Community Trails in Community Context: GIS Analysis of Associations between Trail and Neighborhood Characteristics

This research examines the site and situation characteristics of community trails as landscapes promoting physical activity. Trail segment and neighborhood characteristics for six trails in urban, suburban, and exurban towns in northeastern Massachusetts were assessed from primary Global Positioning System (GPS) data and from secondary Census and land use data integrated in a geographic information system (GIS). Correlations between neighborhood street and housing density, land use mix, and sociodemographic characteristics and trail segment characteristics and amenities measure the degree to which trail segment attributes are associated with the surrounding neighborhood characteristics.

Production Streamlining through Design, Implementation, and Analysis of Lean Manufacturing Methods

Through the correct implementation of lean manufacturing methods, a company can greatly improve their business. Over a period of three months at TTM Technologies, I utilized my knowledge to fix existing problems ans streamline production. In addition, other trouble areas in their production process were discovered and proper lean methods were used to address them. TTM Technologies saw many changed in the right direction over this time period.

From Books to the Web: A Comparative Analysis of Holocaust Denial in the Internet Age

An analysis of print Holocaust denial literature as it compares to internet Holocaust denial, with a focus on how the transition from print literature to the internet has affected Holocaust denial.

A Three Dimensional Analysis of Extraoral Traction Appliances

Submitted in partial fulfillment of the requirements for a Certificate in Orthodontics, Dept. of Orthodontics, University of Connecticut Health Center, 1978

Penalty Enhancement for Hate Crimes: An Economic Analysis

The issue of bias-motivated crimes has attracted consderable attention in recent years. In this paper, we develop an economic framework to analyze penalty enhancements for bias-motivated crimes. We extend the standard model by introducing two different groups of potential victims of crime, and assume that a potential offender's benefits from a crime depend on the group to which the victim belongs. We begin with the assumption that the harm to an individual victim from a bias-motivated crime is identical to that from an equivalent non-hate crime. Nonetheless, we derive the result that a pattern of crimes disproportionately targeting an identifiable group leads to greater social harm. This conclusion follows both from a model where disparities in groups' victimization probabilities lead to social losses due to fairness concerns, as well as a model where potential victims have the opportunity to undertake socially costly victimization avoidance activities. In particular, penalty enhancements can reduce the incentives for avoidance activity, and thereby protect the networks of profitable interactions that link members of different groups. We also argue that those groups that are covered by hate crime statutes tend to be those whose characteristics make it especially likely that penalty enhancement is socially optimal. Finally, we consider a number of other issues related to hate crimes, including teh choice of sanctions from behind a Rawlsian 'veil of ignorance' concerning group identity.

Direct and Indirect Measures of Capacity Utilization: A Nonparametric Analysis of U.S. Manufacturing

We measure the capacity output of a firm as the maximum amount producible by a firm given a specific quantity of the quasi-fixed input and an overall expenditure constraint for its choice of variable inputs. We compute this indirect capacity utilization measure for the total manufacturing sector in the US as well as for a number of disaggregated industries, for the period 1970-2001. We find considerable variation in capacity utilization rates both across industries and over years within industries. Our results suggest that the expenditure constraint was binding, especially in periods of high interest rates.

Empirical Analysis of Credit Risk Regime Switching and Temporal Conditional Default Correlation in Credit Default Swap Valuation: The Market liquidity effect

In this paper, we extend the debate concerning Credit Default Swap valuation to include time varying correlation and co-variances. Traditional multi-variate techniques treat the correlations between covariates as constant over time; however, this view is not supported by the data. Secondly, since financial data does not follow a normal distribution because of its heavy tails, modeling the data using a Generalized Linear model (GLM) incorporating copulas emerge as a more robust technique over traditional approaches. This paper also includes an empirical analysis of the regime switching dynamics of credit risk in the presence of liquidity by following the general practice of assuming that credit and market risk follow a Markov process. The study was based on Credit Default Swap data obtained from Bloomberg that spanned the period January 1st 2004 to August 08th 2006. The empirical examination of the regime switching tendencies provided quantitative support to the anecdotal view that liquidity decreases as credit quality deteriorates. The analysis also examined the joint probability distribution of the credit risk determinants across credit quality through the use of a copula function which disaggregates the behavior embedded in the marginal gamma distributions, so as to isolate the level of dependence which is captured in the copula function. The results suggest that the time varying joint correlation matrix performed far superior as compared to the constant correlation matrix; the centerpiece of linear regression models.