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CNC machining is a critical manufacturing technology in effectively all modern products. Any improvement in efficiency or automation that reduces the cost of CNC machining is of tremendous value to the manufacturing industry. One of the most time-consuming steps in CNC machining, especially in a high-mix low-volume scenario, such as prototyping, is the current tool path planning workflow. The current industrial state of Computer-Aided Manufacturing (CAM) tools used to generate toolpaths requires highly trained CNC programmers. Typically, programmers manually select the features to be machined, the tools to use for each feature, the specific tool paths topology, and the feeds and speeds.
In the research community, there is a lot of focus on the automation of the tool path planning process, aiming to reduce the significant effort required to generate toolpaths. Researchers have developed novel feature recognition techniques, automated tool path generation methods, and tool selection algorithms. However, these methods all come with certain caveats and limitations. Some only work on continuous geometries. Others only work on certain feature types.
This dissertation introduces a feature based automated tool path planning system with the focus on implementing robust and generalized algorithms that work on arbitrary geometries with the full range of features based on discrete geometry. Support for discrete geometry is valuable because there are many situations where only discrete geometry is available as in models generated from 3D scanning systems. Specifically, a robust region segmentation technique is developed to simplify machining feature recognition from discrete geometry. Once the features are recognized, an automated optimal cutter set selection approach aiming at a minimum machining time is proposed to improve the machining efficiency for arbitrary features. Additionally, an automated deburring tool path planning method is introduced to eliminate the manual edge deburring and specifically to work with 3D discrete geometry. With the robust and automated algorithms as a solid foundation, a fully automated tool path planning system with limited human interactions is built and demonstrated on a series of parts with complex intersecting features. The net result is a complete 3D CAM process that goes from geometry to G-code in less than 1 minute.
Recent technological advances have facilitated the use of mobile robots for a wide range of coverage applications such as inspection and mapping of infrastructure, precision agriculture, and disaster management. With the proliferation of these tasks comes an increasing need for autonomous systems to efficiently gather data pertinent for analyzing the state of the environment. The dissertation answers the following fundamental question: How should resource-constrained robots traverse the environment to collect data from all the relevant features? These features of interest can be represented as points, lines or curves, and areas. This dissertation unifies simultaneous coverage of all three types of features into a novel generalized coverage framework, develops algorithms for efficient coverage using multiple mobile robots, and validates them in experiments.
The dissertation comprehensively studies the line coverage problem, i.e., coverage of one-dimensional features, which lays the foundation of the generalized coverage problem. We develop algorithms to transform point and area features into linear features and use line coverage algorithms to solve generalized coverage efficiently. The algorithms substantially improve the state of the art while incorporating battery life constraints, nonholonomic constraints for robots that cannot take turns in place, and multiple home locations for large-scale environments.
Organic-inorganic hybrids may offer material properties not available from their inorganic components. However, they are typically less stable and disordered. A group of highly ordered II-VI based hybrid structures has been shown to possess various unusual properties and potential applications. As a prototype, β-ZnTe(en)0.5 can be viewed as a superlattice with alternating layers of two-monolayer thick (110) ZnTe and single-molecule length ethylenediamine. In contrast to all the known inorganic superlattices where interfacial diffusion is inevitable, we demonstrate in this thesis that β-ZnTe(en)0.5 exhibits an unusually high degree of crystallinity, as is evidenced by < 25′′ XRD rocking curve linewidth and < 1 cm-1 Raman linewidth, which are comparable to many high-quality binaries. Besides manifesting in the macroscopic scale crystallinity characterization, it also shows an exceptionally low level of microscopic scale defects, as suggested by the observed linear dependence of PL intensity on the excitation density over 6 orders of magnitude, which has not been possible even for the very high-quality CdTe and GaAs.
β-ZnTe(en)0.5’s highly-ordered crystallinity enables a systematic investigation of its vibrational property. We apply the orthogonal polarization and the angle-resolved polarization Raman techniques to study β-ZnTe(en)0.5’s vibrational modes. A set of orthogonal polarizations are used to decouple the vibration modes according to their symmetries. A mode-by-mode analysis allows unambiguous assignment for the Raman-active modes. A few exceptions and additional features are discussed. With the assignment, we demonstrated that the Raman tensor could be estimated from both the orthogonal technique and the angle-resolved technique. The two independent measurements yield consistent estimations. In addition, it has been shown that a combination of the two techniques enables unambiguous determination of the crystal orientations.
A distinction among the hybrid materials is its unprecedented ambient long-term stability over 15 years, which is still limited by extrinsic mechanisms but is already the longest documented hybrid semiconductor. In this work, we used Raman spectroscopy to investigate its degradation in air and a protected condition and framed the factors contributing to its long-term stability into (1) intrinsic effect such as large formation energy and large activation barrier in excess of the formation energy; (2) extrinsic factors, including surface or edge effect, where degradation can initiate through processes such as oxidation, and the structural defects, which may provide more accessible paths for degradation. Based on this approach, we estimate the room-temperature lifetime of β-ZnTe(en)0.5 in a protected environment can achieve 1.9x10^8 years, while in the ambient air, its lifetime is on the order of 10^1 years.
As the demand for wireless connectivity increases, new power and area efficient solutions will be required to meet the specifications of these systems. Most transceivers require a local oscillator with quadrature(I/Q) phases and the power and noise specifications of this oscillator plays a crucial role in the system performance. Although traditionally these oscillators were designed using on chip LC components, recent advances in manufacturing have opened the possibilities of incorporating Bulk Acoustic Wave(BAW) resonators in the design of such oscillators. In this work, we introduce a novel coupling technique for creating a Quadrature Voltage Controlled Oscillator(QVCO) which leads to a lower phase noise and power consumption compared to other published designs.
Teacher evaluations are routinely conducted across the United States for licensure and professional development supports. However, there is limited research on the interrater reliability of these evaluation assessment systems, despite federal recommendations (Graham et al., 2012). This research explores the systematic approach to interrater reliability utilized by the Early Educator Support (EES) Office in North Carolina. The EES Office supports the Birth-through-Kindergarten (B-K) teacher licensure of over 900 early educators in both private and public sectors. The evaluators employed undergo extensive trainings and hold a B-K license themselves. As part of the training, the evaluators undergo an interrater reliability activity that requires them to rate ten fictitious profiles, using the North Carolina Teacher Evaluation Process (NCTEP) Rubric. This research aims to understand the evaluator response process. In this study, Many Facets Rasch Models are used to understand evaluator patterns of strictness, leniency and potential bias based on the race of teacher profile. Additionally, two of the models are compared to understand the extent that these rater response patterns are exhibited in their real caseloads of actual early educators. In conclusion, the group of evaluators do show evidence of strictness, leniency, and bias, however it is mostly exhibited by a small number of individual evaluators. It is possible to use the results to inform the professional growth of these evaluators, so that all early educators served by the EES Office receive valid, fair, and reliable teacher evaluations. Furthermore, it depicts a systematic approach to interrater reliability that could be used by other evaluation systems across the country.
The manifestations of institutional and interpersonal racism have been linked to lower recruitment, retention and matriculation rates among ethnic minority students in predominantly white institutions (Harper, 2012). Those who experience racial and ethnic microaggressions have been impacted in numerous deleterious ways. Physical, mental, emotional and political outcomes have been examined in prior research (McGee & Stovall, 2016; Smith, Allen & Danley, 2007; Sue, 2010; ). In counselor training programs, specific coursework in multicultural education introduces counselors to the foundational aspects of the Multicultural and Social Justice Advocacy Competencies (Ratts et al, 2016) . Using Critical Race theory as a framework, a non-experimental, correlational survey design was used to explore the relationship between institutional type, perceived experiences of school-based racial and ethnic microaggressions, racialized experiences in multicultural coursework and social justice advocacy orientation among counseling students and professionals (N= 346). A standard multiple regression indicated a significant relationship between the school-based racial and ethnic microaggressions and racialized experience in multicultural coursework with social justice advocacy orientation. However, there was no significant relationship with social justice advocacy orientation and institutional type. Results from an independent sample t- test indicated there were significant differences between institutional type in experiences with school-based racial and ethnic microaggressions and racialized experience in multicultural counseling coursework. There however, was no significant difference between institutional type with regard to the social justice advocacy orientation of participants in this study.
Diet-related diseases like obesity and type-2 diabetes are on the rise. Precision nu- trition, a way to tailor dietary requirements for each individual, is heralded as a solution to these problems. However, nutritional research is held within sparse, siloed resources that rarely connect, which leads to significant barriers hindering the progress of precision nutrition. Three knowledgebases were produced as a re- sult of this work. The ABCkb 1.0 overcomes these barriers by linking 11 separate resources in the path from plants to disease through molecular mechanisms. This resource is built in Neo4j and provides a web-based interface available for browsing (https://abckb.charlotte.edu). A second knowledgebase, ABCkb 2.0 connects micro- biota information to diet and human health through the incorporation of text-mined associations from full text articles. The final knowledgebase produced links long-covid to dietary components through possible molecular mechanisms. These three knowl- edgebases promote progress in precision nutrition to tackle the rise in diet-related disease.
Previous research has investigated the school context using conceptualizations of two constructs, school culture and school climate, that appear to overlap and contain measurement flaws, limiting their utility in applied research settings. To improve learning conditions and promote more equitable academic opportunities and outcomes for students in grades 3-8, the Charlotte, NC, community would benefit from a standard system of measurement that captures the essential elements of school climate and culture that local stakeholders believe matter most for students to succeed in Charlotte-Mecklenburg Schools (CMS). CMS does not currently administer a comprehensive school culture or climate survey. The present study aimed to address that need. Through a multiphase, participatory community research project, a coherent, parsimonious, and clear conceptualization of school environment emerged, setting the stage for the development and initial validation of the School Environment Survey.
This collaborative effort involved the exchange of knowledge, expertise, and resources via a partnership involving the Community Psychology Research Lab at the University of North Carolina at Charlotte and two community partners: CMS and a nonprofit organization, Communities In Schools of Charlotte-Mecklenburg. During the first phase of this project, essential elements of school climate and culture were reviewed, analyzed, and discussed during interviews and focus groups with 126 local stakeholders until the broader construct of school environment had been defined as a category of concepts that reflect the surroundings or conditions in which people operate in school. With this broad definition of school environment as the underlying, multidimensional construct, five applicable concepts (i.e., domains; see Kohl et al., 2013; Wang & Degol, 2016) were hypothesized to make up school environment: academics, safety, shared vision, community, and physical environment. Multiple participatory steps led to the development of 131 items hypothesized and designed to reflect 16 identified dimensions of school environment, organized into these five domains.
The resulting measure was piloted online with 186 teacher participants during the 2020-2021 school year. Exploratory factor analysis results suggest that within the boundary conditions of this effort (i.e., a focus on two CMS learning communities, the inclusion of teachers from grades 3-8, data collected during school year 2020-2021), a 25-item School Environment Survey that captures three domains (academics, safety, and shared vision) may be a useful indicator of teachers’ perceptions of school environment. That model explained 55% of the total variance and, notably, items that performed well on the resulting version of the measure cover nearly the entire hypothesized breadth of the concept as it was defined and operationalized by stakeholders; reliability estimates met or exceeded acceptable thresholds; and school environment results were found to positively relate to student learning outcomes (specifically, standardized tests in reading and math for students in grades 3-8).
However, this study had a relatively small sample size that prevented researchers from conducting a confirmatory factor analysis, and COVID-19 presented additional challenges and limitations. Therefore, in addition to an overview of specific advantages and the empirical and theoretical support for the current version of the School Environment Survey, recommendations for ongoing validation are provided as well as considerations of the implications for local practice.
Passion can drive entrepreneurs to new heights of success and fulfilment, but the dark side can also lead to conflict with relationships and activities. Work addiction goes a step further as it demands the entrepreneur’s time and energy even when they are off the clock. This study explores the relationship between entrepreneurial passion and work addiction, leaning on the Dualistic Model of Passion. It also investigates the possibility that personality traits influence this connection. Empirical evidence suggests that obsessively passionate entrepreneurs are more likely to encounter work addiction than their less passionate counterparts. The data also supports a weak link between harmonious entrepreneurial passion and work addiction, with harmoniously passionate entrepreneurs being less susceptible to work addiction. Finally, there was minimal support for the idea that the Dark Triad traits (narcissism, Machiavellianism, psychopathy) play a role in this exchange. There is a secondary nuance to this study regarding passion and addiction. It provides evidence that passion with one target can relate to addiction with another. This encourages the examination of other cross-target passion and addiction relationships.
