1,971 research outputs found

    Pubblicare uno scavo all’epoca di YouTube: comunicazione archeologica, narratività e video

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    Methodological reflection on communication in archaeology greatly developed over the past fifteen years. It is now widely accepted that video-narrative medium has a larger potential compared with other media commonly used up to now. The archaeological video can be divided into some different categories - documentary, video update, docudrama - each of them potentially destined to a variety of audiences when the movie is inserted into a narrative framework. By its nature, the archaeological site of Vignale, where the relative poverty of the remains on the ground sharply contrasts with the richness of the 'stories' the site itself can narrate, is an ideal place to test the docudrama-model video. Initially intended to be just an instrument for communicating with and involving local population in the archaeological project as a whole, the video-narrative proved to be a powerful tool in stimulating the research group itself towards a more thoughtful and 'multivocal' recording of the fieldwork done. The output of the project was the making of a brief 'series' of videos, with the general title of 'The Excavation and its Stories. They were initially used as an educational support for younger students in archaeology, but later obtained a wider audience through the web

    Trust within the Organizations of the New Economy: an Empirical Analysis of the Consequences of Institutional Uncertainty

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    This study investigates the effects of different institutional frameworks on the levels of trust within hierarchies. Following the insight into the changing of labour contracts provided by New Economy theorists and International Labour Organization [ILO] reports, this study investigates the possible differences in the levels of trust between two paradigms: the Old Economy and the New Economy. We argue that singular institutional changes which better characterize the New Economy in the form of environmental uncertainty set considerable constrains on trust development. By approaching trust as a dependent variable in a cross-industrial comparison, a questionnaire survey was carried out in Brazil accessing the levels of trust within seven Brazilian private companies. From the literature review and empirical observation of the reality of these organizations, companies were identified and classified into different groups. The study concludes that relative high institutional uncertainty considerably limits the development of trust levels within those companies operating in the New Economy

    Shrec'16 Track: Retrieval of Human Subjects from Depth Sensor Data

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    International audienceIn this paper we report the results of the SHREC 2016 contest on "Retrieval of human subjects from depth sensor data". The proposed task was created in order to verify the possibility of retrieving models of query human subjects from single shots of depth sensors, using shape information only. Depth acquisition of different subjects were realized under different illumination conditions, using different clothes and in three different poses. The resulting point clouds of the partial body shape acquisitions were segmented and coupled with the skeleton provided by the OpenNI software and provided to the participants together with derived triangulated meshes. No color information was provided. Retrieval scores of the different methods proposed were estimated on the submitted dissimilarity matrices and the influence of the different acquisition conditions on the algorithms were also analyzed. Results obtained by the participants and by the baseline methods demonstrated that the proposed task is, as expected, quite difficult, especially due the partiality of the shape information and the poor accuracy of the estimated skeleton, but give useful insights on potential strategies that can be applied in similar retrieval procedures and derived practical applications. Categories and Subject Descriptors (according to ACM CCS): I.4.8 [IMAGE PROCESSING AND COMPUTER VISION]: Scene Analysis—Shap
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