The stable functionality of networked systems is a hallmark of their natural ability to coordinate between their multiple interacting components. Yet, real world networks often appear random and highly irregular, rais...
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Using the Subaru/FOCAS IFU capability, we examine the spatially resolved relationships between gas-phase metallicity, stellar mass, and star-formation rate surface densities (Σ★ and ΣSFR, respectively) in extremely...
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The nodal-line semimetals have attracted immense interest due to the unique electronic structures such as the linear dispersion and the vanishing density of states as the Fermi energy approaching the nodes. Here, we r...
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Data science and technology offer transformative tools and methods to science. This review article highlights latest development and progress in the interdisciplinary field of data-driven plasma science (DDPS). A larg...
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The interpretation of observations of cooling neutron star crusts in quasi-persistent X-ray transients is affected by predictions of the strength of neutrino cooling via crust Urca processes. The strength of crust Urc...
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Data mining is routinely used to organize ensembles of short temporal observations so as to reconstruct useful, low-dimensional realizations of an underlying dynamical system. In this paper, we use manifold learning t...
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We study the ubiquitous super-resolution problem, in which one aims at localizing positive point sources in an image, blurred by the point spread function of the imaging device. To recover the point sources, we propos...
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This paper develops coding techniques to reduce the running time of distributed learning tasks. It characterizes the fundamental tradeoff to compute gradients (and more generally vector summations) in terms of three p...
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In this study, the retention index data of 146 compounds that are found in coal and petroleum-derived liquid fuels were grouped using the K-means clustering method, and the similarities between each cluster were analy...
In this study, the retention index data of 146 compounds that are found in coal and petroleum-derived liquid fuels were grouped using the K-means clustering method, and the similarities between each cluster were analyzed. The psycho-chemical properties of each compound in the cluster were identified and compared with other clusters. Each compound's retention index is grouped based on the similarity between the column polarity and heating rate of one compound to another. Based on the results of tests carried out on nine differentk values, it is known that the grouping with the value of k = 3 is the best determined from the obtained silhouette score = 0.568, where this score is higher than the score obtained on the other k values. The results of clustering with k = 3 obtained three clusters, namely cluster C1, cluster C2, and cluster C3. Cluster C1 and cluster C2 consist of chemical compounds that have a relatively low carbon number and molecular mass, but in cluster C2 the molecular mass of the compound is lower than in cluster C1. In contrast, the C3 cluster consists of chemical compounds that have a relatively high carbon number and molecular mass.
MSC Codes 94A15, 62B10We analyze the problem of estimating a signal from multiple measurements on a group action channel that linearly transforms a signal by a random group action followed by a fixed projection and ad...
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