Orange S.A.

About: Orange S.A. is a company organization based out in Paris, France. It is known for research contribution in the topics: Terminal (electronics) & Signal. The organization has 6735 authors who have published 9190 publications receiving 156440 citations. The organization is also known as: Orange SA & France Télécom.

A fluid model for performance analysis in cellular networks

Abstract: We propose a new framework to study the performance of cellular networks using a fluid model and we derive from this model analytical formulas for interference, outage probability, and spatial outage probability. The key idea of the fluid model is to consider the discrete base station (BS) entities as a continuum of transmitters that are spatially distributed in the network. This model allows us to obtain simple analytical expressions to reveal main characteristics of the network. In this paper, we focus on the downlink other-cell interference factor (OCIF), which is defined for a given user as the ratio of its outer cell received power to its inner cell received power. A closed-form formula of the OCIF is provided in this paper. From this formula, we are able to obtain the global outage probability as well as the spatial outage probability, which depends on the location of a mobile station (MS) initiating a new call. Our analytical results are compared to Monte Carlo simulations performed in a traditional hexagonal network. Furthermore, we demonstrate an application of the outage probability related to cell breathing and densification of cellular networks.

System and method for locating points of interest in an object image using a neural network

Abstract: A system is provided for locating at least two points of interest in an object image. One such system uses an artificial neural network and has a layered architecture having: an input layer, which receives the object image; at least one intermediate layer, known as the first intermediate layer, consisting of a plurality of neurons that can be used to generate at least two saliency maps, which are each associated with a different pre-defined point of interest in the object image; and at least one output layer, which contains the aforementioned saliency maps. The maps include a plurality of neurons, which are each connected to all of the neurons in the first intermediate layer. The points of interest are located in the object image by the position of a unique global maximum on each of the saliency maps.

The natural frequencies of the arterial system and their relation to the heart rate

Abstract: We assume the major function of the arterial system is transporting energy via its transverse vibration to facilitate the blood flowing all the way down to the microcirculation. A highly efficient system is related to maintaining a large pressure pulse along the artery for a given ventricular power. The arterial system is described as a composition of many infinitesimal Windkessels. The strong tethering in the longitudinal direction connects all the Windkessels together and makes them vibrate in coupled modes. It was assumed that at rest condition, the arterial system is in a steady distributed oscillatory state, which is the superposition of many harmonic modes of the transverse vibration in the arterial wall and the adherent blood. Every vibration mode has its own characteristic frequency, which depends on the geometry, the mass density, the elasticity, and the tethering of the arterial system. If the heart rate is near the fundamental natural frequency, the system is in a good resonance condition, we call this "frequency matching". In this condition, the pulsatile pressure wave is maximized. A pressure wave equation derived previously was used to predict this fundamental frequency. The theoretical result gave that heart rate is proportional to the average high-frequency phase velocity of the pressure wave and the inverse of the animal body length dimension. The area compliance related to the efficiency of the circulatory system is also mentioned.