Abstract
In this study, a home energy management system structure is developed in order to determine the optimal commitment of a smart-household. Two types of loads are explicitly modeled: non-thermostatically controllable (electric vehicle, shiftable appliances) and thermostatically controllable loads (air conditioner, electric water heater). Furthermore, small-scale self-production is considered by means of a photovoltaic system. A test case using realistic data is presented in order to investigate the combined effect of the aforementioned assets under real-time pricing demand response.

Abstract

The number of available 3D digital objects has been increasing considerably. As such, searching in large collections has been subject of vast research. However, the main focus has been on algorithms and techniques for classification, indexing and retrieval. While some works have been done on query interfaces and results visualization, they do not explore natural interactions. The authors propose a speech interface for 3D object retrieval in immersive virtual environments. As a proof of concept, they developed the LS3D prototype, using the context of LEGO blocks to understand how people naturally describe such objects. Through a preliminary study, it was found that participants mainly resorted to verbal descriptions. Considering these descriptions and using a low cost visualization device, the authors developed their solution. They compared it with a commercial application through a user evaluation. Results suggest that LS3D can outperform its contestant, and ensures better performance and results perception than traditional approaches for 3D object retrieval.

Abstract

Abstract
Many combinatorial optimization problems (COPs) encountered in real-world logistics, transportation, production, healthcare, financial, telecommunication, and computing applications are NP-hard in nature. These real-life COPs are frequently characterized by their large-scale sizes and the need for obtaining high-quality solutions in short computing times, thus requiring the use of metaheuristic algorithms. Meta-heuristics benefit from different random-search and parallelization paradigms, but they frequently assume that the problem inputs, the underlying objective function, and the set of optimization constraints are deterministic. However, uncertainty is all around us, which often makes deterministic models oversimplified versions of real-life systems. After completing an extensive review of related work, this paper describes a general methodology that allows for extending metaheuristics through simulation to solve stochastic COPs. 'Simheuristics' allow modelers for dealing with real-life uncertainty in a natural way by integrating simulation (in any of its variants) into a metaheuristic-driven framework. These optimization-driven algorithms rely on the fact that efficient metaheuristics already exist for the deterministic version of the corresponding COP. Simheuristics also facilitate the introduction of risk and/or reliability analysis criteria during the assessment of alternative high-quality solutions to stochastic COPs. Several examples of applications in different fields illustrate the potential of the proposed methodology. (c) 2015 The Authors. Published by Elsevier Ltd.

Abstract
Adding to the modal description of transition structures the ability to refer to specific states, hybrid(ised) logics provide an interesting framework for the specification of reconfigurable systems. The qualifier 'hybrid(ised)' refers to a generic method of developing, on top of whatever specification logic is used to model software configurations, the elements of an hybrid language, including nominals and modalities. In such a context, this paper shows how a calculus for a hybrid(ised) logic can be generated from a calculus of the base logic and that, moreover, it preserves soundness and completeness. A second contribution establishes that hybridising a decidable logic also gives rise to a decidable hybrid(ised) one. These results pave the way to the development of dedicated proof tools for such logics used in the design of reconfigurable systems.

Abstract
Robotics constitutes a multidisciplinary area, congregating knowledge from different scientific domains. The learning of robotic systems requires the acquisition of multidisciplinary scientific bases, and high integration and synthesis abilities, which is not an easy task. This paper describes the implementation of a lifelong course that aims to provide a global insight on robotics field, introducing the concepts and technologies for different domain applications, namely industrial robotics, autonomous mobile robotics and robotics applied in medicine. This is accomplished in an international framework where individual knowledge and experiences will be confronted in a multidisciplinary level and intercultural environment.