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This volume contains the extended versions of papers presented at the 3rd International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA 2015) held on 11-13 May, 2015 in Metz, France. The book contains 5 parts: 1. Mathematical programming and optimization: theory, methods and software, Operational research and decision making, Machine learning, data security, and bioinformatics, Knowledge information system, Software engineering. All chapters in the book discuss theoretical and algorithmic as well as practical issues connected with computation methods & optimization methods for knowledge engineering and machine learning techniques.

Cover -- Title Page -- Copyright -- Contents -- Introduction -- Why You Need This Book -- How to Use This Book -- Notes -- Part One Foundation -- Chapter 1 Once Upon A Time -- Defining Terms -- Notes -- Chapter 2 The Angel in the Marble -- Six Perspectives on Purpose -- Purpose Wash? -- Harnessing the Power of Purpose -- Discovering Purpose -- Notes -- Chapter 3 Milk and Mushrooms -- Know Thyself -- Say What You See -- Notes -- Chapter 4 Telling Stories -- What Makes a Good Story? -- Notes -- Chapter 5 Everything Must Change -- Mergers and Acquisitions -- Change - This Time It's Personal -- Turning Theory into Practice -- Notes -- Part Two Story -- Chapter 6 Beginnings -- Once Upon a Time -- First Meeting -- Lawyers, Generally -- Digging Deeper -- Three's a Crowd? -- No Mud, No Lotus -- Writing the Story -- The Story Itself -- Telling the Story -- Notes -- Chapter 7 Starting Out -- Getting to Yes -- Telling Everyone Else -- Getting Organised -- Do It Yourself -- Do It Once, Do It Fast, Do It Right -- Shaping the New Firm -- Project Triangle -- Tell Us Something We Don't Know -- Getting to Know You -- Information Overload -- Notes -- Chapter 8 Making It Happen -- Le Weekend -- Day 1 -- Reality Bites - The First Fortnight -- Bottlenecks and Bloody Marys -- Getting a Grip -- How Do I Love Thee? Let Me Count the Ways -- The First 150 Days - Making a Plan -- Paper, Stone, Scissors - The Best of Three -- Keep Talking . . . -- . . . Whoa, Keep Talking -- Tate That -- Getting It Together -- Moving On -- Notes -- Part Three Because -- Chapter 9 Belonging -- What Is Belonging and Why Does It Matter? -- What Happens to Our Sense of Belonging When Things Change? -- How to Build Belonging -- Connecting and Building Relationships -- A House Is Not A Home -- Identity -- Conclusion -- Notes -- Chapter 10 Evolution -- You Say You Want an Evolution . . .

Front Matter -- Structural Equation Modeling -- Structural Equation Modeling Software -- Steps in Structural Equation Modeling -- Advanced Topics: Principles and Applications -- References -- Index -- Other titles from iSTE in Mathematics and Statistics

The R Companion to Elementary Applied Statistics includes traditional applications covered in elementary statistics courses as well as some additional methods that address questions that might arise during or after the application of commonly used methods. Beginning with basic tasks and computations with R, readers are then guided through ways to bring data into R, manipulate the data as needed, perform common statistical computations and elementary exploratory data analysis tasks, prepare customized graphics, and take advantage of R for a wide range of methods that find use in many elementary applications of statistics. Features: Requires no familiarity with R or programming to begin using this book. Can be used as a resource for a project-based elementary applied statistics course, or for researchers and professionals who wish to delve more deeply into R. Contains an extensive array of examples that illustrate ideas on various ways to use pre-packaged routines, as well as on developing individualized code. Presents quite a few methods that may be considered non-traditional, or advanced. Includes accompanying carefully documented script files that contain code for all examples presented, and more. R is a powerful and free product that is gaining popularity across the scientific community in both the professional and academic arenas. Statistical methods discussed in this book are used to introduce the fundamentals of using R functions and provide ideas for developing further skills in writing R code. These ideas are illustrated through an extensive collection of examples. About the Author: Christopher Hay-Jahans received his Doctor of Arts in mathematics from Idaho State University in 1999. After spending three years at University of South Dakota, he moved to Juneau, Alaska, in 2002 where he has taught a wide range of undergraduate courses at University of Alaska Southeast.

1. Risk measures in finance and insurance. 1.1. Risk measures in finance and portfolio management. 1.2. Risk measures in Solvency II system. 1.3. Risk measures in risk theory. 1.4. Aim and structure of the book. 1.5. Readers, to whom this book is addressed. Problems. 2. Fixed-probability level in a diffusion model. 2.1. Diffusion model: an auxiliary tool. 2.2. Direct level-crossing problem. 2.3. Inverse level-crossing problem. 2.4. Asymptotic behaviour of fixed-probability level. 2.5. Primary upper bounds on fixed-probability level. 2.6. Elaborated upper bounds on fixed-probability level. 2.7. Conclusions and perspectives. Problems. 3. Fixed-probability level in an exceptional renewal model. 3.1. Exponential renewal model: an exceptional case. 3.2. Direct level-crossing problem. 3.3. Inverse level-crossing problem. 3.4. Asymptotic behaviour of fixed-probability level. 3.5. Primary upper bounds on fixed-probability level. 3.6. Elaborated upper bounds on fixed-probability level. 3.7. Conclusions. Problems. 4. Implicit function defined by M-equation. 4.1. Analytical properties of core integral expression. 4.2. Proximity between Mu;c(t) and Mu;c(t j v). 4.3. Analytical properties of M-level. Problem. 5. Fixed-probability level in general renewal model. 5.1. General renewal model: main framework. 5.2. Direct level-crossing problem. 5.3. Inverse level-crossing problem. 5.4. Primary upper bounds on fixed-probability level. 5.5. Proximity to M-level. 5.6. Conclusion. Problem. 6. Case study: numerical evaluation of fixed-probability Level. 6.1. Distributions of T and Y selected for numerical calculations. 6.2. Simulation in level-crossing problems. 6.3. Numerically calculated bounds on the fixed-probability level. 6.4. Conclusion. Problems. 7. Probability mechanism of insurance with migration and ERS-analysis. 7.1. Structural model of insurance business: origin and purpose of ERS-analysis. 7.2. Price competition, migration, and market price. 7.3. Compound Poisson risk model with migration. 7.4. ERS-analysis, when Y is exponentially distributed. 7.5. ERS-analysis, when Y is generally distributed. 7.6. Conclusions. Problems. A. Auxiliary results from analysis. B. Auxiliary results from probability. List of Notations. Notes and Comments. Bibliography. Index.

Front Cover; Game Theory and Applications; Copyright Page; Table of Contents; Contributors; Preface; Chapter 1. Refinement of Nash Equilibrium: The Main Ideas; 1. INTRODUCTION; 2. BACKWARD INDUCTION AND FORWARD INDUCTION; 3. INFORMAL APPLICATIONS; 4. THE PROBLEM OF INCONSISTENCY; 5. THE EXISTENCE THEOREM: VERSION I; 6. FORMAL APPLICATIONS; 7. CONSISTENCY OF BELIEFS; 8. ADMISSIBILITY; 9. RESTRICTIONS ON OUT-OF-EQUILIBRIUM BELIEFS; 10. ALTERNATIVE VIEWS OF ""IRRELEVANT ALTERNATIVES""; 11. DEDUCTIONS BEYOND IIA; 12. CONCLUDING REMARKS; ACKNOWLEDGMENTS; APPENDIX A; APPENDIX B: PROOF OF THEOREM 3.

Unmanned aerial vehicles (UAVs) are increasingly used in military missions because they have the advantages of not placing human life at risk and of lowering operation costs via decreased vehicle weight. These benefits can be fully realized only if UAVs work cooperatively in groups with an efficient exchange of information. This book provides an authoritative reference on cooperative decision and control of UAVs and the means available to solve problems involving them

"Stress tests are the most innovative regulatory tool to prevent and fight financial crises. Their use has fundamentally changed the mathematical modeling of financial systems, financial risk management in the public and private sector, and the policies designed to prevent and mitigate financial crises. When financial crises hit, stress tests take center stage. Despite their centrality to public policy, the optimal design and use of stress tests remains highly contested. Written by an international team of leading thinkers from academia, the public sector and the private sector, this handbook comprehensively surveys and evaluates the state of play and charts the innovations that will determine the path ahead. It is a comprehensive and interdisciplinary resource that bridges theory and practice and places financial stress testing in its wider context. This guide is essential reading for researchers, practitioners and policymakers working on financial risk management and financial regulation"--

In many branches of science relevant observations are taken sequentially over time. Bayesian Analysis of Time Series discusses how to use models that explain the probabilistic characteristics of these time series and then utilizes the Bayesian approach to make inferences about their parameters. This is done by taking the prior information and via Bayes theorem implementing Bayesian inferences of estimation, testing hypotheses, and prediction. The methods are demonstrated using both R and WinBUGS. The R package is primarily used to generate observations from a given time series model, while the WinBUGS packages allows one to perform a posterior analysis that provides a way to determine the characteristic of the posterior distribution of the unknown parameters. Features Presents a comprehensive introduction to the Bayesian analysis of time series. Gives many examples over a wide variety of fields including biology, agriculture, business, economics, sociology, and astronomy. Contains numerous exercises at the end of each chapter many of which use R and WinBUGS. Can be used in graduate courses in statistics and biostatistics, but is also appropriate for researchers, practitioners and consulting statisticians. About the author Lyle D. Broemeling, Ph.D., is Director of Broemeling and Associates Inc., and is a consulting biostatistician. He has been involved with academic health science centers for about 20 years and has taught and been a consultant at the University of Texas Medical Branch in Galveston, The University of Texas MD Anderson Cancer Center and the University of Texas School of Public Health. His main interest is in developing Bayesian methods for use in medical and biological problems and in authoring textbooks in statistics. His previous books for Chapman & Hall/CRC include Bayesian Biostatistics and Diagnostic Medicine, and Bayesian Methods for Agreement.

X and the City, a book of diverse and accessible math-based topics, uses basic modeling to explore a wide range of entertaining questions about urban life. How do you estimate the number of dental or doctor's offices, gas stations, restaurants, or movie theaters in a city of a given size? How can mathematics be used to maximize traffic flow through tunnels? Can you predict whether a traffic light will stay green long enough for you to cross the intersection? And what is the likelihood that your city will be hit by an asteroid? Every math problem and equation in this book tells