The study is designed to assess the presence or absence of recognizable planning processes within the savings and loan industry in the Dallas/Ft. Worth metroplex. Planning processes found are analyzed as to their content and scope in order to describe them in as accurate a manner as possible.

As airspace congestion becomes increasingly more common, one of the primary places airspace congestion is felt today, and will only continue to increase, is in areas where more than one major airport interact. We will call these groups of interdependent airports a metroplex; a term originally coined to describe large metropolitan areas where more than one city of equal (or near equal) size or importance. These metroplex areas are of particular importance in understanding future capacity demands because many of these areas are currently experiencing problems with meeting the current demand, and demand is only projected to increase as air travel becomes more popular. Many of these capacity issues have been identified in the FAA's Future Airport Capacity Task (FACT). From the second FACT report, it is stated that "the FACT 1 analysis revealed that many of our hub airports and their associated metropolitan areas could be expected to experience capacity constraints (i.e. unacceptable levels of delay) by 2013 and 2020, even if the planned improvements envisioned at that time were completed." This analysis shows that the current methods of expanding airports will not scale with the growing demand. To address this growing demand, a three part solution is proposed. The first step is to properly identify the metroplex areas to be evaluated. While the FACT reports serve to identify areas where capacity growth does not meet demand, these areas are not grouped into metroplexes. To do this grouping, an interaction metric was developed based on airport distance and traffic volume. This interaction metric serves as a proxy for how the existence of a second airport impacts the operation of the first. This pairwise metric was then computed for all commercial airports in the US and were grouped into metroplexes using a clustering algorithm. The second obstacle was to develop a tool to evaluate each metroplex as new algorithms were tested. A discrete event based simulation was developed to model each link in the airspace structure for each aircraft that enters the TRACON. This program tracks the delay each aircraft is required to accumulate in holding patterns or traffic trombones. A third and final method discussed here was an optimization program that can be used to schedule aircraft that are entering the TRACON to perform small modifications in their speed while en route to reduce the overall delay (both en route and in the TRACON). While formal optimization methods for scheduling aircraft arrivals have been presented before, the computational complexity has greatly prevented such algorithms from being used to schedule many aircraft in a dense schedule. This is because mixed integer programming (MIP) is a NP-hard problem. Practically, this means that the solution time can grow exponentially as the problem size (number of aircraft) increases. To address this issue, a Benders' decomposition scheme was introduced that allows solutions to be computed in near real-time on commodity hardware. These solutions can be evaluated and compared against the currently used TMA algorithm to show surprising gains in high density traffic.

Urban landscapes are quickly replacing native habitat around the world. As wildlife and people increasingly overlap in their shared space and resources, so does the potential for human-wildlife conflict, especially with predators. Bobcats (Lynx rufus) are a top predator in several urban areas across the United States and a potential contributor to human-carnivore conflicts. This study evaluated the movements and habitat use of bobcats in the Dallas-Fort Worth (DFW), Texas metroplex. Spatial data were collected from 10 bobcats via Global Positioning Satellite (GPS) for approximately one year. Average home range size was 4.60 km2 (n=9, SE=0.99 km2) for all resident bobcats, 3.48 km2 (n=5, SE=1.13 km2) for resident females, and 6.00 km2 (n=4, SE=1.61 km2) for resident males. Resource selection function (RSF) models show that bobcats avoid areas close to and far from grasslands and low-medium development, while selecting for these areas at intermediate distances. Bobcats also selected areas closer to developed open space, agricultural areas, and railroads. In addition, camera trap data analyzed with spatially explicit capture-recapture (SECR) models informed by the RSF results estimated a population density of 0.64 bobcats/km2 (SE = 0.22). Bobcats in DFW have significantly smaller home ranges and occur at higher densities compared to rural bobcat populations. Home ranges were also slightly smaller and densities higher than the most closely similar peri-urban bobcat studies. These differences likely arise due to the abundant urban prey species the DFW landscape provides despite limited space and habitat for bobcats. The dense urban development surrounding this population of bobcats may also discourage dispersing from the area, and contributing to higher densities. These results provide information to facilitate management of urban bobcats by providing new insight into how bobcats live amidst people in urban areas.

Thesis (D. Min.)--Perkins School of Theology, Southern Methodist University, 1986. / Abstract. Includes bibliographical references (leaves 123-126).

Thesis (D. Min.)--Perkins School of Theology, Southern Methodist University, 1986. / Abstract. Includes bibliographical references (leaves 123-126).

The primary motivation for conducting this study was the apparent conflict between Texas Education Agency guidelines for a vocational cooperative education program and the realities of actual program operation. In the program the mid-management student receives instruction, through a cooperative arrangement between the college and employers, in both academic courses and related vocational instruction.

Surfactants are used in a wide assortment of "down-the-drain" consumer products, yet they are often discharged in wastewater treatment plant effluent into receiving water, potentially causing environmental harm. The objective of this project was to predict surfactant toxic units and in-stream nutrients in the upper Trinity River watershed. Surface and pore water samples were collected in late summer 2005. General chemistries and surfactant toxic units were calculated. GIS models of anthropogenic and natural factors were collected and analyzed according to subwatersheds. Multiple regression analyses using the Maximum R2 improvement method were performed to predict surfactant toxic units and in-stream nutrients using GIS and in-stream values. Both geospatial and in-stream parameters generated multiple regression models for surfactant surface and pore water toxic units, as well as in-stream nutrients, with high R2 values. Thus, GIS and in-stream parameter modeling have the potential to be reliable and inexpensive method of predicting surfactant toxic units and nutrient loading in the upper Trinity River watershed.