Synergy between public space politics and mobility strategies

¿Hasta qué punto y en qué circunstancias movilidad, como aspecto funcional e inevitable del entorno humano, se puede convertir en un elemento afirmativo de espacio público dándole un nuevo significado y un valor añadido? Diálogo entre movilidad y espacio público se puede explicar mediante la comprensión de las estrategias de movilidad como partidario de la integración de diferentes lógicas urbanas, observando infraestructura como un elemento de configuración de espacio público y al cuestionar transporte como pivote del carácter e identidad de espacio público. El objetivo principal de esta discusión es la integración urbana y contextual de los sistemas de transporte vistos como confluencias de lógica urbana y lógica de transporte desarrolladas como una sola expresión. Armonizando esta paradoja es posible crear sinergias entre espacio público y transporte que ganan nuevas dimensiones.Up to which point and under which circumstances mobility, as a functional and an inevitable aspect of the human environment, can become an affirmative element of public space giving it a new significance and an additional value? Dialog between mobility and public space can be explained by understanding mobility strategies as a supporter of integration of different urban logics, by observing infrastructure as an element of public space configuration and by questioning transport as a pivot of public space character and identity. The main focus of this discussion is on mobility lines, specifically urban and contextual integration of transport systems seen as a crossroads between urban and transport logic, developed as a single expression. Harmonizing this paradox it is possible to create synergies between public space and mobility which gain new dimensions

Identifying smart design attributes for Industry 4.0 customization using a clustering Genetic Algorithm

Industry 4.0 aims at achieving mass customization at a mass production cost. A key component to realizing this is accurate prediction of customer needs and wants, which is however a challenging issue due to the lack of smart analytics tools. This paper investigates this issue in depth and then develops a predictive analytic framework for integrating cloud computing, big data analysis, business informatics, communication technologies, and digital industrial production systems. Computational intelligence in the form of a cluster k-means approach is used to manage relevant big data for feeding potential customer needs and wants to smart designs for targeted productivity and customized mass production. The identification of patterns from big data is achieved with cluster k-means and with the selection of optimal attributes using genetic algorithms. A car customization case study shows how it may be applied and where to assign new clusters with growing knowledge of customer needs and wants. This approach offer a number of features suitable to smart design in realizing Industry 4.0

Solar Water Splitting Cells

No abstract

Steering the Smart Grid

Increasing energy prices and the greenhouse effect lead to more awareness of energy efficiency of electricity supply. During the last years, a lot of technologies and optimization methodologies were developed to increase the efficiency, maintain the grid stability and support large scale introduction of renewable sources. In previous work, we showed the effectiveness of our three-step methodology to reach these objectives, consisting of 1) offline prediction, 2) offline planning and 3) online scheduling in combination with MPC. In this paper we analyse the best structure for distributing the steering signals in the third step. Simulations show that pricing signals work as good as on/off signals, but pricing signals are more general. Individual pricing signals per house perform better with small prediction errors while one global steering signal for a group of houses performs better when the prediction errors are larger. The best hierarchical structure is to use consumption patterns on all levels except the lowest level and deduct the pricing signals in the lowest node of the tree

A co-operating solver approach to building simulation

This paper describes the co-operating solver approach to building simulation as encapsulated within the ESP-r system. Possible adaptations are then considered to accommodate new functional requirements

Business Case and Technology Analysis for 5G Low Latency Applications

A large number of new consumer and industrial applications are likely to change the classic operator's business models and provide a wide range of new markets to enter. This article analyses the most relevant 5G use cases that require ultra-low latency, from both technical and business perspectives. Low latency services pose challenging requirements to the network, and to fulfill them operators need to invest in costly changes in their network. In this sense, it is not clear whether such investments are going to be amortized with these new business models. In light of this, specific applications and requirements are described and the potential market benefits for operators are analysed. Conclusions show that operators have clear opportunities to add value and position themselves strongly with the increasing number of services to be provided by 5G.Comment: 18 pages, 5 figure