A major challenge to cold regions hydrology and northern water resources management lies in predicting runoff dynamically in the context of warming-induced changes to the rates and patterns of ground thaw and drainage. Meeting this challenge requires new knowledge of the mechanisms and rates of ground thaw and their implications to water drainage and storage patterns and processes. The study carries out to evaluate the concept of energy-based runoff in the perspective of ground heat flux, soil thaw and liquid moisture content, tortuosity of snow-free area, preferential flow and discharge of the hillslope. Based on field measurements, coupled energy and water flow is simulated in the Area of Interest (AOI) with a half-hour time interval by the distributed hydrological model, GEOtop. In the field, the saturated hydraulic conductivity varies exponentially between the superficial organic layer and the underlying mineral layer. In the simulation, the parameters of the soil physical properties are input by fourteen uneven layers below the ground surface. Starting from the initially frozen state, the process of soil thaw is simulated with dynamic variables such as soil liquid moisture and ice content, hydraulic conductivity, thermal conductivity and heat capacity. The simulated frost table depths are validated by 44-point measurements and the simulation of point soil temperature is also compared to data measured in an excavated soil pit. As a result, the frost table topography is dominated by both the snow-free pattern and the energy fluxes on the ground surface. The rate and magnitude of runoff derived from snow drift and the ice content of frozen soil is greatly influenced by the frost table topography. According to the simulation, the frost table depth is closely regressed with the ground surface temperature by a power function. As soil thawing progresses, ground heat flux reduces gradually and the rate of soil thaw becomes small when the frost table descends. Along with the snow-free area expanding, the average soil moisture of the AOI increases prior to that time when the average frost table is less than 25 cm deep. The snow-free patches expand heterogeneously in the AOI, which causes the spatial and temporal variation of hydraulic conductivity due to the non-uniform frost table depth. According to the simulation, the transit time of the flow through the AOI decreases to the shortest span on May 13 with the average frost table of 10 cm. Before this date, the time lag between snowmelt percolation and slope runoff is about 8-10 hours; while after this date, the time lag is no more than 5 hours. The pattern of the preferential flow in the AOI highly depends on the frost table topography. When the snow-free patches are widely scattered and the average frost table is between 0 and 10 cm, the preferential flow paths are inhibited. With soil thaw progresses, the preferential flow paths are prominent with the largest single contributing area occurring when the average frost table is between 10 cm to 15 cm. When the average frost table reaches 25 cm, the importance of preferential flow is not apparent, and matrix flow prevails.

Sammanfattning Syftet med studien var att studera skillnader i vilka mål bordtennisspelare använder sig av beroende på målinriktning. I studien deltog 103 bordtennisspelare (60 män och 43 kvinnor) tävlandes i division ett till tre. Metoden som användes i studien var en kvantitativ undersökning och bestod av enkäterna Collegiate Goal Setting in Sport Questionnaire (Weinberg, Burton, Yukelson, Weigand, 1993) och Task and Ego Orientation in Sport Questionnaire (Duda & Nicholls, 1992; ref i Duda, 1998). Resultatet i studien visade flera signifikanta skillnader mellan bordtennisspelarna med högre resultatinriktning och bordtennisspelare med en lägre resultatinriktning när det gäller uppfattning om målsättning. Resultatet visade exempelvis att bordtennisspelarna med högre resultatinriktning oftare satte resultatmål och prestationsmål jämfört med bordtennisspelare med en lägre resultatinriktning. Vidare visade resultatet också att bordtennisspelarna med en lägre resultatinriktning anser att det är viktigare med gemenskap för att delta i än bordtennisspelare med en högre resultatinriktning. Resultatet diskuterats i relation till tidigare forskning. / Abstract The purpose of this study was to examine the differences in goal preferences of table tennis players, depending on goal orientation. The participants were 103 (60 male and 43 female) table tennis players competing in division one to three. The method used in the study was a quantitative study consisted of questionnaires Collegiate Goal Setting in Sport Questionnaire CGSSQ (Weinberg, Burton, Yukelson, Weigand, 1993) and Task and Ego Orientation in Sport Questionnaire TEOSQ (Duda & Nicholls, 1992; ref in Duda, 1998). The results showed several significant results between table tennis players with a high ego orientation and table tennis players with a lower ego orientation in goal setting. For example the result showed that table tennis players with a high ego orientation used more often outcome goals and performance goals than table tennis players with a lower ego orientation. The result also showed that a table tennis player with a lower ego orientation means that it is more important with fellowship than tennis players with a high ego orientation. The results have been analyzed and discussed in relation to previous research.

<p>Identifying a lower-dimensional latent space for representation of high-dimensional observations is of significant importance in numerous biomedical and machine learning applications. In many such applications, it is now routine to collect data where the dimensionality of the outcomes is comparable or even larger than the number of available observations. Motivated in particular by the problem of predicting the risk of impending diseases from massive gene expression and single nucleotide polymorphism profiles, this dissertation focuses on building parsimonious models and computational schemes for high-dimensional continuous and unordered categorical data, while also studying theoretical properties of the proposed methods. Sparse factor modeling is fast becoming a standard tool for parsimonious modeling of such massive dimensional data and the content of this thesis is specifically directed towards methodological and theoretical developments in Bayesian sparse factor models.</p><p>The first three chapters of the thesis studies sparse factor models for high-dimensional continuous data. A class of shrinkage priors on factor loadings are introduced with attractive computational properties, with operating characteristics explored through a number of simulated and real data examples. In spite of the methodological advances over the past decade, theoretical justifications in high-dimensional factor models are scarce in the Bayesian literature. Part of the dissertation focuses on exploring estimation of high-dimensional covariance matrices using a factor model and studying the rate of posterior contraction as both the sample size & dimensionality increases. </p><p>To relax the usual assumption of a linear relationship among the latent and observed variables in a standard factor model, extensions to a non-linear latent factor model are also considered.</p><p>Although Gaussian latent factor models are routinely used for modeling of dependence in continuous, binary and ordered categorical data, it leads to challenging computation and complex modeling structures for unordered categorical variables. As an alternative, a novel class of simplex factor models for massive-dimensional and enormously sparse contingency table data is proposed in the second part of the thesis. An efficient MCMC scheme is developed for posterior computation and the methods are applied to modeling dependence in nucleotide sequences and prediction from high-dimensional categorical features. Building on a connection between the proposed model & sparse tensor decompositions, we propose new classes of nonparametric Bayesian models for testing associations between a massive dimensional vector of genetic markers and a phenotypical outcome.</p> / Dissertation

Lookup-table (LUT)-based method is a common approach used in all kinds of research topics. In this dissertation, we present several new designs for table-based function evaluation and table-based error correcting coding. In Chapter 3, a new function evaluation method, called two-level approximation, is presented where piecewise degree-one polynomials are used for initial approximation in the first level, followed by the refined approximation for the shared normalized difference functions in the second level. In Chapter 4, we present a new non-uniform segmentation method that searches for the optimal segmentation scheme with the different design goals of minimizing either ROM, total area, or delay. In Chapter 5, a new design methodology for table-based function evaluation is presented. Unlike previous approaches that usually determine the bit widths by assigning allowable errors for individual hardware components, the total error budget of our new design is considered jointly in order to optimized the bit widths of all the hardware components, leading to significant improvements in both area and delay. Finally, in Chapter 6, the similar table-based concept is used in the design of error correcting encoder using the modified polynomial of the Lagrange interpolation formula, resulting in smaller critical path delay and lower power consumption.

A multi-precision function interpolator, which is fitted in with the IEEE-754 single precision floating point standard, is proposed in this paper. It provides logarithms, exponentials, reciprocal and square root reciprocal operations. Each operation is able to dynamically select four different precision modes in demand. The hardware architecture is designed with fully pipeline in order to comply with hardware architectures of general digital signal processors (DSPs) and graphics processors (GPUs). When considering the usefulness of each precision mode, it is designed to minimize the error among various modes as far as possible in the beginning. According to the precision from high to low, function interpolator can provide 23, 18, 13 and 8-bit accuracy respectively in spite of the rounding effect. This function interpolator is designed based on the look-up table method. It can get the approximation value of target function through the calculation of quadratic polynomial. The coefficient of quadratic polynomial is obtained by piecewise minimax approximation. Before implementing the hardware, we use the Maple algebra software to generate the quadratic polynomial coefficients of aforementioned four operations, and estimate whether these coefficients can meet IEEE-754 single precision floating point standard. In addition, we take the exhaustive search to check the results generated by our implementation to make sure that it can meet the requirements for various operations and precision modes. When performing one of the above four operations, only the tables of the operation are used to obtain the quadratic polynomial coefficient. Therefore, we can take the advantage of the tri-state buffer as a switch to reduce dynamic power consumption of tables for the other three operations. In addition, when performing lower precision modes, we can turn off a part of hardwares, which are used to calculate the quadratic polynomial, to save the power consumption more effectively. By providing multi-precision hardware, we hope users or developers, those who use the battery device, can choose a lower precision mode within the permissible error range to extend the battery life.

In the field of the industrial automatic control, both MCU (Micro Control Unit) and PLC (Programmable Logic Controller) are widely being used in DCS (Distributed Control System). Since MCU can provide complex process scheduling, accurate timing control and PLC has the advantages of easy programming and maintaining. However, the control programs of the MCU are hard to design and maintain. Identically, the poor signal processing ability, high cost and the restrictive functions are the major defects of PLC. In order to solve the drawbacks described above in MCU and PLC, we provide a PLC-like interface for users to access the devices and set the registers of MCU. Likewise, designers can develop the control program via Event-table-driven modules. On the other hand, our main goal of DCS is to quickly construct the distributed N level network topology based on Modbus protocol, which is efficient and reliable. Therefore, we bring up a data collection method and Slave-to-Slave strategy so as to distribute the master loading, reduce the package transmission times and improve the real-time latency. In conclusion, our research results not only congregate the benefits of MCU and PLC but provide an environment to quickly construct and conveniently monitor DCS, which meets the time-to-market demands.

Function evaluation is often used in many science and engineering applications. In order to reduce the computation time, different hardware implementations have been proposed to accelerate the speed of function evaluation. Table-based piecewise polynomial approximation is one of the major methods used in hardware function evaluation designs that require simple hardware components to achieve desired precision. Piecewise polynomial method approximates the original function values in each partitioned subinterval using low-degree polynomials with coefficients stored in look-up tables. Errors are introduced in the hardware implementations. Conventional error analysis in piecewise polynomial methods includes four types of error sources: polynomial approximation error, coefficient quantization error, arithmetic truncation error, and final rounding error. Typical design approach is to pre-allocated maximum allowable error budget for each individual hardware component so that the total error induced from these individual errors satisfies the bit accuracy. In this thesis, we present a new design approach by jointly considering the error sources in designing all the hardware components, including look-up tables and arithmetic units, so that the total area cost is reduced compared to the previously published designs.

Common bottlenose dolphins (Tursiops truncatus) are apex predators and indicators of localized ecosystem health. Accurate characterization of population demography is crucial to parameter predictions. However, descriptions of age growth investigations of odontocetes are limited to the postnatal life. In contrast, the modeled scenario for terrestrial mammalian growth has been described along a continuum of pre- and postnatal data. Few age distribution data exist for the western Gulf of Mexico despite the fact that life tables enable demographic comparisons among populations. The objective of this study was to characterize age, growth, and population-level behavior of bottlenose dolphins along Texas. This objective was accomplished by two discrete studies: age analysis, and population-level behavior. Teeth from 290 stranded individuals were extracted for the purposes of age determination. Curvilinear models (the Gompertz and the von Bertalanffy) were fit to postnatal length-at-age data. Fetal age was determined for 408 suspected fetal length records using validated fetal growth trends and empirical measurements from late-term fetuses. Growth analysis indicated that a Gompertz model fit length-at-age data better than a von Bertalanffy model. A postnatal Gompertz model explained less variation than a combined pre- and postnatal model (R2 = 0.9 and 0.94 respectively). The absolute growth rate and rate of growth decay tripled with the inclusion of fetal length and age data. In the second study, life tables were constructed for 280 individuals. Survivorship curves, mortality rates, intrinsic capacity for increase, and the population growth rate were calculated. Bottlenose dolphin mortality did not differ significantly by sex or age class. Survivorship was best characterized by a type III curve. Analyses indicated no substantial increase (r = -0.07), and that the population is not replacing itself in the next time-step (y = 0.93). Bottlenose dolphins conform to a number of eutherian mammalian trends: the production of precocial young, calving seasonality, and rapid fetal growth rate. Population level behavior suggests a population retraction possibly as a compensatory response to ecosystem perturbation rather than a population decline. Reproductive information will confirm population status and stability in the future. This study is the first to demonstrate a significant impact of cetacean fetal growth parameters on postnatal growth trajectory.

The role of fire in determining the structure and composition of many forested ecosystems is well documented (e.g. North American boreal forests; piñon-juniper woodlands of the western US). Fire is also believed to be important in temperate forests of eastern North America, but the processes acting here are less clear, particularly in xerophytic forests dominated by yellow pine (Pinus, subgenus Diploxylon Koehne) and oak (Quercus L.). In this study, I use dendroecological techniques to investigate fire history and vegetation dynamics of mixed pine-oak forests in the central Appalachian Mountains of Virginia. The study addresses three objectives: (1) develop a lengthy fire chronology to document fire history beginning in the late presettlement era and extending throughout the period of European settlement, industrialization and modern fire exclusion; (2) explore fire-climate relationships; and (3) investigate vegetation dynamics in relation to fire occurrence. The study was conducted on three study sites within the George Washington National Forest. I used fire-scarred cross-sections from yellow pine trees to document fire history. Fire-climate relationships were investigated for each study site individually and all sites combined using superposed epoch analysis (SEA). Fire-history information was coupled with dendroecological data on age structure to explore stand development in relation to fire occurrence. Results of fire history analysis reveal a long history of frequent fire with little temporal variation despite changes in land use history. Mean fire intervals (MFI) ranged from 3.7–17.4 years. The most important change in the fire regime was the initiation of fire suppression in the early twentieth century. Results of SEA show that periodic droughts may be important drivers of fire activity. Drought the year of fire was important at two of the three study sites and when all sites were combined. Results of age structure indicate that vegetation development was clearly influenced by fire. Frequent burning maintained populations of yellow pine throughout the period of study until fire suppression allowed fire-sensitive hardwood trees and shrubs to establish. It is clear from this study that continued fire suppression will likely result in fire-tolerant pines and oaks being replaced by more mesophytic trees and shrubs.

This research relates to the relationship between organic political awareness and work stress and involvement and other issues of employees. It also aims to discuss variables for harmonization of organic politics and results using personality as interfering parameter. This study is mainly conducted on lucrative institutions and businesses in private sector. A total of 948 effective questionnaires were received and the survey was conducted using data for factor analysis, credibility analysis, relevant analysis, regressive analysis and level-based regressive analysis among other approaches. The outcome suggests sound credibility of the quantitative tables, which is available for reference. While organic political awareness does create impacts on work involvement and work stress, we have come to realize that personality does remarkably interfere with the interaction between organic political awareness and work stress and involvement.