Search results for "Euclidean Distance"

Rigidity of quasi-isometries for symmetric spaces and Euclidean buildings

1997

Abstract We study quasi-isometries between products of symmetric spaces and Euclidean buildings. The main results are that quasi-isometries preserve the product structure, and that in the irreducible higher rank case, quasi-isometries are at finite distance from homotheties.

2021

Data collected in criminal investigations may suffer from issues like: (i) incompleteness, due to the covert nature of criminal organizations; (ii) incorrectness, caused by either unintentional data collection errors or intentional deception by criminals; (iii) inconsistency, when the same information is collected into law enforcement databases multiple times, or in different formats. In this paper we analyze nine real criminal networks of different nature (i.e., Mafia networks, criminal street gangs and terrorist organizations) in order to quantify the impact of incomplete data, and to determine which network type is most affected by it. The networks are firstly pruned using two specific m…

A robust evolutionary algorithm for the recovery of rational Gielis curves

2013

International audience; Gielis curves (GC) can represent a wide range of shapes and patterns ranging from star shapes to symmetric and asymmetric polygons, and even self intersecting curves. Such patterns appear in natural objects or phenomena, such as flowers, crystals, pollen structures, animals, or even wave propagation. Gielis curves and surfaces are an extension of Lamé curves and surfaces (superquadrics) which have benefited in the last two decades of extensive researches to retrieve their parameters from various data types, such as range images, 2D and 3D point clouds, etc. Unfortunately, the most efficient techniques for superquadrics recovery, based on deterministic methods, cannot…

Non-perturbative renormalization of lattice operators in coordinate space

2004

We present the first numerical implementation of a non-perturbative renormalization method for lattice operators, based on the study of correlation functions in coordinate space at short Euclidean distance. The method is applied to compute the renormalization constants of bilinear quark operators for the non-perturbative O(a)-improved Wilson action in the quenched approximation. The matching with perturbative schemes, such as MS-bar, is computed at the next-to-leading order in continuum perturbation theory. A feasibility study of this technique with Neuberger fermions is also presented.

Dirichlet approximation and universal Dirichlet series

2016

We characterize the uniform limits of Dirichlet polynomials on a right half plane. In the Dirichlet setting, we find approximation results, with respect to the Euclidean distance and {to} the chordal one as well, analogous to classical results of Runge, Mergelyan and Vitushkin. We also strengthen the notion of universal Dirichlet series.

On the Choice of the Most Suitable Period to Map Hill Lakes via Spectral Separability and Object-Based Image Analyses

2023

Technological advances in Earth observation made images characterized by high spatial and temporal resolutions available, nevertheless bringing with them the radiometric heterogeneity of small geographical entities, often also changing in time. Among small geographical entities, hill lakes exhibit a widespread distribution, and their census is sometimes partial or shows unreliable data. High resolution and heterogeneity have boosted the development of geographic object-based image analysis algorithms. This research analyzes which is the most suitable period for acquiring satellite images to identify and delimitate hill lakes. This is achieved by analyzing the spectral separability of the su…

Speech Activity Detection under Adverse Noisy Conditions at Low SNRs

2021

Speech originating from the noisy environments degrades the speech quality and intelligibility, thus reducing the human perceived Quality of Experience (QoE). For example, surveillance using drone during natural catastrophe needs an efficient speech recognition device to recognise the speech of the frozen human in presence of drone noise to save their life. Therefore, it often requires to pre-process the noisy speech in order to reduce the noise artifacts and enhance the speech. This paper detects the speech activity using Voice Activity Detection (VAD). The VAD distinguishes speech activity (speech presence) and speech inactivity (silence/noise) by extracting the speech features and compar…

Isolated roundings and flattenings of submanifolds in Euclidean spaces

2005

We introduce the concepts of rounding and flattening of a smooth map $g$ of an $m$-dimensional manifold $M$ to the euclidean space $\R^n$ with $m<n$, as those points in $M$ such that the image $g(M)$ has contact of type $\Sigma^{m,\dots,m}$ with a hypersphere or a hyperplane of $\R^n$, respectively. This includes several known special points such as vertices or flattenings of a curve in $\R^n$, umbilics of a surface in $\R^3$, or inflections of a surface in $\R^4$.

Intelligent Sampling for Vegetation Nitrogen Mapping Based on Hybrid Machine Learning Algorithms

2021

Upcoming satellite imaging spectroscopy missions will deliver spatiotemporal explicit data streams to be exploited for mapping vegetation properties, such as nitrogen (N) content. Within retrieval workflows for real-time mapping over agricultural regions, such crop-specific information products need to be derived precisely and rapidly. To allow fast processing, intelligent sampling schemes for training databases should be incorporated to establish efficient machine learning (ML) models. In this study, we implemented active learning (AL) heuristics using kernel ridge regression (KRR) to minimize and optimize a training database for variational heteroscedastic Gaussian processes regression (V…

Detection of Internet robots using a Bayesian approach

2015

A large part of Web traffic on e-commerce sites is generated not by human users but by Internet robots: search engine crawlers, shopping bots, hacking bots, etc. In practice, not all robots, especially the malicious ones, disclose their identities to a Web server and thus there is a need to develop methods for their detection and identification. This paper proposes the application of a Bayesian approach to robot detection based on characteristics of user sessions. The method is applied to the Web traffic from a real e-commerce site. Results show that the classification model based on the cluster analysis with the Ward's method and the weighted Euclidean metric is very effective in robot det…