Modular construction is increasingly seen as an efficient construction method in terms of time, cost, and energy. The full realization of these advantages partly relies on the efficiency of the production process inside the modular factories, which currently rely on tedious manual monitoring methods or expensive automated techniques. As a...
The utility of high-throughput, computational screening has become an invaluable asset to the field of materials science. In the hierarchy of computational methods, the most accurate methods are often the most computationally expensive. However, as both the efficiency and fidelity of numerical techniques advance, high-quality screening of large materials datasets...
Rhizopus microsporus is a globally ubiquitous opportunistic human and plant pathogen that is known to harbor endosymbiotic bacteria. Differences between populations of clinical and environmental R. microsporus isolates have yet to be assessed on a global scale. Whole-genome sequence data were used to explore fungal biology and to assess potential...
The continued long-term use of fossil fuels as a primary energy source has resulted in dramatic increases in greenhouse gas emissions and the associated concerns of climate change and environmental pollution. A key strategy to circumvent these issues is a global shift away from fossil fuels toward renewable energy sources....
In this dissertation, the primary objective is to discover more sustainable electrode materials and study new reaction mechanisms using aqueous electrolytes. The first study conducted reveals a reversible conversion reaction from copper to Cu2CO3(OH)2. The reaction mechanism uses OH- and CO32- as charge carriers at the cathode. The results open...
Secure Computation is a powerful tool that enables a set of parties to jointly compute any function over their private inputs, without a trusted third party. Private Set Intersection is a specific case of two-party Secure Computation, where Alice (with private set X) and Bob (with private set Y) specifically...
Fusarium proliferatum is a fungus found in soils which produces the mycotoxin group known as fumonisins. Of human concern due to hepato-, nephro- and neurotoxicity, the threat of fumonisins lies within several food items, including corn, wheat sorghum, asparagus and, more recently, garlic. Manifesting as ““garlic rot”,” F. proliferatum infection...
Bibliographia Bopyridarum is prepared and maintained by John Markham, Arch Cape, Oregon, USA. Any reports of errors or omissions are greatly appreciated. Please contact Dr. Markham with suggestions: jmarkham@seasurf.net This file is updated annually.
The European hazelnut (Corylus avellana L.) is a tree nut crop that is important in Oregon, which produces 99% of the United States’ hazelnuts but only 5% of the world’s supply. In order to maintain this market share, farmers in Oregon need cultivars that produce high quality nuts, mature early,...
Hop (Humulus lupulus L. var. lupulus) is a diploid, dioecious plant with an extensive history of cultivation and use in brewing, as a textile, and for its therapeutic properties. Hop is prized for its ability to produce a variety of aromatic and flavor compounds, as well as compounds with anti-microbial...
Back pain is the leading cause of disability worldwide, entailing a significant socioeconomic impact. A primary source of back pain can be attributed to intervertebral disc (IVD) degeneration allowing nerve ingrowth, facet joint arthritis, disc bulging, and osteophyte formations that press on nearby nerve roots or the spinal cord. While...
We explore the application of deep learning to the disparate fields of natural language processing and computational biology. Both the sentences uttered by humans as well as the RNA and protein sequences found within the cells of their bodies can be considered formal languages in computer science, as sets of...
Paper-based microfluidic assays, like the common pregnancy test, allow for rapid screening at the point- of-care at low cost and with no instrumentation. Fabric has many similar properties to paper, but is more flexible and durable, making it a promising option for use in a variety of diagnostic and screening...
With growing interest in mass timber, especially mass timber panels (MTP), there has been a need to better understand their structural properties. One of the most versatile uses for MTP are as floor systems. Under new code provisions, these floors can be utilized in new and taller building types, but...
There has been tremendous growth in using data analytic and machine learning algorithms to make critical decisions, such as in the national power grid, healthcare operations, and autonomous vehicles. Employing data analytic for decision-making allows cyber attackers to manipulate the decisions of these algorithms through data falsification. Hence, the trustworthiness...
Labeling videos is costly, time-consuming and tedious. These costs can escalate in applications such as medical diagnosis or autonomous driving where we need domain expertise for annotation. Few-shot action recognition aims to solve this problem by annotation-efficient learning mechanisms.
This thesis presents MetaUVFS as the first Unsupervised Meta-learning algorithm for...
The demand for the development of sustainable energy is an all time high as we burn through limited fossil fuel reserves and as environmental concerns rise every year. Renewable energy sources such as wind and solar power have limitations due to inconsistent power supply that cannot meet the regular needs...
The climate of the Pacific Northwest is in flux, and existing forest ecosystems are stressed and poised to shift in fundamental ways, with or without human intervention. This dissertation probes the nature of forest responses to environmental change through investigations of morphology and genetics of three species of alder co-occurring...
Dense electrical recording of biosignals has been developed to provide spatial resolution and precise temporal information for health monitoring, diagnostics, and clinical research. However, more electrodes require more wires, and wiring density quickly becomes a limiting factor. To break this bottleneck, we proposed a frequency-division multiplexing (FDM) based architecture for...
Unlike other biosensing, electrochemical biosensor has the advantages of robustness, easy miniaturization, excellent detection limits, and capability in handling small analyte volumes. The detection selectivity of the electrochemical biosensors is mainly supported by bioreceptors. However, these receptors always suffer from the performance variation caused by the environment and the thermal-...
Traditional localization techniques rely on triangulation or trilateration, where in a set of three or more stationary known locations is used to estimate a “client” position. For inertial navigation, these techniques can estimate client positions merely using the measured data from tri-axial accelerometers and gyroscopes. However, the use of double...
Gamma Ray Bursts (GRBs) are the most energetic explosions in the Universe, producing up to $\sim10^{53}$ ergs of energy in the first few seconds of their emission -- the so-called prompt phase that is dominated by high energy X-ray and $\gamma$-ray photons. The very large luminosities released in these events...
This dissertation addresses few-shot object segmentation in images. The goal of segmentation is to label every image pixel with a class of the object occupying that pixel, where the class may represent a semantic object category or instance. In few-shot segmentation, training and test datasets have different classes. Every new...
The abilities of plant biologists to characterize the genetic basis of physiological traits are limited by their abilities to obtain quantitative data representing precise details of trait variation and mainly to collect this data on a high-throughput scale at low cost. Deep learning-based methods have demonstrated unprecedented potential to automate...
Information about named entities (real-world objects) is usually harvested from different sources and organized as a multiple relational directed graph in Knowledge Bases (KBs). KBs play essential roles in many NLP modules including question answering, fact-checking, search engines, etc. KBs are big but still incomplete: relational information among entities is...
Transport phenomena specially the ones that occur in the various engineering disciplines such as tissue engineering and natural environment are often complex to analyze mostly due to the dynamic and geometric complexities; as such, they have been the subject of an active and intense area of research in past decades....
Humanities have been craving more freedom and conveniences in whatever form. Carriages evolved to cars and ultimately to aircraft so that one can reach any place in the globe within a day. The mobile phone has enabled people to make a phone call without a need to find a phone...
In this dissertation, we address action segmentation in videos under limited supervision. The goal of action segmentation is to predict an action class for each frame of a video. The limited supervision means ground truth labels of video frames are not available in training. We focus on three types of...
This dissertation explores mathematical theory of the 3 dimensional incompressible Navier-Stokes equations that consists a set of partial differential equations which govern the motion of Newtonian fluids and can be seen as Newton's second law of motion for fluids. The main interest of this work focuses on how local perturbation...
In the 21st century, environmental deterioration is now an indisputable fact. Reliable and economically viable electricity systems based on renewable sources are urgently needed to replace the environmentally detrimental fossil fuels. The feasibility of incorporating renewable-but-intermittent solar and wind energy heavily depends on the development of cost-effective and safe technologies,...
Diverse scientific fields collect multiple time series data to investigate the dynamical behavior of complex systems: atmospheric and climate science, geophysics, neuroscience, epidemiology, ecology, and environmental science. Identifying patterns of mutual dependence among such data generates valuable knowledge that can be applied either for inferential or forecasting purposes. Vector autoregressive...
Enabled by a rich ecosystem of Machine Learning (ML) libraries, programming using learned models, i.e., Software-2.0, has gained substantial adoption. However, we do not know what challenges developers encounter when they use ML libraries. With this knowledge gap, researchers miss opportunities to contribute to new research directions, tool builders do...
The environmental health science community recognizes polycyclic aromatic hydrocarbons (PAHs) as a re-emerging class of environmental pollutants due to their persistence and prominence in mixtures of concern. Due to their widespread distribution in the environment, exposure to PAHs often occur as complex chemical mixtures. Exposures are linked to numerous adverse...
Over the decades, worker performance on construction projects has been a significant source of concern to be evaluated. Comprehensive studies have developed models for evaluating worker performance outside of the construction industry; however, minimal research has been conducted to evaluate worker performance in the construction industry. One of the reasons...
While safety improvements have been made in the construction industry, construction still experiences one of the highest numbers of fatalities annually compared to other industries in the United States with over 970 fatalities in 2016 alone. This number of fatalities drives researchers and safety managers to improve safety measures and...
Natural Language Comprehension is a challenging domain of Natural Language Processing. To improve a model’s language comprehension/understanding, one approach would be to enrich the structure of the model to enhance its capability in learning the latent rules of the language.
In this dissertation, we will first introduce several deep models...
Bimetallic catalysis is a promising way to tune the catalytic properties of heterogeneous catalysts. In particular, bimetallic catalysts are extensively used to enhance the selectivity of monometallic catalysts in a variety of contexts, from oxidation catalysis to oxygenate coupling. In this work, we investigate PdxCuy/SiO2 and PdxAgy/SiO2 catalysts in the...
Over the last decades, CMOS-integrated sensors have made impressive progress in performance, form-factor, and energy-efficiency for various applications such as imaging, physical/chemical sensing, bio/health monitoring. In the era of the artificial intelligence (AI) and the internet-of-things (IoT), such CMOS-integrated sensors are essential for massive and comprehensive data acquisition, where sensing...
Harvesting energy from ambient sources can provide power autonomy to energy efficient electronics and sensors. The last decade has seen a multitude of ways to scavenge energy from various sources like solar, thermal, electromagnetic, electrostatic, piezo-electric and many more. Thermal energy from human body heat is ubiquitous and can be...
The shallow aquifer in Southern Willamette Valley (SWV) has high levels of nitrate, and we are exploring the time trends in nitrate, and the hydrologic and land management factors that contribute to this problem. Nitrogen (N) inputs to farmland from fertilizer is thought to be the primary source of nitrogen...
Cervical cancer is the fourth most common cancer in women worldwide with human papillomavirus (HPV) being the main cause of the disease. Currently available treatment methods are limited and emphasize the need for discovery of new therapies that improve patient outcome. Chromosomal amplifications have been identified as a source of...
This thesis studies the problem of structured prediction (SP), where the agent needs to predict a structured output for a given structured input (e.g., Part-of-Speech tagging sequence for an input sentence). Many important applications including machine translation in natural language processing (NLP) and image interpretation in computer vision can be...
Narratives are central to communication and the human experience. For a computer system to understand a narrative, it must be able to identify the key facts or plot elements that describe what happened or how the world has changed. These element are called events;establishing a document’s events and the relationships...
The advent of deep learning models leads to a substantial improvement in a wide range of NLP tasks, achieving state-of-art performances without any hand-crafted features. However, training deep models requires a massive amount of labeled data. Labeling new data as a new task or domain emerges consumes time and efforts...
This thesis presents accurate and time-optimal smooth reference trajectory generation techniques for manufacturing equipment such as high-speed machine tools (MT) and industrial robots (IR). Typical machining tool-paths for MTs and IRs are defined as a series of discrete linear moves. Although Point-to-Point (P2P) feed motion can be generated by interpolating...
We consider the problem of computing the cannonical polyadic decomposition (CPD) for large-scale dense tensors. This work is a combination of alternating least squares and fiber sampling. Data sparsity can be leveraged to handle large tensor CPD, but this route is not feasible for dense data. Inspired by stochastic optimization's...
The concept of construction industrialization, first raised in the 1960s, refers to the transfer of on-site construction work to an off-site factory to improve quality and reduce cost, time, and safety issues. In some countries, industrialization of construction projects is highly recommended and promoted by governments and local construction institutions...
Artificial Intelligence has gained resurgence in popularity through machine learning methods. This thesis investigates the current use of AI, the impact it will have on the economy and the ethical considerations for developing this technology. In the coming decade AI could increase global economic output over $10 Trillion. AI will...
This dissertation is separated into two parts according to the two major distinct research projects. In Part I, the full account of synthetic studies toward C10-functionalized lycopodium alkaloids is described. In Part II, the detailed discussion on the exploration of the Pummerer cyclization methodology and its application to the total...
Movement pattern detection can be applied in a variety of applications such as assisting independent living of seniors at home, behaviour understanding in surveillance systems, sports analytics, and robotics. This project develops a scheme that fuses information from different sensors to detect movement patterns. This report contains three main parts:...