22232 research outputs found
Sort by
Improved Electric Load Modeling of Residential Air Conditioning
No full textThe recent increase in energy production from renewable resource introduces a new challenge in managing and maintaining balance between electricity supply and demand, due to uncertainty and variability of wind speed and solar irradiance. To address this growing problem, demand-side management, such as Demand Response (DR) programs, is employed to adjust power consumption. Residential air conditioners (ACs) are the most suitable candidates for DR, due to their intensive power consumption and inherent thermal inertia that allows flexibility in their operations (by adjusting their set-point temperatures) without sacrificing customer comfort. Most prior research on AC load models assumes that such a load draws constant rated power when the unit is powered on. However, the power consumption depends on outdoor temperature. Furthermore, previous works focused on houses with a single AC load. However, a significant fraction of the homes, especially two-story buildings, have 2 AC units. Unlike AC cycling behavior observed in single-zone houses, where the duty cycles of an AC unit are relatively constant, the two-zone case exhibits varying duty cycles due to the air movement through the stairwells and the different temperature set-points. This thesis proposes an improved RC model of an AC load that takes into account the power consumption’s dependence on the ambient temperature. The model is then extended to a premise with two AC units, by coupling the air temperature dynamics between zones. Model parameters will be estimated using recorded historical data of some local homes. Some applications, including customer bill management under Time-of-Use (TOU) electricity rates and potential participation in grid services (ramping grid service, peak load management), will be assessed through time-series numerical simulation using local weather data
Developments on Abbreviations Towards Machine Reading Comprehension
No full textMachine reading comprehension is a critical step in development of applications that require the semantic understanding of human speech-to-text driven work. Many devices such as smart home appliances like the Amazon Echo Dot, Google Home, or smart assistants like Apple Siri or Microsoft Cortana are examples of these applications. The comprehension task involves a deeper understanding and recognition of named entities such as person names, locations, medicals codes, quantities, abbreviations, and acronyms in speech or text data. In this dissertation, we explore and extend the different approaches and techniques in modern research that tackles the problem of recognition and definition of acronyms and abbreviations. Also, we offer different techniques for disambiguation of abbreviations that are caused by the abundance and frequent introduction of new abbreviations. We provide the following contributions: 1) A historical background on the rule-based and statistical methods for finding acronyms and their definitions. 2) A method based on the bidirectional encoder representations from transformers question answering model to find acronym definitions in each document. Our experiments show that this model can correctly predict 94% of acronym expansions assuming a Jaro–Winkler threshold distance of greater than 0.8. 3) An exploration of the different approaches and techniques to solve the problem of ambiguous abbreviations and their definitions. We reverse engineered the process of creating ad hoc abbreviations and found some preliminary statistics on what makes them easier or harder to define. In addition to recognition and definition of acronyms and abbreviations, this dissertation contributes to a systematic generative method to create datasets and use them to build a corpus for acronym expansion. Our approach for data generation can be used in many applications where there are no standard datasets
Oral Prevalence of Selenomonas Noxia Differs Among Orthodontic Patients Compared to Non-Orthodontic Controls: A Retrospective Biorepository Analysis
No full textIntroduction: The introduction of fixed orthodontic brackets in orthodontic therapy has the potential to significantly alter the oral microbial flora. Most orthodontic research has focused on cariogenic pathogens, while some evidence has demonstrated an increase in many known periodontal pathogens. However, little is known about the prevalence of the gram-negative periodontal pathogen, Selenomonas noxia (SN) among these patients.Methods: Using an existing saliva biorepository, n=208 samples from adult and pediatric orthodontic and non-orthodontic patients were identified and screened for the presence of SN using qPCR and validated primers. Results: In the pediatric study sample (n=89) 36% tested positive for the presence of SN with orthodontic patients comprising more SN- positive samples (87.5%) than SN-negative samples (78.9%), p=0.0271. In the adult study sample (n=119 ), SN was found in 28.6% with orthodontic patients comprising 58.8% of positive samples and only 28.2% of negative samples,, p\u3c 0.0001. Conclusions: These data demonstrated that both pediatric and adult orthodontic patients exhibited higher prevalence of SN compared with age-matched non-orthodontic controls. As this organism is associated not only with periodontal disease, but long-term health issues such as obesity, more research is needed regarding the factors that increase prevalence of this organism
Enhancing Therapeutic Use of Self: The Value of Unfolding Case Studies in Occupational Therapy Education
No full textObjective: This capstone project evaluated the effectiveness of using unfolding case studies (UCS) as a supplemental instructional method to enhance occupational therapy (OT) students’ self-efficacy (SE) in applying therapeutic use of self (TUOS), a core competency in OT education.Methods: Four workshop modules were delivered to and completed by OT students (n=3) enrolled in the occupational therapy doctorate program at the University of Nevada, Las Vegas. The sessions included instructional content, guided discussions, unfolding case study activities, and a TUOS competency. The Self-Efficacy for Therapeutic Use of Self (SETUS) Questionnaire was administered at four points throughout to monitor perceived self-efficacy over time. Findings: Descriptive statistics indicated progressive increases in SETUS scores across all subscales—Self-Efficacy for Therapeutic Mode Use (SETMU), Recognizing Interpersonal Characteristics (SERIC), and Managing Interpersonal Events (SEMIE)—from baseline to post-competency. Qualitative feedback supported these findings, highlighting the workshop’s relevance and the unfolding case study format’s value in promoting confidence and real-time clinical reasoning. Conclusion: Students\u27 perceptions of their self-efficacy in TUOS were positively affected by the UCS-based workshop, suggesting more meaningful and effective ways of bridging theoretical knowledge and practical application in OT education through unfolding case studies. Implementing similar approaches in the future may contribute to the development of other interpersonal and clinical competencies essential to OT practice
Clustering of Internet Behaviors and Associated Mental Health Outcomes Among U.S. Adolescents
No full textIn recent years, the Internet has become an integral part of daily life, influencing education, work, and recreation. As of 2024, approximately two-thirds of the global population is online, with an estimated one-third of users under the age of 18. Given the potential long-term effects of excessive Internet use on health and well-being, adolescents represent a critical population for monitoring online behaviors. This study used baseline data from the SHARE project and conducted a latent class analysis (LCA) to identify patterns of Internet use among a sample of adolescents and the relationship of class membership with mental health outcomes, including Internet addiction, anxiety, depression, and suicidal ideation. The LCA resulted in a four-class solution: “high entertainment use”, “low Internet use”, “gaming-streaming”, and “high Internet use”. Class membership was significantly associated with depression, anxiety, and Internet addiction while membership in the “high Internet use” class was associated with the worst mental health outcomes. Targeted interventions are recommended for adolescents based on their patterns of Internet use, and future research is recommended to focus on age and gender disparities as well as possible moderating factors such as genre of online game and motive for use
Difference in Condylar Position, Dimension, and Angle Among Different Vertical Skeletal Patterns, A Retrospective CBCT Study
No full textIntroduction: This study aimed to evaluate and compare the condylar dimensions, position, and angulation among individuals with different vertical skeletal patterns—hyperdivergent, hypodivergent, and normodivergent—using cone-beam computed tomography (CBCT). The objective was to determine whether vertical skeletal variations influence temporomandibular joint (TMJ) structure and function, providing insights for improved orthodontic diagnosis andtreatment planning.
Methods: A retrospective analysis was conducted on CBCT scans from 185 adult patients (370 TMJs) from the orthodontic clinic at the University of Nevada, Las Vegas. Patients were categorized into three vertical skeletal groups based on the Frankfort horizontal-mandibular plane angle (FMA): hypodivergent (\u3c 20°), normodivergent (20°–30°), and hyperdivergent (\u3e30°). Condylar width, length, height, joint spaces, and condylar angulation were measured using OnDemand 3D software. Descriptive statistics, ANOVA, and post hoc analyses were performed to evaluate differences across skeletal patterns, sex, and ethnicity.
Results: Significant differences in condylar morphology and position were found among the three skeletal groups. Hyperdivergent individuals exhibited significantly smaller medio-lateral condylar widths (p \u3c 0.05) and reduced superior joint spaces, indicating a higher condylar position within the TMJ. Males had significantly larger condylar dimensions than females, with wider medio-lateral condylar widths and greater superior and posterior joint spaces (p \u3c 0.05). Ethnic differences were also observed; African American participants had significantly greater condylar height, while Caucasian individuals had the largest medio-lateral condylar width compared to Hispanics.
Conclusions: This study highlights the influence of vertical skeletal pattern, sex, and ethnicity on condylar morphology and spatial positioning. Hyperdivergent individuals demonstrated distinct condylar adaptations, which may have clinical implications for TMJ assessment and orthodontic treatment planning. Understanding these variations is essential for personalized orthodontic and orthopedic interventions
Beyond Single Metrics: A Holistic Benchmarking Framework for Low-Power Embedded Systems
No full textModern embedded systems encounter a notable challenge in evaluation. While devices may meet traditional benchmarks, they often underperform in real-world applications due to neglected interactions at the system level. Current benchmarking suites, such as MLPerf Tiny and EEMBC ULPMark, evaluate specific metrics including computational throughput, energy efficiency, and memory usage. However, they do not consider the complex interdependencies that affect real-world performance. This thesis presents a benchmarking framework that concurrently evaluates multiple performance dimensions under realistic workloads, revealing system behaviors that are often hidden in conventional benchmarks.Through the comprehensive evaluation of three representative algorithms: Fast Fourier Transform, quantized neural network inference, and Dijkstra\u27s shortest-path algorithm, across 33 hardware platforms, including ARM Cortex-M microcontrollers, ultra-low-power FPGAs, and edge AI accelerators. By integrating cycle-accurate hardware models with RTOS scheduling, power state transitions, and I/O emulation, our framework uncovers critical system-level effects: memory requirements 2.5×-9.6× higher than algorithm size alone (averaging 8.4×), performance degradation up to 42.8% from I/O interference, and power state transition overheads that can dominate energy consumption at low duty cycles. Our simulation-based analysis identifies previously overlooked factors, including bus contention between CPU and DMA operations, interrupt-induced cache pollution, and priority inversion penalties, which collectively impact performance by 20-40%. We present the following contributions: (1) a cohesive measurement architecture that links previously isolated metrics, (2) quantitative evidence revealing systematic measurement errors in current benchmarks, and (3) empirically derived design guidelines that incorporate 2-3× memory safety margins and platform selection criteria informed by observed system behavior. This research allows precise performance forecasting for resource-limited systems, shifting embedded system design from intuition-based approaches to data-driven optimization
Assessing the Impact of CDBG And Home Block Grants on Housing Affordability in the Las Vegas–Henderson–Paradise Metropolitan Statistical Area
No full textThis dissertation aimed to analyze the impacts of aggregated federal funding from the CDBG and HOME block grants on temporal changes in the Housing Affordability Index (HAI Change). The temporal change in Housing Affordability between 2011–2015 and 2016–2020 was constructed as the dependent variable to measure the direct and indirect impacts of CDBG/HOME funding. Therefore, this dissertation seeks to identify the impacts of aggregated funding on changes in housing affordability and to explore spatial spillover effects through spatial dependencies that may influence housing affordability change as a dependent variable. The geographical area of this study is the Las Vegas–Henderson–Paradise MSA, Nevada. Research data were collected as secondary data from two primary sources: the ACS five-year estimates (2011–2015 and 2016–2020), and the HUD’s CDBG and HOME dataset portals. The unit of analysis for the models is the census tract, with all finer-level data aggregated accordingly. Finally, four testable models are specified to respond to the research questions.The first model, the OLS model, is designed to address the first research question: Do the CDBG/HOME block grants impact the temporal change of housing affordability? The estimated result for the main hypothesis indicates that CDBG/HOME funding per capita is significantly and negatively associated with housing affordability change and successfully rejects the null hypothesis (1-1). The second model, the SAR model, addresses the research question regarding the spillover effects of housing affordability change (HAI Change) in neighboring areas on the housing affordability change in a given location. The estimation results for this model indicate an insignificant direct impact of CDBG/HOME funding per capita on HAI Change and fails to reject the null hypothesis (2-1). However, the results confirm significant and positive spatial spillover effects of HAI Change on affordability change in a given location or census tract and successfully rejects the null hypothesis (2-2). The third model, the SARMA model, assessed spatial dependencies beyond those captured by the regular SAR Model by estimating the direct impact of CDBG/HOME funding per capita on HAI Change, along with potential spatial dependencies in the dependent variable (HAI Change) and residuals (error term). The results confirmed an insignificant association between CDBG/HOME funding and housing affordability change (HAI Change) (failing to reject Null Hypothesis 3-1), while also indicating the presence of significant spatial dependencies for HAI Change and unobserved elements (error terms) (rejecting Null Hypotheses 3-2 and 3-3). This means that CDBG/HOME funding per capita does not impact HAI Change as the outcome variable, but HAI Change and unobserved elements in neighboring areas significantly produce spillover effects on affordability change in a subject area or neighborhood. The last model, the Spatial Durbin Model, measured the direct impact of CDBG/HOME funding per capita, the spillover effects of funding, and the spillover effects of HAI Change in neighboring areas on HAI Change. The SDM demonstrated a better fit to the data compared to the other models examined in this study. The results of the main hypothesis test in this model revealed that the model failed to reject the null hypotheses for the direct and spillover effects of CDBG/HOME funding per capita on HAI Change (Null Hypotheses 4-1 and 4-2). On the other hand, the results confirmed the spatial spillover effects of affordability change in neighboring areas on HAI Change in a given neighborhood and led to reject the Null Hypothesis 4-3. As conclusion, the OLS model indicated a significant and negative impact of CDBG/HOME funding per capita on HAI Change. However, after controlling for spatial elements—specifically, the spatial lag of dependent and independent variables and the error term—the results of the estimated spatial econometric models confirmed that CDBG/HOME funding is no longer significant. In other words, the impact of CDBG/HOME funding on HAI Change disappeared after controlling for spatial elements. Housing affordability changed because of spatial clusters, not due to funding allocation. Lastly, a set of actionable recommendations is developed for the CDBG/HOME programs administration
Correlation Between ATNR Retention and Sensory Processing Difficulties in a Pediatric Occupational Therapy Population
No full textThis study aimed to examine the correlation between retained Asymmetric Tonic Neck Reflex (ATNR) and sensory processing difficulties in children. A review of the literature available contributed to understanding the relationship between these; however, the limited research indicated a need for further examination to provide practitioners with evidence-based research for comprehensive care and improved occupational performance in children. A small correlational study was conducted using the snowball method with convenience sampling. The study yielded six participants from an occupational therapy outpatient clinic, A Clubhouse for Kids. Caregivers completed the Sensory Profile 2 in hard copy to assess their child\u27s sensory needs, while ATNR was evaluated using Schilder\u27s Test of ATNR. The results demonstrated that there was a strong correlation between a retained ATNR and sensory processing difficulties exists (Rs=+1). Due to the various limitations, including a small sample size from the same clinic, the generalizability of the study may be limited. Despite this, the results provide evidence that it may be beneficial for practitioners to test for ATNR when working with this population. In addition, it gives occupational therapists and other professionals who work with this population evidence that targeting reflex integration in their interventions may be beneficial to improve the child’s outcomes due to the potential impact the retained reflex has on sensory processing
Enhancing Student Engagement and Support With a Discord Ticketing and AI-driven FAQ System
No full textAs the CS 202 Coordinator overseeing seven sections per semester, I introduced a Discord-based ticketing system to streamline student support and engagement. Traditional methods like office hours and email often created delays, whereas the ticket system allows students to receive timely help from any available TA, regardless of section. To further enhance accessibility, we added a public FAQ channel that displays resolved tickets, helping students quickly find answers without combing through chat logs. This approach supports learners with shorter attention spans and builds a shared knowledge base. Additionally, we are compiling these interactions to train an AI chatbot capable of instantly answering common questions, allowing human staff to focus on more complex issues and continuously improving the course’s instructional support.https://oasis.library.unlv.edu/btp_expo/1204/thumbnail.jp