• European University of Technology

Abstract The paper describes the outcome of a European research project called STEEDS (Scenario-based framework to modelling Transport technology deployment: Energy–Environment Decision Support). It is an advanced Decision Support System (DSS) able to assist the policy makers in exploring the influences on market take-up of different transport technologies under various exogenous scenarios and policy options and in assessing the energy and environmental impacts of these technology mixes. To implement the decision-making analysis a newly developed evaluation methodology has been integrated into the DSS. The method, called NAIADE, allows decision-makers to evaluate complex choices on the basis of enhanced access to information of different types.

Research indicates that aerosol optical thickness (AOT) values and particulate matter (PM10) measurements can be used as indicators of atmospheric pollution. The problem of relating AOT with suspended particulate matter near the ground is still an open question. While satellite images can provide reliable and synoptic measurements from space, comparisons with monitoring surface level air pollution continues to be a challenge since satellite measurements are column integrated quantities. In this study, in-situ spectroradiometric measurements were taken during satellite overpass using field spectrometers to obtain the reflectance values of the calibration targets used. Sun photometer measurements were taken with the Microtops hand-held sun photometer to measure AOT. Meteorological data was collected from nearby meteorological stations and PM10 measurements were collected from local mobile air pollution stations. Following, the darkest pixel method of atmospheric correction was applied to a series of Landsat satellite images. The reflectance values of the atmospherically-corrected image were used in the radiative transfer equation to solve for AOT. Thematic maps were generated in order to develop air quality indices. The image-derived AOT values were examined for a positive correlation with PM10 measurements. It appears there exists a significant correlation between AOT and PM10 measurements. 2012 SPIE.

Factor analysis examines the inter-correlations that exist between a large number of items (questionnaire responses) and in doing so reduces the items into smaller groups, known as factors. These factors contain correlated variables and are typically quite similar in terms of content or meaning. Unlike other methods discussed in this book, exploratory factor analysis (EFA) does not discriminate between variables on whether they are independent or dependent, but rather it is an interdependence technique that does not specify formal hypotheses. It is in this sense it is ‘exploratory’ in nature as it allows the researcher to determine the underlying dimensions or factors that exist in a set of data. The technique is particularly useful for managerial or academic research in reducing items into discrete dimensions that can be summed or aggregated and subsequently used as input for further multivariate analysis such as multiple regression. It is also used extensively in scale development research to condense a large item pool into a more succinct, reliable and conceptually sound measurement instrument. Factor analytic techniques can typically be classified as either exploratory or confirmatory and the former of these is addressed within this chapter using a research example to demonstrate it's use.

In the last few years the investments in PV plants have managed a fast growth of the installed power, especially on grid systems. Most of PV plants are located close to cities or villages, producing for local consumers. The interest in reducing the environmental impact caused by tailpipe emissions in big towns represents a worldwide problem. Electricity production, using solar energy, can achieve a long-term vision of reducing the tailpipe environmental impact. The paper analyzes the use of the PV systems as auxiliary power generators for hybrid and electric vehicles and especially for electric bicycles and electric scooters. Also, it presents a solution to integrate the PV systems in large cities. The incorporation of PV systems into the charging system of electric bicycles and electric scooters, as an alternative of using a car daily helps to reduce the overall amount of fuel consumed. In addition, PV systems are light, noiseless, and maintenance-free.

The focus of this paper is on the comparison of multiple neural network frameworks and the their usage in 2D/3D robot perception applications. Numerous frameworks exists for this task including the recent deep learning based ones, which allow us to develop a perception system, with the chosen parameters for object recognition. In this paper we analyzed the possible solutions, including different Convolutional Neural Networks (CNNs) variants. The advantages of 2D CNNs linked with 3D features lead to another approach, which can be extended further. The leading idea is to create a custom object recognition method that takes advantage of a 2D system's precision and speed, but it can efficiently incorporate 3D features. This way, the disturbances specific to each method separately can be minimized. On the other hand, this is a lightweight solution, that is supposed to be tolerated by less powerful processing units as well. By placing 3D bounding boxes around detected objects, the convenience of the 2D detection methods can be integrated in a 3D metric world.

We investigate the risk–return trade-off on the US and European stock markets. We investigate the non-linear risk–return trade-off with a special eye to the tails of the stock returns using quantile regressions. We first consider the US stock market portfolio. We find that the risk–return trade-off is significantly positive at the upper tail (0.9 quantile), where the upper tail is large positive excess returns. The positive trade-off is as expected from asset pricing models. For the lower tail (0.1 quantile), that is for large negative stock returns, the trade-off is significantly negative. Additionally, for the median (0.5 quantile), the risk–return trade-off is insignificant. These results are recovered for the US industry portfolios and for Eurozone stock market portfolios.

[ESP] En el presente estudio, las principales toxinas producidas por el dinoflagelado Prorocentrum belizeanum (Ácido okadaico, DTX-5c y 7- hidroximetil-2-metilen-octa-4,7-dienil okadaato) fueron analizadas en un sistema de cromatografía líquida acoplado a espectrometría de masas (LC- MS), lo que permitió determinar los tiempos de retención (tR) respectivos y los patrones de fragmentación asociados. Como una muestra de la aplicabilidad de la metodología empleada, diversas muestras provenientes de cultivos in vitro de P. belizeanum fueron analizadas. Los autores agradecen el financiamiento del MEC (AGL2005- 07924-C04-01 y 02/ALI), VALBIOMAR, ICIC (PGC) y CajaCanarias (JGN). La cepa de P. belizeanum fue facilitada por el Dr. S. Fraga, del CCVIEO (Vigo, España).

Yttria–zirconia ceramics in various compositions of Y2O3 and SiO2 were synthesized by a high temperature solid state reaction process in alumina crucibles at 1400°C for 2 h. The obtained samples we...

We combine low loss, perfluorinated polymer optical fibre and femtosecond-laser, direct-write methods to inscribe Bragg grating arrays operating in the 1500-nm wavelength window for dynamic strain sensing and compare with silica optical fibre.

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