Please read the abstract in the front section of this document / Dissertation (MChD (Periodontics and Oral Medicine))--University of Pretoria, 2007. / Oral Pathology and Oral Biology / unrestricted

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A ramjet inlet duct structure has been designed using nonlinear structural analysis to allow local plastic deformations which result in structural weight reduction. To establish the feasibility of reduced shell thickness, the Lower-Bound Theorem of limit analysis has been applied using an existing finite element analysis computer code intended for elastic analysis. The results of the analysis were verified by structural testing. Predicted stresses and deflections showed good correlation with measured values up to the point of failure. This work was supported by the U.S. Air Force Aero Propulsion Laboratory, Wright-Patterson Air Force Base, Ohio, under Contract No. F33615-72-C-1366.

Exploratory data analysis aims to study datasets through the use of iterative, investigative, and visual analytic algorithms. Due to the difficulty in managing and accessing the growing volume of unstructured data, exploratory analysis of datasets has become harder than ever and an interest to data mining researchers. In this dissertation, we study new algorithms for exploratory analysis of data collections using clusters and stories. Clustering brings together similar entities whereas stories connect dissimilar objects. The former helps organize datasets into regions of interest, and the latter explores latent information by connecting the dots between disjoint instances. This dissertation specifically focuses on five different research aspects to demonstrate the applicability and usefulness of clusters and stories as exploratory data analysis tools. In the area of clustering, we investigate whether clustering algorithms can be automatically "alternatized" and how they can be guided to obtain alternative results using flexible constraints as "scatter-gather" operations. We demonstrate the application of these ideas in many application domains, including studying the bat biosonar system and designing sustainable products. In the area of storytelling, we develop algorithms that can generate stories using distance, clique, and syntactic constraints. We explore the use of storytelling for studying document collections in the biomedical literature and intelligence analysis domain. / Ph. D.

This study introduces a method to optimize charging strategies for Automated Guided Vehicles in warehouses and logistics centers, aiming to enhance efficiency and reduce downtime. Using Tecnomatix Plant Simulation, a model with two vehicles and two charging stations was created to simulate realistic delivery scenarios, generating data on order duration, energy consumption, and vehicle charging times. This data was optimized with CPLEX to determine the best order sequences and loading schedules. The key challenge addressed is optimizing Automated Guided Vehicle charging strategies to maximize operational readiness and energy efficiency. A supervised learning approach was used, where a neural network predicts if an Automated Guided Vehicle should charge based on its State of Charge and current order backlog. The model was developed in Python, using an 80-20 split for training and testing. The study demonstrates the effectiveness of machine learning in improving Automated Guided Vehicle fleet management, providing a data-driven solution for real-time decision-making.

Dental implant guidance systems promise precise placement, but postoperative assessment with CBCT scans poses radiation risks. This study utilizes an optical scanning method to evaluate implant placement position and assess the accuracy of robotic assistance using the Neocis Yomi system. METHODS: In a longitudinal study at Boston University, Robotic-assisted dental implant Placement was evaluated. The test population excluded fully edentulous patients. The current cohort focused on eight patients: four were fully guided, and four were partially guided. Optical impressions were obtained with a CEREC Omnicam scanner and indexed using ELOS-accurate Scan Bodies. The preop virtual placement plan was merged with the actual post-op implant placement and then analyzed with Geomagic Control X software to measure deviations between planned and executed positions. RESULTS: In the four Fully guided patients, the deviation of the Implant at the platform level, midpoint, and apex was 1.3133mm, 1.4425mm, and 1.4355mm, respectively. In the four partially guided patients, the implant deviation at the platform, midpoint, and apex was 1.691mm, 1.0291mm, and 2.2226mm. CONCLUSION: Despite the study limitations, robotically assisted implant surgery demonstrates accuracy comparable to traditional guidance systems. The use of Intraoral optical scan bodies provides a radiation-free evaluation of the as planned vs. executed dental implant placement. This method should be adopted for future research.

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