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The Housing Act of 1949 set its goals to revitalize American cities and provide adequate housing and suitable living environments for families. Although this goal has been achieved for some Americans, the lack of affordable housing and homelessness continues to be a serious public policy issue. Chronic homelessness, after declining for years, is on the rise. As a remedy, many cities have adopted the Housing First model, as part of their Continuum of Care, to place people who are homeless into housing. The purpose of this study was to learn more about the locations of Housing First placements and assess their proximity to supportive services in Charlotte, North Carolina. Using geospatial analysis, the findings revealed that housing placements were quite concentrated, with the majority being located in just six zip codes, where median rents were well below the city’s average and poverty rates were higher. Residents were also disproportionately Black or Hispanic. Although most housing placements were close to bus stops, they were not close to other services (e.g., grocery stores, pharmacies, hospitals, schools, or recreation areas). Moreover, nonprofit service providers responding to an online survey acknowledged that transportation, staffing, and funding for supportive services could be better. By adopting Housing First and implementing other efforts to increase affordable housing, Charlotte has demonstrated a clear interest in preventing and ending homelessness. Yet, there are still opportunities to do things differently by learning from other communities, which have adopted a range of creative and innovative policy solutions.
The AI-digital era is characterized by an unprecedented surge in data usage, spanning from data centers to IoT devices. This growth has driven the evolution of AI-optimized networks, designed to fuse AI capabilities with advanced network solutions seamlessly. However, these networks grapple with challenges such as the complexity of network layer protocols, discrepancies between simulated AI models and their real-world implementations, and the need for decentralized AI training due to network distribution.
To address these challenges, we propose the AI-oriented Network Operating System (AINOS). At the core of AINOS are two foundational sub-platforms: the "Network Gym," tailored for AI-driven network training, and "Federated Computing," designed for decentralized training methodologies. AINOS provides a comprehensive toolkit for rapid prototyping, deployment, and validation of AI-optimized networks, bridging the gap from simulation to real-world deployment.
Harnessing the powerful features of AINOS, we prototyped AI-optimized networking solutions using a safe Reinforcement Learning (RL) strategy for Traffic Engineering (TE) at both the link and network layers. At the link layer, we implemented a scalable RL-based traffic splitting mechanism that learns optimal traffic split ratios across Wi-Fi and LTE through guided exploration. For the network layer, we devised an online Multi-agent Reinforcement Learning (MA-RL) approach with domain-specific refinements to determine optimal paths in real-time for wireless multi-hop networks. In our exploration of Network Assisted AI optimization, we reduced Federated Learning training time with our MA-RL multi-routing approach and proposed a robust Decentralized Federated Learning solution that leverages single-hop connections for enhanced network performance. Our results demonstrate the strengths of AI-enhanced networks in proficiently managing heterogeneity and latency.
Young children are assessed to meet federal mandates and inform policy decisions, provide teachers with useful information to make instructional decisions and set reasonable learning goals, and facilitate communication with families. While young children are frequently assessed using whole-child assessments which often yield criterion-referenced score interpretations, norm-referenced score interpretations can help teachers understand relative performance and set reasonable goals for growth. Although researchers have provided validity evidence for both criterion- and norm-referenced score interpretations for one widely used early childhood assessment, GOLD®, current national normative scores lack precision for several reasons, including the use of two-time-point and cross-sectional data. To improve estimates, a nationally representative sample of assessment records from 18,000 children ages birth through kindergarten was fitted to a series of hierarchical linear models (HLMs) to establish normative estimates conditional on months of age or instruction. Secondary study purposes included making inferences about the nature of growth from birth through kindergarten, providing evidence of the most effective time metric for modeling developmental growth, and examining the relationship between child-level characteristics and normative scores. Results indicated that a) HLMs provide reasonably valid normative ability and growth estimates, b) developmental growth, as measured by GOLD®, from birth through kindergarten is non-linear, c) the most effective time metric depends on the age band and domain of development, and d) child-level characteristics, including, race/ethnicity, gender, and primary language are associated with significantly different patterns of preliminary performance and growth for children who are one- or two-years of age or older.
Teacher preparation programs (TPPs) can equip preservice teachers (PSTs) with skills to implement evidence-based interventions in reading with fidelity by engaging PSTs in carefully designed clinical experience opportunities. Providing PSTs with extensive feedback through coaching is one method to strengthen support for PSTs’ implementation of evidence-based interventions, improve PSTs’ fidelity of implementation, and increase the likelihood of positively impacting students’ reading outcomes. This study contributed to gaps in the literature on preparing elementary education PSTs to implement evidence-based practices (EBPs) in reading with fidelity and the impact of sustained and responsive feedback during an authentic reading tutoring clinical experience. To individualize coaching support and facilitate a responsive approach to coaching centered on PSTs’ levels of fidelity, first, this study examined the impact of a multilevel coaching intervention on PSTs’ fidelity of implementation of an evidence-based reading intervention during a tutoring clinical experience. Second, this study examined PSTs’ perceptions of the feasibility, effectiveness, and future impact of the multilevel coaching intervention.
Results of this single-case, multiple baseline across participants study indicated a functional relation between the multilevel coaching intervention and PSTs’ fidelity of implementation, inclusive of both structural and process dimensions of fidelity. Furthermore, PSTs found the multilevel coaching intervention to be socially valid, indicating the intervention was feasible, effective, and impactful on their future teaching experiences. The findings of this study provide relevant implications regarding teacher preparation and coaching support. Major implications include (a) providing PSTs as novice learners with authentic clinical experiences, inclusive of coaching support, when implementing EBPs; (b) viewing fidelity as a multidimensional construct that can inform coaching support and teacher practices; and (c) enhancing TPPs with experiences that impact PSTs’ beliefs and perceptions about teaching reading and their own ability to do so. A few suggestions for future research include (a) investigating the efficiency of various coaching models at supporting PSTs to implement EBPs with fidelity, (b) examining the role of instructional pacing and other factors that may impact the extent to which EBPs are implemented with fidelity, (c) determining the effects of multiple dimensions of fidelity (i.e., structure and process) and the interaction on student outcomes, and (d) extending research findings on coaching supports that impact PSTs’ knowledge and the subsequent impact on student outcomes in reading.
Reports of 2022 employment rates demonstrate that while 65.4% of adults without disabilities are employed, only 21.3% of adults with disabilities are employed (U.S. Bureau of Labor Statistics, 2023). In 2022, data indicated 30% of adults with disabilities who were employed worked parttime jobs, nearly twice as much as those without disabilities (16%). Yet, research indicates that adults with disabilities can be integral parts of the workforce (Lipscomb et al., 2017; Lombardi et al., 2022; Luecking & Fabian, 2000; Newman et al., 2011). Researchers have reported that employees with disabilities are unable to maintain employment often due to difficulty fitting in socially at the workplace (Brickey et al., 1985; Butterworth & Strauch, 1994; Chadsey, 2007; Greenspan & Shoultz, 1981; Kochany & Keller, 1981; Wehman et al., 1982). Since 2009, social skills performance has been identified as a predictor of postschool success (Mazzotti et al., 2016, 2021; Test et al., 2009) meaning that students with disabilities who exited high school were more likely to participate in postschool employment (Benz et al., 1997; Roessler et al., 1990; Test et al., 2009).
Social skills challenges have been identified as one potential barrier to obtaining and maintaining employment for adults with disabilities (Bury et al., 2020; Kochman et al., 2017; Parker et al., 2018). While there is a strong link between social skills performance and success in the workplace, there are limited data on the interventions to maintain teaching these skills to adults with disabilities. Researchers have used different methods to create different intervention or strategies to help individuals with disabilities improve their social skills including specific curricula such as Conversing with Others and WAGES (Lu et al., 2020; Murray & Doren, 2013), instructional models such as the SDCDM and SDLMI (Dean et al., 2021; Shogren et al., 2018), in-ear coaching (Gilson & Carter, 2016), and video modeling (Bross et al., 2019, 2020; Whittenburg et al., 2022); however, these studies do not focus on social interactions between adults with disabilities and their coworkers to increase behaviors, rather communicating with coworkers or communicating about work tasks.
The purpose of this study was to evaluate the effects of a video modeling and a visual support intervention package on appropriate coworker social skills in the workplace for young adults with disabilities. I also collected data on participants’, coworkers’, and the employer’s perceptions of this study's goals, procedures, and outcomes Results of this study indicated a functional relation for one of the two participants. In addition, the participants, employer, and coworkers found the intervention to be socially valid across most measures. The dissertation includes a review of the literature, methods, discussion of each research question, study limitations, directions or future research, and implications.
Throwing arm injuries are common because of the demand on the shoulder. Shoulder exams and pitching mechanics are regularly monitored by team physicians. Excessive instability and joint loading in baseball pitching are risk factors for throwing arm injuries. Altering baseball pitching mechanics affects both performance and the risk of injury. The purpose of this study is to investigate the relationship among injuries, shoulder exam variables, and pitching biomechanics in collegiate baseball pitchers. Pitching biomechanics, shoulder exam tests, and self-reported injury questionnaires were used to study 177 collegiate baseball pitchers. Pitching biomechanics where high-speed cameras record the athlete pitching. This allows us to capture both the athletes body position and calculate joint loadings. Shoulder exam tests where the athletes lay on their backs and their shoulder range of motion, flexibility, and stiffness is measured. Injury questionnaires is where the athletes report if they have had any injuries or surgeries. Our findings show that the shoulder exam, pitching biomechanics, and injury questionnaire variables are related. The ability to understand the relationship between shoulder exam variables, baseball pitching mechanics, and injuries helps further our knowledge and pushes forward the underlying goal of this study which is to improve performance and reduce injuries.
This dissertation explores the fascinating realm of metamaterials and electromagnetic engineering, with a focus on metasurfaces, dual-polarization metascreens, novel dual-band antennas, and time-varying components. Metasurfaces, two-dimensional arrays of subwavelength structures, offer compact solutions to manipulate electromagnetic waves, finding applications in optical devices, imaging systems, communication, and sensing.
The pivotal contribution of this research is the development of dual-polarization metascreens, which enable simultaneous control of horizontal and vertical polarizations. This innovation enhances radar systems, wireless communication, and remote sensing by rapidly switching between polarizations, improving data rates and accuracy.
The dissertation further explores dual-layered antennas operating in Ka and W bands, addressing unique challenges and expanding the boundaries of electromagnetic engineering. This breakthrough has applications in connectivity technology, radar systems, and millimeter-wave technologies.
Additionally, the study emphasizes the importance of rapid dispersion curve calculations and 3D printing for antenna design, accelerating research and development in communication, sensing, and connectivity technologies.
The dissertation concludes by delving into the emerging field of time-varying parameters, particularly time-varying networks composed of lumped elements. This research introduces a novel approach involving aperiodic time modulation of a single capacitor to capture energy from arbitrary pulses. These innovations promise new functionalities in electromagnetic systems, highlighting the interdisciplinary and innovative nature of this research.
In summary, this dissertation covers a wide range of topics in electromagnetic engineering and photonics, showcasing innovative applications and pushing the boundaries of the field.
Limited studies address high school gifted students' social and emotional needs (Knudsen, 2018; Kregel, 2015). Additionally, there is a lack of research regarding high school gifted students' and AIG directors' perspectives on the social and emotional strategies implemented locally within their school districts (Clinkenbeard, 2012; Kitsantas et al., 2017). Therefore, the purpose of this dissertation was (a) to discover the services school districts proposed to implement to meet the social and emotional needs of high school gifted students and (b) to explore high school gifted students’ and AIG directors’ perspectives about these services. Using purposeful sampling, this qualitative research included five participants from two school districts. The data collection methods implemented during this study were compiling school documents (i.e., 2022–2025 Local AIG Plans ) and conducting five separate interviews. I used document analysis to analyze data from the Local AIG Plans and thematic analysis to analyze data from the interviews. Results from the document analysis yielded three themes: program-level and curricula strategies, resources and support, and collaboration and counseling strategies. Results from the thematic analysis of interviews yielded three themes on how schools implement social and emotional services from the participants' perspective: social and emotional services, interaction, and gathering and sharing information. Further, the thematic analysis of participants' in-depth perspectives about these services yielded three themes: satisfaction and awareness, counseling, and limitations and improvements.
Random anti-reflective nanostructured surfaces (rARSS) enhance optical transmission through suppression of Fresnel reflection at layered-media boundaries. Windows with rARSS treatment are characterized (transmittance, reflectance, and scatter) using spectrophotometry and scatterometry to assess transmissive scatter performance over various spectral bands. Using measured spectral data, partial-integrated scatter values were obtained, allowing the comparison of random anti-reflective surface performance to optically flat surfaces.
Using a transfer function approach, an approximation of far-field light scatter can be modeled based on surface statistics. rARSS feature topology was determined using optical profilometry to obtain statistical surface roughness parameters, to assess the structured-surface feature scales. Random rough surfaces are well-modeled by Gaussian statistics, making them ideal candidates for a surface transfer function approach of surface scatter analysis.
The Generalized Harvey-Shack surface scatter theory was used to calculate surface feature diffractive effects. Scatter distributions predicted using a Gaussian two-parameter model of a random surface and structured surface metrology data were compared to measured scatter data for assessment of the transfer function model validity within the bandlimit of interest. Results show that prediction of wide angle rARSS optical scatter is viable using the transfer function approach, but the theory fails to predict transmission enhancement due to the inclusion of roughness.
The significance of this study was to give an active voice to the experiences of women superintendents. By giving voice to the lived experiences of women superintendents, the study sought to further understand the phenomenon of women dominating the teaching profession and other entry-level positions in education yet having a noticeably limited presence in the superintendency. More specifically, studying the barriers and supports women superintendents encounter could lead to significant opportunities to narrow the gender gap of women in the superintendency. Bringing awareness to the barriers and supports women superintendents experience could also foster more equitable workplaces. This qualitative, exploratory study aimed to identify barriers and supports faced by women school district superintendents as they ascended into the role and while they serve in the role. In this basic qualitative study, the researcher’s data sources involved semi-structured, one-on-one interviews with women superintendents. Results of the study indicate that participants felt that advancement factors were multifaceted and systematic, and employment pathways impacted options. In addition, personal obstacles acted as a barrier to reaching the superintendency. Also, gender discrimination was present while ascending to the superintendency and while serving in the role. Results also concluded that women superintendents credited their ongoing success to mentors and professional development. Implications included the need for awareness of leadership development opportunities for women in education, elimination of the glass ceiling, and additional research from women who aspire to be superintendents.
