4 resultados para Data and Information Models

em Instituto Politécnico do Porto, Portugal


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Nowadays there is an increase of location-aware mobile applications. However, these applications only retrieve location with a mobile device's GPS chip. This means that in indoor or in more dense environments these applications don't work properly. To provide location information everywhere a pedestrian Inertial Navigation System (INS) is typically used, but these systems can have a large estimation error since, in order to turn the system wearable, they use low-cost and low-power sensors. In this work a pedestrian INS is proposed, where force sensors were included to combine with the accelerometer data in order to have a better detection of the stance phase of the human gait cycle, which leads to improvements in location estimation. Besides sensor fusion an information fusion architecture is proposed, based on the information from GPS and several inertial units placed on the pedestrian body, that will be used to learn the pedestrian gait behavior to correct, in real-time, the inertial sensors errors, thus improving location estimation.

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The aim of this study was to undertake a comparative analysis of the practices and information behaviour of European information users who visit information units specialising in European information in Portugal and Spain. The study used a quantitative methodology based on a questionnaire containing closed questions and one open question. The questions covered the general sociological profile of the respondents and their use of European Document Centres, in addition to analysing aspects associated with information behaviour relating to European themes. The study therefore examined data on the preferred means and sources for accessing European information, types of documents and the subjects investigated most. The use of European databases and the Internet to access material on Europe was also studied, together with the reasons which users considered made it easy or difficult to access European information, and the aspects they valued most in accessing this information. The questionnaire was administered in European Document Centres in 2008 and 2010.

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Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.

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We investigate whether the positive relation between accounting accruals and information asymmetry documented for U.S. stock markets also holds for European markets, considered as a whole and at the country level. This research is relevant because this relation is likely to be affected by differences in accounting standards used by companies for financial reporting, in the traditional use of the banking system or capital markets for firm financing, in legal systems and cultural environment. We find that in European stock markets discretionary accruals are positively related with the Corwin and Schultz high-low spread estimator used as a proxy for information asymmetry. Our results suggest that the earnings management component of accruals outweighs the informational component, but the significance of the relation varies across countries. Further, such association tends to be stronger for firms with the highest levels of positive discretionary accruals. Consistent with the evidence provided by the authors, our results also suggest that the high-low spread estimator is more efficient than the closing bid-ask spread when analysing the impact of information quality on information asymmetry.