Nowadays, the greatest part of the effort to reduce pollution emissions is directed toward the hybridization of automotive drive trains. In particular, the design of hybrid vehicles requires a complete system analysis, including the optimization of the electric and electronic devices installed on the vehicle and the design of all the mechanical connections between the different power sources to reach the required performances. The aim of this paper is to describe the design and prototype realization of a plug-in hybrid electrical vehicle (PHEV). Specifically, an energetic model was developed in order to analyze and optimize the power flux between the different parts. This model was experimentally validated using a prototype PHEV. In addition, in order to improve the driving range in an all-electric model (all-electric range), a detailed analysis of the inverter control was performed, because this component is one of the key components of the power train. In order to reduce inverter losses and dimensions, several control methods can be adopted. In this paper, a direct self-control strategy for reducing the inverter losses is presented and validated

We explore the practical feasibility of a system based on genetic programming (GP) for the automatic generation of regular expressions. The user describes the desired task by providing a set of labeled examples, in the form of text lines. The system uses these examples for driving the evolutionary search towards a regular expression suitable for the specified task. Usage of the system should require neither familiarity with GP nor with regular expressions syntax. In our GP implementation each individual represents a syntactically correct regular expression. We performed an experimental evaluation on two different extraction tasks applied to realworld datasets and obtained promising results in terms of precision and recall, even in comparison to an earlier stateof-the-art proposal.

Smart monitoring systems are currently gaining more attention and are being employed in several technological areas. These devices are particularly appreciated in the structural field, where the collected data are used with purposes of real time alarm generation and remaining fatigue life estimation. Furthermore, monitoring systems allow one to take advantage of predictive maintenance logics that are nowadays essential tools for mechanical and civil structures. In this context, a smart wireless node has been designed and developed. The sensor node main tasks are to carry out accelerometric measurements, to process data on-board, and to send wirelessly synthetic information. A deep analysis of the design stage is carried out, both in terms of hardware and software development. A key role is played by energy harvesting integrated in the device, which represents a peculiar feature and it is thanks to this solution and to the adoption of low power components that the node is essentially autonomous from an energy point of view. Some prototypes have been assembled and tested in a laboratory in order to check the design features. Finally, a field test on a real structure under extreme weather conditions has been performed in order to assess the accuracy and reliability of the sensors.

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Flash-flood events in mountain basins often involve large volumes of sediment transported by the rivers, with significant changes in the bed morphology even within a single, short-term event. By contrast, flood scenarios are most frequently devised under the assumption of a fixed-bed condition, that is, neglecting the possible change of the river bed elevation during the reference flood. In this work, feasibility and positive outcome of incorporating sediment transport modelling into the evaluation of flood hazard are assessed with reference to the case of the Mallero River in northern Italy.A past flood event has been modelled by means of a fully coupled model of flow and sediment transport. Particular attention has been focused onto the town of Sondrio, located at the downstream end of the river. Results show that interpretation of the event dynamics and proper quantification of flood hazard for the town cannot be obtained without considering the morphologic evolution of the river bed due to sediment transport. In addition, reliability of the results of hydro-morphologic modelling has been proved by extensive sensitivity analysis, showing a weak dependence of the findings on external forcing. Some arguments are thus provided towards the incorporation of morphologic processes into hazard assessment, landscape protection, scenario modelling and emergency management

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