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  1. As autonomous robots interact and navigate around real-world environments such as homes, it is useful to reliably identify and manipulate articulated objects, such as doors and cabinets. Many prior works in object articulation identification require manipulation of the object, either by the robot or a human. While recent works have addressed predicting articulation types from visual observations alone, they often assume prior knowledge of category-level kinematic motion models or sequence of observations where the articulated parts are moving according to their kinematic constraints. In this work, we propose FormNet, a neural network that identifies the articulation mechanisms between pairs ofmore »object parts from a single frame of an RGB-D image and segmentation masks. The network is trained on 100k synthetic images of 149 articulated objects from 6 categories. Synthetic images are rendered via a photorealistic simulator with domain randomization. Our proposed model predicts motion residual flows of object parts, and these flows are used to determine the articulation type and parameters. The network achieves an articulation type classification accuracy of 82.5% on novel object instances in trained categories. Experiments also show how this method enables generalization to novel categories and can be applied to real-world images without fine-tuning.« less
    Free, publicly-accessible full text available October 1, 2022
  2. Purpose : Personalized screening guidelines can be an effective strategy to prevent diabetic retinopathy (DR)-related vision loss. However, these strategies typically do not capture behavior-based factors such as a patient’s compliance or cost preferences. This study develops a mathematical model to identify screening policies that capture both DR progression and behavioral factors to provide personalized recommendations. Methods : A partially observable Markov decision process model (POMDP) is developed to provide personalized screening recommendations. For each patient, the model estimates the patient’s probability of having a sight-threatening diabetic eye disorder (STDED) yearly via Bayesian inference based on natural history, screening results,more »and compliance behavior. The model then determines a personalized, threshold-based recommendation for each patient annually--either no action (NA), teleretinal imaging (TRI), or clinical screening (CS)--based on the patient’s current probability of having STDED as well as patient-specific preference between cost saving ($) and QALY gain. The framework is applied to a hypothetical cohort of 40-year-old African American male patients. Results : For the base population with TRI and CS compliance rates of 65% and 55% and equal preference for cost and QALY, NA is identified as an optimal recommendation when the patient’s probability of having STDED is less than 0.72%, TRI when the probability is [0.72%, 2.09%], and CS when the probability is above 2.09%. Simulated against annual clinical screening, the model-based policy finds an average decrease of 7.07% in cost/QALY (95% CI; 6.93-7.23%) and 15.05% in blindness prevalence over a patient’s lifetime (95% CI; 14.88-15.23%). For patients with equal preference for cost and QALY, the model identifies 6 different types of threshold-based policies (See Fig 1). For patients with strong preference for QALY gain, CS-only policies had an increase in prevalence by a factor of 19.2 (see Fig 2). Conclusions : The POMDP model is highly flexible and responsive in incorporating behavioral factors when providing personalized screening recommendations. As a decision support tool, providers can use this modeling framework to provide unique, catered recommendations.« less
  3. The antifouling properties of self-assembled monolayers (SAMs) on gold generated from custom-designed bidentate unsymmetrical spiroalkanedithiols containing both oligo(ethylene glycol) and hydrocarbon tailgroups (EG3C7-C7 and EG3C7-C18) were evaluated and compared to SAMs derived from analogous monodentate octadecanethiol (C18SH) and the tri(ethylene glycol)-terminated alkanethiol EG3C7SH. Complementary techniques, including in situ surface plasmon resonance spectroscopy (SPR), ex situ electrochemical quartz crystal microbalance (QCM) measurements, and ex situ ellipsometric thickness measurements, were employed to assess the protein resistance of the SAMs using proteins having a wide range of sizes, structures, and properties: protamine, lysozyme, bovine serum albumin (BSA), and fibrinogen. The studies found thatmore »SAMs generated from the bidentate adsorbates EG3C7-C7 and EG3C7-C18, which contain a 1:1 mixture of OEG and hydrocarbon tailgroups, exhibited a diminished capacity to resist protein adsorption compared to the EG3C7SH SAMs, which possess only OEG tailgroups. The data highlight the critical role of hydration of the OEG matrix for generating antifouling OEG-based surface coatings.« less
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  5. Free, publicly-accessible full text available November 1, 2022
  6. Abstract. This paper describes version 2.0 of the Global Change and Air Pollution (GCAP 2.0) model framework, a one-way offline coupling between version E2.1 of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM) and the GEOS-Chem global 3-D chemical-transport model (CTM). Meteorology for driving GEOS-Chem has been archived from the E2.1 contributions to phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the pre-industrial era and the recent past. In addition, meteorology is available for the near future and end of the century for seven future scenarios ranging from extreme mitigation to extreme warming. Emissions and boundary conditionsmore »have been prepared for input to GEOS-Chem that are consistent with the CMIP6 experimental design. The model meteorology, emissions, transport, and chemistry are evaluated in the recent past and found to be largely consistent with GEOS-Chem driven by the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) product and with observational constraints.« less
  7. Methane is a powerful greenhouse gas and a key player in atmospheric chemistry. Important uncertainties remain in the global atmospheric methane budget, with natural geologic emissions being one of the particularly uncertain terms. In recent bottom-up studies, geologic emissions have been estimated to comprise up to 10% of the global budget (40–60 Teragrams of methane per year, Tg CH4 yr–1). In contrast, top-down constraints from 14C of methane in preindustrial air extracted from ice cores indicate that the geologic methane source is approximately an order of magnitude lower. Recent bottom-up inventories propose microseepage (diffuse low-level flux of methane through soilsmore »over large areas) as the largest single component of the geologic methane flux. In this study, we present new measurements of methane microseepage from the Appalachian Basin (Western New York State) and compare these with prior microseepage measurements from other regions and with predicted values from the most recent bottom-up inventory. Our results show lower microseepage values than most prior data sets and indicate that positive microseepage fluxes in this region are not as widespread as previously assumed. A statistical analysis of our results indicates that mean microseepage flux in this region has very likely been overestimated by the bottom-up inventory, even though our measurements more likely than not underestimate the true mean flux. However, this is a small data set from a single region and as such cannot be used to evaluate the validity of the microseepage emissions inventory as a whole. Instead, the results demonstrate the need for a more extensive network of direct geologic emission measurements in support of improved bottom-up inventories.« less
  8. Abstract. Important uncertainties remain in our understanding of the spatial andtemporal variability of atmospheric hydroxyl radical concentration ([OH]).Carbon-14-containing carbon monoxide (14CO) is a useful tracer that canhelp in the characterization of [OH] variability. Prior measurements ofatmospheric 14CO concentration ([14CO] are limited in both theirspatial and temporal extent, partly due to the very large air sample volumes that have been required for measurements (500–1000 L at standardtemperature and pressure, L STP) and the difficulty and expense associatedwith the collection, shipment, and processing of such samples. Here wepresent a new method that reduces the air sample volume requirement to≈90 L STP while allowing for [14CO] measurementmore »uncertainties that are on par with or better than prior work (≈3 % or better, 1σ). The method also for the first time includes accurate characterization of the overall procedural [14CO] blank associated with individual samples, which is a key improvement over prior atmospheric 14CO work. The method was used to make measurements of [14CO] at the NOAA Mauna Loa Observatory, Hawaii, USA, between November 2017 and November 2018. The measurements show the expected [14CO] seasonal cycle (lowest in summer)and are in good agreement with prior [14CO] results from anotherlow-latitude site in the Northern Hemisphere. The lowest overall [14CO]uncertainties (2.1 %, 1σ) are achieved for samples that aredirectly accompanied by procedural blanks and whose mass is increased to≈50 µgC (micrograms of carbon) prior to the 14Cmeasurement via dilution with a high-CO 14C-depleted gas.« less