Application of a Regional Hurricane Wind Risk Forecasting Model for Wood-Frame Houses

Hurricane wind risk in a region changes over time due to changes in the number, type, locations, vulnerability, and value of buildings. A model was developed to quantitatively estimate changes over time in hurricane wind risk to wood-frame houses (defined in terms of potential for direct economic loss), and to estimate how different factors, such as building code changes and population growth, contribute to that change. The model, which is implemented in a simulation, produces a probability distribution of direct economic losses for each census tract in the study region at each time step in the specified time horizon. By changing parameter values and rerunning the analysis, the effects of different changes in the built environment on the hurricane risk trends can be estimated and the relative effectiveness of hypothetical mitigation strategies can be evaluated. Using a case study application for wood-frame houses in selected counties in North Carolina from 2000 to 2020, this article demonstrates how the hurricane wind risk forecasting model can be used: (1) to provide insight into the dynamics of regional hurricane wind risk-the total change in risk over time and the relative contribution of different factors to that change, and (2) to support mitigation planning. Insights from the case study include, for example, that the many factors contributing to hurricane wind risk for wood-frame houses interact in a way that is difficult to predict a priori, and that in the case study, the reduction in hurricane losses due to vulnerability changes (e.g., building code changes) is approximately equal to the increase in losses due to building inventory growth. The potential for the model to support risk communication is also discussed.     

Competing risk analysis in a large cardiovascular clinical trial: An APEX substudy

Competing risk methods are time‐to‐event analyses that account for fatal and/or nonfatal events that may potentially alter or prevent a subject from experiencing the primary endpoint. Competing risk methods may provide a more accurate and less biased estimate of the incidence of an outcome but are rarely applied in cardiology trials. APEX investigated the efficacy of extended‐duration betrixaban versus standard‐duration enoxaparin to prevent a composite of symptomatic deep‐vein thrombosis (proximal or distal), nonfatal pulmonary embolism, or venous thromboembolism (VTE)–related death in acute medically ill patients (n = 7513). The aim of the current analysis was to determine the efficacy of betrixaban vs standard‐duration enoxaparin accounting for non‐VTE–related deaths using the Fine and Gray method for competing risks. The proportion of non‐VTE–related death was similar in both the betrixaban (133, 3.6%) and enoxaparin (136, 3.7%) arms, P = .85. Both the traditional Kaplan‐Meier method and the Fine and Gray method accounting for non‐VTE–related death as a competing risk showed equal reduction of VTE events when comparing betrixaban to enoxaparin (HR/SHR = 0.65, 95% 0.42‐0.99, P = 0.046). Due to the similar proportion of non‐VTE–related deaths in both treatment arms and the use of a univariate model, the Fine and Gray method provided identical results to the traditional Cox model. Using the Fine and Gray method in addition to the traditional Cox proportional hazards method can indicate whether the presence of a competing risk, which is dependent of the outcome, altered the risk estimate.     

Distributed Computer System Capacity Planning and Capacity Loading

The availability of micro-, mini-, and super computers has complicated the laws governing the economies of scale in computers and has increased the tendency to decentralize and distribute computing power. The optimal design of such a system requires integration of computers of varying power and a strategy for capacity loading. This paper considers the problem of capacity planning and capacity loading of a distributed computer system as a hierarchy of decisions. A linear programming model is developed for the initial capacity planning problem. A loading model that accounts for variations in arrival and processing rates of the jobs in a dynamic environment is developed to support the operations.     

Concepts,Theory, and Techniques DISTRIBUTED COMPUTER SYSTEM DESIGN: A MULTICRITERIA DECISION-MAKING METHODOLOGY*

The design of distributed computer systems (DCSs) requires compromise among several conflicting objectives. For instance, high system availability conflicts with low cost which in turn conflicts with quick response time. This paper presents an approach, based on multi-criteria decision-making techniques, to arrive at a good design in this multiobjective environment. An interactive procedure is developed to support the decision making of system designers. Starting from an initial solution, the procedure presents a sequence of non-dominated vectors to designers, allowing them to explore systematically alternative possibilities on the path to a final design. The model user has control over trade-offs among different design objectives. This paper focuses on the details of the mathematical model used to provide decision support. Accordingly, a formulation of DCS design as a multicriteria decision problem is developed. The exchange search heuristic used to generate nondominated solutions also is presented. We argue that multicriteria models provide a more realistic formulation of the DCS design problem than the single-criterion models used widely in the literature. While obtaining a clear definition of design objectives (single or multiple) is an important activity, by explicitly acknowledging the trade-offs among multiple objectives in the design process, our methodology is more likely to produce a better overall design than methods addressing a single criterion in isolation.     

A Model for Resource Constrained Production and Inventory Management

We present a general model for multi-item production and inventory management problems that include a resource restriction. The decision variables in the model can take on a variety of interpretations, but will typically represent cycle times, production batch sizes, number of production runs, or order quantities for each item. We consider environments where item demand rates are approximately constant and performing an activity such as producing a batch of a product or placing an order results in the consumption of a scarceresource that is shared among the items. Some examples of shared resources include limited machine capacity, a restriction on the amount of money that can be tied up in stock, orlimited storage capacity. We focus on the case where the decision variables must be integer valued or selected from a discrete set of choices, such as when an integer number of production runs is desired for each item, or in order quantity problems where the items come in pack sizes containing more than one unit and, therefore, the order quantities must be an integer multiple of the pack sizes. We develop a heuristic and a branch and bound algorithm for solving the problem. The branch and bound algorithm includes reoptimization procedures and the heuristic to improve its performance. Computational testing indicates that the algorithms are effective for solving the general model.     

Space and Imagination

Globalisation is affecting global space in various ways. One of its most dramatic effects is the creation of large spaces of exclusion. But also the privileged spaces ought to pay the cost of adjustment: they have to create a special image of themselves which differentiates them from other places, and in order to achieve a distinct image they have to reinvent themselves. They thus become (hyperreal) ‘imagined localities’ which more and more lose the connection to the ‘lifeworld’ of people. Along with other processes of social disembedding, this creates, on the level of the individual, a sometimes backward-oriented, sometimes utopian-transcendent longing for reembedding. This is also reflected in the (metaphorical) imaginations of people about their social (group) contexts. We may find both reflexive and ‘deflexive’ ways of social imagination as the examples, which are analysed here, show.     

Special majority rules necessary and sufficient condition for quasi-transitivity with quasi-transitive individual preferences

A condition on preferences called strict Latin Square partial agreement is introduced and is shown to be necessary and sufficient for quasi-transitivity of the social weak preference relation generated by any special majority rule, under the assumption that individual preferences themselves are quasi-transitive.     

Replicated measurement error model under exact linear restrictions

We consider a replicated ultrastructural measurement error regression model where predictor variables are observed with error. It is assumed that some prior information regarding the regression coefficients is available in the form of exact linear restrictions. Three classes of estimators of regression coefficients are proposed. These estimators are shown to be consistent as well as satisfying the given restrictions. The asymptotic properties of unrestricted as well as restricted estimators are studied without imposing any distributional assumption on any random component of the model. A Monte Carlo simulations study is performed to assess the effect of sample size, replicates and non-normality on the estimators.     

Pricing Software Upgrades: The Role of Product Improvement and User Costs

The computer software industry is an extreme example of rapid new product introduction. However, many consumers are sophisticated enough to anticipate the availability of upgrades in the future. This creates the possibility that consumers might either postpone purchase or buy early on and never upgrade. In response, many software producers offer special upgrade pricing to old customers in order to mitigate the effects of strategic consumer behavior. We analyze the optimality of upgrade pricing by characterizing the relationship between magnitude of product improvement and the equilibrium pricing structure, particularly in the context of user upgrade costs. This upgrade cost (such as the cost of upgrading complementary hardware or drivers) is incurred by the user when she buys the new version but is not captured by the upgrade price for the software. Our approach is to formulate a game theoretic model where consumers can look ahead and anticipate prices and product qualities while the firm can offer special upgrade pricing. We classify upgrades as minor, moderate or large based on the primitive parameters. We find that at sufficiently large user costs, upgrade pricing is an effective tool for minor and large upgrades but not moderate upgrades. Thus, upgrade pricing is suboptimal for the firm for a middle range of product improvement. User upgrade costs have both direct and indirect effects on the pricing decision. The indirect effect arises because the upgrade cost is a critical factor in determining whether all old consumers would upgrade to a new product or not, and this further alters the product improvement threshold at which special upgrade pricing becomes optimal. Finally, we also analyze the impact of upgrade pricing on the total coverage of the market.     

Civil society organizations and participatory local governance in Pakistan: An exploratory study

This paper analyses the extent to which the civil society organizations (CSOs) have influenced the decision‐making of the local government toward the needs and priorities of citizens. In development discourse, civil society organizations hold a significant importance as they are deemed to provide holistic and new ways to ensure participatory local governance. Therefore, their role against the backdrop of their involvement in mobilizing citizens’ involvement and influencing decision‐making in Pakistan calls for further research. This paper aims to fill this gap. Using qualitative research methods, the current paper appraises the role of CSOs in mobilizing public involvement in the decision‐making process of local government institutions of Punjab, Pakistan. The paper finds that the effectiveness of CSOs is very low due to various institutional and political constraints. Motivations for CSOs seeking citizen involvement have been instrumental in nature rather than motivated by participatory principles.