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In this paper, we describe a soil-fluid-structure interaction model that combines soil mechanics (saturated sediments), fluid mechanics (seawater or air), and solid mechanics (structures). The formulation combines the Material Point Method,…

Numerical Analysis · Mathematics 2022-11-24 Quoc Anh Tran , Gustav Grimstad , Seyed Ali Ghoreishian Amiri

Testing software is often costly due to the need of mass-producing test cases and providing a test oracle for it. This is often referred to as the oracle problem. One method that has been proposed in order to alleviate the oracle problem is…

Machine Learning · Computer Science 2020-02-19 Adrian Wildandyawan , Yasuharu Nishi

We study property testing in directed graphs in the bounded degree model, where we assume that an algorithm may only query the outgoing edges of a vertex, a model proposed by Bender and Ron in 2002. As our first main result, we we present a…

Data Structures and Algorithms · Computer Science 2013-12-03 Frank Hellweg , Christian Sohler

We discuss a generalization of the classic Keplerian disk test problem allowing for both pressure and rotational support, as a method of testing astrophysical codes incorporating both gravitation and hydrodynamics. We argue for the…

Instrumentation and Methods for Astrophysics · Physics 2017-01-25 Cody Raskin , J. Michael Owen

We present examples of validating components of an astrophysical simulation code. Problems of stellar astrophysics are multi-dimensional and involve physics acting on large ranges of length and time scales that are impossible to include in…

Solar and Stellar Astrophysics · Physics 2018-09-10 A. C. Calder , D. M. Townsley

Stochastic fluid-fluid models (SFFMs) offer powerful modeling ability for a wide range of real-life systems of significance. The existing theoretical framework for this class of models is in terms of operator-analytic methods. For the first…

Probability · Mathematics 2022-03-01 Nigel G. Bean , Małgorzata M. O'Reilly , Zbigniew Palmowski

Although data that can be naturally represented as graphs is widespread in real-world applications across diverse industries, popular graph ML benchmarks for node property prediction only cover a surprisingly narrow set of data domains, and…

Machine Learning · Computer Science 2026-05-05 Gleb Bazhenov , Oleg Platonov , Liudmila Prokhorenkova

With the rapid amassing of spatial-temporal (ST) ocean data, many spatial-temporal data mining (STDM) studies have been conducted to address various oceanic issues, including climate forecasting and disaster warning. Compared with typical…

Machine Learning · Computer Science 2026-04-28 Hanchen Yang , Wengen Li , Shuyu Wang , Hui Li , Jihong Guan , Shuigeng Zhou , Jiannong Cao

This chapter describes the main geophysical methods used when studying offshore rifts and rifted margins. Geophysical data are often the only constraints available for interpretation of offshore rifted continental margins. Seismic…

Geophysics · Physics 2024-01-18 Julia Autin , Louise Watremez

The swimming trajectories of self-propelled organisms or synthetic devices in a viscous fluid can be altered by hydrodynamic interactions with nearby boundaries. We explore a multipole description of swimming bodies and provide a general…

Fluid Dynamics · Physics 2012-11-30 Saverio E. Spagnolie , Eric Lauga

In this paper I discuss the relation between the concept of the Fisher metric and the concept of differentiability of a family of probability measures. I compare the concepts of smooth statistical manifolds, differentiable families of…

Differential Geometry · Mathematics 2023-02-14 Hông Vân Lê

We consider goodness-of-fit tests for the distribution of the composed error in Stochastic Frontier Models. The proposed test statistic utilizes the characteristic function of the composed error term, and is formulated as a weighted…

Statistics Theory · Mathematics 2022-03-01 Simos G. Meintanis , Christos K. Papadimitriou

We present an open-source Matlab framework, titled iFluid, for simulating the dynamics of integrable models using the theory of generalized hydrodynamics (GHD). The framework provides an intuitive interface, enabling users to define and…

Statistical Mechanics · Physics 2020-03-18 Frederik S. Møller , Jörg Schmiedmayer

Out-of-distribution (OOD) detection aims to identify OOD data based on representations extracted from well-trained deep models. However, existing methods largely ignore the reprogramming property of deep models and thus may not fully…

Machine Learning · Computer Science 2022-10-28 Qizhou Wang , Feng Liu , Yonggang Zhang , Jing Zhang , Chen Gong , Tongliang Liu , Bo Han

A well-known approach for identifying defect-prone parts of software in order to focus testing is to use different kinds of product metrics such as size or complexity. Although this approach has been evaluated in many contexts, the question…

Software Engineering · Computer Science 2014-02-05 Frank Elberzhager , Stephan Kremer , Jürgen Münch , Danilo Assmann

In numerical modeling of the Earth System, many processes remain unknown or ill represented (let us quote sub-grid processes, the dependence to unknown latent variables or the non-inclusion of complex dynamics in numerical models) but…

Data Analysis, Statistics and Probability · Physics 2019-03-19 Julien Brajard , Anastase Charantonis , Jérôme Sirven

Oceanic tides are a major source of tidal dissipation. They drive the evolution of planetary systems and the rotational dynamics of planets. However, 2D models commonly used for the Earth cannot be applied to extrasolar telluric planets…

Earth and Planetary Astrophysics · Physics 2018-07-18 Pierre Auclair-Desrotour , Stéphane Mathis , Jacques Laskar , Jérémy Leconte

Ordinary differential equations have been used to model dynamical systems in a broad range. Model checking for parametric ordinary differential equations is a necessary step to check whether the assumed models are plausible. In this paper…

Statistics Theory · Mathematics 2020-03-26 Ran Liu , Yun Fang , Lixing Zhu

Operational ocean forecasting systems conventionally employ dynamical ocean models driven by atmospheric forcing derived from numerical weather prediction (NWP) models. Recent advancements in artificial intelligence and machine learning…

Atmospheric and Oceanic Physics · Physics 2026-04-10 Xiaobing Zhou , Frank Colberg , Debra Hudson , Yonghong Yin , Griffith Young , Christopher Bladwell , Catherine Deburgh-Day

In recent years, GraphQL has become a popular way to expose web APIs. With its raise of adoption in industry, the quality of GraphQL APIs must be also assessed, as with any part of a software system, and preferably in an automated manner.…

Software Engineering · Computer Science 2020-12-15 Stefan Karlsson , Adnan Čaušević , Daniel Sundmark
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