Topological descriptors of spatial coherence in a convective boundary layerThe interaction between a turbulent convective boundary layer (CBL) and the underlying land surface is an important research problem in the geosciences. In order to model this interaction adequately,…José Licón-Saláiz, Cedrick Ansorge·Jun 7, 2019SaveLearn
Revision of ISO 19229 to support the certification of calibration gases for purityThe second edition of ISO 19229 expands the guidance in its predecessor in two ways. Firstly, it provides more support and examples describing possible experimental approaches for purity analysis. A…Adriaan M. H. van der Veen, Gerard Nieuwenkamp·Jun 4, 2019SaveLearn
Changes in long-term properties of the Danube river level and flow induced by dammingIn this paper we assessed changes in scaling properties of the river Danube level and flow data, associated with building of Djerdap/Iron Gates hydrological power plants positioned on the border of…Djordje Stratimirovic, Ilija Batas-Bjelic, Vladimir Djurdjevic et al.·May 30, 2019SaveLearn
Dashboard Task Monitor for Managing ATLAS User Analysis on the GridThe organization of the distributed user analysis on the Worldwide LHC Computing Grid (WLCG) infrastructure is one of the most challenging tasks among the computing activities at the Large Hadron…L Sargsyan, J Andreeva, M Jha et al.·May 30, 2019SaveLearn
Practical Statistics for Particle PhysicsThis is the write-up of a set of lectures given at the Asia Europe Pacific School of High Energy Physics in Quy Nhon, Vietnam in September 2018, to an audience of PhD students in all branches of…Roger John Barlow·May 29, 2019SaveLearn
From periodic sampling to irregular sampling through PNS (Periodic Nonuniform Sampling)Resampling is an operation costly in calculation time and accuracy. It regularizes irregular sampling, replacing N data by N periodic estimations. This stage can be suppressed, using formulas built…Bernard Lacaze·May 27, 2019SaveLearn
A Predictive Model for Steady-State Multiphase Pipe Flow: Machine Learning on Lab DataEngineering simulators used for steady-state multiphase pipe flows are commonly utilized to predict pressure drop. Such simulators are typically based on either empirical correlations or…Evgenii Kanin, Andrei Osiptsov, Albert Vainshtein et al.·May 23, 2019SaveLearn
Shades of Dark Uncertainty and Consensus Value for the Newtonian Constant of GravitationThe Newtonian constant of gravitation, G, stands out in the landscape of the most common fundamental constants owing to its surprisingly large relative uncertainty, which is attributable mostly to…Christos Merkatas, Blaza Toman, Antonio Possolo et al.·May 23, 2019SaveLearn
Spin determination from the in-plane angular correlation analysis for various coordinate systemsIn a reaction to excite the resonant state followed by the sequential cluster-decay, the in-plane angular correlation method is usually applied to determine the spin of the mother nucleus. However,…Biao Yang, Yan-Lin Ye, Jian-Ling Lou et al.·May 17, 2019SaveLearn
The partial visibility curve of the Feigenbaum cascade to chaosA family of classical mathematical problems considers the visibility properties of geometric figures in the plane, e.g. curves or polygons. In particular, the domination problem tries to find…Juan Carlos Nuño, Francisco J. Muñoz·May 17, 2019SaveLearn
Data Processing Protocol for Regression of Geothermal Times Series with Uneven IntervalsRegression of data generated in simulations or experiments has important implications in sensitivity studies, uncertainty analysis, and prediction accuracy. Depending on the nature of the physical…Palash Panja, Pranay Asai, Raul Velasco et al.·May 16, 2019SaveLearn
On the Automatic Parameter Selection for Permutation EntropyPermutation Entropy (PE) has been shown to be a useful tool for time series analysis due to its low computational cost and noise robustness. This has drawn for its successful application in many…Audun Myers, Firas Khasawneh·May 15, 2019SaveLearn
Visualising high-dimensional state spaces with "Tuple Plots"Complex systems are described with high-dimensional data that is hard to visualise. Inselberg's parallel coordinates are one representation technique for visualising high-dimensional data. Here…Susan Stepney·May 12, 2019SaveLearn
A class of randomized Subset Selection Methods for large complex networksMost of the real world complex networks such as the Internet, World Wide Web and collaboration networks are huge; and to infer their structure and dynamics one requires handling large connectivity…Amit Reza, Richa Tripathi·May 11, 2019SaveLearn
Delay Parameter Selection in Permutation Entropy Using Topological Data AnalysisPermutation Entropy (PE) is a powerful tool for quantifying the complexity of a signal which includes measuring the regularity of a time series. Additionally, outside of entropy and information…Audun D. Myers, Max M. Chumley, Firas A. Khasawneh·May 10, 2019SaveLearn
A new method to determine multi-angular reflectance factor from lightweight multispectral cameras with sky sensor in a target-less workflow applicable to UAVA new physically based method to estimate hemispheric-directional reflectance factor (HDRF) from lightweight multispectral cameras that have a downwelling irradiance sensor is presented. It combines…Klaus Schneider-Zapp, Manuel Cubero-Castan, Dai Shi et al.·May 8, 2019SaveLearn
Parameter-free quantification of stochastic and chaotic signalsRecurrence entropy ( S) is a novel time series complexity quantifier based on recurrence microstates. Here we show that max( S) is a parameter-free quantifier of time…Sergio Roberto Lopes, Thiago de Lima Prado, Gilberto Corso et al.·May 6, 2019SaveLearn
Estimating the Mutual Information between two Discrete, Asymmetric Variables with Limited SamplesDetermining the strength of non-linear statistical dependencies between two variables is a crucial matter in many research fields. The established measure for quantifying such relations is the mutual…Damián G. Hernández, Inés Samengo·May 6, 2019SaveLearn
Comment on "Rényi entropy yields artifficial biases not in the data and incorrect updating due to the infinite-size data"In their recent paper [Phys. Rev. E 99 (2019) 032134], T. Oikinomou and B. Bagci have argued that Rényi entropy is ill-suited for inference purposes because it is not consistent with the Shore…Petr Jizba, Jan Korbel·May 1, 2019SaveLearn
Wavelet based detection of scaling behaviour in noisy experimental dataThe detection of power-laws in real data is a demanding task for several reasons. The two, more frequently met, being: (i) real data possess noise which affects significantly the power-law tails and…Yiannis F. Contoyiannis, Stelios Potirakis, Fotios K. Diakonos·Apr 27, 2019SaveLearn
Change detection in SAR time-series based on the coefficient of variationThis paper discusses change detection in SAR time-series. Firstly, several statistical properties of the coefficient of variation highlight its pertinence for change detection. Then several criteria…Elise Colin Koeniguer, Jean-Marie Nicolas·Apr 25, 2019SaveLearn
Testing statistical laws in complex systemsThe availability of large datasets requires an improved view on statistical laws in complex systems, such as Zipf's law of word frequencies, the Gutenberg-Richter law of earthquake magnitudes, or…Martin Gerlach, Eduardo G. Altmann·Apr 25, 2019SaveLearn
On the methodologies for the assessment of the impact of parameters in acoustophoretic separation devicesIn this communication I reconcile the kinematic method illustrated by some authors~yang2018,vitali2018 in studying the impact of system and suspension parameters on acoustophoretic separations…Fabio Garofalo·Apr 20, 2019SaveLearn
The peculiar statistical mechanics of Optimal Learning MachinesOptimal Learning Machines (OLM) are systems that extract maximally informative representation of the environment they are in contact with, or of the data they are presented. It has recently been…Matteo Marsili·Apr 19, 2019SaveLearn
FPGA-accelerated machine learning inference as a service for particle physics computingNew heterogeneous computing paradigms on dedicated hardware with increased parallelization, such as Field Programmable Gate Arrays (FPGAs), offer exciting solutions with large potential gains. The…Javier Duarte, Philip Harris, Scott Hauck et al.·Apr 18, 2019SaveLearn