Search results for "Geometry"

"Table 24" of "Energy dependence of event shapes and of alpha(s) at LEP-2."

1999

Distribution of Planarity at cm energy 183 GeV.

Filter approach to the stochastic analysis of MDOF wind-excited structures

1999

Abstract In this paper, an approach useful for stochastic analysis of the Gaussian and non-Gaussian behavior of the response of multi-degree-of-freedom (MDOF) wind-excited structures is presented. This approach is based on a particular model of the multivariate stochastic wind field based upon a particular diagonalization of the power spectral density (PSD) matrix of the fluctuating part of wind velocity. This diagonalization is performed in the space of eigenvectors and eigenvalues that are called here wind-eigenvalues and wind-eigenvectors, respectively. From the examination of these quantities it can be recognized that the wind-eigenvectors change slowly with frequency while the first wi…

"README and Table of Contents" of "Search for trilepton resonances from chargino and neutralino pair production in $\sqrt{s}$ = 13 TeV $pp$ collision…

2021

This is the HEPData space for the trilepton resonance wino search, the full resolution figures can be found here https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SUSY-2018-36/. The full statistical likelihoods have been provided for this analysis. They can be downloaded by clicking on the purple 'Resources' buttun above where they can then be found in the 'Common Resources' area. A detailed README for how to use the likelihoods is also included in this download. Exclusion contours: Obs. data vs SM bkg. exp. in CRs and VRs $\ell=(e, \mu, \tau)$, Obs_0 $\ell=(e, \mu, \tau)$, Obs_0_Up $\ell=(e, \mu, \tau)$, Obs_0_Down $\ell=(e, \mu, \tau)$, Exp_0 $\ell=(e, \mu, \tau)$, Exp_0_Up $\ell=(e, …

The stereographic coordinate system

2003

Anisotropic scaling of tectonic stylolites: A fossilized signature of the stress field?

2010

International audience; [1] Vertical stylolites are pressure solution features, which are considered to be caused by horizontal tectonic loading, with the largest principal compressive stress being (sub-) parallel to the Earth's surface. In the present study we analyze the roughness of such tectonic stylolites from two tectonic settings in southern Germany and northeastern Spain, aiming to investigate their scaling properties with respect to the stress during formation. High-resolution laser profilometry was carried out on opened stylolite surfaces of nine samples. These data sets were then analyzed using one-and two-dimensional Fourier power spectral approaches. We found that tectonic styl…

The Monotone Area-preserving Flux-Form Advection Algorithm: Reducing the Time-splitting Error in Two-Dimensional Flow Fields

1993

Mechanisms of Banner Cloud Formation

2013

Abstract Banner clouds are clouds in the lee of steep mountains or sharp ridges. Their formation has previously been hypothesized as due to three different mechanisms: (i) vertical uplift in a lee vortex (which has a horizontal axis), (ii) adiabatic expansion along quasi-horizontal trajectories (the so-called Bernoulli effect), and (iii) a mixing cloud (i.e., condensation through mixing of two unsaturated air masses). In the present work, these hypotheses are tested and quantitatively evaluated against each other by means of large-eddy simulation. The model setup is chosen such as to represent idealized but prototypical conditions for banner cloud formation. In this setup the lee-vortex mec…

Judging body weight from faces: the height-weight illusion.

2012

Being able to exploit features of the human face to predict health and fitness can serve as an evolutionary advantage. Surface features such as facial symmetry, averageness, and skin colour are known to influence attractiveness. We sought to determine whether observers are able to extract more complex features, namely body weight. If possible, it could be used as a predictor for health and fitness. For instance, facial adiposity could be taken to indicate a cardiovascular challenge or proneness to infections. Observers seem to be able to glean body weight information from frontal views of a face. Is weight estimation robust across different viewing angles? We showed that participants stron…

Organizational information and communication technologies and their influence on communication visibility and perceived proximity

2021

This study investigates the relationships between the use of various organizational ICTs, communication visibility, and perceived proximity to distant colleagues. In addition, this study examines the interplay between visibility and proximity, to determine whether visibility improves proximity, or vice versa. These relationships are tested in a global company using two waves of panel survey data. ESM use increases communication visibility and perceived proximity, while controlling for prior levels of visibility, proximity, and the use of other organizational ICTs. The influence of ESM on network translucence and perceived proximity is generally stronger than the impact of other technologie…

Machine Learning VS Transfer Learning - Smart Camera Implementation for Face Authentication

2018

The aim of this paper is to highlight differences between classical machine learning and transfer learning applied to low cost real-time face authentication. Furthermore, in an access control context, the size of biometric data should be minimized so it can be stored on a remote personal media. These constraints have led us to compare only lightest versions of these algorithms. Transfer learning applied on Mobilenet v1 raises to 85% of accuracy, for a 457Ko model, with 3680s and 1.43s for training and prediction tasks. In comparison, the fastest integrated method (Random Forest) shows accuracy up to 90% for a 7,9Ko model, with a fifth of a second to be trained and a hundred of microseconds …