Price discrimination and market power in export markets: The case of the ceramic tile industry.

This paper combines the pricing-to-market equation and the residual demand elasticity equation to measure the extent of competition in the export markets of ceramic tiles, which has been dominated by Italian and Spanish producers since the late eighties. The findings show that the tile exporters enjoyed substantial market power over the period 1988-1998, and limited evidence that the export market has become more competitive over time.price discrimination, market power, export markets, ceramic tile industry

The impact of exchange rate fluctuations on profit margins: The UK car market, 1971-2002

We investigate the impact on profit margins of exchange rate fluctuations in order to examine optimal pricing policy by source countries in the UK car market. We first estimate a nested logit demand model of new cars to calculate model-specific profit margins. Next we use these estimates to analyse the pricing-to-market (PTM) behaviour of car importers and local producers. The results show that: (1) profit margins fell over the period 1971-2002 as the UK car market moved from being a concentrated market to a looser oligopoly structure; (2) there is a positive association between exchange rate changes and mark-up adjustments of imported cars. Following a 10% pound depreciation, exporters’ profit margins declined by up to 4% and local producers’ profit margins increased by up to 2%; (3) PTM behaviour is asymmetric between appreciations and depreciations in bilateral exchange rates.exchange rates, markup adjustment, pricing to market, cars

A rolling horizon optimization framework for the simultaneous energy supply and demand planning in microgrids

This work focuses on the development of optimization-based scheduling strategies for the coordination of microgrids. The main novelty of this work is the simultaneous management of energy production and energy demand within a reactive scheduling approach to deal with the presence of uncertainty associated to production and consumption. Delays in the nominal energy demands are allowed under associated penalty costs to tackle flexible and fluctuating demand profiles. In this study, the basic microgrid structure consists of renewable energy systems (photovoltaic panels, wind turbines) and energy storage units. Consequently, a Mixed Integer Linear Programming (MILP) formulation is presented and used within a rolling horizon scheme that periodically updates input data information

Javier Garcerá=Exhale Inhale

Proceso de creación del artista Javier Garcerá en cuanto a la utilización de la materia.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

¿Por qué el modelo de dotaciones factoriales no es capaz de explicar la localización de la producción de las provincias españolas?

Este trabajo examina la relación entre dotaciones factoriales y patrón de producción con datos de provincias españolas. Los resultados indican un alto grado de indeterminación en la producción utilizando el modelo de dotaciones factoriales. Dos explicaciones son consistentes con este resultado: 1) los bajos costes de transporte en las actividades de manufacturas dentro de un país magnifican la indeterminación de la producción; 2) la presencia de externalidades geográficas en algunas regiones magnifica la indeterminación de la producció[email protected]

Detecting and tracking using 2D laser range finders and deep learning

Detecting and tracking people using 2D laser rangefinders (LRFs) is challenging due to the features of the human leg motion, high levels of self-occlusion and the existence of objects which are similar to the human legs. Previous approaches use datasets that are manually labelled with support of images of the scenes. We propose a system with a calibrated monocular camera and 2D LRF mounted on a mobile robot in order to generate a dataset of leg patterns through automatic labelling which is valid to achieve a robust and efficient 2D LRF-based people detector and tracker. First, both images and 2D laser data are recorded during the robot navigation in indoor environments. Second, the people detection boxes and keypoints obtained by a deep learning-based object detector are used to locate both people and their legs on the images. The coordinates frame of 2D laser is extrinsically calibrated to the camera coordinates allowing our system to automatically label the leg instances. The automatically labelled dataset is then used to achieve a leg detector by machine learning techniques. To validate the proposal, the leg detector is used to develop a Kalman filter-based people detection and tracking algorithm which is experimentally assessed. The experimentation shows that the proposed system overcomes the Angus Leigh’s detector and tracker which is considered the state of the art on 2D LRF-based people detector and tracker.This work was supported under Grant PID2019-104818RB-I00 funded by MCIN/AEI/10.13039/501100011033 and by ‘‘European Regional Development Fund (ERDF) A way of making Europe’’.Funding for open access charge: Universidad de Granada / CBUA

Using a Deep Learning Model on Images to Obtain a 2D Laser People Detector for a Mobile Robot

Recent improvements in deep learning techniques applied to images allow the detection of people with a high success rate. However, other types of sensors, such as laser rangefinders, are still useful due to their wide field of vision and their ability to operate in different environments and lighting conditions. In this work we use an interesting computational intelligence technique such as the deep learning method to detect people in images taken by a mobile robot. The masks of the people in the images are used to automatically label a set of samples formed by 2D laser range data that will allow us to detect the legs of people present in the scene. The samples are geometric characteristics of the clusters built from the laser data. The machine learning algorithms are used to learn a classifier that is capable of detecting people from only 2D laser range data. Our people detector is compared to a state-of-the-art classifier. Our proposal achieves a higher value of F1 in the test set using an unbalanced dataset. To improve accuracy, the final classifier has been generated from a balanced training set. This final classifier has also been evaluated using a test set in which we have obtained very high accuracy values in each class. The contribution of this work is 2-fold. On the one hand, our proposal performs an automatic labeling of the samples so that the dataset can be collected under real operating conditions. On the other hand, the robot can detect people in a wider field of view than if we only used a camera, and in this way can help build more robust behaviors.This work has been supported by the Spanish Government TIN2016- 76515-R Grant, supported with Feder funds

Formación Accesible en el ámbito de la cultura y el patrimonio de las personas con discapacidad intelectual

El arte y el patrimonio cultural son herramientas de gran valor en la inclusión social y el desarrollo personal de las personas con diversidad funcional. Su accesibilidad es una realidad que poco a poco están desarrollando las diferentes instituciones dirigidas al mundo del arte y la cultura. En este sentido podemos encontrar diferentes líneas u objetivos a seguir, desde la adaptación de las exposiciones a personas con diversidad funcional, la realización de talleres específicos y/o el desarrollo de proyectos artísticos protagonizados por este colectivo.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Fundación ONC