Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Recognition”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Two Independent Histidines One in Human Prolactin and One in Its Receptor Are Critical for pH-dependent Receptor Recognition and Activation

Human prolactin (hPRL), a member of the family of hematopoietic cytokines, functions as both an endocrine hormone and autocrine/paracrine growth factor. We have previously demonstrated that recognition of the hPRL-receptor depends strongly on solution acidity over the physiologic range from pH 6 to pH 8. The hPRL-receptor binding interface contains four histidines whose protonation is hypothesized to regulate pH-dependent receptor recognition. Here, we systematically dissect its molecular origin by characterizing the consequences of His to Ala mutations on pH-dependent receptor binding kinetics, site-specific histidine protonation, and high resolution structures of the intermolecular interface. Thermodynamic modeling of the pH dependence to receptor binding affinity reveals large changes in site-specific protonation constants for a majority of interface histidines upon complexation. Removal of individual His imidazoles reduces these perturbations in protonation constants, which is most likely explained by the introduction of solvent-filled, buried cavities in the crystallographic structures without inducing significant conformational rearrangements.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Structural Insights into RNA Recognition by the Alternate-Splicing Regulator CUG-Binding Protein 1

CUG-binding protein 1 (CUGBP1) regulates multiple aspects of nuclear and cytoplasmic mRNA processing, with implications for onset of myotonic dystrophy. CUGBP1 harbors three RRM domains and preferentially targets UGU-rich mRNA elements. We describe crystal structures of CUGBP1 RRM1 and tandem RRM1/2 domains bound to RNAs containing tandem UGU(U/G) elements. Both RRM1 in RRM1-RNA and RRM2 in RRM1/2-RNA complexes use similar principles to target UGU(U/G) elements, with recognition mediated by face-to-edge stacking and water-mediated hydrogen-bonding networks. The UG step adopts a left-handed Z-RNA conformation, with the syn guanine recognized through Hoogsteen edge-protein backbone hydrogen-bonding interactions. NMR studies on the RRM1/2-RNA complex establish that both RRM domains target tandem UGUU motifs in solution, whereas filter-binding assays identify a preference for recognition of GU over AU or GC steps. We discuss the implications of CUGBP1-mediated targeting and sequestration of UGU(U/G) elements on pre-mRNA alternative-splicing regulation, translational regulation, and mRNA decay.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Door latching recognition apparatus and process

An acoustic door latch detector is provided in which a sound recognition sensor is integrated into a door or door lock mechanism. The programmable sound recognition sensor can be trained to recognize the acoustic signature of the door and door lock mechanism being properly engaged and secured. The acoustic sensor will signal a first indicator indicating that proper closure was detected or sound an alarm condition if the proper acoustic signature is not detected within a predetermined time interval.

47 OTHER INSTRUMENTATION↗
DOE OSTI2012

Dynamic chemistry of anion recognition

In the past 40 years, anion recognition by synthetic receptors has grown into a rich and vibrant research topic, developing into a distinct branch of Supramolecular Chemistry. Traditional anion receptors comprise organic scaffolds functionalized with complementary binding groups that are assembled by multistep organic synthesis. Recently, a new approach to anion receptors has emerged, in which the host is dynamically self-assembled in the presence of the anionic guest, via reversible bond formation between functional building units. While coordination bonds were initially employed for the self-assembly of the anion hosts, more recent studies demonstrated that reversible covalent bonds can serve the same purpose. In both cases, due to their labile connections, the molecular constituents have the ability to assemble, dissociate, and recombine continuously, thereby creating a dynamic combinatorial library (DCL) of receptors. The anionic guests, through specific molecular recognition, may then amplify (express) the formation of a particular structure among all possible combinations (real or virtual) by shifting the equilibria involved towards the most optimal receptor. This approach is not limited to solution self-assembly, but is equally applicable to crystallization, where the fittest anion-binding crystal may be selected. Finally, the pros and cons of employing dynamic combinatorial chemistry (DCC) vs molecular design for developing anion receptors, and the implications of both approaches to selective anion separations, will be discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

An Iris Segmentation Algorithm based on Edge Orientation for Off-angle Iris Recognition

Iris recognition is known as one of the most accurate and reliable biometrics. However, the accuracy of iris recognition systems depends on the quality of data capture and is negatively affected by several factors such as angle, occlusion, and dilation. In this paper, we present a segmentation algorithm for off-angle iris images that uses edge detection, edge elimination, edge classification, and ellipse fitting techniques. In our approach, we first detect all candidate edges in the iris image by using the canny edge detector; this collection contains edges from the iris and pupil boundaries as well as eyelash, eyelids, iris texture etc. Edge orientation is used to eliminate the edges that cannot be part of the iris or pupil. Then, we classify the remaining edge points into two sets as pupil edges and iris edges. Finally, we randomly generate subsets of iris and pupil edge points, fit ellipses for each subset, select ellipses with similar parameters, and average to form the resultant ellipses. Based on the results from real experiments, the proposed method shows effectiveness in segmentation for off-angle iris images.

Karakaya, Mahmut↗
DOE OSTI2013

Method of particle trajectory recognition in particle flows of high particle concentration using a candidate trajectory tree process with variable search areas

The application relates to particle trajectory recognition from a Centroid Population comprised of Centroids having an (x, y, t) or (x, y, f) coordinate. The method is applicable to visualization and measurement of particle flow fields of high particle. In one embodiment, the centroids are generated from particle images recorded on camera frames. The application encompasses digital computer systems and distribution mediums implementing the method disclosed and is particularly applicable to recognizing trajectories of particles in particle flows of high particle concentration. The method accomplishes trajectory recognition by forming Candidate Trajectory Trees and repeated searches at varying Search Velocities, such that initial search areas are set to a minimum size in order to recognize only the slowest, least accelerating particles which produce higher local concentrations. When a trajectory is recognized, the centroids in that trajectory are removed from consideration in future searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Augmenting C. elegans Microscopic Dataset for Accelerated Pattern Recognition

The detection of cell shape changes in 3D time-lapse images of complex tissues is an important task. However, it is a challenging and tedious task to establish a comprehensive dataset to improve the performance of deep learning models. In the paper, we present a deep learning approach to augment 3D live images of the Caenorhabditis elegans embryo, so that we can further speed up the specific structure pattern recognition. We use an unsupervised training over unlabeled images to generate supplementary datasets for further pattern recognition. Technically, we used Alex-style neural networks in a generative adversarial network framework to generate new datasets that have common features of the C. elegans membrane structure. We also made the dataset available for a broad scientific community.

Lu, Zheng↗
DOE OSTI2020

Video Summarization Using Deep Action Recognition Features and Robust Principal Components Analysis

In an instance where desired pre-defined actions, behaviors, or other categories are known a priori, various video classification and recognition models can be trained to discover those classifications and their location within the video. Absent that information, one might still be tasked with identifying interesting portions within a video, a process which—if done manually—is onerous and time-consuming as it requires manual inspection of the video itself. Recognizing high-level interesting segments within a whole video has been a general area of interest due to the ubiquity of video data. However the size of the data makes storage, retrieval, and inspection of large collections of videos cumbersome. This problem motivates the task of generating shortened clips highlighting the primary content of a video, relieving the burden of having to watch the entire video. This paper presents an unsupervised method of creating shortened clips of videos, enabling the rapid review of the most interesting content within a video. Our method uses features extracted from pre-trained action recognition models as input to online moving window robust principal component analysis to generate summaries. The procedure is tested on a publicly available video summarization dataset and demonstrates comparable performance to state-of-the-art in an un-augmented setting while requiring no training.

Claborne, Daniel M.↗
DOE OSTI2024

Commissioning of the Mu2e tracker DAQ, planning for the Vertical Slice Test and pre-pattern recognition studies

The primary objective of the Mu2e experiment at Fermilab is to search for the neutrino-less coherent $\mu \rightarrow e$ conversion in the field of an aluminum nucleus ($\mu^- \text{Al} \rightarrow e^- \text{Al}$). The signature of this process is a monochromatic Conversion Electron (CE) with an energy of approximately 104.97 MeV \cite{bartoszek2015mu2e}. Within the Standard Model (SM), the branching ratio for this process, including neutrino masses and oscillation, is expected to be less than $\mathcal{O}(10^{-50})$. This value is far beyond current experimental capabilities. However, models of physics beyond the SM predict much higher relative rates, approaching an observable level. The SINDRUM II experiment set an upper limit on muon conversion at $7 \times 10^{-13}$ (90\% CL) on Au target \cite{SINDRUMII:2006dvw}, and the Mu2e collaboration aims to improve this limit by four orders of magnitude. Observing this process would provide a clear evidence of physics beyond the Standard Model. A brief discussion of the theoretical and experimental aspects is provided in Chapter \ref{intr}. Mu2e adopts a sophisticated experimental setup to achieve its goals, further described in Chapter \ref{mu2echapter}. The central part of the Mu2e detector is the tracker, that consists of 18 tracking stations. The tracker must provide excellent momentum resolution, approximately 1 MeV/c, to distinguish the monochromatic CE signal from the background. To minimize the energy losses, a straw tube tracker will be used \cite{bobbb}. Chapter \ref{chaptertrk} provides an overview of the straw tracker design and its working principles. This Thesis presents a comprehensive study of the Mu2e tracker, covering complementary aspects from initial commissioning to optimization and first steps of the calibration processes. My work at Fermilab has been focused on the complete Data Acquisition (DAQ) testing from both hardware and software perspectives. I was involved in the commissioning of the Mu2e DAQ system and the Vertical Slice Test (VST) of the tracker. The VST encompasses the entire testing chain, from the straws to the readout, and to processed data on disk. I was also focused on the offline analysis, especially on pre-pattern recognition studies, to explore the best methods for identifying $\delta$-electrons during the data taking. Chapter \ref{commissioning} details the commissioning of the tracker DAQ system, emphasizing the importance of understanding of the readout process before the data acquisition. This includes validating the readout logic and firmware through Monte Carlo simulations to confirm functionality and buffering, monitoring the quality of the data from the tracker preamplifiers and front-end electronics, and assessing overall DAQ performance to ensure reliability during future calibration and data-taking. Chapter \ref{planning} discusses the initial steps towards the tracker calibration. The ultimate goal is to perform a time calibration of the first assembled station of the tracker using cosmic muons, aiming for a longitudinal hit position resolution better than 4 cm. This involves determining the signal propagation times and channel-to-channel delays. I performed a Monte Carlo study to determine the impact of the station orientation on the quality of the calibration, in particular on the cosmic track reconstruction, focusing on potential biases that could arise. These studies provide essential insights into the operation, optimization, and calibration of the Mu2e tracker system. Given the high data volume expected during Mu2e operations, estimated at approximately 7 PBytes per year, optimizing memory usage and minimizing CPU consumption are critical. A significant challenge lies in effectively flagging $\delta$-electron hits, which are the primary source of hits in the tracker, without compromising the efficiency of CE hit detection and track reconstruction. A detailed study of pre-pattern recognition and a thorough comparison of two $\delta$-electron flagging algorithms is provided in Chapter \ref{delta}. In Chapter \ref{conclusions}, the findings are concisely summarized, offering a comprehensive synthesis of the research and emphasizing the key insights derived from this study.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

The BRIAR Dataset: A Comprehensive Whole-Body Biometric Recognition Benchmark at Extreme Distances and Altitudes (Collections 1-6)

The Biometric Recognition and Identification at Altitude and Range (BRIAR) program aims to extend biometric capabilities into severe operational environments characterized by long ranges, atmospheric turbulence, and elevated viewpoints. This paper introduces the program’s two final government collections expanding activities, environments, viewpoints, distances, and modalities, and adding appearance and environmental stressors. We refine curation/evaluation and include sequestered subsets to support controlled assessments. These updates strengthen BRIAR as a comprehensive resource for whole-body, face, and gait recognition at altitude and range, while maintaining privacy-first practices.

Yoon, Rocky [ORNL] (ORCID:0009000491499165)↗
DOE OSTI2015

Structural basis underlying CAC RNA recognition by the RRM domain of dimeric RNA-binding protein RBPMS

RNA-binding protein with multiple splicing (designated RBPMS) is a higher vertebrate mRNA-binding protein containing a single RNA recognition motif (RRM). RBPMS has been shown to be involved in mRNA transport, localization and stability, with key roles in axon guidance, smooth muscle plasticity, as well as regulation of cancer cell proliferation and migration. We report on structure-function studies of the RRM domain of RBPMS bound to a CAC-containing single-stranded RNA. These results provide insights into potential topologies of complexes formed by the RBPMS RRM domain and the tandem CAC repeat binding sites as detected by photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation. These studies establish that the RRM domain of RBPMS forms a symmetrical dimer in the free state, with each monomer binding sequence-specifically to all three nucleotides of a CAC segment in the RNA bound state. Structure-guided mutations within the dimerization and RNA-binding interfaces of RBPMS RRM on RNA complex formation resulted in both disruption of dimerization and a decrease in RNA-binding affinity as observed by size exclusion chromatography and isothermal titration calorimetry. Here, as anticipated from biochemical binding studies, over-expression of dimerization or RNA-binding mutants of Flag-HA-tagged RBPMS were no longer able to track with stress granules in HEK293 cells, thereby documenting the deleterious effects of such mutations in vivo .

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2017

Object and Facial Recognition in Augmented and Virtual Reality: Investigation into Software, Hardware and Potential Uses

As augmented and virtual reality grows in popularity, and more researchers focus on its development, other fields of technology have grown in the hopes of integrating with the up-and-coming hardware currently on the market. Namely, there has been a focus on how to make an intuitive, hands-free human-computer interaction (HCI) utilizing AR and VR that allows users to control their technology with little to no physical interaction with hardware. Computer vision, which is utilized in devices such as the Microsoft Kinect, webcams and other similar hardware has shown potential in assisting with the development of a HCI system that requires next to no human interaction with computing hardware and software. Object and facial recognition are two subsets of computer vision, both of which can be applied to HCI systems in the fields of medicine, security, industrial development and other similar areas.

object recognition↗
DOE OSTI2016

Simulation studies of substrate recognition by the exocellulase CelF from Clostridium cellulolyticum

Molecular dynamics (MD) simulations were used to study substrate recognition by the family 48 exocellulase CelF from Clostridium cellulolyticum. It was hypothesized that residues around the entrance of the active site tunnel of this enzyme might serve to recognize and bind the substrate through an affinity for the cellulose monomer repeat unit, ..beta..-d-glucopyranose. Simulations were conducted of the catalytic domain of this enzyme surrounded by a concentrated solution of ..beta..-d-glucopyranose, and the full three-dimensional probability distribution for finding sugar molecules adjacent to the enzyme was calculated from the trajectory. A significant probability of finding the sugar stacked against the planar faces of Trp 310 and Trp 312 at the entrance of the active site tunnel was observed.

09 BIOMASS FUELS↗
DOE OSTI2021

Peptide nucleic acid Hoogsteen strand linker design for major groove recognition of DNA thymine bases

Sequence-specific targeting of double-stranded DNA and non-coding RNA via triple-helix-forming peptide nucleic acids (PNAs) has attracted considerable attention in therapeutic, diagnostic and nanotechnological fields. An E-base (3-oxo-2,3-dihydropyridazine), attached to the polyamide backbone of a PNA Hoogsteen strand by a side-chain linker molecule, is typically used in the hydrogen bond recognition of the 4-oxo group of thymine and uracil nucleic acid bases in the major groove. We report on the application of quantum chemical computational methods, in conjunction with spatial constraints derived from the experimental structure of a homopyrimidine PNA·DNA-PNA hetero-triplex, to investigate the influence of linker flexibility on binding interactions of the E-base with thymine and uracil bases in geometry-optimised model systems. Hydrogen bond formation between the N2 E-base atom and target pyrimidine base 4-oxo groups in model systems containing a β-alanine linker (J Am Chem Soc 119:11116, 1997) was found to incur significant internal strain energy and the potential disruption of intra-stand aromatic base stacking interactions in an oligomeric context. Additionally, in geometry-optimised model systems containing a 3-trans olefin linker (Bioorg Med Chem Lett 14:1551, 2004) the E-base swung out away from the target pyrimidine bases into the solvent. These findings are in qualitative agreement with calorimetric measurements in hybridisation experiments at T–A and U–A inversion sites. In contrast, calculations on a novel 2-cis olefin linker design indicate that it could permit simultaneous E-base hydrogen bonding with the thymine 4-oxo group, circumvention and solvent screening of the thymine 5-methyl group, and maintenance of triplex intra-stand base stacking interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Development of gas chromatographic pattern recognition and classification tools for compliance and forensic analyses of fuels: A review

Gas chromatography (GC) is undoubtedly the analytical technique of choice for analyzing the composition of petroleum-based fuels. Over the past twenty years, as comprehensive two-dimensional gas chromatography (GC×GC) has evolved, fuel analysis has often been highlighted in scientific reports, as their complexity allows for illustration of the impressive peak capacity gains afforded by GC×GC. Indeed, several research groups in recent years have applied GC×GC and chemometrics to demonstrate the potential of these analytical tools to address important compliance (tax evasion, tax credits, physical quality standards) and forensic (arson investigations, oil spills) applications involving fuels. None the less, routine use of GC×GC in forensic laboratories has been limited largely by (1) legal and regulatory guidelines, (2) lack of chemometrics training, and (3) concerns about the reproducibility of GC×GC. The goal of this review is to highlight recent advances in one-dimensional GC (1D-GC) and GC×GC analyses of fuels for compliance and forensic applications, in an effort to assist scientists in overcoming the aforementioned hindrances. An introduction to 1D-GC principles, GC×GC technology (column stationary phases and modulators) and several chemometric techniques will be provided. More specifically, chemometric techniques will be broken down into (1) signal pre-processing, (2) peak decomposition, identification and quantification, and (3) classification and pattern recognition. Examples of compliance and forensic applications will be discussed, with particular emphasis on the demonstrated success of the employed chemometric techniques. Overall, this review will hopefully make 1D-GC and GC×GC coupled with chemometric data analysis tools more accessible to the larger scientific community, and aid in eventual widespread standardization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗