Learning facial-expression models with crowdsourcing

The computational power is increasing day by day. Despite that, there are some tasks that are still difficult or even impossible for a computer to perform. For example, while identifying a facial expression is easy for a human, for a computer it is an area in development. To tackle this and similar issues, crowdsourcing has grown as a way to use human computation in a large scale. Crowdsourcing is a novel approach to collect labels in a fast and cheap manner, by sourcing the labels from the crowds. However, these labels lack reliability since annotators are not guaranteed to have any expertise in the field. This fact has led to a new research area where we must create or adapt annotation models to handle these weaklylabeled data. Current techniques explore the annotators’ expertise and the task difficulty as variables that influences labels’ correction. Other specific aspects are also considered by noisy-labels analysis techniques. The main contribution of this thesis is the process to collect reliable crowdsourcing labels for a facial expressions dataset. This process consists in two steps: first, we design our crowdsourcing tasks to collect annotators labels; next, we infer the true label from the collected labels by applying state-of-art crowdsourcing algorithms. At the same time, a facial expression dataset is created, containing 40.000 images and respective labels. At the end, we publish the resulting dataset.

A DSL for querying building data streams of energy, eeather and occupation data

The superfluous consumption of energy is faced by the modern society as a Socio-Economical and Environmental problem of the present days. This situation is worsening given that it is becoming clear that the tendency is to increase energy price every year. It is also noticeable that people, not necessarily proficient in technology, are not able to know where savings can be achieved, due to the absence of accessible awareness mechanisms. One of the home user concerns is to balance the need of reducing energy consumption, while producing the same activity with all the comfort and work efficiency. The common techniques to reduce the consumption are to use a less wasteful equipment, altering the equipment program to a more economical one or disconnecting appliances that are not necessary at the moment. However, there is no direct feedback from this performed actions, which leads to the situation where the user is not aware of the influence that these techniques have in the electrical bill. With the intension to give some control over the home consumption, Energy Management Systems (EMS) were developed. These systems allow the access to the consumption information and help understanding the energy waste. However, some studies have proven that these systems have a clear mismatch between the information that is presented and the one the user finds useful for his daily life, leading to demotivation of use. In order to create a solution more oriented towards the user’s demands, a specially tailored language (DSL) was implemented. This solution allows the user to acquire the information he considers useful, through the construction of questions about his energy consumption. The development of this language, following the Model Driven Development (MDD) approach, took into consideration the ideas of facility managers and home users in the phases of design and validation. These opinions were gathered through meetings with experts and a survey, which was conducted to the purpose of collecting statistics about what home users want to know.

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.

Sistema de deteção de eventos adversos baseado num data warehouse

RESUMO - A Segurança do Doente tem assumido uma relevância crescente nas organizações de saúde, resultado da divulgação de diversos estudos que revelaram a magnitude deste problema e simultaneamente, de uma maior pressão por parte da opinião pública e da comunicação social. Este estudo pretende desenvolver e avaliar a performance de um sistema eletrónico de deteção de eventos adversos, baseado num Data Warehouse, por comparação com os resultados obtidos pela metodologia tradicional de revisão dos registos clínicos. O objetivo principal do trabalho consistiu em identificar um conjunto de triggers / indicadores de alerta que permitam detetar potenciais eventos adversos mais comuns. O sistema desenvolvido apresentou um Valor Preditivo Positivo de 18.2%, uma sensibilidade de 65.1% e uma especificidade de 68.6%, sendo constituído por nove indicadores baseados em informação clínica e 445 códigos do ICD-9-CM, relativos a diagnósticos e procedimentos. Apesar de terem algumas limitações, os sistemas eletrónicos de deteção de eventos adversos apresentam inúmeras potencialidades, nomeadamente a utilização em tempo real e em complemento a metodologias já existentes. Considerando a importância da problemática em análise e a necessidade de aprofundar os resultados obtidos neste trabalho de projeto, seria relevante a sua extensão a um universo mais alargado de instituições hospitalares, estando a sua replicabilidade facilitada, uma vez que o Data Warehouse tem por base um conjunto de aplicações disseminadas a nível nacional. O desenvolvimento e a consolidação dos sistemas eletrónicos de deteção de eventos adversos constitui inegavelmente uma área de futuro, com reflexos ao nível da melhoria da informação existente nas organizações e que contribuirá decisivamente para a melhoria dos cuidados de saúde prestados aos doentes.

SDAR: a package for plotting and analyzing stratigraphy data in R

Stratigraphic Columns (SC) are the most useful and common ways to represent the eld descriptions (e.g., grain size, thickness of rock packages, and fossil and lithological components) of rock sequences and well logs. In these representations the width of SC vary according to the grain size (i.e., the wider the strata, the coarser the rocks (Miall 1990; Tucker 2011)), and the thickness of each layer is represented at the vertical axis of the diagram. Typically these representations are drawn 'manually' using vector graphic editors (e.g., Adobe Illustrator®, CorelDRAW®, Inskape). Nowadays there are various software which automatically plot SCs, but there are not versatile open-source tools and it is very di cult to both store and analyse stratigraphic information. This document presents Stratigraphic Data Analysis in R (SDAR), an analytical package1 designed for both plotting and facilitate the analysis of Stratigraphic Data in R (R Core Team 2014). SDAR, uses simple stratigraphic data and takes advantage of the exible plotting tools available in R to produce detailed SCs. The main bene ts of SDAR are: (i) used to generate accurate and complete SC plot including multiple features (e.g., sedimentary structures, samples, fossil content, color, structural data, contacts between beds), (ii) developed in a free software environment for statistical computing and graphics, (iii) run on a wide variety of platforms (i.e., UNIX, Windows, and MacOS), (iv) both plotting and analysing functions can be executed directly on R's command-line interface (CLI), consequently this feature enables users to integrate SDAR's functions with several others add-on packages available for R from The Comprehensive R Archive Network (CRAN).

Identifying the urban communities of New York City using bikeshare data from NYC citibike

This study identifies a measure of the cultural importance of an area within a city. It does so by making use of origindestination trip data and the bike stations of the bike share system in New York City as a proxy to study the city. Rarely is movement in the city studied at such a small scale. The change in strength of the similarity of movement between each station is studied. It is the first study to provide this measure of importance for every point in the system. This measure is then related to the characteristics which make for vibrant city communities, namely highly mixed land use types. It reveals that the spatial pattern of important areas remains constant over differing time periods. Communities are then characterised by the land uses surrounding these stations with high measures of importance. Finally it identifies the areas of global cultural importance alongside the areas of local importance to the city.

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.

The role of qualitative data and systems thinking in addressing service decline in market towns

Retail services are a main contributor to municipal budget and are an activity that affects perceived quality-of-life, especially for those with mobility difficulties (e.g. the elderly, low income citizens). However, there is evidence of a decline in some of the services market towns provide to their citizens. In market towns, this decline has been reported all over the western world, from North America to Australia. The aim of this research was to understand retail decline and enlighten on some ways of addressing this decline, using a case study, Thornbury, a small town in the Southwest of England. Data collected came from two participatory approaches: photo-surveys and multicriteria mapping. The interpretation of data came from using participants as analysts, but also, using systems thinking (systems diagramming and social trap theory) for theory building. This research moves away from mainstream economic and town planning perspectives by making use of different methods and concepts used in anthropology and visual sociology (photo-surveys), decision-making and ecological economics (multicriteria mapping and social trap theory). In sum, this research has experimented with different methods, out of their context, to analyse retail decline in a small town. This research developed a conceptual model for retail decline and identified the existence of conflicting goals and interests and their implications for retail decline, as well as causes for these. Most of the potential causes have had little attention in the literature. This research also identified that some of the measures commonly used for dealing with retail decline may be contributing to the causes of retail decline itself. Additionally, this research reviewed some of the measures that can be used to deal with retail decline, implications for policy-making and reflected on the use of the data collection and analysis methods in the context of small to medium towns.

Use of Poisson spatiotemporal regression models for the Brazilian Amazon Forest: malaria count data

INTRODUCTION: Malaria is a serious problem in the Brazilian Amazon region, and the detection of possible risk factors could be of great interest for public health authorities. The objective of this article was to investigate the association between environmental variables and the yearly registers of malaria in the Amazon region using Bayesian spatiotemporal methods. METHODS: We used Poisson spatiotemporal regression models to analyze the Brazilian Amazon forest malaria count for the period from 1999 to 2008. In this study, we included some covariates that could be important in the yearly prediction of malaria, such as deforestation rate. We obtained the inferences using a Bayesian approach and Markov Chain Monte Carlo (MCMC) methods to simulate samples for the joint posterior distribution of interest. The discrimination of different models was also discussed. RESULTS: The model proposed here suggests that deforestation rate, the number of inhabitants per km², and the human development index (HDI) are important in the prediction of malaria cases. CONCLUSIONS: It is possible to conclude that human development, population growth, deforestation, and their associated ecological alterations are conducive to increasing malaria risk. We conclude that the use of Poisson regression models that capture the spatial and temporal effects under the Bayesian paradigm is a good strategy for modeling malaria counts.

Relationship between national culture, democracy and environmental performance: A panel data analysis

This paper demonstrates the significance of culture in examining the relationshipbetween democratic capital and environmental performance.The aim is to examine the relationship among scores on the Environmental Performance Index and the two dimensions of cross cultural variation suggested by Ronald Inglehart and Christian Welzel. Significantional interrelationships among democracy, cultural and environmental sustaintability measures could be found, following the regression results. Firstly, higher levels of democratic capital stock are associated with better environmental performance. Secondly importance to distinguish between cultural groups could be confirmed.

A method to correct the flow distortion of offshore wind data using CFD simulation and experimental wind tunnel tests

The assessment of wind energy resource for the development of deep offshore wind plants requires the use of every possible source of data and, in many cases, includes data gathered at meteorological stations installed at islands, islets or even oil platforms—all structures that interfere with, and change, the flow characteristics. This work aims to contribute to the evaluation of such changes in the flow by developing a correction methodology and applying it to the case of Berlenga island, Portugal. The study is performed using computational fluid dynamic simulations (CFD) validated by wind tunnel tests. In order to simulate the incoming offshore flow with CFD models a wind profile, unknown a priori, was established using observations from two coastal wind stations and a power law wind profile was fitted to the existing data (a=0.165). The results show that the resulting horizontal wind speed at 80 m above sea level is 16% lower than the wind speed at 80 m above the island for the dominant wind direction sector.

Assessment by doppler ultrasound of entheseal lesions in spondyloarthritis : a longitudial study to determine structural damage and disease activity lesions

RESUMO: Enthesitis is the hallmark of spondyloarthritis (SpA), and is observed in all subtypes. Wide information on SpA abnormalities, including synovitis, tendinitis and enthesitis, can be efficiently perceived by Doppler ultrasound. Furthermore, several studies on imaging of enthesis showed that imaging techniques are better than clinical examination to detect enthesis alterations; and vascularized enthesitis detected by Doppler ultrasound appears to be a valuable diagnostic tool to confirm SpA diagnosis. However, data published until now concerning entheseal elementary alterations that characterize SpA enthesitis (enthesis inflammatory activity) or enthesopathy (permanent structural changes) reflect rather the authors’ empiric opinion than a methodological validation process. In this sense it seems crucial to identify elementary entheseal lesions associated with activity or damage, in order to improve monitoring and treatment response in SpA patients. The development of better assessment tools is today a challenge and a need in SpA. The first study of this thesis focused on the analysis of the reliability of inter-lector and inter-ultrasonography equipment of Madrid sonography enthesitis index (MASEI). Fundamental data for the remaining unrolling project validity. In the second and third studies we concerned about two entheseal elemental lesions: erosions and bursa. In literature erosions represent a permanent structural damage, being useful for monitoring joint injury, disease activity and therapeutic response in many rheumatic diseases; and to date, this concept has been mostly applied in rheumatoid arthritis (RA). Unquestionably, erosion is a tissue-related damage and a structural change. However, the hypothesis that we decided to test was if erosions represent a permanent structural change that can only grow and worsen over time, as occurs in RA, or a transitory alteration. A longitudinal study of early SpA patients was undertaken, and the Achilles enthesis was used as a model. Our results strongly suggested that previously detected erosions could disappear during the course of the disease, being consistent with the dynamic behavior of erosion over time. Based on these striking results it seems reasonable to suggest that the new-bone formation process in SpA could be associated with the resolution of cortical entheseal erosion over time. These results could also be in agreement with the apparent failure of anti-tumor necrosis factor (TNF) therapies to control bone proliferation in SpA; and with the relation of TNF-α, Dickkopf-related protein 1 (Dkk-1) and the regulatory molecule of the Wnt signaling pathway in the bone proliferation in SpA. In the same model, we then proceeded to study the enthesis bursa. Interestingly, the Outcome Measures in Rheumatology Clinical Trials (OMERACT) enthesopathy definition does not include bursa as an elementary entheseal lesion. Nonetheless, bursa was included in 46% of the enthesis studies in a recently systematic literature review, being in agreement with the concept of “synovio-entheseal complex” that includes the link between enthesitis and osteitis in SpA. It has been clarified in recent data that there is not only a close functional integration of the enthesis with the neighboring bone, but also a connection between enthesitis and synovitis. Therefore, we tried to assess the prevalence and relevance of the bursa-synovial lesion in SpA. Our findings showed a significant increase of Achilles bursa presence and thickness in SpA patients compared to controls (healthy/mechanical controls and RA controls). These results raise awareness to the need to improve the enthesopathy ultrasonographic definition. In the final work of this thesis, we have explored new perspectives, not previously reported, about construct validity of enthesis ultrasound as a possible activity outcome in SpA. We performed a longitudinal Achilles enthesis ultrasound study in patients with early SpA. Achilles ultrasound examinations were performed at baseline, six- and twelve-month time periods and compared with clinical outcome measures collected at basal visit. Our results showed that basal erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) are higher in patients with Doppler signal in enthesis, and even that higher basal ESR, CRP and Ankylosing Spondylitis Disease Activity Score (ASDAS) predicted a higher Doppler signal (an ultrasound alteration accepted as representative of inflammation) six months later. Patients with very high disease activity assessed by ASDAS (>3.5) at baseline had significantly higher Achilles total ultrasound score verified at the same time; and ASDAS <1.3 predicted no Doppler signal at six and twelve months. This seems to represent a connection between classical biomarkers and clinical outcomes associated with SpA activity and Doppler signal, not only at the same time, but also for the following months. Remarkably, patients with inactive disease (ASDAS < 1.3) at baseline had no Doppler signal at six and twelve months. These findings reinforce the potential use of ultrasound related techniques for disease progression assessment and prognosis purposes. Intriguingly, Ankylosing Spondylitis Disease Activity Index (BASDAI) didn’t show significant differences between different cut-offs concerning ultrasound lesions or Doppler signal, while verified with ASDAS. These results seem to indicate that ASDAS reflects better than BASDAI what happens in the enthesis. The work herein discussed clearly shows the potential utility of ultrasound in enthesis assessment in SpA patients, and can be important for the development of ultrasound activity and structural damage scores for diagnosis and monitoring purposes. Therefore, local promotion of this technique constitutes a medical intervention that is worth being tested in SpA patients for diagnosis, monitoring and prognosis purposes.

Indicadores de qualidade na emergência médica pré-hospitalar : painel operacional para o INEM, I.P.

RESUMO - A Emergência Médica Pré-Hospitalar é uma parte importante na cadeia de cuidados de saúde, quer pela gravidade das situações a que atende, quer por funcionar como gatekeeper. O estudo é dedicado a instrumentos de medição e em simultâneo a medições de qualidade como processo de melhoria contínua da qualidade na EMPH. Existem projetos a nível internacional para implementação de painéis de indicadores, alguns atribuem significativa relevância aos processos assistenciais. O European Emergency Data Project (EDD) foi selecionado para servir como painel de indicadores a explorar neste trabalho. Porque a nível científico está bem desenhado, as definições e variáveis estão bem explicitadas e interessa ao INEM, I.P. utilizar um painel que lhe permita um benchmarking. Criou-se um dashboard para os indicadores selecionados e com ele analisaram-se os dados para aferir a qualidade do SEM. Não foi possível, pela sua inexistência, coletar dados para dois dos indicadores propostos. Foram apresentadas propostas de melhoria no sistema de captação de dados do INEM, I.P. para que a instituição possa monitorizar periodicamente os indicadores selecionados. A existência de dados e a sua fiabilidade para utilizar na medição por indicadores é algo que se explorou neste trabalho de campo, e as fraquezas encontradas foram matéria para oportunidades, recomendações, e caminho para discussão e o fortalecimento da instituição.

Weight concerns scale applied to college students : Comparison between pencil-and-paper and online formats

Online data collection is becoming increasingly common and has some advantages compared to traditional paper-and-pencil formats, such as reducing loss of data, increasing participants' privacy, and decreasing the effect of social desirability. However, the validity and reliability of this administration format must be established before results can be considered acceptable. The aim of this study was to evaluate the validity, reliability, and equivalence of paper-and-pencil and online versions of the Weight Concerns Scale (WCS) when applied to Brazilian university students. A crossover design was used, and the Portuguese version of the WCS (in both paper-and-pencil and online formats) was completed by 100 college students. The results indicated adequate fit in both formats. The simultaneous fit of data for both groups was excellent, with strong invariance between models. Adequate convergent validity, internal consistency, and mean score equivalence of the WCS in both formats were observed. Thus, the WCS presented adequate reliability and validity in both administration formats, with equivalence/stability between answers.

Contributos para a validação da escala de auto-eficácia na amamentação para português

Dissertação de Mestrado apresentada ao ISPA - Instituto Universitário