This paper addresses the high model complexity and overconfident frame labeling of state-of-the-art (SOTA) action segmenters. Their complexity is typically justified by the need to sequentially refine action segmentation through multiple stages of a deep architecture. However, this multistage refinement does not take into account uncertainty of frame labeling predicted...
Distributed version control allows developers to manage software evolution among distributed development teams. But it does not eliminate all consistency and concurrency issues, and instead introduces additional complexity when merging code. And resolving merge conflicts is nontrivial when automated merging fails. In such cases, developers are forced to inspect the...
Autonomous robotic agents are on their way to becoming in-home personal assistants, construction assistants, and warehouse workers. The degree of autonomy of such systems is reflected by the manner in which we specify goals to them; the abstraction of low-level commands to high-level goals goes hand-in-hand with increased autonomy. In...
Over time, Open Source Software (OSS) has become indispensable in the creation and upkeep of software products, serving as the fundamental building block for widely used solutions in our daily lives, including applications that enable communication, entertainment, and productivity. A sustainable OSS ecosystem is one that attracts and retains a...
The objective of this dissertation is to enhance the monitoring of forest ecosystems through the utilization of remotely sensed data to address the exigencies posed by the Anthropocene. On a global scale, rising temperatures and fluctuating precipitation patterns have strained forests and produced shifts in natural disturbance regimes. Additionally, the...
This dissertation delves into understanding, characterizing, and addressing dataset shift in deep learning, a pervasive issue for deployed machine learning systems. Integral aspects of the problem are examined: We start with the use of counterfactual explanations in order to characterize the behavior of deep reinforcement learning agents in visual input...
Various natural language processing (NLP) tasks necessitate deep models that are fast, efficient, and small based on their ultimate application at the edge or elsewhere. While significant investigation has furthered the efficiency and reduced the size of these models, reducing their downstream latency without significant trade-offs remains a difficult task....
In recent years, model-free Deep Reinforcement Learning (RL) has become an increasingly popular alternative to more traditional model-based or optimization-based control methods in solving robotic legged locomotion. However, deploying RL in the real world can be a significant undertaking. Constructing reward functions which compel controllers to learn the desired behavior...
Nuclear fuel management is an optimization problem on many levels. Finding “viable” solutions for the core reload design problem is difficult without expert knowledge and software automation. Small modular reactors with a shared used fuel pool demonstrate a novel opportunity for fuel cycle optimization.
A Python package was developed and...
Robotic Bipedal locomotion holds the potential for efficient, robust traversal of difficult terrain. The difficulty lies in the dynamics of locomotion which complicate control and motion planning. Bipedal locomotion dynamics are dimensionally large problems, extremely nonlinear, and operate on the limits of actuator capabilities, which limit the performance of generic...
Currently, a popular approach to image classification uses the deep Transformer architecture. In a Transformer, the attention mechanism enables the model to learn efficiently with fewer computational resources than the convolutional neural networks (CNNs). In this thesis, we study the sparse attention mechanism widely used in the Transformers developed specifically...
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...
The use of board games for teaching introductory computer science is a promising recent avenue of research. The goal is to introduce computing concepts through their use in the implementations of simple games, thereby keeping students engaged through their learning process. However, there is a gap between students' algorithmic descriptions...
This thesis describes an automated method to estimate tree trunk width in a commer-cial apple orchard. Trunk cross sectional area, which is an important consideration with regards to nutrient uptake, is a feature being integrated in a decision support system for precision Nitrogen management. The data used to generate the...
As one of the most popular data types, the point cloud is widely used in various appli- cations, including computer vision, computer graphics and robotics. The capability to directly measure 3D point clouds is invaluable in those applications as depth information could remove a lot of the segmentation ambiguities in...
Dysferlin is a ∼230 kDa terminally anchored membrane protein that is ubiquitously expressed, but is particularly enriched in skeletal and cardiac muscle tissue. Mutations covering the length of the protein have been linked to muscle wasting diseases including limb-girdle muscular dystrophy and Myoshi myopathy. Dysferlin has been shown to play...
This thesis seeks to determine whether a self-driving car's behavior should depend on the hearing status of its passengers: namely, hard-of-hearing (including deaf) or hearing. It is believed that auditory deprivation provokes adaptations in visual attention. These adaptations may lead to atypical movement patterns that can translate to different driving...
Top-performing approaches to embodied AI tasks like point-goal navigation often rely on training agents via reinforcement learning over tens of millions (or even billions) of experiential steps – learning neural agents that map directly from visual observations to actions. In this work, we question whether these extreme training durations are...
Animals aggregate and interact in nonuniform and nonrandom patterns, which lead to group level characteristics that have important evolutionary and ecological consequences. Network analysis provides a useful conceptual framework for linking animal interactions at all scales from dyads to communities, to populations and ecosystems. Despite exciting theoretical and applied advances...
Reinforcement learning has emerged as a popular tool for solving control tasks, with multiple works focusing on the complex and dynamic task of locomotion. However, the naive application of reinforcement learning to this problem often produces maladaptive policies that exploit the model or reward function. This results in behavior that...
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...
In this dissertation, we propose Ideal Thumbnail-Preserving Encryption (Ideal TPE), as a special case of format-preserving encryption, to balance image privacy and usability concerns in a cloud environment. We first introduce a concrete construction for Ideal TPE, that provably leaks nothing about the plaintext (unencrypted) image beyond its thumbnail. We...
Emergence of highly accurate Convolutional Neural Networks (CNNs) with the capability to process large datasets, has led to their popularity in many applications, including safety/security-sensitive (e.g. disease recognition, self-driving cars). Despite the high accuracy of convolutional neural networks, they have been found to be susceptible to adversarial noise added to...
This thesis uses a hedonic price model to estimate the value of water for irrigation in Deschutes County, Oregon. The analysis uses a dataset comprising information on 2,274 agricultural parcels across the County. Uniquely, the analysis successfully utilizes assessor-determined real market values in the place of actual land sales. A...
In this thesis, we introduce a novel Explanation Neural Network (XNN) to explain the predictions made by a deep network. The XNN works by embedding a high-dimensional activation vector of a deep network layer non-linearly into a low-dimensional explanation space while retaining faithfulness i.e., the original deep learning predictions can...
Marine sediments are vast sources and reservoirs of methane, a potent greenhouse gas. Most of this methane is anaerobically oxidized by archaea before it can reach the overlying ocean, though the efficiency of this process often depends on methane fluxes and mechanisms of fluid transport. Anaerobic methanotrophic archaea, or ANME,...
How should reinforcement learning (RL) agents explain themselves to humans not trained in AI? To gain insights into this question, we conducted a 124 participant, four-treatment experiment to compare participants’ mental models of an RL agent in the context of a simple Real-Time Strategy (RTS) game. The four treatments isolated...
This dissertation addresses the problem of video labeling at both the frame and pixel levels using deep learning. For pixel-level video labeling, we have studied two problems: i) Spatiotemporal video segmentation and ii) Boundary detection and boundary flow estimation. For the problem of spatiotemporal video segmentation, we have developed recurrent...
In open set recognition, a classifier must label instances of known classes while detecting instances of unknown classes not encountered during training. To detect unknown classes while still generalizing to new instances of existing classes, this thesis introduces a dataset augmentation technique called counterfactual image generation. This approach, based on...
Deep neural networks currently comprise the backbone of many applications where safety is a critical concern, for example: autonomous driving and medical diagnostics. Unfortunately these systems currently fail to detect out-of-distribution (OOD) inputs and can be prone to making dangerous errors when exposed to them. In addition, these same systems...
Microbial ecology has been transformed by metagenomics, the study of the genetic in-formation in entire communities of organisms. In the following we develop metagenomic tools arising from the classic Wasserstein metric as applied to questions regarding the diversity between microbial communities. We provide a novel proof of the characteriza-tion of...
The dissertation focuses on the engineering of light-matter interaction using plasmonic nanoparticles and metamaterials to achieve enhanced luminescence and based on which to improve the performance of biosensing and light-emitting technologies. We designed and fabricated a spectrum of nanostructures to exhibit particular dispersion relations capable of controlling the spontaneous emission...
During the eighteenth century, diagrams increasingly became an important aspect of scientific inquiry. Diagrams employed simplification as a strategy for representing complex information, played a role in standardizing scientific language, and served as instruments of reason to think through and communicate problems and findings in mathematics, physics, chemistry, astronomy, natural...
Geographical datasets are large, complex, and can be difficult for users to navigate and derive meaning from. These datasets, as well as the unique insights derived from them, provide tremendous opportunity for social change -- many of the global challenges humankind is currently facing can benefit from analytics or visualization...
This thesis addresses the problem of temporal action segmentation in videos, where the goal is to label every video frame with the appropriate action class present. We focus on the domain of NFL football videos, where action classes represent common football play types. For action segmentation, we use a temporal...
This work is a culmination of a series of published works related to the use of the Material Point Method (MPM) in modeling wood adhesive bonds. The use of wood as construction material has the potential to play a small role in the solution to the current CO2 and climate...
State-of-the-art personal robots need to perform complex manipulation tasks to be viable in complex scenarios. However, many of these robots, like the PR2, use manipulators with high degrees of freedom. High degrees of freedom are desirable from a functionality standpoint, but make the learning task more difficult by adding a...
Miniaturized and portable microfluidic analytical platforms have been widely explored in the broad field of chemical analysis. The concept of microfluidics offer a number of important advantages, including low reagent consumption, low-cost detection, high sample throughput, and shorter analysis time. Semiconductor nanocrystals or quantum dots have been extensively utilized in...
Recognizing human actions in videos is a long-standing problem in computer vision with a wide range of applications including video surveillance, content retrieval, and sports analysis. This thesis focuses on addressing efficiency and robustness of video classification in unconstrained real-world settings. The thesis work can be broadly divided into four...
At a time when the biodiversity on Earth is being rapidly lost, new technologies and methods in genomic analysis are fortunately allowing scientists to catalog and explore the diversity that remains more efficiently and precisely. The studies in this dissertation investigate genomic diversity within the milkweed genus, Asclepias, at multiple...
Modeling tire-snow interaction is important in designing effective snow tires, which directly affects road safety during wintry weather. Unfortunately, tires have complex tread designs and the physical properties of snow have not been characterized. We employ the Material Point Method (MPM) for simulating a material that mimics the fracturing and...
Time-dependent electronic transport is increasingly important to the state-of-the-art device design and fabrication. The development of nanoscale sensing, the harnessing and control of structural fluctuations, and the advancement of next-generation materials all require a treatment of quantum dynamics beyond the level of traditional methods and a more nuanced approach to...
European hazelnut (Corylus avellana L.) is an important crop Oregon's Willamette Valley, producing 99% of the hazelnuts grown in North America and brings over US $60 million dollars to the region annually. Hazelnuts are rich in fiber and vitamins, as well in demand by consumers due to their popularity as...
This honors undergraduate thesis examines the process of simulating power system state estimation, the use of the alternating direction method of multipliers in the problem of distributed power system state estimation, and provides a rudimentary asynchronous implementation of the above for a linearized DC power system. The asynchronous implementation is...
Here we present a phylogeny of beetles (Insecta: Coleoptera) based on DNA sequence data from eight nuclear genes, including six single-copy nuclear protein-coding genes, for 367 species representing 172 of 183 extant families. Our results refine existing knowledge of relationships among major groups of beetles. Strepsiptera was confirmed as sister...
The Open Modeling Environment (OME) is a tool developed to address some known shortcomings in ecological System Dynamics (SD) modeling research. OME provides a common set of methods for interacting directly with spatial information, reducing the need for modelers to create their own methods for doing so. The environment is...
The development and some applications of holographic optical tweezers (HOT) are presented. Our HOT system uses a spatial light modulator (SLM) to control the location and properties of the optical trap. We have developed a method for optimizing the diffraction efficiency of a SLM that can be applied in situ...
Pseudoperonospora cubensis is an obligate pathogen and
causative agent of cucurbit downy mildew. To help advance
our understanding of the pathogenicity of P. cubensis, we
used RNA-Seq to improve the quality of its reference
genome sequence. We also characterized the RNA-Seq
dataset to inventory transcript isoforms and infer alternative
splicing...
This project was a proof of concept of the use of the RAVEN software, a tool developed for the Risk Informed Safety Margin Characterization (RISMC) approach, with RELAP5-3D. This novel approach combines older probabilistic and mechanistic approaches to look at how and why the complex systems of a nuclear power...
Pathogen invasions pose a growing threat to ecosystem stability and public health. Guidelines for the timing and spatial extent of control measures for pathogen invasions are currently limited, however. We conducted a field experiment using wheat (Triticum aestivum) stripe rust, caused by the wind-dispersed fungus Puccinia striiformis, to study the...
Small modular reactors (SMRs) are a recent advancement in commercial nuclear reactor design with growing interest worldwide. New SMR concepts, such as the Multi-Application Small Light Water Reactor (MASLWR), must undergo a licensing processes established by the U.S. Nuclear Regulatory Commission (NRC) prior to commercial operation. Given the lack of...
Global electromagnetic (EM) induction studies have been the focus of increasing attention during the past few years. A primary stimulus for this interest has been increased quality, coverage and variety of the newly available data sets especially from recent low-Earth-orbiting satellite missions. The combination of traditional ground-based data with satellite-borne...
This study focuses on iodine-131 detected in milk samples from the Dairy Science Unit at Cal Poly, San Luis Obispo, California following events at the Fukushima Dai-ichi Nuclear Power Plant in March of 2011. The samples were collected as part of the Diablo Canyon Nuclear Power Plant (DCPP) Radiological Environmental...
The recent 2013 Oregon State Board of Agriculture report identified several ways to improve agricultural income in Oregon. Recommendations to improve water development are at the top of the report's list of objectives. In this study, I analyze the relationship between net cash farm income (NCFI) and a cross-sectional set...
Signs of climate change across the Pacific Northwest indicate changing patterns of timing and availability of stream flow. Declining summer low flows, decreasing snow pack, higher temperatures and an increasing fraction of mountain precipitation falling as rain, raise concerns about future reliability of stream flows. These changes will likely affect...
The elimination of soluble boron creates several advantages for Small Modular Reactor (SMR) operation. Most of these advantages are realized through significant core simplification (removal of pipes, pumping, and purification systems), the removal of the corrosive effects of soluble boron, and from improved safety effects. However, removing soluble boron creates...
The purpose of this thesis is to design a robust test facility for a small space nuclear power system and model its physical behavior under different scenarios. The test facility will be used to simulate a 1-10kWe nuclear reactor, its electrical generation, and heat removal capabilities. This simulator will be...
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A SNP resource for Douglas-fir: de novo transcriptome assembly and SNP detection and validation
Author(s): Howe, GT (Howe, Glenn T.)[ 1 ] ; Yu, JB (Yu, Jianbin)[ 1 ] ; Knaus, B (Knaus, Brian)[ 2 ] ; Cronn, R (Cronn, Richard)[ 2 ] ; Kolpak,...
DNA has a well-defined structural transition-the denaturation of its double-stranded form into two single strands-that strongly affects its thermal transport properties. We show that, according to a widely implemented model for DNA denaturation, one can engineer DNA 'heattronic' devices that have a rapidly increasing thermal conductance over a narrow temperature...
In the 1970s and 1980s, there was considerable interest in near-equatorial variability at periods of days to weeks associated with oceanic equatorial inertia–gravity waves and mixed Rossby–gravity waves. At that time, the measurements available for studying these waves were much more limited than today: most of the available observations were...
Understanding and modeling microbial responses and feedbacks to climate change is hampered by a lack of a framework in the pelagic environment by which to link local mechanism to large scale patterns. Where terrestrial ecology draws from landscape theory and practice to address issues of scale, the pelagic seascape concept...
The improvement of the agricultural and wine-making qualities of the grapevine (Vitis vinifera) is hampered by adherence to traditional varieties, the recalcitrance of this plant to genetic modifications, and public resistance to genetically modified organism (GMO) technologies. To address these challenges, we developed an RNA virus-based vector for the introduction...
Studies of light-matter interactions in organic semiconductors and in optical tweezer trapping of nanoparticles are presented. In the research related to organic semiconductor materials, a variety of novel materials and their composites have been characterized, and physical mechanisms behind their optoelectronic properties have been established. Three novel functionalized hexacene derivatives...
NCRP report No.160 states that medical exposure increased to nearly half of the total radiation exposure of the U.S. population from all sources in 2006 (NCRP 2009). Part of this increase in exposure is due to the rise in nuclear medicine procedures. With this observed growth in medical radionuclide usage,...
Climate changes are growing environmental concerns which are much in the scientific government and public eye at present. The potential impact on aquatic resources and livelihood are immense. From local to global levels, fisheries and aquaculture play important roles for food supply, food security and income generation. Some 43.5 million...
The Multi-Application Small Light Water Reactor (MASLWR) is a small natural circulation pressurized light water reactor design that was developed by Oregon State University (OSU) and Idaho National Engineering and Environmental Laboratory (INEEL) under the Nuclear Energy Research Initiative (NERI) program to address the growing demand for energy and electricity....
Ion-selective polymeric optical sensors – ion optodes – are a promising alternative to ion-selective electrodes and fluorescent dyes for analytical and biological applications, e.g. extra- and intracellular measurements. They are non-toxic, highly selective robust probes for ionic fluxes monitoring.
A large-scale fabrication of ion optodes using a solvent displacement method...
Within the past several years the technology of high-throughput sequencing has transformed the study of biology by offering unprecedented access to life's fundamental building block, DNA. With this transformation's potential a host of brand-new challenges have emerged, many of which lend themselves to being solved through computational methods. From de...
Detection of reactor antineutrinos for non-proliferation applications has been researched extensively across the globe and is considered as a potential technology to remotely monitor reactor operations without any intrusions to reactor components. Reactor antineutrino detection experiments have been conducted in the past and have proven successful in detecting the changes...
Transcriptomics and gene expression profiling enables the elucidation of the genetic response of an organism to various environmental cues. Transcriptomics enables the deciphering of differences between two closely related organisms to the same environment and in contrast, enables the elucidation of genetic responses of the same organism to different environmental...
Adjoint-derived weight windowing is a hybrid deterministic/Monte Carlo method to simulate radiation transport. In adjoint-derived weight windowing, a deterministic adjoint solution is used to create weight windows for a Monte Carlo simulation. The intent of this work is to identify factors that reduce the Figure of Merit (FOM) of Monte...
As the semiconductor industry works to integrate increasingly more "non-CMOS" devices onto CMOS ICs, compact model development has become an important step in the circuit/system verification tool flow. This research focuses on the two- and three-dimensional modeling of the physical phenomena that occur in nanoscale magnetic devices. This includes the...
The development of micro total analysis systems (µTAS), also called “lab-on-a-chip”, or microfluidic analysis systems, is presented in this dissertation. Various research areas, covering subjects from magnetic particles synthesis to novel microchip fabrication techniques, are explored to develop a lab-on-a-chip system capable of performing magnetic bead-based bioassays. These devices are...
We have developed a compact micro total analysis system (μTAS) to serve as a platform for in-situ spectrophotometric water quality monitoring. Individual fluidic, optical, and electrical components were designed, developed, and characterized. These components were combined in both an integrated (single lithographic “chip-based” platform) and a modular manner. The microfluidic...
The Department of Nuclear Engineering and Radiation Health Physics (NE/RHP) at Oregon State University (OSU) has been developing an innovative modular reactor plant concept since being initiated with a Department of Energy (DoE) grant in 1999.
This concept, the Multi-Application Small Light Water Reactor (MASLWR), is an integral pressurized water...
A novel method for detecting the peptidase activity of clinically relevant peptidases was investigated using solid-contact electrochemical polyion sensors under chronopotentiometric control. Complete instrumental control over ion-extraction was accomplished by incorporating a lipophilic electrolyte into the ion-selective membrane; the sensors had no intrinsic ion-exchange capabilities. The sensors were used to...
Detection technique that proposed utilizing electrochemically controlled, reversible ion extraction into polymeric membrane in an alternating galvanostatic/ potentiostatic mode was introduced. This method is studied in detail to comprehend the advantages of the novel sensor (pulstrode) compared to the potentiometric ion selective electrode (ISE), studies included possible applications and limitations....