Linking Education and Business across Geography of Erasmus +Improving Relationships between Vocational Training and Job Market

A multitude of studies have demonstrated that entrepreneurial competence is not only required to start an enterprise but it is a key lifelong learning competence relevant for the labour market. The recent communications of the European Commission however underlines the need for more entrepreneurs-hip education in Europe. The following paper describes a novel approach to training of entrepreneu-rial skills, which has been developed by the European funded project Linking Education and Business (LEB) (www.oai.ie/linking-education-business.php). The project team, which consists of VET scho-ols and enterprises, focuses on the new dynamics of society, which is demanding not only individuals with critical thinking and ethics training to contribute to sustainable development, but also with strong capabilities to survive in an increasingly demanding job market. The gap between the labor market and the education system generates controversy among experts about how to fix it, being necessary to try to solve the above deficiencies and respond to the new challenges of the production system in a new economic and social contexts. Research paper Reference to this paper should be made as follows: Balaguer, P. A. (2016). “Linking Education and Business across Geography of Erasmus +. Improving Relationships between Vocational Training and Job Market”, Journal of Entrepreneurship, Business and Economics, Vol. 4, No. 1, pp. 73–84

A new frequency dependent approach to model validation for iterative identification and control schemes

Classical validation methods “accept” or “reject” a model as a valid representation of a plant for some intended use. However this binary result has several problems as firstly, models are neither good nor bad but have a certain valid frequency range and secondly the procedure gives no insight into why the model is not useful or how to improve the model. Moreover within the framework of iterative identification and control design the model validation issue arises the following requirements: i) Is it possible to improve an existing model?. ii) How can the model be improved?. iii) How authoritative can be the designed controller?. These facts question the suitability of traditional model validation schemes in general and their suitability for iterative control schemes in particular. We present a new validation procedure that overtakes these problems by performing the model validation frequency dependent. The validation procedure is then more informative due to its frequency information content. As a result the same model can be validated for some frequency band and invalidated for a distinct frequency rang

Optimal averaging time for improving observer accuracy of stochastic dynamical systems

In the problem of remote estimation by a centralized observer, improvements to the accuracy of observer estimates come at a cost of higher communication bandwidth and energy consumption. In this article we improve observer estimation accuracy by reducing the measurement variance on the sensor node before its transmission to the centralized observer node. The main contribution is to show that measurement variance is a trade-off between dynamical system variance and sensor variance. As a result there is an optimal averaging time that minimizes measurement variance, providing more accurate measurement to the observer. The optimal averaging time is computable by solving a univariate optimization problem

Optimal Sampling Pattern for the Free Final Time Linear Quadratic Regulator

The optimal sampling problem is the selection of the optimal sampling instants together with the optimal control actions such that a given cost function is minimized. In this article, we solve the optimal sampling problem for the free final time linear quadratic regulator. Each optimal sampling instant is computed as the minimization of a maximum eigenvalue problem that is formulated at each stage by previously applying dynamic programming. The solution provides the optimal sampling instants, control actions, and the optimal final time in a recursive and constructive way. Furthermore, the solution is optimal for any arbitrary number of control moves N≥1 , as it is not based on asymptotic arguments. Two application examples show the feasibility of the approach

(NEO) Geography Before the Challenges of the Information Society, Cultural and Educational Impact. Perspectives for the Future

The information society associated with the massification of new technologies is provoking a social change that is considered revolutionary by numerous scholars and researchers from different disciplines of the Social Sciences. Such a revolution would already be affecting all aspects of human activity, from politics to economy through to culture, social relationships, leisure time, or education. Geography, as a social science, is not left out of this new situation. Rather it is deeply influenced by the so-called Information and Communication Technologies (ICTs), not only in its methodology and work techniques but also in relation to the new epistemological and sociological questions that the new information society entails. From this last point of view mainly Social Geography faces the new challenge that now is happening at least in part in a new place, the cyberspace or virtual space

Optimal sampling pattern for free final time linear quadratic regulator: the scalar case

The optimal sampling problem is the selection of the optimal sampling instants together with the optimal control actions such that a given cost function is minimized. In this article we solve the optimal sampling problem for free final time linear quadratic regulator with scalar dynamical system. The solution provides the optimal sampling instants, control actions, and the optimal final time in a recursive and constructive way for any arbitrary number of samples N ≥ 1, as it is not based on asymptotic arguments. An application example shows the feasibility of the approach

Tuning of PID Controllers based on simplified single parameter optimization

A simple method to design PID controllers in the frequency domain based on a simplified constrained optimiza- tion is proposed. The method is based on the use of a single tuning parameter, defined as the quotient between the final crossover frequency and the zero of the controller. The tuning procedure is based on the maximization of the controller gain subject to an equality constraint in the phase margin and an inequality constraint in the gain margin. The main advantage of the proposed method is that, even though the maximization of the controller gain is straightforward, since there is only one parameter to be tuned, the solution is close to the optimal tuning obtained with direct numerical optimization methods. Moreover the method is applicable to any linear model structure, including dead time and non-minimum phase systems

Power management strategies and energy storage needs to increase the operability of photovoltaic plants

This paper analyzes the effect of introducing an energy storage (ES) system in an intermittent renewable energy power plant such as a photovoltaic (PV) installation. The aim of this integration is to achieve an improvement in the operability of these power plants by increasing their production predictability. This will allow a further PV integration within the electrical power system, facilitating the system’s load–demand balance. In this manner, the paper proposes two power management strategies (PMSs), each with different configurations, for operating a PV power plant: the first focuses on fixing constant power production and the latter focuses on reducing the high frequency fluctuations of the production. Thereafter, this paper analyzes and quantifies the ratings of the ES system (ESS) required to ensure a reliable performance of the plant on an annual basis for each of the PMSs with their different possible configurations. The resulting ES ratings vary with these PMS configurations. It can be concluded that significant improvements in production predictability are achieved with an ESS energy capacity of approximately 50% of the average daily energy produced by the PV panels and a power rating of around 55% of the plant’s rated power. All the results are based on 1-year-long simulations which used real irradiance data sampled every 2min