As a society, we seek to have our young people, including the gifted, be healthy and happy, and go to good schools with good teachers. Framed by Sayler's theoretical model of giftedness and thriving, this study examined psychological constructs (i.e. general self-efficacy, theories of intelligence, hope, gratitude, religiosity, disposition, and resiliency) to determine their mediating effect on personal well-being and academic success in gifted college students. The 213 subjects for this study included gifted college students from two distinct programs at the University of North Texas. One hundred twenty-two participants were students from the Texas Academy of Mathematics and Science (TAMS). TAMS is an early-college entrance program allowing gifted students to enter college after their sophomore year of high school. Ninety-one participants attended the UNT Honors College. Honors College students are gifted students who enter college after high school graduation. Latent transition, latent class, general linear model repeated measures, and regression analyses were used in the examination of the data. Results of the study revealed that positive disposition and hope-agency were significantly related to the development of personal well-being for gifted students during their first year of college. The ability to identify pathways to goals and the self-theory of intelligence as a fixed trait were significantly related to academic success during the first year at college. Knowledge of psychological constructs that are facilitative of the positive personal well-being and academic achievement helps parents, teachers, administrators, and counselors prepare gifted students for success in college.

The goal of this dissertation is to demonstrate that data from a remotely located building can be utilized for energy modeling of a similar type of building and to demonstrate how to use this remote data without physically moving the data from one server to another using Virtual Information Fabric Infrastructure (VIFI). In order to achieve this goal, firstly an EnergyPlus model was created for Greek Life Center, a campus building located at University of North Texas campus at Denton in Texas, USA. Three thermal comfort models of Fanger model, Pierce two-node model and KSU two-node model were compared in order to find which one of these three models is most accurate to predict occupant thermal comfort. This study shows that Fanger's model is most accurate in predicting thermal comfort. Secondly, an experimental data pertaining to lighting usage and occupancy in a single-occupancy office from Carnegie Mellon University (CMU) has been implemented in order to perform energy analysis of Greek Life Center assuming that occupants in this building's offices behave similarly as occupants in CMU. Thirdly, different data types, data formats and data sources were identified which are required in order to develop a city-scale urban building energy model (CS-UBEM). Two workflows were created, one for an individual scale building energy model and another one for CS-UBEM. A new innovative infrastructure called as Virtual Information Fabric Infrastructure (VIFI) has been introduced in this dissertation. The workflows proposed in this study will demonstrate in the future work that by using VIFI infrastructure to develop building energy models there is a potential of using data for remote servers without actually moving the data. It has been successfully demonstrated in this dissertation that data located at remote location can be used credibly to predict energy consumption of a newly built building. When the remote experimental data of both lighting and occupancy are implemented, 4.57% energy savings was achieved in the Greek Life Center energy model.