Wireless triple play system

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e Computadores

Clearing the cloudy crystal balls: Hybrid modelling for energy and climate change mitigation scenarios – A case study for Portugal

Dissertação para obtenção do Grau de Doutor em Ambiente

Aqueous biphasic system based on cholinium ionic liquids: extraction of biologically active phenolic acids

Phenolic acids are aromatic secondary plant metabolites, widely spread throughout the plant kingdom. Due to their biological and pharmacological properties, they have been playing an important role in phytotherapy and consequently techniques for their separation and purification are in need. This thesis aims at exploring new sustainable separation processes based on ionic liquids (ILs) in the extraction of biologically active phenolic acids. For that purpose, three phenolic acids with similar chemical structures were selected: cinnamic acid, p-coumaric acid and caffeic acid. In the last years, it has been shown that ionic liquids-based aqueous biphasic systems (ABSs) are valid alternatives for the extraction, recovery and purification of biomolecules when compared to conventional ABS or extractions carried out with organic solvents. In particular, cholinium-based ILs represent a clear step towards a greener chemistry, while providing means for the implementation of efficient techniques for the separation and purification of biomolecules. In this work, ABSs were implemented using cholinium carboxylate ILs using either high charge density inorganic salt (K3PO4) or polyethylene glycol (PEG) to promote the phase separation of aqueous solutions containing three different phenolic acids. These systems allow for the evaluation of effect of chemical structure of the anion on the extraction efficiency. Only one imidazolium-based IL was used in order to establish the effect of the cation chemical structure. The selective extraction of one single acid was also researched. Overall, it was observed that phenolic acids display very complex behaviours in aqueous solutions, from dimerization to polymerization and also hetero-association are quite frequent phenomena, depending on the pH conditions. These phenomena greatly hinder the correct quantification of these acids in solution.

Reactive hybrid knowledge bases

Hybrid knowledge bases are knowledge bases that combine ontologies with non-monotonic rules, allowing to join the best of both open world ontologies and close world rules. Ontologies shape a good mechanism to share knowledge on theWeb that can be understood by both humans and machines, on the other hand rules can be used, e.g., to encode legal laws or to do a mapping between sources of information. Taking into account the dynamics present today on the Web, it is important for these hybrid knowledge bases to capture all these dynamics and thus adapt themselves. To achieve that, it is necessary to create mechanisms capable of monitoring the information flow present on theWeb. Up to today, there are no such mechanisms that allow for monitoring events and performing modifications of hybrid knowledge bases autonomously. The goal of this thesis is then to create a system that combine these hybrid knowledge bases with reactive rules, aiming to monitor events and perform actions over a knowledge base. To achieve this goal, a reactive system for the SemanticWeb is be developed in a logic-programming based approach accompanied with a language for heterogeneous rule base evolution having as its basis RIF Production Rule Dialect, which is a standard for exchanging rules over theWeb.

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.