This thesis presents (a) results of a field evaluation of the Traffic Speed Deflectometer (TSD) in the United States (b) deflection thresholds to classify the pavement structural condition obtained from the TSD for a small subset of the Pennsylvania secondary road network. The results of the field evaluation included: (1) repeatability of the TSD, (2) ability of the TSD to identify pavement sections with varying structural conditions, and (3) consistency between the structural number (SNeff) calculated from the TSD and SNeff calculated by the Pennsylvania Department of Transportation (PennDOT). The results showed consistent error standard deviation in the TSD measurements and that the TSD was able to identify pavement sections that varied in structural condition. Comparison of the SNeff calculated with TSD measurements, using an empirically developed equation by Rohde, with the SNeff calculated by PennDOT’s Pavement Management System based on construction history showed similar trends, although the TSD-calculated SNeff was higher. In order to develop deflection thresholds, a model that related the pavement surface condition to pavement surface age and structural condition was developed. Structural condition thresholds were then selected so that the pavement surface condition predicted from the model for a 10-year-old pavement surface fell within one of the three condition categories (Good, Fair, and Poor), to identify pavements in good, fair and poor condition. With Overall Pavement Index(OPI) characterizing the surface condition and Deflection Slope Index(DSI) characterizing the structural condition, the DSI threshold that separates structurally good from structurally fair pavements was determined as follows: (1) the OPI threshold that separates pavements with good surface condition from those with fair surface condition was obtained from the Pennsylvania Pavement Management System (PMS) and (2) the DSI thresholds were calculated using the determined OPI value and the model equation. / Master of Science / This thesis presents (a) some of the results of a field evaluation of the Traffic Speed Deflectometer (TSD) in the United States (b) deflection thresholds to classify the pavement structural condition obtained from the TSD for a small subset of the Pennsylvania secondary road network. The results of the field evaluation included: (1) repeatability of the TSD: which is the variation in repeated TSD measurements on the same section of the road, (2) ability of the TSD to identify pavement sections with varying structural conditions, and (3) consistency between the structural number (SNeff) calculated from the TSD and SNeff calculated by the Pennsylvania Department of Transportation (PennDOT). The pavement structural number is an abstract number expressing the structural strength of the pavement. The results showed that the TSD measurements were repeatable and that the TSD was able to identify pavement sections that varied in structural condition. Comparison of the SNeff calculated with TSD measurements, using an empirically developed equation by Rohde, with the SNeff calculated by PennDOT Pavement Management System based on construction history showed similar trends, although the TSD-calculated SNeff was higher. In order to develop deflection thresholds to categorize pavements in different condition: good, fair and poor, a model that related the pavement surface condition to pavement surface age and structural condition was developed. Structural condition thresholds were then selected so that the pavement surface condition predicted from the model for a 10-year-old pavement surface fell within one of the three condition categories (Good, Fair, and Poor), to identify pavements in good, fair and poor condition. With Overall Pavement Index(OPI) characterizing the surface condition and Deflection Slope Index(DSI) characterizing the structural condition, the DSI threshold that separates structurally good from structurally fair pavements was determined as follows: (1) the OPI threshold that separates pavements with good surface condition from those with fair surface condition was obtained from the Pennsylvania Pavement Management System (PMS) and (2) the DSI thresholds were calculated using the determined OPI value and the model equation.

Highway safety has been a priority for many years now. A system-wide crash analysis is a practical solution when only a limited budget is available for improving safety of highways. A systematic approach, in contrast to a hotspot analysis, allows for a widespread installation of lower-cost countermeasures across the highway network. This study focuses on the safety evaluation of a particular facility type, urban freeway off-ramps, in terms of its geometric and traffic characteristics. 144 off-ramp segments in Richmond, VA were evaluated based on the crash data available from 2011 to 2015. A statistical model was developed that relates crashes to the geometric and traffic characteristics of each off-ramp segment. A test for independence was performed to identify if a statistically significant difference existed between type of collision and severity of crashes with respect to ramp geometry and traffic control. Significant geometric and traffic variables were then identified from the model and independence test to assist in the selection of low-cost countermeasures. AADTs of both freeways and off-ramps were found to be the most statistically significant variables. Installation of advance warning signs for better traffic management near the freeway diverge area and clearing roadsides of fixed objects to reduce rear-end collisions are low-cost solutions for crashes on urban off-ramps in the study area. The results of this study demonstrate an approach to safety evaluations that could support transportation planners and agencies in identifying system-wide locations to install or apply appropriate low-cost countermeasures. / Master of Science

Evaluation of crash count data as a function of roadway characteristics allows Departments of Transportation to predict expected average crash risks in order to assist in identifying segments that could benefit from various treatments. Currently, the evaluation is performed using negative binomial regression, as a function of average annual daily traffic (AADT) and other variables. For this thesis, a crash study was carried out for the interstate, primary and secondary routes, in the Salem District of Virginia. The data used in the study included the following information obtained from Virginia Department of Transportation (VDOT) records: 2010 to 2012 crash data, 2010 to 2012 AADT, and horizontal radius of curvature (CV). Additionally, tire-pavement friction or skid resistance was measured using a continuous friction measurement, fixed-slip device called a Grip Tester. In keeping with the current practice, negative binomial regression was used to relate the crash data to the AADT, skid resistance and CV. To determine which of the variables to include in the final models, the Akaike Information Criterion (AIC) and Log-Likelihood Ratio Tests were performed. By mathematically combining the information acquired from the negative binomial regression models and the information contained in the crash counts, the parameters of each network's true average crash risks were empirically estimated using the Empirical Bayes (EB) approach. The new estimated average crash risks were then used to rank segments according to their empirically estimated crash risk and to prioritize segments according to their expected crash reduction if a friction treatment were applied. / Master of Science

Malaria is one of the leading causes of mortality and morbidity globally. Land use/land cover (LULC) change have been found to affect the transmission and distribution of malaria in other regions, but no study has attempted to examine such relationships in Nepal. Therefore, this study was conducted in Nepal to assess LULC change between 2000 and 2010, to study the spatial and temporal trend of malaria incidence rate (MIR) between 1999 and 2015, and to understand the relationship between LULC and malaria. The land cover types used for this study are forest, water bodies, agriculture, grassland, shrubland, barren areas, built-up areas and paddy areas. Change detection techniques were used to study LULC change. The temporal trend of MIR in 58 districts, and the relationship between MIR and LULC were evaluated using Poisson and negative binomial regression. Forest, water bodies, snow cover, and built-up area increased in Nepal by 28.5%, 2.96%, 55.12% and 21.19% respectively while the rest of the LULC variables decreased. MIR decreased significantly in 21 districts; however, four districts namely Pyuthan, Kaski, Rupandehi and Siraha had a significantly increasing trend of MIR. During 2001, 2002, and 2003, MIR was positively related to water bodies and paddy areas. Similarly, MIR of 2010 was negatively related to grassland. However, there was no relationship between LULC and MIR in 2000, 2011, 2012 and 2013. It may be because MIR is decreasing significantly in the country and thus the influence of LULC change is also decreasing. / MS

The focus of this paper is on cross-region R&D collaboration funded by the 5th EU Framework Programme (FP5). The objective is to measure distance, institutional, language and technological barrier effects that may hamper collaborative activities between European regions. Particular emphasis is laid on measuring discrepancies between two types of collaborative R&D activities, those generating output in terms of scientific publications and those that do not. The study area is composed of 255 NUTS-2 regions that cover the pre-2007 member states of the European Union (excluding Malta and Cyprus) as well as Norway and Switzerland. We employ a negative binomial spatial interaction model specification to address the research question, along with an eigenvector spatial filtering technique suggested by Fischer and Griffith (2008) to account for the presence of network autocorrelation in the origin-destination cooperation data. The study provides evidence that the role of geographic distance as collaborative deterrent is significantly lower if collaborations generate scientific output. Institutional barriers do not play a significant role for collaborations with scientific output. Language and technological barriers are smaller but the estimates indicate no significant discrepancies between the two types of collaborative R&D activities that are in focus of this study. (authors' abstract) / Series: Working Papers in Regional Science

The WikiLeaks Afghanistan war logs contain more than 76 000 reports about fatalities and their circumstances in the US led Afghanistan war, covering the period from January 2004 to December 2009. In this paper we use those reports to build statistical models to help us understand the mortality rates associated with specific circumstances. We choose an approach that combines Latent Dirichlet Allocation (LDA) with negative binomial based recursive partitioning. LDA is used to process the natural language information contained in each report summary. We estimate latent topics and assign each report to one of them. These topics - in addition to other variables in the data set - subsequently serve as explanatory variables for modeling the number of fatalities of the civilian population, ISAF Forces, Anti-Coalition Forces and the Afghan National Police or military as well as the combined number of fatalities. Modeling is carried out with manifest mixtures of negative binomial distributions estimated with model-based recursive partitioning. For each group of fatalities, we identify segments with different mortality rates that correspond to a small number of topics and other explanatory variables as well as their interactions. Furthermore, we carve out the similarities between segments and connect them to stories that have been covered in the media. This provides an unprecedented description of the war in Afghanistan covered by the war logs. Additionally, our approach can serve as an example as to how modern statistical methods may lead to extra insight if applied to problems of data journalism. (author's abstract) / Series: Research Report Series / Department of Statistics and Mathematics

En écologie comme dans bien d’autres domaines, les échantillons de données de comptage comprennent souvent de nombreux zéros et quelques abondances fortes. Leur distribution est particulièrement surdispersée et asymétrique. Les méthodes les plus classiques d’inférence sont souvent mal adaptées à ces distributions, à moins de disposer d’échantillons de très grande taille. Il est donc nécessaire de s’interroger sur la validité des méthodes d’inférence, et de quantifier les erreurs d’estimation pour de telles données. Ce travail de thèse a ainsi été motivé par un jeu de données d’abondance de poissons, correspondant à un échantillonnage ponctuel par pêche électrique. Ce jeu de données comprend plus de 2000 échantillons, dont chacun correspond aux abondances ponctuelles (considérées indépendantes et identiquement distribuées) d’une espèce pour une campagne de pêche donnée. Ces échantillons sont de petite taille (en général, 20 _ n _ 50) et comprennent de nombreux zéros (en tout, 80% de zéros). Les ajustements de plusieurs modèles de distribution classiques pour les données de comptage ont été comparés sur ces échantillons, et la distribution binomiale négative a été sélectionnée. Nous nous sommes donc intéressés à l’estimation des deux paramètres de cette distribution : le paramètre de moyenne m, et le paramètre de dispersion, q. Dans un premier temps, nous avons étudié les problèmes d’estimation de la dispersion. L’erreur d’estimation est d’autant plus importante que le nombre d’individus observés est faible, et l’on peut, pour une population donnée, quantifier le gain en précision résultant de l’exclusion d’échantillons comprenant très peu d’individus. Nous avons ensuite comparé plusieurs méthodes de calcul d’intervalles de confiance pour la moyenne. Les intervalles de confiance basés sur la vraisemblance du modèle binomial négatif sont, de loin, préférables à des méthodes plus classiques comme la méthode de Student. Par ailleurs, ces deux études ont révélé que certains problèmes d’estimation étaient prévisibles, à travers l’observation de statistiques simples des échantillons comme le nombre total d’individus, ou le nombre de comptages non-nuls. En conséquence, nous avons comparé la méthode d’échantillonnage à taille fixe, à une méthode séquentielle, où l’on échantillonne jusqu’à observer un nombre minimum d’individus ou un nombre minimum de comptages non-nuls. Nous avons ainsi montré que l’échantillonnage séquentiel améliore l’estimation du paramètre de dispersion mais induit un biais dans l’estimation de la moyenne ; néanmoins, il représente une amélioration des intervalles de confiance estimés pour la moyenne. Ainsi, ce travail quantifie les erreurs d’estimation de la moyenne et de la dispersion dans le cas de données de comptage surdispersées, compare certaines méthodes d’estimations, et aboutit à des recommandations pratiques en termes de méthodes d’échantillonnage et d’estimation. / In ecology as well as in other scientific areas, count samples often comprise many zeros, and few high abundances. Their distribution is particularly overdispersed, and skewed. The most classical methods of inference are often ill-adapted to these distributions, unless sample size is really large. It is thus necessary to question the validity of inference methods, and to quantify estimation errors for such data. This work has been motivated by a fish abundance dataset, corresponding to punctual sampling by electrofishing. This dataset comprises more than 2000 samples : each sample corresponds to punctual abundances (considered to be independent and identically distributed) for one species and one fishing campaign. These samples are small-sized (generally, 20 _ n _ 50) and comprise many zeros (overall, 80% of counts are zeros). The fits of various classical distribution models were compared on these samples, and the negative binomial distribution was selected. Consequently, we dealt with the estimation of the parameters of this distribution : the parameter of mean m and parameter of dispersion q. First, we studied estimation problems for the dispersion. The estimation error is higher when few individuals are observed, and the gain in precision for a population, resulting from the exclusion of samples comprising very few individuals, can be quantified. We then compared several methods of interval estimation for the mean. Confidence intervals based on negative binomial likelihood are, by far, preferable to more classical ones such as Student’s method. Besides, both studies showed that some estimation problems are predictable through simple statistics such as total number of individuals or number of non-null counts. Accordingly, we compared the fixed sample size sampling method, to a sequential method, where sampling goes on until a minimum number of individuals or positive counts have been observed. We showed that sequential sampling improves the estimation of dispersion but causes the estimation of mean to be biased ; still, it improves the estimation of confidence intervals for the mean. Hence, this work quantifies errors in the estimation of mean and dispersion in the case of overdispersed count data, compares various estimation methods, and leads to practical recommendations as for sampling and estimation methods.

The sequential-touching procedure is employed by researchers studying nonlinguistic categorization in toddlers. TouchStat 3.00 is introduced in this article as an adjunct to the sequential-touching procedure, allowing researchers to compare children’s actual touching behavior to what might be expected by chance. Advantages over the Thomas and Dahlin (2000) framework include ease of use, and fewer assumptive limitations. Improvements over TouchStat 1.00 include calculation of chance probabilities for multiple “special cases” and for immediate intercategory alternations. A new feature for calculating mean run length is also included.

Com o crescimento da população em áreas urbanas, o transporte coletivo assume um importante papel nos deslocamentos diários nas cidades brasileiras. No entanto, o grande volume de pessoas no entorno desses sistemas podem resultar em pontos críticos de segurança viária. Recentemente, as pesquisas sobre melhorias na segurança viária estão se direcionando para a investigação da relação entre o ambiente construído - isto é, padrões de uso do solo; desenho urbano; e sistemas de transporte - e acidentalidade. Porém, a relação entre os sistemas de transporte coletivo por ônibus e o ambiente construído ainda é pouco explorada. O ponto mais crítico em segurança identificado na literatura em sistemas de transporte coletivo são as estações de embarque e desembarque. Assim, esta dissertação tem como objetivo verificar a existência de relação entre elementos do ambiente construído com a ocorrência e severidade de acidentes viários no entorno de pontos de parada em sistemas prioritários para ônibus. Para isso, aplicou-se os modelos de regressão Binomial Negativo (NB), na análise de frequência de acidentes, e os modelos Logit Ordenado (OL) e Logit Multinomial (MNL), para a análise de severidade. No modelo de frequência de acidentes totais, identificou-se duas variáveis significativas e, no modelo estimado para atropelamentos, três variáveis. O modelo de severidade resultou em 19 variáveis significativas para acidentes totais e oito variáveis significativas para atropelamentos. As variáveis referentes ao envolvimento de motocicletas, automóveis, presença de interseção e uso diversificado do solo foram as mais recorrentes. O estudo possibilitou também avaliar as diferenças e vantagens entre os modelos ordenados e os não-ordenados. O modelo Logit Multinomial teve ajustes levemente melhores do que o Logit Ordenado. Ressalta-se, entretanto, que o ajuste do modelo não deve ser o único critério a se considerar na escolha de modelos para o estudo de severidade de acidentes. / Public transport has played an important role in daily commutes in Brazilian cities as population grows in urban areas. However, high volumes of pedestrians near those systems may result in critical safety issues. Recent studies on road safety improvements have sought for evidence on the relationship between built environment - land use patterns; urban design; and transportation systems - and traffic safety. Nevertheless, the relationship between traffic safety at bus priority systems and the built environment is still incipient. According to studies, the most critical safety issues related to public transport are the stations for boarding and alighting. Thus, this thesis aims to verify the relationship between built environment and incidence and severity of traffic crashes in the surroundings of bus priority systems. To do so, we applied Negative Binomial regression models (NB) for the frequency analysis, and the Ordered Logit (OL) and Multinomial Logit (MNL) models for severity analysis. NB models resulted in two significant variables for traffic crashes in general and three variables for pedestrian crashes. The severity model resulted in 19 significant variables overall crashes and eight significant variables for pedestrian crashes. Variables related to the involvement of motorcycles, automobiles, intersections and mixed land use were significant in majority of model estimations. The results allowed to evaluate the goodness of fit between ordered and unordered models. MNL had a slightly better adjustments compared to OL. Goodness of fit, however, should not be the only criterion for selecting a model to assess crash severity.

Após o fim da Segunda Guerra Mundial, teve início um processo de aumento da utilização dos automóveis nos grandes centros urbanos que modificou o desenho das cidades e o padrão de deslocamento nesses espaços. Uma das diversas consequências negativas da consolidação do automóvel como principal meio de transporte nas metrópoles foi o aumento do número de acidentes no trânsito, principalmente os que envolviam os usuários de transporte ativo – pedestres e ciclistas. A promoção dos modos de transporte não motorizados, como a bicicleta, é tida como ação complementar para reversão desse processo, porém, para tanto, é necessário melhorar a percepção de segurança sobre o modo cicloviário. A tomada de decisão por parte dos gestores do tráfego acerca das intervenções viárias que melhoram a segurança dos ciclistas carece de entendimento sobre os elementos que influenciam a ocorrência de acidentes envolvendo estes usuários. Desse modo, o trabalho desenvolvido nesta dissertação tem como objetivo a verificação da existência de relação entre os elementos urbanos construídos, os fatores socioeconômicos e outras possíveis fontes de risco com a frequência e severidade dos acidentes cicloviários na cidade de Porto Alegre O processo de investigação utilizou softwares de georreferenciamento para consolidar os dados coletados segundo as unidades de análise definidas. A frequência de acidentes foi modelada através de Modelo de Regressão Binomial Negativo e a severidade de acidentes foi modelada através de Modelo Logit Multinomial. O modelo de frequência de acidentes apresentou duas variáveis significativas. Em seguida, foi gerado um novo modelo de frequência de acidentes a partir da eliminação de possíveis fontes de discrepância dos dados. Os resultados indicaram que este segundo modelo estava melhor ajustado ao cenário estudado. O modelo de severidade de acidentes foi composto por 18 variáveis significativas. Por fim, os elementos que demonstraram maior prevalência sobre a acidentalidade de ciclistas foram a interação com automóveis, a presença de vias arteriais, a proximidade com áreas de interseção e o envolvimento de usuários vulneráveis (jovens e idosos em bicicletas) nos acidentes. / After the end of the World War II, many cities around the world have experienced an increase on car using which changed the way cities were planned and also mobility patterns. That process has generated some problems at urban areas like road accidents increasing, most of them related to active transport modes - pedestrians and cyclers. Non motorized transportation modes fomentation, for example cycling, emerges as an alternative to change this issue. However, before it happens, cyclers need to feel more safe on transit. Understanding the influence of the elements that affect cyclers's safety gives to decision makers and traffic managers a better possibility to make the right decisions on safety improvement. Thus, this thesis aims to verify the relationship between built environment, socialeconomic factors and other risk sources and frequency and severity of traffic crashes involving cyclists in Porto Alegre. By using GIS softwares, the collected data were consolidated according to the defined analysis units. Accident’s frequencies were modeled and the coefficients were estimated by using Negative Binomial Regression Model and the severity of accidents was modeled as a Multinomial Logit Model. The accident frequency model counted with two sginificant variables. Then, a new accident frequency model was estimated from the elimination of possible sources of data discrepancy. Results have shown that the second model fit better on the studied scenario. The accident severity model resulted in 18 significant variables. Finally, the elements that showed highest prevalences on cyclists safety were car interaction, presence of arterial roads, proximity to intersection areas and vulnerable cyclists users (young and old ones cycling) involvement on accidents.