Factors predicting recommendations for civil commitment of sexually violent predators under Florida's Jimmy Ryce Act

This study investigated the factors considered by forensic examiners when evaluating sexually violent predators (SVP) for civil commitment under Florida's “Jimmy Ryce Act.” The project was funded by a pre-doctoral research grant awarded by the Association for the Treatment of Sexual Abusers (ATSA). ^ This study proposed two specific research questions. First, what is the direct relationship between actuarial risk assessment scores and recommendations for sex offender civil commitment? Second, which other variables are likely to influence SVP commitment decisions, and to what degree? The purpose of the study was to determine if risk assessment practices are evidence-based, and whether offenders selected for commitment meet statutory criteria. ^ The purposive sample of 450 SVPs was drawn from the population of sex offenders evaluated for civil commitment in Florida between July 1, 2000 and June 30, 2001. Data were extracted from SVP evaluations provided by the Florida Department of Children and Families. Using multivariate logistic regression, this correlational research design examined the relationship between the dependent variable, commitment decision, and several sets of independent variables. The independent variables were derived from a review of the literature, and were grouped conceptually according to their degree of correlation with sex offense recidivism. Independent variables included diagnoses, actuarial risk assessment scores, empirically validated static and dynamic risk factors, consensus based risk factors, evaluator characteristics, and demographics. This study investigated the degree to which the identified variables predicted civil commitment decisions. ^ Logistic regression results revealed that the statistically significant predictors of recommendations for sex offender civil commitment were actuarial risk assessment scores, diagnoses of Pedophilia and Paraphilia NOS, psychopathy, younger age of victim, and non-minority race. Discriminant function analysis confirmed that these variables correctly predicted commitment decisions in 90% of cases. ^ It appears that civil commitment evaluators in Florida used empirically-based assessment procedures, and did not make decisions that were heavily influenced by extraneous factors. SVPs recommended for commitment consistently met the criteria set forth by the U.S. Supreme Court in Hendricks v. Kansas (1997): they suffered from a mental abnormality predisposing them to sexual violence, and risk assessment determined that they were likely to reoffend. ^

The civil war of ideas: Ayn Rand, intellectual freedom, and the regulation of thought in the Soviet Union and United States, 1905-1943

The philosopher and novelist Ayn Rand (1905–1982) is an icon of American culture. That culture misunderstands her, however. It perceives her solely as a pure market conservative. In the first forty years of her life, Rand's individualism was intellectual and served as a defense for the free trade of ideas. It originated in the Russian Revolution. In 1926, when Rand left the Soviet Union, she developed her individualism into an American philosophy. Her ideas of the individual in society belonged to a debate where intellectuals intended to abolish the State and free man and woman from its intellectual snares. To present Rand as a freethinker allows me to examine her anticommunism as a reaction against Leninism and to consider the relation of her ideas to Marxism. This approach stresses that Rand, as Marx, opposed the State and argued for the historical importance of a capitalist revolution. For Rand the latter, however, depended on an entrepreneurial class that rejected Protestantism as ideology – which she contended threatened its interests because Christianity had lost its historical significance. This exposes the nature of Rand's intellectual individualism in American society, where the majority on the entire political spectrum still identified with the teachings of Christ. It also reveals the dynamics of her anticommunism. From 1926 to 1943, Rand remodeled American individualism and as she did so, she determined her opposition first to the New Deal liberals and second business conservatives. To these ends, Marxism and Protestantism served Rand's individualism and made her an American icon of the twentieth century.

Development of operational performance models for truck-lane restrictions on freeway corridors

Highways are generally designed to serve a mixed traffic flow that consists of passenger cars, trucks, buses, recreational vehicles, etc. The fact that the impacts of these different vehicle types are not uniform creates problems in highway operations and safety. A common approach to reducing the impacts of truck traffic on freeways has been to restrict trucks to certain lane(s) to minimize the interaction between trucks and other vehicles and to compensate for their differences in operational characteristics. ^ The performance of different truck lane restriction alternatives differs under different traffic and geometric conditions. Thus, a good estimate of the operational performance of different truck lane restriction alternatives under prevailing conditions is needed to help make informed decisions on truck lane restriction alternatives. This study develops operational performance models that can be applied to help identify the most operationally efficient truck lane restriction alternative on a freeway under prevailing conditions. The operational performance measures examined in this study include average speed, throughput, speed difference, and lane changes. Prevailing conditions include number of lanes, interchange density, free-flow speeds, volumes, truck percentages, and ramp volumes. ^ Recognizing the difficulty of collecting sufficient data for an empirical modeling procedure that involves a high number of variables, the simulation approach was used to estimate the performance values for various truck lane restriction alternatives under various scenarios. Both the CORSIM and VISSIM simulation models were examined for their ability to model truck lane restrictions. Due to a major problem found in the CORSIM model for truck lane modeling, the VISSIM model was adopted as the simulator for this study. ^ The VISSIM model was calibrated mainly to replicate the capacity given in the 2000 Highway Capacity Manual (HCM) for various free-flow speeds under the ideal basic freeway section conditions. Non-linear regression models for average speed, throughput, average number of lane changes, and speed difference between the lane groups were developed. Based on the performance models developed, a simple decision procedure was recommended to select the desired truck lane restriction alternative for prevailing conditions. ^

Estimation of average annual daily traffic (AADT) using geographically weighted regression (GWR) method and geographic information system (GIS)

Annual average daily traffic (AADT) is important information for many transportation planning, design, operation, and maintenance activities, as well as for the allocation of highway funds. Many studies have attempted AADT estimation using factor approach, regression analysis, time series, and artificial neural networks. However, these methods are unable to account for spatially variable influence of independent variables on the dependent variable even though it is well known that to many transportation problems, including AADT estimation, spatial context is important. ^ In this study, applications of geographically weighted regression (GWR) methods to estimating AADT were investigated. The GWR based methods considered the influence of correlations among the variables over space and the spatially non-stationarity of the variables. A GWR model allows different relationships between the dependent and independent variables to exist at different points in space. In other words, model parameters vary from location to location and the locally linear regression parameters at a point are affected more by observations near that point than observations further away. ^ The study area was Broward County, Florida. Broward County lies on the Atlantic coast between Palm Beach and Miami-Dade counties. In this study, a total of 67 variables were considered as potential AADT predictors, and six variables (lanes, speed, regional accessibility, direct access, density of roadway length, and density of seasonal household) were selected to develop the models. ^ To investigate the predictive powers of various AADT predictors over the space, the statistics including local r-square, local parameter estimates, and local errors were examined and mapped. The local variations in relationships among parameters were investigated, measured, and mapped to assess the usefulness of GWR methods. ^ The results indicated that the GWR models were able to better explain the variation in the data and to predict AADT with smaller errors than the ordinary linear regression models for the same dataset. Additionally, GWR was able to model the spatial non-stationarity in the data, i.e., the spatially varying relationship between AADT and predictors, which cannot be modeled in ordinary linear regression. ^

Effects of roadway geometric features on run-off road crashes on the Florida State Highway System

Run-off-road (ROR) crashes have increasingly become a serious concern for transportation officials in the State of Florida. These types of crashes have increased proportionally in recent years statewide and have been the focus of the Florida Department of Transportation. The goal of this research was to develop statistical models that can be used to investigate the possible causal relationships between roadway geometric features and ROR crashes on Florida's rural and urban principal arterials. ^ In this research, Zero-Inflated Poisson (ZIP) and Zero-Inflated Negative Binomial (ZINB) Regression models were used to better model the excessive number of roadway segments with no ROR crashes. Since Florida covers a diverse area and since there are sixty-seven counties, it was divided into four geographical regions to minimize possible unobserved heterogeneity. Three years of crash data (2000–2002) encompassing those for principal arterials on the Florida State Highway System were used. Several statistical models based on the ZIP and ZINB regression methods were fitted to predict the expected number of ROR crashes on urban and rural roads for each region. Each region was further divided into urban and rural areas, resulting in a total of eight crash models. A best-fit predictive model was identified for each of these eight models in terms of AIC values. The ZINB regression was found to be appropriate for seven of the eight models and the ZIP regression was found to be more appropriate for the remaining model. To achieve model convergence, some explanatory variables that were not statistically significant were included. Therefore, strong conclusions cannot be derived from some of these models. ^ Given the complex nature of crashes, recommendations for additional research are made. The interaction of weather and human condition would be quite valuable in discerning additional causal relationships for these types of crashes. Additionally, roadside data should be considered and incorporated into future research of ROR crashes. ^

Optimization of adaptive traffic signal control with transit signal priority at isolated intersections using parallel genetic algorithms

Optimization of adaptive traffic signal timing is one of the most complex problems in traffic control systems. This dissertation presents a new method that applies the parallel genetic algorithm (PGA) to optimize adaptive traffic signal control in the presence of transit signal priority (TSP). The method can optimize the phase plan, cycle length, and green splits at isolated intersections with consideration for the performance of both the transit and the general vehicles. Unlike the simple genetic algorithm (GA), PGA can provide better and faster solutions needed for real-time optimization of adaptive traffic signal control. ^ An important component in the proposed method involves the development of a microscopic delay estimation model that was designed specifically to optimize adaptive traffic signal with TSP. Macroscopic delay models such as the Highway Capacity Manual (HCM) delay model are unable to accurately consider the effect of phase combination and phase sequence in delay calculations. In addition, because the number of phases and the phase sequence of adaptive traffic signal may vary from cycle to cycle, the phase splits cannot be optimized when the phase sequence is also a decision variable. A "flex-phase" concept was introduced in the proposed microscopic delay estimation model to overcome these limitations. ^ The performance of PGA was first evaluated against the simple GA. The results show that PGA achieved both faster convergence and lower delay for both under- or over-saturated traffic conditions. A VISSIM simulation testbed was then developed to evaluate the performance of the proposed PGA-based adaptive traffic signal control with TSP. The simulation results show that the PGA-based optimizer for adaptive TSP outperformed the fully actuated NEMA control in all test cases. The results also show that the PGA-based optimizer was able to produce TSP timing plans that benefit the transit vehicles while minimizing the impact of TSP on the general vehicles. The VISSIM testbed developed in this research provides a powerful tool to design and evaluate different TSP strategies under both actuated and adaptive signal control. ^

Development of a medium-capacity guideway transit planning guide

Rapid population increase and booming economic growth have caused a significant escalation in car ownership in many cities, leading to additional or, multiple traffic problems on congested roadways. The increase of automobiles is generating a significant amount of congestion and pollution in many cities. It has become necessary to find a solution to the ever worsening traffic problems in our cities. Building more roadways is nearly impossible due to the limitations of right-of-way in cities. Studies have shown that guideway transit could provide effective transportation and could stimulate land development. The Medium-Capacity Guideway Transit (MCGT) is one of the alternatives to solve this problem. The objective of this research was to better understand the characteristics of MCGT systems, to investigate the existing MCGT systems around the world and determine the main factors behind the planning of successful systems, and to develop a MCGT planning guide. The factors utilized in this study were determined and were analyzed using Excel. A MCGT Planning Guide was developed using Microsoft Visual Basic. ^ A MCGT was defined as a transit system whose capacity can carry up to 20,000 passengers per hour per direction (pphpd). The results shown that Light Rail Transit (LRT) is favored when peak hour demand is less than 13,000 pphpd. Automated People Mover (APM) is favored when the peak hour demand is more than 18,000 pphpd. APM systems could save up to three times the waiting time cost compared to that of the LRT. If comfort and convenience are important, then using an APM does make sense. However, if cost is the critical factor, then LRT will make more sense because it is reasonable service at a reasonable price. If travel time and safety (accident/crush) costs were included in calculating life-cycle “total” costs, the capital cost advantage of LRT disappeared and APM could become very competitive. The results also included a range of cost-performance criteria for MCGT systems that help planners, engineers, and decision-makers to select the most feasible system for their respective areas. ^

Development of prediction models for freeway incident durations using data mining techniques

The nation's freeway systems are becoming increasingly congested. A major contribution to traffic congestion on freeways is due to traffic incidents. Traffic incidents are non-recurring events such as accidents or stranded vehicles that cause a temporary roadway capacity reduction, and they can account for as much as 60 percent of all traffic congestion on freeways. One major freeway incident management strategy involves diverting traffic to avoid incident locations by relaying timely information through Intelligent Transportation Systems (ITS) devices such as dynamic message signs or real-time traveler information systems. The decision to divert traffic depends foremost on the expected duration of an incident, which is difficult to predict. In addition, the duration of an incident is affected by many contributing factors. Determining and understanding these factors can help the process of identifying and developing better strategies to reduce incident durations and alleviate traffic congestion. A number of research studies have attempted to develop models to predict incident durations, yet with limited success. ^ This dissertation research attempts to improve on this previous effort by applying data mining techniques to a comprehensive incident database maintained by the District 4 ITS Office of the Florida Department of Transportation (FDOT). Two categories of incident duration prediction models were developed: "offline" models designed for use in the performance evaluation of incident management programs, and "online" models for real-time prediction of incident duration to aid in the decision making of traffic diversion in the event of an ongoing incident. Multiple data mining analysis techniques were applied and evaluated in the research. The multiple linear regression analysis and decision tree based method were applied to develop the offline models, and the rule-based method and a tree algorithm called M5P were used to develop the online models. ^ The results show that the models in general can achieve high prediction accuracy within acceptable time intervals of the actual durations. The research also identifies some new contributing factors that have not been examined in past studies. As part of the research effort, software code was developed to implement the models in the existing software system of District 4 FDOT for actual applications. ^

Development of thresholds for surface preparation in repair systems with wet lay -up fiber reinforced polymers

Bonded repair of concrete structures with fiber reinforced polymer (FRP) systems is increasingly being accepted as a cost-efficient and structurally viable method of rapid rehabilitation of concrete structures. However, the relationships between long-term performance attributes, service-life, and details of the installation process are not easy to quantify. Accordingly, there is currently a lack of generally accepted construction specifications, making it difficult for the field engineer to certify the adequacy of the construction process. ^ The objective of the present study, as part of the National Cooperative Highway Research Program (NCHRP) Project 10-59B, was to investigate the effect of surface preparation on the behavior of wet lay-up FRP repair systems and consequently develop rational thresholds that provide sufficient performance. ^ The research program was comprised of both experimental and analytical work for wet lay-up FRP applications. The experimental work included flexure testing of sixty-seven (67) reinforced concrete beams and bond testing of ten (10) reinforced concrete blocks. Four different parameters were studied: surface roughness, surface flatness, surface voids and bug holes, and surface cracks/cuts. The findings were analyzed from various aspects and compared with the data available in the literature. As part of the analytical work, finite element models of the flexural specimens with surface flaws were developed using ANSYS. The purpose of this part was to extend the parametric study on the effects of concrete surface flaws and verify the experimental results based on nonlinear finite element analysis. ^ Test results showed that surface roughness does not appear to have a significant influence on the overall performance of the wet lay-up FRP systems with or without adequate anchorage, and whether failure was by debonding or rupture of FRP. Both experimental and analytical results for surface flatness proved that peaks on concrete surface, in the range studied, do not have a significant effect on the performance of wet lay-up FRP systems. However, valleys of particular size could reduce the strength of wet lay-up FRP systems. Test results regarding surface voids and surface cracks/cuts revealed that previously suggested thresholds for these flaws appear to be conservative, as also confirmed by analytical study. ^

Development of test-based wind-driven rain intrusion model for hurricane-induced building interior and contents damage

Major portion of hurricane-induced economic loss originates from damages to building structures. The damages on building structures are typically grouped into three main categories: exterior, interior, and contents damage. Although the latter two types of damages, in most cases, cause more than 50% of the total loss, little has been done to investigate the physical damage process and unveil the interdependence of interior damage parameters. Building interior and contents damages are mainly due to wind-driven rain (WDR) intrusion through building envelope defects, breaches, and other functional openings. The limitation of research works and subsequent knowledge gaps, are in most part due to the complexity of damage phenomena during hurricanes and lack of established measurement methodologies to quantify rainwater intrusion. This dissertation focuses on devising methodologies for large-scale experimental simulation of tropical cyclone WDR and measurements of rainwater intrusion to acquire benchmark test-based data for the development of hurricane-induced building interior and contents damage model. Target WDR parameters derived from tropical cyclone rainfall data were used to simulate the WDR characteristics at the Wall of Wind (WOW) facility. The proposed WDR simulation methodology presents detailed procedures for selection of type and number of nozzles formulated based on tropical cyclone WDR study. The simulated WDR was later used to experimentally investigate the mechanisms of rainwater deposition/intrusion in buildings. Test-based dataset of two rainwater intrusion parameters that quantify the distribution of direct impinging raindrops and surface runoff rainwater over building surface — rain admittance factor (RAF) and surface runoff coefficient (SRC), respectively —were developed using common shapes of low-rise buildings. The dataset was applied to a newly formulated WDR estimation model to predict the volume of rainwater ingress through envelope openings such as wall and roof deck breaches and window sill cracks. The validation of the new model using experimental data indicated reasonable estimation of rainwater ingress through envelope defects and breaches during tropical cyclones. The WDR estimation model and experimental dataset of WDR parameters developed in this dissertation work can be used to enhance the prediction capabilities of existing interior damage models such as the Florida Public Hurricane Loss Model (FPHLM).^