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Based on the analysis of the velocity gradient tensor, we investigate in this paper the physical interpretation and limitations of four vortex criteria: $\omega$, $Q$, $\varDelta$ and $\lambda_{ci}$, and reveal the actual physical meaning…

Fluid Dynamics · Physics 2024-06-06 Zhen Li , Xiwen Zhang , Feng He

A corrugated structure, rather than a smooth surface, is a characteristic feature of insect wings (e.g., dragonfly wings), which enhances their aerodynamic performance at low Reynolds numbers ($Re \simeq O(10^3)$). However, the mechanisms…

Fluid Dynamics · Physics 2025-03-18 Yusuke Fujita , Makoto Iima

G\"{o}rtler vortices develop along concave walls as a result of the imbalance between the centrifugal force and radial pressure gradient. In this study, we introduce a simple control strategy aimed at reducing the growth rate of G\"{o}rtler…

Fluid Dynamics · Physics 2018-04-18 Adrian Sescu , Lamiae Taoudi , Mohammed Afsar

For regularized optimization that minimizes the sum of a smooth term and a regularizer that promotes structured solutions, inexact proximal-Newton-type methods, or successive quadratic approximation (SQA) methods, are widely used for their…

Optimization and Control · Mathematics 2023-05-02 Ching-pei Lee

Rotation augmentations generally improve a model's invariance/equivariance to rotation - except in object detection. In object detection the shape is not known, therefore rotation creates a label ambiguity. We show that the de-facto method…

Computer Vision and Pattern Recognition · Computer Science 2021-10-04 Agastya Kalra , Guy Stoppi , Bradley Brown , Rishav Agarwal , Achuta Kadambi

We consider a robust and self-reliant (or "egoistic") variation of the rigid body localization (RBL) problem, in which a primary rigid body seeks to estimate the pose (i.e., location and orientation) of another rigid body (or "target"),…

Signal Processing · Electrical Eng. & Systems 2026-01-07 Niclas Führling , Giuseppe Thadeu Freitas de Abreu , David González G. , Osvaldo Gonsa

The convergence characteristics of two viscous core corrections as used in straight-line segmentation methods are rigorously analysed. These are \emph{curvature corrections} that account for the induced velocity contribution at a point on a…

Computational Physics · Physics 2012-04-13 Wim Van Hoydonck , Marc Gerritsma , Michel van Tooren

The elliptic restricted three body problem has been well studied. However, the previous formulations of the problem have used a rotating coordinate system to keep the positions of the primary and secondary on the x-axis. This requires the…

Classical Physics · Physics 2021-12-15 Robert W. Easton

We describe a new method for computing coherent Lagrangian vortices in two-dimensional flows according to any of the following approaches: black-hole vortices [Haller & Beron-Vera, 2013], objective Eulerian Coherent Structures (OECSs)…

Fluid Dynamics · Physics 2020-06-23 Daniel Karrasch , Nathanael Schilling

Refractive index matching (RIM) is a powerful tool for multiphase flow studies as it eliminates optical distortions and enables high-fidelity tomographic measurements near solid-fluid interfaces of freely moving solids in the flow. However,…

Fluid Dynamics · Physics 2026-02-19 Jibu Tom Jose , Aviel Ben-Harosh , Omri Ram

Flow-matching robot policies commonly use action-chunking inference for efficient closed-loop control, but chunk boundaries can introduce discontinuous action transitions. Existing RTC guidance improves continuity by injecting correction…

Robotics · Computer Science 2026-05-26 Kai Fang , Hailong Pei , Xuemin Chi

In this paper, we propose a Robbins-Monro augmented Lagrangian method (RMALM) to solve a class of constrained stochastic convex optimization, which can be regarded as a hybrid of the Robbins-Monro type stochastic approximation method and…

Optimization and Control · Mathematics 2022-09-02 Rui Wang , Chao Ding

This paper is concerned with the inverse problem of determining the shape of penetrable periodic scatterers from scattered field data. We propose a sampling method with a novel indicator function for solving this inverse problem. This…

Numerical Analysis · Mathematics 2023-05-24 Dinh-Liem Nguyen , Kale Stahl , Trung Truong

We improved a previously proposed method of using closed-orbit modulation for linear optics correction. Instead of fitting individual closed orbits, the improved method decomposes the orbit oscillation data into two orthogonal modes and…

Accelerator Physics · Physics 2023-06-14 Xiaobiao Huang , Xi Yang

Mode sorting is an essential function for optical systems exploiting the orthogonality of photonic orbital angular momentum mode space. The familiar log-polar optical transformation provides an efficient yet simple approach, however with…

Orthogonal matrix has shown advantages in training Recurrent Neural Networks (RNNs), but such matrix is limited to be square for the hidden-to-hidden transformation in RNNs. In this paper, we generalize such square orthogonal matrix to…

Machine Learning · Computer Science 2017-11-22 Lei Huang , Xianglong Liu , Bo Lang , Adams Wei Yu , Yongliang Wang , Bo Li

Recovering a function from integrals over conical surfaces recently got significant interest. It is relevant for emission tomography with Compton cameras and other imaging applications. In this paper, we consider the weighted conical Radon…

Numerical Analysis · Mathematics 2018-12-05 Markus Haltmeier , Daniela Schiefeneder

We show that a certain class of vortex blob approximations for ideal hydrodynamics in two dimensions can be rigorously understood as solutions to the equations of second-grade non-Newtonian fluids with zero viscosity, and initial data in…

Analysis of PDEs · Mathematics 2025-10-20 Marcel Oliver , Steve Shkoller

Optical Coherence Tomography (OCT) is an emerging medical imaging modality for luminal organ diagnosis. The non-constant rotation speed of optical components in the OCT catheter tip causes rotational distortion in OCT volumetric scanning.…

Regularization is a popular technique in machine learning for model estimation and avoiding overfitting. Prior studies have found that modern ordered regularization can be more effective in handling highly correlated, high-dimensional data…

Machine Learning · Computer Science 2019-11-01 Mahammad Humayoo , Xueqi Cheng
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