Engineering Commons^™

Applying Hls To Fpga Data Preprocessing In The Advanced Particle-Astrophysics Telescope, Meagan Konst

McKelvey School of Engineering Theses & Dissertations

The Advanced Particle-astrophysics Telescope (APT) and its preliminary iteration the Antarctic Demonstrator for APT (ADAPT) are highly collaborative projects that seek to capture gamma-ray emissions. Along with dark matter and ultra-heavy cosmic ray nuclei measurements, APT will provide sub-degree localization and polarization measurements for gamma-ray transients. This will allow for devices on Earth to point to the direction from which the gamma-ray transients originated in order to collect additional data. The data collection process is as follows. A scintillation occurs and is detected by the wavelength-shifting fibers. This signal is then read by an ASIC and stored in an ADC …

Model-Based Deep Learning For Computational Imaging, Xiaojian Xu

McKelvey School of Engineering Theses & Dissertations

This dissertation addresses model-based deep learning for computational imaging. The motivation of our work is driven by the increasing interests in the combination of imaging model, which provides data-consistency guarantees to the observed measurements, and deep learning, which provides advanced prior modeling driven by data. Following this idea, we develop multiple algorithms by integrating the classical model-based optimization and modern deep learning to enable efficient and reliable imaging. We demonstrate the performance of our algorithms by validating their performance on various imaging applications and providing rigorous theoretical analysis.

The dissertation evaluates and extends three general frameworks, plug-and-play priors (PnP), regularized …

Regularized Coordinate-Based Neural Representation Learning For Optical Tomography, Renhao Liu

McKelvey School of Engineering Theses & Dissertations

Neural representation learning recently shows outstanding performance in several computer vision tasks. In this thesis, we propose a novel self-supervised neural represented reconstruction method for optical tomography. Our method uses a Multi-Layer Perceptron (MLP) network to represent the target sample without the need for any ground truth or training data. The MLP weights serve as a latent representation of the target object. Any desired permittivity information can be inferred by querying the neural network within the sample domain. We also investigate applying regularization to implicitly restrict the manifold of MLP for better performance. Our experiments produce low artifacts results with …

Continuous-Time And Complex Growth Transforms For Analog Computing And Optimization, Oindrila Chatterjee

McKelvey School of Engineering Theses & Dissertations

Analog computing is a promising and practical candidate for solving complex computational problems involving algebraic and differential equations. At the fundamental level, an analog computing framework can be viewed as a dynamical system that evolves following fundamental physical principles, like energy minimization, to solve a computing task. Additionally, conservation laws, such as conservation of charge, energy, or mass, provide a natural way to couple and constrain spatially separated variables. Taking a cue from these observations, in this dissertation, I have explored a novel dynamical system-based computing framework that exploits naturally occurring analog conservation constraints to solve a variety of optimization …

Machine Learning Morphisms: A Framework For Designing And Analyzing Machine Learning Work Ows, Applied To Separability, Error Bounds, And 30-Day Hospital Readmissions, Eric Zenon Cawi

McKelvey School of Engineering Theses & Dissertations

A machine learning workflow is the sequence of tasks necessary to implement a machine learning application, including data collection, preprocessing, feature engineering, exploratory analysis, and model training/selection. In this dissertation we propose the Machine Learning Morphism (MLM) as a mathematical framework to describe the tasks in a workflow. The MLM is a tuple consisting of: Input Space, Output Space, Learning Morphism, Parameter Prior, Empirical Risk Function. This contains the information necessary to learn the parameters of the learning morphism, which represents a workflow task. In chapter 1, we give a short review of typical tasks present in a workflow, as …

Numerical Simulation And Optimization Of Blalock-Taussig Shunt, Thomas Hess, Ramesh K. Agarwal

McKelvey School of Engineering Theses & Dissertations

The goal of this study is to create an optimized Blalock-Taussig shunt used to temporarily repair pulmonary vascular blockages allowing a child time to grow so a more permanent surgical repair of the heart and vasculature can be performed. Blalock-Taussig or BT shunts are a surgical procedure performed on infants suffering from cyanosis or “Blue Baby Syndrome.” A BT shunt is an artificial vessel placed between the right ventricle and the pulmonary artery to increase blood flow in the lung and blood oxygen saturation levels. In a study of 96 patients with currently in use modified BT shunts, 32 patients …

Cache Power Optimization Using Multiple Voltage Supplies To Exploit Read/Write Asymmetry, Dengxue Yan

McKelvey School of Engineering Theses & Dissertations

Power consumption becomes more and more critical in computer systems nowadays. Most of the previous work has been focusing on general-purpose computational core, but optimization techniques for conventional CPU core has reached a limit. Our experimental results show that read operations in SRAM can be performed at a lower supply with much reduced power consumption compared to write operations. Based on this observation and the fact that cache, consisting mostly of SRAM, often occupies significant on-chip area of the CPU and consumes a huge portion of the CPU power, we propose a new method to reduce the power consumption of …

A General Framework Of Large-Scale Convex Optimization Using Jensen Surrogates And Acceleration Techniques, Soysal Degirmenci

McKelvey School of Engineering Theses & Dissertations

In a world where data rates are growing faster than computing power, algorithmic acceleration based on developments in mathematical optimization plays a crucial role in narrowing the gap between the two. As the scale of optimization problems in many fields is getting larger, we need faster optimization methods that not only work well in theory, but also work well in practice by exploiting underlying state-of-the-art computing technology.

In this document, we introduce a unified framework of large-scale convex optimization using Jensen surrogates, an iterative optimization method that has been used in different fields since the 1970s. After this general treatment, …

Automating Intensity Modulated Radiation Therapy Treatment Planning By Using Hierarchical Optimization, Paras Babu Tiwari

McKelvey School of Engineering Theses & Dissertations

The intensity modulated radiation therapy (IMRT) optimizes the beam’s intensity to deliver the prescribed dose to the target while minimizing the radiation exposure to normal structures. The IMRT optimization is a complex optimization problem because of the multiple conflicting objectives in it. Due to the complexity of the optimization, the IMRT treatment planning is still a trial and error process. Hierarchical optimization was proposed to automate the treatment planning process, but its potential has not been demonstrated in a clinical setting. Moreover, hierarchical optimization is slower than the traditional optimization. The dissertation studied a sampling algorithm to reduce the hierarchical …

Cfd Simulation And Shape Optimization Of Supersonic Ejectors For Refrigeration And Desalination Applications, Liju Su

McKelvey School of Engineering Theses & Dissertations

The aim of this thesis is to investigate the detailed flow field inside the supersonic ejector using numerical methods and to optimize the ejector’s mixing chamber wall shape to obtain a maximum entrainment ratio (ER) in order to obtain the highest possible efficiency that can be attained by the ejector. A steam ejector applied in the cooling industry is first studied to determine the most accurate turbulence model for its supersonic jet flow field simulation with mixing with the entrained steam in the mixing chamber. A commercial Computational Fluid Dynamics (CFD) package FLUENT 14.5 along with the meshing tool ICEM …

Optimization Of Blalock-Taussig Shunt And Anastomotic Geometry For Vascular Access Fistula Using A Genetic Algorithm, Guangyu Bao

McKelvey School of Engineering 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 …

Integration Of Alignment And Phylogeny In The Whole-Genome Era, Hongtao Sun

McKelvey School of Engineering Theses & Dissertations

With the development of new sequencing techniques, whole genomes of many species have become available. This huge amount of data gives rise to new opportunities and challenges. These new sequences provide valuable information on relationships among species, e.g. genome recombination and conservation. One of the principal ways to investigate such information is multiple sequence alignment (MSA). Currently, there is large amount of MSA data on the internet, such as the UCSC genome database, but how to effectively use this information to solve classical and new problems is still an area lacking of exploration. In this thesis, we explored how to …

Application-Specific Memory Subsystems, Joseph George Wingbermuehle

McKelvey School of Engineering Theses & Dissertations

The disparity in performance between processors and main memories has

led computer architects to incorporate large cache hierarchies in

modern computers. These cache hierarchies are designed to be

general-purpose in that they strive to provide the best possible

performance across a wide range of applications. However, such a memory

subsystem does not necessarily provide the best possible performance for

a particular application.

Although general-purpose memory subsystems are desirable when the

work-load is unknown and the memory subsystem must remain fixed,

when this is not the case a custom memory subsystem may be beneficial.

For example, in an application-specific integrated circuit …

Modeling And Development Of Iterative Reconstruction Algorithms In Emerging X-Ray Imaging Technologies, Jiaofeng Xu

All Theses and Dissertations (ETDs)

Many new promising X-ray-based biomedical imaging technologies have emerged over the last two decades. Five different novel X-ray based imaging technologies are discussed in this dissertation: differential phase-contrast tomography (DPCT), grating-based phase-contrast tomography (GB-PCT), spectral-CT (K-edge imaging), cone-beam computed tomography (CBCT), and in-line X-ray phase contrast (XPC) tomosynthesis. For each imaging modality, one or more specific problems prevent them being effectively or efficiently employed in clinical applications have been discussed. Firstly, to mitigate the long data-acquisition times and large radiation doses associated with use of analytic reconstruction methods in DPCT, we analyze the numerical and statistical properties of two classes …

Design And Implementation Of Position-Encoded Microfluidic Microsphere-Trap Arrays, Xiaoxiao Xu

All Theses and Dissertations (ETDs)

Microarray devices are useful for detecting and analyzing biological targets, such as DNAs, mRNAs, proteins, etc. Applications of microarrays range from fundamental research to clinical diagnostics and drug discovery. In this dissertation, we consider a microsphere array device with predetermined positions of the microspheres. The microspheres are conjugate on their surfaces with molecular probes to capture the targets, and the targets are identified by the microspheres' positions. We implement the microsphere arrays by employing microfluidic technology and a hydrodynamic trapping mechanism. We call our device microfluidic microsphere-trap arrays. To fully realize the potential of the device in biomedical applications, we …

Numerical Simulation And Optimization Of Co2 Sequestration In Saline Aquifers, Zheming Zhang

All Theses and Dissertations (ETDs)

With heightened concerns on CO2 emissions from pulverized-coal power plants, there has been major emphasis in recent years on the development of safe and economical Geological Carbon Sequestration: GCS) technology. Although among one of the most promising technologies to address the problem of anthropogenic global-warming due to CO2 emissions, the detailed mechanisms of GCS are not well-understood. As a result, there remain many uncertainties in determining the sequestration capacity of the formation/reservoir and the safety of sequestered CO2 due to leakage. These uncertainties arise due to lack of information about the detailed interior geometry of the formation and the heterogeneity …