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The Landscape Legacies of Gas Drilling in North Texas

Description: In North Texas, the Barnett Shale underlies large areas of the Dallas-Fort Worth Metroplex (DFW), which magnifies debates about the externalities of shale gas development (SGD). Continued demand for natural gas and expansive urbanization in DFW will cause more people to come in contact with drilling rigs, gas transport, and other urban shale gas landscapes. Thousands of gas wells within the DFW region occupy a large, yet scattered land surface area. DFW city planners, elected officials, and other stakeholders must deal with current and future urban growth and the surface impacts that are associated with gas development. This research examines how shale gas landscapes affect urban land uses, landscapes, and patterns of development in DFW. The study focuses on multiple fast growing DFW municipalities that also have high numbers of gas well pad sites. This study asks what are the spatial characteristics of gas well production sites in DFW and how do these sites vary across the region; how do gas well production sites affect urban growth and development; and how are city governments and surface developers responding to gas well production sites, and what are the dominant themes of contestation arising around gas well production sites and suburban growth?
Date: May 2016
Creator: Sakinejad, Michael C
Partner: UNT Libraries

Dismantling the Psychiatric Ghetto: Evaluating a Blended-Clinic Approach to Supportive Housing in Houston, Texas

Description: Locational decisions based on stigma and low funding have handicapped the efficiency of community based mental healthcare in the United States since 1963. However, the pattern of services in the 21st century American South remains largely unknown. This thesis addresses this gap in knowledge by using a mixed methodology including location allocation, descriptive statistics, and qualitative site visits to explore the geography of community clinics offering both physical and mental health services. The City of Houston has proposed using these facilities to anchor new supportive housing, but introducing more fixed costs to a mismatched system could create more problems than solutions. The findings of this study suggest the presence of an unnecessary concentration of services in the central city and a spatial mismatch between accessible clinics and the poor, sick people in need. Furthermore, this research reveals a new suburban pattern of vulnerability, calling into question long-held assumptions about the vulnerability of the inner city. Building supportive housing around existing community clinics, especially in the central city, may further concentrate vulnerable people thereby contributing to intensifying patterns of service-seeking drift and the continued traumatization of mentally ill homeless persons in Houston.
Date: December 2014
Creator: Lester, Katherine Ann
Partner: UNT Libraries

County Level Population Estimation Using Knowledge-Based Image Classification and Regression Models

Description: This paper presents methods and results of county-level population estimation using Landsat Thematic Mapper (TM) images of Denton County and Collin County in Texas. Landsat TM images acquired in March 2000 were classified into residential and non-residential classes using maximum likelihood classification and knowledge-based classification methods. Accuracy assessment results from the classified image produced using knowledge-based classification and traditional supervised classification (maximum likelihood classification) methods suggest that knowledge-based classification is more effective than traditional supervised classification methods. Furthermore, using randomly selected samples of census block groups, ordinary least squares (OLS) and geographically weighted regression (GWR) models were created for total population estimation. The overall accuracy of the models is over 96% at the county level. The results also suggest that underestimation normally occurs in block groups with high population density, whereas overestimation occurs in block groups with low population density.
Date: August 2010
Creator: Nepali, Anjeev
Partner: UNT Libraries

Analyzing Tuberculosis Vulnerabilities and Variables in Tarrant County

Description: Over 9 million new cases of tuberculosis (TB) were reported worldwide in 2013. While the TB rate is much lower in the US, its uneven distribution and associated explanatory variables require interrogation in order to determine effective strategies for intervention and control. However, paucity of case data at fine geographic scales precludes such research. This research, using zip code level data from 837 confirmed TB cases in Tarrant County obtained from Texas Department of State Health Services, explores and attempts to explain the spatial patterns of TB and related risk markers within a framework of place vulnerability. Readily available census data is then used to characterize the spatial variations in TB risk. The resulting model will enable estimations of the geographic differences in TB case variables using this readily available census data instead of time-consuming and expensive individual data collection.
Date: December 2016
Creator: McGlone, John
Partner: UNT Libraries

Parcel-Based Change Detection Using Multi-Temporal LiDAR Data in the City of Surrey, British Columbia, Canada

Description: Change detection is amongst the most effective critical examination methods used in remote sensing technology. In this research, new methods are proposed for building and vegetation change detection using only LiDAR data without using any other remotely sensed data. Two LiDAR datasets from 2009 and 2013 will be used in this research. These datasets are provided by the City of Surrey. A Parcel map which shows parcels in the study area will be also used in this research because the objective of this research is detecting changes based on parcels. Different methods are applied to detect changes in buildings and vegetation respectively. Three attributes of object –slope, building volume, and building height are derived and used in this study. Changes in buildings are not only detected but also categorized based on their attributes. In addition, vegetation change detection is performed based on parcels. The output shows parcels with a change of vegetation. Accuracy assessment is done by using measures of completeness, correctness, and quality of extracted regions. Accuracy assessments suggest that building change detection is performed with better results.
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Date: December 2016
Creator: Yigit, Aykut
Partner: UNT Libraries

Spatial Analysis of North Central Texas Traffic Fatalities 2001-2006

Description: A traditional two dimensional (planar) statistical analysis was used to identify the clustering types of North Central Texas traffic fatalities occurring in 2001-2006. Over 3,700 crash locations clustered in ways that were unlike other researched regions. A two dimensional (x and y coordinates) space was manipulated to mimic a one dimensional network to identify the tightest clustering of fatalities in the nearly 400,000 crashes reported from state agencies from 2003-2006. The roadway design was found to significantly affect crash location. A one dimensional (linear) network analysis was then used to measure the statistically significant clustering of flow variables of after dark crashes and daylight crashes. Flow variables were determined to significantly affect crash location after dark. The linear and planar results were compared and the one dimensional, linear analysis was found to be more accurate because it did not over detect the clustering of events on a network.
Date: December 2010
Creator: Rafferty, Paula S.
Partner: UNT Libraries

An Investigation of the Relationship between HIV and Prison Facilities in Texas: The Geographic Variation and Vulnerable Neighborhood Characteristics

Description: Previous research suggests that prisons may be fueling the spread of HIV infection in the general population. In 2005, the HIV rate was more than 2.5 times higher in US prison populations. Environmental factors in prisons such as illicit drug use and unprotected sexual activities can be conducive for HIV transmission. Because the vast majority of prison inmates are incarcerated for less than three years, transmission of HIV between prison inmates and members of the general population may occur at a high rate. The environment in which an individual lives and the entities that comprise it affect the health of that person. Thus the location of prisons within communities, as well as socio-demographic characteristics may influence the geography of HIV infection. HIV surveillance data, obtained from the Texas Department of State Health Services, were used to investigate the relationship between the location of prison units in Texas and HIV infection rates in the surrounding zip codes. The results suggest that HIV prevalence rates are higher among geographic areas in close proximity to a prison unit. With continued behavioral risks and low treatment adherence rates among individuals infected with HIV, there is a possibility of increased HIV prevalence. Vulnerable places, locations with higher HIV prevalence, should be targeted for resource allocation and HIV prevention and care service. This study illustrates the importance of spatial analysis of places vulnerable to increased HIV prevalence in creating more effective public health prevention strategies and interventions.
Date: August 2011
Creator: Kutch, Libbey
Partner: UNT Libraries

Comparison of IKONOS Derived Vegetation Index and LiDAR Derived Canopy Height Model for Grassland Management.

Description: Forest encroachment is understood to be the main reason for prairie grassland decline across the United States. In Texas and Oklahoma, juniper has been highlighted as particularly opportunistic. This study assesses the usefulness of three remote sensing techniques to aid in locating the areas of juniper encroachment for the LBJ Grasslands in Decatur, Texas. An object based classification was performed in eCognition and final accuracy assessments placed the overall accuracy at 94%, a significant improvement over traditional pixel based methods. Image biomass was estimated using normalized difference vegetation index (NDVI) for 1 meter resolution IKONOS winter images. A high correlation between the sum of NDVI for tree objects and field tree biomass was determined where R = 0.72, suggesting NDVI sum of a tree area is plausible. However, issues with NDVI saturation and regression produced unrealistically high biomass estimates for large NDVI. Canopy height model (CHM) derived from 3-5m LiDAR data did not perform as well. LiDAR typically used for digital elevation model (DEM) production was acquired for the CHM and produced correlations of R = 0.26. This suggests an inability for this particular dataset to identify juniper trees. When points that registered a tree height where correlated with field values, an R = 0.5 was found, suggesting denser point spacing would be necessary for this type of LiDAR data. Further refining of the methods used in this study could yield such information as the amount of juniper tree for a given location, fuel loads for prescribed burns and better information for the best approach to remove the juniper and ultimately management juniper encroachment into grasslands.
Date: December 2009
Creator: Parker, Gary
Partner: UNT Libraries

High Resolution Satellite Images and LiDAR Data for Small-Area Building Extraction and Population Estimation

Description: Population estimation in inter-censual years has many important applications. In this research, high-resolution pan-sharpened IKONOS image, LiDAR data, and parcel data are used to estimate small-area population in the eastern part of the city of Denton, Texas. Residential buildings are extracted through object-based classification techniques supported by shape indices and spectral signatures. Three population indicators -building count, building volume and building area at block level are derived using spatial joining and zonal statistics in GIS. Linear regression and geographically weighted regression (GWR) models generated using the three variables and the census data are used to estimate population at the census block level. The maximum total estimation accuracy that can be attained by the models is 94.21%. Accuracy assessments suggest that the GWR models outperformed linear regression models due to their better handling of spatial heterogeneity. Models generated from building volume and area gave better results. The models have lower accuracy in both densely populated census blocks and sparsely populated census blocks, which could be partly attributed to the lower accuracy of the LiDAR data used.
Date: December 2009
Creator: Ramesh, Sathya
Partner: UNT Libraries

Neural Tube Defect, Heart Defect, Oral Cleft and Their Geospatial Associations with Supermarket and Convenience Stores in the City of Dallas, Texas

Description: Birth defects are the leading cause of infant death in the United States. Research has linked poor maternal micronutrient intake to birth defects including neural tube defects, heart defects, and oral clefts. After investigating spatial patterns of these birth defects in the City of Dallas and the neighborhood characteristics within clusters, geospatial access to supermarkets and convenience stores measured by proximity and concentrations are examined as environmental risk factors for nutrition-related birth defects. Spatial clusters of all three nutrition-related birth defects exist in the City of Dallas. Cluster for NTD occurs in vulnerable places with lower income and high minority population specifically Hispanics with no supermarkets. Cluster for heart defects mostly occurs in high income and predominantly white neighborhoods with many supermarkets. Clusters of oral clefts mostly occurs in middle-class income with relatively high minority populations with many convenience stores. For the entire study area, geographical access to supermarkets that include healthy foods are shown to be spatially reachable from most of mothers of infants with nutrition-related birth defects as well as convenience stores that typically include the majority of unhealthy processed foods with very few nutrients. Thus, not only easy geographical access to healthy food vendors but to convenience stores with low quality produces is observed at the same time.
Date: August 2013
Creator: Miyakado, Haruna
Partner: UNT Libraries

Spatial Mismatch Between Hiv Infection and Access to Hiv Service Facilities in Texas

Description: Since 2004, the number of people living with HIV (PLWH) has steadily increased by about 5% and currently, the number in Texas is about 86,000. Though the National HIV/AIDS Strategic Plan seeks to ensure “unfettered access to quality healthcare”, barriers to access still exist especially among minority populations. This study examines the relationship between HIV infection rates and the geographic location of HIV service centers with a focus on 4 counties: namely, Dallas, Denton, Harris and Tarrant. The goal is to show whether there is a spatial mismatch between HIV rates and service providers. Are service facilities located in zip codes where they are most needed? Using the vulnerability framework and the Inverse Care Law (ICL), we address the research question using demographic variables (race/ethnicity, sex, poverty, education attainment) and HIV data. Our results show that extreme vulnerable zip codes have high HIV rates and closest proximity to HIV service providers.
Date: August 2013
Creator: Aggrey Korsah, Emmanuel
Partner: UNT Libraries

Automated Treetop Detection and Tree Crown Identification Using Discrete-return Lidar Data

Description: Accurate estimates of tree and forest biomass are essential for a wide range of applications. Automated treetop detection and tree crown discrimination using LiDAR data can greatly facilitate forest biomass estimation. Previous work has focused on homogenous or single-species forests, while few studies have focused on mixed forests. In this study, a new method for treetop detection is proposed in which the treetop is the cluster center of selected points rather than the highest point. Based on treetop detection, tree crowns are discriminated through comparison of three-dimensional shape signatures. The methods are first tested using simulated LiDAR point clouds for trees, and then applied to real LiDAR data from the Soquel Demonstration State Forest, California, USA. Results from both simulated and real LiDAR data show that the proposed method has great potential for effective detection of treetops and discrimination of tree crowns.
Date: May 2013
Creator: Liu, Haijian
Partner: UNT Libraries

Assessing the Role of Smaller Format Retailers on the Food Desert Landscape in Dallas, Texas

Description: Many policy and business decisions regarding food deserts in the U.S. are based on the United States Department of Agriculture (USDA) definition of a food desert. This definition only includes large/national chain grocery retailers, based on the assumption that these major retailers are the only affordable sources of food contributing to balanced diets. As alternative distribution channels, including smaller stores, start to include groceries in their product offering, the need to consider the role of other businesses in the food retailing environment should be addressed. This thesis assesses the role of smaller format grocery retailers (small local grocers, convenience stores, gas stations, dollar stores, and drug stores) in shaping the food desert landscape in Dallas, Texas. The analysis evaluates the products offered in these stores, and then identifies the difference these stores make when included in the USDA analysis. This was done by collecting in-store data to determine the variety of products offered, the affordability of those products, and the overall healthfulness of the store. In addition, the gaps in supply and demand were identified in the USDA-defined food deserts in order to identify the impact any smaller format retailer may have. The findings suggest that, overall, smaller format retailers do offer a variety of products needed for a balanced diet. However, the products in these stores are mostly not affordable, and most stores offer more unhealthy foods, than unhealthy. Overall, results suggest dollar stores may play a role in alleviating the impact of food deserts.
Date: May 2013
Creator: Regan, Amanda D.
Partner: UNT Libraries

Quantitative Comparison of Lidar Data and User-generated Three-dimensional Building Models From Google Building Maker

Description: Volunteered geographic information (VGI) has received increased attention as a new paradigm for geographic information production, while light detection and ranging (LiDAR) data is widely applied to many fields. This study quantitatively compares LiDAR data and user-generated 3D building models created using Google Building Maker, and investigate the potential applications of the quantitative measures in support of rapid disaster damage assessment. User-generated 3D building models from Google Building Maker are compared with LiDAR-derived building models using 3D shape signatures. Eighteen 3D building models are created in Fremont, California using the Google Building Maker, and six shape functions (distance, angle, area, volume, slope, and aspect) are applied to the 18 LiDAR-derived building models and user-generated ones. A special case regarding the comparison between LiDAR data and building models with indented walls is also discussed. Based on the results, several conclusions are drawn, and limitations that require further study are also discussed.
Date: August 2012
Creator: Liu, Yang
Partner: UNT Libraries

Assessment of Post-earthquake Building Damage Using High-resolution Satellite Images and LiDAR Data - a Case Study From Port-au-prince, Haiti

Description: When an earthquake happens, one of the most important tasks of disaster managers is to conduct damage assessment; this is mostly done from remotely sensed data. This study presents a new method for building detection and damage assessment using high-resolution satellite images and LiDAR data from Port-au-Prince, Haiti. A graph-cut method is used for building detection due to its advantages compared to traditional methods such as the Hough transform. Results of two methods are compared to understand how much our proposed technique is effective. Afterwards, sensitivity analysis is performed to show the effect of image resolution on the efficiency of our method. Results are in four groups. First: based on two criteria for sensitivity analysis, completeness and correctness, the more efficient method is graph-cut, and the final building mask layer is used for damage assessment. Next, building damage assessment is done using change detection technique from two images from period of before and after the earthquake. Third, to integrate LiDAR data and damage assessment, we showed there is a strong relationship between terrain roughness variables that are calculated using digital surface models. Finally, open street map and normalized digital surface model are used to detect possible road blockages. Results of detecting road blockages showed positive values of normalized digital surface model on the road centerline can represent blockages if we exclude other objects such as cars.
Date: August 2014
Creator: Koohikamali, Mehrdad
Partner: UNT Libraries

Spatio-temporal Variation of Nitrate Levels in Groundwater in Texas, 1970 to 2010

Description: This study looks at spatial variation of groundwater nitrate in Texas and its fluctuations at 10 year increments using data from the Texas Water Development Board. While groundwater nitrate increased in the Ogallala and Seymour aquifers across the time period, the overall rate in Texas appears to be declining as time progresses. However, the available data is limited. Findings show that a much more targeted, knowledge based strategy for sampling would not only reduce the cost of water quality analysis but also reduce the risk of error in these analyses by providing a more realistic picture of the spatial variation of problem contaminants, thereby giving decision-makers a clearer picture on how best to handle the reduction and elimination of problem contaminants.
Date: December 2012
Creator: Rice, Susan C.
Partner: UNT Libraries

The Geography of Maternal Mortality in Nigeria

Description: Maternal mortality is the leading cause of death among women in Nigeria, especially women aged between 15 and 19 years. This research examines the geography of maternal mortality in Nigeria and the role of cultural and religious practices, socio-economic inequalities, urbanization, access to pre and postnatal care in explaining the spatial pattern. State-level data on maternal mortality rates and predictor variables are presented. Access to healthcare, place of residence and religion explains over 74 percent of the spatial pattern of maternal mortality in Nigeria, especially in the predominantly Muslim region of northern Nigeria where poverty, early marriage and childbirth are at its highest, making them a more vulnerable population. Targeting vulnerable populations in policy-making procedures may be an important strategy for reducing maternal mortality, which would also be more successful if other socio-economic issues such as poverty, religious and health care issues are promptly addressed as well.
Date: May 2012
Creator: Ebeniro, Jane
Partner: UNT Libraries

A Multiscalar Analysis of Buruli Ulcer in Ghana: Environmental and Behavioral Factors in Disease Prevalence

Description: Buruli ulcer (BU), an infectious disease caused by Mycobacterium ulcerans, is the third most common mycobacterial disease after leprosy and tuberculosis and a WHO-defined neglected tropical disease. Despite years of research, the mode of transmission of BU remains unknown. This master’s thesis provides an integrated spatial analysis of disease dynamics in Ghana, West Africa, an area of comparatively high BU incidence. Within a case/matched control study design, environmental factors associated with BU infection and spatial behaviors are investigated to uncover possible links between individual daily activity spaces and terrains of risk across disturbed landscapes. This research relies upon archival and field-collected data and analyses conducted with geographical information systems (GIS).
Date: May 2012
Creator: Ferring, David
Partner: UNT Libraries

Emergency Fire Response in Ghana: The Case of Fire Stations in Kumasi

Description: Comprehensive emergency management and response is crucial for disaster prevention and health emergencies. However, in African countries with an abundance of natural disasters and a rising surge in cardiovascular and obstetric emergencies, little research exists on emergency response. This study examines the fire emergency response in Kumasi Metropolitan Assembly (KMA), Ghana's second largest city. We use Geographic Information Systems (GIS) tools including location -allocation modeling to evaluate the existing system of fire facilities, identify gaps in service, and suggest locations for new fire stations to maximize population coverage. Our results show that fire stations within KMA are poorly distributed and large portions of the metropolis are underserved, a situation that is partly responsible for the huge losses of lives and property during fire outbreaks.
Date: May 2017
Creator: Boakye, Kwadwo Adu
Partner: UNT Libraries

The Geography of Maternal Health Indicators in Ghana

Description: Ghana is identified among the developing countries with high maternal mortality ratio in Africa. This study unpacked the Demographic and Health Survey data by examining the maternal health indicators at the district level using GIS methods. Understanding the geographic patterns of antenatal care, place of delivery, and skilled birth attendants at the small scale will help to formulate and plan for location-specific health interventions that can improve maternal health care behavior among Ghanaian women. Districts with high rates and low rates were identified. Place of residence, Gini-Coefficient, wealth status, internet access, and religious affiliation were used to explore the underlying factors associated with the observed patterns. Economic inequality was positively associated with increased use of maternal health care services. The ongoing free maternal health policy serves as a cushion effect for the economic inequality among the districts in the Northern areas. Home delivery is common among the rural districts and is more prominent mostly in the western part of Northern Region and southwest of Upper West. Educating women about the free maternal health policy remains the most viable strategy for positive maternal health outcomes and in reducing MMR in Ghana.
Date: May 2017
Creator: Iyanda, Ayodeji Emmanuel
Partner: UNT Libraries

Residential Grid-Connected Photovoltaics Adoption in North Central Texas: Lessons from the Solarize Plano Project

Description: Residential Grid-Connected Photovoltaics (GPV) systems hold remarkable promise in their potential to reduce energy use, air pollution, greenhouse gas emissions, and energy costs to consumers, while also providing grid efficiency and demand-side management benefits to utilities. Broader adoption of customer-sited GPV also has the potential to transform the traditional model of electricity generation and delivery. Interest and activity has grown in recent years to promote GPV in north central Texas. This study employs a mixed methods design to better understand the status of residential GPV adoption in the DFW area, and those factors influencing a homeowner's decision of whether or not to install a system. Basic metrics are summarized, including installation numbers, distribution and socio-demographic information for the case study city of Plano, the DFW region, Texas, and the United States. Qualitative interview methods are used to gain an in-depth understanding of the factors influencing adoption for the Solarize Plano case study participants; to evaluate the effectiveness of the Solarize Plano program; and to identify concepts that may be regionally relevant. Recommendations are presented for additional research that may advance GPV adoption in north central Texas.
Date: August 2016
Creator: Jack, Katherine G.
Partner: UNT Libraries

Computational Methods for Vulnerability Analysis and Resource Allocation in Public Health Emergencies

Description: POD (Point of Dispensing)-based emergency response plans involving mass prophylaxis may seem feasible when considering the choice of dispensing points within a region, overall population density, and estimated traffic demands. However, the plan may fail to serve particular vulnerable sub-populations, resulting in access disparities during emergency response. Federal authorities emphasize on the need to identify sub-populations that cannot avail regular services during an emergency due to their special needs to ensure effective response. Vulnerable individuals require the targeted allocation of appropriate resources to serve their special needs. Devising schemes to address the needs of vulnerable sub-populations is essential for the effectiveness of response plans. This research focuses on data-driven computational methods to quantify and address vulnerabilities in response plans that require the allocation of targeted resources. Data-driven methods to identify and quantify vulnerabilities in response plans are developed as part of this research. Addressing vulnerabilities requires the targeted allocation of appropriate resources to PODs. The problem of resource allocation to PODs during public health emergencies is introduced and the variants of the resource allocation problem such as the spatial allocation, spatio-temporal allocation and optimal resource subset variants are formulated. Generating optimal resource allocation and scheduling solutions can be computationally hard problems. The application of metaheuristic techniques to find near-optimal solutions to the resource allocation problem in response plans is investigated. A vulnerability analysis and resource allocation framework that facilitates the demographic analysis of population data in the context of response plans, and the optimal allocation of resources with respect to the analysis are described.
Date: August 2015
Creator: Indrakanti, Saratchandra
Partner: UNT Libraries

Influence of the Choice of Disease Mapping Method on Population Characteristics in Areas of High Disease Burdens

Description: Disease maps are powerful tools for depicting spatial variations in disease risk and its underlying drivers. However, producing effective disease maps requires careful consideration of the statistical and spatial properties of the disease data. In fact, the choice of mapping method influences the resulting spatial pattern of the disease, as well as the understanding of its underlying population characteristics. New developments in mapping methods and software in addition to continuing improvements in data quality and quantity are requiring map-makers to make a multitude of decisions before a map of disease burdens can be created. The impact of such decisions on a map, including the choice of appropriate mapping method, not been addressed adequately in the literature. This research demonstrates how choice of mapping method and associated parameters influence the spatial pattern of disease. We use four different disease-mapping methods – unsmoothed choropleth maps, smoothed choropleth maps produced using the headbanging method, smoothed kernel density maps, and smoothed choropleth maps produced using spatial empirical Bayes methods and 5-years of zip code level HIV incidence (2007- 2011) data from Dallas and Tarrant Counties, Texas. For each map, the leading population characteristics and their relative importance with regards to HIV incidence is identified using a regression analysis of a CDC recommended list of socioeconomic determinants of HIV. Our results show that the choice of mapping method leads to different conclusions regarding the associations between HIV disease burden and the underlying demographic and socioeconomic characteristics. Thus, the choice of mapping method influences the patterns of disease we see or fail to see. Accurate depiction of areas of high disease burden is important for developing and targeting appropriate public health interventions.
Date: December 2015
Creator: Desai, Khyati Sanket
Partner: UNT Libraries