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We model two time and space scales discrete observations by using a unique continuous diffusion process with time dependent coefficient. We define new parameters for the large scale model as functions of the small scale distribution…

Methodology · Statistics 2009-09-09 V. Calian , G. Stefansson , L. P. Folkow , A. S. Blix

In this paper we study the combined effects of size and shape of small solid state particles on the absorption, emission and scattering characteristics. We use the statistical approach to calculate these optical properties. In this approach…

Astrophysics · Physics 2009-11-10 M. Min , J. W. Hovenier , A. de Koter

Dwarf Irregular galaxies (dIrrs) are the smallest stellar systems with extended HI discs. The study of the kinematics of such discs is a powerful tool to estimate the total matter distribution at these very small scales. In this work, we…

Astrophysics of Galaxies · Physics 2017-03-22 Giuliano Iorio , Filippo Fraternali , Carlo Nipoti , Enrico Di Teodoro , Justin I. Read , Giuseppina Battaglia

We show that quasi localized low-frequency modes in the vibrational spectrum can be used to construct soft spots, or regions vulnerable to rearrangement, which serve as a universal tool for the identification of flow defects in solids. We…

Soft Condensed Matter · Physics 2015-06-19 Joerg Rottler , Samuel S. Schoenholz , Andrea J. Liu

Trajectory segmentation refers to dividing a trajectory into meaningful consecutive sub-trajectories. This paper focuses on trajectory segmentation for 3D rigid-body motions. Most segmentation approaches in the literature represent the…

Robotics · Computer Science 2024-10-28 Arno Verduyn , Maxim Vochten , Joris De Schutter

Statistical shape modeling (SSM) is a valuable and powerful tool to generate a detailed representation of complex anatomy that enables quantitative analysis and the comparison of shapes and their variations. SSM applies mathematics,…

Image and Video Processing · Electrical Eng. & Systems 2022-09-14 Krithika Iyer , Alan Morris , Brian Zenger , Karthik Karanth , Benjamin A Orkild , Oleksandre Korshak , Shireen Elhabian

The study of physiology demonstrates that the form (shape)of anatomical structures dictates their functions, and analyzing the form of anatomies plays a crucial role in clinical research. Statistical shape modeling (SSM) is a widely used…

Computer Vision and Pattern Recognition · Computer Science 2024-07-03 Krithika Iyer , Shireen Y. Elhabian

We propose point estimators for the three-parameter (location, scale, and the fractional parameter) variant distributions generated by a Wright function. We also provide uncertainty quantification procedures for the proposed point…

Methodology · Statistics 2017-11-13 Dexter Cahoy , Sharifa Minkabo

Motivated by strategies for targeted microfluidic transport of droplets, we investigate how sessile droplets can be steered toward a preferred direction using travelling waves in substrate wettability or deformations of the substrate. To…

Fluid Dynamics · Physics 2024-08-14 Josua Grawitter , Holger Stark

Self-assembly of particles with short-range attraction and long-range repulsion (SALR) interactions on a flat and on a spherical surface is compared. Molecular dynamics (MD) simulations are performed for the two systems having the same area…

Soft Condensed Matter · Physics 2018-11-20 Jakub Pękalski , Alina Ciach

In recent years there has been a resurgence of interest in our community in the shape analysis of 3D objects represented by surface meshes, their voxelized interiors, or surface point clouds. In part, this interest has been stimulated by…

Computer Vision and Pattern Recognition · Computer Science 2021-12-01 Morteza Rezanejad , Mohammad Khodadad , Hamidreza Mahyar , Herve Lombaert , Michael Gruninger , Dirk B. Walther , Kaleem Siddiqi

Multi-view data provides complementary information on the same set of observations, with multi-omics and multimodal sensor data being common examples. Analyzing such data typically requires distinguishing between shared (joint) and unique…

Machine Learning · Statistics 2025-08-14 Renat Sergazinov , Armeen Taeb , Irina Gaynanova

Micron-sized self-propelled (active) particles can be considered as model systems for characterizing more complex biological organisms like swimming bacteria or motile cells. We produce asymmetric microswimmers by soft lithography and study…

Slow dynamics in a fluid are studied in one of the most basic systems possible: polydisperse hard spheres. Monodisperse hard spheres cannot be studied as the slow down in dynamics as the density is increased is preempted by crystallisation.…

Soft Condensed Matter · Physics 2009-10-31 Richard P. Sear

Dispersion is a fundamental concept in statistics, yet standard approaches - especially via stochastic orders - face limitations in the discrete setting. In particular, the classical dispersive order, well-established for continuous…

Methodology · Statistics 2025-11-11 Andreas Eberl , Bernhard Klar , Alfonso Suárez-Llorens

Recently it has been reported that biased range-measurements among neighboring agents in the gradient distance-based formation control can lead to predictable collective motion. In this paper we take advantage of this effect and by…

Systems and Control · Computer Science 2016-09-26 Hector Garcia de Marina , Bayu Jayawardhana , Ming Cao

The irregularity of particle motions during quasi-static deformation is investigated using discrete element (DEM) simulations of sphere and sphere-cluster assemblies. A total of three types of interparticle movements are analyzed: relative…

Soft Condensed Matter · Physics 2018-12-20 Matthew R. Kuhn

The problem of image segmentation is known to become particularly challenging in the case of partial occlusion of the object(s) of interest, background clutter, and the presence of strong noise. To overcome this problem, the present paper…

Computer Vision and Pattern Recognition · Computer Science 2010-06-15 Robert Sheng Xu , Oleg Michailovich , Magdy Salama

This paper presents a new approach for dimension reduction of data observed in a sphere. Several dimension reduction techniques have recently developed for the analysis of non-Euclidean data. As a pioneer work, Hauberg (2016) attempted to…

Methodology · Statistics 2021-05-27 Jang-Hyun Kim , Jongmin Lee , Hee-Seok Oh

To identify emerging microscopic structures in low temperature spin glasses, we study self-sustained clusters (SSC) in spin models defined on sparse random graphs. A message-passing algorithm is developed to determine the probability of…

Disordered Systems and Neural Networks · Physics 2018-07-04 Jacopo Rocchi , David Saad , Chi Ho Yeung
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