"Vision is regarded as the most noble of the senses, and the loss of eyesight as the ultimate physical loss" -- Juhani Pallasmaa To see or not to see?   As a child growing up in the Dominican Republic, my vision was blurred by a perception strongly held by my elders.  A perception that have been nurtured and carried out for many centuries.  This perception have kept me away from the 'reality', limiting my vision to what existed in the other side of the borderline.   As my eyes were blindfolded, my ears opened to received words that would slowly construct my own imaginary world.  A particular world, in which hearing was dominant over my other senses.  As one would imagine that a world could painful while living in 'darkness', what was actually painful was living with the existence of the unknown, of the invisible In April 2011, I decided to visit the imaginary line that runs along Dominican Republic and Haiti.  My experience was truly remarkable.  At that present moment, I had a very exciting encounter with a new sense of reality.  As I approached to an unfinished construction, I climbed to a metal stair reaching an altitude of nearly twenty feet.  My eyes witnessed what was hidden for nearly thirty years of my existence. Through the wavy transparent mirage caused by the refraction of the blistering sun, I was able to see the neighboring country of Haiti for the first time.  Along the Massacre River, there was an element that immediately captivated by curiosity.  It was  a thin, blue metal gate located right in the middle of a concrete bridge that expanded east and west uniting the border towns of Dajabon and Ounaminthe. To my eyes, this gate was a visible and an invisible boundary -- A line, a remarkably powerful, and fundamental element in Architecture -- which was strongly visible, by dividing and marking its presence demarcating territories.  Yet, was also transparent uniting two cultures during the market days. My thesis unfolds in the quest of what can exist by the emergence of the visible and the invisible -- what I envisioned while standing at the site, a Binational Market along the imaginary line. / Master of Architecture

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Freeway work zones with lane closures can adversely affect mobility, safety, and sustainability. Capacity drop phenomena near work zone areas can further decrease work zone capacity and exacerbate traffic congestion. To mitigate the negative impacts caused by freeway work zones, many variable speed limits (VSL) control methods have been proposed to proactively regulate the traffic flow. However, a simple yet robust VSL controller that considers the nonlinearity induced by the associated capacity drop is still needed. Also, most existing studies of VSL control neglected the impacts of traffic sensor failures that commonly occur in transportation systems. Large deviations of traffic measurements caused by sensor faults can greatly affect the reliability of VSL controllers. To address the aforementioned challenges, this research proposes a fault-tolerant VSL controller for a freeway work zone with consideration of sensor faults. A traffic flow model was developed to understand and describe the traffic dynamics near work zone areas. Then a VSL controller based on sliding mode control was designed to generate dynamic speed limits in real time using traffic measurements. To achieve VSL control fault tolerance, analytical redundancy was exploited to develop an observer-based method and an interacting multiple model with a pseudo-model set (IMMP) based method for permanent and recurrent sensor faults respectively. The proposed system was evaluated under realistic freeway work zone conditions using the traffic simulator SUMO. This research contributes to the body of knowledge by developing fault-tolerant VSL control for freeway work zones with reliable performance under permanent and recurrent sensor faults. With reliable sensor fault diagnosis, the fault-tolerant VSL controller can consistently reduce travel time, safety risks, emissions, and fuel consumption. Therefore, with a growing number of work zones due to aging road infrastructure and increasing demand, the proposed system offers broader impacts through congestion mitigation and consistent improvements in mobility, safety, and sustainability near work zones. / Thesis / Doctor of Philosophy (PhD) / Freeway work zones can increase congestion with higher travel time, safety risk, emissions and fuel consumption. This research aims to improve traffic conditions near work zones using a variable speed limits control system. By exploiting redundant traffic information, a variable speed limit control system that is insensitive to traffic sensor failures is presented. The proposed system was evaluated under realistic freeway work zone conditions in a simulation environment. The results show that the proposed system can reliably detect sensor failures and consistently provide improvements in mobility, safety and sustainability despite the presence of traffic sensor failures.

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Syftet med denna rapport är att undersöka effektiviteten av de inbyggda verktygen för att minska skärmtid i Apples iOS för studenter. Frågeställningen vi har undersökt är “Hur förändras studenters mobilvanor genom att låta Apples Skärmtid låsa appar?”. Vi har genomfört en undersökning där våra deltagare har fått sätta egna begränsningar på sin totala appanvändning under en vecka. Därefter har vi samlat in data med enkäter och intervjuer kring deras appanvändning. Resultatet har visat på att många studenter vill minska sin skärmtid, speciellt inom sociala medier, men verktygen vi undersökt  är inte effektiva nog för att ändra dessa vanor. Många av deltagarna låste upp sina appar trots att de ville minska sin skärmtid. Deltagarna menade på att det finns bra och dålig skärmtid, där produktivitet och kommunikation är bra och sociala medier är dåligt. Därför ville många av deltagarna hellre bara begränsa sociala medier istället för att begränsa all skärmtid. / The purpose of this report is to examine the effectiveness of the built-in tool for reducing screen time in Apple’s iOS on students. The problem statement we’ve looked at is “How are students phone habits affected by letting Apple’s Screen Time lock apps?”. We have carried out an experiment where participants set limits to their own total screen time during one week. Afterwards, we have collected data with surveys and interviews examining their app usage. The results show that many students want to lower their screen time, especially within social media, however, the tools we looked at are not effective to change these habits. Many of the participants unlocked their apps despite wanting to decrease their screen time. Many participants expressed that there is good and bad screen time, where productivity and communication is good, and social media is bad. Therefore, many participants said they would rather only limit social media instead of limiting all their screen time.

This is a discourse analysis of three WebPages which topic is sexual information. Our purpose is to examine the WebPages RFSL (The Swedish Federation for Lesbian, Gay, Bisexual and Transgender Rights), RFSU (The Swedish Association for Sexuality Education) and UMO (Reception for young people) from a queer theoretical perspective and illustrate how they discuss the subjects’ gender, sexual preference and sexual limits. Our questions are; what information about gender, sexual preference and sexual limits are presented on the WebPages RFSU, RFSL and UMO, and what similarities and differences can be identified and how can these be analyzed from a queer perspective? Our material was collected from the three WebPages and categorized according to three topics of interest; gender, sexual preference and sexual limits. Our analyses are based on queer theory and former research in the field. We found a number of topics and interesting information which were categorized under new headlines. Our conclusion is that the topics mentioned on the WebPages are in most of the cases homogenous. On the theme gender we found that the categories man and woman were prominent. In the discussion about gender we found that all three WebPages only wrote about hetero-, homo- and bisexuality. None of the WebPages write about subjects whom concern the theme sexual limits. All WebPages write about hetero norms and are questioning them.

Recent research at UCF into defining surrogate measures for identifying crash prone conditions on freeways has led to the introduction of several statistical models which can flag such conditions with a good degree of accuracy. Outputs from these models have the potential to be used as real-time safety measures on freeways. They may also act as the basis for the evaluation of several intervention strategies that might help in the mitigation of risk of crashes. Ramp Metering and Variable Speed Limits are two approaches which have the potential of becoming effective implementation strategies for improving the safety conditions on congested freeways. This research evaluates both these strategies in different configurations and attempts to quantify their effect on risk of crash on a 9-mile section of Interstate-4 in the Orlando metropolitan region. The section consists of 17 Loop Detector stations, 11 On-ramps and 10 off-ramps. PARAMICS micro-simulation is used as the tool for modeling the freeway section. The simulated network is calibrated and validated for 5 minute average flows and speeds using loop detector data. Feedback Ramp Metering algorithm, ALINEA, is used for controlling access from up to 7 on-ramps. Variable Speed Limits are implemented based on real-time speed conditions prevailing in the whole 9-mile section. Both these strategies are tested separately as well as collectively to determine the individual effects of all the parameters involved. The results have been used to formulate and recommend the best possible strategy for minimizing the risk of crashes on the corridor. The study concluded that Ramp Metering improves the conditions on the freeway in terms of safety by decreasing variance in speeds and decreasing average occupancy. A safety benefit index was developed for quantifying the reduction in crash risk and it indicated that an optimal implementation strategy might produce benefits of up to 55%. The condition on the freeway section improved with increase in the number of metered ramps. It was also observed that shorter signal cycles for metered ramps were more suitable for metering multiple ramps. Ramp Metering at multiple locations also decreased the segment wide travel-times by 5% and was even able to offset the delays incurred by drivers at the metered on-ramps. Variable Speed Limits (VSL) were individually not as effective as ramp metering but when implemented along with ramp metering, they were found to further improve the safety on the freeway section under consideration. By means of a detailed experimental design it was observed that the best strategy for introducing speed limit changes was to raise the speed limits downstream of the location of interest by 5 mph and not affecting the speed limits upstream. A coordinated strategy - involving simultaneous application of VSL and Ramp Metering - provided safety benefits of up to 56 % for the study section according to the safety benefit index. It also improved the average speeds on the network besides decreasing the overall network travel time by as much as 21%.

Traffic safety has become the first concern in the transportation area. Crashes have cause extensive human and economic losses. With the objective of reducing crash occurrence and alleviating crash injury severity, major efforts have been dedicated to reveal the hazardous factors that affect crash occurrence at both the aggregate (targeting crash frequency per segment, intersection, etc.,) and disaggregate levels (analyzing each crash event). The aggregate traffic safety studies, mainly developing safety performance functions (SPFs), are being conducted for the purpose of unveiling crash contributing factors for the interest locations. Results of the aggregate traffic safety studies can be used to identify crash hot spots, calculate crash modification factors (CMF), and improve geometric characteristics. Aggregate analyses mainly focus on discovering the hazardous factors that are related to the frequency of total crashes, of specific crash type, or of each crash severity level. While disaggregate studies benefit from the reliable surveillance systems which provide detailed real-time traffic and weather data. This information could help in capturing microlevel influences of the hazardous factors which might lead to a crash. The disaggregate traffic safety models, also called real-time crash risk evaluation models, can be used in monitoring crash hazardousness with the real-time field data fed in. One potential use of real-time crash risk evaluation models is to develop Variable Speed Limits (VSL) as a part of a freeway management system. Models have been developed to predict crash occurrence to proactively improve traffic safety and prevent crash occurrence. iv In this study, first, aggregate safety performance functions were estimated to unveil the different risk factors affecting crash occurrence for a mountainous freeway section. Then disaggregate real-time crash risk evaluation models have been developed for the total crashes with both the machine learning and hierarchical Bayesian models. Considering the need for analyzing both aggregate and disaggregate aspects of traffic safety, systematic multi-level traffic safety studies have been conducted for single- and multi-vehicle crashes, and weekday and weekend crashes. Finally, the feasibility of utilizing a VSL system to improve traffic safety on freeways has been investigated. This research was conducted based on data obtained from a 15-mile mountainous freeway section on I-70 in Colorado. The data contain historical crash data, roadway geometric characteristics, real-time weather data, and real-time traffic data. Real-time weather data were recorded by 6 weather stations installed along the freeway section, while the real-time traffic data were obtained from the Remote Traffic Microwave Sensor (RTMS) radars and Automatic Vechicle Identification (AVI) systems. Different datasets have been formulated from various data sources, and prepared for the multi-level traffic safety studies. In the aggregate traffic safety investigation, safety performance functions were developed to identify crash occurrence hazardous factors. For the first time real-time weather and traffic data were used in SPFs. Ordinary Poisson model and random effects Poisson models with Bayesian inference approach were employed to reveal the effects of weather and traffic related variables on crash occurrence. Two scenarios were considered: one seasonal based case and one crash type v based case. Deviance Information Criterion (DIC) was utilized as the comparison criterion; and the correlated random effects Poisson models outperform the others. Results indicate that weather condition variables, especially precipitation, play a key role in the safety performance functions. Moreover, in order to compare with the correlated random effects Poisson model, Multivariate Poisson model and Multivariate Poisson-lognormal model have been estimated. Conclusions indicate that, instead of assuming identical random effects for the homogenous segments, considering the correlation effects between two count variables would result in better model fit. Results from the aggregate analyses shed light on the policy implication to reduce crash frequencies. For the studied roadway segment, crash occurrence in the snow season have clear trends associated with adverse weather situations (bad visibility and large amount of precipitation); weather warning systems can be employed to improve road safety during the snow season. Furthermore, different traffic management strategies should be developed according to the distinct seasonal influence factors. In particular, sites with steep slopes need more attention from the traffic management center and operators especially during snow seasons to control the excess crash occurrence. Moreover, distinct strategy of freeway management should be designed to address the differences between single- and multi-vehicle crash characteristics. In addition to developing safety performance functions with various modeling techniques, this study also investigates four different approaches of developing informative priors for the independent variables. Bayesian inference framework provides a complete and coherent way to balance the empirical data and prior expectations; merits of these informative priors have been tested along with two types of Bayesian hierarchical models (Poisson-gamma and Poisson- vi lognormal models). Deviance Information Criterion, R-square values, and coefficients of variance for the estimations were utilized as evaluation measures to select the best model(s). Comparisons across the models indicate that the Poisson-gamma model is superior with a better model fit and it is much more robust with the informative priors. Moreover, the two-stage Bayesian updating informative priors provided the best goodness-of-fit and coefficient estimation accuracies. In addition to the aggregate analyses, real-time crash risk evaluation models have been developed to identify crash contributing factors at the disaggregate level. Support Vector Machine (SVM), a recently proposed statistical learning model and Hierarchical Bayesian logistic regression models were introduced to evaluate real-time crash risk. Classification and regression tree (CART) model has been developed to select the most important explanatory variables. Based on the variable selection results, Bayesian logistic regression models and SVM models with different kernel functions have been developed. Model comparisons based on receiver operating curves (ROC) demonstrate that the SVM model with Radial basis kernel function outperforms the others. Results from the models demonstrated that crashes are likely to happen during congestion periods (especially when the queuing area has propagated from the downstream segment); high variation of occupancy and/or volume would increase the probability of crash occurrence. Moreover, effects of microscopic traffic, weather, and roadway geometric factors on the occurrence of specific crash types have been investigated. Crashes have been categorized as rear- vii end, sideswipe, and single-vehicle crashes. AVI segment average speed, real-time weather data, and roadway geometric characteristics data were utilized as explanatory variables. Conclusions from this study imply that different active traffic management (ATM) strategies should be designed for three- and two-lane roadway sections and also considering the seasonal effects. Based on the abovementioned results, real-time crash risk evaluation models have been developed separately for multi-vehicle and single-vehicle crashes, and weekday and weekend crashes. Hierarchical Bayesian logistic regression models (random effects and random parameter logistic regression models) have been introduced to address the seasonal variations, crash unit level’s diversities, and unobserved heterogeneity caused by geometric characteristics. For the multi-vehicle crashes: congested conditions at downstream would contribute to an increase in the likelihood of multi-vehicle crashes; multi-vehicle crashes are more likely to occur during poor visibility conditions and if there is a turbulent area that exists downstream. Drivers who are unable to reduce their speeds timely are prone to causing rear-end crashes. While for the singlevehicle crashes: slow moving traffic platoons at the downstream detector of the crash occurrence locations would increase the probability of single-vehicle crashes; large variations of occupancy downstream would also increase the likelihood of single-vehicle crash occurrence. Substantial efforts have been dedicated to revealing the hazardous factors that affect crash occurrence from both the aggregate and disaggregate level in this study, however, findings and conclusions from these research work need to be transferred into applications for roadway design and freeway management. This study further investigates the feasibility of utilizing Variable Speed Limits (VSL) system, one key part of ATM, to improve traffic safety on freeways. A proactive traffic safety improvement VSL control algorithm has been proposed. First, an viii extension of the traffic flow model METANET was employed to predict traffic flow while considering VSL’s impacts on the flow-density diagram; a real-time crash risk evaluation model was then estimated for the purpose of quantifying crash risk; finally, the optimal VSL control strategies were achieved by employing an optimization technique of minimizing the total predicted crash risks along the VSL implementation area. Constraints were set up to limit the increase of the average travel time and differences between posted speed limits temporarily and spatially. The proposed VSL control strategy was tested for a mountainous freeway bottleneck area in the microscopic simulation software VISSIM. Safety impacts of the VSL system were quantified as crash risk improvements and speed homogeneity improvements. Moreover, three different driver compliance levels were modeled in VISSIM to monitor the sensitivity of VSL’s safety impacts on driver compliance levels. Conclusions demonstrate that the proposed VSL system could effectively improve traffic safety by decreasing crash risk, enhancing speed homogeneity, and reducing travel time under both high and moderate driver compliance levels; while the VSL system does not have significant effects on traffic safety enhancement under the low compliance scenario. Future implementations of VSL control strategies and related research topics were also discussed.

Understanding how climate determines species’ geographic distributions is an important question in ecology with direct implications for predicting climate change-driven range shifts. For Lepidoptera, growing degree-days, a measure of growing season length, has been shown to be an important predictor of species’ distributions in some cases. Most studies use a standardized estimate of base development temperature in their calculations of growing degree-days instead of a species-specific threshold so past investigations of the influence of growing degree-days on Lepidoptera distributions may not have been optimal. Species distribution models (SDMs) are a commonly used approach in ecology that typically only implicitly capture the underlying processes that limit a species’ distribution. A species-specific estimate of growing degree-days should better characterize these processes than standard thermal thresholds and thus improve the accuracy of species distribution models. In this thesis, I use species distribution modelling to model the geographic distribution of 30 moth species native to North America. I ask whether a) growing degree-days are the best climatic predictor of these moth species distributions at broad scales; b) a lab-estimated biological threshold (i.e., BDT) can scale up and improve the predictive ability of SDMs; and c) the quality of experiments used to estimate species-specific BDT influences the predictive accuracy of SDMs. To do so, I compare the predictive accuracy of a correlative model based on a commonly-used thermal threshold to define growing degree-days to a hybrid model with degree-days defined based on a species-specific thermal threshold. I found that the predictive performance of the hybrid models was indistinguishable from the correlative models likely because growing degree-days was not the best climatic predictor of the geographic distributions of the majority of these moth species. I also found that there was no link between the quality of the lab experiments and the difference in performance of the hybrid and correlative models. My findings suggest that lab-estimated thermal thresholds may not always scale up to be predictive at a broad scale and that more work is needed to leverage the data from lab experiments into broad scale SDMs. Determining the ultimate factors that limit species’ distributions will be critical in accurately predicting species’ range shifts response to future climate change.

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