2009
Authors
Carvalho, G; de Matos, DM; Rocio, V;
Publication
EVALUATING SYSTEMS FOR MULTILINGUAL AND MULTIMODAL INFORMATION ACCESS
Abstract
IdSay is an open domain Question Answering (QA) system for Portuguese. Its current version can be considered a baseline version, using mainly techniques from the area of Information Retrieval (IR). The only external information it uses besides the text. collections is lexical information for Portuguese. It was submitted to the monolingual Portuguese task of the QA track of the Cross-Language Evaluation Forum 2008 (QA@CLEF) for the first time, and it answered correctly to 65 of the 200 questions in the first answer, and to 85 answers considering the three answers that could be returned per question. Generally, the types of questions that are answered better by IdSay system are measure factoids, Count factoids and definitions, but there is still work to be done in these areas, as well as in the treatment of time. List questions, location and people/organization factoids are the types of question with more room for improvement.
2009
Authors
Mamede, HS; Amaral, L;
Publication
INFORMATION SYSTEMS - CREATIVITY AND INNOVATION IN SMALL AND MEDIUM-SIZED ENTERPRISES
Abstract
The World Wide Web technology, supported on Internet, is transforming all business activities into information-based activities. As a result, one can see a radical change in the traditional theoretical models and organisation. The small and medium enterprises (SME) are the type of enterprises that can reap more advantages with the usage of Internet for electronic business. We found that current methodologies present gaps which make them inadequate and unable to help the small and medium enterprises define an effective strategy and follow an plausible implementation path. This being so, we propose a methodology to support the complete implementation lifecycle of electronic business in small and medium enterprises. © IFIP International Federation for Information Processing 2009.
2009
Authors
Mamede, HS; Santos, V;
Publication
INFORMATION SYSTEMS - CREATIVITY AND INNOVATION IN SMALL AND MEDIUM-SIZED ENTERPRISES
Abstract
Considering that the capacity to innovate is increasingly becoming a decisive factor in the competition between organisations, the study and conception of systems that help the birth of new ideas, products and solutions is rising in importance. In this article, the authors consider the concept of Creative Information Systems and present a proposal for the development of architecture for such a system based on the creative technique of brute thinking.
2009
Authors
Fatichi, S; Barbosa, SM; Caporali, E; Silva, ME;
Publication
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
Abstract
The detection of a trend in a time series and the evaluation of its magnitude and statistical significance is an important task in geophysical research. This importance is amplified in climate change contexts, since trends are often used to characterize long-term climate variability and to quantify the magnitude and the statistical significance of changes in climate time series, both at global and local scales. Recent studies have demonstrated that the stochastic behavior of a time series can change the statistical significance of a trend, especially if the time series exhibits long-range dependence. The present study examines the trends in time series of daily average temperature recorded in 26 stations in the Tuscany region (Italy). In this study a new framework for trend detection is proposed. First two parametric statistical tests, the Phillips-Perron test and the Kwiatkowski-Phillips-Schmidt-Shin test, are applied in order to test for trend stationary and difference stationary behavior in the temperature time series. Then long-range dependence is assessed using different approaches, including wavelet analysis, heuristic methods and by fitting fractionally integrated autoregressive moving average models. The trend detection results are further compared with the results obtained using nonparametric trend detection methods: Mann-Kendall, Cox-Stuart and Spearman's rho tests. This study confirms an increase in uncertainty when pronounced stochastic behaviors are present in the data. Nevertheless, for approximately one third of the analyzed records, the stochastic behavior itself cannot explain the long-term features of the time series, and a deterministic positive trend is the most likely explanation.
2009
Authors
Barbosa, SM; Silva, ME; Fernandes, MJ;
Publication
THEORETICAL AND APPLIED CLIMATOLOGY
Abstract
Atmospheric pressure varies within a wide range of scales and thus a multi-scale description of its variability is particularly appealing. In this study, a scale-by-scale analysis of the global sea-level pressure field is carried out from reanalysis data. Wavelet-based analysis of variance is applied in order to describe the variability of the pressure field in terms of patterns representing the contribution of each scale to the overall variance. Signals at the seasonal scales account for the largest fraction of sea-level pressure variance (typically more than 60%) except in the Southern Ocean, in the Equatorial Pacific and in the North Atlantic. In the Southern Ocean and over the North Atlantic, high-frequency signals contribute to a considerable fraction (30-50%) of the overall variance in sea-level pressure. In the Equatorial Pacific, large-scale variability, associated with ENSO, contributes up to 40% of the total variance.
2009
Authors
Barbosa, SM; Silva, ME;
Publication
ESTUARINE COASTAL AND SHELF SCIENCE
Abstract
Long-term sea-level variability in Chesapeake Bay is examined from long tide gauge records in order to assess the influence of climate factors on sea-level changes in this complex estuarine system. A time series decomposition method based on autoregression is applied to extract flexible seasonal and low-frequency components from the tide gauge records, allowing to analyse long-term sea-level variability not only by estimating linear trends from the records, but also by examining fluctuations in seasonal and long-term patterns. Long-term sea-level variability in Chesapeake Bay shows considerable decadal variability. At the annual scale, variability is mainly determined by atmospheric factors, specifically atmospheric pressure and zonal wind, but no systematic trends are found in the amplitude of the annual cycle. On longer time scales, precipitation rate, a proxy for river discharge, is the main factor influencing decadal sea-level variability. Linear trends in relative sea-level heights range from 2.66 +/- 0.075 mm/year (at Baltimore) to 4.40 +/- 0.086 mm/year (at Hampton Roads) for the 1955-2007 period. Due to the gentle slope of most of the bay margin, a sea-level increase of this magnitude poses a significant threat in terms of wetland loss and consequent environmental impacts.
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