Crime Scene Management. Scene Specific Methods

Хрупкость тончайшего бисквитного фарфора, из которого выполнили подсвечник, подчеркнули уникальным узором, выгравированным в старинной технике. После того как изделие отлили в специальной форме, а материал прошел двойную процедуру обжига, мастера мануфактуры вручную нанесли на поверхность изображение, рассказывающее о свадебном торжестве. Когда свеча внутри будет зажжена, рисунок станет визуально объемным.

Каждый подсвечник мануфактуры Bernardaud — единственный в своем роде. Дело не только в разных скульптурных изображениях (например, на этом изделии мастера выполнили сюжет, посвященный Рождеству), но и в старинной технике исполнения, которую в Лиможе используют с 1828 года. После того как основу из тончайшего бисквитного фарфора запекли, на ней вручную искусно вырезали картину, сравнимую с произведением искусства.

HIGHLIGHTS THE USE OF BAYESIAN STATISTICS TO GAIN INSIGHTS FROM EMPIRICAL DATA Featuring an accessible approach, Bayesian Methods for Management and Business: Pragmatic Solutions for Real Problems demonstrates how Bayesian statistics can help to provide insights into important issues facing business and management. The book draws on multidisciplinary applications and examples and utilizes the freely available software WinBUGS and R to illustrate the integration of Bayesian statistics within data-rich environments. Computational issues are discussed and integrated with coverage of linear models, sensitivity analysis, Markov Chain Monte Carlo (MCMC), and model comparison. In addition, more advanced models including hierarchal models, generalized linear models, and latent variable models are presented to further bridge the theory and application in real-world usage. Bayesian Methods for Management and Business: Pragmatic Solutions for Real Problems also features: Numerous real-world examples drawn from multiple management disciplines such as strategy, international business, accounting, and information systems An incremental skill-building presentation based on analyzing data sets with widely applicable models of increasing complexity An accessible treatment of Bayesian statistics that is integrated with a broad range of business and management issues and problems A practical problem-solving approach to illustrate how Bayesian statistics can help to provide insight into important issues facing business and management Bayesian Methods for Management and Business: Pragmatic Solutions for Real Problems is an important textbook for Bayesian statistics courses at the advanced MBA-level and also for business and management PhD candidates as a first course in methodology. In addition, the book is a useful resource for management scholars and practitioners as well as business academics and practitioners who seek to broaden their methodological skill sets.

STATISTICS IN PRACTICE A practical exploration of alternative approaches to analyzing water-related environmental issues Written by an experienced environmentalist and recognized expert in the field, this text is designed to help water resource managers and scientists to formulate, implement, and interpret more effective methods of water quality management. After presenting the basic foundation for using statistical methods in water resource management, including the use of appropriate hypothesis test procedures and some rapid calculation procedures, the author offers a range of practical problems and solutions on environmental topics that often arise, but are not generally covered. These include: * Formulating water quality standards * Determining compliance with standards * MPNs and microbiology * Water-related, human health risk modeling * Trends, impacts, concordance, and detection limits In order to promote awareness of alternative approaches to analyzing data, both frequentist and Bayesian, statistical methods are contrasted in terms of their applicability to various environmental issues. Each chapter ends with a number of set problems for which full answers are provided. The book also encourages discussion between technical staff and management before embarking on statistical studies.

An accessible introduction to the essential quantitative methods for making valuable business decisions Quantitative methods-research techniques used to analyze quantitative data-enable professionals to organize and understand numbers and, in turn, to make good decisions. Quantitative Methods: An Introduction for Business Management presents the application of quantitative mathematical modeling to decision making in a business management context and emphasizes not only the role of data in drawing conclusions, but also the pitfalls of undiscerning reliance of software packages that implement standard statistical procedures. With hands-on applications and explanations that are accessible to readers at various levels, the book successfully outlines the necessary tools to make smart and successful business decisions. Progressing from beginner to more advanced material at an easy-to-follow pace, the author utilizes motivating examples throughout to aid readers interested in decision making and also provides critical remarks, intuitive traps, and counterexamples when appropriate. The book begins with a discussion of motivations and foundations related to the topic, with introductory presentations of concepts from calculus to linear algebra. Next, the core ideas of quantitative methods are presented in chapters that explore introductory topics in probability, descriptive and inferential statistics, linear regression, and a discussion of time series that includes both classical topics and more challenging models. The author also discusses linear programming models and decision making under risk as well as less standard topics in the field such as game theory and Bayesian statistics. Finally, the book concludes with a focus on selected tools from multivariate statistics, including advanced regression models and data reduction methods such as principal component analysis, factor analysis, and cluster analysis. The book promotes the importance of an analytical approach, particularly when dealing with a complex system where multiple individuals are involved and have conflicting incentives. A related website features Microsoft Excel® workbooks and MATLAB® scripts to illustrate concepts as well as additional exercises with solutions. Quantitative Methods is an excellent book for courses on the topic at the graduate level. The book also serves as an authoritative reference and self-study guide for financial and business professionals, as well as readers looking to reinforce their analytical skills.

A high-level introduction to new technologies andmethods in the field of software engineering Recent years have witnessed rapid evolution of software engineering methodologies, and until now, there has been no single-source introduction to emerging technologies in the field. Written by a panel of experts and divided into four clear parts, Emerging Methods, Technologies, and Process Management in SoftwareEngineering covers: Software Architectures – Evolution of software composition mechanisms; compositionality in software product lines; and teaching design patterns Emerging Methods – The impact of agent-oriented software engineering in service-oriented computing; testing object-oriented software; the UML and formal methods; and modern Web application development Technologies for Software Evolution – Migrating to Web services and software evolution analysis and visualization Process Management – Empirical experimentation in software engineering and foundations of agile methods Emerging Methods, Technologies, and Process Management in Software Engineering is a one-stop resource for software engineering practitioners and professionals, and also serves as an ideal textbook for undergraduate and graduate students alike.

The main goal of this text is to introduce the systems approach to disasters management community as an alternative approach that can provide support for interdisciplinary activities involved in the management of disasters. The systems approach draws on the fields of operations research and economics to create skills in solving complex management problems. The text is organized into four parts. Part I provides an introductory discussion of disaster management including an overview of the main terms used. Part II is devoted to the introduction of systems theory, mathematical formalization and classification of methods. The material presented in this section should be of practical relevance during the process of selecting an appropriate tool for the solution of a problem. Part III is technical in nature, providing a simulation approach and a detailed description of system dynamics simulation. This section details two areas of application: flood evacuation simulation, and disaster risk assessment. Part IV ends with a chapter covering steps to improve disaster management. Finally parts of the book can be used as a tool for specialized short courses for practitioners. For example a course on 'System analysis for emergency management optimization' could be based on Chapters 3, 4 and parts of Chapter 6. Included in the book is a CD with three computer programs Vensim PLE, LINPRO, and COMPRO. Vensim PLE (Personal Learning Edition) is state-of-the-art simulation software used for the implementation of system dynamics simulation. The other two programs are: LINPRO, a linear programming optimization tool; and COMPRO, for the implementation of the multi-objective analysis tool of compromise programming.

A valuable reference for understanding operational risk Operational Risk with Excel and VBA is a practical guide that only discusses statistical methods that have been shown to work in an operational risk management context. It brings together a wide variety of statistical methods and models that have proven their worth, and contains a concise treatment of the topic. This book provides readers with clear explanations, relevant information, and comprehensive examples of statistical methods for operational risk management in the real world. Nigel Da Costa Lewis (Stamford, CT) is president and CEO of StatMetrics, a quantitative research boutique. He received his PhD from Cambridge University.