|26 September, 2019|
|11:00 am||a||12:00 pm|
Speaker: Antonino Laudani (Università Degli Studi Roma Tre)
Title: “Mathematics vs Photovoltaic systems”
Date: Thursday, September 26, 11:00 a.m.
Localication: Classrooms 0.1 and 0.2 of the CIO (Torretamarit Building)
Abstract. All the field of engineering are fullfilled by mathematic approaches and this is particularly true for the fields of electrical and electronic engineering. On the other hand, it is also true that in the case of Photovoltaic systems (with this term I indicate all the Photovoltaic objects from the small devices to the large power plants), there are still a lot of things that mathematicians can do to improve the analysis, the modelling and the design of them. In this talk, I will discuss the contribution given by mathematic techniques (from Lambert function to Least Square Problem solution, etc) applied to photovoltaics and their open problems. Mathematicians together with electrical and electronic enginers and computer science scientists can provide a fundamental contribution in the research advance.
|27 September, 2019|
|12:30 pm||a||1:30 pm|
Speaker: Annick Laruelle (Basque Country University)
Title: “Cost-Benefit analysis in participatory budgeting”
Date: Friday, September 27, 12:30 a.m.
Localication: CIO Seminar Room (Torretamarit Building)
Abstract. In participatory budgeting, citizens are invited to vote on different projects. Those with the most votes are chosen and implemented. The voting rules used in practice are usually based on single winner elections. A shortcoming of using these rules is that they do not take into account the costs of the projects, although those costs may differ substantially. The aim of this study is to provide an algorithm for a decision support system adapted to participatory budgeting processes. It relies on two main principles: First, a costly project should require more votes than a cheap project in order to be adopted¡ second, it is important to satisfy as many participants as possible. The method is applied to the 2018 participatory budgeting of the city of Portugalete (Spain).
María Jesús Gisbert (Miguel Hernández University of Elche), María Josefa Cánovas (Miguel Hernández University of Elche), Juan Parra (Miguel Hernández University of Elche) and Fco. Javier Toledo (Miguel Hernández University of Elche).
Abstract. The present paper is devoted to the computation of the Lipschitz modulus of the optimal value function restricted to its domain in linear programming under different types of perturbations. In the first stage, we study separately perturbations of the right-hand side of the constraints and perturbations of the coefficients of the objective function. Secondly, we deal with canonical perturbations, i.e., right-hand side perturbations together with linear perturbations of the objective. We advance that an exact formula for the Lipschitz modulus in the context of right-hand side perturbations is provided, and lower and upper estimates for the corresponding moduli are also established in the other two perturbation frameworks. In both cases, the corresponding upper estimates are shown to provide the exact moduli when the nominal (original) optimal set is bounded. A key strategy here consists in taking advantage of the background on calmness in linear programming and providing the aimed Lipschitz modulus through the computation of a uniform calmness constant.
Keywords. Lipschitz modulus; Optimal value; Linear programming; Variational analysis; Calmness
María Victoria Herranz (Miguel Hernández University of Elche), Diego Napp (Universidade de Aveiro) and Carmen Perea (Miguel Hernández University of Elche).
Abstract. In this paper we study two different concatenation schemes of twodimensional (2D) convolutional codes. We consider Fornasini–Marchesini state space representation of 2D linear systems to describe our concatenated codes. Also we present upper and lower bounds on the distance of the proposed concatenated codes.
Keywords. 2D convolutional code; Concatenated convolutional code; Marchesini– Fornasini 2D model; Minimum distance; Free distance