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A natural approach to analyze interaction data of form "what-connects-to-what-when" is to create a time-series (or rather a sequence) of graphs through temporal discretization (bandwidth selection) and spatial discretization (vertex…

Machine Learning · Statistics 2015-01-13 Nam H. Lee , Carey Priebe , Youngser Park , I-Jeng Wang , Michael Rosen

Solar active regions (ARs) that produce strong flares and coronal mass ejections (CMEs) are known to have a relatively high non-potentiality and are characterized by delta-sunspots and sheared magnetic structures. In this study, we conduct…

Solar and Stellar Astrophysics · Physics 2017-11-29 Shin Toriumi , Shinsuke Takasao

Systematic studies of the rotation rate of sunspot groups using white-light images yield controversial results on the variations of the rotation rate: sunspot groups were found to either accelerate or decelerate systematically. This…

Solar and Stellar Astrophysics · Physics 2023-01-18 Alexander S. Kutsenko , Valentina I. Abramenko , Daria V. Litvishko

Unstable states of the solar coronal magnetic field structure result in various flare behaviors. In this study, we compared the confined and eruptive flares that occurred under similar magnetic circumstances in the active region 12673, on…

Solar and Stellar Astrophysics · Physics 2025-03-24 Kouhei Teraoka , Daiki Yamasaki , Yusuke Kawabata , Shinsuke Imada , Toshifumi Shimizu

We consider the problem of clustering functional data according to their covariance structure. We contribute a soft clustering methodology based on the Wasserstein-Procrustes distance, where the in-between cluster variability is penalised…

Methodology · Statistics 2022-12-29 V. Masarotto , G. Masarotto

The two-point correlation function has been the standard statistic for quantifying how galaxies are clustered. The statistic uses the positions of galaxies, but not their properties. Clustering as a function of galaxy property, be it type,…

Astrophysics · Physics 2007-05-23 Ravi K. Sheth , Andrew J. Connolly , Ramin Skibba

Clustering on the data with multiple aspects, such as multi-view or multi-type relational data, has become popular in recent years due to their wide applicability. The approach using manifold learning with the Non-negative Matrix…

Machine Learning · Computer Science 2020-09-08 Khanh Luong , Richi Nayak

We study the predictive capabilities of magnetic feature properties (MF) generated by Solar Monitor Active Region Tracker (SMART) for solar flare forecasting from two datasets: the full dataset of SMART detections from 1996 to 2010 that has…

Solar and Stellar Astrophysics · Physics 2018-12-07 Katarina Domijan , D. Shaun Bloomfield , Francois Pitie

The colonisation of a soft passive material by motile cells such as bacteria is common in biology. The resulting colonies of the invading cells are often observed to exhibit intricate patterns whose morphology and dynamics can depend on a…

Soft Condensed Matter · Physics 2021-01-12 Mohammad Imaran , Mandar Inamdar , Ranganathan Prabhakar , Raghunath Chelakkot

There are various cluster validity indices used for evaluating clustering results. One of the main objectives of using these indices is to seek the optimal unknown number of clusters. Some indices work well for clusters with different…

Machine Learning · Statistics 2024-01-09 Nathakhun Wiroonsri

This paper provides a theoretical explanation on the clustering aspect of nonnegative matrix factorization (NMF). We prove that even without imposing orthogonality nor sparsity constraint on the basis and/or coefficient matrix, NMF still…

Machine Learning · Computer Science 2010-06-15 Andri Mirzal , Masashi Furukawa

Clustering is an essential technique for network analysis, with applications in a diverse range of fields. Although spectral clustering is a popular and effective method, it fails to consider higher-order structure and can perform poorly on…

Social and Information Networks · Computer Science 2020-09-14 William George Underwood , Andrew Elliott , Mihai Cucuringu

How does the clustering of galaxies depend on their inner properties like morphological type and luminosity? We address this question in the mathematical framework of marked point processes and clarify the notion of luminosity and…

Astrophysics · Physics 2009-10-31 Claus Beisbart , Martin Kerscher

Subspace clustering is a growing field of unsupervised learning that has gained much popularity in the computer vision community. Applications can be found in areas such as motion segmentation and face clustering. It assumes that data…

Machine Learning · Statistics 2019-11-12 Hankui Peng , Nicos G. Pavlidis

Spatial cluster analysis, the detection of localized patterns of similarity in geospatial data, has a wide-range of applications for scientific discovery and practical decision making. One way to detect spatial clusters is by using local…

Human-Computer Interaction · Computer Science 2024-04-10 Lee Mason , Blánaid Hicks , Jonas S. Almeida

We analyse a catalogue of simulated clusters within the theoretical framework of the Spherical Collapse Model (SCM), and demonstrate that the relation between the infall velocity of member galaxies and the cluster matter overdensity can be…

Cosmology and Nongalactic Astrophysics · Physics 2015-03-13 Guido Cupani , Marino Mezzetti , Fabio Mardirossian

While sunspots are easily observed at the solar surface, determining their subsurface structure is not trivial. There are two main hypotheses for the subsurface structure of sunspots: the monolithic model and the cluster model. Local…

We consider the coordinate-space matrix elements that correspond to fixed-angle scattering amplitudes involving partons and Wilson lines in coordinate space, working in Feynman gauge. In coordinate space, both collinear and short-distance…

High Energy Physics - Phenomenology · Physics 2015-05-04 Ozan Erdoğan , George Sterman

Spectral clustering requires the time-consuming decomposition of the Laplacian matrix of the similarity graph, thus limiting its applicability to large datasets. To improve the efficiency of spectral clustering, a top-down approach was…

Machine Learning · Computer Science 2024-12-19 Zhichang Xu , Zhiguo Long , Hua Meng

We use observations of line-of-sight magnetograms from Helioseismic and Magnetic Imager (HMI) on board of Solar Dynamics Observatory (SDO) to investigate polarity separation, magnetic flux, flux emergence rate, twist and tilt of solar…

Solar and Stellar Astrophysics · Physics 2019-02-20 A. S. Kutsenko , V. I. Abramenko , A. A. Pevtsov
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