Clustering Patients with Tensor Decomposition

In this paper we present a method for the unsupervised clustering of high-dimensional binary data, with a special focus on electronic healthcare records. We present a robust and efficient heuristic to face this problem using tensor decomposition. We present the reasons why this approach is preferable for tasks such as clustering patient records, to more commonly used distance-based methods. We run the algorithm on two datasets of healthcare records, obtaining clinically meaningful results.Comment: Presented at 2017 Machine Learning for Healthcare Conference (MLHC 2017). Boston, M

Company-university collaboration in applying gamification to learning about insurance

Incorporating gamification into training–learning at universities is hampered by a shortage of quality, adapted educational video games. Large companies are leading in the creation of educational video games for their internal training or to enhance their public image and universities can benefit from collaborating. The aim of this research is to evaluate, both objectively and subjectively, the potential of the simulation game BugaMAP (developed by the MAPFRE Foundation) for university teaching about insurance. To this end, we have assessed both the game itself and the experience of using the game as perceived by 142 economics students from various degree plans and courses at the University of Seville during the 2017–2018 academic year. As a methodology, a checklist of gamification components is used for the objective evaluation, and an opinion questionnaire on the game experience is used for the subjective evaluation. Among the results several findings stand out. One is the high satisfaction of the students with the knowledge acquired using fun and social interaction. Another is that the role of the university professors and the company monitors turns out to be very active and necessary during the game-learning sessions. Finally, in addition to the benefits to the university of occasionally available quality games to accelerate student skills training, the company–university collaboration serves as a trial and refinement of innovative tools for game-based learning

Enlarging the domain of attraction of MPC controllers

This paper presents a method for enlarging the domain of attraction of nonlinear model predictive control (MPC). The usual way of guaranteeing stability of nonlinear MPC is to add a terminal constraint and a terminal cost to the optimization problem such that the terminal region is a positively invariant set for the system and the terminal cost is an associated Lyapunov function. The domain of attraction of the controller depends on the size of the terminal region and the control horizon. By increasing the control horizon, the domain of attraction is enlarged but at the expense of a greater computational burden, while increasing the terminal region produces an enlargement without an extra cost. In this paper, the MPC formulation with terminal cost and constraint is modified, replacing the terminal constraint by a contractive terminal constraint. This constraint is given by a sequence of sets computed off-line that is based on the positively invariant set. Each set of this sequence does not need to be an invariant set and can be computed by a procedure which provides an inner approximation to the one-step set. This property allows us to use one-step approximations with a trade off between accuracy and computational burden for the computation of the sequence. This strategy guarantees closed loop-stability ensuring the enlargement of the domain of attraction and the local optimality of the controller. Moreover, this idea can be directly translated to robust MPC.Ministerio de Ciencia y Tecnología DPI2002-04375-c03-0

Identification of Public Objectives Related to Agricultural Sector Support

The Common Agricultural Policy (CAP) is a widely debated policy in terms of both its budget and its instruments. In order to serve the citizens of Europe properly, CAP requires optimal identification of the public objectives desired. This paper aims to analyse the relative weights that citizens assign to the various potential objectives of the CAP and to show how these can be used to improve the selection of policy instruments. As a means of identifying social preferences we used the Analytical Hierarchy Process (AHP) technique on a population sample in Castilla y León (Spain). Results show how the current policy decision process lacks mechanisms capable of identifying social preferences and thus leading to the choice of sub-optimal policies.Common Agricultural Policy, Objectives, Social preferences, AHP, Castilla y León.

Predicting willingness to pay for geographical origin in Albania: A logistic approach

This study empirically evaluates the factors that determine willingness to pay a premium for a product’s geographical origin and the effect of socio-demographics in indicating one or another factor. The premium to origin is linked with the traditional aspect, low health risk and high nutritional values. Logistic regression shows that elder, highly educated people buying in dairy shops are less likely to pay a higher premium. Consumers who are more likely to pay more include: those on high incomes who place importance on origin and taste attributes during the buying decision process and, in so doing, link the extra cost with the fact that it comes from a traditional cheese-producing region.Cette étude évalue de manière empirique les facteurs qui déterminent le consentement à payer une prime pour l’origine géographique d’un produit et les effets socio- démographie du consommateur en indiquant un ou l’autre facteur. Le prime à l’origine est liée à l’aspect traditionnel, au faible risque à la santé et de haute valeur nutritionnelle. La régression logistique montre que les personnes le plus âgées, bien éduqués qui achètent dans les magasins des produits laitiers sont moins susceptibles de payer une prime plus élevée. Tandis que les consommateurs qui sont plus susceptibles de payer plus comprennent: les personnes à revenus élevés qui placent importance sur l’origine et le goût pendant le processus de décision d’achat et le prime payée est lié avec les aspects traditionnels du produit

Enlarging the domain of attraction of MPC controller using invariant sets

2002 IFAC15th Triennial World Congress, Barcelona, SpainThis paper presents a method for enlarging the domain of attraction of nonlinear model predictive control (MPC). The useful way of guaranteeing stability of nonlinear MPC is to add a terminal constraint and a terminal cost in the optimization problem. The terminal constraint is a positively invariant set for the system and the terminal cost is an associated Lyapunov function. The domain of attraction of the controller depends on the size of the terminal region and the prediction horizon. By increasing the prediction horizon, the domain of attraction is enlarged but at expense of a greater computational burden. A strategy to enlarge the domain of attraction of MPC without increasing the prediction horizon is presented. The terminal constraint is replaced by a contractive terminal constraint which is given by a sequence of control invariant sets for the system. This strategy guarantees closed loop stability under the same assumptions

Robust stability of min-max MPC controllers for nonlinear systems with bounded uncertainties

Sixteenth International Symposium on Mathematical Theory of Networks and Systems 05/07/2004 Leuven, BélgicaThe closed loop formulation of the robust MPC has been shown to be a control technique capable of robustly stabilize uncertain nonlinear systems subject to constraints. Robust asymptotic stability of these controllers has been proved when the uncertainties are decaying. In this paper we extend the existing results to the case of uncertainties that decay with the state but do not tend to zero. This allows us to consider both plant uncertainties and external disturbances in a less conservative way. First, we provide some results on robust stability under the considered kind of uncertainties. Based on these, we prove robust stability of the min-max MPC. In the paper we show how the robust design of the local controller is translated to the min-max controller and how the persistent term of the uncertainties determines the convergence rate of the closed-loop system.Ministerio de Ciencia y Tecnología DPI-2001-2380-03-01Ministerio de Ciencia y Tecnología DPI-2002-4375-C02-0

Multicriteria Modelling of Irrigation Water Market at Basin Level

This paper develops a multi-criteria methodology to simulate irrigation water markets at basin level. For this purpose it is assumed that irrigators try to optimise personal multi-attribute utility functions via their productive decision making process (crop mix), subject to a set of constraints based upon the structural features of their farms. In this sense, farmers with homogeneous behaviour regarding water use have been grouped, such groups being established as .types. to be considered in the whole water market simulation model. This model calculates the equilibrium through a solution that maximises aggregate welfare, which is quantified as the sum of the multi-attribute utilities reached by each of the participating agents. This methodology has been empirically applied for the Duero Basin (Northern Spain), finding that the implementation of this institution would increase economic efficiency and agricultural labour demand, particularly during droughts.Water markets, Multi-Attribute Utility Theory, Irrigation water, Duero Valley (Spain).

The complexity of environmental education: teaching ideas and strategies from teachers

Ponencia de 7th International Conference on Intercultural Education “Education, Health and ICT for a Transcultural World”, EDUHEM 2016The research presented tries to understand and analyze the conceptions that the teachers keep from different levels of education (primary, secondary, and higher education), about the paradigm in which are placed in the treatment of Environmental Education (EE ), as well as methodological strategies used and / or designed for practice. This work argues with the intention of detecting possible reductionism, determinism and fragmentation, in the conceptions of teachers. To do this quantitative techniques have been combined, by using a questionnaire, with qualitative techniques, through the interview in depth; which has allowed us to know and analyze the current situation of the participating teachers in their conceptions of EE, as well as methodological aspects used in its treatment. For this, it conducted an investigation of descriptive-interpretative type with 58 teaching participants, of different educational levels and they teach different subjects and / or disciplines. The results make visible that there is interest in a reflective view closer to the complex thought in the treatment of EE, howev er we check reductionism associated with the difficulties of their practic