Reabilitação de edifícios: enquadramento e estudo da reabilitação num grupo empresarial

Dissertação para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização em Edificações

Construction of womanhood in the bengali language of Bangladesh

The subject-matter of this essay is gender justice in language which, as I argue, may be achieved through the development of a gender-related approach to linguistic human rights. The last decades of the 20th century, globally marked by a “gender shift” in attitudes to language policy, gave impetus to the social movement for promoting linguistic gender equality. It was initiated in Western Europe and nowadays is moving eastwards, as ideas of gender democracy progress into developing countries. But, while in western societies gender discrimination through language, or linguistic sexism, was an issue of concern for over three decades, in developing countries efforts to promote gender justice in language are only in their infancy. My argument is that to promote gender justice in language internationally it is necessary to acknowledge the rights of women and men to equal representation of their gender in language and speech and, therefore, raise a question of linguistic rights of the sexes. My understanding is that the adoption of the Universal Declaration of Linguistic Rights in 1996 provided this opportunity to address the problem of gender justice in language as a human rights issue, specifically as a gender dimension of linguistic human rights.

A expressão plástica e os materiais pedagógicos, na Educação Pré-Escolar e no 1.º Ciclo do Ensino Básico : perspetivas e diálogos

Mestrado (PES II), Educação Pré-Escolar e Ensino do 1.º Ciclo do Ensino Básico, 24 de Junho de 2015, Universidade dos Açores.

An Evaluation of Local Feature Combiners for Robot Visual Localization

In the last decade, local image features have been widely used in robot visual localization. To assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image to those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, we compare several candidate combiners with respect to their performance in the visual localization task. A deeper insight into the potential of the sum and product combiners is provided by testing two extensions of these algebraic rules: threshold and weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance. The voting method, whilst competitive to the algebraic rules in their standard form, is shown to be outperformed by both their modified versions.

Construction and evaluation of cysteine selective electrodes for FIA analysis of pharmaceuticals

A flow injection analysis (FIA) system comprising a cysteine selective electrode as detection system was developed for determination of this amino acid in pharmaceuticals. Several electrodes were constructed for this purpose, having PVC membranes with different ionic exchangers and mediator solvents. Better working characteristics were attained with membranes comprising o-nitrophenyl octyl ether as mediator solvent and a tetraphenylborate based ionic-sensor. Injection of 500 µL standard solutions into an ionic strength adjuster carrier (3x10-3 M) of barium chloride flowing at 2.4mL min-1, showed linearity ranges from 5.0x10-5 to 5.0x10-3 M, with slopes of 76.4±0.6mV decade-1 and R2>0.9935. Slope decreased significantly under the requirement of a pH adjustment, selected at 4.5. Interference of several compounds (sodium, potassium, magnesium, barium, glucose, fructose, and sucrose) was estimated by potentiometric selectivity coefficients and considered negligible. Analysis of real samples were performed and considered accurate, with a relative error to an independent method of +2.7%.

Chlormequat selective electrodes: construction, evaluation and application at FIA systems

A flow injection analysis (FIA) system having a chlormequat selective electrode is proposed. Several electrodes with poly(vinyl chloride) based membranes were constructed for this purpose. Comparative characterization suggestedthe use of membrane with chlormequat tetraphenylborate and dibutylphthalate. On a single-line FIA set-up, operating with 1x10-2 mol L-1 ionic strength and 6.3 pH, calibration curves presented slopes of 53.6±0.4mV decade-1 within 5.0x10-6 and1.0x10-3 mol L-1, andsquaredcorrelation coefficients >0.9953. The detection limit was 2.2x10-6 mol L-1 and the repeatability equal to ±0.68mV (0.7%). A dual-channel FIA manifold was therefore constructed, enabling automatic attainment of previous ionic strength andpH conditions and thus eliminating sample preparation steps. Slopes of 45.5±0.2mV decade -1 along a concentration range of 8.0x10-6 to 1.0x10-3 mol L-1 with a repeatability ±0.4mV (0.69%) were obtained. Analyses of real samples were performed, and recovery gave results ranging from 96.6 to 101.1%.

Influence of wearing an unstable shoe construction on compensatory control of posture

This study investigated the influence of wearing unstable shoe construction (WUS) on compensatory postural adjustments (CPA) associated with external perturbations. Thirty-two subjects stood on a force platform resisting an anterior-posterior horizontal force applied to a pelvic belt via a cable, which was suddenly released. They stood under two conditions: barefoot and WUS. The electromyographic (EMG) activity of gastrocnemius medialis, tibialis anterior, rectus femoris, biceps femoris, rectus abdominis, and erector spinae muscles and the center of pressure (CoP) displacement were acquired to study CPA. The EMG signal was used to assess individual muscle activity and latency, antagonist co-activation and reciprocal activation at joint and muscle group levels. Compared to barefoot, WUS led to: (1) increased gastrocnemius medialis activity, (2) increased total agonist activity, (3) decreased antagonist co-activation at the ankle joint and muscle group levels, (4) increased reciprocal activation at the ankle joint and muscle group levels, and (5) decrease in all muscle latencies. No differences were observed in CoP displacement between conditions. These findings demonstrate that WUS led to a reorganization of the postural control system associated to improved performance of some components of postural control responses.

Feature selection for clustering categorical data with an embedded modelling approach

Research on the problem of feature selection for clustering continues to develop. This is a challenging task, mainly due to the absence of class labels to guide the search for relevant features. Categorical feature selection for clustering has rarely been addressed in the literature, with most of the proposed approaches having focused on numerical data. In this work, we propose an approach to simultaneously cluster categorical data and select a subset of relevant features. Our approach is based on a modification of a finite mixture model (of multinomial distributions), where a set of latent variables indicate the relevance of each feature. To estimate the model parameters, we implement a variant of the expectation-maximization algorithm that simultaneously selects the subset of relevant features, using a minimum message length criterion. The proposed approach compares favourably with two baseline methods: a filter based on an entropy measure and a wrapper based on mutual information. The results obtained on synthetic data illustrate the ability of the proposed expectation-maximization method to recover ground truth. An application to real data, referred to official statistics, shows its usefulness.

Diagnóstico e análise da rede social: o caso da prestação de cuidados continuados a crianças com diabetes

Mestrado em Intervenção Sócio-Organizacional na Saúde - Ramo de especialização: Qualidade e Tecnologias da Saúde

Enhancing Multimodal Silent Speech Interfaces With Feature Selection

In research on Silent Speech Interfaces (SSI), different sources of information (modalities) have been combined, aiming at obtaining better performance than the individual modalities. However, when combining these modalities, the dimensionality of the feature space rapidly increases, yielding the well-known "curse of dimensionality". As a consequence, in order to extract useful information from this data, one has to resort to feature selection (FS) techniques to lower the dimensionality of the learning space. In this paper, we assess the impact of FS techniques for silent speech data, in a dataset with 4 non-invasive and promising modalities, namely: video, depth, ultrasonic Doppler sensing, and surface electromyography. We consider two supervised (mutual information and Fisher's ratio) and two unsupervised (meanmedian and arithmetic mean geometric mean) FS filters. The evaluation was made by assessing the classification accuracy (word recognition error) of three well-known classifiers (knearest neighbors, support vector machines, and dynamic time warping). The key results of this study show that both unsupervised and supervised FS techniques improve on the classification accuracy on both individual and combined modalities. For instance, on the video component, we attain relative performance gains of 36.2% in error rates. FS is also useful as pre-processing for feature fusion. Copyright © 2014 ISCA.

Incremental filter and wrapper approaches for feature discretization

Discrete data representations are necessary, or at least convenient, in many machine learning problems. While feature selection (FS) techniques aim at finding relevant subsets of features, the goal of feature discretization (FD) is to find concise (quantized) data representations, adequate for the learning task at hand. In this paper, we propose two incremental methods for FD. The first method belongs to the filter family, in which the quality of the discretization is assessed by a (supervised or unsupervised) relevance criterion. The second method is a wrapper, where discretized features are assessed using a classifier. Both methods can be coupled with any static (unsupervised or supervised) discretization procedure and can be used to perform FS as pre-processing or post-processing stages. The proposed methods attain efficient representations suitable for binary and multi-class problems with different types of data, being competitive with existing methods. Moreover, using well-known FS methods with the features discretized by our techniques leads to better accuracy than with the features discretized by other methods or with the original features. (C) 2013 Elsevier B.V. All rights reserved.

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.

Design and construction of tunnels in zones subjected to high convergences

The economic development of a region depends on the speed that people and goods can travel. The reduction of people and goods travel time can be achieved by planning smooth road layouts, which are obtained by crossing natural obstacles such as hills, by tunneling at great depths, and allowing the reduction of the road alignment length. The stress state in rock masses at such depths, either because of the overburden or due to the tectonic conditions of the rock mass induces high convergences of the tunnel walls. These high convergence values are incompatible with the supports structural performance installed in the excavation stabilization. In this article it is intended to evaluate and analyze some of the solutions already implemented in several similar geological and geotechnical situations, in order to establish a methodological principle for the design of the tunnels included in a highway section under construction in the region influenced by the Himalayas, in the state of Himachal Pradesh (India) and referenced by "four laning of Kiratpur to Ner Chowk section".