ITC/USA 2010 Conference Proceedings / The Forty-Sixth Annual International Telemetering Conference and Technical Exhibition / October 25-28, 2010 / Town and Country Resort & Convention Center, San Diego, California / Providing normal telemetry behavior predictions prior to and post launch will help to stop surprise catastrophic satellite and spacecraft equipment failures. In-orbit spacecraft fail from surprise equipment failures that can result from not having normal telemetry behavior available for comparison with actual behavior catching satellite engineers by surprise. Some surprise equipment failures lead to the total loss of the satellite or spacecraft. Some recovery actions from a surprise equipment failure increase spacecraft risk and involve decisions requiring a level of experience far beyond the responsible engineers.

ITC/USA 2009 Conference Proceedings / The Forty-Fifth Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2009 / Riviera Hotel & Convention Center, Las Vegas, Nevada / Providing normal telemetry behavior predictions prior to and post launch will help to stop surprise catastrophic satellite and spacecraft equipment failures. In-orbit spacecraft fail from surprise equipment failures that can result from not having normal telemetry behavior available for comparison with actual behavior catching satellite engineers by surprise. Some surprise equipment failures lead to the total loss of the satellite or spacecraft. Some recovery actions as a consequence of a surprise equipment failure are high risk and involve decisions requiring a level of experience far beyond the responsible engineers.

The purpose of this study was to explore factors which are predictive of parenting stress for first-time parents. Based on attachment theory and empirical research, the factors investigated were the responsibility for child care and housework, the current and retrospective relationship with the family of origin, the change in emotions related to parenthood, the marital relationship, and attachment and individuation.

This study examines the usefulness of general price level information (GPL) and current cost information (CC) originally provided by SFAS No. 33 as compared to historical cost information (HC) in predicting bankruptcy. The study also examines the usefulness of GPL data versus CC data when each supplements HC data. In addition, this study tests the usefulness of the three types of information systems combined in one model (HC, GPL, and CC) versus HC data in predicting bankruptcy. The study focuses on the predictability of business failure using financial ratios as predictors. A comparison of these predictors is made in order to identify the accounting system that yields a better prediction of bankruptcy. Two multivariate statistical techniques, multiple discriminant analysis (MDA) and logistic regression analysis (LRA), are used to derive the ex—post classification and the ex-ante prediction results. Six functions are developed, based on ratios computed with HC, CC, GPL, the combined HC and GPL, the combined HC and CC, and the combined HC, GPL, and CC. The resulting functions are used to classify 40 firms as failed or nonfailed. The analysis is repeated for three time bases—one, two, and three years before bankruptcy. The main results of the various analyses indicate that the combined HC and CC model has more discriminant power than does the HC, the GPL, or the combined HC and GPL models in each of the three years before bankruptcy. The results also show that there are significant differences in the overall classification rate derived from the combined HC, GPL, and CC model and the HC model, the GPL model, or the combined HC and GPL model . The differences between the combined HC and CC and the combined HC, GPL, and CC models are not significant in each of the three years before bankruptcy. The results also indicate that the differences in the the performance of MDA and LRA are not significant except in the second year before bankruptcy when the combined HC and GPL model is used.

Twenty factors identified through a factor analysis of a 102-item biographical inventory were used as predictors in a multiple regression equation to predict on-the-job performance (supervisory ratings) of oil field employees. This yielded a multiple R of .41. A total of 295 subjects participated in the study. Cross-validation yielded a correlation coefficient of .06. The t-test analyses of the factor means of equipment operators and field mechanics proved that two factors could discriminate between the groups, Mechanical Experience (p<.01) and Social Orientation (p<.05). The results of this study indicate that conducting a factor analysis of unvalidated biographical items and attempting to predict performance would be less appropriate than factor analyzing predictive items to gain an understanding of their underlying dimensions.

How is information organized in the brain during natural reading? Where and when do the required processes occur, such as the perception of individual words and the construction of sentence meanings. How are semantics, syntax and higher-level narrative structure represented? Answering these questions is core to understanding how the brain processes language and organizes complex information. However, due to the complexity of language processing, most brain imaging studies focus only on one of these questions using highly controlled stimuli which may not generalize beyond the experimental setting. This thesis proposes an alternative framework to study language processing. We acquire data using a naturalistic reading paradigm, annotate the presented text using natural language processing tools and predict brain activity with machine learning techniques. Finally, statistical testing is used to form rigorous conclusions. We also suggest the use of direct non-parametric hypothesis tests that do not rely on any model assumptions, and therefore do not suffer from model misspecification. Using our framework, we construct a brain reading map from functional magnetic resonance imaging data of subjects reading a chapter of a popular book. This map represents regions that our model reveals to be representing syntactic, semantic, visual and narrative information. Using this single experiment, our approach replicates many results from a wide range of classical studies that each focus on one aspect of language processing. We extend our brain reading map to include temporal dynamics as well as spatial information by using magnetoencephalography. We obtain a spatio-temporal picture of how successive words are processed by the brain. We show the progressive perception of each word in a posterior to anterior fashion. For each region along this pathway we show a differentiation of the word properties that best explain its activity.

This study was undertaken to investigate the predictive value of certain tests in relationship to first grade reading success. The following predictor tests were administered to seventy first grade students during the first two weeks of school: Metropolitan Readiness Test, Naming Letters Test, Light Response Test and Matching Symbol Test. The Teacher's Reading Readiness Rating Scale was filled out by each of the seven teachers at the end of the sixth week. The Wechsler Intelignce Scale for Children was administered to each child during the fall. The seventh predictor test was computed by finding the difference in individual scores of the Light Response Test and the Matching Symbol Test.

This study was conducted to evaluate several forms of equations for predicting Cheddar cheese yields based on the fat and protein content of milk and moisture content of cheese. Production and quality control data from a Cheddar cheese plant for one entire year was used. This included the pounds of milk that went into each vat of cheese, yield of cheese from each vat, cheese moisture from each vat, and fat and protein percentages of the milk. Seven models were derived to predict the yield of Cheddar cheese. The seven models were statistically fitted to the data by applying the Marquardt non-linear least squares method of iteration. These were compared with the commonly used Van Slyke and Price formula, with casein estimated as a percentage of total protein. The differences among the eight models were small.

Crowdfunding that is the combination word of crowdsourcing and funding makes people can start a business easily. Legislating JOBS act in US played a major role in removing restricted barriers of crowdfunding on public offerings of fence and private funds for small business. The growth speed of crowdfunding takes some beating. Through Kickstarter that is a popular crowdfunding platform and being considered the typical case of crowdfunding, 480 million dollars and more than half a billion dollars were invested in about 19 thousand and 22 projects for 2013 and 2014 respectively. But in spite of the rapid growth, the successful rate of projects at large is decreasing because of imprudent project launching. People just imagine a success story of some triumphant projects without any kind of preparedness when they launch a project. Up to now most of papers researched based on Kickstarter platform because it is the biggest crowdfunding site. But there is no research paper studying with the entire data yet. So, we gathered all the project's main pages in Kickstarter that are finished whether a project is funded or not from its launched date on 2009 to September, 2014. And we also collected all users' profile pages including initiators and backers. The goal of this research project is to analyze evolution of projects and users, investigate techniques and predict successfully funded projects and expected pledged funding levels, and providing intelligent search and discovery based on time series patterns of projects. To successfully achieve the goal, we propose to analyze all projects and users in Kickstarter toward understanding evolution of them over time and thus develop statistical models to automatically predict successfully funded projects and expected funding level. We used as many features as possible such as features being obtainable from text (project main, reward and biography description). Our result will be very helpful for people especially a person preparing a crowdfunding project to fulfill a dream.

The Second World War, often called the Global War, is largely a war of technocracy. The last few decades have seen many discoveries and inventions which, when used in war, have far reaching implications. To a relatively large extent the United States and the United Nations have left many of these discoveries in the theoretical state, thus allowing a large margin of advantage to the Axis Nations who have rather thoroughly exploited, for military purposes, new discoveries at their command. Since the two groups of nations have come to grips it means that survival demands extensive ramifications of all discoveries which in any way will aid in the prosecution of the war.