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A key purpose of the transportation system is to provide access to critical services such as grocery stores. Maintaining food access during an emergency or other disruption is all the more important, particularly for vulnerable households. Most people in the United States rely on the use of private automobiles for grocery shopping. Thus, disruptions to road networks due to heavy precipitation, flooding, or even major maintenance and repair projects present notable threats to accessibility. Regional planning models that address food accessibility issues (not all do) typically do not consider households’ familiarity with grocery locations. However, during a disruptive event, a household’s familiarity with at least one available route to a retail grocery location becomes paramount. Identifying the roadways that are most critical to food access can help decision makers devise strategies to mitigate the risks of food insecurity for vulnerable households and populations.Researchers at the University of Vermont developed a methodology that provides an ordinal measure of demand-side food access. It takes into account the spatial distribution of both the origin and destination, the topology of the road network, and the characteristics of the roadway network such as capacities, volumes, and travel speeds. The analysis considers household familiarity with retail grocery locations, destination weighting to account for retail grocery characteristics (square footage), and origin weighting to account for household vulnerability. The researchers demonstrated the methodology using the travel demand model for Chittenden County, Vermont. This policy brief summarizes the findings from that research and provide policy implications.View the NCST Project Webpage

This project focuses on modeling access to food locations by identifying the most critical roadway links in a transportation network. This project extends the Critical Closeness Accessibility (CCA) measure developed by Novak and Sullivan (2014) to identify the roadway infrastructure components that are most critical with respect to food accessibility. Specifically, origin and destination weighting are included for the application of food security, where origins are weighted according to household vulnerability and destinations are weighted by retail-grocery square footage. The CCA is further extended by calibrating the trip impedance constant, ω, in the original formulation of the CCA with actual grocery-shopping data from the National Household Travel Survey. This calibration modifies the functional form of the accessibility measure to address trips focused on food access and thus incorporates realistic travel expectations for retail grocery familiarity of households. The project also provides a unique method for estimating household-level vulnerability characteristics using population synthesis. The modification of the CCA to address food accessibility can be used to support more targeted investment in transportation assets, as the CCA is indexed to specific roadway links in the network. The methodology is demonstrated using the Travel Demand Model of Chittenden County, Vermont.View the NCST Project Webpage

We have developed a text mining system that can be used as an add-on for Orange, a data mining platform. Orange envelops a set of supervised and unsupervised machine learning methods that benefit a typical text mining platform and therefore offers an excellent foundation for development. We have studied the field of text mining and reviewed several open-source toolkits to define its base components. We have included widgets that enable retrieval of data from remote repositories, such as PubMed and New York Times. The pre-processing was designed to include transformation of documents to vectors, stop word removal, lemmatization and stemming. The results can be visualized via widgets such as the word cloud. Our goal was to develop widgets that can be easily incorporated into the existing Orange workflow, can be upgraded with additional widgets, and perform well in a visual programming environment.

BackgroundBlack young men who have sex with men (BYMSM) experience higher human immunodeficiency virus (HIV) incidence than their white and Latino counterparts. ObjectiveThe aim of our study was to understand BYMSM’s preferences for mobile phone–based HIV prevention and treatment in order to inform culturally tailored interventions to reduce the spread of HIV and improve HIV treatment outcomes in this population. MethodsQualitative focus groups (N=6) with BYMSM aged 18-29 years (N=41; 46%, 19/41 HIV-positive) were conducted to elucidate their preferences for the design and delivery of mobile phone–based HIV prevention and treatment interventions. A modified grounded theory approach to data analysis was undertaken using ATLAS.ti textual analysis software. ResultsParticipants preferred holistic health interventions that did not focus exclusively on HIV prevention and treatment. Issues of privacy and confidentiality were paramount. Participants preferred functionality that enables discreet connections to culturally competent health educators and treatment providers who can address the range of health and psychosocial concerns faced by BYMSM. ConclusionsMobile phone–based HIV prevention has the potential to increase engagement with HIV prevention and treatment resources among BYMSM. For these approaches to be successful, researchers must include BYMSM in the design and creation of these interventions.

This paper describes the procedures and technologies used for scanning and three-dimensional reconstruction of objects using the optical scanner Kinect. Theoretical backgrounds of basic computer graphics, projective geometry, optics and graphical reconstruction were studied for better understanding of this field of computer science. A part of the content also describes the structure and operating of the Kinect and is used as a theoretical basis for implementing a new framework for three-dimensional object scanning. Methods and procedures of other developers were taken into account, when implementing the framework. Therefore their solutions and approaches to solving the problem were studied, to achieve better results. Described are also the ideas for further improvement of the solution.

Network administration has become more difficult as the number of Internet users has grown and customer usage patterns have changed over time. Rapidly increasing subscriber bases, data intensive applications (such as streaming audio and video), heavy Web browsing, and large file downloads require significant resources and may tax existing network bandwidth. Reliability and quality of service are becoming serious issues for service providers across the country. Due to the dynamic nature of the information technology (IT) sector in general, it is difficult to predict future network usage patterns or what types of applications may be available, and how these applications may be used over time. This research presents a methodology to facilitate capacity planning and to improve the evaluation of network performance for connection-based networks using the Virginia Tech modem pool as a test bed. The abstract research question is can innovative business strategies be employed in lieu of, or in addition to, traditional management practices such as adding capacity in order to improve the performance of a dialup network? Examples of such strategies or business rules may include limiting the duration of an online session or limiting the number of times a given customer can dial into the pool in a specified time period. A complete network traffic characterization is conducted based on service time and interarrival time variables. A longitudinal analysis is performed to examine how traffic patterns have changed over time. Finally, a simulation model is utilized to examine how imposing different business rules during peak-periods of operation can reduce the blocking probability and improve the overall level-of-service. The potential contribution of this research appears to be significant based on the lack of existing literature. Ph. D.