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.

UAV - based imagery processing using structure from motion and remote sensing technology

With the recent advances in technology and miniaturization of devices such as GPS or IMU, Unmanned Aerial Vehicles became a feasible platform for a Remote Sensing applications. The use of UAVs compared to the conventional aerial platforms provides a set of advantages such as higher spatial resolution of the derived products. UAV - based imagery obtained by a user grade cameras introduces a set of problems which have to be solved, e. g. rotational or angular differences or unknown or insufficiently precise IO and EO camera parameters. In this work, UAV - based imagery of RGB and CIR type was processed using two different workflows based on PhotoScan and VisualSfM software solutions resulting in the DSM and orthophoto products. Feature detection and matching parameters influence on the result quality as well as a processing time was examined and the optimal parameter setup was presented. Products of the both workflows were compared in terms of a quality and a spatial accuracy. Both workflows were compared by presenting the processing times and quality of the results. Finally, the obtained products were used in order to demonstrate vegetation classification. Contribution of the IHS transformations was examined with respect to the classification accuracy.

Structural connectivity based on diffusion Kurtosis imaging

Structural connectivity models based on Diffusion Tensor Imaging (DTI) are strongly affected by the technique’s inability to resolve crossing fibres, either intra- or inter-hemispherical connections. Several models have been proposed to address this issue, including an algorithm aiming to resolve crossing fibres which is based on Diffusion Kurtosis Imaging (DKI). This technique is clinically feasible, even when multi-band acquisitions are not available, and compatible with multi-shell acquisition schemes. DKI is an extension of DTI enabling the estimation of diffusion tensor and diffusion kurtosis metrics. In this study we compare the performance of DKI and DTI in performing structural brain connectivity. Six healthy subjects were recruited, aged between 25 and 35 (three females). The MRI experiments were performed using a 3T Siemens Trio with a 32-channel head coil. The scans included a T1-weighted sequence (1mm3), and a DWI with b-values 0, 1000 and 2000 s:mm

User-centric product derivation in software product lines

Software Product Line (SPL) engineering aims at achieving efficient development of software products in a specific domain. New products are obtained via a process which entails creating a new configuration specifying the desired product’s features. This configuration must necessarily conform to a variability model, that describes the scope of the SPL, or else it is not viable. To ensure this, configuration tools are used that do not allow invalid configurations to be expressed. A different concern, however, is making sure that a product addresses the stakeholders’ needs as best as possible. The stakeholders may not be experts on the domain, so they may have unrealistic expectations. Also, the scope of the SPL is determined not only by the domain but also by limitations of the development platforms. It is therefore possible that the desired set of features goes beyond what is possible to currently create with the SPL. This means that configuration tools should provide support not only for creating valid products, but also for improving satisfaction of user concerns. We address this goal by providing a user-centric configuration process that offers suggestions during the configuration process, based on the use of soft constraints, and identifying and explaining potential conflicts that may arise. Suggestions help mitigating stakeholder uncertainty and poor domain knowledge, by helping them address well known and desirable domain-related concerns. On the other hand, automated conflict identification and explanation helps the stakeholders to understand the trade-offs required for realizing their vision, allowing informed resolution of conflicts. Additionally, we propose a prototype-based approach to configuration, that addresses the order-dependency issues by allowing the complete (or partial) specification of the features in a single step. A subsequent resolution process will then identify possible repairs, or trade-offs, that may be required for viabilization.

Comuns: An Open-Data Provider, Explorer and Analytic Toolbox Based on FOSS

Contém resumo

Minimal computation structures for visual information applications based on printed electronics

In the early nineties, Mark Weiser wrote a series of seminal papers that introduced the concept of Ubiquitous Computing. According to Weiser, computers require too much attention from the user, drawing his focus from the tasks at hand. Instead of being the centre of attention, computers should be so natural that they would vanish into the human environment. Computers become not only truly pervasive but also effectively invisible and unobtrusive to the user. This requires not only for smaller, cheaper and low power consumption computers, but also for equally convenient display solutions that can be harmoniously integrated into our surroundings. With the advent of Printed Electronics, new ways to link the physical and the digital worlds became available. By combining common printing techniques such as inkjet printing with electro-optical functional inks, it is starting to be possible not only to mass-produce extremely thin, flexible and cost effective electronic circuits but also to introduce electronic functionalities into products where it was previously unavailable. Indeed, Printed Electronics is enabling the creation of novel sensing and display elements for interactive devices, free of form factor. At the same time, the rise in the availability and affordability of digital fabrication technologies, namely of 3D printers, to the average consumer is fostering a new industrial (digital) revolution and the democratisation of innovation. Nowadays, end-users are already able to custom design and manufacture on demand their own physical products, according to their own needs. In the future, they will be able to fabricate interactive digital devices with user-specific form and functionality from the comfort of their homes. This thesis explores how task-specific, low computation, interactive devices capable of presenting dynamic visual information can be created using Printed Electronics technologies, whilst following an approach based on the ideals behind Personal Fabrication. Focus is given on the use of printed electrochromic displays as a medium for delivering dynamic digital information. According to the architecture of the displays, several approaches are highlighted and categorised. Furthermore, a pictorial computation model based on extended cellular automata principles is used to programme dynamic simulation models into matrix-based electrochromic displays. Envisaged applications include the modelling of physical, chemical, biological, and environmental phenomena.

An agent based architecture to support monitoring in plug and produce manufacturing systems using knowledge extraction

In recent years a set of production paradigms were proposed in order to capacitate manufacturers to meet the new market requirements, such as the shift in demand for highly customized products resulting in a shorter product life cycle, rather than the traditional mass production standardized consumables. These new paradigms advocate solutions capable of facing these requirements, empowering manufacturing systems with a high capacity to adapt along with elevated flexibility and robustness in order to deal with disturbances, like unexpected orders or malfunctions. Evolvable Production Systems propose a solution based on the usage of modularity and self-organization with a fine granularity level, supporting pluggability and in this way allowing companies to add and/or remove components during execution without any extra re-programming effort. However, current monitoring software was not designed to fully support these characteristics, being commonly based on centralized SCADA systems, incapable of re-adapting during execution to the unexpected plugging/unplugging of devices nor changes in the entire system’s topology. Considering these aspects, the work developed for this thesis encompasses a fully distributed agent-based architecture, capable of performing knowledge extraction at different levels of abstraction without sacrificing the capacity to add and/or remove monitoring entities, responsible for data extraction and analysis, during runtime.

ReedCob – An eco-efficient building technology for monolithic walls based on earth and reeds

4th Conference COST ACTION FP1303 – Designing with Bio-based Materials – Challenges and opportiunities. INIA – CSIC, Madrid, 24-25 February 2016. Book of abstracts, T.Troya, J.Galván, D.Jones (Eds.), INIA and IETcc – CSIS, pg. 79-80 (ISBN: 978-91-88349-16-3)

Engineering bio-based polymers using alternative solvents and processes

The work presented in this thesis explores novel routes for the processing of bio-based polymers, developing a sustainable approach based on the use of alternative solvents such as supercritical carbon dioxide (scCO2), ionic liquids (ILs) and deep eutectic solvents (DES). The feasibility to produce polymeric foams via supercritical fluid (SCF) foaming, combined with these solvents was assessed, in order to replace conventional foaming techniques that use toxic and harmful solvents. A polymer processing methodology is presented, based on SCF foaming and using scCO2 as a foaming agent. The SCF foaming of different starch based polymeric blends was performed, namely starch/poly(lactic acid) (SPLA) and starch/poly(ε-caprolactone) (SPCL). The foaming process is based on the fact that CO2 molecules can dissolve in the polymer, changing their mechanical properties and after suitable depressurization, are able to create a foamed (porous) material. In these polymer blends, CO2 presents limited solubility and in order to enhance the foaming effect, two different imidazolium based ILs (IBILs) were combined with this process, by doping the blends with IL. The use of ILs proved useful and improved the foaming effect in these starch-based polymer blends. Infrared spectroscopy (FTIR-ATR) proved the existence of interactions between the polymer blend SPLA and ILs, which in turn diminish the forces that hold the polymeric structure. This is directly related with the ability of ILs to dissolve more CO2. This is also clear from the sorption experiments results, where the obtained apparent sorption coefficients in presence of IL are higher compared to the ones of the blend SPLA without IL. The doping of SPCL with ILs was also performed. The foaming of the blend was achieved and resulted in porous materials with conductivity values close to the ones of pure ILs. This can open doors to applications as self-supported conductive materials. A different type of solvents were also used in the previously presented processing method. If different applications of the bio-based polymers are envisaged, replacing ILs must be considered, especially due to the poor sustainability of some ILs and the fact that there is not a well-established toxicity profile. In this work natural DES – NADES – were the solvents of choice. They present some advantages relatively to ILs since they are easy to produce, cheaper, biodegradable and often biocompatible, mainly due to the fact that they are composed of primary metabolites such as sugars, carboxylic acids and amino-acids. NADES were prepared and their physicochemical properties were assessed, namely the thermal behavior, conductivity, density, viscosity and polarity. With this study, it became clear that these properties can vary with the composition of NADES, as well as with their initial water content. The use of NADES in the SCF foaming of SPCL, acting as foaming agent, was also performed and proved successful. The SPCL structure obtained after SCF foaming presented enhanced characteristics (such as porosity) when compared with the ones obtained using ILs as foaming enhancers. DES constituted by therapeutic compounds (THEDES) were also prepared. The combination of choline chloride-mandelic acid, and menthol-ibuprofen, resulted in THEDES with thermal behavior very distinct from the one of their components. The foaming of SPCL with THEDES was successful, and the impregnation of THEDES in SPCL matrices via SCF foaming was successful, and a controlled release system was obtained in the case of menthol-ibuprofen THEDES.

Genetic algorithm for shipping route estimation with long-range tracking data : automatic reconstruction of shipping routes based on the historical ship positions for maritime safety applications

Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.