Traffic fatalities accounted for 1.24 million lives lost in 2013 worldwide, and almost 33 thousand of those fatalities were in the U.S. in 2013. The southeastern region of the nation stands out for continuously having higher fatality rates per mile driven than the national average. If one can establish compelling relationships between various factors and fatality rates, then policies and investments can be targeted to increase the safety on the network by focusing on policies that mitigate those factors. In this research effort risk-taking characteristics are explored. These factors have not been as comprehensively reviewed as conventional factors such as vehicle and facility conditions associated with safety. The hypothesis assumes if a person exhibits risk-taking behavior, that risk-taking behavior is not limited to only one aspect of risk, but is likely to occur in multiple facets of the person's life. Some of the risk-taking characteristics explored include credit score, safety belt use, smoking and tobacco use, drug use, mental health, educational attainment, obesity, and overall general health characteristics. All risk-taking characteristics with the exception of mental health were found to have statistically significant correlations with fatality rates alone. However, when a regression model was formed to estimate fatality rates by risk-taking characteristics, only four risk-taking characteristics - credit score, educational attainment, overall poor health, and seat belt use were found to be statistically significant at an integrated level with other demographic characteristics such as unemployment levels and population born is state of residency. By identifying at-risk population segments, education, counseling, enforcement, or other strategies may be deployed to help improve travel safety.

<p>The goal of this paper is to examine whether the introduction of a qualifying day in the use of sick insurance in the Swedish welfare system resulted in an increase in the use of parental benefits as substitute to avoid the qualifying day. We believe that this could be the case because of the higher gain from the welfare system. We use OLS to perform a linear regression from a data set from the data base LINDA during 1991-1996. The results in this paper are that there is a significant increase in the parental benefit after the reform although there is a negative trend for parental benefit during the examined period.</p> / <p>Syftet med denna uppsats är att undersöka hur införandet av en karensdag i det svenska sjukförsäkringssystemet påverkade uttaget av tillfällig föräldrapenning för vård av sjukt barn. Tidigare studier påvisar att individer som har möjlighet att utnyttja förmånen, väljer att sjukanmäla barnet trots egen sjukdom för att minska inkomstbortfallet. Vi utför en linjär regressionsanalys på datamaterialet, bestående av paneldatabasen LINDA för åren 1991-1996. Resultaten påvisar en signifikant ökning i uttaget av tillfällig föräldrapenning i vår population efter införandet av en karensdag, samtidigt som en negativ trend i uttaget observeras.</p>

<p>This thesis investigates the statistical properties of preliminary test estimators of linear models with normally distributed errors. Specifically, we derive exact expressions for the mean, variance and quadratic risk (i.e. the Mean Square Error) of estimators whose form are determined by the outcome of a statistical test. In the process, some new results on the moments of truncated linear or quadratic forms in normal vectors are established.</p><p>In the first paper (Paper I), we consider the estimation of the vector of regression coefficients under a model selection procedure where it is assumed that the analyst chooses between two nested linear models by some of the standard model selection criteria. This is shown to be equivalent to estimation under a preliminary test of some linear restrictions on the vector of regression coefficients. The main contribution of Paper I compared to earlier research is the generality of the form of the test statistic; we only assume it to be a quadratic form in the (translated) observation vector. Paper II paper deals with the estimation of the regression coefficients under a preliminary test for homoscedasticity of the error variances. In Paper III, we investigate the statistical properties of estimators, truncated at zero, of variance components in linear models with random effects. Paper IV establishes some new results on the moments of truncated linear and/or quadratic forms in normally distributed vectors. These results are used in Papers I-III. In Paper V we study some algebraic properties of matrices that occur in the comparison of two nested models. Specifically we derive an expression for the inertia (the number of positive, negative and zero eigenvalues) of this type of matrices.</p>

This thesis investigates the statistical properties of preliminary test estimators of linear models with normally distributed errors. Specifically, we derive exact expressions for the mean, variance and quadratic risk (i.e. the Mean Square Error) of estimators whose form are determined by the outcome of a statistical test. In the process, some new results on the moments of truncated linear or quadratic forms in normal vectors are established. In the first paper (Paper I), we consider the estimation of the vector of regression coefficients under a model selection procedure where it is assumed that the analyst chooses between two nested linear models by some of the standard model selection criteria. This is shown to be equivalent to estimation under a preliminary test of some linear restrictions on the vector of regression coefficients. The main contribution of Paper I compared to earlier research is the generality of the form of the test statistic; we only assume it to be a quadratic form in the (translated) observation vector. Paper II paper deals with the estimation of the regression coefficients under a preliminary test for homoscedasticity of the error variances. In Paper III, we investigate the statistical properties of estimators, truncated at zero, of variance components in linear models with random effects. Paper IV establishes some new results on the moments of truncated linear and/or quadratic forms in normally distributed vectors. These results are used in Papers I-III. In Paper V we study some algebraic properties of matrices that occur in the comparison of two nested models. Specifically we derive an expression for the inertia (the number of positive, negative and zero eigenvalues) of this type of matrices.

The goal of this paper is to examine whether the introduction of a qualifying day in the use of sick insurance in the Swedish welfare system resulted in an increase in the use of parental benefits as substitute to avoid the qualifying day. We believe that this could be the case because of the higher gain from the welfare system. We use OLS to perform a linear regression from a data set from the data base LINDA during 1991-1996. The results in this paper are that there is a significant increase in the parental benefit after the reform although there is a negative trend for parental benefit during the examined period. / Syftet med denna uppsats är att undersöka hur införandet av en karensdag i det svenska sjukförsäkringssystemet påverkade uttaget av tillfällig föräldrapenning för vård av sjukt barn. Tidigare studier påvisar att individer som har möjlighet att utnyttja förmånen, väljer att sjukanmäla barnet trots egen sjukdom för att minska inkomstbortfallet. Vi utför en linjär regressionsanalys på datamaterialet, bestående av paneldatabasen LINDA för åren 1991-1996. Resultaten påvisar en signifikant ökning i uttaget av tillfällig föräldrapenning i vår population efter införandet av en karensdag, samtidigt som en negativ trend i uttaget observeras.

För alpina skidåkare mäter man prestationer i så kallad FIS-ranking. Vi undersöker några metoder för hur man kan analysera data där responsen består av ranger som dessa. Vid situationer då responsdata utgörs av urval av ranger finns ingen självklar analysmetod. Det vi undersöker är skillnaderna vid användandet av olika regressionsanpassningar så som linjär, logistisk och ordinal logistisk regression för att analysera data av denna typ. Vidare används bootstrap för att bilda konfidensintervall. Det visar sig att för våra datamaterial ger metoderna liknande resultat när det gäller att hitta betydelsefulla förklarande variabler. Man kan därmed utgående från denna undersökning, inte se några skäl till varför man ska använda de mer avancerade modellerna. / Alpine skiers measure their performance in FIS ranking. We will investigate some methods on how to analyze data where response data is based on ranks like this. In situations where response data is based on ranks there is no obvious method of analysis. Here, we examine differences in the use of linear, logistic and ordinal logistic regression to analyze data of this type. Bootstrap is used to make confidence intervals. For our data these methods give similar results when it comes to finding important explanatory variables. Based on this survey we cannot see any reason why one should use the more advanced models.

The objective of this work is to determine the effect of four process variables on the properties of blends composed of bisphenol-A polycarbonate (PC) and poly (butylene terephthalate) (PBT) polymers which are compounded using a large scale commercial extruder. The four variables studied are blend composition, specific energy consumption, residence time and shear rate. The last three factors were varied using the extruder screw speed and feed rate. The PC/PBT blends, commercially known as XENOY, were compounded using a WP ZSK 58 mm co-rotating twin screw extruder at the facility of SABIC Innovative Plastics in Cobourg Ontario. The extruder was instrumented to measure online the die pressure, specific energy consumption and blend temperature. The blends were characterized using differential scanning calorimetry, (DSC), scanning electron microscopy, (SEM), gel permeation chromatography, (GPC), and melt volume flow rate, (MVR). After processing, the blend properties determined were melting temperature, glass transition temperature, crystallinity, amorphous phase weight fraction, amorphous phase composition, phase morphology, PBT-rich-phase size, blend molecular weight distribution, and MVR. Using principles available in the literature, a linear regression model was developed to relate the process variables with the online measured properties and output blend properties. Fitting this model allowed the relative importance of each process variable to be estimated for each property. An attempt was also made to identify the general type of PC/PBT blend studied and how it compares with published PC/PBT blend data. It was found that the blends studied were well stabilized since there was no evidence of significant co-polymer formation during processing. Small decreases in molecular weight were attributed to mechanical degradation. Blending increased the crystallization and melting temperatures, as well as blend crystallinity. No practically significant difference in melting temperatures was observed between the different processing conditions. Analysis of glass transitions indicated that the blend components were partially miscible. The amorphous phase compositions were unaffected by blend composition or processing; however, the weight fraction PC-rich-phase present in the blend was strongly influenced by the screw speed. The phase structure of as-extruded blends could not be resolved using the SEM. Therefore, the blends were annealed to coarsen the phases. After annealing, a continuous PC-rich-phase and a discrete PBT-rich-phase were observed. The PBT phase size increased with increasing PBT content. No other statistically significant effects on phase size were observed but this is not conclusive due to the large scatter in the measurements. MVR was primarily influenced by blend composition and specific energy consumption, with the effects of composition being dominant. Further study using higher imaging resolution is required if the phase structures of as received blend pellets are to be characterized. Contrary to current practice, it is recommended that the Utracki-Jukes equation be used rather than the Fox equation for determining amorphous phase composition from glass transition data in PC/PBT blends.

The objective of this work is to determine the effect of four process variables on the properties of blends composed of bisphenol-A polycarbonate (PC) and poly (butylene terephthalate) (PBT) polymers which are compounded using a large scale commercial extruder. The four variables studied are blend composition, specific energy consumption, residence time and shear rate. The last three factors were varied using the extruder screw speed and feed rate. The PC/PBT blends, commercially known as XENOY, were compounded using a WP ZSK 58 mm co-rotating twin screw extruder at the facility of SABIC Innovative Plastics in Cobourg Ontario. The extruder was instrumented to measure online the die pressure, specific energy consumption and blend temperature. The blends were characterized using differential scanning calorimetry, (DSC), scanning electron microscopy, (SEM), gel permeation chromatography, (GPC), and melt volume flow rate, (MVR). After processing, the blend properties determined were melting temperature, glass transition temperature, crystallinity, amorphous phase weight fraction, amorphous phase composition, phase morphology, PBT-rich-phase size, blend molecular weight distribution, and MVR. Using principles available in the literature, a linear regression model was developed to relate the process variables with the online measured properties and output blend properties. Fitting this model allowed the relative importance of each process variable to be estimated for each property. An attempt was also made to identify the general type of PC/PBT blend studied and how it compares with published PC/PBT blend data. It was found that the blends studied were well stabilized since there was no evidence of significant co-polymer formation during processing. Small decreases in molecular weight were attributed to mechanical degradation. Blending increased the crystallization and melting temperatures, as well as blend crystallinity. No practically significant difference in melting temperatures was observed between the different processing conditions. Analysis of glass transitions indicated that the blend components were partially miscible. The amorphous phase compositions were unaffected by blend composition or processing; however, the weight fraction PC-rich-phase present in the blend was strongly influenced by the screw speed. The phase structure of as-extruded blends could not be resolved using the SEM. Therefore, the blends were annealed to coarsen the phases. After annealing, a continuous PC-rich-phase and a discrete PBT-rich-phase were observed. The PBT phase size increased with increasing PBT content. No other statistically significant effects on phase size were observed but this is not conclusive due to the large scatter in the measurements. MVR was primarily influenced by blend composition and specific energy consumption, with the effects of composition being dominant. Further study using higher imaging resolution is required if the phase structures of as received blend pellets are to be characterized. Contrary to current practice, it is recommended that the Utracki-Jukes equation be used rather than the Fox equation for determining amorphous phase composition from glass transition data in PC/PBT blends.

When systems designers are making decisions about which components or technologies to select for a design, they often use experience or intuition to select one technology over another. Additionally, developers of new technologies rarely provide more information about their inventions than discrete data points attained in testing, usually in a laboratory. This makes it difficult for system designers to select newer technologies in favor of proven ones. They lack the knowledge about these new technologies to consider them equally with existing technologies. Prior research suggests that set-based design representations can be useful for facilitating collaboration among engineers in a design project, both within and across organizational boundaries. However, existing set-based methods are limited in terms of how the sets are constructed and in terms of the representational capability of the sets. The goal of this research is to introduce and demonstrate new, more general set-based design methods that are effective for characterizing and comparing competing technologies in a utility-based decision framework. To demonstrate the new methods and compare their relative strengths and weaknesses, different technologies for a power plant condenser are compared. The capabilities of different condenser technologies are characterized in terms of sets defined over the space of common condenser attributes (cross sectional area, heat exchange effectiveness, pressure drop, etc.). It is shown that systems designers can use the resulting sets to explore the space of possible condenser designs quickly and effectively. It is expected that this technique will be a useful tool for system designers to evaluate new technologies and compare them to existing ones, while also encouraging the use of new technologies by providing a more accurate representation of their capabilities. I compare four representational methods by measuring the solution accuracy (compared to a more comprehensive optimization procedure's solution), computation time, and scalability (how a model changes with different data sizes). My results demonstrate that a support vector domain description-based method provides the best combination of these traits for this example. When combined with recent research on reducing its computation time, this method becomes even more favorable.

The surface quality is identified by surface roughness parameters. The average surface roughness (Ra) is used in this study, as it is the most commonly used roughness parameter in the industry. A particular curved cavity of a forging die is selected for the experimental study. Different milling methods are tested. The comparison studies are conducted between 3-axes and 5-axes milling, linear and circular tool path strategies and down and up milling. According to the experimental study, appropriate method is determined for the milling of a particular curved cavity of a forging die. The experimental analysis based on design of experiments (DOE) has been employed by considering cutting speed, feed per tooth and stepover parameters. Multiple linear regression technique is used by which a mathematical formula has been developed to predict the Ra values for milling parameters. The results of the mathematical formula are controlled by conducting test experiments and good correlations are observed between the results of the formula and the results of test experiments.