Multi-Sensor System For Level Measurements With Optical Fibres

A system for measuring liquid level in multiple tanks using optical fibre technology has been developed. The oil field service industry can benefit from this intrinsically safe technology. Plastic optical fibre (POF) sensor heads are excited by a 650 nm laser. Laser diodes are housed in ST connectors to obtain compact and rough prototypes and these connectors are also used in the fibre pigtails. Optical multiplexing is used to increase the measuring safety area. POF splitters and connectors are used to combine all the receiving sensor head fibres in a single one. Frequency division multiplexing is used to address each sensor head. The global system is controlled through a user friendly software application running in a PC connected to the system via an RS-232 port. A scalable prototype with a range greater than 2 meter, good linearity, better than 1.5% FS (full scale), high accuracy and resolution is developed using a unique lens to collimate and focus the light. Measurements are taken to validate the designs. Up to 8 sensor heads can be connected in the present implementation. But a greater number of sensors can be allocated with minor modifications in the electronics.Universidad Carlos III de MadridPublicad

Perturbation theory in a pure exchange non-equilibrium economy

We develop a formalism to study linearized perturbations around the equilibria of a pure exchange economy. With the use of mean field theory techniques, we derive equations for the flow of products in an economy driven by heterogeneous preferences and probabilistic interaction between agents. We are able to show that if the economic agents have static preferences, which are also homogeneous in any of the steady states, the final wealth distribution is independent of the dynamics of the non-equilibrium theory. In particular, it is completely determined in terms of the initial conditions, and it is independent of the probability, and the network of interaction between agents. We show that the main effect of the network is to determine the relaxation time via the usual eigenvalue gap as in random walks on graphs.Comment: 7 pages, 2 figure

Using synchronization to improve earthquake forecasting in a cellular automaton model

A new forecasting strategy for stochastic systems is introduced. It is inspired by the concept of anticipated synchronization between pairs of chaotic oscillators, recently developed in the area of Dynamical Systems, and by the earthquake forecasting algorithms in which different pattern recognition functions are used for identifying seismic premonitory phenomena. In the new strategy, copies (clones) of the original system (the master) are defined, and they are driven using rules that tend to synchronize them with the master dynamics. The observation of definite patterns in the state of the clones is the signal for connecting an alarm in the original system that efficiently marks the impending occurrence of a catastrophic event. The power of this method is quantitatively illustrated by forecasting the occurrence of characteristic earthquakes in the so-called Minimalist Model.Comment: 4 pages, 3 figure

Periodically rippled graphene: growth and spatially resolved electronic structure

We studied the growth of an epitaxial graphene monolayer on Ru(0001). The graphene monolayer covers uniformly the Ru substrate over lateral distances larger than several microns reproducing the structural defects of the Ru substrate. The graphene is rippled with a periodicity dictated by the difference in lattice parameter between C and Ru. The theoretical model predict inhomogeneities in the electronic structure. This is confirmed by measurements in real space by means of scanning tunnelling spectroscopy. We observe electron pockets at the higher parts of the ripples.Comment: 5 page

A Generic Agent Organisation Framework For Autonomic Systems

Autonomic computing is being advocated as a tool for managing large, complex computing systems. Specifically, self-organisation provides a suitable approach for developing such autonomic systems by incorporating self-management and adaptation properties into large-scale distributed systems. To aid in this development, this paper details a generic problem-solving agent organisation framework that can act as a modelling and simulation platform for autonomic systems. Our framework describes a set of service-providing agents accomplishing tasks through social interactions in dynamically changing organisations. We particularly focus on the organisational structure as it can be used as the basis for the design, development and evaluation of generic algorithms for self-organisation and other approaches towards autonomic systems

Towards the characterization of individual users through Web analytics

We perform an analysis of the way individual users navigate in the Web. We focus primarily in the temporal patterns of they return to a given page. The return probability as a function of time as well as the distribution of time intervals between consecutive visits are measured and found to be independent of the level of activity of single users. The results indicate a rich variety of individual behaviors and seem to preclude the possibility of defining a characteristic frequency for each user in his/her visits to a single site.Comment: 8 pages, 4 figures. To appear in Proceeding of Complex'0

Playing for Data: Ground Truth from Computer Games

Recent progress in computer vision has been driven by high-capacity models trained on large datasets. Unfortunately, creating large datasets with pixel-level labels has been extremely costly due to the amount of human effort required. In this paper, we present an approach to rapidly creating pixel-accurate semantic label maps for images extracted from modern computer games. Although the source code and the internal operation of commercial games are inaccessible, we show that associations between image patches can be reconstructed from the communication between the game and the graphics hardware. This enables rapid propagation of semantic labels within and across images synthesized by the game, with no access to the source code or the content. We validate the presented approach by producing dense pixel-level semantic annotations for 25 thousand images synthesized by a photorealistic open-world computer game. Experiments on semantic segmentation datasets show that using the acquired data to supplement real-world images significantly increases accuracy and that the acquired data enables reducing the amount of hand-labeled real-world data: models trained with game data and just 1/3 of the CamVid training set outperform models trained on the complete CamVid training set.Comment: Accepted to the 14th European Conference on Computer Vision (ECCV 2016

Multifractal properties of growing networks

We introduce a new family of models for growing networks. In these networks new edges are attached preferentially to vertices with higher number of connections, and new vertices are created by already existing ones, inheriting part of their parent's connections. We show that combination of these two features produces multifractal degree distributions, where degree is the number of connections of a vertex. An exact multifractal distribution is found for a nontrivial model of this class. The distribution tends to a power-law one, $\Pi (q) \sim q^{-\gamma}$, $\gamma =\sqrt{2}$ in the infinite network limit. Nevertheless, for finite networks's sizes, because of multifractality, attempts to interpret the distribution as a scale-free would result in an ambiguous value of the exponent $\gamma$.Comment: 7 pages epltex, 1 figur