Thesis (M.S. in Meteorology and Physical Oceanography)--Naval Postgraduate School, March 2006. / Thesis Advisor(s): Peter Chu. Includes bibliographical references (p. 301-303). Also available online.

Thesis (Ph.D.)--University of Nebraska-Lincoln, 2005. / Title from title screen (site viewed May 23, 2007). PDF text: v, 58 p. : ill. ; 5.42Mb UMI publication number: AAT 3250375. Includes bibliographical references. Also available in microfilm and microfiche formats.

Thesis (Ph. D.)--Oklahoma State University, 2007. / Vita. Includes bibliographical references.

No description available.

Thesis (Ed.D.)--Boston University

The generation of predictions shapes our experience of the world around us. By making inferences about what is likely to happen within a given scenario, we can conserve cognitive resources and enhance our prospects of survival. Predictive coding accounts of perception indicate that this is achieved by minimally processing information that is consistent with our expectations, and prioritising the processing of unexpected or meaningful information. Predictions are also beneficial in situations where accurate perception is difficult, and clues like contextual information allow expectations to ‘fill in the blanks’ when sensory information is noisy or ambiguous. This comes at a cost, however, and a reliance upon expectations can lead to perceptual biases, and in certain cases misperceptions. According to Assimilation Contrast Theory (ACT) and the Affective Expectation Model (AEM), when we attempt to judge affectively ambiguous stimuli, our judgements are biased by expectations in a similar manner. If stimuli are within an acceptable range of an existing expectation, minor discrepancies will be ignored and judgements of those stimuli will fall in line with expectations (assimilation). Alternatively, if the affective discrepancy between expectation and stimulus is so large that it is acknowledged, the extent of that discrepancy will be exaggerated instead (contrast). This thesis aimed to investigate the boundaries and time-course of these effects. A series of behavioural experiments were conducted to investigate: (i) whether predictive cues promoted a state of affective readiness, where judgements across a range of stimuli were biased based upon the assumption that they were broadly part of a positive or negative category (chapters 3 and 4); (ii) whether affective biases (assimilation effects) persisted over time (chapters 5 and 6); and (iii) whether the boundaries of affective and perceptual assimilation effects remained consistent over time (chapter 6 and 7). Psychophysical measures of affective bias indicated that predictive cues influenced participants to judge the same stimuli differently, according to whether they expected those stimuli to be positive or negative. Furthermore, after expectations were learned, judgements of the same stimuli continued to be biased toward expectations after a period of one week. When stimuli from affectively or perceptually distinct categories were manipulated slowly over time, to the point where they became identical, judgements of those stimuli continued to be influenced by the expectation that they should remain distinct. These findings indicate that the boundaries of perceptual and affective assimilation effects may not be static, and if deviations from expectation are small enough to go generally unnoticed, people may update their internal representations of items over time, and the boundaries of acceptance which surround those representations.

Prediction markets have recently gained favour with the academic and business communities. Prediction markets have evolved a long way from their basic beginnings as friendly wagers among friends to become large scale markets connecting traders from around the world. They have been adopted into many large and dynamic corporations that require up to the minute information that can keep up with their business. Organisations like Google, HP, Yahoo! and Best Buy have been experimenting with prediction markets for demand forecasting tasks. Governments have also been using markets, although not always as successfully. The U.S. government looked at PAM which became the terrorist futures market in the post 9/11 world. This did not appeal to the American populous and it has since been withdrawn. Through technological advancements the capabilities and availability of prediction markets has grown. With this the interest in how they work and what can be done to improve the accuracy of the markets. This research looked at the inclusion of a deliberative technique to the markets to improve that accuracy of the market. For this research, markets that made use of discussion boards were used. They were compared against traditional markets, which had no means of communication between traders.The research took the form of a quantitative comparison between the two market types. Data was acquired from the Iowa Electronics Market (IEM) and Inkling Public Markets. The findings from this research indicate that there was a significant difference with α=0.012 for the markets at close. This indicated that there was a significant between the traditional (control) and non-traditional (experimental groups) markets from descriptive statistics it was indicated that the traditional markets performed better in the prediction tasks. The conclusions of this research indicate that allowing traders to communicate and see the actions of others creates group biases which impacts on their independence when making trades and thus on the performance of the market.Copyright / Dissertation (MBA)--University of Pretoria, 2012. / Gordon Institute of Business Science (GIBS) / unrestricted

South Florida has transformed from a natural to a managed ecosystem upon channelization of Kissimmee River and the wetlands in the 1960’s. The drainage has resulted in fast transport of water and nutrient, and subsequently eutrophication of the downstream water bodies. The intervention required: intensive management of the shallow groundwater to balance ecological water requirement; and nutrient removal, namely phosphorus, to minimize eutrophication. The study was set to examine and develop an operational prediction method for groundwater-phosphorus interactions to support the wetlands management. Accordingly, a point scale and a spatio-temporal groundwater level was simulated using sequence based Markovian stochastic analysis and dynamic factor analysis methods respectively. A root mean square error of 0.12m and 0.15m was observed for a point and spatio-temporal groundwater prediction. Soluble and sequestered phosphorus were also simulated at 13% error using a watershed based model called ArcWAM. A spatial analysis on simulated soluble phosphorus and groundwater level indicated similarity of patterns (spatial correlation) 99% of the time. A geographically weighted multivariate analysis of soluble phosphorus using predictors of groundwater level, total phosphorus of surficial water, and distance from Kissimmee River showed a goodness of fit (R2 ) of 0.2 – 0.7. Amongst the factors, the groundwater explained 70% of the soluble phosphorus variability. In summary, an increase in soluble phosphorus was observed with groundwater rise and a decrease during groundwater recession. A reversed relationship was identified for the total phosphorus. Presumably, organic matter in the root zone has contributed to increased soluble phosphorus with the rise in groundwater. On the other hand, solubility of calcium carbonate from the karst aquifers seems to fix and precipitate phosphorus during recession of groundwater. The least sequestration of phosphorus, observed in oversaturated wetlands also suggested that nutrient removal on karst hydrogeology could be risky unless a check is made using vegetation strip to enhance phosphorus uptake. The study concluded that phosphorus could be operationally predicted associated with forecasting of groundwater fluctuation. Further research is recommended to explore factors that could be derived either empirically or from satellite data for prediction of soluble phosphorus at minimum cost.

Withdrawal from a program of studies can have negative consequences that extend beyond those that directly affect the dropouts. Beyond the lack of employment related skills and the impact that dropping out may have on students' confidence in their ability as learners, attrition also has an effect on the educational institute and sponsoring agencies. For example, program attrition leaves the training provider with empty seats but no corresponding reduction in training costs and the sponsoring agencies with a limited return on their training investments. This study examined attrition in short-term vocational programs to determine if factors from research on other postsecondary populations are applicable to these kinds of students. A formula was also developed to predict, early in the program, which students are most likely to withdraw. A review of the research confirmed that what is known about factors related to attrition for students in short-term vocational programs is limited. This necessitated a "borrowing" of factors from research directed at high school students and those in adult and higher education programs. By means of a mailed questionnaire, and using institute records, data were collected for those factors relevant to the population and program under study. These factors were divided into those students brought with them and those they experienced after they began their training. Of the 36 pre-entry factors studied, 12 produced statistically significant relationships when compared to persistence/withdrawal. The significant factors included high school graduation; test scores on reading vocabulary, reading comprehension, reference skills, math computation, math concepts and applications, and combined reading and combined math scores; mean differences in age; the student's socioeconomic status; certainty of program choice; and locus of control as related to high school persistence/withdrawal. Of those categorized as postentry, 10 of the 28 factors produced statistically significant relationships when compared to the indicator variable. These factors were enough study time, study time compared to others, hours per week at PVI, tests passed per attempt, tests exceeded per attempt, feeling that friends had gained from the program, estimation of program success, financial concern, agency sponsorship, and the use of Training Consultants. Combining the statistically significant factors using multiple regression analysis produced a prediction formula which included tests passed per attempt, combined math scores, study time compared, age, and feeling that friends had gained from the program. Conclusions based upon the results of the study centered around the application of attrition factors from the study of other populations and the utility of prediction for practitioners. In essence, the researcher believes it is inappropriate to make assumptions regarding attrition by short-term vocational students based upon research findings from other populations. In addition, even though the findings which characterized persisters as "good students" indicate that attrition rates may be reduced by either restricting admission by students who do not fit the profile or by providing these students with additional support, the amount of variance accounted for (16 percent) based upon the results of the multiple regression analysis suggest caution be used in making any decision. The researcher concludes by recommending that future studies examine attrition by using a variety of research methods in an attempt to clarify which factors are related to student attrition. / Education, Faculty of / Educational Studies (EDST), Department of / Graduate

The purpose of this study was to identify a culturally deprived Vancouver Elementary School population through a correlation of socioeconomic group and academic performance. Two assumptions were made in this paper: one was that intelligence is not a fixed entity, predetermined at birth; the second was that unequal treatment is justified if we aspire to equality of opportunity. To show a relationship between socioeconomic group and academic performance, the school population had to be ranked on a socioeconomic scale and an academic scale. Since a lower-class group was of most interest, districts were scored on their proximity to description of lower class. The criteria of a low socioeconomic group was low income, high percentage of laborers and low educational attainments. These factors were considered significant in Warner's book on stratification, Social Class in America. The figures for these factors were taken from the Dominion Bureau of Statistics census figures. The school performance was ranked according to scores on the Stanford Achievement Tests. The correlation between the paired ranks of the socioeconomic class the school served and school performance was made using Spearman's Rank Correlation Coefficient. The resulting correlation was .77. Generally lower-class district schools received the lowest test scores, while the higher socioeconomic districts received the highest test scores. Two questionnaires were developed, one for principals and one for special counsellors, to see if equipment and services were given equally to all schools, irrespective of the socioeconomic district the school served. The results showed a very slight advantage for the poorer schools in terms of special classes, audio-visual equipment, counsellor services, and hot lunch provision. This partial response to certain of the educational problems of the lower socioeconomic districts could be broadened. It would seem that the results of this study would warrant an investigation of the possibility of setting up an organized program for the culturally deprived in Vancouver. / Education, Faculty of / Educational and Counselling Psychology, and Special Education (ECPS), Department of / Graduate