Risk-Management and Risk-Analysis-Based Decision Tools for Attacks on Electric Power

Incident data about disruptions to the electric power grid provide useful information that can be used as inputs into risk management policies in the energy sector for disruptions from a variety of origins, including terrorist attacks. This article uses data from the Disturbance Analysis Working Group (DAWG) database, which is maintained by the North American Electric Reliability Council (NERC), to look at incidents over time in the United States and Canada for the period 1990-2004. Negative binomial regression, logistic regression, and weighted least squares regression are used to gain a better understanding of how these disturbances varied over time and by season during this period, and to analyze how characteristics such as number of customers lost and outage duration are related to different characteristics of the outages. The results of the models can be used as inputs to construct various scenarios to estimate potential outcomes of electric power outages, encompassing the risks, consequences, and costs of such outages.     

Properties of systems with two exchangeable Pareto components

The life lengths of the units in a system can be modelled by a bivariate distribution. In this paper, we suppose that the joint distribution of the units is a symmetric bivariate Pareto (Lomax) distribution. For this model, we obtain basic reliability properties for series and parallel systems. J. M. Ruiz Partially Supported by Ministerio de Ciencia y Tecnologia under grant BFM2003-02947 and Fundacion Seneca under grant 00698/PI/04.     

Estimation of the mean quality-adjusted survival using a multistate model for the sojourn times

In clinical trials, it may be of interest taking into account physical and emotional well-being in addition to survival when comparing treatments. Quality-adjusted survival time has the advantage of incorporating information about both survival time and quality-of-life. In this paper, we discuss the estimation of the expected value of the quality-adjusted survival, based on multistate models for the sojourn times in health states. Semiparametric and parametric (with exponential distribution) approaches are considered. A simulation study is presented to evaluate the performance of the proposed estimator and the jackknife resampling method is used to compute bias and variance of the estimator.     

A Bayesian analysis of directional data using the projected normal distribution

This paper presents a Bayesian analysis of the projected normal distribution, which is a flexible and useful distribution for the analysis of directional data. We obtain samples from the posterior distribution using the Gibbs sampler after the introduction of suitably chosen latent variables. The procedure is illustrated using simulated data as well as a real data set previously analysed in the literature.     

Mind the Gap,Please! The Effect of Temporary Help Agencies on the Consequences of Work Accidents

Using data from a Spanish register on work-related accidents, this paper analyses the effect of contract types on two consequences of accidents: the probability of suffering a serious/fatal accident and the number of working days lost after an accident has happened. The focus is on the difference among temporary workers hired through temporary help agencies, direct temporary workers and open-ended workers. We find that workers hired through temporary help agencies are less likely to suffer serious/fatal accidents and the durations of their absences are shorter when they do, compared with workers holding either open-ended contracts or direct temporary contracts once personal, job and accident characteristics are controlled for.     

Level-dependent deforestation trajectories in the Brazilian Amazon from 1970 to 2001

This article demonstrates the importance of examining level-dependent deforestation trajectories that may be undetected within regional analyses. We examine Amazon-wide, sub-regional, settlement, and farm-level deforestation trajectories in the Brazilian Amazon and suggest factors that underlie level-dependent differences in spatial patterns and temporal magnitudes of deforestation from 1970 to 2001. At a sub-regional level, we find significant variation in frequency, magnitude, and intensity of deforestation associated with context-specific processes, including areas that have stopped deforesting, are rapidly reforesting, while at the same time increasing economic value of forest-based production. We use remote-sensing data from 1970 to 2001. For Amazon-wide and state-level analyses, we use data available from Brazil??s National Institute for Space Research. For sub-regional, settlement, and farm-lot levels, time-series Landsat images and aerial photographs and detailed field-based research are used to reconstruct the history of deforestation. Our analysis empirically demonstrates that understanding deforestation trajectories requires differentiating underlying causes at different levels of analysis and to be wary of overarching explanations and solutions that ignore differences in scale.     

A WEIGHTED RANK MEASURE OF CORRELATION

Spearman's rank correlation coefficient is not entirely suitable for measuring the correlation between two rankings in some applications because it treats all ranks equally. In 2000, Blest proposed an alternative measure of correlation that gives more importance to higher ranks but has some drawbacks. This paper proposes a weighted rank measure of correlation that weights the distance between two ranks using a linear function of those ranks, giving more importance to higher ranks than lower ones. It analyses its distribution and provides a table of critical values to test whether a given value of the coefficient is significantly different from zero. The paper also summarizes a number of applications for which the new measure is more suitable than Spearman's.     

Redesigning the Downtown of an Expansive Sunbelt City: The Phoenix Case

ABSTRACT

Non-motorized traffic safety is a major public health concern, especially in the sprawling sunbelt cities of the United States. Phoenix is ranked quite high on the number of pedestrian and cyclist crashes in North American cities. This article analyses non-motorist safety incidents in downtown Phoenix. Non-motorist safety concerns were addressed by examining crash types in order to suggest adequate safety treatments. We also demonstrated the use of a countermeasure framework for higher crash locations denominated hotspots. Our findings indicate that it is important to implement a combination of countermeasures to reduce the high number of non-motorist crashes in city centers.     

On the number of local minima for the multidimensional assignment problem

The Multidimensional Assignment Problem (MAP) is an NP-hard combinatorial optimization problem occurring in many applications, such as data association, target tracking, and resource planning. As many solution approaches to this problem rely, at least partly, on local neighborhood search algorithms, the number of local minima affects solution difficulty for these algorithms. This paper investigates the expected number of local minima in randomly generated instances of the MAP. Lower and upper bounds are developed for the expected number of local minima, E[M], in an MAP with iid standard normal coefficients. In a special case of the MAP, a closed-form expression for E[M] is obtained when costs are iid continuous random variables. These results imply that the expected number of local minima is exponential in the number of dimensions of the MAP. Our numerical experiments indicate that larger numbers of local minima have a statistically significant negative effect on the quality of solutions produced by several heuristic algorithms that involve local neighborhood search.Partially supported by the NSF grant DMI-0457473.