operations on Urbanized Terrain (Mout) U. S. Marine Corps, 2015-02-01 This manual provides guidance for the organization, planning, and conduct of the full range of military operations on urbanized terrain. This publication was prepared primarily for commanders, staffs, and subordinate leaders down to the squad and fire team level. It is written from a Marine air-ground task force perspective, with emphasis on the ground combat element as the most likely supported element in that environment. It provides the level of detailed information that supports the complexities of planning, preparing for, and executing small-unit combat operations on urbanized terrain. It also provides historical and environmental information that supports planning and training for combat in built-up areas |
| back ups 600 apc manual: Operations Management in Automotive Industries Marco Gobetto, 2013-10-23 This book has proved its worth over the years as a text for courses in Production Management at the Faculty of Automotive Engineering in Turin, Italy, but deserves a wider audience as it presents a compendium of basics on Industrial Management, since it covers all major topics required. It treats all subjects from product development and “make or buy”-decision strategies to the manufacturing systems setting and management through analysis of the main resources needed in production and finally exploring the supply chain management and the procurement techniques. The very last chapter recapitulates the previous ones by analysing key management indicators to pursue the value creation that is the real purpose of every industrial enterprise. As an appendix, a specific chapter is dedicated to the basics of production management where all main relevant definitions, techniques and criteria are treated, including some numerical examples, in order to provide an adequate foundation for understanding the other chapters. This book will be of use not only to Automotive Engineering students but a wide range of readers who wish to gain insight in the world of automotive engineering and the automotive industry in general. |
| back ups 600 apc manual: Bayesian Networks Olivier Pourret, Patrick Naïm, Bruce Marcot, 2008-04-30 Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is now employed across a variety of fields for the purposes of analysis, simulation, prediction and diagnosis. This book provides a general introduction to Bayesian networks, defining and illustrating the basic concepts with pedagogical examples and twenty real-life case studies drawn from a range of fields including medicine, computing, natural sciences and engineering. Designed to help analysts, engineers, scientists and professionals taking part in complex decision processes to successfully implement Bayesian networks, this book equips readers with proven methods to generate, calibrate, evaluate and validate Bayesian networks. The book: Provides the tools to overcome common practical challenges such as the treatment of missing input data, interaction with experts and decision makers, determination of the optimal granularity and size of the model. Highlights the strengths of Bayesian networks whilst also presenting a discussion of their limitations. Compares Bayesian networks with other modelling techniques such as neural networks, fuzzy logic and fault trees. Describes, for ease of comparison, the main features of the major Bayesian network software packages: Netica, Hugin, Elvira and Discoverer, from the point of view of the user. Offers a historical perspective on the subject and analyses future directions for research. Written by leading experts with practical experience of applying Bayesian networks in finance, banking, medicine, robotics, civil engineering, geology, geography, genetics, forensic science, ecology, and industry, the book has much to offer both practitioners and researchers involved in statistical analysis or modelling in any of these fields. |
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