bluuebunny/crossref_metadata_2025_split huggingface dataset:
Operational Risk Development
Authors: Davies Brandon J. 
Published: September 2014

Abstract
This paper looks at the application of operational risk ‘models’ under Pillar 1 of the Basel II regulatory framework. It looks both at the conceptual problems underlying the definition of operational risk and the practical issues of data collection associated with modeling operational risk events. It also looks at operational value at risk (Op. VaR) as a measure of operational risk and the issues associated with implementing such a measure; it contrasts Op. VaR with an expected shortfall approach as used in the insurance industry. When managing operational risk, it is proposed that a process control approach operational risk management has many advantages especially when implemented through conformance to ISO and similar standards.
Use of Decision Support Techniques for Information System Risk Management
Authors: Buckshaw Donald L. 
Published: September 2014

AbstractIdentifying and understanding security risks for information system design or evaluation is very challenging. Making decisions about accepting or mitigating these risks through a rational, traceable, and understandable process is even harder. Quantitative risk analysis techniques can help stakeholders understand and communicate risk‐informed design decisions even when the stakeholders have conflicting objectives. Quantitative risk analysis also helps stakeholders understand security, cost, and functionality trade‐off decisions in repeatable process. This paper discusses the roles of stakeholders in risk analysis, the advantages and disadvantages of quantitative risk analysis, basic cyber risk decision support concepts and processes, and the mathematical definitions of risk for information systems. This paper recommends the use of properly constructed quantitative risk analysis models and discourages the use of semiquantitative risk analysis models.
Game Theoretic Methods
Authors: Bier Vicki M. 
Published: September 2014

Abstract
Protecting homeland security against intentional attacks on homeland security is fundamentally different from protecting against accidents or acts of nature. In particular, an intelligent and adaptable adversary may adopt a different offensive strategy in response to our protective security measures, in order to circumvent or disable them. Game theory provides a way of taking this into account analytically. Thus, security can benefit from game‐theoretic methods. This article discusses approaches for applying game theory to the problem of defending systems against attack. The results yield insights into the nature of optimal defensive investments.
Privacy Protection in an Era of Data Mining and Record Keeping
Authors: Karr Alan F. 
Published: September 2014

AbstractThe computerization of the world is changing the nature and degree of privacy protection, and even the very definition of privacy. The topic is rife with compromises, inconsistencies and paradoxes. Concern about privacy engenders “classical” trade‐offs between individual risk and social benefit, which are understood in only some contexts. Corporations and educational institutions hold immense amounts of information about individuals, most of which was provided willingly, but is subject to misuse. People fear identity theft, but employ their usernames as computer passwords. This article lays out a way to think about the issues, and summarizes history, current concerns, and possible futures.
Coding: Statistical Data Masking Techniques
Authors: Slavkovic Aleksandra B. 
Published: September 2014

Abstract
Coding broadly refers to altering the data in some way. In computer science literature, it may refer to encryption, compression, or error correction. These are relevant for cryptography and cryptanalysis, and for data privacy and homeland security. In statistical confidentiality literature, coding encompasses various data‐masking techniques. These techniques generally introduce bias and variance to data. The question is how much and what kind of bias and variance is introduced and how this influences the utility of data‐mining algorithms and precision of identification, that is the false positive error rate. This article gives a brief overview of statistical disclosure limitation techniques for data masking, pointing out the likelihood of their use and potential impacts for data privacy.
Scenario‐Based Risk Management and Simulation Optimization
Authors: Better Marco , Glover Fred 
Published: September 2014

AbstractTraditional optimization approaches for handling uncertainty and risk typically require severe assumptions that are often not satisfied in complex practical settings. In an effort to overcome such limitations, several methods have been developed to handle uncertainty when the data and associated real‐world parameters do not behave according to classical assumptions. Two of the leading and most widely used examples are scenario optimization and robust optimization, both of which seek high‐quality decisions that are feasible for all scenarios. However, both of these approaches likewise succumb to deficiencies encountered by classical methods, by exhibiting serious limitations in terms of the complexity and size of the models they can handle. Simulation optimization overcomes these limitations, and its flexibility and ease of use has contributed to its popularity as a preferred optimization approach to risk‐management applications.
Uncertainty Analysis and Dependence Modeling
Authors: Cooke Roger M. , Kurowicka Dorota 
Published: September 2014

AbstractUncertainty analysis involves quantifying (joint) uncertainty on the inputs of models, propagating this through the mathematical model, and interpreting the results. We sketch the emergence of uncertainty analysis, give recent examples, and briefly illustrate current active issues. Depencence modeling and probability inversion are high on the research agenda.
Engineered Nanomaterials
Authors: Maynard Andrew D. 
Published: September 2014

Abstract
Engineered nanomaterials are a product of nanotechnology, and have an intentionally produced structure at the scale of approximately 1–100 nm. These materials demonstrate properties that depend on a carefully controlled and implemented nanostructure; the close dependency between this structure and material functionality challenges how quantitative risk assessment is applied to some engineered nanomaterials. For instance, nanostructure‐related functionality may lead to health risks that depend on properties such as particle size, surface area, and shape. There is evidence that the size, surface area, surface chemistry, and possibly shape of some engineered nanomaterials may determine transport and response within the body. Quantitative risk assessment of these materials will depend on determining when they behave differently from conventional materials, what properties are associated with their potential impact, and how exposure, dose and response can be most appropriately evaluated. At present, insufficient data and incomplete methodologies are available for conducting comprehensive quantitative risk assessments on many emerging nanomaterials. Until more comprehensive information is available, it will be necessary to identify those nanomaterials that present unique challenges, and to use existing information together with expert extrapolation as a basis for qualitative and semi‐quantitative risk assessment.
Homeland Security and Transportation Risk
Authors: Steffey Duane L. 
Published: September 2014

Abstract
The coordinated hijackings and deliberate crashes of airplanes into the World Trade Center in New York and the Pentagon in Washington, DC, on September 11, 2001, dramatically heightened both the perception and the reality of the threat terrorism poses to public transportation systems. Governments of countries that perceive an elevated level of threat are investing considerable resources to implement comprehensive programs to enhance security in all key modes of transportation, including aviation, maritime traffic, highways, and mass transit.
A systems‐based approach to managing such risks involves the assessment of threats, vulnerabilities, and consequences. Assessments are conducted to identify and evaluate potential threats, recognize weaknesses that may be exploited by identified threats, suggest countermeasures to address those weaknesses, and determine which structures or processes are relatively more important to protect from attack. The characterization of security risk is completed through qualitative or quantitative analysis of the consequences associated with the partial or total loss of critical transportation assets because of intentional harmful attacks. Formal methodologies for assessing and managing risks to transportation security provide a conceptual structure and practical tools for allocating resources in cost‐effective ways to improve public safety.
Environmental Justice, Statistics in
Authors: Waller Lance A. 
Published: September 2014

Abstract
We briefly review the historical, legal, and regulatory background of environmental justice assessments, paying particular attention to the role of statistical techniques in such assessments. We stress the difference between “disparate impact” and intentional discrimination and the role of statistical comparisons as defined in the associated regulatory statutes. We contrast two general approaches, the first comparing demographic proportions within exposure categories and the second comparing exposure (or exposure surrogate) distributions between demographic categories.
Environmental Mutagenesis, Statistics in
Authors: Piegorsch Walter W. 
Published: September 2014

AbstractIn experiments studying the effects of environmental stimuli on biological organisms, major endpoints of interest include damage to genetic components such as deoxyribonucleic acid (DNA). DNA damage as represented by mutagenic insult(s) is perhaps the most varied of any toxicological endpoint, since the potential mechanisms of genetic damage are so numerous. Statistical issues associated with mutagenicity experiments include construction of models to characterize dose–response and other features of genetic damage, sample size determinations/study design, and the selection of statistical approaches associated with these models and methods; these are briefly discussed
Environmental Teratogenesis, Statistics in
Authors: Chen James J. 
Published: September 2014

Abstract
Teratology is the study of adverse effects of environmental agents on the developing system. The major source of information for studying potential teratogenic (developmental) effects of chemicals on humans is generally the animal dose–response experiments. Quantitative risk assessment involves an assessment of the relationship between exposure and adverse health effects to derive an allowable exposure level. Acceptable levels of human exposure are derived by dividing the lower confidence limit benchmark dose by the product of several uncertainty factors. This article describes the statistical models and benchmark approach for quantitative risk assessment of developmental effects. The benchmark dose method involves selection of a dose–response function to fit animal experimental data. The benchmark dose and its lower confidence limit are then estimated from the fitted dose–response model. The dose–response function for continuous response data is modeled using the litter‐based analysis. The dose–response function for dichotomous response data is modeled using beta binomial.
Extreme Event Risk
Authors: Brillinger David R. 
Published: September 2014

Abstract
“Extreme event” is a vague concept with a variety of formal definitions based on specific cases and contexts. Particular extreme events include, great earthquakes, floods, droughts, nuclear meltdowns, space shuttle losses, deaths, giant sea waves, stock crashes, landslides, storms, hurricanes, tornadoes, wildfires, and consequences of any of the preceding. The event of interest might be caused by man or by nature. They may occur in time or space. The size might be measured in deaths or costs. The study of extreme event situations has led to important research results and management methods. The specific concern of the entry is quantitative formulation of the problem.
Fate and Transport Models: Details
Authors: Pistocchi Alberto 
Published: September 2014

Abstract
In the following section we provide general background information about mathematical descriptions of phase partitioning of chemicals, mechanisms of their transfer between and within environmental media, and degradation, also introducing the most common mathematical representations of the processes described. Eventually, such representations are combined in a general equation used for fate and transport modeling: the advection–dispersion–reaction equation (ADRE). The processes described by the ADRE are very general; depending on the specific medium (soil, water, air) where they take place, the different terms of the equation are represented differently.
In a subsequent section, we describe specific cases of the ADRE in relation to surface water, soil/groundwater, and air, which are the domains where it is normally solved. For each case, we introduce some examples of publicly available computing codes that solve the equation.
In the last section, we introduce multimedia/multispecies fate and transport of chemicals using linear box models.
Gene‐Environment Interaction: Overview
Authors: Umbach David M. 
Published: September 2014

Abstract
Current biomedical research is guided by the idea that genetic makeup and environmental exposures, broadly construed, work together through time to cause human disease. This idea is the broad essence of gene–environment interaction. The detailed assessment of gene–environment interaction using epidemiologic data involves issues such as how one defines such interactions in a statistical sense and how one might infer that interactions seen in observational studies reflect causal relationships. That gene–environment interaction is hard to detect and estimate, requiring much larger sample sizes than main effects, has prompted research into novel approaches to increase power and precision through both methods of data analysis methods and study designs. Efforts to make studies robust against hidden genetic population structure have prompted other innovations in study design. The needs of biomedical science continue to stimulate research toward improved methods for studying gene–environment interaction.
Global Warming, Statistics for
Authors: Tebaldi Claudia , Mastrandrea Michael D. , Smith Richard L. 
Published: September 2014

AbstractGlobal warming is a worldwide environmental, social, and economic challenge, with far‐reaching implications for human welfare and the health of natural systems. While this qualitative assessment is generally agreed upon by a large share of scientific, policy‐making, and stakeholder communities, a quantification of the risks associated with global warming is far from straightforward. There exist considerable uncertainties, including limits to predicting future changes in the drivers of greenhouse gas emissions (population, economic growth, etc.), incomplete scientific understanding of the response of the climate system to those emissions, and components of intrinsic randomness or unpredictability in the processes involved. From the size of the changes to be expected to their timing and from the significance of impacts to the costs of adaptation and mitigation strategies, every link of the chain from emissions, to impacts, to the effects of policy is affected by uncertainties. This article characterizes the main sources of uncertainty in modeling of the climate system and in the development of scenarios for future emissions, as well as the most rigorous efforts currently documented in the peer reviewed literature to quantify uncertainty and incorporate it into risk analysis.
Hotspot Geoinformatics
Authors: Patil Ganapathi P. , Joshi Sharadchandra W. , Rathbun Stephen L. 
Published: September 2014

AbstractGovernment agencies continue to require meaningful summaries of georeferenced data to support policies and decisions involving risk maps, geographic targets, and resource allocations. So also the public with initiatives of digital governance, enabling transparency, efficiency, and efficacy in the risk assessment and management.This article briefly introduces hotspot geoinformatics for hotspot detection and prioritization, and provides examples of societal importance involving environmental risk.
Potency Estimation
Authors: Bailer A. John , Piegorsch Walter W. 
Published: September 2014

AbstractA common goal in environmental risk assessment is description of the hazardous agent's toxic or otherwise‐harmful effects, often for comparison with others agents of related structure or exposure. Summary measures are most useful in this regard, as these describe the potency of an agent or some product of an agent on the organism or system under study. A number of quantitative summaries can be used to measure or define potency, each based on a slightly different feature of the observed dose–response. We consider a few of these in this article.
Environmental Remediation, Statistics in
Authors: Stein Alfred , Kerle Norman 
Published: September 2014

Abstract

This entry gives an overview of environmental remediation, with an emphasis on soil issues. The concept of risk is defined, followed by different ways of modeling (deterministic, probabilistic, and hybrid). A distinction is made between
in situ
and
ex situ
remediation and issues of spatial statistics are included. The issue is illustrated with an example on an environmental cost model.
Spatial Risk Assessment
Authors: Lawson Andrew B. 
Published: September 2014

Abstract
The spatial analysis of risk is defined as the analysis of georeferenced data pertaining to some adverse outcome. Approaches used for this usually lie in the area of clustering methodology either as hypothesis tests or modeling of risk itself. For fixed spatial sites, and clustering around these, there are well‐developed methods related to distance and direction that can be used. When a focus site is not available, more sophisticated models or scan tests must be employed.
Spatiotemporal Risk Analysis
Authors: Lawson Andrew B. 
Published: September 2014

Abstract
This article focuses on the issues related to risk assessment when the domain consists of space and time. Spatiotemporal risk assessment could involve separate analyses of risk in a geographical domain, risk in a temporal window, or the interaction of space and time. Often the focus will be on magnitude and frequency of an outcome but this will have a spatial and temporal expression. The link with surveillance for adverse outcomes is made, and health risk is a focus of the review, although the concepts illustrated can be applied in other areas such as financial or industrial risk analysis.
Public Participation
Authors: Bayley Clare L. 
Published: September 2014

AbstractIncreasingly, governments and public bodies are involving stakeholders and the general public to a far greater extent in decision‐making processes, particularly relating to the environment in which they live. A strong motivation for the uptake of participatory processes is a need for transparency and accountability in decision making. Additionally, agreements such as the Aarhus convention granting the public rights regarding access to information, public participation, and access to justice in governmental decision making on matters concerning the environment have led to an increase in stakeholder participation. Many participatory tools and strategies have been developed to involve the public and stakeholders in societal decisions, including workshops, citizen juries, focus groups, electronic forums, web polling, and other means of consultation. In this article, the objectives of public participation are discussed and the merits of a number of participatory processes at meeting these objectives are evaluated.
Risk Attitude
Authors: Munier Bertrand R. , Tapiero Charles 
Published: September 2014

AbstractThe concepts and analytical expressions of absolute and relative risk aversion, in both weak and strong senses, are explained and discussed. Examples are computed. The extension to multivariate risk aversion, the problem of background risk, and the relationship between mean‐variance and expected utility (EU) models are dealt with in an EU framework. Finally, new developments in relation to the question of generalized risk aversion in a non‐EU framework and to the measurement of risk aversion concepts in financial analysis are discussed.
Ethical Issues in Using Statistics, Statistical Methods, and Statistical Sources in Work Related to Homeland Security
Authors: Seltzer William , Anderson Margo 
Published: September 2014

AbstractThe article emphasizes that there are distinctive ethical, as well as scientific and legal, issues involved in deploying statistical methods and data for homeland security, even as we note the overlaps between science and ethics on the one hand and law and ethics on the other hand. The article discusses (a) ethical challenges that arise from using inappropriate methods, whether they are “quick‐fix” shortcuts and approximations or elaborate models; (b) the ethical imperative to avoid causing harm to innocent people embodied in the need to respect the principle of statistical confidentiality and the need to take into account the intermediary and long‐term substantive objectives of any risk assessment; and (c) the common ethical failure involved in using only the technical indicator, “risk of disclosure”, rather than its ethically informed counterpart “the harm arising, given the disclosure”, in the assessment of the efficacy alternative approaches. The special ethical challenges that arise when data systems are used to target individuals or population subgroups based on racial, ethnic, religious, or similar attributes are also discussed. The article concludes by stressing the importance of establishing a mechanism for appropriate ethical review and oversight lest, in our untempered zeal for the value of the data and methods we employ or the important objectives of work on homeland security, we become complicit in harming innocent individuals or vulnerable population subgroups.
Expert Elicitation for Risk Assessment
Authors: Wiedlea Andrew C.K. 
Published: September 2014

AbstractExpert elicitation—the use of structured, calibrated questions to gather qualitative risk information—is a key risk assessment tool. Particularly when there does not exist sufficient observed data to estimate the nature of a risk process, or in cases when a system risk is generated by the interactions of a complex set of component interactions, qualitative information gathered from subject matter experts may be the best, if not the only, source of relevant information. Ensuring that information gathered from subject matter experts is relatively free from bias and probability logic inconsistency is a key interest of elicitation research.
Scientific Uncertainty in Social Debates Around Risk
Authors: Driedger S. Michelle 
Published: September 2014

Abstract
Quantitative risk assessments based on scientific understandings of a risk issue are often used in managing risk controversies in a policy domain. However, in several areas of risk, particularly in an environment and health domain, managing uncertainties in scientific knowledge is difficult and complex. It is important to understand how the production and use of scientific evidence can be understood as a social process and how scientific evidence may be used in regulatory decision making.