Abstract
Electric drive vehicle technologies are being considered as possible solutions to mitigate environmental problems and fossil fuels dependence. Several studies have used life cycle analysis technique, to assess energy use and CO2 emissions, addressing fuels Well-to-Wheel life cycle or vehicle's materials Cradle-to-Grave. However, none has considered the required infrastructures for fuel supply. This study presents a methodology to evaluate energy use and CO2 emissions from construction, maintenance and decommissioning of support infrastructures for electricity and fossil fuel supply of vehicles applied to Portugal case study. Using Global Warming Potential and Cumulative Energy Demand, three light-duty vehicle technologies were considered: Gasoline, Diesel and Electric. For fossil fuels, the extraction well, platform, refinery and refuelling stations were considered. For the Electric Vehicle, the Portuguese 2010 electric mix, grid and the foreseen charging point's network were studied. Obtained values were 0.6-1.5 gCO(2eq)/km and 0.03-0.07 MJ(eq)/km for gasoline, 0.6-1.6 gCO(2eq)/km and 0.02-0.06 MJ(eq)/km for diesel, 3.7-8.5 gCO(2eq)/km and 0.06-0.17 MJ(eq)/km for EV. Monte Carlo technique was used for uncertainty analysis. We concluded that EV supply infrastructures are more carbon and energetic intensive. Contribution in overall vehicle LCA does not exceed 8%.

Abstract
A digital image correlation (DIC) algorithm for displacement measurements combining cross-correlation and a differential technique was validated through a set of experimental tests. These tests consisted of in-plane rigid-body translation and rotation tests, a tensile mechanical test, and a mode I fracture test. The fracture mechanical test, in particular, was intended to assess the accuracy of the method when dealing with discontinuous displacement fields, for which subset-based image correlation methods usually give unreliable results. The proposed algorithm was systematically compared with the Aramis (R) DIC-2D commercial code by processing the same set of images. When processing images from rigid-body and tensile tests (associated with continuous displacement fields), the two methods provided equivalent results. When processing images from the fracture mechanical test, however, the proposed method obtained a better qualitative description of the discontinuous displacements. Moreover, the proposed method gave a more reliable estimation of both crack length and crack opening displacement of the fractured specimen.(C) (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.OE.51.4.043602]

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.