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.

Integrated data model and DSL modifications

Companies are increasingly more and more dependent on distributed web-based software systems to support their businesses. This increases the need to maintain and extend software systems with up-to-date new features. Thus, the development process to introduce new features usually needs to be swift and agile, and the supporting software evolution process needs to be safe, fast, and efficient. However, this is usually a difficult and challenging task for a developer due to the lack of support offered by programming environments, frameworks, and database management systems. Changes needed at the code level, database model, and the actual data contained in the database must be planned and developed together and executed in a synchronized way. Even under a careful development discipline, the impact of changing an application data model is hard to predict. The lifetime of an application comprises changes and updates designed and tested using data, which is usually far from the real, production, data. So, coding DDL and DML SQL scripts to update database schema and data, is the usual (and hard) approach taken by developers. Such manual approach is error prone and disconnected from the real data in production, because developers may not know the exact impact of their changes. This work aims to improve the maintenance process in the context of Agile Platform by Outsystems. Our goal is to design and implement new data-model evolution features that ensure a safe support for change and a sound migration process. Our solution includes impact analysis mechanisms targeting the data model and the data itself. This provides, to developers, a safe, simple, and guided evolution process.

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.

Quality of life of hypertensive and diabetic patients: Who suffers the most?

Objective: Quality of life was measured using the EQ-5D index for Portugal and a Self-Assessed Ranking of Health (SARH) to understand which patients suffer the most decrease in quality of life: diabetics or hypertensive. Method: Using the National Health Survey (NHS), two analyses were conducted on 5649 respondents. The EQ-5D index was calculated by matching questions in the NHS with its dimensions. The SARH was calculated based on a specific question in the NHS. Results: Differences between diseases do not occur using the EQ-5D index. Using the SARH, type 1 diabetics suffer the most while hypertensive suffers the least.

The graduate: Spillovers from the entry of the first worker with a college degree in a firm

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

Productivity gains from migration: An analysis of Cape Verdean return migrants

Are return migrants more productive than non-migrants? If so, is it a causal effect or simply self-selection? Existing literature has not reached a consensus on the role of return migration for origin countries. To answer these research questions, an empirical analysis was performed based on household data collected in Cape Verde. One of the most common identification problems in the migration literature is the presence of migrant self-selection. In order to disentangle potential selection bias, we use instrumental variable estimation using variation provided by unemployment rates in migrant destination countries, which is compared with OLS and Nearest Neighbor Matching (NNM) methods. The results using the instrumental variable approach provide evidence of labour income gains due to return migration, while OLS underestimates the coefficient of interest. This bias points towards negative self-selection of return migrants on unobserved characteristics, although the different estimates cannot be distinguished statistically. Interestingly, migration duration and occupational changes after migration do not seem to influence post-migration income. There is weak evidence that return migrants from the United States have higher income gains caused by migration than the ones who returned from Portugal.

Visual and verbal processing effects on human memory

In this study in the field of Consumer Behavior, brand name memory of consumers with regard to verbal and visual incongruent and congruent information such as memory structure of brands was tested. Hence, four experimental groups with different constellations of verbal and visual congruity and incongruity were created to compare their brand name memory performance. The experiment was conducted in several classes with 128 students, each group with 32 participants. It was found that brands, which are presented in a congruent or moderately incongruent relation to their brand schema, result in a better brand recall than their incongruent counterparts. A difference between visual congruity and moderately incongruity could not be confirmed. In contrast to visual incongruent information, verbal incongruent information does not result in a worse brand recall performance.

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

Contém resumo

Healthcare- Associated infections: An analysis of costs in a Portuguese Hospital

Hospital-acquired infections (HAIs) delay healing, prolong Hospital stay, and increase both Hospital costs and risk of death. This study aims to estimate the extra length of stay and mortality rate attributable to each of the following HAIs: wound infection (WI); bloodstream infection (BSI); urinary infections (UI); and Hospital-acquired pneumonia (HAP). The study population consisted of patients discharged in CHLC in 2014. Data was collected to identify demographic information, surgical operations, development of HAIs and its outputs. The study used regressions and a matched strategy to compare cases (infected) and controls (uninfected). The matching criteria were: age, sex, week and type of admission, number of admissions, major diagnostic category and type of discharge. When compared to matched controls, cases with HAI had a higher mortality rate and greater length of stay. WI related to hip or knee surgery, increased mortality rate by 27.27% and the length of stay by 74.97 days. WI due to colorectal surgery caused an extra mortality rate of 10.69% and an excess length of stay of 20.23 days. BSI increased Hospital stay by 28.80 days and mortality rate by 32.27%. UI caused an average additional length of stay of 19.66 days and risk of death of 12.85%. HAP resulted in an extra Hospital stay of 25.06 days and mortality rate of 24.71%. This study confirms the results of the previous literature that patients experiencing HAIs incur in an excess of mortality rates and Hospital stay, and, overall, it presents worse results comparing with other countries.