Reconceptualising public spaces of (IN)equality: sensing and creating layers of visibility

Tese apresentada para cumprimento dos requisitos necessários à obtenção do grau de Doutor em Geografia e Planeamento Territorial - Especialidade: Geografia Humana

Agent-based parking occupancy simulation

The existing parking simulations, as most simulations, are intended to gain insights of a system or to make predictions. The knowledge they have provided has built up over the years, and several research works have devised detailed parking system models. This thesis work describes the use of an agent-based parking simulation in the context of a bigger parking system development. It focuses more on flexibility than on fidelity, showing the case where it is relevant for a parking simulation to consume dynamically changing GIS data from external, online sources and how to address this case. The simulation generates the parking occupancy information that sensing technologies should eventually produce and supplies it to the bigger parking system. It is built as a Java application based on the MASON toolkit and consumes GIS data from an ArcGis Server. The application context of the implemented parking simulation is a university campus with free, on-street parking places.

Creation of a web application for smart park system and parking prediction study for system integration

In the last few years, we have observed an exponential increasing of the information systems, and parking information is one more example of them. The needs of obtaining reliable and updated information of parking slots availability are very important in the goal of traffic reduction. Also parking slot prediction is a new topic that has already started to be applied. San Francisco in America and Santander in Spain are examples of such projects carried out to obtain this kind of information. The aim of this thesis is the study and evaluation of methodologies for parking slot prediction and the integration in a web application, where all kind of users will be able to know the current parking status and also future status according to parking model predictions. The source of the data is ancillary in this work but it needs to be understood anyway to understand the parking behaviour. Actually, there are many modelling techniques used for this purpose such as time series analysis, decision trees, neural networks and clustering. In this work, the author explains the best techniques at this work, analyzes the result and points out the advantages and disadvantages of each one. The model will learn the periodic and seasonal patterns of the parking status behaviour, and with this knowledge it can predict future status values given a date. The data used comes from the Smart Park Ontinyent and it is about parking occupancy status together with timestamps and it is stored in a database. After data acquisition, data analysis and pre-processing was needed for model implementations. The first test done was with the boosting ensemble classifier, employed over a set of decision trees, created with C5.0 algorithm from a set of training samples, to assign a prediction value to each object. In addition to the predictions, this work has got measurements error that indicates the reliability of the outcome predictions being correct. The second test was done using the function fitting seasonal exponential smoothing tbats model. Finally as the last test, it has been tried a model that is actually a combination of the previous two models, just to see the result of this combination. The results were quite good for all of them, having error averages of 6.2, 6.6 and 5.4 in vacancies predictions for the three models respectively. This means from a parking of 47 places a 10% average error in parking slot predictions. This result could be even better with longer data available. In order to make this kind of information visible and reachable from everyone having a device with internet connection, a web application was made for this purpose. Beside the data displaying, this application also offers different functions to improve the task of searching for parking. The new functions, apart from parking prediction, were: - Park distances from user location. It provides all the distances to user current location to the different parks in the city. - Geocoding. The service for matching a literal description or an address to a concrete location. - Geolocation. The service for positioning the user. - Parking list panel. This is not a service neither a function, is just a better visualization and better handling of the information.

Uncertain Spaces: Virtual Configurations in Contemporary Art and Museums

Contém artigos apresentados na International Conference “Uncertain Spaces: Virtual Configurations in Contemporary Art and Museums”, na Fundação Calouste Gulbenkian (Lisboa), 31 Outubro - 1 de Novembro de 2014) de: Helena Barranha e Susana S. Martins - Introduction: Art, Museums and Uncertainty (pp.1-12); Alexandra Bounia e Eleni Myrivili - Beyond the ‘Virtual’: Intangible Museographies and Collaborative Museum Experiences (pp.15-32); Annet Dekker - Curating in Progress. Moving Between Objects and Processes (pp.33-54); Giselle Beiguelman - Corrupted Memories. The aesthetics of Digital Ruins and the Museum of the Unfinished (pp.55-82); Andrew Vaas Brooks - The Planetary Datalinks (pp.85-110); Sören Meschede - Curators’ Network: Creating a Promotional Database for Contemporary Visual Arts (pp.11-130); Stefanie Kogler - Divergent Histories and Digital Archives of Latin American and Latino Art in the United States – Old Problems in New Digital Formats (pp.131-156); Luise Reitstätter e Florian Bettel - Right to the City! Right to the Museum!(pp.159-182); Roberto Terracciano - On Geo-poetic systems: virtual interventions inside and outside the museum space (pp.183-210); e, Catarina Carneiro de Sousa e Luís Eustáquio - Art Practice in Collaborative Virtual Environments (pp.211-240).