EC32-713 The Trench Silo in Nebraska

The original idea of using a trench for the storing of ensilage seems to have been the outgrowth of the practice long used in several European countries of storing clover and beet tops in pits. Shortly after the World War, western Canada followed by Montana and North Dakota began to use the trench silo. In Nebraska the true trench silo made its appearance about 1925 or 1926. The trench silo as described in this circular, unless lined with some permanent material such as brick, concrete or stone, must be considered a temporary structure which will serve for a few years only and then must be discarded or rebuilt. In an emergency it will save a crop even though the farmer has little capital to expend other than his own labor.

RB31-258 The Contribution fo Nebraska Farm Women to Family Income Through Poultry and Dairy Products

This investigation was made in 1929-1930 for the purpose of studying the activities of Nebraska farm women in the raising of poultry and in the care of dairy products, to discover whether or not such activities resulted in a contribution to the family income. With this in view, a group of women were asked to keep records for one year (from April 1, 1929 to March 31, 1930) of the value and amount of dairy and poultry products sold or used, of all expense incurred in production, and of the time spent both by the homemaker herself and by all other members of the household, in the production and sale of dairy and poultry products. When this study was outlined it was intended to cover only actual cash addition to the family income. This, however, did not prove to be feasible, as a considerable portion of the contribution to the family income was in the form of dairy and poultry products used at home.

A Controlled Experiment Assessing Test Case Prioritization Techniques via Mutation Faults

Regression testing is an important part of software maintenance, but it can also be very expensive. To reduce this expense, software testers may prioritize their test cases so that those that are more important are run earlier in the regression testing process. Previous work has shown that prioritization can improve a test suite’s rate of fault detection, but the assessment of prioritization techniques has been limited to hand-seeded faults, primarily due to the belief that such faults are more realistic than automatically generated (mutation) faults. A recent empirical study, however, suggests that mutation faults can be representative of real faults. We have therefore designed and performed a controlled experiment to assess the ability of prioritization techniques to improve the rate of fault detection techniques, measured relative to mutation faults. Our results show that prioritization can be effective relative to the faults considered, and they expose ways in which that effectiveness can vary with characteristics of faults and test suites. We also compare our results to those collected earlier with respect to the relationship between hand-seeded faults and mutation faults, and the implications this has for researchers performing empirical studies of prioritization.

Balancing Exploration and Exploitation: A New Algorithm for Active Machine Learning

Active machine learning algorithms are used when large numbers of unlabeled examples are available and getting labels for them is costly (e.g. requiring consulting a human expert). Many conventional active learning algorithms focus on refining the decision boundary, at the expense of exploring new regions that the current hypothesis misclassifies. We propose a new active learning algorithm that balances such exploration with refining of the decision boundary by dynamically adjusting the probability to explore at each step. Our experimental results demonstrate improved performance on data sets that require extensive exploration while remaining competitive on data sets that do not. Our algorithm also shows significant tolerance of noise.