Color-based surface reflectance separation for scene illumination estimation and rendering

Given the importance of color processing in computer vision and computer graphics, estimating and rendering illumination spectral reflectance of image scenes is important to advance the capability of a large class of applications such as scene reconstruction, rendering, surface segmentation, object recognition, and reflectance estimation. Consequently, this dissertation proposes effective methods for reflection components separation and rendering in single scene images. Based on the dichromatic reflectance model, a novel decomposition technique, named the Mean-Shift Decomposition (MSD) method, is introduced to separate the specular from diffuse reflectance components. This technique provides a direct access to surface shape information through diffuse shading pixel isolation. More importantly, this process does not require any local color segmentation process, which differs from the traditional methods that operate by aggregating color information along each image plane. ^ Exploiting the merits of the MSD method, a scene illumination rendering technique is designed to estimate the relative contributing specular reflectance attributes of a scene image. The image feature subset targeted provides a direct access to the surface illumination information, while a newly introduced efficient rendering method reshapes the dynamic range distribution of the specular reflectance components over each image color channel. This image enhancement technique renders the scene illumination reflection effectively without altering the scene’s surface diffuse attributes contributing to realistic rendering effects. ^ As an ancillary contribution, an effective color constancy algorithm based on the dichromatic reflectance model was also developed. This algorithm selects image highlights in order to extract the prominent surface reflectance that reproduces the exact illumination chromaticity. This evaluation is presented using a novel voting scheme technique based on histogram analysis. ^ In each of the three main contributions, empirical evaluations were performed on synthetic and real-world image scenes taken from three different color image datasets. The experimental results show over 90% accuracy in illumination estimation contributing to near real world illumination rendering effects. ^

A Model for Teacher Induction and Mentoring Programs

There is argument for differentiation between induction and mentoring programs. A basis of this paper is that both programs must coexist; that neither program can be effective without the other. Literature, data and the experiences of a novice teacher revealed components of effective mentoring/induction programs for teachers.

Differential outcomes of two -way and transitional programs on English language learners at different entry levels

This study investigated the effects of two types of bilingual education programs (two-way and transitional) on the academic performance, attitudes, and metacognitive awareness of 5th grade students who entered kindergarten or first grade with different levels of English proficiency. The multi-stage sample consisted of students who had participated in each program for a period of at least five years. A mixed model design allowed for the collection of quantitative and qualitative data that were analyzed accordingly and integrated. ^ The findings indicated no significant differences between the two groups on measures of academic achievement in English. Significant differences were found in the number of semesters required for the students to become proficient English speakers. An important conclusion, based on these findings, was that the students enrolled in the two-way bilingual education (TWBE) programs learned English faster. Moreover, they maintained a high level of proficiency in Spanish, scoring significantly higher than the transitional bilingual education group on measures of Spanish reading ability.^ Questionnaire and interview data indicated that the students in the two-way bilingual education programs tended to use more Spanish for recreational purposes and tended to rate themselves as more proficient Spanish speakers than their peers. Conversely, the students enrolled in the transitional bilingual education programs tended to rate themselves as more proficient in English than their peers. ^ The level of English language proficiency upon entering school (five years later) was found to make a difference in academic achievement, as measured by standardized tests. Five years of schooling did not fully eliminate the gap in academic performance between students with different ESOL entry levels at kindergarten. However, entry level did not have an effect on attitudes towards bilingualism. ^ It is concluded that, although there was no significant difference between the two groups on measures of academic achievement in English, TWBE and transitional programs have differential effects. Students in the TWBE programs acquired oral language at a faster rate, developed literacy skills in their native language, and acquired more positive attitudes towards bilingualism. Theoretical, methodological, and policy implications of the findings are discussed. ^

Adult education directors' perceptions of performance indicators for adult education programs in the state of Florida

Current demands for accountability in education emphasize outcome-based program evaluation and tie program funding to individual student performance. As has been the case for elementary and secondary programs, demands for accountability have increased pressure on adult educators to show evidence of the benefits of their programs in order to justify their financial support. In Florida, recent legislation fundamentally changes the delivery of adult education in the state by establishing a performance-based funding system that is based on outcomes related to the retention, completion, and employment of program participants.^ A performance-based funding system requires an evaluation process that stresses outcome indicators over indicators that focus on program context or process. Although the state has adopted indicators of program quality to evaluate its adult education programs, these indicators focus mostly on program processes rather than student outcomes. In addition, the indicators are not specifically tied to workforce development outcomes, a priority to federal and local funding agents.^ Improving the accountability of adult education programs and defining the role of these programs in Florida's Workforce Development System has become a priority to policy makers across the state. Another priority has been to involve adult education practitioners in every step of this process.^ This study was conducted in order to determine what performance indicators, as judged by the directors and supervisors of adult education programs in the state of Florida, are important and feasible in measuring the quality and effectiveness of these programs. The results of the study indicated that, both statewide and by region, the respondents consistently gave the highest ratings on both importance and feasibility to the indicators of Program Context, which reflect the needs, composition, and structure of the programs, and to the indicators of Educational Gain, which reflect learner progress in the attainment of basic skills and competencies. In turn, the respondents gave the lowest ratings on both importance and feasibility to the indicators in the areas of Return on State's Investment, Efficiency, Retention, and Workforce Training. In general, the indicators that received high ratings for importance also received high ratings for feasibility. ^

The effects of government disability benefits, accessibility laws and rehabilitation on employment choices by individuals with spinal cord injuries

Greater inclusion of individuals with disabilities into mainstream society is an important goal for society. One of the best ways to include individuals is to actively promote and encourage their participation in the labor force. Of all disabilities, it is feasible to assume that individual with spinal cord injuries can be among the most easily mainstreamed into the labor force. However, less that fifty percent of individuals with spinal cord injuries work. ^ This study focuses on how disability benefit programs, such as Social Security Disability Insurance, and Worker's Compensation, the Americans with Disabilities Act and rehabilitation programs affect employment decisions. The questions were modeled using utility theory with an augmented expenditure function and indifference theory. Statically, Probit, Logit, predicted probability, and linear regressions were used to analyze these questions. Statistical analysis was done on the probability of working, ever attempting to work after injury, and on the number of years after injury that work was first attempted and the number of hours worked per week. The data utilized were from the National Spinal Cord Injury Database and the Spinal Cord Injuries and Labor Database. The Spinal Cord Injuries and Labor Database was created specifically for this study by the author. Receiving disability benefits decreased the probability of working, of ever attempting to work, increased the number of years after injury before the first work attempt was made, and decreased the number of hours worked per week for those individuals working. These results were all statistically significant. The Americans with Disabilities Act decrease the number of years before an individual made a work attempt. The decrease is statistically significant. The amount of rehabilitation had a significant positive effect for male individuals with low paraplegia, and significant negative effect for individuals with high tetraplegia. For women, there were significant negative effects for high tetraplegia and high paraplegia. ^ This study finds that the financial disincentives of receiving benefits are the major determinants of whether an individual with a spinal cord injury returns to the labor force. Policies are recommended that would decrease the disincentive. ^

A novel 3-D segmentation algorithm for anatomic liver and tumor volume calculations for liver cancer treatment planning

Three-Dimensional (3-D) imaging is vital in computer-assisted surgical planning including minimal invasive surgery, targeted drug delivery, and tumor resection. Selective Internal Radiation Therapy (SIRT) is a liver directed radiation therapy for the treatment of liver cancer. Accurate calculation of anatomical liver and tumor volumes are essential for the determination of the tumor to normal liver ratio and for the calculation of the dose of Y-90 microspheres that will result in high concentration of the radiation in the tumor region as compared to nearby healthy tissue. Present manual techniques for segmentation of the liver from Computed Tomography (CT) tend to be tedious and greatly dependent on the skill of the technician/doctor performing the task. ^ This dissertation presents the development and implementation of a fully integrated algorithm for 3-D liver and tumor segmentation from tri-phase CT that yield highly accurate estimations of the respective volumes of the liver and tumor(s). The algorithm as designed requires minimal human intervention without compromising the accuracy of the segmentation results. Embedded within this algorithm is an effective method for extracting blood vessels that feed the tumor(s) in order to plan effectively the appropriate treatment. ^ Segmentation of the liver led to an accuracy in excess of 95% in estimating liver volumes in 20 datasets in comparison to the manual gold standard volumes. In a similar comparison, tumor segmentation exhibited an accuracy of 86% in estimating tumor(s) volume(s). Qualitative results of the blood vessel segmentation algorithm demonstrated the effectiveness of the algorithm in extracting and rendering the vasculature structure of the liver. Results of the parallel computing process, using a single workstation, showed a 78% gain. Also, statistical analysis carried out to determine if the manual initialization has any impact on the accuracy showed user initialization independence in the results. ^ The dissertation thus provides a complete 3-D solution towards liver cancer treatment planning with the opportunity to extract, visualize and quantify the needed statistics for liver cancer treatment. Since SIRT requires highly accurate calculation of the liver and tumor volumes, this new method provides an effective and computationally efficient process required of such challenging clinical requirements.^

Chlorine contribution to quantitative structure and activity relationship models of disinfection by -products' quantum chemical descriptors and toxicities

Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: (1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (E LUMO) via QSAR modelling and analysis; (2) to validate the models by using internal and external cross-validation techniques; (3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl ) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: (1) Linear or Multi-linear Regression (MLR); (2) Partial Least Squares (PLS); and (3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: (1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; (2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; (3) E LUMO are shown to correlate highly with the NCl for several classes of DBPs; and (4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.

Influence of religious coping on the substance use and HIV risk behaviors of recent Latino immigrants

This study examines the influence of acculturative stress on substance use and HIV risk behaviors among recent Latino immigrants. The central hypothesis of the study is that specific religious coping mechanisms influence the relationship that acculturative stress has on the substance use and HIV-risk behaviors of recent Latino immigrants. Within the Latino culture religiosity is a pervasive force, guiding attitudes, behaviors, and even social interactions. When controlling for education and socioeconomic status, Latinos have been found to use religious coping mechanisms more frequently than their Non-Latino White counterparts. In addition, less acculturated Latinos use religious coping strategies more frequently than those with higher levels of acculturation. Given its prominent role in Latino culture, it appears probable that this mechanism may prove to be influential during difficult life transitions, such as those experienced during the immigration process. This study examines the moderating influence of specific religious coping mechanisms on the relationship between acculturative stress and substance use/HIV risk behaviors of recent Latino immigrants. Analyses for the present study were conducted with wave 2 data from an ongoing longitudinal study investigating associations between pre-immigration factors and health behavior trajectories of recent Latino immigrants. Structural equation and zero-inflated Poisson modeling were implemented to test the specified models and examine the nature of the relationship among the variables. Moderating effects were found for negative religious coping. Higher levels of negative religious coping strengthened an inverse relationship between acculturative stress and substance use. Results also indicated direct relationships between religious coping mechanisms and substance use. External and positive religious coping were inversely related to substance use. Negative religious coping was positively related to substance use. This study aims to contribute knowledge of how religious coping influence's the adaptation process of recent Latino immigrants. Expanding scientific understanding as to the function and effect of these coping mechanisms could lead to enhanced culturally relevant approaches in service delivery among Latino populations. Furthermore this knowledge could inform research about specific cognitions and behaviors that need to be targeted in prevention and treatment programs with this population.

Effect of the Supplemental Nutrition Assistance Program (SNAP) and nutrition education on nutrition and health outcomes of HIV+ individuals

Factors associated with and barriers to participation in Supplemental Nutrition Assistance Program (SNAP) and the effect participation has on food security, nutrition status, disease status and quality of life was investigated in a cross-sectional study including 175 HIV infected individuals. In addition, the effect of a targeted nutrition education on nutrition knowledge, readiness to dietary behavior change, nutrition status, disease status and quality of life was also investigated among a subset of the population (N = 45) in a randomized clinical control trial. ^ SNAP participation rate was 70.3%, similar to the State of Florida and national participation rates. SNAP participation was positively and independently associated with being born in the US (P < 0.001), having monthly income less than $1000 (P = 0.006), and receiving antiretroviral treatment (P < 0.001). Participation barriers include denial of participation by program, recent incarceration, living in a shelter where participation is not allowed and unawareness of eligibility status. In regression analyses, SNAP participation was not significantly associated with improved food security, nutrition status, disease status and health related quality of life (HRQOL). Over half (56%) of the population experienced food insecurity and had inadequate intakes of half of the nutrients assessed. Illicit drug, alcohol and cigarette use were high in this population (31%, 55% and 63% respectively), and affected food security, nutrients intake, disease status and HRQOL. The nutrition education intervention resulted in a trend towards improvements nutrition knowledge, self-efficacy, and readiness to change without impacting nutrition status, disease state and quality of life. ^ Food insecurity and other nutrition related issues, with implications for treatment, management and cost of HIV disease, continue to plague infected individuals living in poverty. More resources, including food and nutrition programs, specifically targeted towards this population are needed to address these issues.^

The effects of government disability benefits, accessibility laws and rehabilitation on employment choices by individuals with spinal cord injuries

Greater inclusion of individuals with disabilities into mainstream society is an important goal for society. One of the best ways to include individuals is to actively promote and encourage their participation in the labor force. Of all disabilities, it is feasible to assume that individual with spinal cord injuries can be among the most easily mainstreamed into the labor force. However, less that fifty percent of individuals with spinal cord injuries work. This study focuses on how disability benefit programs, such as Social Security Disability Insurance, and Worker's Compensation, the Americans with Disabilities Act and rehabilitation programs affect employment decisions. The questions were modeled using utility theory with an augmented expenditure function and indifference theory. Statically, Probit, Logit, predicted probability, and linear regressions were used to analyze these questions. Statistical analysis was done on the probability of working, ever attempting to work after injury, and on the number of years after injury that work was first attempted and the number of hours worked per week. The data utilized were from the National Spinal Cord Injury Database and the Spinal Cord Injuries and Labor Database. The Spinal Cord Injuries and Labor Database was created specifically for this study by the author. Receiving disability benefits decreased the probability of working, of ever attempting to work, increased the number of years after injury before the first work attempt was made, and decreased the number of hours worked per week for those individuals working. These results were all statistically significant. The Americans with Disabilities Act decrease the number of years before an individual made a work attempt. The decrease is statistically significant. The amount of rehabilitation had a significant positive effect for male individuals with low paraplegia, and significant negative effect for individuals with high tetraplegia. For women, there were significant negative effects for high tetraplegia and high paraplegia. This study finds that the financial disincentives of receiving benefits are the major determinants of whether an individual with a spinal cord injury returns to the labor force. Policies are recommended that would decrease the disincentive.

Factors of Inflammation in Haitian Americans and African Americans with and without Type 2 Diabetes

Chronic low-grade inflammation has been implicated in the processes leading to the development of type 2 diabetes (T2D) and its progression. Non-Hispanic Blacks bear a disproportionate burden of T2D and are highly susceptible to inflammation. This cross-sectional study assessed and compared the serum levels of established adipocytokines; interleukin-6 (IL-6), C-reactive protein (CRP), leptin, and novel adipocytokines; chemerin and omentin in Haitian and African Americans with and without T2D. The relationships of these adipocytokines with metabolic syndrome (MetS), anthropometric and HOMA2 measures by ethnicity and diabetes status were also assessed. Serum levels of IL-6, CRP, leptin, chemerin and omentin were determined by the ELISA method. HOMA2 measures were calculated for insulin sensitivity (HOMA2-IS) and insulin resistance (HOMA2-IR). Analyses of available data for 230 Haitian Americans and 241 African Americans (240 with and 231 without T2D) for the first study showed that Haitian Americans with and without MetS had lower levels of IL-6 and CRP compared to African Americans with and without MetS (P Ethnic-specific diabetes intervention and treatment programs must be designed to target Haitian Americans and African Americans as separate unique groups, in order to reduce the burden of T2D among the non-Hispanic Black community. Further research is needed to gain better understanding of the role of inflammation and T2D in this population.

Utilizing Traditional Cognitive Measures of Academic Preparation to Predict First-Year Science, Technology, Engineering, and Mathematics (STEM) Majors' Success in Math and Science Courses

For the past several years, U.S. colleges and universities have faced increased pressure to improve retention and graduation rates. At the same time, educational institutions have placed a greater emphasis on the importance of enrolling more students in STEM (science, technology, engineering and mathematics) programs and producing more STEM graduates. The resulting problem faced by educators involves finding new ways to support the success of STEM majors, regardless of their pre-college academic preparation. The purpose of my research study involved utilizing first-year STEM majors’ math SAT scores, unweighted high school GPA, math placement test scores, and the highest level of math taken in high school to develop models for predicting those who were likely to pass their first math and science courses. In doing so, the study aimed to provide a strategy to address the challenge of improving the passing rates of those first-year students attempting STEM-related courses. The study sample included 1018 first-year STEM majors who had entered the same large, public, urban, Hispanic-serving, research university in the Southeastern U.S. between 2010 and 2012. The research design involved the use of hierarchical logistic regression to determine the significance of utilizing the four independent variables to develop models for predicting success in math and science. The resulting data indicated that the overall model of predictors (which included all four predictor variables) was statistically significant for predicting those students who passed their first math course and for predicting those students who passed their first science course. Individually, all four predictor variables were found to be statistically significant for predicting those who had passed math, with the unweighted high school GPA and the highest math taken in high school accounting for the largest amount of unique variance. Those two variables also improved the regression model’s percentage of correctly predicting that dependent variable. The only variable that was found to be statistically significant for predicting those who had passed science was the students’ unweighted high school GPA. Overall, the results of my study have been offered as my contribution to the literature on predicting first-year student success, especially within the STEM disciplines.

Chlorine Contribution to Quantitative Structure and Activity Relationship Models of Disinfection By-Products' Quantum Chemical Descriptors and Toxicities

Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: 1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (ELUMO) via QSAR modelling and analysis; 2) to validate the models by using internal and external cross-validation techniques; 3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: 1) Linear or Multi-linear Regression (MLR); 2) Partial Least Squares (PLS); and 3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: 1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; 2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; 3) ELUMO are shown to correlate highly with the NCl for several classes of DBPs; and 4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.