Improving accuracy for OTD based 3G geolocation in real urban/suburban environments

This paper presents the recent research results about the development of a Observed Time Difference (OTD) based geolocation algorithm based on network trace data, for a real Universal Mobile Telecommunication System (UMTS) Network. The initial results have been published in [1], the current paper focus on increasing the sample convergence rate, and introducing a new filtering approach based on a moving average spatial filter, to increase accuracy. Field tests have been carried out for two radio environments (urban and suburban) in the Lisbon area, Portugal. The new enhancements produced a geopositioning success rate of 47% and 31%, and a median accuracy of 151 m and 337 m, for the urban and suburban environments, respectively. The implemented filter produced a 16% and 20% increase on accuracy, when compared with the geopositioned raw data. The obtained results are rather promising in accuracy and geolocation success rate. OTD positioning smoothed by moving average spatial filtering reveals a strong approach for positioning trace extracted events, vital for boosting Self-Organizing Networks (SON) over a 3G network.

Atuação do fisioterapeuta dermatofuncional e seu reconhecimento pelos profissionais de saúde da região de Lisboa

Mestrado em Fisioterapia

Mobile collaborative cloudless computing

Although the computational power of mobile devices has been increasing, it is still not enough for some classes of applications. In the present, these applications delegate the computing power burden on servers located on the Internet. This model assumes an always-on Internet connectivity and implies a non-negligible latency. The thesis addresses the challenges and contributions posed to the application of a mobile collaborative computing environment concept to wireless networks. The goal is to define a reference architecture for high performance mobile applications. Current work is focused on efficient data dissemination on a highly transitive environment, suitable to many mobile applications and also to the reputation and incentive system available on this mobile collaborative computing environment. For this we are improving our already published reputation/incentive algorithm with knowledge from the usage pattern from the eduroam wireless network in the Lisbon area.

Fisioterapia cardiorrespiratória em pacientes vítimas de queimaduras: projeto de intervenção precoce

Mestrado em Fisioterapia

The evolution of user mobility on the Eduroam network

The emergence of smartphones with Wireless LAN (WiFi) network interfaces brought new challenges to application developers. The expected increase of users connectivity will impact their expectations for example on the performance of background applications. Unfortunately, the number and breadth of the studies on the new patterns of user mobility and connectivity that result from the emergence of smartphones is still insufficient to support this claim. This paper contributes with preliminary results on a large scale study of the usage pattern of about 49000 devices and 31000 users who accessed at least one access point of the eduroam WiFi network on the campuses of the Lisbon Polytechnic Institute. Results confirm that the increasing number of smartphones resulted in significant changes to the pattern of use, with impact on the amount of traffic and users connection time.

Psoríase: o impacto da doença no dia-a-dia dos portadores

Mestrado em Fisioterapia

The daily and hourly energy consumption and load forecasting using artifitial neural network method: a case study using a set of 93 households in Portugal

It is important to understand and forecast a typical or a particularly household daily consumption in order to design and size suitable renewable energy systems and energy storage. In this research for Short Term Load Forecasting (STLF) it has been used Artificial Neural Networks (ANN) and, despite the consumption unpredictability, it has been shown the possibility to forecast the electricity consumption of a household with certainty. The ANNs are recognized to be a potential methodology for modeling hourly and daily energy consumption and load forecasting. Input variables such as apartment area, numbers of occupants, electrical appliance consumption and Boolean inputs as hourly meter system were considered. Furthermore, the investigation carried out aims to define an ANN architecture and a training algorithm in order to achieve a robust model to be used in forecasting energy consumption in a typical household. It was observed that a feed-forward ANN and the Levenberg-Marquardt algorithm provided a good performance. For this research it was used a database with consumption records, logged in 93 real households, in Lisbon, Portugal, between February 2000 and July 2001, including both weekdays and weekend. The results show that the ANN approach provides a reliable model for forecasting household electric energy consumption and load profile. © 2014 The Author.

Determination of airborne nanoparticles in elderly care centres

According to numerous studies, airborne nanoparticles have a potential to produce serious adverse human health effects when deposited into the respiratory tract. The most important parts of the lung are the alveolar regions with their enormous surface areas and potential to transfer nanoparticles into the blood stream. These effects may be potentiated in case of the elderly, since this population is more susceptible to air pollutants in general and more to nanoparticles than larger particles. The main goal of this investigation was to determine the exposure of institutionalized elders to nanoparticles using Nanoparticle Surface Area Monitor (NSAM) equipment to calculate the deposited surface area (DSA) of nanoparticles into elderly lungs. In total, 193 institutionalized individuals over 65 yr of age were examined in four elderly care centers (ECC). The occupancy daily pattern was achieved by applying a questionnaire, and it was concluded that these subjects spent most of their time indoors, including the bedroom and living room, the indoor microenvironments with higher prevalence of elderly occupancy. The deposited surface area ranged from 10 to 46 mu m(2)/cm(3). The living rooms presented significantly higher levels compared with bedrooms. Comparing PM10 concentrations with nanoparticles deposited surface area in elderly lungs, it is conceivable that living rooms presented the highest concentration of PM10 and were similar to the highest average DSA. The temporal distribution of DSA was also assessed. While data showed a quantitative fluctuation in values in bedrooms, high peaks were detected in living rooms.

Avaliação da gestão do tempo no contexto da organização do trabalho dos técnicos de radiologia

Mestrado em Intervenção Sócio-Organizacional na Saúde - Área de especialização: Políticas de Administração e Gestão de Serviços de Saúde

Consumo de benzodiazepinas por idosos institucionalizados: inapropriação, qualidade de sono e contributo para a segurança na medicação

A racionalização do uso de medicamentos constitui-se como um fator contribuinte para a melhoria da segurança do doente, no que respeita à segurança da medicação e do medicamento, especialmente quando este é administrado a idosos. A avaliação do uso de medicamentos potencialmente inapropriados no idoso constitui-se como uma medida que concorre para evitar, prevenir ou corrigir eventos adversos associados ao seu uso. As benzodiazepinas (BZD) são uma das classes de medicamentos mais prescritas em idosos. No entanto, e apesar da sua utilidade clínica algumas são consideradas inapropriadas nesta faixa etária por potenciarem o efeito sedativo e aumentar a incidência de quedas e fraturas. A longo prazo, na promoção da qualidade do sono, a sua efetividade é discutível já que a toma de uma benzodiazepina para a resolução de um problema como o sono, muitas vezes pontual, passa a ser um problema crónico de exigência de toma contínua, sem que a qualidade deste seja restabelecida, pondo em risco a segurança do doente.

The effect of superplasticizers on the mechanical performance of concrete made with fine recycled concrete aggregates

It is considered that using crushed recycled concrete as aggregate for concrete production is a viable alternative to dumping and would help to conserve abiotic resources. This use has fundamentally been based on the coarse fraction because the fine fraction is likely to degrade the performance of the resulting concrete. This paper presents results from a research work undertaken at Institut Superior Tecnico (IST), Lisbon, Portugal, in which the effects of incorporating two types of superplasticizer on the mechanical performance of concrete containing fine recycled aggregate were evaluated. The purpose was to see if the addition of superplasticizer would offset the detrimental effects associated with the use of fine recycled concrete aggregate. The experimental programme is described and the results of tests for splitting tensile strength, modulus of elasticity and abrasion resistance are presented. The relative performance of concrete made with recycled aggregate was found to decrease. However, the same concrete with admixtures in general exhibited a better mechanical performance than the reference mixes without admixtures or with a less active superplasticizer. Therefore, it is argued that the mechanical performance of concrete made with fine recycled concrete aggregates can be as good as that of conventional concrete, if superplasticizers are used to reduce the water-cement ratio of the former concrete.

The effect of superplasticizers on the workability and compressive strength of concrete made with fine recycled concrete aggregates

The reuse of structural concrete elements to produce new concrete aggregates is accepted as an alternative to dumping them and is favourable to the sustainability of natural reserves. Even though the construction sector is familiar with the use of coarse recycled concrete aggregates, the recycled concrete fines are classified as less noble resources. This research sets out to limit the disadvantages associated with the performance of concrete containing fine recycled concrete aggregates through the use of superplasticisers. Two types of latest generation superplasticisers were used that differ in terms of water reduction capacity and robustness, and the workability, density and compressive strength of each of the compositions analysed were then compared: a reference concrete, with no plasticisers, and concrete mixes with the superplasticisers. For each concrete family mixes with 0%, 10%, 30%, 50% and 100% replacement ratios of fine natural aggregates (FNA) by fine recycled concrete aggregates (FRA) were analysed. Concrete with incorporation of recycled aggregates was found to have poorer relative performance. The mechanical performance of concrete with recycled aggregates and superplasticisers was generally superior to that of the reference concrete with no admixtures and of conventional concrete with lower performance superplasticisers.

An unsupervised approach to feature discretization and selection

Many learning problems require handling high dimensional datasets with a relatively small number of instances. Learning algorithms are thus confronted with the curse of dimensionality, and need to address it in order to be effective. Examples of these types of data include the bag-of-words representation in text classification problems and gene expression data for tumor detection/classification. Usually, among the high number of features characterizing the instances, many may be irrelevant (or even detrimental) for the learning tasks. It is thus clear that there is a need for adequate techniques for feature representation, reduction, and selection, to improve both the classification accuracy and the memory requirements. In this paper, we propose combined unsupervised feature discretization and feature selection techniques, suitable for medium and high-dimensional datasets. The experimental results on several standard datasets, with both sparse and dense features, show the efficiency of the proposed techniques as well as improvements over previous related techniques.

Efficient feature selection filters for high-dimensional data

Feature selection is a central problem in machine learning and pattern recognition. On large datasets (in terms of dimension and/or number of instances), using search-based or wrapper techniques can be cornputationally prohibitive. Moreover, many filter methods based on relevance/redundancy assessment also take a prohibitively long time on high-dimensional. datasets. In this paper, we propose efficient unsupervised and supervised feature selection/ranking filters for high-dimensional datasets. These methods use low-complexity relevance and redundancy criteria, applicable to supervised, semi-supervised, and unsupervised learning, being able to act as pre-processors for computationally intensive methods to focus their attention on smaller subsets of promising features. The experimental results, with up to 10(5) features, show the time efficiency of our methods, with lower generalization error than state-of-the-art techniques, while being dramatically simpler and faster.

On the assessment of exposure to airborne ultrafine particles in urban environments

The aim of this study was to contribute to the assessment of exposure levels of ultrafine particles in the urban environment of Lisbon, Portugal, due to automobile traffic, by monitoring lung deposited alveolar surface area (resulting from exposure to ultrafine particles) in a major avenue leading to the town center during late spring, as well as in indoor buildings facing it. Data revealed differentiated patterns for week days and weekends, consistent with PM2.5 and PM10 patterns currently monitored by air quality stations in Lisbon. The observed ultrafine particulate levels may be directly correlated with fluxes in automobile traffic. During a typical week, amounts of ultrafine particles per alveolar deposited surface area varied between 35 and 89.2 mu m2/cm3, which are comparable with levels reported for other towns in Germany and the United States. The measured values allowed for determination of the number of ultrafine particles per cubic centimeter, which are comparable to levels reported for Madrid and Brisbane. In what concerns outdoor/indoor levels, we observed higher levels (32 to 63%) outdoors, which is somewhat lower than levels observed in houses in Ontario.