<p>Theories of self-regulation address the continuous process in which individuals compare their behavior to salient goals or standards. Two well-known theories of self-regulation, self-discrepancy theory (SDT) and regulatory focus theory (RFT), each make distinctions regarding the types of standards and goals in reference to which individuals self-regulate. Authenticity--the idea of being one's true self--has the potential to influence the kinds of goals or standards that individuals come to possess and may have implications for understanding the outcomes of self-regulatory processes. This research links the construct of authenticity with SDT and RFT, emphasizing how individual differences in authenticity could influence the motivational and affective consequences of self-regulation predicted within each theory. Individual differences in authenticity were expected to influence the nature of the goals and standards that individuals hold, as well as the acute and chronic affective consequences of discrepancies between the actual self and the ideal and ought self-guides respectively. Specifically, individual differences in authenticity were expected to predict magnitude of actual:ideal and actual:ought self-discrepancy as well as the intensity of distress that individuals report (acutely as well as chronically) in association with self-discrepancies. More importantly, self-discrepancies were expected to be less prevalent among individuals high in authenticity, but more distressing among high-authenticity individuals than among individuals with lower levels of authenticity. The results of this research suggest that individual differences in authentic behavior do have a direct influence on both acute and chronic affect. Authenticity was found to interact with self-discrepancies in predicting chronic affect. Authenticity has a unique role in the process of self-regulation, distinct from the contributions of SDT and RFT.</p> / Dissertation

Due to the fast development of IT, quick change of market demand and collaboration in business operation between companies, departments, and individuals, the concept of collaborative commerce has drawn much attention gradually. However, the tools of collaborative commerce used in the past, just like PDM and CPD, are merely used for control in a single stage; despite functions of data management and collaborative design are more capable of doing cross-function work. New PLM solutions can recover the disadvantages of past collaborative commerce tools in the new product development process, make the RD control link from spot to line, in order to control process effectively, establish operation standard, and accumulate experiences of new product design and manufacture. During the process of implementing IT, although not perfect in the beginning, enterprises will find the problems out only when users apply IT and find some problems which don¡¦t be found before implementing IT. It is just the purpose of enterprises to take advantage of implementing IT to review business processes. Technology and organization should make an adaptation in order to solve these problems and the key way to judge the IT to be successful or fail is to see whether IT and organization make a good adaptation. There are few successful cases applying PLM solution to support new product development process in Taiwan; moreover, manufacturing industry is the most representative of industries in Taiwan. For this reason, manufacturing enterprises which have implemented PLM solution and succeeded in closing the case are chosen for case studies, and based on adaptive structuration perspective to research the adaptation done by three structures of technology, organization, and task after PLM solutions are implemented into enterprises. Through this research to find that the adaptation degree is different in the interaction and appropriation between technology, organization, and task. Discrepancy events will also produced in the adaptation process. The key factors to decide whether enterprises take advantage of implementing IS to get advantage are the degree of solving discrepancy events by enterprises. In order to make enterprises get more competitive advantages through implementing PLM solution, the manager should realize more deeply that what changes are result from IT implemented in enterprises and what reason to make this change, so as to know well what advantages PLM solution make.

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Previous research suggests that discrepant ratings of symptoms, behaviors, and competencies may have important implications for childhood adjustment. Consequently, several theoretical explanations regarding the meanings and implications of inter-rater discrepancies have been proposed. The current study examined several largely unexplored issues regarding the statistical and conceptual properties of discrepant ratings; these include heterogeneity of agreement, shared method variance, and direction-specific effects. In a sample of 384 seventh and eighth-grade adolescents, it was found that each of the issues is integral in the interpretation of significant relationships between discrepant ratings of social rejection and childhood adjustment variables. More specifically, results demonstrated that the influence of shared method variance appears to be largely related to heterogeneity of agreement, and that accounting for shared method variance can increase, decrease, or even change the direction of the relationship between discrepancy scores and other variables. Also, results showed that the magnitude of discrepancies can be unrelated, equally related, or differentially related to the adjustment variables for the different forms of bias. Altogether, the findings of this study have implications for the theoretical conceptualization and statistical analysis of inter-rater discrepancy scores.

A concept of a well-posed problem was initially introduced by J. Hadamard in 1923, who expressed the idea that every mathematical model should have a unique solution, stable with respect to noise in the input data. If at least one of those properties is violated, the problem is ill-posed (and unstable). There are numerous examples of ill- posed problems in computational mathematics and applications. Classical numerical algorithms, when used for an ill-posed model, turn out to be divergent. Hence one has to develop special regularization techniques, which take advantage of an a priori information (normally available), in order to solve an ill-posed problem in a stable fashion. In this thesis, theoretical and numerical investigation of Tikhonov's (variational) regularization is presented. The regularization parameter is computed by the discrepancy principle of Morozov, and a first-kind integral equation is used for numerical simulations.

The one-dimensional distribution of pseudo-random numbers generated by the ratio of uniforms methods using linear congruential generators (LCGs) as the source of uniform random numbers is investigated in this paper. Due to the two-dimensional lattice structure of LCGs there is always a comparable large gap without a point in the one-dimensional distribution of any ratio of uniforms method. Lower bounds for these probabilities only depending on the modulus and the Beyer quotient of the LCG are proved for the case that the Cauchy the normal or the exponential distribution are generated. These bounds justify the recommendation not to use the ratio of uniforms method combined with LCGs. (author's abstract) / Series: Preprint Series / Department of Applied Statistics and Data Processing

Background: Differences in health and living conditions between urban and rural settings can be seen as an important example of gaps between population groups. Birth weight and child growth are important predictors for the future health of a person and at aggregate level, for the public health of a population.The general aim of this thesis is to describe and discuss birth weight, physical growth and breastfeeding of children, as well as associated factors, from birth to 24 months of age in urban and rural areas of Vietnam, thus contributing to the evidence base for health strategy and policy. Methods: Two Health and Demographic Surveillance Sites in Hanoi were used; urban Dodalab and FilaBavi in the rural part. To study rural birth weight 1999 to 2010 information was obtained for 10,114 newborn in FilaBavi. To study urban rural growth disparities 2008-2010, 1,466 children were followed for two years after birth with measurements of weight and length. A study of breastfeeding included 2,572 mothers followed for one year after delivery. Background information about households and mothers was taken from routine surveys in the two sites. Results: The mean birth weight in FilaBavi remained stable at about 3,100 grams, over the 12 years studied despite rapid economic and technological development. At the individual level we found birth weight to be associated with household economy and the education of mothers. In the urban rural comparison, the mean birth weight for urban boys and girls were 3,298 and 3,203 g as compared with 3,105 and 3,057 g for the rural infants. Children in the urban area grew faster than those in the rural area. There were markedly higher frequencies of stunting in the rural area compared with the urban. The initiation of breastfeeding during the first hour of life was more frequent in the urban area. Exclusive breastfeeding during the first three months of age was more commonly reported in the rural than in the urban area. Both birth weight and child growth were statistically significantly and positively associated with economic conditions and mother’s education. Conclusion: The results of the studies presented in this thesis show that there are large and important differences in child birth weight, child growth and infant breastfeeding between urban and rural areas. There are also major differences between the areas with respect to education and economic resources. All predictors of child birth weight and growth discussed are directly or indirectly associated with the social and economic conditions. Globalization and urbanization means obvious risks for increasing gaps between as well as within the rural and urban areas. Large discrepancies in a society will lead to serious public health problems in all segments of the population, not only the underprivileged.

The association between intelligence and achievement has been investigated by many researchers, and a moderate to strong correlation between the two has been repeatedly found. Few researchers, however, have studied the intelligence–achievement relationship within the context of poverty. The purpose of this study was to examine the relationship between the verbal and the nonverbal scores of students within the context of poverty. The study investigated how students’ verbal and nonverbal scores differentiate by ability levels within each grade, specifically kindergarten through fifth grades. It also focused on gifted fifth grade students, and investigated the relationship between their verbal scores and poverty status. Research questions guiding the study were: (1) What is the relationship between verbal and nonverbal intelligence scores of students from poverty, (2) how does this relationship differ by ability levels within each grade, and (3) what is the relationship between verbal scores and poverty status of fifth grade gifted students? The data was collected and analyzed with quantitative methods. The study had two different samples. The first sample consisted of 1935 kindergarten through fifth graders and was used to answer the first and second research questions. The second sample consisted of 128 gifted fifth grade students and was used to answer the third question. The Reynolds Intellectual Assessment Scale (RIAS), the Otis-Lennon School Ability Test, Eighth Edition (OLSAT 8), and the Stanford Achievement Test–Tenth Edition (Stanford 10) were used to collect data. The results indicated that students living in poverty, as measured by free- or reduced lunch status, evidenced large gaps between their verbal and nonverbal intelligence scores. The observed gaps were not specific to any grade level or ability level. Rather, all grades from kindergarten through fifth, demonstrated large gaps between their verbal and nonverbal IQ scores. These gaps were even larger for students with higher nonverbal IQ scores. In addition, free or reduced-lunch status was a significant predictor of verbal intelligence scores as well as of achievement scores. In the light of the results, the study discussed the findings and offered implications: Identification and placement processes for gifted and talented students from poverty should be extra cautious given this demonstrated verbal-nonverbal score discrepancy. Verbal abilities should be assessed when placing students into advanced programs given the verbal demands of these programs. While many students with high nonverbal scores may have had the potential to learn, they were not ready to learn due to their lower verbal scores. Therefore, building verbal intelligence of impoverished students with lower achievement scores will make them more likely to be successful in academic coursework that demands high verbal ability.

Quasi-Monte Carlo (QMC) methods are playing an increasingly important role in computational finance. This is attributed to the increased complexity of the derivative securities and the sophistication of the financial models. Simple closed-form solutions for the finance applications typically do not exist and hence numerical methods need to be used to approximate their solutions. QMC method has been proposed as an alternative method to Monte Carlo (MC) method to accomplish this objective. Unlike MC methods, the efficiency of QMC-based methods is highly dependent on the dimensionality of the problems. In particular, numerous researches have documented, under the Black-Scholes models, the critical role of the generating matrix for simulating the Brownian paths. Numerical results support the notion that generating matrix that reduces the effective dimension of the underlying problems is able to increase the efficiency of QMC. Consequently, dimension reduction methods such as principal component analysis, Brownian bridge, Linear Transformation and Orthogonal Transformation have been proposed to further enhance QMC. Motivated by these results, we first propose a new measure to quantify the effective dimension. We then propose a new dimension reduction method which we refer as the directional method (DC). The proposed DC method has the advantage that it depends explicitly on the given function of interest. Furthermore, by assigning appropriately the direction of importance of the given function, the proposed method optimally determines the generating matrix used to simulate the Brownian paths. Because of the flexibility of our proposed method, it can be shown that many of the existing dimension reduction methods are special cases of our proposed DC methods. Finally, many numerical examples are provided to support the competitive efficiency of the proposed method.

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