Abstract
This study presents a method to measure the displacement fields on the surface of planar objects with sub-pixel resolution, by combining image correlation with a differential technique. First, a coarse approximation of the pixel level displacement is obtained by cross-correlation (CC). Two consecutive images, taken before and after the application of a given deformation, are recursively split in sub-images, and the CC coefficient is used as the similarity measure. Secondly, a fine approximation is performed to assess the sub-pixel displacements by means of an optical flow method based on a differential technique. To validate the effectiveness and robustness of the proposed method, several numerical tests were carried out on computer-generated images. Moreover, real images from a static test were also processed for estimating the displacement resolution. The results were compared with those obtained by a commercial digital image correlation code. Both methods showed similar and reliable results according to the proposed tests.

Abstract
We aim to analyze the current problems and the main difficulties encountered by information systems and information technologies managers, featuring different actors and how they relate. This work introduces a design pattern, a fact table, for management and decision support, named CRUDI Table. The CRUDI Table is an abstraction idealized from the CRUD Matrix concept extended by an extra dimension: the importance dimension.

Abstract
We consider the. re-scaled PSI20 daily index positive returns r(t)(alpha) and negative returns (-r(t))(alpha) called, after normalization, the. positive and negative fluctuations, respectively. We use the Kolmogorov-Smirnov statistical test as a method to find the values of alpha that optimize the data collapse of the histogram of the. fluctuations with the truncated Bramwell-Holdsworth-Pinton (BHP) probability density function (pdf) fBHP and the truncated generalized log-normal pdf fLN that best approximates the truncated BHP pdf. The optimal parameters we found are alpha(+)(BHP) = 0.48, alpha(-)(BHP) = 0.46, alpha(+)(LN) = 0.50 and alpha(-)(LN) = 0.49. Using the optimal alpha's we compute the analytical approximations of the pdf of the normalized positive and negative PSI20 index daily returns r(t). Since the BHP probability density function appears in several other dissimilar phenomena, our result reveals a universal feature of the stock exchange markets.

Abstract
In this work we present XMuSer, a multi-relational framework suitable to explore temporal patterns available in multi-relational databases. XMuSer's main idea consists of exploiting frequent sequence mining, using an efficient and direct method to learn temporal patterns in the form of sequences. Grounded on a coding methodology and on the efficiency of sequential miners, we find the most interesting sequential patterns available and then map these findings into a new table, which encodes the multi-relational timed data using sequential patterns. In the last step of our framework, we use an ILP algorithm to learn a theory on the enlarged relational database that consists on the original multi-relational database and the new sequence relation. We evaluate our framework by addressing three classification problems. Moreover, we map each one of three different types of sequential patterns: frequent sequences, closed sequences or maximal sequences.

Abstract
A Temperature-independent strain sensor based on Four-Wave Mixing (FWM) using Raman fiber Bragg grating (FBG) laser sensor with cooperative Rayleigh scattering is proposed. Two FBG were used to form two linear cavities laser sensors based on Raman amplification combined with cooperative Rayleigh scattering. Due to the low dispersion coefficient of the fiber, it is possible to obtain the FWM using the two Raman FBG laser sensors. This configuration allows the operation as a temperature-independent strain sensor where both sensors are sensitive to temperature but only one of the FBG is sensitive to strain. The FWM efficiency is thus dependent on the applied strain but independent to the temperature.

Abstract
In this work a self-referencing fiber optic intensity sensor using virtual instrumentation is presented. To ensure higher flexibility and dynamic optimization, the use of an optical fiber delay line or an electrical delay line is avoided by implementing a delay line in the virtual domain, preserving the self-referencing and sensitivity characteristics of the proposed optical intensity sensing structure. Results are presented where displacement is measured with an 18 mu m resolution demonstrating the concept feasibility.