LOUIS University of Alabama in Huntsville
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An Analysis of Process Optimization and Labor Reallocation with its Effects on Efficiency in the Automotive Industry
Full text linkhttps://louis.uah.edu/research-horizons/1384/thumbnail.jp
Synthetic Ferality: An Interactive Exploration with AI and Digital Idolatry
Full text linkhttps://louis.uah.edu/research-horizons/1387/thumbnail.jp
Implementation of a protocol for use during Medicare annual wellness visits to increase lung cancer screening utilization
No full textIn the United States (U.S.), lung cancer is the foremost contributor to cancer-related deaths. Tobacco use is associated with more than 80% of lung cancer diagnoses and the likelihood of developing lung cancer among long-term cigarette smokers increases as individuals age, placing many Medicare beneficiaries at heightened risk. Early detection of lung cancer dramatically improves outcomes for patients, but most cases are found at advanced stages when survival rates are worse. Many expert panels recommend annual low-dose chest computed tomography (LDCT) scans to screen high-risk individuals, yet LDCT remains underutilized in the Medicare population. Medicare beneficiaries who participate in annual wellness visits (AWVs) are more likely to receive recommended preventive services. This clinical practice change project was conducted at a medical center in the Southeastern U.S. and established a lung cancer screening protocol for primary care clinicians to use during Medicare AWVs to increase screening LDCT scans among eligible patients. The protocol was implemented after clinicians received targeted education regarding lung cancer screening guidelines and referral processes. The protocol was designed to aid clinicians in identifying at-risk Medicare beneficiaries for lung cancer. Clinicians used discrete data fields to document patient tobacco use history. A standardized note template was incorporated into AWVs to address lung cancer screening eligibility. Data were analyzed for three months before and after implementation. The analysis included a total of 861 AWVs. Following the educational session, survey data showed a significant improvement in clinicians’ knowledge and perspectives regarding lung cancer screening (Wilcoxon signed-rank test: Z = 2.032, p \u3c 0.05). The quality of tobacco use documentation, referrals, and uptake of screening LDCT scans improved after the initiation of the protocol. These findings demonstrate the benefit of using a comprehensive lung cancer screening protocol during Medicare AWVs to identify at-risk patients and improve lung cancer screening utilization
Experimental evaluation of recent theoretical real-time signal higher-order sliding mode differentiators on noisy sensors
No full textThis thesis explores the performance of higher-order sliding mode differentiators applied to sensor signals under varying sampling rates and switching functions. Two differentiator designs are evaluated: a hybrid algorithm that combines a super-twisting algorithm with a linear observer, and a fixed-time higher-order sliding mode differentiator. Each was tested on a physical sensor testbed using position data from a servomotor and electronic compass. The differentiators were implemented in a ROS2 environment, and their estimates were evaluated by obtaining the minimum and maximum position and velocity values, as well as analyzing graphs to capture the nature of the algorithms\u27 noise reduction. The results indicate that the sampling rate and switching functions have a significant impact on performance. These findings provide insight into the robustness of higher-order differentiators for real-time signal processing
Deep learning time series prediction strategies for efficiently emulating Noah Land Surface Model soil moisture dynamics
No full textThis work examines the ability of deep learning time series generative models to accurately and efficiently emulate the hourly temporal dynamics of the Noah Land Surface Model (Noah-LSM) out to a 2 week forecast horizon, given atmospheric forcings and static parameterization provided by the second phase North American Land Data Assimilation System (NLDAS-2) framework. Results from multiple neural network architectures are compared alongside variations in prediction target, loss function characteristics, and model properties. The most performant model types are subsequently evaluated with respect to forecast distance, annual seasonality, and against a variety of regional scenarios, including several event case studies. Ultimately, we present a software system and suite of evaluation techniques for developing and testing neural networks that use time-varying and static data to estimate temporal dynamics, with the goal of providing a foundation for similar data-driven modeling techniques to be implemented within the upcoming third phase of the NLDAS data record
AI enabled scrabble scoring system : design and implementation
No full textThe scope of this thesis is to present an AI-powered system for automati- cally scoring real-world Scrabble games using computer vision and deep learning. To achieve this purpose a DeepLabv3 model is trained to segment the board from top- down images, while an EfficientNet-B0 classifier identifies individual tile characters, including blank and empty tiles. The system continuously tracks the gameplay by detecting newly placed tiles and applies official Scrabble rules to compute scores, in- cluding crosswords, bonus tiles, and bingo logic simultaneously. The scoring engine supports multi-move gameplay, player turns, and endgame handling. All moves are visualized with a color-coded board and logged for transparency. The system was tested on over 25 real moves and consistently matched the expected scores. Unlike traditional OCR methods, this approach works efficiently in a wide array of lighting, angle, and tile variations. Additionally, the system offers a hands-free alternative for educational and recreational Scrabble settings
Differing Views on the East India Company
No full textThere are two sides to every story, and the rise of the East India Company offers a clear example of how global commodities like tea can both enrich a culture and hide exploitation. Tea’s global importance—especially in relation to British imperial power—reveals both the celebrated and troubling aspects of the 18th and 19th centuries. While tea became a symbol of British refinement, its path from plantation to teacup was steeped in colonialism, coerced labor, and conflict. This project uses visual and historical sources to explore tea’s dual legacy within the context of British imperialism.https://louis.uah.edu/honors-399/1025/thumbnail.jp
The Apollo Soyuz Test Project 50th Anniversary
No full texthttps://louis.uah.edu/rceu-hcr/1509/thumbnail.jp
Can We Use Dispersion Distances to Rapidly Measure Pulsar Accelerations?
No full texthttps://louis.uah.edu/rceu-hcr/1523/thumbnail.jp