A crop-land allocation model: A case study in La Rioja, Spain

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

Competências interpessoais em saúde : comunicar para a qualidade, com o utente e em equipa multidisciplinar

RESUMO - O processo de comunicação em saúde encontra-se relacionado com a melhoria dos resultados em saúde através da informação, com o objectivo de influenciar indivíduos e comunidades. Os profissionais de saúde, no contexto da prestação de cuidados, necessitam de deter determinadas competências interpessoais e de comunicação no sentido de promover a qualidade e segurança do doente, contribuindo para a diminuição do erro clínico através de uma comunicação eficaz em equipa. Estabelecer uma relação de empatia e confiança com o doente, saber escutar e compreender a sua perspectiva definem-se, entre outras, por capacidades essenciais a estes profissionais, a par de uma comunicação verbal e escrita clara e assertiva, cujo impacto se reflecte também na satisfação do utente. O ensino destas competências é fundamental para habilitar os profissionais a lidar com diversas situações, contribuindo para a excelência técnica e qualidade dos cuidados. A sua avaliação é essencialmente realizada durante a formação académica, a nível internacional, sobre o que a literatura descreve várias metodologias possíveis. O método utilizado com maior frequência consiste na observação directa da interacção entre o aluno e o doente, em contexto real ou simulado, através de uma checklist formada por itens correspondentes a atitudes e comportamentos que avalia a presença das competências necessárias. O desenvolvimento destas competências passa por sensibilizar os profissionais para a sua importância, dar-lhes formação e avaliar, apostando na continuidade da investigação.

Segmentação, seguimento e avaliação automática de bactérias em imagens de microscópio

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

RetInfo - Identificação de alterações retinianas usando processamento digital de imagem

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Hospital-acquired infections: a cost estimation for CLABSI in Portugal

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

Cues for cancer stem cells origin

Dissertação para obtenção do Grau de Mestre em Genética Molecular e Biomedicina

Service-oriented infrastructure to support the control, monitoring and management of a shop floor system

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

CMOS indoor light energy harvesting system for wireless sensing applications

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

A framework for efficient model transformations

The reported productivity gains while using models and model transformations to develop entire systems, after almost a decade of experience applying model-driven approaches for system development, are already undeniable benefits of this approach. However, the slowness of higher-level, rule based model transformation languages hinders the applicability of this approach to industrial scales. Lower-level, and efficient, languages can be used but productivity and easy maintenance seize to exist. The abstraction penalty problem is not new, it also exists for high-level, object oriented languages but everyone is using them now. Why is not everyone using rule based model transformation languages then? In this thesis, we propose a framework, comprised of a language and its respective environment, designed to tackle the most performance critical operation of high-level model transformation languages: the pattern matching. This framework shows that it is possible to mitigate the performance penalty while still using high-level model transformation languages.

A SDK improvement towards gesture support

Human-Computer Interaction have been one of the main focus of the technological community, specially the Natural User Interfaces (NUI) field of research as, since the launch of the Kinect Sensor, the goal to achieve fully natural interfaces just got a lot closer to reality. Taking advantage of this conditions the following research work proposes to compute the hand skeleton in order to recognize Sign Language Shapes. The proposed solution uses the Kinect Sensor to achieve a good segmentation and image analysis algorithms to extend the skeleton from the extraction of high-level features. In order to recognize complex hand shapes the current research work proposes the redefinition of the hand contour making it immutable to translation, rotation and scaling operations, and a set of tools to achieve a good recognition. The validation of the proposed solution extended the Kinects Software Development Kit to allow the developer to access the new set of inferred points and created a template-matching based platform that uses the contour to define the hand shape, this prototype was tested in a set of predefined conditions and showed to have a good success ration and has proven to be eligible for real-time scenarios.

Characterization of novel heme-containing sensor proteins from Geobacter sulfurreducens

The focus of this Thesis was the study of the sensor domains of two heme-containing methyl-accepting chemotaxis proteins (MCP) from Geobacter sulfurreducens: GSU0582 and GSU0935. These domains contain one c-type heme, form swapped dimers with a PAS-like fold and are the first examples of a new class of heme sensors. NMR spectroscopy was used to assign the heme and polypeptide signals in both sensors, as a first step to probe conformational changes in the vicinity of the hemes. However, the presence of two conformations in solution impaired the confident assignment of the polypeptide signals. To understand how conformational changes and swapped dimerization mechanism can effectively modulate the function of the two sensor domains and their signal transduction process, the sensor domains folding and stability were studied by circular dichroism and UV-visible spectroscopy. The results showed differences in the thermodynamic stability of the sensors, with GSU0582 displaying higher structural stability. These studies also demonstrated that the heme moiety undergoes conformational changes matching those occurring at the global protein structure and that the content of intrinsically disordered segments within these proteins (25% for GSU0935; 13% for GSU0582) correlates with the stability differences observed. The thermodynamic and kinetic properties of the sensor domains were determined at different pH and ionic strength by visible spectroscopy and stopped-flow techniques. Despite the remarkably similar spectroscopic and structural features of the two sensor domains, the results showed that their properties are quite distinct. Sensor domain GSU0935 displayed more negative reduction potentials and smaller reduction rate constants, which were more affected by pH and ionic strength. The available structures were used to rationalize these differences. Overall, the results described in this Thesis indicate that the two G. sulfurreducens MCP sensor domains are designed to function in different working potential ranges, allowing this bacterium to trigger an adequate cellular response in distinct anoxic subsurface environments.

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.

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.

Image processing for displacement measurements

Since the invention of photography humans have been using images to capture, store and analyse the act that they are interested in. With the developments in this field, assisted by better computers, it is possible to use image processing technology as an accurate method of analysis and measurement. Image processing's principal qualities are flexibility, adaptability and the ability to easily and quickly process a large amount of information. Successful examples of applications can be seen in several areas of human life, such as biomedical, industry, surveillance, military and mapping. This is so true that there are several Nobel prizes related to imaging. The accurate measurement of deformations, displacements, strain fields and surface defects are challenging in many material tests in Civil Engineering because traditionally these measurements require complex and expensive equipment, plus time consuming calibration. Image processing can be an inexpensive and effective tool for load displacement measurements. Using an adequate image acquisition system and taking advantage of the computation power of modern computers it is possible to accurately measure very small displacements with high precision. On the market there are already several commercial software packages. However they are commercialized at high cost. In this work block-matching algorithms will be used in order to compare the results from image processing with the data obtained with physical transducers during laboratory load tests. In order to test the proposed solutions several load tests were carried out in partnership with researchers from the Civil Engineering Department at Universidade Nova de Lisboa (UNL).

Education in Brazil: A big challenge?

Brazil is an emerging country where community school is being promoted in order to respond to the still significant gap between the poor and the rich population. This paper attempts to analyze one community school. Although other social programs whose scopes are also to enhance education have been implemented, such as the "Bolsa Familia", the impact of community schools need attention as well. Indeed, community schools must be studied due to the relevant positive attributes they can provide. Moreover, by improving the quality of education, studies show an enhancement of a higher-skilled nation and a better qualified labour force for the future. To clearly demonstrate the impacts of these communities, the treatment effect will be measured by using a matching estimator.