An Examination of Race, Socioeconomic Status, and Individualism-Collectivsm as Moderators of the Work/Family Antecedent and Work-Family Conflict Relationship

This study examines the role of race, socioeconomic status, and individualism-collectivism as moderators of the relationship between selected work and family antecedents and work-family conflict and evaluates the contribution of energy-based conflict to the work-family conflict (WFC) research. The study uses data obtained from a survey questionnaire given to 414 participants recruited from an online labor market. Study hypotheses were tested through structural equation modeling. The results indicate that while moderating effects were slight, a proposed model where energy-based conflict is included outperforms traditional time/strain/behavior-based models and that established variables may drop to non-significance when additional variables are included in prediction. In addition, novel individual difference variables such as individualism and collectivism were demonstrated to have effects beyond moderating antecedent-outcome relationships in the model. The findings imply that WFC models would benefit from the inclusion of variables found in the current study.

A comparative study of block scheduling and traditional scheduling on academic achievement

The purpose of this study was to evaluate the effectiveness of an alternate day block schedule design (n = 419) versus a traditional six-period schedule design (n = 623) on the academic achievement of the graduating classes in two schools in which the design was used respectively. Academic achievement was measured by (a) two standardized tests: the Florida Comprehensive Assessment Test Sunshine State Standards (FCAT-SSS) in mathematics and reading for 9th and 10th grade and the Scholastic Reading Inventory Test (SRI) for 9 th, 10th, and 11th grade; (b) three school grades: the mathematics final course grades for 9th, 10th, and 11th grade, the English final course grades for 9th, 10th, 11th, and 12th grade and the graduating GPA. A total of five repeated measure analyses of variance (ANOVAs) were conducted to analyze the difference between the two schools (representing the two designs) with respect to five achievement indicators (FCAT-SSS mathematics scores, FCAT-SSS reading scores, SRI scores, mathematics final course grades, and English final course grades). The between-subject factor for the five ANOVAs was the schedule design and the within-subject factor was the time the tests were taken or the time the course grades were issued. T-tests were performed on all eighth grade achievement indicators to ensure there were no significant differences in achievement between the two cohorts prior to entering high school. An independent samples t-test was conducted to analyze the difference between the two schedule designs with respect to graduating GPA. Achievement in the alternate day block schedule design was significantly higher than in the traditional six-period schedule design for some of the locally assigned school grades. The difference between the two types of schedule designs was not significant for the standardized measures (the FCAT-SSS in reading and mathematics and the SRI). This study concludes that the use of an alternate day block schedule design can be considered an educational tool that can help improve the academic achievement of students as measured by local indicators of achievement; but, apparently the design is not an important factor in achievement as measured by state examinations such as the FCAT-SSS or the SRI.

Improving Analytical Travel Time Estimation for Transportation Planning Models

This dissertation aimed to improve travel time estimation for the purpose of transportation planning by developing a travel time estimation method that incorporates the effects of signal timing plans, which were difficult to consider in planning models. For this purpose, an analytical model has been developed. The model parameters were calibrated based on data from CORSIM microscopic simulation, with signal timing plans optimized using the TRANSYT-7F software. Independent variables in the model are link length, free-flow speed, and traffic volumes from the competing turning movements. The developed model has three advantages compared to traditional link-based or node-based models. First, the model considers the influence of signal timing plans for a variety of traffic volume combinations without requiring signal timing information as input. Second, the model describes the non-uniform spatial distribution of delay along a link, this being able to estimate the impacts of queues at different upstream locations of an intersection and attribute delays to a subject link and upstream link. Third, the model shows promise of improving the accuracy of travel time prediction. The mean absolute percentage error (MAPE) of the model is 13% for a set of field data from Minnesota Department of Transportation (MDOT); this is close to the MAPE of uniform delay in the HCM 2000 method (11%). The HCM is the industrial accepted analytical model in the existing literature, but it requires signal timing information as input for calculating delays. The developed model also outperforms the HCM 2000 method for a set of Miami-Dade County data that represent congested traffic conditions, with a MAPE of 29%, compared to 31% of the HCM 2000 method. The advantages of the proposed model make it feasible for application to a large network without the burden of signal timing input, while improving the accuracy of travel time estimation. An assignment model with the developed travel time estimation method has been implemented in a South Florida planning model, which improved assignment results.

Time orientation in organizations: Polychronicity and multitasking

This dissertation consists of four studies examining two constructs related to time orientation in organizations: polychronicity and multitasking. The first study investigates the internal structure of polychronicity and its external correlates in a sample of undergraduate students (N = 732). Results converge to support a one-factor model and finds measures of polychronicity to be significantly related to extraversion, agreeableness, and openness to experience. The second study quantitatively reviews the existing research examining the relationship between polychronicity and the Big Five factors of personality. Results reveal a significant relationship between extraversion and openness to experience across studies. Studies three and four examine the usefulness of multitasking ability in the prediction of work related criteria using two organizational samples (N = 175 and 119, respectively). Multitasking ability demonstrated predictive validity, however the incremental validity over that of traditional predictors (i.e., cognitive ability and the Big Five factors of personality) was minimal. The relationships between multitasking ability, polychronicity, and other individual differences were also investigated. Polychronicity and multitasking ability proved to be distinct constructs demonstrating differential relationships with cognitive ability, personality, and performance. Results provided support for multitasking performance as a mediator in the relationship between multitasking ability and overall job performance. Additionally, polychronicity moderated the relationship between multitasking ability and both ratings of multitasking performance and overall job performance in Study four. Clarification of the factor structure of polychronicity and its correlates will facilitate future research in the time orientation literature. Results from two organizational samples point to work related measures of multitasking ability as a worthwhile tool for predicting the performance of job applicants.

Localized surface plasmon resonance biosensors for real-time biomolecular binding study

Surface Plasmon Resonance (SPR) and localized surface plasmon resonance (LSPR) biosensors have brought a revolutionary change to in vitro study of biological and biochemical processes due to its ability to measure extremely small changes in surface refractive index (RI), binding equilibrium and kinetics. Strategies based on LSPR have been employed to enhance the sensitivity for a variety of applications, such as diagnosis of diseases, environmental analysis, food safety, and chemical threat detection. In LSPR spectroscopy, absorption and scattering of light are greatly enhanced at frequencies that excite the LSPR, resulting in a characteristic extinction spectrum that depends on the RI of the surrounding medium. Compositional and conformational change within the surrounding medium near the sensing surface could therefore be detected as shifts in the extinction spectrum. This dissertation specifically focuses on the development and evaluation of highly sensitive LSPR biosensors for in situ study of biomolecular binding process by incorporating nanotechnology. Compared to traditional methods for biomolecular binding studies, LSPR-based biosensors offer real-time, label free detection. First, we modified the gold sensing surface of LSPR-based biosensors using nanomaterials such as gold nanoparticles (AuNPs) and polymer to enhance surface absorption and sensitivity. The performance of this type of biosensors was evaluated on the application of small heavy metal molecule binding affinity study. This biosensor exhibited ∼7 fold sensitivity enhancement and binding kinetics measurement capability comparing to traditional biosensors. Second, a miniaturized cell culture system was integrated into the LSPR-based biosensor system for the purpose of real-time biomarker signaling pathway studies and drug efficacy studies with living cells. To the best of our knowledge, this is the first LSPR-based sensing platform with the capability of living cell studies. We demonstrated the living cell measurement ability by studying the VEGF signaling pathway in living SKOV-3 cells. Results have shown that the VEGF secretion level from SKOV-3 cells is 0.0137 ± 0.0012 pg per cell. Moreover, we have demonstrated bevacizumab drug regulation to the VEGF signaling pathway using this biosensor. This sensing platform could potentially help studying biomolecular binding kinetics which elucidates the underlying mechanisms of biotransportation and drug delivery.

The effects of student -centered and traditional models of teaching on reading skills

A pre-test, post-test, quasi-experimental design was used to examine the effects of student-centered and traditional models of reading instruction on outcomes of literal comprehension and critical thinking skills. The sample for this study consisted of 101 adult students enrolled in a high-level developmental reading course at a large, urban community college in the Southeastern United States. The experimental group consisted of 48 students, and the control group consisted of 53 students. Students in the experimental group were limited in the time spent reading a course text of basic skills, with instructors using supplemental materials such as poems, news articles, and novels. Discussions, the reading-writing connection, and student choice in material selection were also part of the student-centered curriculum. Students in the control group relied heavily on a course text and vocabulary text for reading material, with great focus placed on basic skills. Activities consisted primarily of multiple-choice questioning and quizzes. The instrument used to collect pre-test data was Descriptive Tests of Language Skills in Reading Comprehension; post-test data were taken from the Florida College Basic Skills Exit Test. A MANCOVA was used as the statistical method to determine if either model of instruction led to significantly higher gains in literal comprehension skills or critical thinking skills. A paired samples t-test was also used to compare pre-test and post-test means. The results of the MANCOVA indicated no significant difference between instructional models on scores of literal comprehension and critical thinking. Neither was there any significant difference in scores between subgroups of age (under 25 and 25 and older) and language background (native English speaker and second-language learner). The results of the t-test indicated, however, that students taught under both instructional models made significant gains in on both literal comprehension and critical thinking skills from pre-test to post-test.

On-Line Real-Time Service-Oriented Task Scheduling Using TUF

We present our approach to real-time service-oriented scheduling problems with the objective of maximizing the total system utility. Different from the traditional utility accrual scheduling problems that each task is associated with only a single time utility function (TUF), we associate two different TUFs—a profit TUF and a penalty TUF—with each task, to model the real-time services that not only need to reward the early completions but also need to penalize the abortions or deadline misses. The scheduling heuristics we proposed in this paper judiciously accept, schedule, and abort real-time services when necessary to maximize the accrued utility. Our extensive experimental results show that our proposed algorithms can significantly outperform the traditional scheduling algorithms such as the Earliest Deadline First (EDF), the traditional utility accrual (UA) scheduling algorithms, and an earlier scheduling approach based on a similar model.

Real-time scheduling of embedded applications on multi-core platforms

For the past several decades, we have experienced the tremendous growth, in both scale and scope, of real-time embedded systems, thanks largely to the advances in IC technology. However, the traditional approach to get performance boost by increasing CPU frequency has been a way of past. Researchers from both industry and academia are turning their focus to multi-core architectures for continuous improvement of computing performance. In our research, we seek to develop efficient scheduling algorithms and analysis methods in the design of real-time embedded systems on multi-core platforms. Real-time systems are the ones with the response time as critical as the logical correctness of computational results. In addition, a variety of stringent constraints such as power/energy consumption, peak temperature and reliability are also imposed to these systems. Therefore, real-time scheduling plays a critical role in design of such computing systems at the system level. We started our research by addressing timing constraints for real-time applications on multi-core platforms, and developed both partitioned and semi-partitioned scheduling algorithms to schedule fixed priority, periodic, and hard real-time tasks on multi-core platforms. Then we extended our research by taking temperature constraints into consideration. We developed a closed-form solution to capture temperature dynamics for a given periodic voltage schedule on multi-core platforms, and also developed three methods to check the feasibility of a periodic real-time schedule under peak temperature constraint. We further extended our research by incorporating the power/energy constraint with thermal awareness into our research problem. We investigated the energy estimation problem on multi-core platforms, and developed a computation efficient method to calculate the energy consumption for a given voltage schedule on a multi-core platform. In this dissertation, we present our research in details and demonstrate the effectiveness and efficiency of our approaches with extensive experimental results.

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.

Time Orientation in Organizations: Polychronicity and Multitasking

This dissertation consists of four studies examining two constructs related to time orientation in organizations: polychronicity and multitasking. The first study investigates the internal structure of polychronicity and its external correlates in a sample of undergraduate students (N = 732). Results converge to support a one-factor model and finds measures of polychronicity to be significantly related to extraversion, agreeableness, and openness to experience. The second study quantitatively reviews the existing research examining the relationship between polychronicity and the Big Five factors of personality. Results reveal a significant relationship between extraversion and openness to experience across studies. Studies three and four examine the usefulness of multitasking ability in the prediction of work related criteria using two organizational samples (N = 175 and 119, respectively). Multitasking ability demonstrated predictive validity, however the incremental validity over that of traditional predictors (i.e., cognitive ability and the Big Five factors of personality) was minimal. The relationships between multitasking ability, polychronicity, and other individual differences were also investigated. Polychronicity and multitasking ability proved to be distinct constructs demonstrating differential relationships with cognitive ability, personality, and performance. Results provided support for multitasking performance as a mediator in the relationship between multitasking ability and overall job performance. Additionally, polychronicity moderated the relationship between multitasking ability and both ratings of multitasking performance and overall job performance in Study four. Clarification of the factor structure of polychronicity and its correlates will facilitate future research in the time orientation literature. Results from two organizational samples point to work related measures of multitasking ability as a worthwhile tool for predicting the performance of job applicants.

Localized Surface Plasmon Resonance Biosensors for Real-Time Biomolecular Binding Study

Surface Plasmon Resonance (SPR) and localized surface plasmon resonance (LSPR) biosensors have brought a revolutionary change to in vitro study of biological and biochemical processes due to its ability to measure extremely small changes in surface refractive index (RI), binding equilibrium and kinetics. Strategies based on LSPR have been employed to enhance the sensitivity for a variety of applications, such as diagnosis of diseases, environmental analysis, food safety, and chemical threat detection. In LSPR spectroscopy, absorption and scattering of light are greatly enhanced at frequencies that excite the LSPR, resulting in a characteristic extinction spectrum that depends on the RI of the surrounding medium. Compositional and conformational change within the surrounding medium near the sensing surface could therefore be detected as shifts in the extinction spectrum. This dissertation specifically focuses on the development and evaluation of highly sensitive LSPR biosensors for in situ study of biomolecular binding process by incorporating nanotechnology. Compared to traditional methods for biomolecular binding studies, LSPR-based biosensors offer real-time, label free detection. First, we modified the gold sensing surface of LSPR-based biosensors using nanomaterials such as gold nanoparticles (AuNPs) and polymer to enhance surface absorption and sensitivity. The performance of this type of biosensors was evaluated on the application of small heavy metal molecule binding affinity study. This biosensor exhibited ~7 fold sensitivity enhancement and binding kinetics measurement capability comparing to traditional biosensors. Second, a miniaturized cell culture system was integrated into the LSPR-based biosensor system for the purpose of real-time biomarker signaling pathway studies and drug efficacy studies with living cells. To the best of our knowledge, this is the first LSPR-based sensing platform with the capability of living cell studies. We demonstrated the living cell measurement ability by studying the VEGF signaling pathway in living SKOV-3 cells. Results have shown that the VEGF secretion level from SKOV-3 cells is 0.0137 ± 0.0012 pg per cell. Moreover, we have demonstrated bevacizumab drug regulation to the VEGF signaling pathway using this biosensor. This sensing platform could potentially help studying biomolecular binding kinetics which elucidates the underlying mechanisms of biotransportation and drug delivery.