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A technique for designing and optimizing the next generation of smart process controllers has been developed in this dissertation. The literature review indicated that neural networks held the most promise for this application, yet fundamental limitations have prevented their introduction to commercial settings thus far. This fundamental limitation has been overcome through the enhancement of neural network theory. The approach taken in this research was to produce highly intelligent process control systems by accurately modeling the nervous structures of higher biological organisms. The mammalian cerebral cortex was selected as the primary model since it is the only computational element capable of interpreting and complex patterns that develop over time. However the choice of the mammalian cerebral cortex as the model introduced two new levels of network complexity. First, the cerebral cortex is a three dimensional structure with extremely complicated patterns of interconnectivity. Second, the structure of the cerebral cortex can only be realized when thousands or millions of neurons are integrated into a massive scale neural network. The neural networks developed in this research were designed around the Hebbian adaptation, the only training technique proven by the literature review to be applicable to massive scale networks. These design difficulties were resolved by not only modeling the cerebral cortex, but the process by which it develops and evolves in biological systems. To complete this model, an advanced genetic algorithm was produced, and a technique was developed to encode all functional and structural parameters that define the cerebral cortex into the artificial chromosome. The neural networks were designed by a cell growth simulation program that decoded the structural and functional information on the chromosome. The cell growth simulation program is capable of producing patterns of differentiation unique for any slight variations in the genetic parameters. These growth patterns are similar to patterns of cellular differentiation seen in biological systems. While the computational resources needed to implement a massive scale neural network are beyond that available in existing computer systems, the technique has produced output lists which fully define the interconnections and functional characteristic of the neurons, thereby laying the foundation for their future use in process control. / Ph. D.

This dissertation attempts to expand our understanding of the deficient self-regulation (DSR) of Internet use and media habit development. Drawing from a social cognitive perspective, DSR is described as lapses in effective self-control that are self-corrected over time. A shortcoming in this area of research is that factors relevant to the technology that may encourage the development of DSR or media habits are rarely, if ever, discussed. A large focus of existing research is instead narrowly placed on individual factors that motivate DSR and media habits. An extension is proposed to theory on DSR in this dissertation by examining the role played by novelty perceptions of technology. In the initial stages of technology use, when perceptions of novelty generally grow, perceived novelty is hypothesized to elicit a state of flow, which in turn diminishes the subfunctions of self-regulation and provokes DSR. The relationship between perceived novelty and flow is moderated by psychosocial problems, boredom proneness, and self-reactive outcome expectation. As perceived novelty of a technology decreases, it is presumed that self-control is restored given that flow no longer inhibits self-regulation. However, DSR and media habits are hypothesized to persist in later technology use if individuals experience psychosocial problems, boredom proneness, or high self-reactive outcome expectations. The manifestation of DSR in later stages of technology use increases the likelihood of forming media habits. The influence of novelty perceptions was evaluated on flow, DSR, and media habits at initial and later stages of technology use. The pretest demonstrated that a novelty frame successfully manipulated novelty perceptions of Second Life, the technology used in this experiment, in anticipated directions. In the main study, perceived novelty resulted in flow, which in turn predicted growth of DSR during initial stages of Second Life use. In the familiar stages of use, DSR led to the development of media habits over time; however, the relationship between novelty perceptions and DSR was not moderated by psychosocial problems, boredom proneness, or self-reactive outcome expectation. The findings of this investigation are discussed aside their implications for research, theory, and practice.

Hierarchical Linear Modeling (HLM) sample size recommendations are mostly made with traditional group-design research in mind, as HLM as been used almost exclusively in group-design studies. Single-case research can benefit from utilizing hierarchical linear growth modeling, but sample size recommendations for growth modeling with HLM are scarce and generally do not consider the sample size combinations typical in single-case research. The purpose of this Monte Carlo simulation study was to expand sample size research in hierarchical linear growth modeling to suit single-case designs by testing larger level-1 sample sizes (N1), ranging from 10 to 80, and smaller level-2 sample sizes (N2), from 5 to 35, under the presence of autocorrelation to investigate bias and power. Estimates for the fixed effects were good for all tested sample-size combinations, irrespective of the strengths of the predictor-outcome correlations or the level of autocorrelation. Such low sample sizes, however, especially in the presence of autocorrelation, produced neither good estimates of the variances nor adequate power rates. Power rates were at least adequate for conditions in which N2 = 20 and N1 = 80 or N2 = 25 and N1 = 50 when the squared autocorrelation was .25.Conditions with lower autocorrelation provided adequate or high power for conditions with N2 = 15 and N1 = 50. In addition, conditions with high autocorrelation produced less than perfect power rates to detect the level-1 variance.

abstract: Designing studies that use latent growth modeling to investigate change over time calls for optimal approaches for conducting power analysis for a priori determination of required sample size. This investigation (1) studied the impacts of variations in specified parameters, design features, and model misspecification in simulation-based power analyses and (2) compared power estimates across three common power analysis techniques: the Monte Carlo method; the Satorra-Saris method; and the method developed by MacCallum, Browne, and Cai (MBC). Choice of sample size, effect size, and slope variance parameters markedly influenced power estimates; however, level-1 error variance and number of repeated measures (3 vs. 6) when study length was held constant had little impact on resulting power. Under some conditions, having a moderate versus small effect size or using a sample size of 800 versus 200 increased power by approximately .40, and a slope variance of 10 versus 20 increased power by up to .24. Decreasing error variance from 100 to 50, however, increased power by no more than .09 and increasing measurement occasions from 3 to 6 increased power by no more than .04. Misspecification in level-1 error structure had little influence on power, whereas misspecifying the form of the growth model as linear rather than quadratic dramatically reduced power for detecting differences in slopes. Additionally, power estimates based on the Monte Carlo and Satorra-Saris techniques never differed by more than .03, even with small sample sizes, whereas power estimates for the MBC technique appeared quite discrepant from the other two techniques. Results suggest the choice between using the Satorra-Saris or Monte Carlo technique in a priori power analyses for slope differences in latent growth models is a matter of preference, although features such as missing data can only be considered within the Monte Carlo approach. Further, researchers conducting power analyses for slope differences in latent growth models should pay greatest attention to estimating slope difference, slope variance, and sample size. Arguments are also made for examining model-implied covariance matrices based on estimated parameters and graphic depictions of slope variance to help ensure parameter estimates are reasonable in a priori power analysis. / Dissertation/Thesis / Ph.D. Educational Psychology 2011

Alcohol abuse is a ubiquitous issue for college students across the United States (U.S.) including Native Hawaiians and Pacific Islanders (NHPI). As compared to their counterparts, NHPI students tend to underutilize university counseling services and have significantly lower retention rates than their White counterparts. Considering that NHPI may be reluctant to go to counseling, their levels of distress and alcohol abuse may have to reach a higher threshold before they seek treatment. This study examined NHPI college students' presenting levels of alcohol abuse both at intake and over time and compared these students to students from other ethnic/racial groups. Data were gathered from the Center for Collegiate Mental Health (CCMH), a practice-research network used by hundreds of college counseling centers across the U.S. Aggregated data from the years 2012-2015 included variables measured by the Standardized Data Set (SDS) and the Counseling Center Assessment of Psychological Symptoms (CCAPS). The data were analyzed using Latent Growth Modeling (LGM) to assess the differences at intake and over time in alcohol abuse and distress across ethnic groups. Results of this study indicated that NHPI college students at college counseling centers had higher levels of alcohol abuse and presenting distress at intake than students from other ethnic/racial groups. However, NHPI did not have significantly different changes in levels of alcohol abuse from session one to session 12 as compared to other students. Implications and directions for further research are also discussed.

Using measures of student growth has become more popular in recent years—especially in the context of high stakes testing and accountability. While these methods have advantages over historical status measures, there is still much evidence to be gathered on patterns of growth generally and in student subgroups. To date, most research studies dealing with student growth focus on the effectiveness of specific interventions or examine growth in a few urban areas. This project explored math, reading, and English language arts (ELA) growth in the students of two rural school districts in Utah. The study incorporated hierarchical and latent growth methods to describe and compare these students’ growth in third, fourth and fifth grades. Additionally, student characteristics were tested as predictors of growth. Results showed student growth as complex and patterns varied across grade levels, subjects and student subgroups. Growth generally declined after third grade and students experienced summer loss in the second summer more than the first. Females began third grade ahead of their male peers in ELA and reading and began at a similar level in math. Male students narrowed the gap in reading and ELA in fourth and fifth grade and pulled ahead of their female peers in math in third grade. Low SES students were the most similar to their peers in math and ELA growth but were ahead of their peers in reading. Hispanic and Native American students started consistently behind white students in all subjects. Hispanic students tended to grow faster during the school year but lost more over the summer months. Native American students had more shallow growth than white students with a gradual decline in growth in fourth and fifth grades. ELA and reading growth were more closely related to each other than with math growth. Initial achievement estimates were more highly correlated with subsequent growth than previous years’ growth. A cross-classified model for teacher-level effects was attempted to account for students changing class groupings each school year but computational limits were reached. After estimating subjects and grade levels separately, results showed variance in test scores was primarily due to student differences. In ELA and reading, school differences accounted for a larger portion of the overall variance than teacher differences.

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Submitted by Celso Magalhaes (celsomagalhaes@ufrrj.br) on 2017-09-29T11:51:49Z No. of bitstreams: 1 2017 - Leif Armando Portal Cahuana.pdf: 7996361 bytes, checksum: aa4cdf76609baa144dc4396e673afb96 (MD5) / Made available in DSpace on 2017-09-29T11:51:49Z (GMT). No. of bitstreams: 1 2017 - Leif Armando Portal Cahuana.pdf: 7996361 bytes, checksum: aa4cdf76609baa144dc4396e673afb96 (MD5) Previous issue date: 2017-02-21 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior - CAPES / The objective of this work was to determine the dendrochronological potential of five forest species of the Fabaceae family from Amazonia Peru. Five native tree species (Apuleia leiocarpa, Hymenaea oblonglifolia, Myroxylon balsamum, Amburana cearensis and Dipteryx odorata), which occur naturally in the Madre de Dios region of Peru, were used. The anatomical characteristics of the wood, growth ring characterization, dendrochronology, growth modeling and X-ray microdensitometry were determined. In the study of the anatomy and characterization of growth rings, the species H. oblonglifolia and A. cearensis presented rings of Growth to the naked eye, demarcated by the fibrous zones and the marginal parenchyma. In the study of dendrochronology the master chronological series of the H. oblonglifolia species of 1778-2013 years and A. cearensis of 1866-2013 years were constructed, and the relation with the climate of the region (precipitation and temperature), it was verified that the variable Climatic conditions in the area of study determining for the greatest growth in diameter of the trunks of the trees was the last rainfall the species presented answers common to the El Ni?o phenomenon. In the growth modeling study, the species A. cearensis was determined the minimum age according to the Law of Peru of 96 years and a technical age of 58 years and for H. oblonglifolia, it was determined the minimum age according to Law Of Peru of 123 years and a technical age of 57 years. Finally, in the study of the radial physical and anatomical variability of the tree wood of Amburana cearensis, X-ray microdensitometry provided an accurate measurement of the variations in the apparent density of A. cearensis wood, indicative of its anatomical structure and demarcating the limits of the rings Fibrous areas. / O objetivo do trabalho foi Este trabalho foi determinar o potencial dendrocronol?gico de cinco esp?cies florestais da fam?lia Fabaceae oriunda da Amaz?nia Peru. Foram utilizadas cinco esp?cies arb?reas nativas (Apuleia leiocarpa, Hymenaea oblonglifolia, Myroxylon balsamum, Amburana cearensis e Dipteryx odorata), de ocorr?ncia natural na regi?o de Madre de Dios no Peru. Foram determinadas as caracter?sticas anat?micas do lenho, caracteriza??o dos an?is de crescimento, dendrocronologia, modelagem de crescimento e a microdensitometria de raios X. No estudo da anatomia e caracteriza??o dos an?is de crescimento, as esp?cies H. oblonglifolia e A. cearensis, apresentaram an?is de crescimento ao olho nu, demarcados pelas zonas fibrosas e o par?nquima marginal. No estudo de dendrocronologia foram constru?das as s?ries cronol?gicas mestre das esp?cies H. oblonglifolia de 1778-2013 anos e A. cearensis de 1866-2013 anos, e a rela??o com o clima da regi?o (precipita??o e temperatura), verificou-se que a vari?vel clim?tica na ?rea de estudo determinante para o maior crescimento em di?metro dos troncos das ?rvores foi a precipita??o por ?ltimo as esp?cies apresentaram respostas comuns ao fen?meno do El Ni?o. No estudo de modelagem de crescimento a esp?cie A. cearensis, determinou-se a idade m?nima em fun??o a Lei do Peru de 96 anos e uma idade t?cnica de 58 anos e para H. oblonglifolia, determinou-se a idade m?nima em fun??o a Lei do Peru de 123 anos e uma idade t?cnica de 57 anos. Por ?ltimo no estudo da variabilidade radial f?sica e anat?mica do lenho de ?rvores de Amburana cearensis, a microdensitometria de raios X proporcionou uma mensura??o acurada das varia??es da densidade aparente do lenho de A. cearensis, indicativas da sua estrutura anat?mica e demarcando os limites dos an?is pelas zonas fibrosas