UARK (University of Arkansas )
Not a member yet
19829 research outputs found
Sort by
Assessing Language Skills of Children Within the Head Start Program Using Language Sampling Analysis
Get PDFFluency disorders, including stuttering and cluttering, disrupt one’s natural rate of speech and can cause implications for one’s emotional well-being. This study explores the relationship between language factors and stuttered events in preschool-age children by analyzing a spontaneous language sample using two transcription software programs, CLAN and SALT. A language sample was collected from a child enrolled in a local Head Start program and was transcribed and analyzed using the software programs. Results from CLAN’s KIDEVAL and FLUCALC features offered analysis of the child’s language profile, as well as SALT’s standards measure report feature. This study highlights the importance of LSA in the assessment process for fluency disorders along with creating intervention plans
Parental Perceptions of Child Life Specialists
Get PDFMost children spend time in the hospital at some point during their childhood whether it is for a short visit or a long-term stay. Hospitalization can be a very stressful experience for children and their families. Child life specialists work in hospitals to help families navigate hospitalizations and cope with stress. This study aimed to investigate parental perceptions of child life specialists, including parents’ familiarity with their role, recognition of its importance, appreciation for help provided, and the formation of meaningful relationships with child life specialists. A survey was conducted among child life specialists who had worked with children and families in hospital settings, and ninety-one responses were collected. The findings indicate that parents were generally unfamiliar with the role of a child life specialist before entering the hospital. However, after interacting with a child life specialist, parents came to recognize the importance and value of the child life specialists’ role and appreciated the help that they provided for their child and family. Child life specialists also feel that they can form meaningful relationships with the parents they work with. Overall, the study emphasizes the crucial role that child life specialists play in supporting children and families throughout hospitalization
Survival Signature Estimation Using Optimization and Monte-Carlo Simulation for \u3ci\u3eK\u3c/i\u3e ≥ 3 Classes of Nodes on Two-Terminal Networks
Get PDFThis research develops an efficient approach to estimating survival signatures for two-terminal networks with more than two classes of components. Recently, the survival signature has gained substantial attention in the literature on network reliability estimation due to its unique separability property, which enables passing the network topology information independent of the failure distribution of the components. Following recent results from the literature, estimating the two-terminal survival signature by Monte Carlo simulation entails solving a multi-objective maximum capacity path problem on a two-terminal network in each replication. We adapt a multi-objective Dijkstra’s algorithm from the literature to construct the set of non-dominated paths solving the multi-objective maximum capacity path problem for each replication of the Monte-Carlo simulation. We have carried out experiments on random two-terminal networks and grid networks with three, four, and five classes of components. In these experiments, our version of the multi-objective Dijkstra’s algorithm was compared against four benchmark algorithms and an improvement technique that prunes some paths to be explored in the multi-objective Dijkstra’s algorithm setting lower bounds on capacities. We compared the run-time of our approach with all these benchmark approaches and found that the multi-objective Dijkstra’s algorithm performs significantly better in most instances
Investigating the Impact of GEAR UP Arkansas on College Readiness and Post-Secondary Enrollment in the Delta
Get PDFThis study evaluates the impact of the Gaining Early Awareness and Readiness for Undergraduate Programs (GEAR UP) Arkansas initiative on improving college readiness and postsecondary enrollment among low-socioeconomic status (SES) students in the Arkansas Delta, a region marked by systemic educational inequities and persistent poverty. Framed by Opportunity Gap Theory, this quantitative, quasi-experimental research addresses two questions: (1) How does GEAR UP participation influence postsecondary enrollment compared to nonparticipants? (2) Do participants achieve higher ACT scores than nonparticipants? Using data from 491 students across high-poverty schools, the study employs logistic regression to assess enrollment rates and multiple regression to analyze ACT performance, accounting for demographic and contextual factors. Key program elements, including tutoring, ACT preparation, and financial aid counseling, are hypothesized to drive improvements. Findings are expected to show positive effects on enrollment and ACT scores, demonstrating GEAR UP’s role in reducing structural barriers to higher education. The research provides actionable insights for policymakers and educators, advocating for sustained investment in equity-driven programs like GEAR UP to close opportunity gaps. By highlighting the program’s effectiveness, the study informs strategies for scaling similar initiatives in underserved, high-poverty regions to promote educational equity and access
Geochemical Analysis for Potential Critical Mineral Resources in Carbon Fly Ash
No full textThe growing demand for critical minerals, coupled with the increasing supply chain vulnerabilities, has intensified the need for alternative domestic resources of critical minerals beyond traditional mining. Many of these critical minerals are essential for advanced technologies, energy storage, and national security, yet the United States remains heavily dependent on foreign imports, particularly from China. This study evaluates the economic potential of critical mineral recovery from Carbon Fly Ash (CFA), a byproduct of coal combustion, to determine its viability as a secondary source of critical minerals. A geochemical and mineralogical assessment was conducted on CFA samples from various storage sites to analyze the concentration of 33 critical minerals. The study identified varying concentrations and economic potential, which are influenced by factors such as the type of coal burned and the scale of the CFA deposits. Results indicate that 24 of these critical minerals exhibit viable economic potential, suggesting that processing CFA for their recovery could offer high financial return while contributing to the strengthening of global infrastructure resilience. Given the growing urgency to reduce reliance on foreign suppliers, especially in light of recent trade restrictions and supply chain disruptions, developing domestic processing infrastructure for critical mineral recovery from CFA could provide a strategic advantage. Additionally, many of these high-value critical minerals co-occur or share similar extraction and processing methods, allowing for cost effective co-recovery. While challenges remain, including CFA heterogeneity and the need for large-scale processing capabilities, the findings of this study underscore the importance of investing in critical mineral recovery from CFA as a means to enhance resource security, strengthen economic resilience, and mitigate risk associated with geopolitical supply constraints
Susceptibility Analysis of Flash Flood in Jeddah City, Saudi Arabia, Using a GIS-Based Analytical Hierarchy Process
No full textFloods rank among the most devastating natural hazards on Earth, posing significant threats to human society across various geographies, including arid regions such as Saudi Arabia. In Saudi Arabia, Jeddah is the second largest city in terms of population with more than 4.5 million residents. The city experiences long and arid summers and short, dry, and windy winters. As the severity and frequency of floods continue to increase, there is a growing demand for improved flood risk assessment to mitigate damage to lives and properties. Given the complex nature of flood evaluation and prediction, a systematic criteria-based methodology, such as the Analytical Hierarchy Process (AHP), offers a robust solution. This study integrates the AHP with a Geographic Information System (GIS) to model flash flood risk hazards in Jeddah, Saudi Arabia. Key parameters for this evaluation included precipitation, elevation, slope, proximity to drainage networks, land cover, and lithology. A pairwise comparison was conducted to rank these criteria by order of magnitude in flood contribution. Four susceptibility grades – ranging from Low to Very High – were identified to represent flood hazard likelihood. The findings show that the eastern and central parts of Jeddah, particularly areas leading to the coast, are identified as the most vulnerable areas to flash flooding due to their proximity to natural water channels and their low-lying, intermittent topography, which creates valleys. Obviously, the rapid urbanization of Jeddah contributes also to flash flooding caused by seasonal downpours. Local authority should develop coping strategies, such as widening drainage systems and reducing paved surface areas in highly susceptible zones, to mitigate future flood risks effectively
Detecting Item Preknowledge in Longitudinally-Collected Assessment Data
No full textEducational assessment policymakers and stakeholders have recently called for assessments that incorporate instruction and learning into the assessment process (e.g., through-course assessment and longitudinal certification assessments). A feature of these assessments is repeated measurements of examinee ability intended to inform learning interventions. Though these longitudinally-administered assessments are often designed to be more flexible for examinees, the increased flexibility presents testing practitioners with unique challenges in maintaining the integrity of exam scores. These assessments, often characterized by on-demand or continuous administration, necessitate repeated use of items over time. Repeating items increases the risk of compromised items that may lead to examinees with item preknowledge, thereby compromising the validity of score interpretations.
Test security, and more specifically, item preknowledge, has received much attention among researchers. Given the recency of longitudinally-administered assessments, however, test security statistics applied to longitudinally-collected assessment data have received little or no attention. Beyond increased security threats, these assessments introduce challenges to item preknowledge detection because of systematic (e.g., change in examinee ability) and unsystematic (e.g., unreliability in proficiency estimation) influences. Nonetheless, longitudinally-collected assessment data may provide additional possibilities for detecting aberrant response behavior not possible in point-in-time assessment contexts.
The purpose of this dissertation was to develop and examine methods for identifying examinees exhibiting item preknowledge in a longitudinal assessment framework. This dissertation comprises three studies that may help testing organizations administering longitudinally-administered assessments develop a suite of test security statistics. By leveraging the information from longitudinal data, the first study extends preexisting test security statistics developed for point-in-time assessments to evaluate for changes in examinee response behavior. The second study extends test security statistics specifically developed to detect sudden changes in examinee response behavior to detect whether and when an examinee begins exhibiting item preknowledge throughout a longitudinal assessment. The third study examines if test security programs should adopt specialized longitudinal statistics, such as those from studies one and two, or if conventional point-in-time methods are sufficient. The three studies comprise simulation studies to assess the test security statistics\u27 performance in realistic testing conditions and applied examples to showcase their practical use and limitations with real data
Fixed-time Artificial Insemination Protocols Using Pre-synchronization in Suckled Beef Cows
Get PDFAdoption of artificial insemination by beef producers has been limited within the United States. Estrous synchronization (ES) for fixed-time artificial insemination (FTAI) has been one of the most effective ways to implement artificial insemination into beef production systems, but its efficiency has primarily been restrained by the dependency on the effectiveness of the initial gonadotropin releasing hormone (GnRH) injection in many FTAI protocols. The hypotheses of these studies were to determine practical methods of pre-synchronization to improve current FTAI protocols, ultimately increasing beef herd reproductive performance. The objective was to evaluate the use of prostaglandin F2α (PGF) and progesterone (P4) to increase the effectiveness of the initial GnRH injection within protocols to increase the synchronization of estrous cycles within a herd, ultimately increasing the number of pregnant animals. Utilizing P4 and PGF as a method of pre-synchronization for a shortened ES protocol induced a greater percentage of animals exhibiting estrus behavior compared to animals that had received only PGF as a method of pre-synchronization or no method of pre-synchronization. Cows subject to methods of pre synchronization also resulted in a greater percentage of animals pregnant to AI than those not receiving a method of pre-synchronization. Furthermore, evaluation of pre-synchronization utilizing P4 and PGF prior to differing FTAI protocols yielded AI pregnancy results that may contrast with the typical relationship of estrus expression and AI pregnancy rates within fixed time artificial insemination protocols. Evidence suggests that the use of P4 and PGF in methods of pre-synchronization within ES protocols provide potential in producing greater reproductive outcomes and provide evidence as a potential method to further improve the efficiency of the beef production industry
Design and Implementation of Asynchronous Communication in Multi-Chiplet Systems: A Comparative Study of Pseudo-Crossbar and Bus Architectures
Get PDFSystem-on-Chip (SoC) complexity continues to present challenges in global clock distribution and power management. The Globally Asynchronous Locally Synchronous (GALS) approach addresses these issues by enabling asynchronous communication between locally synchronous chiplets. This thesis details the design and implementation of two GALS architectures employing asynchronous handshaking protocols through Multi-Threshold CMOS NULL Convention Logic (MTNCL). The first architecture, a pseudo-crossbar, uses arbiters and multiplexers/demultiplexers (MUX/DEMUX) for prioritized and dynamic communication between chiplets. The second, a bus-based approach, employs D-latches to manage communication sequentially with predetermined interrupts. This research explores the detailed implementation, functional distinctions, scalability, and integration trade-offs inherent to each design. The insights gained provide practical guidance for future advancements in embedded asynchronous communication system
A Robust RF Fingerprinting Approach Using Physics-Informed Neural Networks
Get PDFRadio frequency (RF) fingerprints, caused by unique imperfections in communication hardware, offer a promising solution for zero-trust security. However, existing RF fingerprinting techniques, which aim to extract these signatures from transmitters to uniquely identify devices, often struggle with robustness in the face of temporal and spatial variations in real-world, time-varying wireless environments. For example, a neural network trained on RF signals collected on Day 1 can experience a significant performance drop when tested with data from Day 2.
To address this challenge, we propose a novel, robust RF fingerprinting method based on Physics-Informed Neural Networks (PINNs). Rather than training the model solely on the received signal, a complex mixture of RF fingerprints, time-varying channel conditions, and random channel noise, we incorporate invariant radio physics, specifically the estimated Carrier Frequency Offset (CFO), to guide the model’s learning. In addition, we input a distilled, frequency-domain equalized signal to mitigate the effects of dynamic wireless propagation conditions. Extensive experiments using USRPs were conducted to collect real-world RF data, and the proposed PINN model was benchmarked against state-of-the-art approaches. While all three methods achieved high classification accuracy (\u3e98%) when training and testing on the same day, the cross-day performance of baseline models dropped to approximately 35%. In contrast, the proposed PINN model maintained an accuracy of 97.54% across days. These results demonstrate that embedding radio physics into the learning process significantly enhances model robustness, offering a more resilient and practical path for deploying RF fingerprinting in real-world security systems