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At least 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Mammograms restoration by using Wiener filter

Restoration of digital mammograms, as a pre-processing tool, using deconvolution procedures, is analysed. It implies, knowing Modulation Transfer Function (MTF) of the mammography device and the estimation of the mammogram’s noise. Wiener filter is used, as the most objective in mammograms restoration by deconvolution. Using MATLAB program the deconvolution procedures are conducted in two ways with different level of approximation. The first method approximates the noise/signal power ratio by a constant and the second method uses autocorrelation functions of the noise and signals. Abilities and limitations of the methods are analysed and checked by using the raw images of the bar-pattern due to better visualisation of the obtained results. The raw images are obtained at a Computed Radiography (CR) mammography device in Clinical Centre in Podgorica. It is found that quality of the restored image highly depends of knowledge of type and magnitude of noise. In the both methods spatial resolution of the restored images are improved, but much better in a case where autocorrelation functions of the noise and signal are used. This procedure is proposed as an objective pre-processing tool to put back imperfectness of mammography devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Computational and experimental study of laminar flames

During the past three years, our research has centered on an investigation of the effects of complex chemistry and detailed transport on the structure and extinction of hydrocarbon flames in coflowing axisymmetric configurations. We have pursued both computational and experimental aspects of the research in parallel on both steady-state and time-dependent systems. The computational work has focused on the application of accurate and efficient numerical methods for the solution of the steady-state and time-dependent boundary value problems describing the various reacting systems. Detailed experimental measurements were performed on axisymmetric coflow flames using two-dimensional imaging techniques. Previously, spontaneous Raman scattering, chemiluminescence, and laser-induced fluorescence were used to measure the temperature, major and minor species profiles. Particle image velocimetry (PIV) has been used to investigate velocity distributions and for calibration of time-varying flames. Laser-induced incandescence (LII) with an extinction calibration was used to determine soot volume fractions, while soot surface temperatures were measured with three-color optical pyrometry using a color digital camera. A blackbody calibration of the camera allows for determination of soot volume fraction as well, which can be compared with the LII measurements. More recently, we have concentrated on a detailed characterization of soot using a variety of techniques including time-resolved LII (TiRe-LII) for soot primary particles sizes, multi-angle light scattering (MALS) for soot radius of gyration, and spectrally-resolved line of sight attenuation (spec-LOSA). Combining the information from all of these soot measurements can be used to determine the soot optical properties, which are observed to vary significantly depending on spatial location and fuel dilution. Our goal has been to obtain a more fundamental understanding of the important fluid dynamic and chemical interactions in these flames so that this information can be used effectively in combustion modeling.

02 PETROLEUM↗
DOE OSTI2017

Uncertainty in the use of MAMA software to measure particle morphological parameters from SEM images

The MAMA software package developed at LANL is designed to make morphological measurements on a wide variety of digital images of objects. At LANL, we have focused on using MAMA to measure scanning electron microscope (SEM) images of particles, as this is a critical part of our forensic analysis of interdicted radiologic materials. In order to successfully use MAMA to make such measurements, we must understand the level of uncertainty involved in the process, so that we can rigorously support our quantitative conclusions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

LDRD23-0730: Invoking Multilayer Networks to Develop a Paradigm for Security Science—Summary Report

Current approaches to securing high consequence facilities (HCF) and critical assets are linear and static and therefore struggle to adapt to emerging threats (e.g., unmanned aerial systems) and changing environmental conditions (e.g., decreasing operational control). The pace of change in technological, organizational, societal, and political dynamics necessitates a move toward codifying underlying scientific principles to better characterize the rich interactions observed between HCF security technology, infrastructure, digital assets, and human or organizational components. The promising results of Laboratory Directed Research and Development (LDRD) 20-0373—“Developing a Resilient, Adaptive, and Systematic Paradigm for Security Analysis”—suggest that when compared to traditional security analysis, invoking multilayer network (MLN) modeling for HCF security system components captures unexpected failure cases and unanticipated interactions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Prospective Study of Cone-Beam Computed Tomography Image-Guided Radiotherapy for Prone Accelerated Partial Breast Irradiation

Purpose: To report setup variations during prone accelerated partial breast irradiation (APBI). Methods: New York University (NYU) 07-582 is an institutional review board-approved protocol of cone-beam computed tomography (CBCT) to deliver image-guided ABPI in the prone position. Eligible are postmenopausal women with pT1 breast cancer excised with negative margins and no nodal involvement. A total dose of 30 Gy in five daily fractions of 6 Gy are delivered to the planning target volume (the tumor cavity with 1.5-cm margin) by image-guided radiotherapy. Patients are set up prone, on a dedicated mattress, used for both simulation and treatment. After positioning with skin marks and lasers, CBCTs are performed and the images are registered to the planning CT. The resulting shifts (setup corrections) are recorded in the three principal directions and applied. Portal images are taken for verification. If they differ from the planning digital reconstructed radiographs, the patient is reset, and a new CBCT is taken. Results: 70 consecutive patients have undergone a total of 343 CBCTs: 7 patients had four of five planned CBCTs performed. Seven CBCTs (2%) required to be repeated because of misalignment in the comparison between portal and digital reconstructed radiograph image after the first CBCT. The mean shifts and standard deviations in the anterior-posterior (AP), superior-inferior (SI), and medial-lateral (ML) directions were -0.19 (0.54), -0.02 (0.33), and -0.02 (0.43) cm, respectively. The average root mean squares of the daily shifts were 0.50 (0.28), 0.29 (0.17), and 0.38 (0.20). A conservative margin formula resulted in a recommended margin of 1.26, 0.73, 0.96 cm in the AP, SI, and ML directions. Conclusion: CBCTs confirmed that the NYU prone APBI setup and treatment technique are reproducible, with interfraction variation comparable to those reported for supine setup. The currently applied margin (1.5 cm) adequately compensates for the setup variation detected.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Population of 224 realistic human subject-based computational breast phantoms

Purpose: To create a database of highly realistic and anatomically variable 3D virtual breast phantoms based on dedicated breast computed tomography (bCT) data. Methods: A tissue classification and segmentation algorithm was used to create realistic and detailed 3D computational breast phantoms based on 230 + dedicated bCT datasets from normal human subjects. The breast volume was identified using a coarse three-class fuzzy C-means segmentation algorithm which accounted for and removed motion blur at the breast periphery. Noise in the bCT data was reduced through application of a postreconstruction 3D bilateral filter. A 3D adipose nonuniformity (bias field) correction was then applied followed by glandular segmentation using a 3D bias-corrected fuzzy C-means algorithm. Multiple tissue classes were defined including skin, adipose, and several fractional glandular densities. Following segmentation, a skin mask was produced which preserved the interdigitated skin, adipose, and glandular boundaries of the skin interior. Finally, surface modeling was used to produce digital phantoms with methods complementary to the XCAT suite of digital human phantoms. Results: After rejecting some datasets due to artifacts, 224 virtual breast phantoms were created which emulate the complex breast parenchyma of actual human subjects. The volume breast density (with skin) ranged from 5.5% to 66.3% with a mean value of 25.3% ± 13.2%. Breast volumes ranged from 25.0 to 2099.6 ml with a mean value of 716.3 ± 386.5 ml. Three breast phantoms were selected for imaging with digital compression (using finite element modeling) and simple ray-tracing, and the results show promise in their potential to produce realistic simulated mammograms. Conclusions: This work provides a new population of 224 breast phantoms based on in vivo bCT data for imaging research. Compared to previous studies based on only a few prototype cases, this dataset provides a rich source of new cases spanning a wide range of breast types, volumes, densities, and parenchymal patterns.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2011

New developments for the determination of the response function for a BC501A compact neutron spectrometer for fusion diagnostics

The compact neutron spectrometer project was initiated to develop a device able to study fast neutrons produced by fusion reactions in a tokamak. The goal is to provide a fully characterized BC501A detector using a digital acquisition system developed by ENEA. The pulse height resolution and the response matrix of the detector are determined using experimental data acquired at the PTB facility. To achieve this goal, methods of data analysis involving entropy maximization and new software were developed. The methods are described and the current results for the pulse height resolution are presented. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Presentation: Sensor Anomaly Detection for Nuclear Reactor Systems Utilizing Linear Regression and K-Means Unsupervised Machine Learning: An overview of methods and results

This presentation is a culmination of work which has occurred over the course of a 10-week internship. Anomaly detection methods must be both robust enough to detect subtle anomalies yet not so sensitive to report false positives, which would result significant loss of revenue. Methods currently being developed for autonomous systems are often pursuing a Digital Twin method, which will look at the entire system and model it as a whole. This presentation, however, focuses less on direct application to an NPP, rather acting as a proof of concept for the methods developed. For the project, we look to develop methods to analyze steady-state data and report anomalies.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

How Can Construction Process Simulation Modeling Aid the Integration of Lean Principles in the Factory-Built Housing Industry?

New and existing factories that produce and deliver factory-built housing can benefit from construction process simulation modeling to explore the integration of Lean principles in their operations. Construction process simulation modeling provides digital or virtual recreations of the real-world factory environments to visualize, quantify, analyze, and optimize their underlying behavior, including factory productivity, material flow, labor dynamics, bottlenecks, and work scope. One of the key benefits of process simulation modeling is the ability to create and compare "what-if" scenarios, including integrating Lean principles such as reducing waste (for example, transportation, waiting), line balancing, and just-in-time concepts. In general, three process simulation methods are widely used: discrete event simulation (DES), agentbased modeling (ABM), and system dynamics (SD). Myriad process simulation software also is available, but depending on the industry, complexity of the system, and purposes of the simulation, some software might be more appropriate. Similar to how computer-aided design (CAD) software such as AutoCAD and Rhinoceros enable building design of modular or factory-built housing, process simulation modeling software such as jStrobe, ProModel, and AnyLogic can enable factory design of new and existing factories to deliver modular affordable housing at scale, as opposed to traditional site-built construction. Software with DES capabilities can help generate a process model that is a logical representation of resources and activities in a factory. Software with CAD-DES integration can leverage product-process data integration to help spatially visualize a DES model of the factory in the CAD environment. Software with multimethod simulation capabilities, widely used in the manufacturing industry, brings together DES, ABM, and SD in a single platform that allows visualization, quantification, analyses, and optimization at varying data fidelities. Near-real-time data from an existing factory can be directly plugged into multimethod simulation software so that the construction process simulation model is a near-accurate representation of the real-world factory conditions. This report provides insights into the use of simulation as an aid to integrate Lean concepts in factories, including guidelines for selecting the appropriate process simulation modeling method and software. These insights have been developed as part of ongoing process simulation modeling research, development, and demonstration projects at the U.S. Department of Housing and Urban Development, the U.S. Department of Energy, and the National Renewable Energy Laboratory focused on how process simulation models can enable better integration of resilience, energy efficiency, and low-carbon design strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

A mathematical discussion concerning the performance of multilayer perceptron-type artificial neural networks through use of orthogonal bipolar vectors

This work proposes the use of orthogonal bipolar vectors (OBV) as targets for multilayer perceptron (MLP) Artificial neural networks pertaining to the pattern recognition field. Implications involving this proposal are supported by a proper mathematical discussion. This study shows that the use of OBV as targets improves the class identification performance of MLP networks for pattern recognition with more than two classes when compared to the widely used conventional target bipolar vector (CBV). In addition to the overall performance improvement, it is possible to obtain high recognition rates with fewer training epochs, while keeping a feasible generalization with other data. This behavior is related to the Euclidean distance of the points in the output space, which is much higher in the case of OBVs. Therefore, with a greater distance between the points in the output space, the MLP network becomes less prone to associate trained outputs with incorrect targets. The mathematical discussion in this study is based on the backpropagation training algorithm. In addition to the mathematical discussion, results from experiments with real data are presented. These results follow those obtained by mathematical derivations. Real data sets used in the experiments are available from: (a) the Semeion Handwritten Digit of Machine Learning Repository, international repository; (b) Iris Image Database from the Chinese Academy of Sciences—CASIA; (c) Australian Sign Language, signs of Machine Learning Repository, international repository. Experiments were conducted to measure the mean Euclidean distance between the MLP network output subjected to a given input pattern and outputs related to other pattern classifications. Experimental results show that MLP networks trained with OBVs were able to ensure a Euclidean distance between the output and incorrect targets greater than MLP networks trained with CBVs (by up to 4 times for handwritten, by up to 12 times for iris images and by up to 10 times for Auslan signs language). As such, the adoption of OBVs as target vectors for MLPs reduces the computational effort for training the network.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

On convergent finite difference schemes for variational–PDE-based image processing

We study an adaptive anisotropic Huber functional-based image restoration scheme. Using a combination of L2–L1 regularization functions, an adaptive Huber functional-based energy minimization model provides denoising with edge preservation in noisy digital images. We study a convergent finite difference scheme based on continuous piecewise linear functions and use a variable splitting scheme, namely the Split Bregman (In: Goldstein and Osher, SIAM J Imaging Sci 2(2):323–343, 2009) algorithm, to obtain the discrete minimizer. Experimental results are given in image denoising and comparison with additive operator splitting, dual fixed point, and projected gradient schemes illustrates that the best convergence rates are obtained for our algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

An artificial intelligence accelerated virtual screening platform for drug discovery

Abstract Structure-based virtual screening is a key tool in early drug discovery, with growing interest in the screening of multi-billion chemical compound libraries. However, the success of virtual screening crucially depends on the accuracy of the binding pose and binding affinity predicted by computational docking. Here we develop a highly accurate structure-based virtual screen method, RosettaVS, for predicting docking poses and binding affinities. Our approach outperforms other state-of-the-art methods on a wide range of benchmarks, partially due to our ability to model receptor flexibility. We incorporate this into a new open-source artificial intelligence accelerated virtual screening platform for drug discovery. Using this platform, we screen multi-billion compound libraries against two unrelated targets, a ubiquitin ligase target KLHDC2 and the human voltage-gated sodium channel Na V 1.7. For both targets, we discover hit compounds, including seven hits (14% hit rate) to KLHDC2 and four hits (44% hit rate) to Na V 1.7, all with single digit micromolar binding affinities. Screening in both cases is completed in less than seven days. Finally, a high resolution X-ray crystallographic structure validates the predicted docking pose for the KLHDC2 ligand complex, demonstrating the effectiveness of our method in lead discovery.

Science & Technology - Other Topics↗
DOE OSTI2016

TU-FG-209-11: Validation of a Channelized Hotelling Observer to Optimize Chest Radiography Image Processing for Nodule Detection: A Human Observer Study

Purpose: To validate the use of a Channelized Hotelling Observer (CHO) model for guiding image processing parameter selection and enable improved nodule detection in digital chest radiography. Methods: In a previous study, an anthropomorphic chest phantom was imaged with and without PMMA simulated nodules using a GE Discovery XR656 digital radiography system. The impact of image processing parameters was then explored using a CHO with 10 Laguerre-Gauss channels. In this work, we validate the CHO’s trend in nodule detectability as a function of two processing parameters by conducting a signal-known-exactly, multi-reader-multi-case (MRMC) ROC observer study. Five naive readers scored confidence of nodule visualization in 384 images with 50% nodule prevalence. The image backgrounds were regions-of-interest extracted from 6 normal patient scans, and the digitally inserted simulated nodules were obtained from phantom data in previous work. Each patient image was processed with both a near-optimal and a worst-case parameter combination, as determined by the CHO for nodule detection. The same 192 ROIs were used for each image processing method, with 32 randomly selected lung ROIs per patient image. Finally, the MRMC data was analyzed using the freely available iMRMC software of Gallas et al. Results: The image processing parameters which were optimized for the CHO led to a statistically significant improvement (p=0.049) in human observer AUC from 0.78 to 0.86, relative to the image processing implementation which produced the lowest CHO performance. Conclusion: Differences in user-selectable image processing methods on a commercially available digital radiography system were shown to have a marked impact on performance of human observers in the task of lung nodule detection. Further, the effect of processing on humans was similar to the effect on CHO performance. Future work will expand this study to include a wider range of detection/classification tasks and more observers, including experienced chest radiologists.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Methodological approach to the sensitivity analysis of failure effects in modern digital I and C systems - 136

Modern I and C systems of nuclear power plants increasingly use digital equipment, software-based applications for I and C functions and different types and topologies of communication networks as well. The structure, operation and communication of digital safety-related I and C systems are strongly influenced by the implemented automatic fault detection and fault treatment procedures as barriers against failure propagation. Thus, these I and C systems can change their operating states automatically during the operation time, e.g. due to the detection and correction of certain failure types. Reasonably because of these dynamic properties of digital I and C systems the use of classical fault tree and event tree methods solely for the reliability analysis of modern I and C systems is less suitable. These methods basically apply static models and do not consider the temporal changes of the operating state of the I and C system or equipment appropriately. In this paper, a recently developed approach for the sensitivity analysis of digital I and C systems will be introduced that allows to investigate the dynamic behavior of such systems in cases of internal faults and to quantify the effects on the system reliability. The development and testing of the analysis methodology is carried out using models of generic I and C systems with different typical architectures of stepwise increased complexity. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

The OME Framework for genome-scale systems biology

The life sciences are undergoing continuous and accelerating integration with computational and engineering sciences. The biology that many in the field have been trained on may be hardly recognizable in ten to twenty years. One of the major drivers for this transformation is the blistering pace of advancements in DNA sequencing and synthesis. These advances have resulted in unprecedented amounts of new data, information, and knowledge. Many software tools have been developed to deal with aspects of this transformation and each is sorely needed. However, few of these tools have been forced to deal with the full complexity of genome-scale models along with high throughput genome-scale data. This particular situation represents a unique challenge, as it is simultaneously necessary to deal with the vast breadth of genome-scale models and the dizzying depth of high-throughput datasets. It has been observed time and again that as the pace of data generation continues to accelerate, the pace of analysis significantly lags behind. It is also evident that, given the plethora of databases and software efforts, it is still a significant challenge to work with genome-scale metabolic models, let alone next-generation whole cell models. We work at the forefront of model creation and systems scale data generation. The OME Framework was borne out of a practical need to enable genome-scale modeling and data analysis under a unified framework to drive the next generation of genome-scale biological models. Here we present the OME Framework. It exists as a set of Python classes. However, we want to emphasize the importance of the underlying design as an addition to the discussions on specifications of a digital cell. A great deal of work and valuable progress has been made by a number of communities towards interchange formats and implementations designed to achieve similar goals. While many software tools exist for handling genome-scale metabolic models or for genome-scale data analysis, no implementations exist that explicitly handle data and models concurrently. The OME Framework structures data in a connected loop with models and the components those models are composed of. This results in the first full, practical implementation of a framework that can enable genome-scale design-build-test. Over the coming years many more software packages will be developed and tools will necessarily change. However, we hope that the underlying designs shared here can help to inform the design of future software.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Experiments and Computational Theory for Electrical Breakdown in Critical Components: THz Imaging of Electronic Plasmas.

This report describes the development of ultra-short pulse laser (USPL) induced terahertz (THz) radiation to image electronic plasmas during electrical breakdown. The technique uses three pulses from two USPLs to (1) trigger the breakdown, (2) create a 2 picosecond (ps, 10 -12 s), THz pulse to illuminate the breakdown, and (3) record the THz image of the breakdown. During this three year internal research program, sub-picosecond jitter timing for the lasers, THz generation, high bandwidth (BW) diagnostics, and THz image acquisition was demonstrated. High intensity THz radiation was optically-induced in a pulse-charged gallium arsenide photoconductive switch. The radiation was collected, transported, concentrated, and co-propagated through an electro-optic crystal with an 800 nm USPL pulse whose polarization was rotated due to the spatially varying electric field of the THz image. The polarization modulated USPL pulse was then passed through a polarizer and the resulting spatially varying intensity was detected in a high resolution digital camera. Single shot images had a signal to noise of %7E3:1. Signal to noise was improved to %7E30:1 with several experimental techniques and by averaging the THz images from %7E4000 laser pulses internally and externally with the camera and the acquisition system (40 pulses per readout). THz shadows of metallic films and objects were also recorded with this system to demonstrate free-carrier absorption of the THz radiation and improve image contrast and resolution. These 2 ps THz pulses were created and resolved with 100 femtosecond (fs, 10 -15 s) long USPL pulses. Thus this technology has the capability to time-resolve extremely fast repetitive or single shot phenomena, such as those that occur during the initiation of electrical breakdown. The goal of imaging electrical breakdown was not reached during this three year project. However, plans to achieve this goal as part of a follow-on project are described in this document. Further modifications to improve the THz image contrast and resolution are proposed, and after they are made, images of photo-induced carriers in gallium arsenide and silicon will be acquired to evaluate image sensitivity versus carrier density. Finally electrical breakdown will be induced with the first USPL pulse, illuminated with THz radiation produced with the second USPL pulse and recorded with the third USPL pulse.

36 MATERIALS SCIENCE↗
DOE OSTI2023

CRADA Number NFE-20-08292 with Quantum Lock Technologies LLC (CRADA Final Report)

At Quantum Lock Technologies, our mission is to use future-proof hardware and software to bridge the gap between physical access control and cyber security. Physical security includes access to doors, lockboxes/containers, and machinery/robots. Connecting physical access control to the cloud allows for remote detection, fast ledger updates, and mobile or remote access. However, this also opens physical security up to the world of cyber-attacks. At Quantum Lock, we use quantum random number generation to generate completely random and unpredictable digital keys to be used by connected equipment in a facility. This quantum technology is then paired with end-to-end encryption and a one-time-key communication protocol to ensure the highest level of security. Through the Innovation Crossroads program at Oak Ridge National Laboratory, we have developed benchtop prototypes of our technology, connected with utility boards as our first target customers, and prepared for our first pilot with customers (target end of summer 2022).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Electronic Bottleneck Suppression in Next‐Generation Networks with Integrated Photonic Digital‐to‐Analog Converters

Digital‐to‐analog converters (DAC) are indispensable functional units in signal processing instrumentation and wide‐band telecommunication links for both civil and military applications. As photonic systems are capable of high data throughput and low latency, an increasingly found system limitation stems from the required domain crossing such as digital to analog and electronic to optical. A photonic DAC implementation, in contrast, enables a seamless signal conversion with respect to both energy efficiency and short signal delay, often requiring bulky discrete optical components and electric–optic transformation, hence introducing inefficiencies. Herein, a novel coherent parallel photonic DAC concept along with a 4‐bit experimental prototype capable of performing this DAC without optic–electric–optic domain crossing is introduced. This new paradigm guarantees a linear intensity weighting among bits when operating at high sampling rates (50 GHz), featuring an exceptional sampling efficiency (> 100 GS ) and small footprint (≈1 mm 2 ) in an 8‐bit implementation. Importantly, this photonic DAC enables seamless interfaces of next‐generation data processing hardware with high relevance in data centers, task‐specific compute accelerators such as neuromorphic engines, and network edge processing applications.

Meng, Jiawei↗