JWST spectra of brown dwarf candidates in the Orion Nebula Cluster
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K L Luhman↗
SEARCH · Engineering Papers
Results for “k -Means clustering”
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.
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Benchmark relativistic delta-coupled-cluster calculations of K-edge core-ionization energies of third-row elements
Here a benchmark computational study of K-edge core-ionization energies of third-row elements using relativistic delta-coupled-cluster (ΔCC) methods and a revised core-valence separation (CVS) scheme is reported. High-level relativistic (HLR) corrections beyond the spin-free exact two-component theory in its one-electron variant (SFX2C-1e), including the contributions from two-electron picture-change effects, spin–orbit coupling, the Breit term, and quantum electrodynamics effects, have been taken into account and demonstrated to play an important role. Relativistic ΔCC calculations are shown to provide accurate results for core-ionization energies of third-row elements. The SFX2C-1e-CVS-ΔCC results augmented with HLR corrections show a maximum deviation of less than 0.5 eV with respect to experimental values.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Cluster Method Analysis of K. S. C. Image
Information obtained from satellite-based systems has moved to the forefront as a method in the identification of many land cover types. Identification of different land features through remote sensing is an effective tool for regional and global assessment of geometric characteristics. Classification data acquired from remote sensing images have a wide variety of applications. In particular, analysis of remote sensing images have special applications in the classification of various types of vegetation. Results obtained from classification studies of a particular area or region serve towards a greater understanding of what parameters (ecological, temporal, etc.) affect the region being analyzed. In this paper, we make a distinction between both types of classification approaches although, focus is given to the unsupervised classification method using 1987 Thematic Mapped (TM) images of Kennedy Space Center.
Rodriguez, Joe, Jr.↗
Optical signatures of molecular particles via mass-selected cluster spectroscopy
A new molecular beam apparatus was developed to study optical absorption in cold (less than 100 K) atomic clusters and complexes produced by their condensation with simple molecular gases. In this instrument, ionized clusters produced in a laser vaporization nozzle source are mass selected and studied with photodissociation spectroscopy at visible and ultraviolet wavelengths. This new approach can be applied to synthesize and characterize numerous particulates and weakly bound complexes expected in planetary atmospheres and in comets.
Duncan, Michael A.↗
Metal abundance in the Praesepe and Hyades clusters
Calcium K-line photometry is reported for 27 A-type stars in the Praesepe cluster, and the data obtained are compared with previous K-line observations of Hyades stars. It is found that calcium and other metals are generally overabundant in Praesepe relative to field stars and that there is a considerable scatter in metal-abundance indices. Comparison with the Hyades results indicates that the Praesepe stars are as metal-enriched as the Hyades stars. These results are taken as evidence favoring Eggen's (1960) proposal that the Hyades and Praesepe clusters should be regarded as a single group having, on the average, about a factor-of-two higher metal abundance than solar-neighborhood field stars as well as a high internal dispersion in metal-line strengths. The questions of where and how the Praesepe-Hyades stars acquired their high average metal abundances, K-line strengths, and associated dispersions are briefly considered.
Henry, R. C.↗
Z-Sequence: photometric redshift predictions for galaxy clusters with sequential random k-nearest neighbours
ABSTRACT We introduce Z-Sequence, a novel empirical model that utilizes photometric measurements of observed galaxies within a specified search radius to estimate the photometric redshift of galaxy clusters. Z-Sequence itself is composed of a machine learning ensemble based on the k-nearest neighbours algorithm. We implement an automated feature selection strategy that iteratively determines appropriate combinations of filters and colours to minimize photometric redshift prediction error. We intend for Z-Sequence to be a standalone technique but it can be combined with cluster finders that do not intrinsically predict redshift, such as our own DEEP-CEE. In this proof-of-concept study, we train, fine-tune, and test Z-Sequence on publicly available cluster catalogues derived from the Sloan Digital Sky Survey. We determine the photometric redshift prediction error of Z-Sequence via the median value of |Δ$z$|/(1 + $z$) (across a photometric redshift range of 0.05 ≤ $z$ ≤ 0.6) to be ∼0.01 when applying a small search radius. The photometric redshift prediction error for test samples increases by 30–50 per cent when the search radius is enlarged, likely due to line-of-sight interloping galaxies. Eventually, we aim to apply Z-Sequence to upcoming imaging surveys such as the Legacy Survey of Space and Time to provide photometric redshift estimates for large samples of as yet undiscovered and distant clusters.
Chan, Matthew C.↗
Unsupervised Image-Based Classification of Corrosion Severity in Automobile Engine Connecting Rods
Corrosion in engine connecting rods is a critical issue in the automotive industry, potentially leading to catastrophic engine failure, monetary losses, and safety hazards. The labor shortage in the industry further emphasizes the need for fast, accurate, and automated corrosion detection methods to ensure appropriate surface treatments can be applied to restore component integrity. We present an unsupervised image-based framework for classifying corrosion severity in automobile engine connecting rods using short-wave infrared (SWIR) and telecentric grayscale imaging. We employ the structural similarity index measure (SSIM) as a dissimilarity metric and the k-medians clustering algorithm for classification. Our algorithm achieves an overall accuracy of 80.64% for SWIR images, with 100% accuracy in classifying highly corroded samples. For grayscale images, the method attains an overall accuracy of 77.42%, with 90.91% accuracy for highly corroded samples. The method’s ability to work with different imaging modalities and its high accuracy in identifying severe corrosion cases make it a promising tool for automated corrosion assessment in the automotive industry, potentially improving efficiency and safety in engine component maintenance.
42 ENGINEERING↗
Cluster Combustion of Binary-Fuel Drops
Most fuels used in practical combustion liquid-fuel sprays devices are blends of several components. In many cases, the composition of the fuel is considered critical for the operation of the device due to efficiency and pollution production considerations. This investiga- tion focuses on cluster flames for binary-fuel drops. Studied are spherical clusters of relatively cold drops exposed to an axial flow.
cluster flames liquid-fuel sprays spray systems co↗
Updated neutrino mass constraints from galaxy clustering and CMB lensing-galaxy cross-correlation measurements
In this work, we revisit cosmological constraints on the sum of the neutrino masses Σm v from a combination of full-shape BOSS galaxy clustering [P(k)] data and measurements of the cross-correlation between Planck Cosmic Microwave Background (CMB) lensing convergence and BOSS galaxy overdensity maps [$C_{l}^{kg}$], using a simple but theoretically motivated model for the scale-dependent galaxy bias in auto- and cross-correlation measurements. We improve upon earlier related work in several respects, particularly through a more accurate treatment of the correlation and covariance between P(k) and $C_{l}^{kg}$ measurements. When combining these measurements with Planck CMB data, we find a 95% confidence level upper limit of Σm v sum of neutrino masses < 0.14 eV, while slightly weaker limits are obtained when including small-scale ACTPol CMB data, in agreement with our expectations. We confirm earlier findings that (once combined with CMB data) the full-shape information content is comparable to the geometrical information content in the reconstructed BAO peaks given the precision of current galaxy clustering data, discuss the physical significance of our inferred bias and shot noise parameters, and perform a number of robustness tests on our underlying model. While the inclusion of $C_{l}^{kg}$ measurements does not currently appear to lead to substantial improvements in the resulting Σm v of neutrino mass constraints, we expect the converse to be true for near-future galaxy clustering measurements, whose shape information content will eventually supersede the geometrical one.
79 ASTRONOMY AND ASTROPHYSICS↗
Timing based clustering of childhood BMI trajectories reveals differential maturational patterns; Study in the Northern Finland Birth Cohorts 1966 and 1986
Children’s biological age does not always correspond to their chronological age. In the case of BMI trajectories, this can appear as phase variation, which can be seen as shift, stretch, or shrinking between trajectories. With maturation thought of as a process moving towards the final state - adult BMI, we assessed whether children can be divided into latent groups reflecting similar maturational age of BMI. The groups were characterised by early factors and time-related features of the trajectories. We used data from two general population birth cohort studies, Northern Finland Birth Cohorts 1966 and 1986 (NFBC1966 and NFBC1986). Height (n = 6329) and weight (n = 6568) measurements were interpolated in 34 shared time points using B-splines, and BMI values were calculated between 3 months to 16 years. Pairwise phase distances of 2999 females and 3163 males were used as a similarity measure in k-medoids clustering. We identified three clusters of trajectories in females and males (Type 1: females, n = 1566, males, n = 1669; Type 2: females, n = 1028, males, n = 973; Type 3: females, n = 405, males, n = 521). Similar distinct timing patterns were identified in males and females. The clusters did not differ by sex, or early growth determinants studied. Trajectory cluster Type 1 reflected to the shape of what is typically illustrated as the childhood BMI trajectory in literature. However, the other two have not been identified previously. Type 2 pattern was more common in the NFBC1966 suggesting a generational shift in BMI maturational patterns.
60 APPLIED LIFE SCIENCES↗
Measurement and QCD analysis of double-differential inclusive jet cross sections in proton-proton collisions at $\sqrt{s}$ = 13 TeV
A measurement of the inclusive jet production in proton-proton collisions at the LHC at $ \sqrt{s} $ = 13 TeV is presented. The double-differential cross sections are measured as a function of the jet transverse momentum p$_{T}$ and the absolute jet rapidity |y|. The anti-k$_{T}$ clustering algorithm is used with distance parameter of 0.4 (0.7) in a phase space region with jet p$_{T}$ from 97 GeV up to 3.1 TeV and |y| < 2.0. Data collected with the CMS detector are used, corresponding to an integrated luminosity of 36.3 fb$^{-1}$ (33.5 fb$^{-1}$). The measurement is used in a comprehensive QCD analysis at next-to-next-to-leading order, which results in significant improvement in the accuracy of the parton distributions in the proton. Simultaneously, the value of the strong coupling constant at the Z boson mass is extracted as α$_{S}$(m$_{Z}$) = 0.1170±0.0019. For the first time, these data are used in a standard model effective field theory analysis at next-to-leading order, where parton distributions and the QCD parameters are extracted simultaneously with imposed constraints on the Wilson coefficient c$_{1}$ of 4-quark contact interactions.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Mobility Gaps between Low-Income and Not Low-Income Households: A Case Study in New York State
Understanding the travel challenges faced by low-income residents has always been and continues to be one of the most important transportation equity topics. This study aims to explore the mobility gaps between low-income households (HHs) and not low-income HHs, and how the gaps vary within different socio-demographic population groups in New York State (NYS). The latest National Household Travel Survey data was used as the primary data source for the analysis. The study first employed the K-prototype clustering algorithm to categorize the HHs in NYS based on their socio-demographic attributes. Five population groups were identified based on nine different household (HH) features such as HH size, vehicle ownership, and elderly status of its members. Then, the mobility differences, measured by trip frequency, trip distance, travel time, and person miles traveled, were examined among the five population groups. Results suggest that the individuals in low-income HHs consistently took fewer trips and made shorter trips compared to their not low-income counterparts in NYS. The travel distance gaps were most obvious among white HHs with more vehicles than drivers. In addition, while the population from low-income HHs made shorter trips on average (2.7 mi shorter per trip), they experienced longer travel time than those from not low-income HHs (1.8 min longer per trip). These key findings provide a deeper understanding of the travel behavior disparities between low-income and not low-income households. The findings could also support policymakers and transportation planners in addressing the critical needs of residents in low-income households in NYS and provide inputs for designing a more equitable transportation system.
Liu, Yuandong↗
Supramolecular assembly of blue and green halide perovskites with near-unity photoluminescence
The metal-halide ionic octahedron is the optoelectronic unit for halide perovskites, and a crown ether–assisted supramolecular assembly approach can pack various ionic octahedra into tunable symmetries. In this work, we demonstrate near-unity photoluminescence quantum yield (PLQY) blue and green emission with the supramolecular assembly of hafnium (Hf) and zirconium (Zr) halide octahedral clusters. (18C6@K) 2 HfBr 6 powders showed blue emission with a near-unity PLQY (96.2%), and green emission was also achieved with (18C6@K) 2 ZrCl 4 Br 2 powders at a PLQY of 82.7%. In conclusion, these highly emissive powders feature facile low-temperature solution-based synthesis conditions and maintain high PLQY in solution-processable semiconductor inks under ambient conditions, and they were used in thin-film displays and emissive three-dimensional–printed architectures that exhibited high spatial resolution.
36 MATERIALS SCIENCE↗
A Siamese CNN + KNN-Based Classification Framework for Non-intrusive Load Monitoring
Through the development of smart grids, programs such as demand side response, have been presented as auxiliary services to the real-time operation of distributed networks. In order to provide consumers information on their energy consumption, so that a modulation in consumption is possible, non-intrusive load monitoring has been introduced as an solution to this pattern recognition problem. Non-intrusive load monitoring enables the modeling of electrical loads connected to the low-voltage system, considering only a single measurement point. Presented state-of-the-art solutions though, consider availability of data as well as representation of all possible classes of the environment. This is of course a most conservative hypothesis, since in real-life applications availability of such data is much difficult, as well as the dynamic behavior of models is implicitly evolving in time. Here, a framework that uses neural Siamese networks with k-nearest neighbor clustering is presented toward non-intrusive load monitoring. Online learning feature is implemented, which relaxes the hypothesis of data requirements as well addresses the evolving nature of load profile. k-nearest clustering allows nonlinear characteristic space modelling. Test results using synthetics and real-life data show that the solution, besides obtaining a good generalizability in the classification, also obtained results with an accuracy of 95.77%.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Microhydration of the metastable N -Protomer of 4-Aminobenzoic acid by condensation at 80 K: H/D exchange without conversion to the more stable O- protomer
4-Aminobenzoic acid (4ABA) is a model scaffold for studying solvent-mediated proton transfer. Although protonation at the carboxylic group (O-protomer) is energetically favored in the gas phase, the N-protomer, where the proton remains on the amino group, can be kinetically trapped by electrospray ionization of 4ABA in an aprotic solvent such as acetonitrile. Here we report the formation of the hydrated deuterium isotopologues of the N-protomers, RND 3 + ·(H 2 O) n=1-3 , (R=C 6 H 4 COOD), which are generated by condensing water molecules onto the bare N-protomers in a liquid nitrogen cooled, radiofrequency octopole ion trap at 80 K. The product clusters are then transferred to a 20 K cryogenic ion trap where they are tagged with weakly bound D 2 molecules. The structures of these clusters are determined by analysis of their vibrational patterns obtained by resonant IR photodissociation. The resulting patterns confirm that the metastable N-protomer configuration remains intact even when warmed by sequential condensation of water molecules. Attachment of H 2 O molecules onto the RND 3 + head group also affords the opportunity to explore the possibility of H/D exchange between the acid scaffold and the proximal water network. The spectroscopic results establish that although the RND 3 + ·(H 2 O) n=1,2 clusters are formed without H/D exchange, the n = 3 cluster exhibits about 10% H/D exchange as evidenced by the appearance of the telltale HOD bands. Furthermore, the site of exchange on the acid is determined to be the acidic OH by the emergence of the OH stretching fundamental in the -COOH motif.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
[CII] 158 um Observations of a Sample of Late-type Galaxies from the Virgo Cluster
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galaxy clusters Virgo [CII]↗
Three dimensional cluster analysis for atom probe tomography using Ripley’s K-function and machine learning
The size and structure of spatial molecular and atomic clustering can significantly impact material properties and is therefore important to accurately quantify. Ripley’s K-function (K(r)), a measure of spatial correlation, can be used to perform such quantification when the material system of interest can be represented as a marked point pattern. This work demonstrates how machine learning models based on K (r)-derived metrics can accurately estimate cluster size and intra-cluster density in simulated three dimensional (3D) point patterns containing spherical clusters of varying size; over 90% of model estimates for cluster size and intra-cluster density fall within 11% and 18% error of the true values, respectively. These K (r)-based size and density estimates are then applied to an experimental APT reconstruction to characterize MgZn clusters in a 7000 series aluminum alloy. Here we find that the estimates are more accurate, consistent, and robust to user interaction than estimates from the popular maximum separation algorithm. Using K (r) and machine learning to measure clustering is an accurate and repeatable way to quantify this important material attribute.
36 MATERIALS SCIENCE↗
High Undercooling of Ni59Nb41 Alloy in a Containerless Electrostatic Levitation Facility
Utilizing the containerless electrostatic levitation facility at NASA/MSFC, we were able to undercool the Ni59Nb41 (atomic) alloy by 210 K which was 160 degrees farther than the results of previous flight experiments. Undercoolings were clustered around 200 K during the repeated melting-freezing cycles on a single sample. Prior to this work, a metastable liquid separation had been presumed to limit the undercooling of this alloy. However, microstructural observations have revealed that undercooling was limited by crystal nucleation.
Robinson, M. B.↗