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Articles 1321 - 1350 of 10597
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Computational Imaging And Its Application, Helen Peng
Computational Imaging And Its Application, Helen Peng
Theses
Traditional optical imaging systems have constrained angular and spatial resolution, depth of field, field of view, tolerance to aberrations and environmental conditions, and other image quality limitations. Computational imaging provided an opportunity to create new functionality and improve the performance of imaging systems by encoding the information optically and decoding it computationally. The design of a computational imaging system balances hardware costs and the accuracy and complexity of the algorithms. In this thesis, two computational imaging systems are presented: Randomized Aperture Imaging and Laser Suppression Imaging. The former system increases the angular resolution of telescopes by replacing a continuous primary …
The Earth Disk Model: Analysis And Integration Of Protoplanetary Disk Mineralogy And Structure, William Allen Richard Grimble
The Earth Disk Model: Analysis And Integration Of Protoplanetary Disk Mineralogy And Structure, William Allen Richard Grimble
Theses
Our understanding of how exoplanets form and evolve relies on analyses of both the mineralogy of protoplanetary disks and their detailed structures; however, these key complementary aspects of disks are usually studied separately. We present initial results from a hybrid model that combines the empirical characterization of the mineralogy of a disk, as determined from its mid-infrared spectral features, with the well-tested MCFOST radiative transfer disk model that takes into account realistic disk density and temperature structures, a combination we call the EaRTH Disk Model. With the results of the mineralogy detection serving as input to the radiative transfer model, …
Experimental Designs For Observing The Hong-Ou-Mandel Manifolds Using Silicon Micro-Ring Resonators, Joseph Monteleone Iii
Experimental Designs For Observing The Hong-Ou-Mandel Manifolds Using Silicon Micro-Ring Resonators, Joseph Monteleone Iii
Theses
We propose three experimental designs for observing the Hong-Ou-Mandel Manifolds using silicon micro-ring resonators. These experimental designs tackle the challenges of producing and coupling identical photon pairs to be incident on a silicon micro-ring resonator, and they describe methods of photon observation. We experimentally characterized a silicon micro-ring resonator with Mach-Zehnder Interferometer couplers. We modified the Hong-Ou-Mandel Manifold theory to include these realistic Mach-Zehnder Interferometer couplers, and computationally predict new manifold structures based on experimental power transmission spectrum comparisons. We also characterized a packaged foundry-fabricated silicon spiral photon pair source to be used as a possible identical photon pair source.
Towards Real-Time Classification Of Human Imagined Language, Joseph Zonghi
Towards Real-Time Classification Of Human Imagined Language, Joseph Zonghi
Theses
The primary goal of this research was to develop a system capable of predicting a given user's imagined language in real time using their brainwave data. This research analyzed both FPGA-based and software based approaches to real-time classification of imagined language. The classification was binary between English and Japanese, and a dataset containing imagined speech from both languages was also created. Another goal of this research was to consider the effects of quantization of the network weights in order to examine the resulting utilization of the FPGA to allow for other applications to run in conjunction with our proposed system. …
Learning Representations In The Hyperspectral Domain In Aerial Imagery, Aneesh Rangnekar
Learning Representations In The Hyperspectral Domain In Aerial Imagery, Aneesh Rangnekar
Theses
We establish two new datasets with baselines and network architectures for the task of hyperspectral image analysis. The first dataset, AeroRIT, is a moving camera static scene captured from a flight and contains per pixel labeling across five categories for the task of semantic segmentation. The second dataset, RooftopHSI, helps design and interpret learnt features on hyperspectral object detection on scenes captured from an university rooftop. This dataset accounts for static camera, moving scene hyperspectral imagery. We further broaden the scope of our understanding of neural networks with the development of two novel algorithms - S4AL and S4AL+. We develop …
Design Of An 8-Bit Configurable Cnn Hardware Accelerator For Audio And Image Classification, Christie Agbalessi
Design Of An 8-Bit Configurable Cnn Hardware Accelerator For Audio And Image Classification, Christie Agbalessi
Theses
Picture yourself resting or attending a meeting in the back seat while your car is driving you home with all the privacy a driverless vehicle offers. Designing autonomous systems involves decoding environmental cues and making safe decisions. Convolution Neural Networks (CNNs) are the leading choices for computer vision tasks due to their high performance and scalability to pieces of hardware. They have long been run on Graphical Processing Units (GPUs) and Central Processing Units (CPUs). Yet, today, there is an urgent need to accelerate CNNs in low-power consumption hardware for real-time inference. This research aims to design a configurable hardware …
Light Scattering Studies Of Hyaluronate Solutions, Tim Mcnutt
Light Scattering Studies Of Hyaluronate Solutions, Tim Mcnutt
Theses
The results of light scattering experiments on aqueous solutions of sodium hyaluronate are reported. Hyaluronate is an important component of the eye lens vitreous and many other connective tissues. The dependence of the light scattering on sodium hyaluronate molecular weight is studied and compared with a renormalization group model of polymer solution free energies. The results for the molecular weight and concentration ranges investigated fall on or near a universal scaling relationship provided by the model. This work extends previous comparisons of polyelectrolyte solutions to the same scaling relation.
A Method For Measuring Puffing And Respiratory Parameters Of Tobacco Users Within Their Natural Usage Environment, Shehan Jayasekera
A Method For Measuring Puffing And Respiratory Parameters Of Tobacco Users Within Their Natural Usage Environment, Shehan Jayasekera
Theses
Background: Although researchers have investigated the puffing behavior of tobacco products, no attempt has yet been made to observe both puffing and respiratory behaviors simultaneously in the natural use environment. Observation of puffing behavior alone is insufficient for predicting the health effects of tobacco use, as it can only be used to estimate the amount of emissions generated and transferred to the oral cavity. Respiration behavior must be observed for the estimation of delivery and retention of nicotine and other HPHCs in the lungs. Parameters that quantify respiratory behavior include inhalation and exhalation volumes, flow rates, and durations, as well …
Clean Deconvolution Of Radio Pulsar Pulses, Olivia Young
Clean Deconvolution Of Radio Pulsar Pulses, Olivia Young
Theses
Broadband radio waves emitted from pulsars are distorted as they propagate toward Earth due to interactions with the free electrons that comprise the interstellar medium (ISM). Irregularities in the ISM cause multipath propagation of the wavefronts along the line of sight toward Earth, with lower radio frequencies being more greatly impacted than higher frequencies. These delays result in later times of arrival for the lower frequencies and cause the observed pulse to arrive with a broadened tail, which can be described using a pulse broadening function. CLEAN deconvolution, as outlined in Bhat et al. (2003) for use in pulsar scattering …
An Investigation Of Novel Object Recognition Memory In A North American River Otter (Lontra Canadensis), Jessica J. Wegman
An Investigation Of Novel Object Recognition Memory In A North American River Otter (Lontra Canadensis), Jessica J. Wegman
Theses
Memory is the mental processes of receiving and storing information for later retrieval, with long-term memories being those that are stored longer than 30 seconds. Little research has been done to investigate memory in any of the 13 species of otters. Object recognition memory has the potential to aid otters in identifying conspecifics, prey, and predators, which would contribute to better survival and fitness. Object recognition memory has been investigated in many non-human animals using the novel object recognition (NOR) task. This study was the first to investigate long-term object recognition memory in the North American river otter using the …
Using Gmos Spectroscopy To Study Star Formation And Agn In The Candels Cosmos And Uds Fields, Isabella G. Cox
Using Gmos Spectroscopy To Study Star Formation And Agn In The Candels Cosmos And Uds Fields, Isabella G. Cox
Theses
Spectroscopic measurements of galaxies can help us to better understand their properties. Spectroscopy allows for the measurement of spectroscopic redshifts, which have better precision than redshifts derived from photometry. Precise redshifts are needed to eliminate distance un- certainties when deriving distance-dependent properties of galaxies. Additionally, spectroscopy provides insight into the physical state and processes within a galaxy, such as its rate of on- going star formation, its chemical abundance, and the properties of the interstellar medium within the galaxy. Spectroscopy is particularly powerful when coupled with broad, multiwavelength photometric data. The five extragalactic fields from the Cosmic Assembly Near-infrared Deep …
On Uncertainty Propagation In Image-Guided Renal Navigation: Exploring Uncertainty Reduction Techniques Through Simulation And In Vitro Phantom Evaluation, Peter Jackson
Theses
Image-guided interventions (IGIs) entail the use of imaging to augment or replace direct vision during therapeutic interventions, with the overall goal is to provide effective treatment in a less invasive manner, as an alternative to traditional open surgery, while reducing patient trauma and shortening the recovery time post-procedure. IGIs rely on pre-operative images, surgical tracking and localization systems, and intra-operative images to provide correct views of the surgical scene. Pre-operative images are used to generate patient-specific anatomical models that are then registered to the patient using the surgical tracking system, and often complemented with real-time, intra-operative images. IGI systems are …
Cochlear Compartments Segmentation And Pharmacokinetics Using Micro Computed Tomography Images, Sanketh Satyanarayana Moudgalya
Cochlear Compartments Segmentation And Pharmacokinetics Using Micro Computed Tomography Images, Sanketh Satyanarayana Moudgalya
Theses
Local drug delivery to the inner ear via micropump implants has the potential to be much more effective than oral drug delivery for treating patients with sensorineural hearing loss and to protect hearing from ototoxic insult due to noise exposure. Delivering appropriate concentrations of drugs to the necessary cochlear compartments is of paramount importance; however, directly measuring local drug concentrations over time throughout the cochlea is not possible. Indirect measurement using otoacoustic emissions and auditory brainstem response are ineffective as they only provide an estimate of concentration and are susceptible to non-linear sensitivity effects. Imaging modalities such as MRI with …
Canine Gait Analysis: Interactive Online Tutorials For Veterinary Students, Allison Buck
Canine Gait Analysis: Interactive Online Tutorials For Veterinary Students, Allison Buck
Theses
The purpose of this thesis is to produce interactive tutorials that veterinary students can use to explore concepts that are often difficult to conceptualize, including (a) change in joint function, (b) muscle action and innervation, and (c) recognizing and locating normal vs. abnormal structure and function. Elements of this thesis include a complete 3D skeleton constructed using a series of canine CT (DICOM) files, illustrated overlays on video footage of a dog undergoing examination, and short interactive self-assessment tools. Students will be able to deconstruct and toggle components of the skeleton, as well as view the animated skeleton superimposed over …
The View From 50 Au: Measuring The Cosmic Optical Background With New Horizons, Teresa Symons
The View From 50 Au: Measuring The Cosmic Optical Background With New Horizons, Teresa Symons
Theses
The extragalactic background light (EBL) is the sum of the light emitted by sources beyond the Milky Way throughout the history of the universe. While the EBL is present at all wavelengths, at optical wavelengths it is largely sourced by the light from stars and galaxies and is referred to as the cosmic optical background (COB). Direct photometric measurements of the COB provide an important comparison to population models of galaxy formation and evolution. Such measurements therefore provide a cosmic consistency test with the potential to reveal additional diffuse sources of emission. However, the COB has been difficult to measure …
Selfies And The Self: The Influence Of Instagram Posting On Self And Cognition, Giovanni Castillo
Selfies And The Self: The Influence Of Instagram Posting On Self And Cognition, Giovanni Castillo
Theses
Research on Social Networking Sites (SNS) has shown a variety of both beneficial and detrimental psychological and cognitive outcomes associated with high frequency usage. We conducted an online study consisting of a series of questionnaires and a working memory task to explore the relationship between Instagram use intensity and cognition. The present study first investigated the relationship between Instagram (IG) use intensity, rumination, and cognitive failures. We randomly assigned participants into a selfie-posting, selfie-sending, or likes/comments reporting condition to determine whether selfie-posting behavior affects working memory performance. While we did not find significant associations between IG use intensity, rumination, and …
Manifold Based Deep Learning: Advances And Machine Learning Applications, Navya Nagananda
Manifold Based Deep Learning: Advances And Machine Learning Applications, Navya Nagananda
Theses
Manifolds are topological spaces that are locally Euclidean and find applications in dimensionality reduction, subspace learning, visual domain adaptation, clustering, and more. In this dissertation, we propose a framework for linear dimensionality reduction called the proxy matrix optimization (PMO) that uses the Grassmann manifold for optimizing over orthogonal matrix manifolds. PMO is an iterative and flexible method that finds the lower-dimensional projections for various linear dimensionality reduction methods by changing the objective function. PMO is suitable for Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Canonical Correlation Analysis (CCA), Maximum Autocorrelation Factors (MAF), and Locality Preserving Projections (LPP). We extend …
Towards A Carbon-Neutral City By 2035: Innovative Transformation Of Domestic Solid Waste Collection And Recovery Services In Sharjah, Basem Abu Sneineh
Towards A Carbon-Neutral City By 2035: Innovative Transformation Of Domestic Solid Waste Collection And Recovery Services In Sharjah, Basem Abu Sneineh
Theses
This study quantifies the impact of an identified major step in the process of significant contribution to the transformation of Sharjah into a carbon-neutral city by the year 2035. This identified step applies to the concept of waste segregation at the residential sector source which means that the waste generators, i.e. Sharjah residents, are required to segregate the waste that they generate in their houses while disposing it. The march towards a carbon neutral city means driving the carbon dioxide emissions of the city to reach net-zero. This requires the UAE adopt this concept to ensure that the emitted amount …
Fabrication Of Nonplanar Surfaces Via 5-Axis 3d Printing, Ajinkya S. Patil
Fabrication Of Nonplanar Surfaces Via 5-Axis 3d Printing, Ajinkya S. Patil
Theses
The advancements in manufacturing have always played a vital role in human life. One of the most recent and growing manufacturing methods is additive manufacturing (AM). AM has been in focus for its ability to manufacture intricate parts with internal features which are not possible with traditional manufacturing processes. Making parts lighter and stronger has been the goal for most AM processes. The advancements in AM have made it possible to produce parts with high strength internal structures. The overall strength of the manufactured plastic parts depends on several variables. The part’s strength is determined by the material, the build …
Efficient Photonic Integrated Circuits – Optimizing Fiber-To-Chip Coupling, Modulation, And Detection, Peichuan Yin
Efficient Photonic Integrated Circuits – Optimizing Fiber-To-Chip Coupling, Modulation, And Detection, Peichuan Yin
Theses
Photonic integrated circuits (PICs) are attracting attention in a wide range of applications due to their superior performance over traditional discrete photonic devices. However, the development of PICs is bottlenecked by the integration of different fundamental building blocks. High sensitivity and diverse material properties hinder the realization of a monolithic photonic integrated circuit platform. High-efficiency solutions for photonic device integration are critical for making high-performance and low-cost devices. The objective of this work is to demonstrate high-efficiency optimization methods for a comprehensive photonic integrated chip system. This work analyzes the transition of optical signal waves between each component in a …
The Effects Of Overshadowing In Drosophila Melanogaster With Experimentally Evolved Preference, Jill Lee
The Effects Of Overshadowing In Drosophila Melanogaster With Experimentally Evolved Preference, Jill Lee
Theses
As seen in decades of psychology research, preferences play a major role in driving the decision-making process in both humans and animals. Researchers have advocated for using the technique of experimental evolution as a way to address some of the foundational questions on preferences. These preferences can also affect what is later learned and how well new experiences are learned. Salience is usually mentioned as an important component of what could influence preferences. Animals such as Drosophila melanogaster, that lay eggs without any additional maternal or paternal care, it is important to be selective when deciding where to lay …
A Morality Play Or Just Simply Queer: Lillian Hellman's The Children's Hour, Rebecca Weaver
A Morality Play Or Just Simply Queer: Lillian Hellman's The Children's Hour, Rebecca Weaver
Theses
Queer theatre during the early 1900s in America seems to be almost non-existent when students study literature, history, and even theatre history because the records were suppressed, leaving the teaching of queer history at a disadvantage. One of the most influential queer plays in theatre history was written in 1934 by Lillian Hellman. The Children’s Hour takes place in an all-girls school ran by Karen Wright and Martha Dobie. The two friends encounter a continuous problem by the name of Mary Tilford – one of the girls who attends the school. In an effort to convince her grandmother to withdraw …
Norman Lewis & Philip Guston: From Modernist Margins To Postmodernism, Joette Deanna James
Norman Lewis & Philip Guston: From Modernist Margins To Postmodernism, Joette Deanna James
Theses
This thesis examines the ways in which the African American painter Norman Lewis (1909-1979) and Canadian American Jewish painter Philip Guston (1913-1980) deviated from the dogma of Abstract Expressionism and presaged Postmodernism. The modernist Abstract Expressionist movement placed value on the heroic nature of the painter, the denial of the social and political milieu outside of the work of art, and the formalist quality of the work above all. This paper argues that both Guston and Lewis, in their penchant for experimentation and stylistic fluidity, were prevented from attaining the level of commercial success and popularity of their much better …
Smart And Intelligent Automation For Industry 4.0 Using Millimeter-Wave And Deep Reinforcement Learning, Abhishek Vashist
Smart And Intelligent Automation For Industry 4.0 Using Millimeter-Wave And Deep Reinforcement Learning, Abhishek Vashist
Theses
Innovations in communication systems, compute hardware, and deep learning algorithms have led to the advancement of smart industry automation. Smart automation includes industrial sectors such as intelligent warehouse management, smart infrastructure for first responders, and smart monitoring systems. Automation aims to maximize efficiency, safety, and reliability. Autonomous forklifts can significantly increase productivity, reduce safety-related accidents, and improve operation speed to enhance the efficiency of a warehouse. Forklifts or robotic agents are required to perform different tasks such as position estimation, mapping, and dispatching. Each of the tasks involves different requirements and design constraints. Smart infrastructure for first responder applications requires …
Credit Card Fraud Detection Using Machine Learning, Meera Alemad
Credit Card Fraud Detection Using Machine Learning, Meera Alemad
Theses
The purpose of this project is to detect the fraudulent transactions made by credit cards by the use of machine learning techniques, to stop fraudsters from the unauthorized usage of customers’ accounts. The increase of credit card fraud is growing rapidly worldwide, which is the reason actions should be taken to stop fraudsters. Putting a limit for those actions would have a positive impact on the customers as their money would be recovered and retrieved back into their accounts and they won’t be charged for items or services that were not purchased by them which is the main goal of …
Nlp And Ml Methods For Pre-Processing, Clustering And Classification Of Technical Logbook Datasets, Farhad Akhbardeh
Nlp And Ml Methods For Pre-Processing, Clustering And Classification Of Technical Logbook Datasets, Farhad Akhbardeh
Theses
Technical logbooks are a challenging and under-explored text type in automated event identification. These texts are typically short and written in non-standard yet technical language, posing challenges to off-the-shelf NLP pipelines. These datasets typically represent a domain (a technical field such as automotive) and an application (e.g., maintenance). The granularity of issue types described in these datasets additionally leads to class imbalance, making it challenging for models to accurately predict which issue each logbook entry describes. In this research, we focus on the problem of technical issue pre-processing, clustering, and classification by considering logbook datasets from the automotive, aviation, and …
Leveraging Formulae And Text For Improved Math Retrieval, Behrooz Mansouri
Leveraging Formulae And Text For Improved Math Retrieval, Behrooz Mansouri
Theses
Large collections containing millions of math formulas are available online. Retrieving math expressions from these collections is challenging. Users can use formula, formula+text, or math questions to express their math information needs. The structural complexity of formulas requires specialized processing. Despite the existence of math search systems and online community question-answering websites for math, little is known about mathematical information needs. This research first explores the characteristics of math searches using a general search engine. The findings show how math searches are different from general searches. Then, test collections for math-aware search are introduced. The ARQMath test collections have two …
Active Learning From Knowledge-Rich Data, Weishi Shi
Active Learning From Knowledge-Rich Data, Weishi Shi
Theses
With the ever-increasing demand for the quality and quantity of the training samples, it is difficult to replicate the success of modern machine learning models in knowledge-rich domains, where the labeled data for training is scarce and labeling new data is expensive. While machine learning and AI have achieved significant progress in many common domains, the lack of large-scale labeled data samples poses a grand challenge for the wide application of advanced statistical learning models in key knowledge-rich domains, such as medicine, biology, physical science, and more. Active learning (AL) offers a promising and powerful learning paradigm that can significantly …
Towards Multimodal Open-World Learning In Deep Neural Networks, Manoj Acharya
Towards Multimodal Open-World Learning In Deep Neural Networks, Manoj Acharya
Theses
Over the past decade, deep neural networks have enormously advanced machine perception, especially object classification, object detection, and multimodal scene understanding. But, a major limitation of these systems is that they assume a closed-world setting, i.e., the train and the test distribution match exactly. As a result, any input belonging to a category that the system has never seen during training will not be recognized as unknown. However, many real-world applications often need this capability. For example, self-driving cars operate in a dynamic world where the data can change over time due to changes in season, geographic location, sensor types, …
Technology Use By Registered Dietitians For Patient Care In An Outpatient Setting, Donika Emerllahu
Technology Use By Registered Dietitians For Patient Care In An Outpatient Setting, Donika Emerllahu
Theses
Background Technology use in digital health tools has increased significantly since the COVID-19 pandemic disrupted many in-office patient care services. Although healthcare practices have adopted several technologies, they remain surrounded by a saturated increase in consumer-based wearables and smartphone applications. As a result, attitudes and acceptability toward integrating these technologies for patient care are evolving. Digital health tools is an umbrella term including several technologies utilized among health care providers for the purpose of patient care. The inclusion of digital health tools by Registered Dietitian Nutritionists’ (RDNs) in practice provides a more robust and personalized approach to patients and their …