This study introduces a dynamic approach to sorting, making use of predictions and data gathered during run-time to optimize the sorting of the current data set. This approach is used to develop a sorting algorithm called DynamicSort which partitions data and calculates a partial standard deviation for each partition to determine which of two sorting algorithms should be used to sort the partition. The algorithm is tested against Quicksort and radix sort on data sets of different sizes and standard deviation with the intent of finding advantages of the approach. In order to adapt to modern applications, the algorithm is tested in an environment utilizing parallel processing on multiple machines on data sets generated to mimic the characteristic size of big data. To accommodate this the data is divided at start and merged together after sorting using a k-way merge sort. While the tests conducted do not show any concrete gain in performance there are several factors that could be further optimized and evaluated. We find that it is not enough to simply consider the standard deviation in this approach. While no real instance of big data was used the algorithm was adapted for limited cache sizes and multiple hosts working in parallel.

Problem: Running is one of the most widespread physical activities. Incorrect running technique, training quantity but also the runner's equipment can strongly affect health condition of the individual, both positively and negatively. For that reason various trends emerge in the area of running footwear. They include classical sports shoes with different types of impact attenuation as well as the minimalist footwear made to imitate barefoot running, which should be much more natural for humans, as insisted by B. Nigg in his book "Born to Run" - where he says that man was born to walk and run barefooted. Inappropriate shoes can cause various health complications, not only in the foot area. Objective: To find out how foot strike changes in the area of the foot-shoe interaction in running on flat ground when an amateur runner uses minimalist and sports footwear and to draw conclusions for training practice on the basis of the results. Methods: The thesis deals with amateur endurance running in different shoe types (minimalist and sports shoes). The study specimen consisted of 14 female runners (mean body weight 63,31 ± 4,89 kg, height 169,69 ± 4,71 cm, age 31,92 ± 5,34 years, speed in minimalist shoes (MO) 3,34 ± 0,06 m.s- 1 , speed in sports shoes (SO) 3,29 ± 0,06 m.s-1 , weekly mileage 37,54 ± 9,43...

No description available.

Although it is common to model modulus of elasticity (MOE) and modulus of rupture (MOR) of graded lumber as normal, lognormal, or Weibull distributions, recent theories and empirical practices have cast doubt on these models. Mathematical proofs have been used to shown how the MOR distributions of graded lumber can be derived from the MOR distributions of mill-run populations. The MOR distribution of a graded lumber subpopulation is "pseudo- truncated" and does not exhibit the same theoretical form as the mill-run population from which it was drawn. Therefore, it is essential to explore the properties of mill-run lumber populations and properly characterize their MOE and MOR distributions. To investigate this topic, this dissertation has three objectives: 1) to determine if the within-mill means and standard deviations of MOE and MOR in mill-run southern pine (Pinus spp.) lumber differ over time, 2) to determine the correlations among hand-held grain angle meter readings, MOE, and MOR in mill- run southern pine lumber, and 3) to model statistical distributions of MOE and MOR in mill-run red pine (Pinus resinosa) and spruce (Picea spp.) lumber. This research features four main sections: 1) an introduction summarizing the conclusions of each chapter, 2) a chapter investigating if there are statistically significant differences between the means and variances of MOE and MOR in mill-run southern pine lumber populations at the same mill over time, 3) a chapter evaluating the bivariate correlations among handheld grain angle meter readings, MOR, and three measures of MOE in mill-run southern pine lumber, and 4) a chapter modeling the distributions of MOE and MOR in mill-run red pine and spruce lumber populations and comparing those to previous work on mill-run southern pine lumber populations.

Många sammanslagningar av myndigheter har skett utifrån beslut av regeringen. Anledningarna till dessa har skiftat, men några vanliga anledningar har varit att öka effektiviteten, förbättra styrningen, öka flexibilitet osv. Syftet med studien var att ta reda på hur projektledarna till sammanslagningsprojekt upplevde processen. 10 projektledare intervjuades och insamlade data tematiserades. Resultaten visade att de flesta projekt initierats av ett regeringsbeslut om att slå ihop myndigheter, i många fall sökte personalen tjänster i den nya myndigheten, i andra fall var personalen garanterade en tjänst i den nya myndigheten. Det fanns en generell förväntan inför sammanslagningen, ledarskapet påverkade processen och det fanns kulturella skillnader i de olika myndigheterna. Resultaten diskuterades med utgångpunkt i olika teorier kring grupprocesser, motivation, delaktighet och ledarskap. Det saknas ytterligare forskning, speciellt longitudinella studier, för att få svar på hur medarbetarnas mognad och motivation påverkats under tiden och några år efter att projektet sammanslagningar genomförts. / Several mergers of state-run agencies were the result of government decisions. The reasons for these have shifted, but some common reasons identified have been to improve efficiency, exercise better governance and increase flexibility. The purpose of this research is to examine how the project managers challenged the process of the mergers. 10 project managers were interviewed, and the collected data was categorized into separate themes. The results showed that most projects were initiated by a government decision to merge these state-run agencies. Furthermore, in many cases staff sought new career opportunities in the amalgamated agency. In some cases, staff were even guaranteed a position in the amalgamated agency. It was revealed that there was a general expectation for the merger, leadership affected the process and there were challenges marrying the differences in culture between the agencies. The results are discussed with the starting with the different theories about group processes, then onto motivations, participation and lastly leadership. It is clear there is a lack of research in the mergers of state-run agencies, especially longitudinal studies to find out how employees' maturity and motivation were affected throughout the process, and a lack of post-mortem review in the years following the project completion.

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This thesis studies currency premia and their connections with macroeconomics. In the first essay, I link currency premia to capital-output ratios and the well-known “Lucas Paradox”. The “Lucas Paradox” states that there are large and persistent differences in capital-output ratios across countries, suggesting capital is not flowing to countries where it is relatively scarce. In the data, capital-output ratios vary a lot cross-sectionally even within developed countries, and they are negatively correlated with currency risk premia and risk-free rates. To rationalize these patterns, I build a quantitative multi-country model of capital accumulation with external habit and heterogeneous exposures to a global productivity shock. I show that currency risk in this model generates cross-country variations in risk-free rates and capital-output ratios that are consistent with the data. I estimate the model using GDP data from countries issuing the G10 currencies and find two main results: (1) The heterogenous loadings that I extract from GDP data alone are highly correlated with capital-output ratios; and (2) when I feed the estimated loadings into the model, model-generated capital-output ratios account for roughly 55% of the cross-country variation in the data. I conclude that variation in currency risk and therefore currency risk premia have significant effects on the real economy. In the second essay, I identify a quantitative puzzle when using canonical consumption-based asset pricing models to match currency premia under complete markets. Canonical long-run risk and habit models induce a strong, negative correlation between the variance and the mean of the log stochastic discount factor to address the well-known equity premium puzzle. When applied to an open economy with complete markets, this key feature requires that differences in currency returns should arise primarily from predictable appreciations, a requirement that is at odds with the data. We term this tension between a high equity premium, smooth risk-free rates, and largely unpredictable exchange rates the currency premium puzzle and argue it is the underlying reason why existing international asset pricing models have struggled to simultaneously match data on currency returns, equity returns, and risk-free rates. In the third essay, I show that perturbation methods lead to significant computational errors when used to solve international risk-sharing models with Epstein and Zin (1989) preferences. In particular, if countries feature different sizes, the simulating results violate law of iterated expectations. Even under symmetric setups, the errors along a typical simulation path are non-negligible. I conclude that perturbation-based solutions of EZ risk-sharing models should be used with caution.

<p> This dissertation is concerned with the problems of constructing testable models of the short-run dynamics of urban labour markets, given the currently available data sources. Bimonthly data for manufacturing production workers in U.S. cities were considered the most complete for the purpose. Twenty-nine cities were chosen (Indiana, 1 city; Michigan, 1 city; New York State, 7 cities; Ohio, 8 cities; Pennsylvania, 12 cities). The period of the study, 1964-73, was chosen to avoid changes in data-base definition and to avoid the impact of the oil embargo of late 1973. </p> <p> Two types of model were estimated for each city, with different specifications for each model. The first model consisted of three linear, simultaneous difference equations determining, for each city, the number of hours worked per period (number of employees x number of hours worked per employee), the supply of hours available per period and the average weekly wage rate. When tested empirically this model was successful in explaining all these variables. The second model consisted of five equations, determining the number of people employed per period, the number of hours worked per employee per period, the size of the labour force, the hourly wage rate and the voluntary quit rate from employment. This model was considered the theoretically superior of the two in that it allowed for employers substituting between the number of their employees and the number of hours worked by each employee per period. This model also proved the more empirically successful of the two models. The models were tested using the Two-Stage Least-Squares estimation technique. It is believed that this is the first time that such models have been tested in order to analyse short-run urban labour market behaviour. </p> <p> It was hypothesised that the level of manufacturing production is a major determinant of labour market activity in each city. Unfortunately no short-run urban manufacturing production data are available either for the U.S.A. or elsewhere. This fundamental deficiency in the data base was overcome by the development of a synthetic urban manufacturing production time-series, using national U.S.A. production time-series weighted by the proportions of each of nine manufacturing categories in each city. The technique cannot be validated directly but the results from the models are consistent with the synthetic series being excellent proxies for the true series. </p> <p> The results indicated that the cities all had labour markets that behaved in remarkably similar ways, despite the fact that the labour forces involved ranged in size from 57,000 to 5,558,400 people. In particular the labour markets all exhibited highly stable dynamic behaviour. This result indicated that the labour markets were unlikely to be the generators of boom or slump in their respective cities. When estimated labour market parameters were mapped there appeared to be only weak spatial groupings of the parameter values. Similarly weak groupings appeared when the parameter values were plotted against labour force size. No firm conclusions could be drawn from the groupings. Originally it was intended to model the inter-urban labour market interactions but this proved impossible. All the results are based, therefore, on the assumption that those inter-urban interactions are weak enough to be ignored in the short-run. </p> / Thesis / Doctor of Philosophy (PhD)

Low back pain is one of the most common and disabling musculoskeletal disorders worldwide and the third most common reason for surgery in the United States. The lower back, or lumbar region, supports most of the body's weight; it controls spinal movement and stability through the interaction between bones, nerves, muscles, ligaments, and fascia within the lumbar region. Any disorder of those tissues could cause low back pain (LBP); emerging evidence indicates that the thoracolumbar fascia (TLF) is the lower back's most pain-sensitive soft tissue structure. TLF consists of dense connective tissue separated by loose connective tissue, allowing TLF layers to pass easily during torso movement. A series of foundational studies found that patients enduring long-term low back pain have different TLF structures than those without LBP. Injuries may result in adhesions and fibrosis, which may cause adjacent dense connective tissue layers to lose independent motion, limiting movement and causing pain. LBP is diagnosed by investigating the patient's medical history to identify symptoms and then examining the patient to determine the cause of the pain. If the pain persists after diagnosis and treatment, further investigation is required; an ultrasound scan is used as the next step. Ultrasound (US) imaging is a non-invasive and instantaneous method to evaluate soft, connective tissue structures such as muscles, tendons, ligaments, and fascia. Even though measuring echo intensity helps evaluate the soft tissues, this method still has limitations in diagnosing LBP; 90 % of all LBP patients are diagnosed with non-specific LBP, referred to as pain with no definitive cause . An in-depth investigation of US images could potentially provide more specificity in identifying sources of LBP. By providing information about soft tissue structure, texture analysis could increase US images' diagnostic power. The texture of an ultrasound image is the variation of pixel intensities throughout the region of interest (ROI) that produces different patterns; texture analysis is an approach that quantifies the characteristic variation of pixel intensities within ROI to describe tissue morphological characteristics. First-order texture analysis, second-order texture analysis, and grey-level run length texture analysis are types of analysis that could be applied to quantify parameters that describe the features of the texture; the grey-level analysis is usually conducted in four directions of the texture. This study has four objectives; the first objective is to use first-order and second-order analysis to determine texture parameters and determine whether those parameters can differentiate between individuals with and without LBP. The second objective is to use grey level run length analysis to quantify texture parameters in four directions (0^°,45^°,90^°,135^°) and examine whether those parameters can differentiate between individuals with and without LBP. The third objective is to determine the correlation between the first, second, and run length parameters. The fourth objective is to explore how first-order, second order and grey level run length parameters are affected by US machine settings. A custom-written MATLAB program was developed to quantify first and second-order texture parameters and grey-level run length parameters. Using JMP software, each parameter was statistically compared between individuals with and without LBP. Among nine first- and second-order texture parameters, four showed statistically significant differences between individuals with and without LBP. Among 44 run-length parameters, 9 showed statistically significant differences between individuals with and without LBP. The current study also revealed some strong correlations between first, second, and run length parameters; it also shows that the US machine setting has minor effects on the three types of parameters. Although the present study was conducted on a relatively small sample size, the results indicate that one direction of grey level run length analysis and first and second-order texture analysis can differentiate between people with and without LBP. / Master of Science / Low back pain (LBP) is one of the most common and disabling musculoskeletal disorders worldwide and the third most common reason for surgery in the United States. Due to LBP's effect on mobility, it is one of the leading causes of absence from work, early retirement, and long-term disability payments. The thoracolumbar fascia (TLF), a connective tissue that stabilizes the trunk, pelvis, and spine, is considered the most sensitive tissue to LBP. LBP diagnosis is based on the patient's medical history to identify symptoms and then on an examination to determine the cause. If the pain persists after diagnosis and treatment, imaging is recommended as the next step. Ultrasound (US) imaging produces a cross-sectional image of the structure and has been used to compare TLF structure in people with and without LBP. Additional analyses must be done to increase US images' ability to diagnose LBP. In the current project, three types of analysis of US images were performed; first-order, second-order, and grey level run length analyses were performed to determine parameters for the images of the two groups of people; selected parameters were noted to distinguish between people with and without LBP.

The development, testing, and use of liquid propellant and hybrid rocket propulsion systems for spacecraft and their launch vehicles routinely involves the use of cryogenic propellants. These propellants provide high energy densities that enable high propulsive efficiency and high engine thrust to vehicle weight ratios. However, use of cryogenic propellants also introduces technical problems not associated with other types of propellants. One of the major technical problems is the phenomenon of propellant tank pressurant and ullage gas collapse. This collapse is mainly caused by heat transfer from most of the ullage gas to tank walls and interfacing propellant, which are both at temperatures well below those of this gas. Pressurant gas is supplied into cryogenic propellant tanks in order to initially pressurize these tanks and then to maintain required pressures as propellant is expelled from these tanks. The cryogenic propellants expelled from the tanks feed rocket engine assemblies, subassemblies, and components at required interface pressures and mass flow rates. The net effect of pressurant and ullage gas collapse is increased total mass and mass flow rate requirements of pressurant gases. For flight vehicles this leads to significant and undesirable weight penalties. For rocket engine component and subassembly ground test facilities this results in high construction and operational cost impacts. Accurate predictions of pressurant gas mass transfer and flow rate requirements are essential to the proper design of systems used to supply these gases to cryogenic propellant tanks. While much work has been done in the past for predicting these gas requirements at low subcritical tank pressures, very little has been done at supercritical tank pressure conditions and there are selected cases where errors of analytical predictions are high. The objectives of this study are to develop a new generalized and improved computer program to determine pressurant gas requirements at both subcritical and supercritical tank pressure conditions, and then evaluate and validate the consistent accuracy of this program over a wide range of conditions by comparison of program results to empirical data.