Pozzolanic components in lime mortars: correlating behaviour, composition and microstructure.

Int. J. for Restoration of Buildings and Monuments, vol.11, nº 2 (2005), p.111-118

Long-term behaviour of railway transitions under dynamic loading application to soft soil sites

Dissertação para obtenção do Grau de Doutor em Engenharia Civil

Children consumer behaviour field lab: The Nestum consumer

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

The influence of brick residues in the behaviour of lime mortars

XXXVI IAHS World Congress on Housing - National Housing Programs-New Visions, November 03–07, 2008, Kolkata, India

Dissolved organic nitrogen behaviour during denitrification with suspended and attached biomass

Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente, perfil Engenharia Sanitária

Analysis and simulation of social unrest in Europe: towards understanding social unrest in Europe

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies

Spatial Patterns and Irregularities of the electoral data: general elections in Canada

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Corporate social responsible behaviour in the financial industry

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Lime mortars with ceramic wastes: characterization of components and their influence on the mechanical behaviour

Considering the fundamental importance of preserving the built heritage and of ensuring the good performance achieved by incorporating ceramic particles in lime mortars in ancient times, it is important to study solutions that use materials the available today, in order to produce mortars intended to repair and replace the old ones. Solutions incorporating industrial ceramic waste might be profitable for several reasons, namely for economic, environmental and technical aspects. In this paper, seven ceramic waste products collected from ceramics factories are characterized. Their mineralogy, dimensional features and pozzolanicity were determined. Three of these products, with different particle size fractions (obtained directly from milling, dust only and fragment fractions only), were selected, incorporated into air lime mortars, and their mechanical strength was determined. In the present work, evidence of mechanical efficiency, when common sand or air lime were partially replaced by ceramic wastes, was made clear, drawing attention to the sustainability of this type of mortars, hence, encouraging further research.

Hygrothermal behaviour of earthen plasters for sustainable housing construction

A ready-mixed and several laboratory formulated mortars were produced and tested in fresh state and after hardening, simulating a masonry plaster for indoor application. All the mortars used a clayish earth from the same region and different compositions of aggregates, eventually including fibres and a phase change material. All the formulated mortars were composed by 1:3 volumetric proportions of earth and aggregate. Tests were developed for consistency, fresh bulk density, thermal conductivity, capillary absorption and drying, water vapour permeability and sorption-desorption. The use of PCM changed drastically the workability of the mortars and increased their capillary absorption. The use of fibres and variations on particle size distribution of the mixtures of sand that were used had no significant influence on tested properties. But particularly the good workability of these mortars and the high capacity of sorption and desorption was highlighted. With this capacity plasters made with these mortars are able to adsorb water vapour from indoor atmosphere when high levels of relative humidity exist and release water vapour when the indoor atmosphere became too dry. This fact makes them able to contribute passively for a healthier indoor environment. The technical, ecological and environmental advantages of the application of plasters with this type of mortars are emphasized, with the aim of contributing for an increased use for new or existent housing.

Tool for discovering sequential patterns in financial markets

The goal of this thesis is the study of a tool that can help analysts in finding sequential patterns. This tool will have a focus on financial markets. A study will be made on how new and relevant knowledge can be mined from real life information, potentially giving investors, market analysts, and economists new basis to make informed decisions. The Ramex Forum algorithm will be used as a basis for the tool, due to its ability to find sequential patterns in financial data. So that it further adapts to the needs of the thesis, a study of relevant improvements to the algorithm will be made. Another important aspect of this algorithm is the way that it displays the patterns found, even with good results it is difficult to find relevant patterns among all the studied samples without a proper result visualization component. As such, different combinations of parameterizations and ways to visualize data will be evaluated and their influence in the analysis of those patterns will be discussed. In order to properly evaluate the utility of this tool, case studies will be performed as a final test. Real information will be used to produce results and those will be evaluated in regards to their accuracy, interest, and relevance.

State detection in a financial portfolio: a self-organizing maps approach for financial time series

This study analyses financial data using the result characterization of a self-organized neural network model. The goal was prototyping a tool that may help an economist or a market analyst to analyse stock market series. To reach this goal, the tool shows economic dependencies and statistics measures over stock market series. The neural network SOM (self-organizing maps) model was used to ex-tract behavioural patterns of the data analysed. Based on this model, it was de-veloped an application to analyse financial data. This application uses a portfo-lio of correlated markets or inverse-correlated markets as input. After the anal-ysis with SOM, the result is represented by micro clusters that are organized by its behaviour tendency. During the study appeared the need of a better analysis for SOM algo-rithm results. This problem was solved with a cluster solution technique, which groups the micro clusters from SOM U-Matrix analyses. The study showed that the correlation and inverse-correlation markets projects multiple clusters of data. These clusters represent multiple trend states that may be useful for technical professionals.

Analyzing Geospatial patterns of syrian refugee flows in southeastern Turkey by use of remote sensing and complementary data

Crisis-affected communities and global organizations for international aid are becoming increasingly digital as consequence geotechnology popularity. Humanitarian sector changed in profound ways by adopting new technical approach to obtain information from area with difficult geographical or political access. Since 2011, turkey is hosting a growing number of Syrian refugees along southeastern region. Turkish policy of hosting them in camps and the difficulty created by governors to international aid group expeditions to get information, made such international organizations to investigate and adopt other approach in order to obtain information needed. They intensified its remote sensing approach. However, the majority of studies used very high-resolution satellite imagery (VHRSI). The study area is extensive and the temporal resolution of VHRSI is low, besides it is infeasible only using these sensors as unique approach for the whole area. The focus of this research, aims to investigate the potentialities of mid-resolution imagery (here only Landsat) to obtain information from region in crisis (here, southeastern Turkey) through a new web-based platform called Google Earth Engine (GEE). Hereby it is also intended to verify GEE currently reliability once the Application Programming Interface (API) is still in beta version. The finds here shows that the basic functions are trustworthy. Results pointed out that Landsat can recognize change in the spectral resolution clearly only for the first settlement. The ongoing modifications vary for each case. Overall, Landsat demonstrated high limitations, but need more investigations and may be used, with restriction, as a support of VHRSI.

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.