Reinventando los museos

Cap. 1. Museos en la posmodernidad : restos y desafíos. Iñaki Arrieta Urtizberea. Cap. 2. Never let a crisis go to waste. John Coppola. Cap. 3. Logique du don et biens communs : réinventer le musée. François Mairesse. Cap. 4. Procesos de hibridación: la evolución de las infraestructuras museísticas, gestión independiente y autogestión como reinvención del sistema del arte. Nekane Aramburu. Cap. 5. Patrimoine et musées du XXIe. Lieux de vie fédérateurs d’actions sociales. Lieux de vie créateurs d’innovation. Annette Viel. Cap. 6. El museo etnográfico: su prolongada adaptación a la crisis. Experiencias en Galicia. Xosé C. Sierra Rodríguez. Cap. 7. Reflexiones en torno a una “refundación”: El nuevo Museu Marítim de Barcelona. Olga López Miguel. Cap. 8. “El museu de todos, el museo para todos”: la accesibilidad como política. Carme Comas Camacho. Cap. 9. Pedagogía pública en participación a través de la construcción de un retrato transmedia de un territorio: caso de estudio en el Barco Museo Mater. Margarita León Guereño, Izaskun Suberbiola Garbizu, Lierni Gartzia Telleria, Josu Aramberri Miranda, José Miguel Correa Gorospe. Cap. 10. ¿Hacia una gestión de museos en red (MGMenRED)?: postcrisis, benchmarking y Euskal Hiria. Karmele Barandiaran e Igor Calzada.

Morals in business organizations: an approach based on strategic value and strength for business management

[EN] In the last decades, the topic of business ethics has attracted great interest at the academic and professional levels. Nowadays business ethics is being increasingly implemented as a necessary discipline in universities’ study plans on business management. Moreover, its importance is also evident according to the worldwide increase of organizations and/or institutions that have implemented ethics systems. However, some approaches thoroughly do not consider the importance and the need of an ethical behaviour and are still guiding the actions and the way of thinking of many academics and professionals led to consider that the only responsibility of business is limited just to profit maximization.

A Data Dropout Compensation Algorithm Based on the Iterative Learning Control Methodology for Discrete-Time Systems

This paper deals with the convergence of a remote iterative learning control system subject to data dropouts. The system is composed by a set of discrete-time multiple input-multiple output linear models, each one with its corresponding actuator device and its sensor. Each actuator applies the input signals vector to its corresponding model at the sampling instants and the sensor measures the output signals vector. The iterative learning law is processed in a controller located far away of the models so the control signals vector has to be transmitted from the controller to the actuators through transmission channels. Such a law uses the measurements of each model to generate the input vector to be applied to its subsequent model so the measurements of the models have to be transmitted from the sensors to the controller. All transmissions are subject to failures which are described as a binary sequence taking value 1 or 0. A compensation dropout technique is used to replace the lost data in the transmission processes. The convergence to zero of the errors between the output signals vector and a reference one is achieved as the number of models tends to infinity.