University of Central Florida
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Advancing Temporal Safety Performance Functions: A Comprehensive Evaluation of Express Lanes, Ramps, and Ramp Metering Effects On Freeway Safety
No full textFreeway safety remains a critical concern, especially in high-risk areas such as ramps, merges, and managed lane segments, where complex traffic interactions significantly elevate crash risks. This dissertation advances crash frequency prediction by developing short-term Safety Performance Functions (SPFs) that address the limitations of traditional long-term SPFs models and real-time safety analysis. By leveraging high-resolution microscopic traffic detector data from multiple states, the dissertation introduces innovative methodologies and delivers actionable insights into freeway safety dynamics. The dissertation pioneers the application of Multivariate Poisson-Lognormal (MVPLN) models to identify interdependencies between crashes at ramp and merge segments. To address challenges like data skewness and excessive zeros, advanced Bayesian frameworks, including the Negative Binomial Lindley (NB-L) and Poisson-Lognormal Lindley (PLN-L) models, are proposed. Additionally, a novel copula-based framework uncovers intricate safety relationships between Express Lanes (ELs) and General-Purpose Lanes (GPLs), offering new perspectives on inter-lane safety, particularly at critical access points. The key findings of the dissertation emphasize the significant role of traffic exposure, geometric configuration, and operational strategies in shaping crash risks. For instance, managed lanes, such as the I-4 Ultimate Express Lanes, exhibit unique safety patterns, with elevated crash risk associated with higher rightmost lane occupancy near merge areas. Ramp metering (RM) is demonstrated to effectively reduce crashes, particularly in weaving areas, with safety impacts varying based on control strategies and segment types. This dissertation delivers a robust framework for crash prediction and safety assessment, blending methodological advances with practical insights. Its contributions lay the groundwork for safer freeway designs, optimized Active Traffic Management (ATM) strategies, and enhanced safety practices. By bridging the gap between theoretical research and iv real-world applications, this dissertation equips policymakers, engineers, and researchers with the tools needed to improve freeway safety
Florida Title I School Principals\u27 Characteristics and Practices in Professional Learning as Related to Student Reading Achievement
No full textThis study explored the relation between Florida’s Title I elementary school principals’ characteristics and how they design professional learning with student reading achievement. This study used Descriptive Statistics, Spearman’s Correlation, Independent Samples T-tests, Pearson’s Correlation, and ANCOVA to explore the relation between 259 of Florida’s Title I public elementary school principals’ characteristics (years of experience, number of state reading certifications, degrees, and level of autonomy) and how they design professional learning with student reading achievement. The research design was quantitative and correlational. Data was collected from 58 districts through a piloted survey using parametric sampling. A statistically significant difference was found between the number of degrees a Florida Title I public elementary principal has and their school’s third grade mean scale score in reading, rs(259) = .125, p \u3c 0.5. Implications indicate, it is possible that if a Title I elementary principal in Florida has an educational specialist or doctoral degree, their school reading achievement is likely to be higher
Hallucinogen Usage, Experiencing Mystical Phenomena, and Transformational Identity Change
No full textThis study seeks to understand the therapeutic potential of multiple prominent hallucinogens (LSD, Psilocybin, MDMA, Cannabis, and DMT) by examining corresponding posttraumatic growth, transformational identity change, and experience(s) of mystical phenomena. College students (N = 278) completed an anonymous online survey. The data was analyzed to assess hallucinogen usage history and possible changes, as well as any significant differences between each hallucinogen. Participants were first asked about their hallucinogen usage including which hallucinogens they have specifically used, number of uses, age of first use, and the last time they used. They were also asked to rate their short-term vs long term reactions from memory, as well as identity changes they may have experienced from their hallucinogen usage. They then answered The Posttraumatic Growth Inventory (PTGI-X; Tedeschi et al., 2017) which was adapted for this study by asking if the possible growth/change they experienced was a result of hallucinogen usage. Next, participants answered The Scales for Transformational Change (Waterman et al., 2020) to assess for possible identity changes because of hallucinogen usage. Lastly, participants were presented with The Mystical Experience Questionnaire (MEQ-30; Maclean et al., 2012), which attempts to characterize hallucinogen-oriented spiritual experiences and determine the role mystical experiences may play when engaging in hallucinogen use. Possible correlations did arise between classic hallucinogen usage, mystical experiences, and resulting posttraumatic growth and transformational change. Data analysis does suggest that classic psychedelics yield more significant identity changes than cannabis or MDMA
Requisites for a Dream: An Evaluation into the National Urban League’s Adjustment Efforts for Southern Migrants, 1911-1930
No full textThe American Dream is loosely defined as a universalist rhetoric that promises any American the opportunity to succeed in life. However, for African Americans this has not always been guaranteed. Historiography around the mantra uncovers a gap in consideration for Black Americans’ unique marginalization in American society despite their long history within the nation. This paradox inspired a myriad of proposed solutions towards racial disparities, with the early twentieth century favoring ideas of racial uplift as a panacea for prejudice. This thesis examines the use of racial uplift as a solution by the National Urban League during the first half of the Great Migration.
The central argument addresses how in the early twentieth century the National Urban League’s standards of conduct attempted to shape the social conditioning of Black migrants and how these standards were influenced by enduring, nationalistic traditions. The work of the National Urban League, chronicled through their annual reports from 1911-1930, illuminated complicated dynamics between Black migrants and the Black middle-class, southern cultural ties and northern societal expectations, and citizenship and racial inequality. Ultimately, the thesis evaluates a specific institutional approach towards racial uplift and posits that the very nature of the National Urban League’s efforts to “adjust” or mold the migrant contradicted ideas of an American Dream of innate equality and opportunity
Towards High-Performance, Low-Overhead Integrity Authentication for Secure-Memory in Embedded and Heterogeneous Computing Platforms
Get PDFThe use of secure-memory has been crucial for embedded and heterogeneous computing systems, especially in the light of emerging memory adversaries. The state-of-the-art hardware platforms targeting different sectors such as Internet-of-Things (IoT) and cloud computing require strong protection against memory exploits through different side-channel attacks. Such a tamper-resistant memory system comprises different security techniques such as encryption and integrity protection. Generally, the integrity protection against the adversarial attacks in secure-memory platforms relies on integrity trees such as the Bonsai Merkle Tree (BMT). However, the highly-recursive authentication and update algorithms associated with such tree structures are challenging to implement in heterogeneous systems with domain-specific acceleration (such as FPGA) for secure-memory. In the scope of this dissertation, we talk about four research works that highlight novel algorithmic, microarchitectural and logic design techniques for high-performance integrity authentication processes in secure-memory platforms. The first work focuses on hardware-efficient verification of the memory integrity with lazy-update BMT on an FPGA-based secure embedded system. It proposes an innovative partitioned parallel cache structure that leverages the unique reconfigurable capability of modern FPGA devices and successfully circumvents the hardware implementation challenges due to the recursiveness in lazy-update methods. The second work, HMT, is a hardware-friendly BMT algorithm that enables the verification and update processes to function independently. The HMT algorithm is hardware-targeted, parallel and it relaxes the update depending on BMT cache hit but makes the update conditions more flexible compared to lazy update. The third work, OMT, devises a run-time adaptive and unified BMT framework that can protect both volatile and non-volatile memory systems with optimal performance. Finally, CTR+ introduces a novel metadata access scheme to ensure significant BMT overhead reduction through speculative verification and concurrent secure computation
Novel Symmetrical Components-Based Methods for Protection of Systems with High-Level Penetration of IBRs
Get PDFThe global electric power system is undergoing a transition which has resulted in the proliferation of inverter-based resources (IBRs), mainly renewable energy resources and battery energy storage. These offer the advantage of decarbonization targets in electricity generation while potentially improving resilience and overall efficiency of the electric grid. Furthermore, this has led to the development of inverter-interfaced microgrids at the sub-transmission, and especially, distribution levels.
An effective protection system is a prerequisite for any power system operation. However, the departure of modern power systems, in this regard, from conventional sources and topologies presents new challenges to effective protection from power system faults. Active distribution networks formed by integration of IBRs introduce bi-directionality in fault current flow. This is a major departure from the radial nature of fault currents in conventional distribution systems. This impacts the selectivity and security of existing protection systems.
Similarly, the sensitivity and dependability of existing protection systems are impacted by in modern systems due to the fault current magnitudes of IBRs. Based on the state-of-the-art, these current levels are significantly lower than current contribution from conventional sources. In fact, the general characteristics of IBR fault signatures tend to depart from traditional sources. In order to accommodate high penetration of IBRs in distribution networks, modern solutions have to be developed to deal with the protection challenges introduced by their integration.
This dissertation presents a a series of research works aimed at addressing the aforementioned sensitivity and selectivity challenges in detecting faults in modern distribution systems. The works employ various models using symmetrical components. The first work models a superimposed quantity to provide a new fault detection element for unbalanced faults. The element also provides a way to determine the direction of faults detected to improve selectivity. The second work introduces a dynamic phasor model as measured quantity for fault detection. A sub-cycle version of the dynamic phasor is further decomposed into symmetrical quantities to investigate potential improvement in the sensitivity and speed of fault detection. Finally, the final work addresses coordination of protection devices in an inverter-interfaced distribution system. This new model is based on positive sequence voltage to reduce the impact of IBR low fault current in coordinating relays during fault detection. Hadware-in-the-Loop and offline computer simulation results demonstrate the effectiveness of the proposed methods in improving protection systems in inverter-interfaced distribution networks
Benchmarking Robustness of Gait Recognition Models
No full textThis study investigates the robustness of gait recognition systems under realistic perturbations, with a focus on both silhouette parsing and gait recognition components. Experiments are conducted on three diverse datasets—CASIA-B, CCPG, and SUSTech1K—using five state-of-the-art parsing models and six gait recognition architectures. To simulate real-world degradations, we introduce 15 types of noise across five severity levels, resulting in 75 distinct corrupted scenarios. Our findings reveal that no parsing model performs optimally under all conditions, and transformer-based gait models exhibit greater resilience than CNN-based counterparts. However, all models remain highly sensitive to digital noise and occlusions. Interestingly, performance under temporal noise is relatively stable, despite the sequential nature of the task. Additionally, training with noisy data enhances robustness but may reduce peak accuracy on clean inputs. This benchmark provides insights for designing gait recognition systems that are more robust and deployable in unconstrained environments
Mitigation Of Transverse Gusts On Morphing Wings Via Span-Wise Twisting
No full textWind gust encounters create a highly unstable and unpredictable environment for air vehicles. Small aircraft are especially susceptible to gust-induced disturbances due to their limited size and weight, leading to significant fluctuations during flight. This study introduces a novel concept involving a twisting mechanism along the wingspan, allowing for span wise variations in pitch. Using a towing tank and a gust generator apparatus, we demonstrate the effectiveness of the proposed mechanism. Force data and flow field data obtained from Particle Image Velocimetry (PIV) provide insights into the vortex mechanisms at play. A Modified Discrete Vortex Method using the leading-edge separation parameter is developed and used to develop optimized twisting kinematics
Comparative Analysis of Matrix Factorization and Neural Collaborative Filtering for Movie Recommendation Systems
No full textThis paper presents a comparative study of two recommendation system approaches for predicting movie ratings: Matrix Factorization with Stochastic Gradient Descent (SGD) optimization and Neural Collaborative Filtering (NCF) using Tensor Flow. The study aims to evaluate the effectiveness of these methods in recommending movies to users based on the MovieLens 100K dataset. The Matrix Factorization approach utilizes latent features to model user preferences and item characteristics, optimizing parameters through SGD. On the other hand, NCF integrates traditional collaborative filtering with neural networks to capture complex user-item interactions. Experimental results demonstrate the performance of both models in terms of Root Mean Square Error (RMSE) on the test dataset. The findings provide insights into the strengths and limitations of each approach, aiding in the selection of suitable recommendation techniques for movie recommendation systems
