Analysis of the rain basin depressions of Clay County, Nebraska.

Introduction: The state of Nebraska has an area of 76,612 square miles and is divided into thirteen distinct physiographic regions (Figure 1). In recent years, attention has been focused upon one particular portion of the Central Loess Plains—the “rainbasin area” or, as it is sometimes called, the “rainwater basin”

Evaluation of AIS Data for Agronomic and Rangeland Vegetation: Preliminary Results for August 1984 Flight over Nebraska Sandhills Agricultural Laboratory

Since 1978 scientists from the Center for Agricultural Meteorology and Climatology at the University of Nebraska have been conducting research at the Sandhills Agricultural Laboratory on the effects of water stress on crop growth, development and yield using remote sensing techniques. We have been working to develop techniques, both remote and ground-based, to monitor water stress, phenological development, leaf area, phytomass production and grain yields of corn, soybeans and sorghum. Because of the sandy soils and relatively low rainfall at the site it is an excellent location to study water stress without the necessity of installing expensive rainout shelters. The primary objectives of research with the airborne imaging spectrometer (AIS) data collected during an August 1984 flight over the Sandhills Agricultural Laboratory are to evaluate the potential of using AIS to: (1) discriminate crop type; (2) to detect subtle architectural differences that exist among different cultivars or hybrids of agronomic crops; (3) to detect and quantify, if possible, the level of water stress imposed on the crops; and (4) to evaluate leaf area and biomass differences for different crops

Classification improvement by optimal dimensionality reduction when training sets are of small size

A computer simulation was performed to test the conjecture that, when the sizes of the training sets are small, classification in a subspace of the original data space may give rise to a smaller probability of error than the classification in the data space itself; this is because the gain in the accuracy of estimation of the likelihood functions used in classification in the lower dimensional space (subspace) offsets the loss of information associated with dimensionality reduction (feature extraction). A number of pseudo-random training and data vectors were generated from two four-dimensional Gaussian classes. A special algorithm was used to create an optimal one-dimensional feature space on which to project the data. When the sizes of the training sets are small, classification of the data in the optimal one-dimensional space is found to yield lower error rates than the one in the original four-dimensional space

An algorithm for optimal single linear feature extraction from several Gaussian pattern classes

A computational algorithm is presented for the extraction of an optimal single linear feature from several Gaussian pattern classes. The algorithm minimizes the increase in the probability of misclassification in the transformed (feature) space. Numerical results on the application of this procedure to the remotely sensed data from the Purdue Cl flight line as well as LANDSAT data are presented. It was found that classification using the optimal single linear feature yielded a value for the probability of misclassification on the order of 30% less than that obtained by using the best single untransformed feature. Also, the optimal single linear feature gave performance results comparable to those obtained by using the two features which maximized the average divergence

Innovative Teaching Strategies In Research Methods For Health Professions

The purpose of this article is to assist the health educator in teaching and creating innovative methods for facilitating research. A brief background and discussion of the research process is presented followed by how and why research is directly applicable in health professions. A variety of methods and strategies are presented in an overall format of the research process. Lastly, practical application of the strategies presented in this article is discussed

Latex: It\u27s Not Just for Condoms! A Learning Experience to Actively Engage and Educate Students Regarding Testicular Anomalies

Testicular cancer is the most prevalent form of cancer among younger males, and, if detected early, it is highly curable. Objectives: Specific to testicular cancer, after this lesson, students will be able to (1) identify the two main forms, (2) identify genetic and behavioral risk factors, (3) access valid and reliable information, (4) assess personal beliefs/feelings about testicular self-exams (TSEs), and (5) correctly identify pathological and non-pathological testes as demonstrated through palpation of latex models. Primary Audience: High-school through college-aged students. The instructor may decide to present the lesson in single sex classrooms if student or parent discomfort level exists

Connecting the Dots: Families and Children with Special Needs in a Rural Community

Due to the rising number of children with disabilities, the needs of these families must be addressed. This article describes the development and implementation of a regional forum in a rural community to address education and training needs of families and professionals. The Special Needs Summit provided workshops, information, and activities for parents and professionals. Participants were invited to participate in a study through a survey soliciting feedback regarding the importance and effectiveness of the training and information received through the Summit, gaps in resources, and future educational and training needs. Overall, participants gave satisfactory ratings regarding the training and education provided during the forum, and gave direction for future programming

Measuring and modeling near-surface reflected and emitted radiation fluxes at the FIFE site

Information is presented pertaining to the measurement and estimation of reflected and emitted components of the radiation balance. Information is included about reflectance and transmittance of solar radiation from and through the leaves of some grass and forb prairie species, bidirectional reflectance from a prairie canopy is discussed and measured and estimated fluxes are described of incoming and outgoing longwave and shortwave radiation. Results of the study showed only very small differences in reflectances and transmittances for the adaxial and abaxial surfaces of grass species in the visible and infrared wavebands, but some differences in the infrared wavebands were noted for the forbs. Reflectance from the prairie canopy changed as a function of solar and view zenith angles in the solar principal plane with definite asymmetry about nadir. The surface temperature of prairie canopies was found to vary by as much as 5 C depending on view zenith and azimuth position and on the solar azimuth. Aerodynamic temperature calculated from measured sensible heat fluxes ranged from 0 to 3 C higher than nadir-viewed temperatures. Models were developed to estimate incoming and reflected shortwave radiation from data collected with a Barnes Modular Multiband Radiometer. Several algorithms for estimating incoming longwave radiation were evaluated and compared to actual measures of that parameter. Net radiation was calculated using the estimated components of the shortwave radiation streams, determined from the algorithms developed, and from the longwave radiation streams provided by the Brunt, modified Deacon, and the Stefan-Boltzmann models. Estimates of net radiation were compared to measured values and found to be within the measurement error of the net radiometers used in the study

A concise taxonomy for describing data as an art material.

How can we describe data when used as an art material? As the number of artists using data in their work increases, so too must our ability to describe the material in a way that is understood by both specialist and general audiences alike. In this paper we review existing vocabularies, glossaries, and taxonomies of data, and propose our own concise taxonomy. We present a number of examples of how existing data art works are described, and demonstrate our taxonomy by applying it to these works. To conclude we propose the adoption of this concise taxonomy by artists, critics, and curators, and suggest that on-going refinement of the taxonomy takes place through crowd-sourced knowledge sharing on the web