Cape Sable Seaside Sparrow Habitat Monitoring and Assessment - 2010 Final Report

For the last two decades, the Cape Sable seaside sparrow (CSSS), a federally endangered species, has been a pivot point for water management operations in the Everglades, primarily because a decline in sparrow population in the early 1990s was attributed in part to managementinduced alterations in hydrologic regimes. With a goal of understanding the response of landscape-level processes to hydrological restoration and its interaction with fire, a study intended to monitor vegetation structure and composition throughout the marl prairie landscape has been conducted since 2003 with funding from U.S. Army Corps of Engineers (USACE). In the first three years (2003-2005), vegetation structure and composition was characterized in relation to the existing hydrologic regime and fire history. During 2006-2010, vegetation was resampled to assess vegetation change within the sparrow habitat. This document summarizes the vegetation change pattern observed between the two sampling periods in sub-population A, C, E and F, emphasizing the work accomplished in FY 2010.

The European Union Foreign Policy in the Caucasus and Central Asia: The Limitations of the Opening towards the East

This article intends to study the evolution of the European Union foreign policy in the Southern Caucasus and Central Area throughout the Post-Cold War era. The aim is to analyze Brussels’ fundamental interests and limitations in the area, the strategies it has implemented in the last few years, and the extent to which the EU has been able to undermine the regional hegemons’ traditional supremacy. As will be highlighted, the Community’s chronic weaknesses, the local determination to preserve sovereignty and an increasing international geopolitical competition undermine any European aspiration to become a pre-eminent actor at the heart of the Eurasian continent in the near future.

Aquatic Faunal Survey of Camp Roberts Military Reservation and Camp San Luis Obispo National Guard Reservation, California with Emphasis on Rare Species

Final Report

Rozwój technologiczny samolotów myśliwskich, a ich taktyka w Royal Air Force oraz US Army Air Force na zachodnioeuropejskim tetrze działań operacyjnych podczas II wojny światowej w latach 1939 – 1944

Wydział Historyczny: Instytut Historii

A study at high energy-resolution and at low primary energies of the secondary emission from (100) tungsten

This work was supported by the Joint Services Electronics Program (U.S. Army, U.S. Navy, and U.S. Air Force) under Contract No. DA 28 043 AMC 00073(E).

KNOWING THE ENEMY: NAZI FOREIGN INTELLIGENCE IN WAR, HOLOCAUST, AND POSTWAR

“Knowing the Enemy: Nazi Foreign Intelligence in War, Holocaust and Postwar,” reveals the importance of ideologically-driven foreign intelligence reporting in the wartime radicalization of the Nazi dictatorship, and the continued prominence of Nazi discourses in postwar reports from German intelligence officers working with the U.S. Army and West German Federal Intelligence Service after 1945. For this project, I conducted extensive archival research in Germany and the United States, particularly in overlooked and files pertaining to the wartime activities of the Reichssicherheitshauptamt, Abwehr, Fremde Heere Ost, Auswärtiges Amt, and German General Staff, and the recently declassified intelligence files pertaining to the postwar activities of the Gehlen Organization, Bundesnachrichtendienst, and Foreign Military Studies Program. Applying the technique of close textual analysis to the underutilized intelligence reports themselves, I discovered that wartime German intelligence officials in military, civil service, and Party institutions all lent the appearance of professional objectivity to the racist and conspiratorial foreign policy beliefs held in the highest echelons of the Nazi dictatorship. The German foreign intelligence services’ often erroneous reporting on Great Britain, the Soviet Union, the United States, and international Jewry simultaneously figured in the radicalization of the regime’s military and anti-Jewish policies and served to confirm the ideological preconceptions of Hitler and his most loyal followers. After 1945, many of these same figures found employment with the Cold War West, using their “expertise” in Soviet affairs to advise the West German Government, U.S. Military, and CIA on Russian military and political matters. I chart considerable continuities in personnel and ideas from the wartime intelligence organizations into postwar West German and American intelligence institutions, as later reporting on the Soviet Union continued to reproduce the flawed wartime tropes of innate Russian military and racial inferiority.

QUT speaker identity verification system for EVALITA 2009

This document outlines the system submitted by the Speech and Audio Research Laboratory at the Queensland University of Technology (QUT) for the Speaker Identity Verication: Application task of EVALITA 2009. This submission consisted of a score-level fusion of three component systems, a joint-factor GMM system and two SVM systems using GLDS and GMM supervector kernels. Development and evaluation results are presented, demonstrating the effectiveness of this fused system approach.

Estimation of travel time on urban networks with midlink sources and sinks

This paper presents a methodology for estimation of average travel time on signalized urban networks by integrating cumulative plots and probe data. This integration aims to reduce the relative deviations in the cumulative plots due to midlink sources and sinks. During undersaturated traffic conditions, the concept of a virtual probe is introduced, and therefore, accurate travel time can be obtained when a real probe is unavailable. For oversaturated traffic conditions, only one probe per travel time estimation interval—360 s or 3% of vehicles traversing the link as a probe—has the potential to provide accurate travel time.

Property damage crash equivalency factors to solve crash frequency-severity dilemma: Case study on South Korean rural roads

Safety interventions (e.g., median barriers, photo enforcement) and road features (e.g., median type and width) can influence crash severity, crash frequency, or both. Both dimensions—crash frequency and crash severity—are needed to obtain a full accounting of road safety. Extensive literature and common sense both dictate that crashes are not created equal, with fatalities costing society more than 1,000 times the cost of property damage crashes on average. Despite this glaring disparity, the profession has not unanimously embraced or successfully defended a nonarbitrary severity weighting approach for analyzing safety data and conducting safety analyses. It is argued here that the two dimensions (frequency and severity) are made available by intelligently and reliably weighting crash frequencies and converting all crashes to property-damage-only crash equivalents (PDOEs) by using comprehensive societal unit crash costs. This approach is analogous to calculating axle load equivalents in the prediction of pavement damage: for instance, a 40,000-lb truck causes 4,025 times more stress than does a 4,000-lb car and so simply counting axles is not sufficient. Calculating PDOEs using unit crash costs is the most defensible and nonarbitrary weighting scheme, allows for the simple incorporation of severity and frequency, and leads to crash models that are sensitive to factors that affect crash severity. Moreover, using PDOEs diminishes the errors introduced by underreporting of less severe crashes—an added benefit of the PDOE analysis approach. The method is illustrated with rural road segment data from South Korea (which in practice would develop PDOEs with Korean crash cost data).

New criteria for evaluating methods of identifying hot spots

Identification of hot spots, also known as the sites with promise, black spots, accident-prone locations, or priority investigation locations, is an important and routine activity for improving the overall safety of roadway networks. Extensive literature focuses on methods for hot spot identification (HSID). A subset of this considerable literature is dedicated to conducting performance assessments of various HSID methods. A central issue in comparing HSID methods is the development and selection of quantitative and qualitative performance measures or criteria. The authors contend that currently employed HSID assessment criteria—namely false positives and false negatives—are necessary but not sufficient, and additional criteria are needed to exploit the ordinal nature of site ranking data. With the intent to equip road safety professionals and researchers with more useful tools to compare the performances of various HSID methods and to improve the level of HSID assessments, this paper proposes four quantitative HSID evaluation tests that are, to the authors’ knowledge, new and unique. These tests evaluate different aspects of HSID method performance, including reliability of results, ranking consistency, and false identification consistency and reliability. It is intended that road safety professionals apply these different evaluation tests in addition to existing tests to compare the performances of various HSID methods, and then select the most appropriate HSID method to screen road networks to identify sites that require further analysis. This work demonstrates four new criteria using 3 years of Arizona road section accident data and four commonly applied HSID methods [accident frequency ranking, accident rate ranking, accident reduction potential, and empirical Bayes (EB)]. The EB HSID method reveals itself as the superior method in most of the evaluation tests. In contrast, identifying hot spots using accident rate rankings performs the least well among the tests. The accident frequency and accident reduction potential methods perform similarly, with slight differences explained. The authors believe that the four new evaluation tests offer insight into HSID performance heretofore unavailable to analysts and researchers.

Forecasting crashes at the planning level: Simultaneous negative binomial crash model applied in Tucson, Arizona

At least two important transportation planning activities rely on planning-level crash prediction models. One is motivated by the Transportation Equity Act for the 21st Century, which requires departments of transportation and metropolitan planning organizations to consider safety explicitly in the transportation planning process. The second could arise from a need for state agencies to establish incentive programs to reduce injuries and save lives. Both applications require a forecast of safety for a future period. Planning-level crash prediction models for the Tucson, Arizona, metropolitan region are presented to demonstrate the feasibility of such models. Data were separated into fatal, injury, and property-damage crashes. To accommodate overdispersion in the data, negative binomial regression models were applied. To accommodate the simultaneity of fatality and injury crash outcomes, simultaneous estimation of the models was conducted. All models produce crash forecasts at the traffic analysis zone level. Statistically significant (p-values < 0.05) and theoretically meaningful variables for the fatal crash model included population density, persons 17 years old or younger as a percentage of the total population, and intersection density. Significant variables for the injury and property-damage crash models were population density, number of employees, intersections density, percentage of miles of principal arterial, percentage of miles of minor arterials, and percentage of miles of urban collectors. Among several conclusions it is suggested that planning-level safety models are feasible and may play a role in future planning activities. However, caution must be exercised with such models.

Effects of transportation accessibility on residential property values: Application of spatial hedonic price model in Seoul, South Korea, metropolitan area

A number of studies have focused on estimating the effects of accessibility on housing values by using the hedonic price model. In the majority of studies, estimation results have revealed that housing values increase as accessibility improves, although the magnitude of estimates has varied across studies. Adequately estimating the relationship between transportation accessibility and housing values is challenging for at least two reasons. First, the monocentric city assumption applied in location theory is no longer valid for many large or growing cities. Second, rather than being randomly distributed in space, housing values are clustered in space—often exhibiting spatial dependence. Recognizing these challenges, a study was undertaken to develop a spatial lag hedonic price model in the Seoul, South Korea, metropolitan region, which includes a measure of local accessibility as well as systemwide accessibility, in addition to other model covariates. Although the accessibility measures can be improved, the modeling results suggest that the spatial interactions of apartment sales prices occur across and within traffic analysis zones, and the sales prices for apartment communities are devalued as accessibility deteriorates. Consistent with findings in other cities, this study revealed that the distance to the central business district is still a significant determinant of sales price.

Use of expert panels in highway safety: A critique

Expert panels have been used extensively in the development of the "Highway Safety Manual" to extract research information from highway safety experts. While the panels have been used to recommend agendas for new and continuing research, their primary role has been to develop accident modification factors—quantitative relationships between highway safety and various highway safety treatments. Because the expert panels derive quantitative information in a “qualitative” environment and because their findings can have significant impacts on highway safety investment decisions, the expert panel process should be described and critiqued. This paper is the first known written description and critique of the expert panel process and is intended to serve professionals wishing to conduct such panels.

Expected safety performance of rural signalized intersections in South Korea

Understanding the expected safety performance of rural signalized intersections is critical for (a) identifying high-risk sites where the observed safety performance is substantially worse than the expected safety performance, (b) understanding influential factors associated with crashes, and (c) predicting the future performance of sites and helping plan safety-enhancing activities. These three critical activities are routinely conducted for safety management and planning purposes in jurisdictions throughout the United States and around the world. This paper aims to develop baseline expected safety performance functions of rural signalized intersections in South Korea, which to date have not yet been established or reported in the literature. Data are examined from numerous locations within South Korea for both three-legged and four-legged configurations. The safety effects of a host of operational and geometric variables on the safety performance of these sites are also examined. In addition, supplementary tables and graphs are developed for comparing the baseline safety performance of sites with various geometric and operational features. These graphs identify how various factors are associated with safety. The expected safety prediction tables offer advantages over regression prediction equations by allowing the safety manager to isolate specific features of the intersections and examine their impact on expected safety. The examination of the expected safety performance tables through illustrated examples highlights the need to correct for regression-to-the-mean effects, emphasizes the negative impacts of multicollinearity, shows why multivariate models do not translate well to accident modification factors, and illuminates the need to examine road safety carefully and methodically. Caveats are provided on the use of the safety performance prediction graphs developed in this paper.

Development of accident prediction models for rural highway intersections

A study was done to develop macrolevel crash prediction models that can be used to understand and identify effective countermeasures for improving signalized highway intersections and multilane stop-controlled highway intersections in rural areas. Poisson and negative binomial regression models were fit to intersection crash data from Georgia, California, and Michigan. To assess the suitability of the models, several goodness-of-fit measures were computed. The statistical models were then used to shed light on the relationships between crash occurrence and traffic and geometric features of the rural signalized intersections. The results revealed that traffic flow variables significantly affected the overall safety performance of the intersections regardless of intersection type and that the geometric features of intersections varied across intersection type and also influenced crash type.