Abstract

Abstract
Although spreadsheets can be seen as a flexible programming environment, they lack some of the concepts of regular programming languages, such as structured data types. This can lead the user to edit the spreadsheet in a wrong way and perhaps cause corrupt or redundant data. We devised a method for extraction of a relational model from a spreadsheet and the subsequent embedding of the model back into the spreadsheet to create a model-based spreadsheet programming environment. The extraction algorithm is specific for spreadsheets since it considers particularities such as layout and column arrangement. The extracted model is used to generate formulas and visual elements that are then embedded in the spreadsheet helping the user to edit data in a correct way. We present preliminary experimental results from applying our approach to a sample of spreadsheets from the EUSES Spreadsheet Corpus. © 2012 Springer-Verlag.

Abstract
Nowadays, Informed Driving is crucial to the transportation industry. We present an online recommendation model to help the driver to decide about the best stand to head in each moment, minimizing the waiting time. Our approach uses time series forecasting techniques to predict the spatiotemporal distribution in real-time. Then, we combine this information with the live current network status to produce our output. Our online test-beds were carried out using data obtained from a fleet of 441 vehicles running in the city of Porto, Portugal. We demonstrate that our approach can be a major contribution to this industry: 395.361/506.873 of the services dispatched were correctly predicted. Our tests also highlighted that a fleet equipped with such framework surpassed a fleet that is not: they experienced an average waiting time to pick-up a passenger 5% lower than its competitor.

Abstract
Sports simulation can help to assess the performance of strategies and players in a sand-boxed environment. Ultimately it can lead to improved real-life performance of actual teams if it is able to provide useful information to the team coach or manager. Many tools are now available for many different sports, most notably Soccer Server Simulator, a soccer simulator, that has already attracted many researchers from the artificial intelligence community into developing intelligent agents (soccer players) for them to form teams to play against each other in simulated matches. This paper presents a methodology for developing agents for testing and further developing the Handball Sport Simulator, which is based on the Soccer Server Simulator. The main contribution of this work is to provide a basic, expandable, agent architecture, specifically capable of playing at a Handball Sport Simulator server, while at the same time testing what features and sport's rules of the Handball Sport Simulator have been implemented correctly.

Abstract
A spatial optical filter based on a hollow-core silica tube is proposed. Because of the hollow-core dimensions, it is possible to obtain a periodical spatial filter ranging from 1200 to 1700 nm with a channel spacing of 2.64 THz. The bandwidth is approximately 5.32 nm, and the isolation loss is similar to 30 dB. The optical losses are approximately similar to 0.67 dB/mm for a wavelength of 1500 nm. The 40 mm long spatial optical filter is tested as a sensing element and subjected to different physical parameters. The spatial optical filter is wavelength sensitive to strain and temperature, while for refractive-index variations there is an optical power dependency. This fiber structure can be used as a sensing element for extreme conditions, such as in very high temperature environments, where it presents a sensitivity of 27.5 pm degrees C-1. (C) 2012 Optical Society of America

Abstract
Hydrogen and electric vehicle technologies are being considered as possible solutions to mitigate environmental burdens and fossil fuel dependency. Life cycle analysis (LCA) of energy use and emissions has been used with alternative vehicle technologies to assess the Well-to-Wheel (WTW) fuel cycle or the Cradle-to-Grave (CTG) cycle of a vehicle's materials. Fuel infrastructures, however, have thus far been neglected. This study presents an approach to evaluate energy use and CO2 emissions associated with the construction, maintenance and decommissioning of energy supply infrastructures using the Portuguese transportation system as a case study. Five light-duty vehicle technologies are considered: conventional gasoline and diesel (ICE), pure electric (EV), fuel cell hybrid (FCHEV) and fuel cell plug-in hybrid (FC-PHEV). With regard to hydrogen supply, two pathways are analysed: centralised steam methane reforming (SMR) and on-site electrolysis conversion. Fast, normal and home options are considered for electric chargers. We conclude that energy supply infrastructures for FC vehicles are the most intensive with 0.03-0.53 MJ(eq)/MJ emitting 0.7-27.3 g CO2eq/MJ of final fuel. While fossil fuel infrastructures may be considered negligible (presenting values below 2.5%), alternative technologies are not negligible when their overall LCA contribution is considered. EV and FCHEV using electrolysis report the highest infrastructure impact from emissions with approximately 8.4% and 8.3%, respectively. Overall contributions including uncertainty do not go beyond 12%. Copyright