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In this paper we present a semantic study of motion complexes (ie. of a motion verb followed by a spatial preposition). We focus on the spatial and the temporal intrinsic semantic properties of the motion verbs, on the one hand, and of the…

cmp-lg · Computer Science 2016-08-31 Pierre Sablayrolles

An extended interference pattern close to surface may result in both a transmissive or evanescent surface fields for large area manipulation of trapped particles. The affinity of differing particle sizes to a moving standing wave light…

Recent improvements in positioning technology has led to a much wider availability of massive moving object data. A crucial task is to find the moving objects that travel together. Usually, these object sets are called spatio-temporal…

Databases · Computer Science 2016-11-26 Phan Nhat Hai , Pascal Poncelet , Maguelonne Teisseire

Sentence ordering is the task of arranging the sentences of a given text in the correct order. Recent work using deep neural networks for this task has framed it as a sequence prediction problem. In this paper, we propose a new framing of…

Computation and Language · Computer Science 2020-05-04 Shrimai Prabhumoye , Ruslan Salakhutdinov , Alan W Black

Our objective is to discover and localize monotonic temporal changes in a sequence of images. To achieve this, we exploit a simple proxy task of ordering a shuffled image sequence, with `time' serving as a supervisory signal, since only…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Charig Yang , Weidi Xie , Andrew Zisserman

Given an autohomeomorphism on an ordered topological space or its subspace, we show that it is sometimes possible to introduce a new topology-compatible order on that space so that the same map is monotonic with respect to the new ordering.…

General Topology · Mathematics 2023-06-27 Raushan Buzyakova

What is chaos? Despite several decades of research on this ubiquitous and fundamental phenomenon there is yet no agreed-upon answer to this question. Recently, it was realized that all stochastic and deterministic differential equations,…

Chaotic Dynamics · Physics 2019-09-10 Igor V. Ovchinnikov , Massimiliano Di Ventra

A topological measure on a locally compact space is a set function on open and closed subsets which is finitely additive on the collection of open and compact sets, inner regular on open sets, and outer regular on closed sets. Almost all…

General Topology · Mathematics 2019-02-07 Svetlana Butler

We have analyzed the interplay between noise and periodic spatial modulations in bistable systems outside equilibrium and found that noise is able to increase the spatial order of the system, giving rise to periodic patterns which otherwise…

Statistical Mechanics · Physics 2016-08-15 J. M. G. Vilar , J. M. Rubí

In this letter we present a method of constructing dynamical systems with any preassigned number of equilibria by adding symmetry to another system with at least one equilibrium point. If the resulting system is chaotic, we call this…

Chaotic Dynamics · Physics 2012-09-03 Zeraoulia Elhadj , J. C. Sprott

A convenient measure of a map or flow's chaotic action is the topological entropy. In many cases, the entropy has a homological origin: it is forced by the topology of the space. For example, in simple toral maps, the topological entropy is…

Dynamical Systems · Mathematics 2013-05-28 Sarah Tumasz , Jean-Luc Thiffeault

Mathematical morphology, a field within image processing, includes various filters that either highlight, modify, or eliminate certain information in images based on an application's needs. Key operations in these filters are dilation and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Marvin Kahra , Michael Breuß

A novel paradigm for sorting is introduced, based upon resetting. Using simple examples, we demonstrate that sorting is achieved by resetting the velocity component(s) or orientation of the particles, rather than position. The objects to be…

Statistical Mechanics · Physics 2026-03-23 Bart Cleuren , Ralf Eichhorn

Circuit topology refers to the arrangement of interactions between objects belonging to a linearly ordered object set. Linearly ordered set of objects are common in nature and occur in a wide range of applications in economics, computer…

Disordered Systems and Neural Networks · Physics 2015-09-02 Alireza Mashaghi , Abolfazl Ramezanpour

In sorting situations where the final destination of each item is known, it is natural to repeatedly choose items and place them where they belong, allowing the intervening items to shift by one to make room. (In fact, a special case of…

Combinatorics · Mathematics 2008-09-18 Sergi Elizalde , Peter Winkler

The field of mathematical morphology offers well-studied techniques for image processing. In this work, we view morphological operations through the lens of persistent homology, a tool at the heart of the field of topological data analysis.…

Computational Geometry · Computer Science 2021-03-25 Yu-Min Chung , Sarah Day , Chuan-Shen Hu

The theory of multidimensional persistent homology was initially developed in the discrete setting, and involved the study of simplicial complexes filtered through an ordering of the simplices. Later, stability properties of…

Computational Geometry · Computer Science 2013-03-28 Niccolò Cavazza , Marc Ethier , Patrizio Frosini , Tomasz Kaczynski , Claudia Landi

For spatiotemporal chaos described by partial differential equations, there are generally locations where the dynamical variable achieves its local extremum or where the time partial derivative of the variable vanishes instantaneously. To a…

Chaotic Dynamics · Physics 2013-03-07 Quntao Zhuang , Xun Gao , Qi Ouyang , Hongli Wang

The curvature field is measured from tracer particle trajectories in a two-dimensional fluid flow that exhibits spatiotemporal chaos, and is used to extract the hyperbolic and elliptic points of the flow. These special points are pinned to…

Fluid Dynamics · Physics 2009-11-13 Nicholas T. Ouellette , J. P. Gollub

We use topological data analysis and machine learning to study a seminal model of collective motion in biology [D'Orsogna et al., Phys. Rev. Lett. 96 (2006)]. This model describes agents interacting nonlinearly via attractive-repulsive…