A web-based platform for biosignal visualization and annotation

With the advent of wearable sensing and mobile technologies, biosignals have seen an increasingly growing number of application areas, leading to the collection of large volumes of data. One of the difficulties in dealing with these data sets, and in the development of automated machine learning systems which use them as input, is the lack of reliable ground truth information. In this paper we present a new web-based platform for visualization, retrieval and annotation of biosignals by non-technical users, aimed at improving the process of ground truth collection for biomedical applications. Moreover, a novel extendable and scalable data representation model and persistency framework is presented. The results of the experimental evaluation with possible users has further confirmed the potential of the presented framework.

Learning and Knowledge in the Context of Absorptive Capacity

Develop a new model of Absorptive Capacity taking into account two variables namely Learning and knowledge to explain how companies transform information into knowledge

Web 2.0 and its impact on knowledge and business organizations

Today, information overload and the lack of systems that enable locating employees with the right knowledge or skills are common challenges that large organisations face. This makes knowledge workers to re-invent the wheel and have problems to retrieve information from both internal and external resources. In addition, information is dynamically changing and ownership of data is moving from corporations to the individuals. However, there is a set of web based tools that may cause a major progress in the way people collaborate and share their knowledge. This article aims to analyse the impact of ‘Web 2.0’ on organisational knowledge strategies. A comprehensive literature review was done to present the academic background followed by a review of current ‘Web 2.0’ technologies and assessment of their strengths and weaknesses. As the framework of this study is oriented to business applications, the characteristics of the involved segments and tools were reviewed from an organisational point of view. Moreover, the ‘Enterprise 2.0’ paradigm does not only imply tools but also changes the way people collaborate, the way the work is done (processes) and finally impacts on other technologies. Finally, gaps in the literature in this area are outlined.

PHYLOViZ: phylogenetic inference and data visualization for sequence based typing methods

Background: With the decrease of DNA sequencing costs, sequence-based typing methods are rapidly becoming the gold standard for epidemiological surveillance. These methods provide reproducible and comparable results needed for a global scale bacterial population analysis, while retaining their usefulness for local epidemiological surveys. Online databases that collect the generated allelic profiles and associated epidemiological data are available but this wealth of data remains underused and are frequently poorly annotated since no user-friendly tool exists to analyze and explore it. Results: PHYLOViZ is platform independent Java software that allows the integrated analysis of sequence-based typing methods, including SNP data generated from whole genome sequence approaches, and associated epidemiological data. goeBURST and its Minimum Spanning Tree expansion are used for visualizing the possible evolutionary relationships between isolates. The results can be displayed as an annotated graph overlaying the query results of any other epidemiological data available. Conclusions: PHYLOViZ is a user-friendly software that allows the combined analysis of multiple data sources for microbial epidemiological and population studies. It is freely available at http://www.phyloviz.net.

Symbolic Knowledge Extraction from Trained Neural Networks Governed by Lukasiewicz Logics

This work describes a methodology to extract symbolic rules from trained neural networks. In our approach, patterns on the network are codified using formulas on a Lukasiewicz logic. For this we take advantage of the fact that every connective in this multi-valued logic can be evaluated by a neuron in an artificial network having, by activation function the identity truncated to zero and one. This fact simplifies symbolic rule extraction and allows the easy injection of formulas into a network architecture. We trained this type of neural network using a back-propagation algorithm based on Levenderg-Marquardt algorithm, where in each learning iteration, we restricted the knowledge dissemination in the network structure. This makes the descriptive power of produced neural networks similar to the descriptive power of Lukasiewicz logic language, minimizing the information loss on the translation between connectionist and symbolic structures. To avoid redundance on the generated network, the method simplifies them in a pruning phase, using the "Optimal Brain Surgeon" algorithm. We tested this method on the task of finding the formula used on the generation of a given truth table. For real data tests, we selected the Mushrooms data set, available on the UCI Machine Learning Repository.

Observação e controlo da segurança estrutural de barragens de betão: utilização integrada de modelos numéricos e de modelos de separação de efeitos

Dissertação de Natureza Científica elabora da no âmbito do protocolo de cooperação entre o ISEL e o LNEC para obtenção do grau de Mestre em Engenharia Civil

Repertório Contemporâneo como disciplina de desenvolvimento técnico e artístico

Relatório Final de Estágio apresentado à Escola Superior de Dança, com vista à obtenção do grau de Mestre em Ensino de Dança.

Impact of a training course on the quality of malaria diagnosis by microscopy in Angola

Background: In Angola, malaria is an endemic disease having a major impact on the economy. The WHO recommends testing for all suspected malaria cases, to avoid the presumptive treatment of this disease. In malaria endemic regions laboratory technicians must be very comfortable with microscopy, the golden standard for malaria diagnosis, to avoid the incorrect diagnosis. The improper use of medication promotes drug resistance and undesirable side effects. The present study aims to assess the impact of a three-day refresher course on the knowledge of technicians, quality of blood smears preparation and accuracy of microscopy malaria diagnosis, using qPCR as reference method. Methods: This study was implemented in laboratories from three hospitals in different provinces of Angola: Bengo, Benguela and Luanda. In each laboratory samples were collected before and after the training course (slide with thin and thick blood smears, a dried blood spot and a form). The impact of the intervention was evaluated through a written test, the quality of slide preparation and the performance of microscopy. Results: It was found a significant increase on the written test median score, from 52.5% to 65.0%. A total of 973 slides were analysed to evaluate the quality of thick and thin blood smears. Considering all laboratories there was a significant increase in quality of thick and thin blood smears. To determine the performance of microscopy using qPCR as the reference method we used 1,028 samples. Benguela presented the highest values for specificity, 92.9% and 98.8% pre and post-course, respectively and for sensitivity the best pre-course was Benguela (75.9%) and post-course Luanda (75.0%). However, no significant increase in sensitivity and specificity after the training course was registered in any laboratory analysed. Discussion: The findings of this study support the need of continuous refresher training for microscopists and other laboratory staff. The laboratories should have a quality control programme to supervise the diagnosis and also to assess the periodicity of new training. However, other variables needed to be considered to have a correct malaria diagnosis, such as adequate equipment and reagents for staining and visualization, good working conditions, motivated and qualified personnel.

ALSMon: sistema para monitorizar ALS

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Informática e de Computadores

Integrated didactics: an example of a curriculum model enhancing knowledge crossing

In this paper, we introduce an innovative course in the Portuguese Context, the Master's Course in “Integrated Didactics in Mother Tongue, Maths, Natural and Social Sciences”, taking place at the Lisbon School of Education and discussing in particular the results of the evaluation made by the students who attended the Curricular Unit - Integrated Didactics (CU-ID). This course was designed for in-service teachers of the first six years of schooling and intends to improve connections between different curriculum areas. In this paper, we start to present a few general ideas about curriculum development; to discuss the concept of integration; to present the principles and objectives of the course created as well as its structure; to describe the methodology used in the evaluation process of the above mentioned CU-ID. The results allow us to state that the students recognized, as positive features of the CU-ID, the presence in all sessions of two teachers simultaneously from different scientific areas, as well as invitations issued to specialists on the subject of integration and to other teachers that already promote forms of integration in schools. As negative features, students noted a lack of integrated purpose, applying simultaneously the four scientific areas of the course, and also indicated the need to be familiar with more models of integrated education. Consequently, the suggestions for improvement derived from these negative features. The students also considered that their evaluation process was correct, due to the fact that it was focused on the design of an integrated project for one of the school years already mentioned.