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Cover; Half Title; Series Page; Title Page; Copyright Page; Table of Contents; Foreword; Preface; Editors; Contributors; Chapter 1: Implications of World Mega Trends for MCDM Research; Chapter 2: MCDA/M in Telecommunication Networks: Challenges and Trends; Chapter 3: SISTI: A Multicriteria Approach to Structure Complex Decision Problems; Chapter 4: Applying Intangible Criteria in Multiple-Criteria Optimization Problems: Challenges and Solutions; Chapter 5: Some Methods and Algorithms for Constructing Smart-City Rankings

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.

Метою статті є ретроспективний аналіз розвитку прикладної спрямованості навчання математики в школах України. Для досягнення поставленої мети використовувалися такі теоретичні методи дослідження, як аналіз науково-методичної літератури різних історичних періодів; узагальнення, систематизація, порівняльний і системний аналіз результатів. Установлено, що на різних стадіях розвитку системи математичної освіти зберігається стійкий інтерес до проблеми зв'язку курсу математики з практикою, проте цілі і зміст предмету математики змінюється в залежності від домінувальних у суспільстві уявлень про місце і роль математики в системі національних цінностей у певний історичний період розвитку. Практичне значення даного дослідження полягає в тому, що для успішної реалізації прикладної спрямованості навчання математики дуже важливим є процес вивчення попереднього досвіду, пов'язаного з певними її аспектами. ; The purpose of the article is a retrospective analysis of the development of applied mathematics teaching in Ukrainian schools. To achieve this goal, the following theoretical research methods were used: analysis of scientific and methodological literature of different historical periods; generalization, systematization, comparative and systematic analysis of results. It is established that at different stages of development of the mathematical education system there is a persistent interest in the problem of linking the course of mathematics with practice, but the purpose and content of the subject of mathematics varies depending on the dominant in society ideas about the place and role of mathematics in the system of national values in a certain historical period of development. For example, in Cossack times, in Cossack schools, mathematics was used to produce many types of Cossack weapons and military transport. Later, in Soviet times, the development of Ukrainian mathematical education took place against the backdrop of Soviet revolutionary views. In the early twentieth century Mathematics was completely dissolved in social work. The tasks of that period were more like certain instructions for performing specific life exercises. Subsequently, in the mathematical education began to dominate the "principle of polytechnism", which involved the connection of mathematics with production and developing students' ability to use the acquired mathematical knowledge to build a communist society. But in the late 70s of the twentieth century, there was a shift in emphasis and along with the ideas began to actively develop the problem of implementing the applied orientation of the mathematics course. The recent history of the applied orientation of mathematics teaching of fundamental changes has come closer to our times. Since 2012, the content of mathematics teaching was based on a competence approach, and in 2016, Ukraine began reforming the education system and implementation of the New Ukrainian School, the key features of which are the pedagogy of partnership, readiness for technological and procedural innovations, new learning standards, connected with life. Thus, having passed the path from the era of Kievan Rus to the present day, the applied orientation of mathematics education has transformed into the process of developing a new system of mathematical education, which is organically combined with the introduction of STEM-learning and implementation of completely innovative approaches to the organization of the educational process. The practical value of this study is that the process of learning from previous experiences related to certain aspects of it is very important for the successful implementation of the applied focus of mathematics teaching.

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.

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

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.

"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"--

The 2018–2020 Ebola virus disease epidemic in Democratic Republic of the Congo (DRC) resulted in 3481 cases (probable and confirmed) and 2299 deaths. In this paper, we use a novel statistical method to analyze the individual-level incidence and hospitalization data on DRC Ebola victims. Our analysis suggests that an increase in the rate of quarantine and isolation that has shortened the infectiousness period by approximately one day during the epidemic's third and final wave was likely responsible for the eventual containment of the outbreak. The analysis further reveals that the total effective population size or the average number of individuals at risk for the disease exposure in three epidemic waves over the period of 24 months was around 16,000–a much smaller number than previously estimated and likely an evidence of at least partial protection of the population at risk through ring vaccination and contact tracing as well as adherence to strict quarantine and isolation policies.

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.