A magnified glance into the dark sector: probing cosmological models with strong lensing in A1689

In this paper we constrain four alternative models to the late cosmic acceleration in the Universe: Chevallier-Polarski-Linder (CPL), interacting dark energy (IDE), Ricci holographic dark energy (HDE), and modified polytropic Cardassian (MPC). Strong lensing (SL) images of background galaxies produced by the galaxy cluster Abell $1689$ are used to test these models. To perform this analysis we modify the LENSTOOL lens modeling code. The value added by this probe is compared with other complementary probes: Type Ia supernovae (SNIa), baryon acoustic oscillations (BAO), and cosmic microwave background (CMB). We found that the CPL constraints obtained of the SL data are consistent with those estimated using the other probes. The IDE constraints are consistent with the complementary bounds only if large errors in the SL measurements are considered. The Ricci HDE and MPC constraints are weak but they are similar to the BAO, SNIa and CMB estimations. We also compute the figure-of-merit as a tool to quantify the goodness of fit of the data. Our results suggest that the SL method provides statistically significant constraints on the CPL parameters but weak for those of the other models. Finally, we show that the use of the SL measurements in galaxy clusters is a promising and powerful technique to constrain cosmological models. The advantage of this method is that cosmological parameters are estimated by modelling the SL features for each underlying cosmology. These estimations could be further improved by SL constraints coming from other galaxy clusters.Comment: 13 pages, 5 figures, accepted for publication in Ap

Artemisa: early design of an eco-driving assistant

Actas del XIII Jornadas de ARCA: Sistemas Cualitativos y sus Aplicaciones en Diagnosis, Robótica e Inteligencia Ambiental, Huelva 26 – 29 de Junio de 2011Eco-driving is becoming a very important topic in recent years since aspects such as environmental pollution, energy conservation, global warming and user safety depend on it. To save fuel, it requires a combination of vehicle design principles (including aerodynamics, engine optimization, fuel type and vehicle weight) and that the driver adopt an efficient driving style. This paper presents an eco-driving assistant that evaluates the driver's driving style from the standpoint of fuel consumption. Then, based on the assessment provides advice to adopt eco-driving habits. Eco-driving assistant will facilitate that drivers learn the techniques of efficient driving. We solution runs on mobile devices with Android OS requiring minimal HW inside the vehicle. Furthermore, analyze better driver's driving style than other solutions because it takes into account environmental variables that influence in the fuel consumption.The research leading to these results has received funding by the ARTEMISA project TIN2009-14378-C02-02 within the Spanish "Plan Nacional de I+D+I", and the Madrid regional community projects S2009/TIC-1650 and CCG10- UC3M/TIC-4992

WATI: Warning of Traffic Incidents for Fuel Saving

Traffic incidents (heavy traffic, adverse weather conditions, and traffic accidents) cause an increase in the frequency and intensity of the acceleration and deceleration. The result is a very significant increase in fuel consumption. In this paper, we propose a solution to reduce the impact of such events on energy consumption. The solution detects the traffic incidents based on measured telemetry data from vehicles and the different driver profiles. The proposal takes into account the rolling resistance coefficient, the road slope angle, and the vehicles speeds, from vehicles which are on the scene of the traffic incident, in order to estimate the optimal deceleration profile. Adapted advice and feedback are provided to the drivers in order to appropriately and timely release the accelerator pedal. The expert system is implemented on Android mobile devices and has been validated using a dataset of 150 tests using 15 different drivers. The main contribution of this paper is the proposal of a system to detect traffic incidents and provide an optimal deceleration pattern for the driver to follow without requiring sensors on the road. The results show an improvement on the fuel consumption of up to 13.47%

Artemisa: An eco-driving assistant for android Os

Proceedings of the 1st IEEE International Conference on Consumer Electronics - Berlin (IEEE ICCE-Berlin 2011), September 6 - 8, 2011, Berlin, GermanyThis paper proposes an eco-driving assistant that facilitates the user to learn the techniques of efficient driving. The Artemisa´s assistant evaluates the driver´s driving style taking into account some environmental as well as some vehicles´s variables such as speed, gear, R.P.M, etc. Besides, tips are inferred to teach efficient driving habits. Compared to other similar systems, the Artemisa’s assistant runs on a mobile device with Android O.S. and it does not need to install additional hardwareProyecto CCG10-UC3M/TIC-4992 de la Comunidad Autónoma de Madrid y la Universidad Carlos III de Madri

Solitary wave collisions for Whitham-Boussinesq systems

This work concerns soliton-type numerical solutions for two Whitham-Boussinesq-type models. Solitary waves are computed using an iterative Newton-type and continuation methods with high accuracy. The method allow us to compute solitary waves with large amplitude and speed close to the singular limit. These solitary waves are set as initial data and overtaking collisions are considered for both systems. We show that both system satisfy the geometric Lax-categorization of two-soliton collision. Numerical evidences indicate that one of the systems also admits an algebraic Lax-categorization based on the ratio of the initial solitary wave amplitudes with a different range from the one predicted by Lax. However, we show that such categorization is not possible for the second system