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Articles 1 - 10 of 10
Full-Text Articles in Computational Engineering
Improving Semantic Precision In Text-To-Image Diffusion Models Via Latent-Space Optimization And Semantically-Parsed Evaluation, Mohammad Rouie Miab
Improving Semantic Precision In Text-To-Image Diffusion Models Via Latent-Space Optimization And Semantically-Parsed Evaluation, Mohammad Rouie Miab
McKelvey School of Engineering Graduate Student Theses & Dissertations
Text-to-image diffusion models can produce visually impressive images from natural-language prompts, but they often fail to satisfy the detailed semantic constraints expressed in compositional prompts. Typical failure modes include omitted objects, merged entities, incorrect quantities, incorrect attribute binding, and leakage of one entity's attributes onto another. This thesis studies the problem of semantic precision in text-to-image generation: how faithfully a generated image satisfies the structured meaning of its prompt. The thesis makes two linked contributions. First, it presents a training-free inference-time refinement method for diffusion-based image generation. The method operates directly in latent space during denoising and uses noun-phrase-aware cross-attention …
A Computational And Mathematical Approach To The Preclinical Development Of Alpha Emitting Radiopharmaceutical Therapies, Abdulaziz Said
A Computational And Mathematical Approach To The Preclinical Development Of Alpha Emitting Radiopharmaceutical Therapies, Abdulaziz Said
McKelvey School of Engineering Graduate Student Theses & Dissertations
Numerous candidate nuclides have been undergoing rigorous preclinical development in the pursuit of novel targeted therapies. Successful development of these drugs relies on the understanding of physiological impacts at the macro and micro scales, in addition to a scalable process for their production. Here, mathematical and computerized approaches have been developed to guide this preclinical development. In this report, two alpha emitting nuclides Pb-212 and Ra-223 are modeled. Radium-223 dichloride citrate a newly approved ion indicated for treatment of bone metastatic castrate resistant prostate cancer, irradiates lesions through targeted uptake in bone at sites of disease. We have undertaken the …
An Attention Lstm U-Net Model For Drosophila Melanogaster Heart Tube Segmentation, Xiangping Ouyang
An Attention Lstm U-Net Model For Drosophila Melanogaster Heart Tube Segmentation, Xiangping Ouyang
McKelvey School of Engineering Graduate Student Theses & Dissertations
Machine learning is commonly used in biomedical image analysis, as it allows automated image segmentation and identification that minimizes the need for tedious human involvement. Drosophila melanogaster is often used as a cardiac disease model, where optical coherence microscopy (OCM) is used to image and analyze its beating dynamics. As OCM often generates a large volume of images, automated image segmentation is necessary to quantify the heart beating efficiently. Our most recent heart segmentation model, FlyNet 2.0+, is a fully convolutional LSTM U-Net model. However, the performance of the model diminishes in the presence of artifacts, such as image reflection …
Automatic Cardiac Mri Image Segmentation And Mesh Generation, Ziyuan Li
Automatic Cardiac Mri Image Segmentation And Mesh Generation, Ziyuan Li
McKelvey School of Engineering Graduate Student Theses & Dissertations
Segmenting and reconstructing cardiac anatomical structures from magnetic resonance (MR) images is essential for the quantitative measurement and automatic diagnosis of cardiovascular diseases [1]. However, manual evaluation of the time-series cardiac MRI (CMRI) obtained during routine clinical care are laborious, inefficient, and tends to produce biased and non-reproducible results [2]. This thesis proposes an end-to-end pipeline for automatically segmenting short-axis (SAX) CMRI images and generating high-quality 2D and 3D meshes suitable for finite element analysis. The main advantage of our approach is that it can not only work as a stand-alone pipeline for the automatic CMR image segmentation and mesh …
Tell It Slant: Investigating The Engagement, Discourse, And Popularity Of Data Visualization In Online Communities, Emma Baker
McKelvey School of Engineering Graduate Student Theses & Dissertations
Data visualizations are increasingly accessible to people online, often to non-specialized audiences. However, what we know about how people make sense of data and engage with the visualized content is typically limited to observations from controlled user studies, sometimes with highly-specialized participants. As a result, there is a limited vocabulary to describe how visualizations as a technique of information sharing permeate organic communities. This thesis investigates how data visualization systems infiltrate online social settings and characterizes the conditions under which users engage or do not engage with them. We captured conversations on Reddit from March 2, 2021 to December 31, …
Modeling Of Swimming Cells From Nano-Scale To Micro-Scale, Yicheng Zhao
Modeling Of Swimming Cells From Nano-Scale To Micro-Scale, Yicheng Zhao
McKelvey School of Engineering Graduate Student Theses & Dissertations
Certain human genetic diseases -- primary ciliary dyskinesia, infertility, and hydrocephalus -- are characterized by changes in beat frequency and waveform of cilia and flagella. Chlamydomonas reinhardtii, which is a single-cell green alga about ten micrometers in diameter that swims with two flagella, serves as an excellent biological model because its flagella share the same structure and genetic background as mammalian cilia and flagella. This study uses the finite element method to investigate the behavior of C. reinhardtii swimming from nano-scale to micro-scale. At the device-level, micro-scale modeling indicates that well-designed acoustic microfluidic devices can be used to trap groups …
Uncertainty Quantification Of Turbulence Model Closure Coefficients On Openfoam And Fluent For Mildly Separated Flows, Ike Witte
McKelvey School of Engineering Graduate Student Theses & Dissertations
In this thesis, detailed uncertainty quantification studies focusing on the closure coefficients of eddy-viscosity turbulence models for several flows using two CFD solvers have been performed. Three eddy viscosity turbulence models considered are: the one-equation Spalart-Allmaras (SA) model, the two-equation Shear Stress Transport (SST) k-ω model, and the one-equation Wray-Agarwal (WA) model. OpenFOAM and ANSYS Fluent are used as flow solvers. Uncertainty quantification analyses are performed for subsonic flow over a flat plate, subsonic flow over a backward-facing step, and transonic flow past an axisymmetric bump. In the case of flat plate, coefficients of pressure, lift, drag, and skin friction …
The Next Generation Of Wireless Cyber-Physical Simulator, Xinghan Wang, Kevin Xu
The Next Generation Of Wireless Cyber-Physical Simulator, Xinghan Wang, Kevin Xu
Undergraduate Research Symposium Posters
In order to make Wireless Cyber-Physical Simulator(WCPS) more accessible to people in the research community, and also to improve its accuracy of representing real industrial models, we worked on the dockerization of WCPS, and implemented the multi-rate feature for WCPS, enabling the simulator to have different network rate and plant rate when running a simulation. We created a new version of WCPS by dockerizing run-time libraries and the TOSSIM server and also embedding the multi-rate feature in the old version. This report includes the introduction and dockerization of WCPS, and shows the results of using the new generation of WCPS …
Applying Bayesian Machine Learning Methods To Theoretical Surface Science, Shane Carr
Applying Bayesian Machine Learning Methods To Theoretical Surface Science, Shane Carr
McKelvey School of Engineering Graduate Student Theses & Dissertations
Machine learning is a rapidly evolving field in computer science with increasingly many applications to other domains. In this thesis, I present a Bayesian machine learning approach to solving a problem in theoretical surface science: calculating the preferred active site on a catalyst surface for a given adsorbate molecule. I formulate the problem as a low-dimensional objective function. I show how the objective function can be approximated into a certain confidence interval using just one iteration of the self-consistent field (SCF) loop in density functional theory (DFT). I then use Bayesian optimization to perform a global search for the solution. …
Optimization Of Blalock-Taussig Shunt And Anastomotic Geometry For Vascular Access Fistula Using A Genetic Algorithm, Guangyu Bao
Optimization Of Blalock-Taussig Shunt And Anastomotic Geometry For Vascular Access Fistula Using A Genetic Algorithm, Guangyu Bao
McKelvey School of Engineering Graduate Student Theses & Dissertations
Blalock-Taussig (BT) shunts are used for defects that affect the flow of blood from the right ventricle, through the pulmonary artery, and to the lungs. Arteriovenous (AV) fistula is one type of vascular access which is a surgically created vein used to remove and return blood during hemodialysis. Plastic grafts used in the above two reconstructions may result in areas of non-physiologic flow in the grafts leading to risk of stenosis (blocked area) and thrombosis, which is the single major cause for access morbidity. The focus of this thesis is to study BT shunts and anastomoses models using Computational Fluid …