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- ItemThe challenges in the development of technological research projects in generational gap contexts(DIGICOM - International Conference on Digital Design & Communication, 2020-11) Rodrigues, Rui; Melro, AnaThe generational differences that exist in a society or community are not only evidence that one cannot be escape, but a plus for its development. Furthermore, this allows an existence of a connection to the past and as a way of continuity for the future. However, and to increase this importance, the analysis of generational gaps is considered as an aspect that allows development, innovation and creativity, considering the specific context of the research project LOCUS - playfuL cOnneCted rUral territorieS. The article aims to contextualize the generational gaps in Amiais, Sever do Vouga, Portugal and is part of the LOCUS project. The LOCUS project has as main goal to carry out a survey of cultural heritage of the village, with the purpose of developing and apply an Internet of Things (IoT) system for use by residents, stakeholders and visitors. The methodology described in the article is the analysis of the ethnographic research results, namely interviews with privileged informants and informal conversations with residents. Based on these results, it is intended to outline the challenges that are expected to be found in the technological development of the project and the way as it is expected to outcome them.
- ItemA Prototype for Classification of Classical Music Using Neural Networks(Proceedings of the Eighth IASTED International Conference, 2004-09) Malheiro, Ricardo; Paiva, Rui Pedro; Mendes, A. J.; Mendes, T.; Cardoso, A.As a result of recent technological innovations, there has been a tremendous growth in the Electronic Music Distribution industry. In this way, tasks such us automatic music genre classification address new and exciting research challenges. Automatic music genre recognition involves issues like feature extraction and development of classifiers using the obtained features. As for feature extraction, we use features such as the number of zero crossings, loudness, spectral centroid, bandwidth and uniformity. These are statistically manipulated, making a total of 40 features. As for the task of genre modeling, we train a feedforward neural network (FFNN). A taxonomy of subgenres of classical music is used. We consider three classification problems: in the first one, we aim at discriminating between music for flute, piano and violin; in the second problem, we distinguish choral music from opera; finally, in the third one, we aim at discriminating between all five genres. Preliminary results are presented and discussed, which show that the presented methodology may be a good starting point for addressing more challenging tasks, such as using a broader range of musical categories.
- ItemClassification of Recorded Classical Music: a methodology and a comparative study(University of Stirling, 2004-09) Malheiro, Ricardo; Paiva, R. P.; Mendes, A. J.; Mendes, T.; Cardoso, A.As a result of recent technological innovations, there has been a tremendous growth in the Electronic Music Distribution industry. Consequently, tasks such as automatic music genre classification address new and exciting research challenges. Automatic music genre recognition involves issues like feature extraction and development of classifiers using the obtained features. We use the number of zero crossings, loudness, spectral centroid, bandwidth and uniformity for feature extraction. These features are statistically manipulated, making a total of 40 features. Regarding the task of genre modeling, we follow three approaches: the K-Nearest Neighbors (KNN) classifier, Gaussian Mixture Models (GMM) and feedforward neural networks (FFNN). A taxonomy of sub-genres of classical music is used. We consider three classification problems: in the first one, we aim at discriminating between music for flute, piano and violin; in the second problem, we distinguish choral music from opera; finally, in the third one, we seek to discriminate between all five genres. The best results were obtained using FFNNs: 85% classification accuracy in the three-class problem, 90% in the two-class problem and 76% in the five-class problem. These results are encouraging and show that the presented methodology may be a good starting point for addressing more challenging tasks.
- ItemA interactividade na esfera do Ciberjornalismo(SOPCOM, 2005) Amaral, InêsA tecnologia gera o campo cultural (Kerckhove, 1997). Com base nesta premissa, é objecto de estudo a transformação do campo comunicacional que se verifica com os novos media. Neste sentido, propõe-se a análise da alteração dos processos de produção e, consequentemente, de recepção de notícias introduzida pela interactividade. Parte-se do pressuposto de que a interacção é um elemento incontornável da própria comunicação mediada por computador, pelo que o novo paradigma da comunicação introduzido pela Cibercultura emerge como noção central na problematização a desenvolver. São elementos de análise: o novo cenário digital do Ciberjornalismo, as características dos novos media, a emergência da interactividade enquanto processo de comunicação, e os self media como extensão dos novos media.