Brain Injury Resources for the World Wide Web, 2004

Report produced by Iowa Public Health, Divsion of Brain Injury.

Synthesis of Nondestructive Testing Technologies for Geomaterial Applications, May 2005

Current monitoring techniques for determination of compaction of earthwork and asphalt generally involve destructive testing of the materials following placement. Advances in sensor technologies show significant promise for obtaining necessary information through nondestructive and remote techniques. To develop a better understanding of suitable and potential technologies, this study was undertaken to conduct a synthesis review of nondestructive testing technologies and perform preliminary evaluations of selected technologies to better understand their application to testing of geomaterials (soil fill, aggregate base, asphalt, etc.). This research resulted in a synthesis of potential technologies for compaction monitoring with a strong emphasis on moisture sensing. Techniques were reviewed and selectively evaluated for their potential to improve field quality control operations. Activities included an extensive review of commercially available moisture sensors, literature review, and evaluation of selected technologies. The technologies investigated in this study were dielectric, nuclear, near infrared spectroscopy, seismic, electromagnetic induction, and thermal. The primary disadvantage of all the methods is the small sample volume measured. In addition, all the methods possessed some sensitivity to non-moisture factors that affected the accuracy of the results. As the measurement volume increases, local variances are averaged out providing better accuracy. Most dielectric methods with the exception of ground penetrating radar have a very small measurement volume and are highly sensitive to variations in density, porosity, etc.

Web-based Implementation of Winter Maintenance Decision Support System Using GIS and Remote Sensing, May 2005

Winter maintenance, particularly snow removal and the stress of snow removal materials on public structures, is an enormous budgetary burden on municipalities and nongovernmental maintenance organizations in cold climates. Lately, geospatial technologies such as remote sensing, geographic information systems (GIS), and decision support tools are roviding a valuable tool for planning snow removal operations. A few researchers recently used geospatial technologies to develop winter maintenance tools. However, most of these winter maintenance tools, while having the potential to address some of these information needs, are not typically placed in the hands of planners and other interested stakeholders. Most tools are not constructed with a nontechnical user in mind and lack an easyto-use, easily understood interface. A major goal of this project was to implement a web-based Winter Maintenance Decision Support System (WMDSS) that enhances the capacity of stakeholders (city/county planners, resource managers, transportation personnel, citizens, and policy makers) to evaluate different procedures for managing snow removal assets optimally. This was accomplished by integrating geospatial analytical techniques (GIS and remote sensing), the existing snow removal asset management system, and webbased spatial decision support systems. The web-based system was implemented using the ESRI ArcIMS ActiveX Connector and related web technologies, such as Active Server Pages, JavaScript, HTML, and XML. The expert knowledge on snow removal procedures is gathered and integrated into the system in the form of encoded business rules using Visual Rule Studio. The system developed not only manages the resources but also provides expert advice to assist complex decision making, such as routing, optimal resource allocation, and monitoring live weather information. This system was developed in collaboration with Black Hawk County, IA, the city of Columbia, MO, and the Iowa Department of transportation. This product was also demonstrated for these agencies to improve the usability and applicability of the system.