Abstract
The art of telling stories in digital format is currently widely available due to the popularization of digital cameras, computers and other mobile devices. In this paper we discuss the use of collaborative learning strategies based on Digital Storytelling in corporative training. The text includes a concise review on theoretical and technical foundations about educational communication through the use of audiovisual products based on disciplines such as Communication, Education and Cognitive Sciences. We will also discuss how Digital Storytelling may be integrated in traditional contents oriented self-training systems, used by many corporations. However the main focus will be the discussion of the potential of the use of Digital Storytelling methodology in corporative training context which will be detailed based on data collected in scenarios from Portugal and Brazil. The paper is based on qualitative research and it will argue that digital storytelling may contribute to the improvement of the effectiveness of collaborative learning processes in corporative training, because it provides means for the swift delivery of highly contextualized learning materials and the sharing of relevant personal trainers and trainees’ experiences. Furthermore, Digital Storytelling methodology provides an opportunity to value, respect and promote the multiple and different cultural and social interactions in the corporative knowledge construction process. The research methodology adopted on this study involved three phases: 1) literature review; 2) detailed analysis of the digital Storytelling methodology and its implications in corporative training context; 3) collecting data from and discussing about some corporative cases in Portugal and Brazil. The result of the research aims at suggesting a critical analysis and creative attitude in the production of audiovisual teaching materials for the corporative training context.

Abstract
O potencial dos testemunhos pessoais em educação tem recolhido o interesse de muitos investigadores e profissionais do sector dado a riqueza desses materiais para promoverem aprendizagens significativas. No entanto esse potencial ainda necessita de ser explorado em contexto de formação empresarial, em que ainda são mal conhecidos os desafios e soluções para as várias questões relevantes, entre as quais: organização e estrutura dos materiais de formação; requisitos de produção; dinâmicas de formação; avaliação de resultados. Estudar, dos pontos de vista conceptual e de implementação, estas questões foi a principal motivação de um projeto de investigação realizado em parceria pela unidade de investigação CETAC.MEDIA da Universidade de Aveiro e a empresa PT Inovação S.A., que teve como contexto de estudo o portal de Objetos de Aprendizagem COLOR em desenvolvimento na empresa.

Abstract
Finding an effective control interface to manipulate complex geometric objects has traditionally relied on experienced users to place the animation controls. This process, whether for key framed or for motion captured animation, takes a lot of time and effort. We introduce a novel sketching interface control system inspired in the way artists draw, in which a stroke defines the shape of an object and reflects the user's intention. We also introduce the canvas, a 2D drawing region where the users can make their strokes, which determines the domain of interaction with the object. We show that the combination of strokes and canvases provides a new way to manipulate the shape of an implicit volume in space. And most importantly, it is independent from the 3D model rig. The strokes can be easily stored and reused in other characters, allowing retargeting of poses. Our interactive approach is illustrated using facial models of different styles. As a result, we allow rapid manipulation of 3D faces on the fly in a very intuitive and interactive way. Our informal study showed that first time users typically master the system within seconds, creating appealing 3D poses and animations in just a few minutes. © 2011 ACM.

Abstract
Good design and implementation are necessary but not sufficient pre-requisites for successfully reusing object-oriented frameworks. Although not always recognized, good documentation is crucial for effective framework reuse, and often hard, costly, and tiresome, coming with many issues, especially when we are not aware of the key problems and respective ways of addressing them. Based on existing literature, case studies and lessons learned, the authors have been mining proven solutions to recurrent problems of documenting object-oriented frameworks, and writing them in pattern form, as patterns are a very effective way of communicating expertise and best practices. This paper presents a small set of patterns addressing problems related to the framework documentation itself, here seen as an autonomous and tangible product independent of the process used to create it. The patterns aim at helping non-experts on cost-effectively documenting object-oriented frameworks. In concrete, these patterns provide guidance on choosing the kinds of documents to produce, how to relate them, and which contents to include. Although the focus is more on the documents themselves, rather than on the process and tools to produce them, some guidelines are also presented in the paper to help on applying the patterns to a specific framework. © 2011 Springer-Verlag Berlin Heidelberg.

Abstract

Abstract
In real-world information retrieval systems, the underlying document collection is rarely stable or definitive. This work is focused on the study of signals extracted from the content of documents at different points in time for the purpose of weighting individual terms in a document. The basic idea behind our proposals is that terms that have existed for a longer time in a document should have a greater weight. We propose 4 term weighting functions that use each document's history to estimate a current term score. To evaluate this thesis, we conduct 3 independent experiments using a collection of documents sampled from Wikipedia. In the first experiment, we use data from Wikipedia to judge each set of terms. In a second experiment, we use an external collection of tags from a popular social bookmarking service as a gold standard. In the third experiment, we crowdsource user judgments to collect feedback on term preference. Across all experiments results consistently support our thesis. We show that temporally aware measures, specifically the proposed revision term frequency and revision term frequency span, outperform a term-weighting measure based on raw term frequency alone.