Abstract
Agile methodology as a relatively new approach to software engineering is becoming more popular in both industry and academia. Learning agile software development methodologies will unquestionably increase the capabilities and competences of our students as entry-level software engineers. However, how agile methods and techniques should be taught at the undergraduate level in additional to traditional approaches is still being debated. This study was conducted on a studentprogramming project, with sample size of 23 students from the Informatics Engineering course. The Scrum methodology was adopted and 28 user stories and 4 sprints were created. The results indicate a significant impact on students’ skill improvement and let them to have the first contact with real projects and clients. Besides that, the students agree that the adoption of the Scrum methodology helped them to improve the participation and collaboration. However, some issues were also detected in terms of communication and tasks planning. Therefore, we proposed some polities that could help and boost the software development process inside a classroom.

Abstract
An optical fiber sensor based on a tapered-FBG coated with 150 nm-thick Pd film is proposed for hydrogen pressure detection. The FBG was written in a 50 µm-diameter tapered fiber by DUV femtosecond laser technology. A second FBG was inscribed in the untapered fiber region for temperature compensation. The sensing head was able to detect the variation of hydrogen pressure in the range 0-780 kPa and a maximum sensitivity of 0.15 pm/kPa was achieved. © 2012 OSA.

Abstract
Eukaryotic cells make many types of primary and processed RNAs that are found either in specific subcellular compartments or throughout the cells. A complete catalogue of these RNAs is not yet available and their characteristic subcellular localizations are also poorly understood. Because RNA represents the direct output of the genetic information encoded by genomes and a significant proportion of a cell's regulatory capabilities are focused on its synthesis, processing, transport, modification and translation, the generation of such a catalogue is crucial for understanding genome function. Here we report evidence that three-quarters of the human genome is capable of being transcribed, as well as observations about the range and levels of expression, localization, processing fates, regulatory regions and modifications of almost all currently annotated and thousands of previously unannotated RNAs. These observations, taken together, prompt a redefinition of the concept of a gene.

Abstract
Mobile mapping is a multidisciplinary technique which requires several dedicated equipment, calibration procedures that must be as rigorous as possible, time synchronization of all acquired data and software for data processing and extraction of additional information. To decrease the cost and complexity of Mobile Mapping Systems (MMS), the use of less expensive sensors and the simplification of procedures for calibration and data acquisition are mandatory features. This article refers to the use of MMS technology, focusing on the main aspects that need to be addressed to guarantee proper data acquisition and describing the way those aspects were handled in a terrestrial MMS developed at the University of Porto. In this case the main aim was to implement a low cost system while maintaining good quality standards of the acquired georeferenced information. The results discussed here show that this goal has been achieved.

Abstract
There has been increasing interest in pattern classification methods and neuroimaging studies using permutation tests to estimate the statistical significance of a classifier (p-value). Permutation tests usually use the test error as a dataset statistic to estimate the p-value(s) by measuring the dissimilarity between two or more populations. Using the test error as a dataset statistic; however, may camouflage the lowest recognizable classes, and the resulting p-value will be biased toward better values (usually lower values) because of the highly recognizable classes; thus, lower p-values could sometimes be the result of undercoverage. In this study, we investigate this problem and propose the implementation of permutation tests based on a per-class test error as a dataset statistic. We also propose a model that is based on partially scrambling the testing samples (in this model, the training samples are not scrambled) when computing the non-permuted statistic in order to judge the p-value's tolerance and to draw conclusions regarding, which permutation test procedures are more reliable. For the same purpose, we propose another model that is based on chance-level shifting of the permuted statistic. We tested these two proposed models on functional magnetic resonance imaging data that were collected while human subjects responded to visual stimulation paradigms, and our results showed that these models can aid in determining, which permutation test procedure is superior. We also found that permutation tests that use a per-class test error as a dataset statistic are more reliable in addressing the null hypothesis that all classes in the problem domain are drawn from the same distribution.

Abstract
Hand gesture recognition for human computer interaction is an area of active research in computer vision and machine learning. The primary goal of gesture recognition research is to create a system, which can identify specific human gestures and use them to convey information or for device control. This paper presents a comparative study of four classification algorithms for static hand gesture classification using two different hand features data sets. The approach used consists in identifying hand pixels in each frame, extract features and use those features to recognize a specific hand pose. The results obtained proved that the ANN had a very good performance and that the feature selection and data preparation is an important phase in the all process, when using low-resolution images like the ones obtained with the camera in the current work.