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Investigating Health Events in Dairy Cattle
No full textThis research focuses on identifying the key predictors of mastitis and ketosis in dairy cattle, two common and costly diseases affecting milk production and animal health. The primary objective was to identify significant risk factors and evaluate the predictive performance of modeling approaches.
To analyze these complex relationships, a longitudinal dataset following a large sample of dairy cattle is studying using several advanced methods. Survival analysis techniques, like Kaplan-Meier estimations, help measure how long cows remain free from health issues. The Cox Proportional Hazards (CPH) model complements this approach by identifying risk factors associated with health-related events over time. These statistical tools reveal patterns and differences in health outcomes based on various predictors. Additionally, machine learning techniques like gradient boosting are used to improve prediction accuracy and uncover subtle interactions among variables. The results from the CPH model are then validated using k-fold cross-validation and evaluated with the concordance index (C-index).
The findings from this research show influential variables associated with mastitis and ketosis risk. While all approaches performed with solid predictive ability, the gradient boosting models performed with marginal improvements in predicting time-to-occurrence in health events.
Overall, this research pinpoints critical risk factors that affect mastitis and ketosis. The goal is to help farmers improve prediction for early intervention. The approach combines statistical rigor with advanced technology, providing a comprehensive understanding of mastitis and ketosis risk factors
More Than Words: How Communication Shapes Maternal Healthcare Experiences in Mississippi
No full textEffective communication between healthcare providers and pregnant individuals is a critical factor in shaping maternal healthcare experiences. This study explores the role of provider-patient communication in prenatal and postnatal care among a group of Mississippi mothers, highlighting how communication influences trust, decision-making, and overall satisfaction with care. Using qualitative data collected through in-depth interviews, this case study examines both positive and negative communication experiences, identifying key barriers such as dismissiveness, lack of transparency, and rushed interactions. Findings suggest that when providers engage in clear, compassionate, and culturally competent communication, patients feel more empowered and supported in their care. Conversely, poor communication can lead to uncertainty, stress, and dissatisfaction. This study underscores the need for improved communication training for providers, structured patient engagement strategies, and policy interventions to enhance maternal healthcare outcomes in Mississippi
Optimizing Mars terrain segmentation with weakly supervised learning: A focus on weighted loss from annotation metadata
No full textThe study of planetary surfaces heavily depends upon space rovers that gather detailed images of terrain needed for analysis and navigation. Deep neural networks and other sophisticated machine learning techniques are necessary for autonomous navigation in challenging terrain. However, the inconsistent annotations by citizen scientists frequently hinder the performance of these models. This study seeks to optimize terrain segmentation to improve the autonomous capabilities of future Mars rovers by presenting a novel weakly supervised learning framework to handle noise and unreliability in datasets. Using factors like number of clicks, pixel accuracy, and annotator dependability, the method utilizes annotation metadata in the training process through a custom weighted cross-entropy loss function. Through extensive data analysis, outliers are excluded and key features are extracted to improve the dataset’s reliability and effectiveness, which lead to more precise training. Thus the segmentation model significantly improves rovers’ autonomous navigation capabilities and advances planetary exploration
An insight into graph-based optimization approach to robot navigation and mapping with Human Autonomy Teaming-based strategy
No full textThe field of autonomous robotics has witnessed significant advancements, with robots increasingly deployed in critical applications such as search and rescue, environmental monitoring, precision agriculture, and defense operations. These systems must navigate highly dynamic and obstacle-dense environments, demanding enhanced adaptability, efficiency, and decision-making capabilities. This research presents a comprehensive integration of graph-based techniques, nature inspired optimization algorithms, and deep learning to address these challenges. By combining methodologies such as adaptive graph traversal, spatial decomposition, and task coordination, the study aims to advance navigation, mapping, and control mechanisms while ensuring safety and reliability in diverse operational scenarios. A Dynamically Constrained Delaunay Triangulation (D2T) algorithm is developed to enable adaptive real-time navigation in changing environments. The Improved Node Selection Algorithm (iNSA) enhances graph traversal by optimizing path selection in dense obstacle regions. A Human Autonomy Teaming (HAT) framework combines the Node Optimization Protocol (NOP) and a bio-inspired neural network with an Adaptive Window Strategy (BNN-AWS) to facilitate responsive adjustments based on human input, environmental changes, and critical waypoints for robust navigation in search and rescue scenarios. A middle point cell decomposition model is presented, utilizing vertical cell decomposition and dynamically regulated middle points with an enhanced optimization algorithm to achieve smoother paths and increased computational efficiency. Deep learning augments precision agriculture and multi-robot collaboration, enabling seamless data collection and navigation between aerial and ground vehicles. A Self-Organizing Map (SOM) neural network, combined with advanced formation control strategies, enhances task allocation and coordination in multi-robot systems. This integration ensures efficient spatial organization and reliable performance, particularly in large-scale environmental assessments and remote sensing tasks. Simulation and comparison studies validate the effectiveness and robustness of these methodologies, establishing new benchmarks for autonomous robotic systems in complex, real-world applications. Simulation, comparison studies and on-going experimental results of optimization algorithms applied for autonomous robot systems demonstrate their effectiveness, efficiency and robustness of the proposed methodologies
Asymmetric Effects of the Ebbinghaus Illusion on Relative Depth Judgments in a Perceptual Matching Task
Get PDFThe Ebbinghaus illusion, also know as Titchner Circles, is a perceptual illusion that is typically presented as a two-dimensional set of disks. These disks are configured as a central disk surrounded by an annulus of smaller or larger disks. Numerous studies have found the illusion to have an effect on size perception, but fewer studies have analyzed its effects on depth judgments. This study utilized a head-worn virtual reality environment as well as a three-dimensional display to examine the effects of the Ebbinghaus illusion on relative depth judgments in a perceptual matching task. Findings indicated that Ebbinghaus configurations featuring an annulus composed of small disks elicited a greater misjudgment of depth than configurations featuring an annulus composed of larger disks in both the head-worn virtual reality environment and the three-dimensional display
A Statistical Analysis of Southern Land Grants in Addressing Declining College Enrollment
Get PDFWith declining enrollment of higher education, it is crucial to analyze current mechanics in order to maintain higher education’s benefits to society. Currently, research is aware that land grants serve an important historical role in promoting enrollment, yet additional research is required on their contemporary impact on enrollment and institutional aid. Specifically, this study evaluates land grants universities - institutions established under the Morrill Act of 1862 - and data collected from their respective Common Data Sets on historical enrollment and institutional aid from 2013 to 2023. A point-biserial correlation analysis and two sample t-test are used to understand the statistical significance of land grant status. This study concludes that land grants status is not statistically significant in percent change for enrollment and institutional aid. However, the land grants studied exhibit significance in the proportion of students applying for aid and students who received it. The findings of this study highlights the need for further analysis of the contemporary role of land grants in addressing higher education enrollment trends
Letter, James Franklin Buchanan to Anna Buchanan, July 1968
Get PDFIn this letter, dated July 1968, James Franklin Buchanan writes to his sister, Anna Buchanan concerning the death of their older brother, Webster. He informs her of all the cards and memorials he\u27s received and shares a portion of a letter he received from Senator John C. Stennis about their brother\u27s death.https://scholarsjunction.msstate.edu/mss-james-franklin-buchanan/1019/thumbnail.jp
Letter, Marion E. Buchanan to Mr. M. A. Smith, November 28, 1938
Get PDFIn this letter, dated November 28, 1938, Marion E. Buchanan writes to Mr. M. A. Smith to offer him her terms in meeting with him and his relatives in order to view the papers she allegedly has concerning some Buchanan family lore of a large trust fund due them from an alleged ancestor in 1850\u27s Scottland. Her terms specify that he and his group pay all of her travel expenses to bring the papers to them to view as she will not let them leave her hands.https://scholarsjunction.msstate.edu/mss-james-franklin-buchanan/1035/thumbnail.jp
Army Discharge Papers for James Franklin Buchanan, February 20, 1946
Get PDFThis set of Army paperwork documents the honorable discharge and separation of James Franklin Buchanan from the United States Army in February of 1946. The paper work includes a final payment worksheet, general instructions, detailed instructions, Army of the United States Separation Qualification Record, Honorable Discharge certificate, enlisted record and report of separation, and an identification discharge certificate. A federal Security Agency envelope is also included.https://scholarsjunction.msstate.edu/mss-james-franklin-buchanan/1059/thumbnail.jp
Note on an envelope, James Franklin Buchanan, 1946
Get PDFA note on this unused Robert B. Ray, M. D. envelope states what a dog tag is and what it is used for and declares the tags within belonged to Frank Buchanan in his tour in France during World War II and declares that they go to his daughter, Harriet Ann Buchanan. The dog tags are not longer inside the envelope.https://scholarsjunction.msstate.edu/mss-james-franklin-buchanan/1061/thumbnail.jp