Seeing into the past: integrating 3D documentation and non-invasive prospecting methods for the analysis, understanding and reconstruction of the ancient Pompeii. The case of the House of Obellio Firmo (IX, 14)

In 2015 the Department of History and Cultures of the Bologna University took part in the Grande Progetto Pompei - Piano della Conoscenza, with the task of providing a modern and complete documentation of the so-called Lotto 3 in Pompeii. The new survey was carried out by means of integrated innovative diagnostic survey techniques in order to provide a total documentary research of the whole sector. In 2016 a new project was started in agreement with the competent Superintendency, and focused on the study and preservation of the House of Obellio Firmo, included in the Lotto 3 of the Roman city. The new research contemplates an in-depth analysis of the building, employing systematic laser scanning and photogrammetry methods to generate an accurate 3D model of the house. This model is going to constitute the starting point for the further analysis of the wall stratigraphies and for the mapping and monitoring of the structures’ state of decay. The full-scale analytical documentation of the building also includes a detailed geophysical mapping of all the accessible domestic spaces, by using the ground penetrating radar technique. The preliminary results achieved by the non-invasive prospecting survey, integrated with the analysis of the surviving walls and building techniques, supply valid information for the archaeological interpretation of the house’s history. In order to allow the management and sharing of the information collected, the data are going to be organised within a building information model (BIM) with a triple objective: the reconstruction of a fragment of the ancient urban landscape in Pompeii during the oldest phase, with particular attention directed to the Samnitic period; the outlining of a precise strategy of intervention for the restoration and preservation of the House of Obellio Firmo; the re-opening of the building to sightseeing tours and its restitution to public use

Dynamic User Modeling for Personalized Advertisement Delivery on Mobile Devices

With the advent of broadband connections, the Internet service providers have begun to charge users with fees in order to cover the higher infrastructural costs due to the management/rental of broadband networks. However, the user is often left the chance for a free Internet connection, provided that he/she accepts to be invaded by banner ads, which arbitrarily, in terms of time and position, appear on the screen. In order to make effective the latter approach, the Internet service providers have been studying the most appropriate advertisement (ad, for short) supply policy, in order to satisfy companies who wish to advertise their products without annoying the user while he/she is interacting with the service. Personalized delivery of ads is recognized to be a promising approach to capture users’ interests in certain domains. However, further attention still deserves the issue of finding an adequate thread-off between the requirements elicited from advertising companies and the degree to which a user may accept to be bothered while performing some task. This problem is even more complex when ads are presented on mobile devices, where the reduced screen size considerably limits user’s capability to continue his/her task, so increasing the frustration caused by the presence of the ads. In this paper we present an approach for the presentation of personalized ads on mobile devices, which is based on a user model that takes into account user’s in-terests over time. The approach has been adopted within the LUNA wireless net-work project, which is targeted at realizing a business model such that the services provided in the area of Trento, in the North of Italy, are accessible and usable by everybody, at a very low cost. The client-side of the mobile LUNA application re-lies on a dynamic user modeling technique. We describe the personalization com-ponent of the advertising management system employed and we explain how a user model is dynamically created, saved and updated on the basis of the latest interaction history and of the delivered contents