How Relevant is the Disclosure of a CEO Pay Ratio?

An aftershock of the so called “Great Recession” in 2008, the Dodd-Frank Wall Street Reform and Consumer Protection Act effective July 21, 2010 aimed to increase the transparency of public companies. Section 953(b) of this act is targeting the transparency of executive and employee compensation by requiring the disclosure of a CEO to median employee pay ratio. This disclosure requirement, set to affect all filings with a fiscal year beginning after January 1, 2017, was a response to the public outcry against excessive CEO compensation. Although it does promote the transparency initiative of the Dodd-Frank Act, this disclosure may be wholly unnecessary. Because total CEO compensation is already a required disclosure, this study is examining the benefits and necessity of Section 953(b) by taking into account the driving force behind the ratio and its effect on the business environment

Guest Editorial: The 2014 Capstone Design Conference

The goal of the 2014 Capstone Design Conference held in Columbus, OH was to build upon the success of three previous conferences (2007 and 2010 in Boulder, CO, and 2012 in Champaign, IL) and expand the community of educators, students, and industry members engaged in discussing, analyzing, and improving capstone design education. Sessions at the 2014 Capstone Design Conference were designed for vibrant sharing of ideas and experiences across the capstone community via interactive panel sessions, poster session socials, and hands-on workshops. This editorial discusses conference planning, structure, and feedback. Technical papers that follow in this issue document scholarship surrounding noteworthy capstone course innovations. Most of these began as four page peer-reviewed papers included in the conference proceedings

Evaluating the Impact of Spatial Ability in Virtual and Real World Environments

Survey agencies in the United States continue to move many map-based surveys from paper to handheld computers. With large highly diverse workforces, it is necessary to test software with a diverse population. The present work examines the performance of participants grouped by their level of spatial visualization. The participants were tested in either the field or in a fully immersive virtual environment. The methodology of the study is explained. The performance of the participants in the two environments is modeled with least squares regression. Results of the study are presented and discussed

Who is an “artist” being “copied” and who’s just raw material

There’s something racialized about copyright

A systematic review of automated medical coding and classification systems

Correct coding and reporting of healthcare diagnoses and services have become more critical in recent years as healthcare data needs have evolved. Computer applications for automating this process are available yet, to date such automated solutions are not widely used. The objective of this systematic review is to assess whether automated coding and classification systems, currently available for administrative coding purposes, perform as well as human coders

Statistical methods for random rotations

The analysis of orientation data is a growing field in statistics. Though the rotationally symmetric location model for orientation data is simple, statistical methods for estimation and inference for the location parameter, S are limited. In this dissertation we develop point estimation and confidence region methods for the central orientation. Both extrinsic and intrinsic approaches to estimating the central orientation S have been proposed in the literature, but no rigorous comparison of the approaches is available. In Chapter 2 we consider both intrinsic and extrinsic estimators of the central orientation and compare their statistical properties in a simulation study. In particular we consider the projected mean, geometric mean and geometric median. In addition we introduce the projected median as a novel robust estimator of the location parameter. The results of a simulation study suggest the projected median is the preferred estimator because of its low bias and mean square error. Non-parametric confidence regions for the central orientation have been proposed in the literature, but they have undesirable coverage rates for small samples. In Chapter 3 we propose a nonparametric pivotal bootstrap to calibrate confidence regions for the central orientation. We demonstrate the benefits of using calibrated confidence regions in a simulation study and prove the proposed bootstrap method is consistent. Robust statistical methods for estimating the central orientation has received very little attention. In Chapter 4 we explore the finite sample and asymptotic properties of the projected median. In particular we derive the asymptotic distribution of the projected median and show it is SB-robust for the Cayley and matrix Fisher distributions. Confidence regions for the central orientation S are proposed, which can be shown to have preferable finite sample coverage rates compared to those based on the projected mean. Finally the rotations package is developed in Chapter 5, which contains functions for the statistical analysis of rotation data in SO(3)

The impact of metadata on the accuracy of automated patent classification

During the last decade, the advance of machine-learning tools and algorithms has resulted in tremendous progress in the automated classification of documents. However, many classifiers base their classification decisions solely on document text and ignore metadata (such as authors, publication date, and author affiliation). In this project, automated classifiers using the k-Nearest Neighbour algorithm were developed for the classification of patents into two different classification systems. Those using metadata (in this case inventor names, applicant names and International Patent Classification codes) were compared with those ignoring it. The use of metadata could significantly improve the classification of patents with one classification system, improving classification accuracy from 70.8% up to 75.4%, which was highly statistically significant. However, the results for the other classification system were inconclusive: while metadata could improve the quality of the classifier for some experiments (recall increased from 66.0% to 68.9%, which was a small but nonetheless significant improvement), experiments with different parameters showed that it could also lead to a deterioration of quality (recall dropping as low as 61.0%). The study shows that metadata can play an extremely useful role in the classification of patents. Nonetheless, it must not be used indiscriminately but only after careful evaluation of its usefulness

Master of Science

thesisThis study examined elementary school teacher attitudes and beliefs about their perceived and desired role in childhood obesity prevention. An online survey was administered to K-6 teachers (n=628) in 55 public elementary schools in the greater Salt Lake City area. Questions addressed teachers' classroom practices, personal health behaviors, and their beliefs and attitudes about role in childhood obesity prevention. The majority of teachers (64%) believed they should play a role in childhood obesity prevention and 68% believed they can impact student health behaviors. Seventy percent of teachers included nutrition education in the classroom, with the majority (56%) teaching between 1-5 hours of nutrition lessons during the school year. On average, teachers self-reported moderate levels of nutrition self-efficacy and good to excellent overall health. Personal health practices, nutrition-self efficacy, and nutrition attitudes and beliefs were significantly correlated. Overall, teachers understood the impact of healthy nutrition practices in the classroom, but less than a quarter (21%) agreed that they have the support they need to teach nutrition in the classroom. Barriers to nutrition education include core curriculum demands, lack of time, and pressure to integrate lessons. Teachers reported the need for curriculum with short nutrition lessons, resources for nutrition guest speakers, and support for a healthy school nutrition environment

Developmental trajectory of postural control during various sensory conditions in typical and atypical children

textDevelopmental delays are known to exist in children with autism when compared to their typically developing peers. Foundations of these delays stem from the cognitive and motor performance realm, but information regarding specific characteristics, such as postural stability and sensory integration, are less defined. In this study, postural stability differences were investigated between children with autism and neurotypical children. Past research has shown the role of sensory integration during postural sway has been a strong indicator in showing developmental progress. Due to the focus of the protocol being on static balance, the Modified-Central Test of Sensory Interaction for Balance was used to measure postural stability. The age range for this study is set between 3 and 5 years of age and follows CTSIB protocol to assess 32 neurotypical developing children and compare their results to an archived data set containing CTSIB results from a sample of children with autism. Results from the study indicate that when the autism and neurotypical groups were compared, no significant main effect was found. Developmental differences were found across age groups in that 5 year olds displayed more stability than 4 year olds, but there was no difference between 3 and 4 year olds or 3 and 5 year olds. Further analyses of these developmental results indicated that children in the neurotypical group follow an expected developmental progression while children in the autism group display a divergence from this typical progression. Findings of this research add to the existing literature that children with autism display inconsistent developmental patterns which have a strong relationship with the delayed activity levels of these children. The knowledge and understanding of these delays will allow practitioners to implement specially designed programs to ensure that these children receive the activity that they need and deserve.Kinesiology and Health Educatio

Dopaminergic Genetic Contributions to Obesity in Kidney Transplant Recipients

Background: Kidney transplant recipients are a population who experience a high likelihood of gaining a significant amount of weight (between 6 and 13 kilograms) during the first year after transplantation. However, not all kidney transplant recipients gain weight. Studies have found little difference in physical activity and nutritional intake among those who do and do not gain weight. Immunosuppressant medications have also not been shown to play a substantive role in post-transplant weight gain. Additionally, although some studies have shown that age, gender, and race can influence weight gain, this information does not fully capture the observed variance. These observations suggest that genetic factors may have a role in the differential weight gain experienced by kidney transplant recipients. Dopamine is a neurotransmitter that has previously been implicated in substance addiction. Recently, neuroimaging and neurogenetic data have shown that dopamine may also play a role in obesity. Both dopamine receptor genes and genes related to overall dopamine activity have been associated with obesity, weight gain, and food addiction. Gene expression studies in subcutaneous adipose tissue of kidney transplant recipients showed that expression of some dopaminergic pathway genes was negatively correlated with weight gain. Polymorphisms in some of these genes have been linked to weight gain by others. Taken together, these results suggest that genetic variation in some dopaminergic genes may underlie changes in their expression or function and may contribute to the risk for gaining weight. The purpose of the proposed study was to determine if polymorphisms associated with these previously found dopaminergic genes have predictive value when combined with demographic characteristics to identify kidney transplant recipients who are at risk of gaining weight. Methods: The subjects for this study represent a subsample of participants in a previous observational study. As a part of this study, age, race, and gender information were collected, as well as baseline and twelve month weight and height. Additionally, white blood cells were collected at baseline. Quantitative real time polymerase chain reaction (qPCR) and restriction fragment length polymorphism (RFLP) techniques were used to determine the genotype of these dopaminergic polymorphisms noted in previous work and in the literature as being related to weight gain. This included a total of 10 variants in 7 genes: dopamine receptor type 2 gene (DRD2) single nucleotide polymorphisms (SNPs) rs1800497, rs6277, and rs12364283, dopamine receptor type 3 gene (DRD3) SNP rs6280, dopamine receptor type 4 gene (DRD4) variable number tandem repeat (VNTR), catechol-o-methyltransferase gene (COMT) SNPs rs4680 and rs4818, monoamine oxidase A gene (MAOA) VNTR, monoamine oxidase B gene (MAOB) SNP rs1799836, and dopamine active transporter gene (SLC6A3/DAT1) VNTR. Genotypes were analyzed using dose dependent and risk allele approaches, and those variants with p≤0.20 were included in regression modeling. Regression models were built in a stepwise manner, first by building a model with only demographic characteristics, then by building a model with only genetic variants. Next, models were built with demographic and just individual genetic variants, and finally a model was built with demographic and all genetic variants included. Results: Seventy subjects were included in this study (43% female, 57% African American, mean age 50.7 ±13.2 years). Age was found to be weakly correlated with percent weight change (r=-0.32), but race and gender showed no appreciable relationship to percent weight change at 12 months. A simple regression of age on percent weight change was significant (p=0.006) and explained 11.2% of the variance. Multiple regression models of genetic and demographic factors explained between 11.4 and 25% of the variance, but no model reached statistical significance overall. However, age was consistently significant as a regressor. The SLC6A3/DAT1 9/10 genotype and the DRD2 rs1800497 TC genotype both approached significance in the modeling with p values of 0.08 and 0.07 respectively. The DRD2 rs1800497 genotype was also significantly correlated with percent weight gain in a dose dependent fashion (r=-0.28, p=0.05). Conclusions: Increasing age is associated with less weight gain in the first year after kidney transplantation. Although the regression modeling failed to find significant association between weight gain and specific genotypes in the set of dopaminergic genes, this study was conducted as a pilot study to test the feasibility of the methodology. Even with the current sample size and effect size limitations, these results suggest that the DRD2 SNP rs1800497 and the SLC6A3/DAT1 VNTR have value in prediction of weight gain in kidney transplant recipients. To test the predictive value of these polymorphisms, further studies using a larger cohort of patients is required