Soil Survey of Black Hawk County, Iowa, 2005

The general soil map, which is a color map, shows the survey area divided into groups of associated soils called general soil map units. This map is useful in planning the use and management of large areas. To find information about your area of interest, locate that area on the map, identify the name of the map unit in the area on the color-coded map legend, then refer to the section General Soil Map Units for a general description of the soils in your area.

Soil Survey of Clay County, Iowa, 2005

The general soil map, which is a color map, shows the survey area divided into groups of associated soils called general soil map units. This map is useful in planning the use and management of large areas. To find information about your area of interest, locate that area on the map, identify the name of the map unit in the area on the color-coded map legend, then refer to the section General Soil Map Units for a general description of the soils in your area.

LSTA Five Year Plan Evaluation Report 2008-2012, March 29, 2012

The evaluation’s overarching question was “Did the activities undertaken through the state’s LSTA plan achieve results related to priorities identified in the Act?” The evaluation was conducted and is organized according to the six LSTA priorities. The research design employed two major methodologies: 1. Data sources from Iowa Library Services / State Library of Iowa2 as well as U.S and state sources were indentified for quantitative analysis. These sources, which primarily reflect outputs for various projects, included: Statistics from the Public Library Annual Survey Statistics collected internally by Iowa Library Services such as number of libraries subscribing to sponsored databases, number of database searches, attendance at continuing education events, number of interlibrary loan transactions Evaluation surveys from library training sessions, professional development workshops and other programs supported by LSTA funds Internal databases maintained by Iowa Library Services Impact results from post training evaluations conducted by Iowa Library Services 2010 Iowa census data from the U.S. Census Bureau LSTA State Program Reports for the grant period 2. Following the quantitative analysis, the evaluator gathered qualitative data through interviews with key employees, a telephone focus group with district library consultants and two surveys: LSTA Evaluation Survey (Public Libraries) and LSTA Evaluation Survey (Academic Libraries). Both surveys provided sound samples with 43 representatives of Iowa’s 77 academic libraries and 371 representatives of Iowa’s 544 public libraries participating. Respondents represented libraries of all sizes and geographical areas. Both surveys included multiple choice and rating scale items as well as open-ended questions from which results were coded to identify trends, issues and recommendations.

Development of a Computer Controlled Underbody Plow: TR412, Final Report, January 2006

Underbody plows can be very useful tools in winter maintenance, especially when compacted snow or hard ice must be removed from the roadway. By the application of significant down-force, and the use of an appropriate cutting edge angle, compacted snow and ice can be removed very effectively by such plows, with much greater efficiency than any other tool under those circumstances. However, the successful operation of an underbody plow requires considerable skill. If too little down pressure is applied to the plow, then it will not cut the ice or compacted snow. However, if too much force is applied, then either the cutting edge may gouge the road surface, causing significant damage often to both the road surface and the plow, or the plow may ride up on the cutting edge so that it is no longer controllable by the operator. Spinning of the truck in such situations is easily accomplished. Further, excessive down force will result in rapid wear of the cutting edge. Given this need for a high level of operator skill, the operation of an underbody plow is a candidate for automation. In order to successfully automate the operation of an underbody plow, a control system must be developed that follows a set of rules that represent appropriate operation of such a plow. These rules have been developed, based upon earlier work in which operational underbody plows were instrumented to determine the loading upon them (both vertical and horizontal) and the angle at which the blade was operating.These rules have been successfully coded into two different computer programs, both using the MatLab® software. In the first program, various load and angle inputs are analyzed to determine when, whether, and how they violate the rules of operation. This program is essentially deterministic in nature. In the second program, the Simulink® package in the MatLab® software system was used to implement these rules using fuzzy logic. Fuzzy logic essentially replaces a fixed and constant rule with one that varies in such a way as to improve operational control. The development of the fuzzy logic in this simulation was achieved simply by using appropriate routines in the computer software, rather than being developed directly. The results of the computer testing and simulation indicate that a fully automated, computer controlled underbody plow is indeed possible. The issue of whether the next steps toward full automation should be taken (and by whom) has also been considered, and the possibility of some sort of joint venture between a Department of Transportation and a vendor has been suggested.

Prevalence and Distribution of Young Driver Distraction Errors in Naturalistic Driving, TPF-5(207), 2014

Naturalistic driving studies are the latest resource for gathering data associated with driver behavior. The University of Iowa has been studying teen driving using naturalistic methods since 2006. By instrumenting teen drivers’ vehicles with event-triggered video recorders (ETVR), we are able to record a 12-second video clip every time a vehicle exceeds a pre-set g-force threshold. Each of these video clips contains valuable data regarding the frequency and types of distractions present in vehicles driven by today’s young drivers. The 16-year old drivers who participated in the study had a distraction present in nearly half of the events that were captured. While a lot of attention has been given to the distractions associated with technology in the vehicle (cell phones, navigation devices, entertainment systems, etc.), the most frequent type of distraction coded was the presence of teen passengers engaging in conversation (45%). Cognitive distractions, such as singing along with the radio, were the second most common distraction. Cell phone use was the third most common distraction, detected in only 10% of the events containing distraction.