Spartan Daily, November 7, 1989

Volume 93, Issue 46https://scholarworks.sjsu.edu/spartandaily/7906/thumbnail.jp

Computer-Assisted Interactive Documentary and Performance Arts in Illimitable Space

This major component of the research described in this thesis is 3D computer graphics, specifically the realistic physics-based softbody simulation and haptic responsive environments. Minor components include advanced human-computer interaction environments, non-linear documentary storytelling, and theatre performance. The journey of this research has been unusual because it requires a researcher with solid knowledge and background in multiple disciplines; who also has to be creative and sensitive in order to combine the possible areas into a new research direction. [...] It focuses on the advanced computer graphics and emerges from experimental cinematic works and theatrical artistic practices. Some development content and installations are completed to prove and evaluate the described concepts and to be convincing. [...] To summarize, the resulting work involves not only artistic creativity, but solving or combining technological hurdles in motion tracking, pattern recognition, force feedback control, etc., with the available documentary footage on film, video, or images, and text via a variety of devices [....] and programming, and installing all the needed interfaces such that it all works in real-time. Thus, the contribution to the knowledge advancement is in solving these interfacing problems and the real-time aspects of the interaction that have uses in film industry, fashion industry, new age interactive theatre, computer games, and web-based technologies and services for entertainment and education. It also includes building up on this experience to integrate Kinect- and haptic-based interaction, artistic scenery rendering, and other forms of control. This research work connects all the research disciplines, seemingly disjoint fields of research, such as computer graphics, documentary film, interactive media, and theatre performance together.Comment: PhD thesis copy; 272 pages, 83 figures, 6 algorithm

A Digital Library for Research Data and Related Information in the Social Sciences

In the social sciences, researchers search for information on the Web, but this is most often distributed on different websites, search portals, digital libraries, data archives, and databases. In this work, we present an integrated search system for social science information that allows finding information around research data in a single digital library. Users can search for research data sets, publications, survey variables, questions from questionnaires, survey instruments, and tools. Information items are linked to each other so that users can see, for example, which publications contain data citations to research data. The integration and linking of different kinds of information increase their visibility so that it is easier for researchers to find information for re-use. In a log-based usage study, we found that users search across different information types, that search sessions contain a high rate of positive signals and that link information is often explored

An explainable recommender system based on semantically-aware matrix factorization.

Collaborative Filtering techniques provide the ability to handle big and sparse data to predict the ratings for unseen items with high accuracy. Matrix factorization is an accurate collaborative filtering method used to predict user preferences. However, it is a black box system that recommends items to users without being able to explain why. This is due to the type of information these systems use to build models. Although rich in information, user ratings do not adequately satisfy the need for explanation in certain domains. White box systems, in contrast, can, by nature, easily generate explanations. However, their predictions are less accurate than sophisticated black box models. Recent research has demonstrated that explanations are an essential component in bringing the powerful predictions of big data and machine learning methods to a mass audience without a compromise in trust. Explanations can take a variety of formats, depending on the recommendation domain and the machine learning model used to make predictions. Semantic Web (SW) technologies have been exploited increasingly in recommender systems in recent years. The SW consists of knowledge graphs (KGs) providing valuable information that can help improve the performance of recommender systems. Yet KGs, have not been used to explain recommendations in black box systems. In this dissertation, we exploit the power of the SW to build new explainable recommender systems. We use the SW\u27s rich expressive power of linked data, along with structured information search and understanding tools to explain predictions. More specifically, we take advantage of semantic data to learn a semantically aware latent space of users and items in the matrix factorization model-learning process to build richer, explainable recommendation models. Our off-line and on-line evaluation experiments show that our approach achieves accurate prediction with the additional ability to explain recommendations, in comparison to baseline approaches. By fostering explainability, we hope that our work contributes to more transparent, ethical machine learning without sacrificing accuracy

Senseable Spaces: from a theoretical perspective to the application in augmented environments

Grazie all’ enorme diffusione di dispositivi senzienti nella vita di tutti i giorni, nell’ ultimo decennio abbiamo assistito ad un cambio definitivo nel modo in cui gli utenti interagiscono con lo spazio circostante. Viene coniato il termine Spazio Sensibile, per descrivere quegli spazi in grado di fornire servizi contestuali agli utenti, misurando e analizzando le dinamiche che in esso avvengono, e di reagire conseguentemente a questo continuo flusso di dati bidirezionale. La ricerca è stata condotta abbracciando diversi domini di applicazione, le cui singole esigenze hanno reso necessario testare il concetto di Spazi Sensibili in diverse declinazioni, mantenendo al centro della ricerca l’utente, con la duplice accezione di end-user e manager. Molteplici sono i contributi rispetto allo stato dell’ arte. Il concetto di Spazio Sensibile è stato calato nel settore dei Beni Culturali, degli Spazi Pubblici, delle Geosciences e del Retail. I casi studio nei musei e nella archeologia dimostrano come l’ utilizzo della Realtà Aumentata possa essere sfruttata di fronte a un dipinto o in outdoor per la visualizzazione di modelli complessi, In ambito urbano, il monitoraggio di dati generati dagli utenti ha consentito di capire le dinamiche di un evento di massa, durante il quale le stesse persone fruivano di servizi contestuali. Una innovativa applicazione di Realtà Aumentata è stata come servizio per facilitare l’ ispezione di fasce tampone lungo i fiumi, standardizzando flussi di dati e modelli provenienti da un Sistema Informativo Territoriale. Infine, un robusto sistema di indoor localization è stato istallato in ambiente retail, per scopi classificazione dei percorsi e per determinare le potenzialità di un punto vendita. La tesi è inoltre una dimostrazione di come Space Sensing e Geomatica siano discipline complementari: la geomatica consente di acquisire e misurare dati geo spaziali e spazio temporali a diversa scala, lo Space Sensing utilizza questi dati per fornire servizi all’ utente precisi e contestuali.Given the tremendous growth of ubiquitous services in our daily lives, during the last few decades we have witnessed a definitive change in the way users' experience their surroundings. At the current state of art, devices are able to sense the environment and users’ location, enabling them to experience improved digital services, creating synergistic loop between the use of the technology, and the use of the space itself. We coined the term Senseable Space, to define the kinds of spaces able to provide users with contextual services, to measure and analyse their dynamics and to react accordingly, in a seamless exchange of information. Following the paradigm of Senseable Spaces as the main thread, we selected a set of experiences carried out in different fields; central to this investigation there is of course the user, placed in the dual roles of end-user and manager. The main contribution of this thesis lies in the definition of this new paradigm, realized in the following domains: Cultural Heritage, Public Open Spaces, Geosciences and Retail. For the Cultural Heritage panorama, different pilot projects have been constructed from creating museum based installations to developing mobile applications for archaeological settings. Dealing with urban areas, app-based services are designed to facilitate the route finding in a urban park and to provide contextual information in a city festival. We also outlined a novel application to facilitate the on-site inspection by risk managers thanks to the use of Augmented Reality services. Finally, a robust indoor localization system has been developed, designed to ease customer profiling in the retail sector. The thesis also demonstrates how Space Sensing and Geomatics are complementary to one another, given the assumption that the branches of Geomatics cover all the different scales of data collection, whilst Space Sensing gives one the possibility to provide the services at the correct location, at the correct time

Senseable Spaces: from a theoretical perspective to the application in augmented environments

openGrazie all’ enorme diffusione di dispositivi senzienti nella vita di tutti i giorni, nell’ ultimo decennio abbiamo assistito ad un cambio definitivo nel modo in cui gli utenti interagiscono con lo spazio circostante. Viene coniato il termine Spazio Sensibile, per descrivere quegli spazi in grado di fornire servizi contestuali agli utenti, misurando e analizzando le dinamiche che in esso avvengono, e di reagire conseguentemente a questo continuo flusso di dati bidirezionale. La ricerca è stata condotta abbracciando diversi domini di applicazione, le cui singole esigenze hanno reso necessario testare il concetto di Spazi Sensibili in diverse declinazioni, mantenendo al centro della ricerca l’utente, con la duplice accezione di end-user e manager. Molteplici sono i contributi rispetto allo stato dell’ arte. Il concetto di Spazio Sensibile è stato calato nel settore dei Beni Culturali, degli Spazi Pubblici, delle Geosciences e del Retail. I casi studio nei musei e nella archeologia dimostrano come l’ utilizzo della Realtà Aumentata possa essere sfruttata di fronte a un dipinto o in outdoor per la visualizzazione di modelli complessi, In ambito urbano, il monitoraggio di dati generati dagli utenti ha consentito di capire le dinamiche di un evento di massa, durante il quale le stesse persone fruivano di servizi contestuali. Una innovativa applicazione di Realtà Aumentata è stata come servizio per facilitare l’ ispezione di fasce tampone lungo i fiumi, standardizzando flussi di dati e modelli provenienti da un Sistema Informativo Territoriale. Infine, un robusto sistema di indoor localization è stato istallato in ambiente retail, per scopi classificazione dei percorsi e per determinare le potenzialità di un punto vendita. La tesi è inoltre una dimostrazione di come Space Sensing e Geomatica siano discipline complementari: la geomatica consente di acquisire e misurare dati geo spaziali e spazio temporali a diversa scala, lo Space Sensing utilizza questi dati per fornire servizi all’ utente precisi e contestuali.Given the tremendous growth of ubiquitous services in our daily lives, during the last few decades we have witnessed a definitive change in the way users' experience their surroundings. At the current state of art, devices are able to sense the environment and users’ location, enabling them to experience improved digital services, creating synergistic loop between the use of the technology, and the use of the space itself. We coined the term Senseable Space, to define the kinds of spaces able to provide users with contextual services, to measure and analyse their dynamics and to react accordingly, in a seamless exchange of information. Following the paradigm of Senseable Spaces as the main thread, we selected a set of experiences carried out in different fields; central to this investigation there is of course the user, placed in the dual roles of end-user and manager. The main contribution of this thesis lies in the definition of this new paradigm, realized in the following domains: Cultural Heritage, Public Open Spaces, Geosciences and Retail. For the Cultural Heritage panorama, different pilot projects have been constructed from creating museum based installations to developing mobile applications for archaeological settings. Dealing with urban areas, app-based services are designed to facilitate the route finding in a urban park and to provide contextual information in a city festival. We also outlined a novel application to facilitate the on-site inspection by risk managers thanks to the use of Augmented Reality services. Finally, a robust indoor localization system has been developed, designed to ease customer profiling in the retail sector. The thesis also demonstrates how Space Sensing and Geomatics are complementary to one another, given the assumption that the branches of Geomatics cover all the different scales of data collection, whilst Space Sensing gives one the possibility to provide the services at the correct location, at the correct time.INGEGNERIA DELL'INFORMAZIONEembargoed_20181001Pierdicca, RobertoPierdicca, Robert

Sets in Order: the official magazine of square dancing.

Published monthly for and by Square Dancers and for the general enjoyment of all