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Prospective Students
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Faculty and Staff
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Current Students
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Alumni and Friends
As colleges work to meet performance standards, staff have been placed in key service areas to help students be successful. With the majority of the seven million community college students attending part-time, needing developmental education, and not graduating on time, it is vital that students take advantage of services such as academic advising, financial aid advising, tutoring, career counseling, student organizations, disability services, and military/veteran’s services (American Association of Community Colleges, 2019a; McClenny, 2016; Tippett & Kahn, 2018a). Students who utilize some of these services have been retained and had higher grade point averages (GPA) than students who did not use these services (Bremer et al., 2013; Drake, 2011; Habley et al., 2010; Hatch & Garcia, 2017; McClenney & Dare, 2013; Nakajima et al., 2012; Smith & Allen, 2014). By making use of the provided services, students were more successful, but the frequency of visits to these services has not been analyzed in-depth. Using data from one institution’s Community College Survey of Student Engagement (CCSSE), this study set out to determine if there was an association between the frequency of use of a service and the student’s GPA or intent to return to that college for future semesters. The research questions that guided this study ask if there is a relationship between the frequency of service utilization and student success. By using an analysis of variance to examine the data, it was determined that the reported frequency of using financial aid advising showed a statistically significant difference in the student’s GPA. The research did not find any statistically significant differences in a student’s GPA for the use of multiple services nor a statistically significant difference in a student’s intent to return based on the use of services. Based on this study, community colleges will want to determine the individual services offered by financial aid advising and how to best adapt a financial aid advising program to assist those students who are visiting more often and not seeing academic success.
The U.S. Environmental Protection Agency (EPA) report on Municipal Solid Waste (MSW) (EPA, 2018) shows that the amount of MSW generated by Americans increased from 88.1 million tons in 1960 to 262.4 million tons in 2015. Out of the 262.4 million tons, 137.7 million was the estimated amount disposed into landfills. Only 67.8 million tons or about 26% of the total waste generated was recycled. It is clear from the numbers above that the success of existing recycling programs is limited. Increasing populations will continue to put pressure on our existing resources, compelling governments at all levels to take additional action to increase recycling efforts to transition from a linear model of make, use, and dispose to a closed-loop circular economy system, emphasizing reduce, reuse and recycle.
Within this context, my research evaluates recycling programs in the state of North Carolina, using counties as the unit of analysis. The first part explores county level factors that affect recycling rates. Factors span across the economic, demographic, social, geographic, technical, and programmatic aspects of recycling programs. The second part of my study focusses on exploring the economic and environmental merits of recycling. Specifically, this section explores the GHG emissions and wage creation from recycling certain materials as compared to landfilling them, and the causal mechanism between recycling, and GHG emissions and employment generation. Qualitative interviews with stakeholders in the recycling community inform the findings of my quantitative analysis.
I found that recycling is moving away from being a behavior based in individual taste and preferences to a mainstream behavior—part of everyday life. We must view recycling not only as an individual altruistic action but also as a means to decrease the cost of goods, lower landfill costs, combat climate change, and reduce resource and energy use while engaging the community. Most important is the need for standardized measures for recycling, new ways to measure recycling performance, and greater consistency in solid waste management policies so that scholars and program analysts can conduct more comparative studies. My study provides a unique, yet comprehensive look at recycling in the state of North Carolina, and provides recommendations to decision-makers, leaders, and scholars on how to improve existing recycling programs to achieve the goals of environmental and economic sustainability.
The rapid development of IoT devices and distributed computing brings convenience and high efficiency to modern society. To enhance the security of hardware devices, quite a few cryptographic algorithms were proposed and applied. These encryption algorithms show good resilience to brute-force attacks, but are still vulnerable to side-channel attacks.
Side-channel attacks are non-invasive and passive attack that shows high efficiency on secret data extraction and brings a lot of difficulties for detection and defense. Unlike the brute-force attack and the cryptanalysis attack, that targets the weakness in the encryption algorithm, side-channel attacks utilize weaknesses of implementation and use statistical models such as differential analysis and correlation analysis to steal secret information.
In this work, we explore different side-channel attacks and propose feasible countermeasures for mitigation, including power-based analysis, electromagnetic-based analysis and Direct Memory Access(DMA) attack.
For power/EM based side channel attacks, we first demonstrate multiple attacks on both software-based implementation and hardware-based implementation, including template attack, power-based correlation analysis, and EM-based correlation analysis. To mitigate the risk, we propose a key update scheme to provide resilience to correlation-based side-channel attacks for encryption engine and prove the efficiency by experiments. To protect the process of key generation and key storage from the tampering attack, we use a secure coprocessor to generate and store secret keys.
For DMA attack, we propose a lightweight scheme to provide resilience without any physical and protocol-level modification. The proposed scheme constructs a unique identifier for each DMA-supported PCIe device based on profiling time and builds a trusted database for authentication. The efficiency is also tested and proved by experiments.
Coming from countries across the world, immigrants have chosen to start a new life in the United States, and become part of the fabric that makes up American society. Today, immigrant children face a unique set of challenges and hardships including trauma, acculturative stress, and poverty. Helping to support their needs is a diverse workforce of helping professionals, providing support in a variety of settings. After-school programming has been utilized as a successful approach to supporting immigrant children, and by extension their families and communities. It is unique for children in after-school programs to be supported by staff that share similar lived experiences and ethnic backgrounds. The purpose of this qualitative study was to explore the issues facing first-generation and immigrant staff caring for immigrant youth in a supportive after-school program. Semi-structured interviews were conducted with 8 participants via Zoom to facilitate in-depth descriptions of their perspectives. Six participants were interviewed twice over a period of six weeks to explore their experiences and perspectives across a time span during the Covid-19 pandemic. Two participants were interviewed once due to scheduling conflicts. The Pragmatic Qualitative Data Analysis (PQDA) method was utilized to analyze data from the interviews and observational field memos. A total of three major themes emerged from the data that included: (a) Emotional Labor, (b) Identity Development, and (e) Covid-19 Pandemic Impacts. This research found that there was a relationship between the central themes of emotional labor, Covid-19, and identity development. Participants’ experience of emotional labor created the unique space for employees to create and reinforce their own cultural identity, while being open and supportive to the various cultural identities. This sense of support from colleagues added a mediator which helped participants to cope with the stress of emotional labor and the Covid-19 pandemic. Other implications for counselors, organizations, policy and future research investigations are explored.
Entrepreneurship is of crucial importance in facilitating economic recovery and growth. While research largely focuses on the role of the individual entrepreneur, venture success also depends on the ability for the entrepreneur to attract and retain top employees. This dissertation investigates some of the state-like psychological resources that can predict entrepreneurial employee outcomes. We examine how employee performance (specifically turnover and promotions) within an entrepreneurial venture is influenced by the employee’s written language expresses one's PsychologicalCapital (PsyCap), and how this relationship is moderated by employee gender. This study consists of 174 hired employees from a young digital new venture. All behavioral and demographic data was provided to further the research and understanding of how employee PsyCap measurement can help optimize hiring and retention. Overall, the study's findings offer promise in advancing PsyCap utilization in selection activities, while better understanding if the interaction of gender changes performance. This study makes three unique contributions to the literature. First, this dissertation adds to the minimal stream of research that currently exists at the intersection of human resources and entrepreneurship. Second, this study expands current PsyCap literature by leveraging its usability to understanding entrepreneurial employees. The third contribution comes in expanding the potential use of content text analysis during the hiring process for new ventures. Implications from this study, as well as recommendations for future studies, are also discussed.
Childhood obesity has been on the rise for decades with negative impact on health, psychology of the people and with significant economic cost to the society. Some risk factors attributed to obesity are quality and quantity of food, sugary drinks, and sedentary lifestyle. This project evaluates the effect of an educational intervention to improve parents’ nutrition label literacy as parents make healthy food choices for their children.
The literature review discussed the causes and consequences of childhood obesity, and importance of nutrition label literacy in prevention of childhood obesity. This quantitative descriptive study was conducted at an outpatient pediatric clinic among parents. One of the aims of the project was to identify the participants’ nutrition label illiteracy by administering a Food Label Literacy for Applied Nutrition Knowledge (FLLANK) pretest. Thirty participants completed the pre and post intervention questionnaire. 73.3% of the participants had a least a 2-year college degree and 60% made more than $45,000/ year. The results showed that irrespective of socioeconomic status, the participants improved in their nutrition label literacy after the educational intervention. It is important for healthcare providers to initiate early intervention in nutrition literacy in prevention of childhood obesity.
Childhood obesity has been on the rise for decades with negative impact on health, psychology of the people and with significant economic cost to the society. Some risk factors attributed to obesity are quality and quantity of food, sugary drinks, and sedentary lifestyle. This project evaluates the effect of an educational intervention to improve parents’ nutrition label literacy as parents make healthy food choices for their children.
The literature review discussed the causes and consequences of childhood obesity, and importance of nutrition label literacy in prevention of childhood obesity. This quantitative descriptive study was conducted at an outpatient pediatric clinic among parents. One of the aims of the project was to identify the participants’ nutrition label illiteracy by administering a Food Label Literacy for Applied Nutrition Knowledge (FLLANK) pretest. Thirty participants completed the pre and post intervention questionnaire. 73.3% of the participants had a least a 2-year college degree and 60% made more than $45,000/ year. The results showed that irrespective of socioeconomic status, the participants improved in their nutrition label literacy after the educational intervention. It is important for healthcare providers to initiate early intervention in nutrition literacy in prevention of childhood obesity.
This dissertation features financial market innovation and product market innovation. Two essays feature return predictability in commodity futures, which have been financialized during the past two decades. One essay studies the relation between CEO’s external job market tournament and product innovation in the stock market. The first essay identifies a trend factor that exploits the short-, intermediate-, and long-run moving averages of settlement price in commodity futures markets. The trend factor generates statistically and economically large returns during the sample period 2004-2019. It outperforms the well-known momentum factor by more than five times the Sharpe ratio and less downside risk. The trend factor cannot be explained by existing factor models and is priced cross-sectionally. Then we find that the trend factor can be explained by funding liquidity measured by TED spread. Overall, the results indicate that there are significant economic gains from using the information on historical prices in commodity futures markets. The second essay uses machine learning tools to study the serial dependence (lead-lag relations) of commodity futures returns. We use LASSO to select the predictors because the number of predictors is large relative to the number of observations. We find significant full-sample and out-of-sample predictability. In the full sample, we find that LASSO can identify a sparse set of predictors that either come from economically linked commodities or are likely driven by excessive speculative trading. The out-of-sample forecasts based on LASSO generate statistically and economically large gains. When we use more complex machine learning models such as regression trees and neural networks to forecast commodity futures returns, the out-of-sample performance is worse than LASSO portfolios, suggesting that nonlinearities and interactions do not appear substantial in the data. We also find that index trading due to financialization drives the excess comovement among commodity futures. The third essay examines how the tournament-like progression in the CEO labor market influences corporate innovation strategies. By exploiting a text-based proxy for product innovation based on product descriptions from 10-Ks, we find a significant positive relation between industry tournament incentives (ITIs) and product innovation. We then explore the trade-off effects of ITIs on product innovation created through long-term patenting technologies and short-term “routine” product development. We discover that ITIs strengthen routine product development activities but decrease patent-based innovation. Further analyses show that the effect of ITIs on product innovation is stronger when the product market is more competitive and when CEO characteristics indicate a higher probability of winning the tournament prize.
Most of the coagulation studies done thus far were either site-specific or focused on only one variable and hence do not apply to real-world conditions. Developing a universal and practical model of coagulation has been a near-impossible task because 1) water is a chemically complex medium that varies spatially and temporally 2) the sheer number of factors and their interactions that determine the performance of the coagulant. The focus of this research is to develop a general model for coagulation with aluminum sulfate that has practical applications. The goal is also to identify the parameters that control optimum coagulation conditions while considering the removal of particulate (e.g., bacteria) and dissolved (e.g., organic matter) contaminants as well as chemical costs.
Wearable technology became popular not only in the consumer market, but also in the field of academic research. Studies related to smart wearables have increased dramatically during recent years. However, personal safety perspectives of wearable devices have not been adequately addressed in the literature so far. There have been debates regarding the potential health risk of using wireless technology and batteries from wearable devices. Regardless of the actual health risks from wearable devices, these controversial debates could affect and form users’ perceptions toward purchasing and using the technology. The uniqueness of wearable devices is that they are not only considered as technical devices, but also considered as fashion items. By adding perceived risk and fashnology (combination of fashion and technology) constructs to the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), this study examines how perceived risks and fashion-related perceptions influence a consumer’s intention to purchase and use wireless earbuds. Based on survey data from a sample group of 205 respondents, Perceived Health Risk, Perceived Fashionability, and wearable comfort have a significant impact on a consumer’s intention to purchase wireless earbuds. These results fill in the gap of wearable technology literature and provide a reason why Perceived Health Risk should be studied more for future research. In addition, practitioners should make sure they produce wearable devices that are safe, fashionable, and comfortable to wear.
