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Fuzzy data, prevalent in social sciences and other fields, capture uncertainties arising from subjective evaluations and measurement imprecision. Despite significant advancements in fuzzy statistics, a unified inferential regression-based…

Methodology · Statistics 2025-06-05 Antonio Calcagnì , Przemysław Grzegorzewski , Maciej Romaniuk

Consider the problem when $X_1,X_2,..., X_n$ are distributed on a circle following an unknown distribution $F$ on $S^1$. In this article we have consider the absolute general set-up where the density can have local features such as…

Methodology · Statistics 2016-11-26 Kinjal Basu , Debapriya Sengupta

We present a visualization tool to exhaustively search and browse through a set of large-scale machine learning datasets. Built on the top of the VizWiz dataset, our dataset browser tool has the potential to support and enable a variety of…

Machine Learning · Computer Science 2019-12-20 Nilavra Bhattacharya , Danna Gurari

To investigate the interplay between microscopic dynamics and macroscopic rheology in soft matter, we couple a stress-controlled-rheometer equipped with a Couette cell to a light scattering setup in the imaging geometry, which allows us to…

Soft Condensed Matter · Physics 2016-11-23 N. Ali , DCD. Roux , L. Cipelletti , F. Caton

Ring diagram analysis of solar oscillation power spectra obtained from MDI data is carried out to study the velocity fields in the outer part of the solar convection zone. The three dimensional power spectra are fitted to a model which has…

Astrophysics · Physics 2009-10-30 Sarbani Basu , H. M. Antia , S. C. Tripathy

We study the performance of sparse regression methods and propose new techniques to distill the governing equations of dynamical systems from data. We first look at the generic methodology of learning interpretable equation forms from data,…

Machine Learning · Computer Science 2019-03-25 Chinmay S. Kulkarni

In this work, we deal with a bivariate time series of wind speed and direction. Our observed data have peculiar features, such as informative missing values, non-reliable measures under a specific condition and interval-censored data, that…

Methodology · Statistics 2017-04-18 Gianluca Mastrantonio , Gianfranco Calise

The pressure and flow statistics of Darcy flow through a random permeable medium are expressed in a form suitable for evaluation by the method of simulated annealing. There are several attractive aspects to using simulated annealing: (i)…

Computational Engineering, Finance, and Science · Computer Science 2019-04-04 Marise J. E. Westbroek , Peter R. King , Dimitri D. Vvedensky , Ronnie L. Schwede

A box model of the inter-hemispheric Atlantic meridional overturning circulation is developed, including a variable pycnocline depth for the tropical and subtropical regions. The circulation is forced by winds over a periodic channel in the…

Atmospheric and Oceanic Physics · Physics 2012-11-07 Andrea A. Cimatoribus , Sybren S. Drijfhout , Henk A. Dijkstra

Directional data arise in various contexts such as oceanography (wave directions) and meteorology (wind directions), as well as with measurements on a periodic scale (weekdays, hours, etc.). Our contribution is to introduce a model-based…

Applications · Statistics 2013-01-09 Giovanna Jona-Lasinio , Alan Gelfand , Mattia Jona-Lasinio

The complete flow field surrounding a rotating cylinder is calculated by solving the Navier-Stokes equations using the finite difference method. The numerical simulation is performed on a transformed rectilinear grid, with axes representing…

Computational Physics · Physics 2018-10-25 Alan Hsu , Fei Liu

As machine learning systems become democratized, it becomes increasingly important to help users easily debug their models. However, current data tools are still primitive when it comes to helping users trace model performance problems all…

Databases · Computer Science 2019-01-08 Yeounoh Chung , Tim Kraska , Neoklis Polyzotis , Ki Hyun Tae , Steven Euijong Whang

Sliced inverse regression (SIR) is a pioneer tool for supervised dimension reduction. It identifies the effective dimension reduction space, the subspace of significant factors with intrinsic lower dimensionality. In this paper, we propose…

Machine Learning · Statistics 2018-06-26 Ning Zhang , Zhou Yu , Qiang Wu

The northeastern coast of the U.S. is projected to expand its offshore wind capacity from the existing 30 MW to over 22 GW in the next decade. Yet, only a few wind measurements are available in the region and none at hub height, thus…

Atmospheric and Oceanic Physics · Physics 2020-06-30 Maryam Golbazi , Cristina L. Archer

Accurate prediction of wind speed and power is vital for enhancing the efficiency of wind energy systems. Numerous solutions have been implemented to date, demonstrating their potential to improve forecasting. Among these, deep learning is…

Machine Learning · Computer Science 2024-01-17 Mulomba Mukendi Christian , Yun Seon Kim , Hyebong Choi , Jaeyoung Lee , SongHee You

Extracted event data from information systems often contain a variety of process executions making the data complex and difficult to comprehend. Unlike current research which only identifies the variability over time, we focus on other…

Software Engineering · Computer Science 2024-06-10 Ali Norouzifar , Majid Rafiei , Marcus Dees , Wil van der Aalst

Mode-based clustering methods define clusters to be the basins of attraction of the modes of a density estimate. The most common version is mean shift clus- tering which uses a gradient ascent algorithm to find the basins. Rodriguez and…

Methodology · Statistics 2018-05-14 Isabella Verdinelli , Larry Wasserman

The description of wind phenomena is frequently based on data obtained from anemometers, which usually report the wind speed and direction only in a horizontal plane. Such measurements are commonly used either to develop wind generation…

Data Analysis, Statistics and Probability · Physics 2016-03-08 P. A. Sanchez , M. Robles , O. A. Jaramillo

Nor'easters frequently impact the North American East Coast, bringing hazardous precipitation, winds, and coastal flooding. Accurate simulation of their pressure and wind fields is essential for forecasting, risk assessment, and…

Atmospheric and Oceanic Physics · Physics 2025-09-12 Seyedeh Fatemeh Mirfakhar , Reda Snaiki , Frank Lombardo

Today, huge amounts of data are being collected with spatial and temporal components from sources such as meteorological, satellite imagery etc. Efficient visualisation as well as discovery of useful knowledge from these datasets is…

Databases · Computer Science 2017-03-31 Nhien-An Le-Khac , Martin Bue , Michael Whelan , Tahar Kechadi
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