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At least 163 records · Page 9

Unsupervised Power System Event Detection and Classification Using Unlabeled PMU Data

This paper proposes a novel data-driven power system event detection and classification method based on 5TB of actual PMU measurements collected from the US western interconnect. Firstly, a set of comprehensive power quality rules are proposed to pre-filter the raw data and extract the regions of interest (ROI). Six distinct event categories are defined and corresponding patterns are chosen as references. Meanwhile, detailed characteristics of patterns are summarized to enhance our understanding of the actual events. Then, the time-independent feature vectors are generated by extracting the statistical, temporal, and spectral features from the raw time-series data. Furthermore, an ensemble model is proposed to cluster the events by combining multiple K-means clustering models using a voting strategy. Besides, both system-level and PMU-level clustering models are developed. The accuracy and robustness of the event detection method are further improved through interactive evaluation of the two-level clustering results. This paper summarizes the actual characteristics of each event category and provides a reliable basis for accurate label generation. The experiments demonstrate the effectiveness of the proposed event detection and classification method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Unsupervised Power System Event Detection and Classification Using Unlabeled PMU Data

This paper proposes a novel data-driven power system event detection and classification method based on 5TB of actual PMU measurements collected from the US western interconnect. Firstly, a set of comprehensive power quality rules are proposed to pre-filter the raw data and extract the regions of interest (ROI). Six distinct event categories are defined and corresponding patterns are chosen as references. Meanwhile, detailed characteristics of patterns are summarized to enhance our understanding of the actual events. Then, the time-independent feature vectors are generated by extracting the statistical, temporal, and spectral features from the raw time-series data. Furthermore, an ensemble model is proposed to cluster the events by combining multiple K-means clustering models using a voting strategy. Besides, both system-level and PMU-level clustering models are developed. The accuracy and robustness of the event detection method are further improved through interactive evaluation of the two-level clustering results. This paper summarizes the actual characteristics of each event category and provides a reliable basis for accurate label generation. The experiments demonstrate the effectiveness of the proposed event detection and classification method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Classifying biophysical subpopulations of insulin secretory granules using quantitative whole-cell structure analysis

Pancreatic beta cells contain insulin secretory granules (ISGs), organelles where proinsulin is converted into insulin. As ISGs mature, they undergo extensive biophysical remodeling, producing a spectrum of subpopulations with heterogeneous molecular and spatial characteristics. However, systematic methods to define ISG subpopulations remain underdeveloped. To address this gap in knowledge, we employed soft X-ray tomography (SXT), which can quantitatively measure the biochemical density of ISGs within whole beta cells. Using unsupervised clustering, we classified subpopulations based on molecular density, size, and spatial positioning. Across different insulin secretory stimuli, we observed shifts toward mature and releasable subtypes, demonstrating that exogenous signals can dynamically remodel ISG subpopulation distributions. We extended this methodology to primary beta cells characterized using volume electron microscopy (vEM). Integrating subpopulations from SXT and vEM uncovered insights inaccessible by a single method in isolation. This strategy establishes a framework for defining therapeutic approaches aimed at enriching physiologically beneficial ISG subpopulations.

dense-core granules↗

Investigation of the isoscalar monopole response in the proton-rich nucleus 14 O

Deuteron inelastic scattering on 14 O was measured in inverse kinematics using an active-target time projection chamber and a magnetic spectrograph. The experimental technique enabled precise measurements of deuteron recoiling particles in coincidence with beam-like fragments detected in the spectrograph focal plane. The double differential cross section was reconstructed for scattering angles of 3–6 degrees and excitation energies up to 26 MeV. The monopole strength distribution was obtained from the data using a multipole decomposition analysis. The results were compared to quasiparticle random-phase approximation (QRPA) and generator coordinate method (GCM) calculations. The QRPA calculation accurately describes experimental data in the energy range of 13 to 26 MeV. GCM calculations assuming a 12 C (g . s .) + p + p cluster configuration were used to determine the 0 + strength in 14 O below 13 MeV. The monopole transition strength of these cluster states provides a good description of the experimental distribution in the 9–11 MeV region, while the 0$^{+}_{2}$ state accounts for only a small fraction of the experimental strength around 6 MeV.

Active target↗

Structural Changes during the Growth of Atomically Precise Metal Oxido Nanoclusters from Combined Pair Distribution Function and Small-Angle X-ray Scattering Analysis

The combination of in situ pair distribution function (PDF) analysis and small-angle X-ray scattering (SAXS) enables analysis of the formation mechanism of metal oxido nanoclusters and cluster–solvent interactions as they take place. Herein, we demonstrate the method for the formation of clusters with a [Bi 38 O 45 ] core. Upon dissolution of crystalline [Bi 6 O 5 (OH) 3 (NO 3 ) 5 ]∙3 H 2 O in DMSO, an intermediate rapidly forms, which slowly grows to stable [Bi 38 O 45 ] clusters. To identify the intermediate, we developed an automated modeling method, where smaller [Bi x O y ] structures based on the [Bi 38 O 45 ] framework are tested against the data. [Bi 22 O 26 ] was identified as the main intermediate species, illustrating how combined PDF and SAXS analysis is a powerful tool to gain insight into nucleation on an atomic scale. PDF also provides information on the interaction between nanoclusters and solvent, which is shown to depend on the nature of the ligands on the cluster surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Constraining IGM enrichment and metallicity with the C iv forest correlation function

ABSTRACT The distribution and abundance of metals in the diffuse intergalactic medium (IGM) have implications for galaxy formation and evolution models, and has been argued to be sensitive to the Universe’s reionization history. However, reduced sensitivity in the near-IR implies that probing IGM metals at z > 4 is currently out of reach with the traditional method of detecting individual absorbers. We present a new technique based on clustering analysis that enables the detection of these weak IGM absorbers. We investigate the two-point correlation function (2PCF) of the ${\rm C\, {\small IV}}$ forest as a probe of IGM metallicity and enrichment topology by simulating the z = 4.5 IGM with models of inhomogeneous metal distributions. The 2PCF of the ${\rm C\, {\small IV}}$ forest demonstrates a clear peak at a characteristic separation corresponding to the doublet separation of the ${\rm C\, {\small IV}}$ line.The peak amplitude scales quadratically with metallicity, while enrichment topology affects both the shape and amplitude of the 2PCF. For models consistent with the distribution of metals at z ∼ 3, we find that we can constrain [C/H] to within 0.2 dex, log$\, M_{\rm {min}}$ to within 0.4 dex, and R to within 15 per cent. We show that CGM absorbers can be reliably identified and masked, thus recovering the underlying IGM signal. The auto-correlation of the metal-line forest presents a compelling avenue to constrain the IGM metallicity and enrichment topology with high precision at z > 4, thereby pushing such measurements into the Epoch of Reionization.

79 ASTRONOMY AND ASTROPHYSICS↗

Extended CO(7-6) emission from warm gas in Orion

Results of a search for extended CO(7-6) line emission in the Orion A molecular cloud using the University of Texas submillimeter laser heterodyne receiver are presented. The large-scale distribution of quiescent CO(7-6) emission is mapped along a cut across the Trapezium cluster extending more than 13 arcmin (nearly 2 pc) in R.A. The receiver, observing method, and calibration techniques are described, and the CO(7-6) spectra and maps are presented. The physical parameters and energetics of the molecular gas are discussed. The findings are compared with observations of other high-luminosity star-forming regions.

Howe, J. E.↗

A direct method for the solution of unsteady two-dimensional incompressible Navier-Stokes equations

The unsteady incompressible Navier-Stokes equations are formulated in terms of vorticity and stream function in generalized curvilinear orthogonal coordinates to facilitiate analysis of flow configurations with general geometries. The numerical method developed solves the conservative form of the transport equation using the alternating-direction implicit method, whereas the stream-function equation is solved by direct block Gaussian elimination. The method is applied to a model problem of flow over a back-step in a doubly infinite channel, using clustered conformal coordinates. One-dimensional stretching functions, dependent on the Reynolds number and the asymptotic behavior of the flow, are used to provide suitable grid distribution in the separation and reattachment regions, as well as in the inflow and outflow regions. The optimum grid distribution selected attempts to honor the multiple length scales of the separated-flow model problem. The asymptotic behavior of the finite-differenced transport equation near infinity is examined and the numerical method is carefully developed so as to lead to spatially second-order accurate wiggle-free solutions, i.e., with minimum dispersive error. Results have been obtained in the entire laminar range for the backstep channel and are in good agreement with the available experimental data for this flow problem.

Ghia, K. N.↗

Mapping causal patterns in crystalline solids

The evolution of the atomic structures of the combinatorial library of Sm-substituted thin film BiFeO 3 along the phase transition boundary from the ferroelectric rhombohedral phase to the non-ferroelectric orthorhombic phase is explored using scanning transmission electron microscopy. Localized properties, including polarization, lattice parameter, and chemical composition, are parameterized from atomic-scale imaging, and their causal relationships are reconstructed using a linear non-Gaussian acyclic model. This approach is further extended to explore the spatial variability of the causal coupling using the sliding window transform method, which revealed that new causal relationships emerged at both the expected locations, such as domain walls and interfaces, and at additional regions forming clusters in the vicinity of the walls or spatially distributed features. While the exact physical origins of these relationships are unclear, they likely represent nanophase-separated regions in the morphotropic phase boundaries. Overall, we posit that an in-depth understanding of complex disordered materials away from thermodynamic equilibrium necessitates understanding not only the generative processes that can lead to observed microscopic states but also the causal links between multiple interacting subsystems.

Causal inference↗

Testing the Archivas Cluster (Arc) for Ozone Monitoring Instrument (OMI) Scientific Data Storage

The Ozone Monitoring Instrument (OMI) launched on NASA's Aura Spacecraft, the third of the major platforms of the EOS program on July 15,2004. In addition to the long term archive and distribution of the data from OM1 through the Goddard Earth Science Distributed Active Archive Center (GESDAAC), we are evaluating other archive mechanisms that can archive the data in a more immediately available method where it can be used for futher data production and analysis. In 2004, Archivas, Inc. was selected by NASA s Small Business Innovative Research (SBIR) program for the development of their Archivas Cluster (ArC) product. Arc is an online disk based system utilizing self-management and automation on a Linux cluster. Its goal is to produce a low cost solution coupled with the ease of management. The OM1 project is an application partner of the SBIR program, and has deployed a small cluster (5TB) based on the beta Archwas software. We performed extensive testing of the unit using production OM1 data since launch. In 2005, Archivas, Inc. was funded in SBIR Phase II for further development, which will include testing scalability with the deployment of a larger (35TB) cluster at Goddard. We plan to include Arc in the OM1 Team Leader Computing Facility (TLCF) hosting OM1 data for direct access and analysis by the OMI Science Team. This presentation will include a brief technical description of the Archivas Cluster, a summary of the SBIR Phase I beta testing results, and an overview of the OMI ground data processing architecture including its interaction with the Phase II Archivas Cluster and hosting of OMI data for the scientists.

Tilmes, Curt↗

Dark Energy Survey Year 3 results: redshift calibration of the weak lensing source galaxies

ABSTRACT Determining the distribution of redshifts of galaxies observed by wide-field photometric experiments like the Dark Energy Survey (DES) is an essential component to mapping the matter density field with gravitational lensing. In this work we describe the methods used to assign individual weak lensing source galaxies from the DES Year 3 Weak Lensing Source Catalogue to four tomographic bins and to estimate the redshift distributions in these bins. As the first application of these methods to data, we validate that the assumptions made apply to the DES Y3 weak lensing source galaxies and develop a full treatment of systematic uncertainties. Our method consists of combining information from three independent likelihood functions: self-organizing map p(z) (sompz), a method for constraining redshifts from galaxy photometry; clustering redshifts (WZ), constraints on redshifts from cross-correlations of galaxy density functions; and shear ratios (SRs), which provide constraints on redshifts from the ratios of the galaxy-shear correlation functions at small scales. Finally, we describe how these independent probes are combined to yield an ensemble of redshift distributions encapsulating our full uncertainty. We calibrate redshifts with combined effective uncertainties of σ〈z〉 ∼ 0.01 on the mean redshift in each tomographic bin.

79 ASTRONOMY AND ASTROPHYSICS↗

The CLASSY clustering algorithm: Description, evaluation, and comparison with the iterative self-organizing clustering system (ISOCLS)

A clustering method, CLASSY, was developed, which alternates maximum likelihood iteration with a procedure for splitting, combining, and eliminating the resulting statistics. The method maximizes the fit of a mixture of normal distributions to the observed first through fourth central moments of the data and produces an estimate of the proportions, means, and covariances in this mixture. The mathematical model which is the basic for CLASSY and the actual operation of the algorithm is described. Data comparing the performances of CLASSY and ISOCLS on simulated and actual LACIE data are presented.

Lennington, R. K.↗

Detecting low-mass perturbers in cluster lenses using curved arc bases

ABSTRACT Strong gravitationally lensed arcs produced by galaxy clusters have been observationally detected for several decades now. These strong lensing constraints provided high-fidelity mass models for cluster lenses that include substructure down to $10^{9{-}10}\, \mathrm{M}_\odot$. Optimizing lens models, where the cluster mass distribution is modelled by a smooth component and subhaloes associated with the locations of individual cluster galaxies, has enabled deriving the subhalo mass function, providing important constraints on the nature and granularity of dark matter. In this work, we explore and present a novel method to detect and measure individual perturbers (subhaloes, line-of-sight haloes, and wandering supermassive black holes) by exploiting their proximity to highly distorted lensed arcs in galaxy clusters, and by modelling the local lensing distortions with curved arc bases. This method offers the possibility of detecting individual low-mass perturber subhaloes in clusters and haloes along the line of sight down to a mass resolution of $10^8\, \mathrm{M}_\odot$. We quantify our sensitivity to low-mass perturbers ($M\sim 10^{7{-}9}\, \mathrm{M}_\odot$) in clusters (M ∼ 1014–15 M⊙), by creating realistic mock data. Using three lensed images of a background galaxy in the cluster SMACS J0723, taken by JWST, we study the retrieval of the properties of potential perturbers with masses $M=10^{7{-}9}\, \mathrm{M}_\odot$. From the derived posterior probability distributions for the perturber, we constrain its concentration, redshift, and ellipticity. By allowing us to probe lower mass substructures, the use of curved arc bases can lead to powerful constraints on the nature of dark matter as discrimination between dark matter models appears on smaller scales.

Astronomy & Astrophysics↗

Aerosol Models for the CALIPSO Lidar Inversion Algorithms

We use measurements and models to develop aerosol models for use in the inversion algorithms for the Cloud Aerosol Lidar and Imager Pathfinder Spaceborne Observations (CALIPSO). Radiance measurements and inversions of the AErosol RObotic NETwork (AERONET1, 2) are used to group global atmospheric aerosols using optical and microphysical parameters. This study uses more than 105 records of radiance measurements, aerosol size distributions, and complex refractive indices to generate the optical properties of the aerosol at more 200 sites worldwide. These properties together with the radiance measurements are then classified using classical clustering methods to group the sites according to the type of aerosol with the greatest frequency of occurrence at each site. Six significant clusters are identified: desert dust, biomass burning, urban industrial pollution, rural background, marine, and dirty pollution. Three of these are used in the CALIPSO aerosol models to characterize desert dust, biomass burning, and polluted continental aerosols. The CALIPSO aerosol model also uses the coarse mode of desert dust and the fine mode of biomass burning to build a polluted dust model. For marine aerosol, the CALIPSO aerosol model uses measurements from the SEAS experiment 3. In addition to categorizing the aerosol types, the cluster analysis provides all the column optical and microphysical properties for each cluster.

Omar, Ali H.↗

Determination of the Cosmic Distance Scale from Sunyaev-Zel'dovich Effect and Chandra X-ray Measurements of High Redshift Galaxy Clusters

We determine the distance to 38 clusters of galaxies in the redshift range 0.14 less than or equal to z less than or equal to 0.89 using X-ray data from Chandra and Sunyaev-Zeldovich Effect data from the Owens Valley Radio Observatory and the Berkeley-Illinois-Maryland Association interferometric arrays. The cluster plasma and dark matter distributions are analyzed using a hydrostatic equilibrium model that accounts for radial variations in density, temperature and abundance, and, the statistical and systematic errors of this method are quantified. The analysis is performed via a Markov chain Monte Carlo technique that provides simultaneous estimation of all model parameters. W

Bonamente, Massimiliano↗

Synthesis of a laterally displaced cluster feed for a reflector antenna with application to multiple beams and contoured patterns

Two methods are described for efficiently synthesizing the excitation coefficients of a laterally displaced cluster feed in a reflector antenna subject to beam distortion. Applications are presented for rotationally symmetric paraboloids excited by an equilateral triangular array of feed elements. The basic cluster is a central element surrounded by a hexagonal ring. The first method - termed the sequential current method - determines a set of excitation coefficients which minimizes the phase distortion in the 'effective' aperture distribution of the reflector. The second method - termed the gradient optimization method - is such that the distortion in the secondary power pattern is directly minimized in a min-L2 form by a gradient optimization algorithm regarded as a systematic computer iteration procedure. Application to the synthesis of contour patterns is included.

Galindo-Israel, V.↗

An interactive Barnes objective map analysis scheme for use with satellite and conventional data

The Barnes (1973) objective map analysis scheme is employed to develop an interactive analysis package for assessing the impact of satellite-derived data on analyses of conventional meteorological data sets. The method permits modification of the values of input parameters in the objective analysis within objectively determined, internally set limits. The effects of the manipulations are rapidly displayed, and methods are included for assimilating the spatially clustered characteristics of satellite data and the various horizontal resolutions of the data types. Data sets from the SESAME rawinsonde wind data with uniform spatial distribution, with the same data set plus satellite cloud motion data, and a data set from the atmospheric sounder radiometer on the GOES satellite were analyzed as examples. The scheme is demonstrated to recover details after two iterations through the data.

Koch, S. E.↗

Dust extinction and molecular gas in the dark cloud IC 5146

In this paper we describe a powerful method for mapping the distribution of dust through a molecular cloud using data obtained in large-scale, multiwavelength, infrared imaging surveys. This method combines direct measurements of near-infrared color excess and certain techniques of star counting to derive mean extinctions and map the dust column density distribution through a cloud at higher angular resolutions and greater optical depths than those achieved previously by optical star counting. We report the initial results of the application of this method to a dark cloud complex near the cluster IC 5146, where we have performed coordinated, near-infrared, JHK imaging and (13)CO, C(18)O, and CS millimeter-wave, molecular-line surveys of a large portion of the complex. More than 4000 stars were detected in our JHK survey of the cloud. Of these, all but about a dozen appear to be field stars not associated with the cloud. Star count maps at J band show a striking and detailed anticorrelation between the surface density of J-band sources and CO and CS molecular-line emission. We used the (H-K) colors and positions of nearly 1300 sources to directly measure and map the extinction and thus trace the dust column density through the cloud at an effective angular resolution of 1 min .5. We report an interesting correlation between the measured dispersion in our extinction determinations and the extinction. Modeling this relation indicates that effects of small-scale cloud structure dominate the uncertainties in our measurements. Moreover, we demonstrate that such observations can be used to place constraints on the nature of the spatial distribution of extinction on scales smaller than our resolution. In particular, we show that models in which the dust is distributed uniformly or in discrete high-extinction clumps on scales smaller than (1 min .5) are inconsistent with the observations. We have derived extinctions at the same positions and at the same angular resolution (1 min .7) as our molecular-line observations. This enabled a direct comparison of (13)CO, C(18)O, and CS integrated intensities and column densities with A(sub V) for more than 500 positions in the cloud, corresponding to a range in A(sub V) between 0 to 32 mag of extinction. We found the integrated intensities of (13)CO, C(18)O, and CS to be roughly linearly correlated with extinction over different ranges of extinction. However, for all three molecules we find the scatter in the observed relations to be larger than can be accounted for by instrumental error, suggesting that there are large intrinsic variations in the abundances or excitation of the molecules through the cloud. Mean abundances for all the molecules relative to hydrogen were directly derived from the data. The ratio of (13)CO to C(18)O abundances was found to be significantly higher than the terrestrial ratio in regions where extinction is less than 10 mag. In the same region, the dispersion in the abundance ratio is also found to be very large, suggesting that the abundances of one or both molecules are very unstable even at relatively large cloud optical depths. Beyond 10 mag of extinction the abundances of both species appear very stable with their ratio close to the terrestrial value.

Lada, Charles J.↗