Courtney E. Cady and David A. Christian
In recent years, an increasing portion of consumer expenditures on services is allocated to healthcare. The aging of the U.S. population, the Affordable Healthcare Act, and the rising per unit costs of hospital trips all have influenced this trend. In this study, we test the hypothesis that healthcare sector prices covary directly with consumer expenditures on healthcare services. Using regression analysis, we regress 5 Healthcare sector ETF's on Healthcare consumption expenditures. The ETF's are: (1) Healthcare Sector ETF (XLV), (2) Healthcare Equipment ETF (XHE), (3) Biotech ETF (XBI), (4) Pharmaceuticals ETF (XHP), and (5) Healthcare Services ETF (XHS). Quarterly data are used in the analysis and the time period is from 2004 - 2014. We expect b>0, t-statistics>2, and R2 is significantly different from zero.
A multi-pass distributed localized search technique to solve the problem of path planning of hyper-redundant manipulators for the shortest path in real-time in the presence of obstacles is proposed. The problem is approached from a control perspective as a shortest path Optimal control problem, where the configuration space is searched for path points that optimize a cost function. This method addresses the ‘’Curse of Dimensionality” of exhaustive search techniques via the multi-pass distributed local search and local minima of Greedy approach via a backtracking technique. Further, theoretical proof shows that the proposed technique converges to an optimal (if only one exists) or a suboptimal (if many exist) solution. The algorithm is implemented on a 9-DOF manipulator arm for various paths.
For the longitudinal dynamics of a fixed wing aircraft with rigid frame, a Proportional-Integral (PI) controller for controlling the forward velocity of the aircraft and a gain-scheduled Proportional-Integral-Differential (PID) like controller, with the forward velocity used as the scheduling variable, for controlling the flight path angle of the aircraft are designed. For a set of working PI gains, previously found through an experienced-based design, derivation and tuning of PID gains for a select number of forward velocities is computationally achieved through the use of a stable Adaptive Particle Swarm Optimization algorithm. Several performance measures, normalized so as to suppress differences in scale, are aggregated into the designed cost function.
David Jack Beebe
A number of studies conducted by students in the Davis Center for Portfolio Management suggest that the fundamental characteristics of stocks can be successfully used to generate portfolio alpha. In this study, several key valuation measures are used to develop portfolio weights for a concentrated portfolio of Consumer Staples stocks. They are, Price to Book, Price to Earnings, Price to Sales, and Price to Cash Flow. In addition, expected earnings growth one year ahead is also included in the weighting process. Two weighting strategies are used: (1) higher price to's get higher weights and (2) higher inverted weighted price to's get higher weights. The 10 stock portfolio performance is then compared to the performance of the DOW, The S&P 500, and the Consumer Staples SPDR ETF on a quarterly and yearly bases for 2014.
First-year students are at risk due to a university’s alcohol culture. This is creating a distorted reality of what college is about for many incoming students. First-year students assimilate into college with various external factors impacting their decisions; among these is whether or not to participate in high-risk alcohol consumption. Previous research focused on college environment, peers and the developmental stages of first-year students separately to identify how these factors impact a student’s decision to consume in high-risk ways. However, little research focused on the holistic impact of all three factors on the first-year student’s experience and alcohol consumption. This study demonstrated the effect of alcohol on first-year students and their overall experience by delving into their stories to understand their lived experiences. Eight interviews were completed, transcribed, and evaluated to develop a thematic understanding of their lived experience. By understanding each student’s story and their common experiences, interventions can be intentionally developed to assist students who are struggling or who might be at risk for issues throughout their college careers.
A Longitudinal, Sibling- Comparison Analysis of Associations Between Depression and Delinquency in Adolescence
Kathleen Elizabeth Mcguire
This study examines the prospective relationship between delinquency and depression in adolescence, as previous research suggests that they may be related. Our study was interested in testing the direction of the relationship between these factors, and whether they would be related when controlling for potential confounds using statistical covariates in one analysis and the comparison of siblings in a second analysis. Data from 11,495 offspring of a large nationally representative sample of mothers were used. Participants reported on delinquency and depression from the ages of 14 to 17. Covariates included race, gender, mother’s education, family income, birth order, maternal age at childbirth, and maternal history of delinquency, all of which were reported by participants’ mothers. As predicted, depression in ages 14-15 predicted future depression in ages 16-17, and delinquency in ages 14-15 predicted future delinquency in ages 16-17, suggesting continuity in both outcomes during adolescence. In addition, a significant positive association was found between depression at ages 14-15 and delinquency at ages 16-17 and between delinquency at ages 14-15 and depression at ages 16-17. Although boys had higher levels of delinquency than girls and girls had higher levels of depression than boys, no gender differences were found in the strength of the associations between delinquency and depression. Results were consistent between analyses controlling for measured covariates and sibling-comparisons. The findings suggest that depression and delinquency are mutually influential. This would suggest that addressing one outcome could serve to reduce or prevent the other.
A Match or a Mismatch: Comparing College Stated Learning Goals to Student Learning Goals and Perception of Educational Quality
Michelle D. Foster
An institution’s ability to meet students’ learning expectations influences student perceptions of educational quality and usefulness. Currently, colleges and universities are trying to provide evidence of these attributes through various summative assessment instruments. However, the content and structure of most assessment instruments measures what students have retained, not actual cognitive change or instances of goal achievement. This study surveyed a random sample of students at a four-year liberal arts college asking them to describe their personal learning goals and quantify the quality and usefulness of the education they received. The students’ goals were then compared to the stated goals of the institution. Findings revealed valuable information about how achievement of personal goals is tied to student perception of quality, and the implications of matching or mismatching students with institutions that can meet their predetermined expectations.
American and International Students on Body Image and Pop Culture:Self-Perceptions of Domestic and International Students Side by Side in the Mid-West
This quantitative study took an interesting look into determining factors of self-image through the eyes of both international and domestic students in Southwest Ohio. In an effort to find comparative data, Self-Perceptions of Domestic and International Students Side by Side in the Mid-West USA provided a unique glimpse into perception and appearance. Survey participants included 84 International students and 26 American students, with 52 Undergraduate and 58 either Graduate or enrolled in an intensive English program. Expanding internationalization is a cultural trend among both populations and is relational to altered perceptions as a result of foreign, peer counterparts. While this study is applicable, more research is needed among this growing student dynamic.
An Analysis of Corporate Social Responsibility Websites: Seafood Production and Environmental Degradation
Corporations are under increasing pressure from internal and external stakeholders to consider the social and environmental cost of their operations. To alleviate this concern, corporations have designed professional ethical codes by which to conduct business. This expanding practice is a facet of public relations known as “Corporate Social Responsibility,” or CSR. This project examines the seafood production industry. Seafood production poses unique environmental concerns, which can be addressed by producers in a variety of ways. A content analysis of the top seafood production websites investigates which environmental themes are being addressed in CSR policies and information pages,and how corporations are measuring their impact.
An Examination of the Relationship Between Perceived Social Support and Medication Adherence in Uninsured Patients with Hypertension
Megan K. Flaherty
Hypertension is a relatively common chronic condition that affects approximately one in three Americans. Successful management and treatment often requires individuals to take antihypertensive medications regularly. However, non-adherence to varying levels and for different reasons is rather common. Untreated hypertension can lead to serious health consequences including heart attacks, heart disease, and kidney damage. Additionally, individuals without health insurance are more likely to have uncontrolled levels of high blood pressure than those with health insurance. It was predicted that increased perceptions of social support would be correlated with higher levels of antihypertensive medication adherence. 79 uninsured individuals with at least a 3-month history of hypertension were recruited for this study from an urban free medical clinic located in a midsize Midwestern city. Participants completed survey measures to assess demographics, medication adherence, perceptions of social support from family and friends, and perceptions of social support from the clinic. Single interval compliance was also calculated from prescription claims data as an additional measure of medication adherence. Correlational analyses did not support the major hypothesis that higher perceptions of social support would be associated with better medication adherence. Future research might continue to evaluate additional aspects of social support and other factors that might be associated with medication adherence.
Lung cancer is the leading cause of cancerous death in the United States. It usually exhibits its presence with the formation of pulmonary nodules. Nodules are round or oval-shaped growth present in the lung. Chest radiographs are used by radiologists to detect and treat such nodules but they are quite difficult to detect with human eye and are sometimes misinterpreted with lesions present. Thus, automated analysis of such data is very essential and would be of valuable help in lung cancer screening. A new computer aided detection (CAD) system in chest radiography is proposed in this paper. The algorithmic steps include (i) local contrast enhancement; (ii) automated anatomical segmentation; (iii) detection of nodule candidates; (iv) feature extraction; (v) candidate classification. In this research, we present facets of the proposed algorithm using a publically available dataset and we explore into new set of features and classifiers. The publically available database was created by the Standard Digital Image Database Project Team of the Scientific Committee of the Japanese Society of Radiological Technology (JRST). The JRST dataset comprises of 154 chest radiographs containing one radiologist confirmed nodule each. In this term paper, we compute a rich set of 117 features for each potential candidate. Local contrast enhancement is achieved using a Gaussian low pass filter. Anatomical segmentation is performed using an active shape model. Potential candidate nodules can then be determined by using an adaptive distance- based threshold algorithm limited to delineated lung fields. Later, a set of features are computed for each potential candidate. Based on those tailored features, a classifier/neural network system can be used to identify the candidates as either true positives or false positives. This CAD system would aid in providing a second opinion to radiologists. Algorithm will be trained using River rain Database and would be tested later in JRST database.
A Personal Touch to Advising: A Comparison of Two Academic Advising Models at a Mid-Western Catholic Institution
Erin T. Brown
This research explored the differences between advisers in the school of business and the engineering department. It provides an interactive opportunity for participants to share their opinions. The significance of this qualitative study is to help higher education institutions continue to develop an environment, which will best fit students with their different needs. According to the research that has been found, both faculty and professional advisers have positive and negative attributes (Filson 2011). This research shows that it is vital for student affairs professionals to take a closer look at the effect academic advisers have on the student experience.
Are intermediate stage product prices early warning indicators of U.S. final goods prices? A covariance analysis for the period 2004-2014.
Anthony J. Bello
In this study I examine the correlation patterns between the price movements for the four intermediate stages of production and final demand prices. Since changes in final demand prices reflect both the levels of demand for goods and services and the rate of inflation, they are particularly important to investors in the financial markets.Using step-wise regression analysis, I develop predictor equations that show final demand prices as a function of the prices for the four intermediate stages of production. Monthly times series for the above price variables over the period 2004-2014 are used in the analysis. I expect all of the b coefficients to be positive and statistically significant at the 95% confidence level.
Few studies have examined Racial/Ethnic (R/E) Identity in early childhood. The current study utilizes a novel approach to measuring this construct and, further, investigates whether R/E Identity is related to cross-race acceptance. African American and White kindergarten children were asked to rate the quality of 4 female and 4 male singers, each of whom is depicted on a video clip. Among the 8 video clips are 2 pairs of female singers and 2 pairs of male singers. Within each pair of same-sex singers, one is Black and the other is White. The same sound track is used for each pair. Differences in the ratings of African American and White singers could represent young children’s R/E Identity, which is compared across African American and White children. It was hypothesized that R/E Identity would either be positively related, or not at all related, to cross-race inclusion. The latter is measured by a modified version of the Cross-Race Inclusion Task developed by Blackwell and Katsuyama (2012).
A Self Organizing Maps Approach to Segmenting Tumors in Computed Tomography (CAT) and Magnetic Resonance Imaging (MRI) Scans
Fatema A. Albalooshi, Yakov Diskin, and Sidike Paheding
Studies and explorations of human visual perception have been the main source of inspiration for computer vision algorithms. Understanding how the human brain represents basic attributes of objects helps in developing computer vision algorithms for automatic object interpretation and understanding. Human visual perception is based on the neural coding of fundamental features, such as object boundaries, color, orientation, shape, etc. Thus, finding the contours and boundaries of objects provides the first step for object recognition and interpretation. Form here, the idea of this research inspired to introduce an automatic boundary detection technique based on active contours that is designed to detect the contours of abnormalities in X-ray and MRI imagery. Our research is aimed to aid healthcare professionals to sort and analyze large amount of imagery more effectively. Our segmentation algorithm incorporates prior information within segmentation framework to enhance the performance of object region and boundary extraction of defected tissue regions in medical imagery. We exploit Self Organizing Map (SOM) unsupervised neural network to train our prior information. One reason to prefer SOMs to other neural network models is the specific ability of SOMs to learn the intensity information via their topology preservation property. In addition, SOMs have several characteristics that make them pretty much similar to the way the human brain works. A dual self-organizing map approach is being used to learn the object of interest and the background independently in order to guide the active contour to extract the target region. The segmentation process is achieved by the construction of a level set cost function, in which, the dynamic variables are the Best Matching Units (BMU)s coming from the SOM maps. We evaluate our algorithm by comparing our detection results to the results of the manually segmented by health professionals.
A Smart Beta Approach to Portfolio Weighting for a Concentrated Portfolio of Consumer Discretionary Stocks
Daniel Robert Caponi and Rory T. Houser
The two major approaches to weighting market indexes are price weighting (DOW) and market cap weighting (S&P 500). In this study, we use a Smart Beta approach by weighting stocks based on their fundamental and earnings growth characteristics. Using price to earnings, price to book, price to sales, and price to cash flow measures plus expected one year earnings growth, we weight the top 10 holdings of the SPDR Consumer Discretionary ETF (XLY) and compare their performance as a portfolio of stocks to XLY, the DOW, and the S&P 500 for the year 2014. Two weighting strategies are used. A momentum strategy which gives higher weights for higher price-to metrics, and a relative value strategy which gives higher weights to stocks whose inverted price-to's are higher. The concentrated portfolio begins in 2014 with a beginning value of $5,000,000.
Jeremy T. Schwob
This ongoing study develops and evaluates the acceptability and effectiveness of a smartphone application for the treatment of Generalized Anxiety Disorder (GAD). Cognitive-behavioral therapy (CBT) is commonly used to manage and minimize the aversive symptoms of GAD; however, studies have found only modest treatment gains when CBT is used alone (Brown et al., 2001). Previous studies have measured client acceptability of smartphone applications (Ainsworth et al., 2013; Pramana et al., 2013), but they have failed to measure the impact of the application on treatment outcomes (e.g., reductions in symptom severity). To fill this gap in the literature, the proposed study will compare therapists using their treatment as usual (TAU; typically cognitive behavioral therapy) plus inclusion of the smartphone application (TAU+app) to two alternative treatment conditions: TAU plus the addition of a paper log for daily assessment of client data (TAU+paper), and treatment as usual alone (TAU). The current study will test the hypothesis that the integration of a cognitive-behavioral based smartphone application will produce greater reductions in anxiety by facilitating a better quality of communication between therapist and client, strengthening the quality of the therapeutic alliance, promoting skill acquisition, and providing more data regarding client progress. All participants will complete dependent measures of anxiety and depression, global functioning and therapeutic alliance on a weekly basis during the 6 weeks of the study. In addition, the study will test mediation of the treatment effect through enhanced therapist-client communication, therapeutic alliance, and treatment compliance, which also will be measured during the six-week treatment period. Dependent and mediating variables will be measured again at week 10 to determine any lasting effects of the intervention.Keywords: smartphone application, treatment outcomes, anxiety, depression, therapeutic alliance.
Alex M. Watt
Polymer extrusion is a manufacturing process of forcing a melted plastic through a die to create a continuous part with a constant cross-section dictated by the die’s geometry. The typical process uses a fixed die that creates high output at low cost when compared to injection molding. The overarching goal of this project is to develop dies capable of changing cross sectional area during the extrusion process. Preliminary dies have been designed, created and operated in a production process. In order to test the shape repeatability of these dies, a laser scanner was used to capture cross sections at numerous locations along the resulting parts. A numerical process was then developed to accept the data from the scanner and create a representation of the profile. These profiles were then compared to the profiles at other locations. The repeatability of the sections from these variable geometry parts has been found to be similar to fixed-geometry parts. Further, the extruded parts have also been compared to the die exit geometry to examine expansion that occurs during the process.
A study in Dividend Investment StrategiesHigh Yield vs. High Dividend GrowthFor the Period 2008 - 2014
Joseph P. Riazzi
From a total return perspective, there is an on-going debate among financial analysts as to which is the better strategy: (1) investing in high yield stocks or (2) investing in stocks with high dividend growth rates. Since stocks with high dividend growth rates also tend to be lower yielding stocks, the strategy debate is often more about low vs. high levels of yield. In this study I test several hypotheses: (1) low yield stocks outperform high yield stocks, (2) high dividend growth rate stocks outperform low dividend growth rate stocks, (3) high dividend growth rate stocks outperform high dividend yielding stocks. Using the S&P 500 as my sample universe, I sort the 500 stocks each year by dividend yield and the expected dividend growth rate one year ahead. Portfolios are constructed based on yield and dividend growth rate ranges. Yields, as an example, are divided into class intervals of 100 basis points i.e. 0-1%, 1-2%, 2-3%, up to 6-7%. Dividend growth rates are classified in a similar manner. Returns are developed for each portfolio tied to a class interval and then compared to each other as well as the benchmark S&P 500 on a year to year basis. Regression analysis will be used to test the above hypotheses with the b coefficients expected to be greater than zero and statistically significant at the 95% confidence level.
A time series analysis of Service Consumption expenditures as determinants of the consumer discretionary and consumer staples sector price movements, 2004-2014.
John C. Scheuble and Dimitra A. Spandonidis
A growing portion of U.S. Consumer income is spent on services. Both directly and indirectly these expenditures effect the stock market prices of firms in the consumer discretionary and consumer staples sectors. The objective of this study, therefore is to determine if the market prices of these two sectors co-vary with the growth in consumer services expenditures. The period of analysis is 2004-2014. Quarterly pricing and expenditure level data are used in the analysis. Using regression analysis, the hypothesis to be tested is service expenditures and discretionary and staples sector prices co-vary directly with each other. We expect the b coefficients in the regression analysis to be greater than zero and statistically significant at the 95% confidence level.
Auditory Information in the Form of a Scratching Sound Enhances the Effects of the Rubber Hand Illusion
Brittany C. Fischer, Natalya N. Lynn, and Bridget K. O'Mera
The body schema is generated from a number of different sense modalities such as vision and proprioception. Botvinick and Cohen's rubber hand illusion (1998) demonstrates the relative contributions of vision, tactile perception and proprioception to body awareness. In this illusion, a participant's real hand is concealed from view and a prosthetic rubber hand is seen in its place. An experimenter simultaneously administers tactile stimulation to both the seen rubber hand and participant's actual hidden hand. The combination of this visual and tactile information overrides proprioceptive cues to body perception, creating a sense of ownership of the rubber hand. The present experiment extends research on the sensory inputs to the body schema by employing the rubber hand illusion to investigate the role of auditory information in construction of the body schema. Tactile stimulation was administered with sandpaper while a prerecorded scratching noise played from a concealed speaker. We found that the inclusion of a sound cue heightened the effects of the illusion and caused participants to more readily accept the rubber hand into the body schema. The findings of this study will contribute to the existing understanding of body perception by demonstrating the influence of the auditory system in limb localization.
Almabrok Essa Essa and Sidike Paheding
Object detection in aerial imagery has received a great deal of attention in recent years and become one of the most popular research areas in the field of surveillance systems. Issues in aerial imagery, such as low resolution, the presence of noise, complex appearances of objects and more importantly viewpoints variations of objects have made the process of intrusion detection on oil pipeline Right-of-Way (RoW) more challenge. Thus, a detection system must be able to extract prominent features from an object which has to be distinct and stable under different conditions during the image acquisition process. In this work, we present a novel scheme that automatically detects intrusions such as construction vehicles and equipment on pipeline RoW from aerial imagery. In the first part of the framework, a region-of-interest detector is employed to extract potential regions that may contain objects and to reduce the search region from imagery that are not considered to be a region-of-interest. Next, we develop a rotation-invariant gradient histogram based descriptor for a robust object representation. Since it is built in grayscale space, it is independent of the color changes. In terms of tackling motion blur and noise introduced by sensors or atmospheric effects, a noise reducing kernel is used to compute the gradient of the region, and then histogram of orientated gradient is computed for each key region obtained from the first step of the algorithm. The final descriptor is built by concatenating the magnitude of fast Fourier transform of orientation histograms over all key regions. In the last phase of the framework, a support vector machine with radial basis kernel is used as the classifier to detect objects in an image.
Nina M. Varney
LiDAR is a remote sensing technology which uses a set of 3D geo-referenced points in order to describe a scene. Aerial LiDAR is often collected using UAVs or airplanes which can passively collect data over a short period of time, often over several miles. This can result in millions of points used to describe a scene. LiDAR data is often used for surveillance and military applications and because of the large amount of data and varying resolutions it can be difficult for analysts to recognize and identify mission critical targets within the scene. The goal of this project is to develop a technique for the automatic segmentation and classification of distinct objects within the scene to aid analysts in scene understanding. We focus our method on five distinct classes that we wish to identify; ground, vegetation, buildings, vehicles and fences or barriers. The first step is to use a RANSAC-based ground estimation in order to estimate the digital terrain model (DTM) of the scene. Next, 3D octree segmentation is performed in order to distinguish between individual objects within the data. A novel volume component analysis (VCA) method is used to extract distinct geometric signatures from each individual object and these features are used as the input to several support vector machines (SVM) in cascade of classifiers configuration. The cascade of classifiers separates the objects into the four remaining classes. Our method was tested on an aerial urban LiDAR scene from Vancouver, Canada with a resolution of 15.6 pts/m^2 and was found to have an overall accuracy of 93.6%.
Behavioral Activation in a Homeless Shelter: Development and Validation of the Behavioral Activation Treatment Efficacy Measure
Zachary S. Glendening
Beginning in the summer of 2013, Reeb and colleagues implemented a Behavioral Activation (BA) Program in a homeless shelter for men. Based on operant conditioning, BA is a “therapeutic process that emphasizes structured attempts at engendering increases in overt behaviors that are likely to bring [the person] into contact with reinforcing environmental contingencies and produce corresponding improvements in thoughts, mood, and overall quality of life” (Hopko et al., 2003, p. 700). Quantitative and qualitative results show that BA has efficacy in increasing homeless men’s participation in various shelter activities (Reeb et al., 2014). With funding from the Graduate Student Summer Fellowship, the author co-developed and is in the process of validating the Behavioral Activation Treatment Efficacy Measure (BATEM) to assess psychosocial outcomes of BA. This brief psychometric instrument assesses the following constructs central to mental health maintenance and recovery from mental illness: agency, hope, purpose/meaning in life, quality of life, perceived social support, emotional well-being, and positive social climate. Validation of the measure relies on anticipated support for the following hypotheses: (A) The BATEM will have strong internal consistency. (B) At baseline, participants without a history of mental illness and/or substance abuse will have higher (i.e., less clinically significant) BATEM scores, relative to those with such histories. (C) Men who engage in high numbers of BA sessions will show greater improvements in BATEM scores over a one month period, relative to those who engage less or not at all. That is, changes in BATEM scores will positively correlate with the number of BA activities in which individuals participate during the previous month. Though final statistical analysis is underway, preliminary results will be provided.
Matthew Thomas Cusumano, Mark J. Edmonds, Daniel P. Prince, and Andrew J. Sutter
The purpose of this project is to expand the capabilities of an existing interface of controlling a static robotic arm with brainwaves. Brainwaves are collected with an Emotiv EPOC headset. The Emotiv headset utilizes electroencephalography (EEG) to collect the brain signals. This project makes use of the Emotiv software suites to classify the thoughts of a subject as a specific action. The software then sends a keystroke to the robotic interface to control the robotic arm. The team is to identify actions for mapping, implement these chosen actions, and evaluate the system’s performance. The actions chosen and their implementation would also test the limits of the interface, and provide groundwork for future research. This semester, we are actively working on creating our own, independent signal processing system for analysis on subjects' thought patterns.