Contribution of the evaluation strategy and the use of hearing protection for the uncertainty associated with occupational exposure to noise

Doctoral Thesis for PhD degree in Industrial and Systems Engineering

Hand gesture recognition for human computer interaction : a comparative study of different image features

Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.

Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

The greener grass: da autorrepresentação em Alanis Morissette

Tese de Doutoramento em Ciências da Literatura - Especialidade em Teoria da Literatura

Metallic glass/PVDF magnetoelectric energy harvester working up to the radiofrequency range

Companies and researchers involved in developing miniaturized electronic devices face the basic problem of the needed batteries size, finite life of time and environmental pollution caused by their final deposition. The current trends to overcome this situation point towards Energy Harvesting technology. These harvesters (or scavengers) store the energy from sources present in the ambient (as wind, solar, electromagnetic, etc) and are costless for us. Piezoelectric devices are the ones that show a higher power density, and materials as ceramic PZT or polymeric PVDF have already demonstrated their ability to act as such energy harvester elements. Combinations between piezoelectric and electromagnetic mechanism have been also extensively investigated. Nevertheless, the power generated by these combinations is limited under the application of small magnetic fields, reducing the performance of the energy harvester [1]. In the last years the appearance of magnetoelectric (ME) devices, in which the piezoelectric deformation is driven by the magnetostrictive element, enables to extract the energy of very small electromagnetic signals through the generated magnetoelectric voltage at the piezoelectric element. However, very little work has been done testing PVDF polymer as piezoelectric constituent of the ME energy harvester device, and only to be proposed as a possibility of application [2]. Among the advantages of using piezopolymers for vibrational energy harvesting we can remember that they are ductile, resilient to shock, deformable and lightweight. In this work we demonstrate the feasibility of using magnetostrictive Fe-rich magnetic amorphous alloys/piezoelectric PVDF sandwich-type laminated ME devices as energy harvesters. A very simple experimental set-up will show how these laminates can extract energy, in amounts of μW, from an external AC field.

Postoperative self-efficacy and psychological morbidity in radical prostatectomy

Objective: evaluate the general and perceived self-efficacy, psychological morbidity, and knowledge about postoperative care of patients submitted to radical prostatectomy. Identify the relationships between the variables and know the predictors of self-efficacy. Method: descriptive, cross-sectional study, conducted with 76 hospitalized men. The scales used were the General and Perceived Self-efficacy Scale and the Hospital Anxiety and Depression Scale, in addition to sociodemographic, clinical and knowledge questionnaires. Results: a negative relationship was found for self-efficacy in relation to anxiety and depression. Psychological morbidity was a significant predictor variable for self-efficacy. An active professional situation and the waiting time for surgery also proved to be relevant variables for anxiety and knowledge, respectively. Conclusion: participants had a good level of general and perceived self-efficacy and small percentage of depression. With these findings, it is possible to produce the profile of patients about their psychological needs after radical prostatectomy and, thus, allow the nursing professionals to act holistically, considering not only the need for care of physical nature, but also of psychosocial nature.

Using balanced scorecards to evaluate the data warehouse system utility

Dissertação de mestrado em Systems Engineering

Criação de um sistema de apoio para o suporte avançado de vida

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)

Concrete with triphasic conductive materials for self-monitoring of cracking development subjected to flexure

In this study, the macro steel fiber (SF), carbon fiber (CF) and nano carbon black (NCB) as triphasic conductive materials were added into concrete, in order to improve the conductivity and ductility of concrete. The influence of NCB, SF and CF on the post crack behavior and conductivity of concrete was explored. The effect of the triphasic conductive materials on the self-diagnosing ability to the load–deflection property and crack widening of conductive concrete member subjected to bending were investigated. The relationship between the fractional change in surface impedance (FCR) and the crack opening displacement (COD) of concrete beams with conductive materials has been established. The results illustrated that there is a linear relationship between COD and FCR.

Biomimetic supramolecular designs for the controlled release of growth factors in bone regeneration

The extracellular matrix (ECM) of tissues is an assembly of insoluble macromolecules that specifically interact with soluble bioactive molecules and regulate their distribution and availability to cells. Recapitulating this ability has been an important target in controlled growth factor delivery strategies for tissue regeneration and requires the design of multifunctional carriers. This review describes the integration of supramolecular interactions on the design of delivery strategies that encompass self-assembling and engineered affinity components to construct advanced biomimetic carriers for growth factor delivery. Several glycan- and peptide-based self-assemblies reported in the literature are highlighted and commented upon. These examples demonstrate how molecular design and chemistry are successfully employed to create versatile multifunctional molecules which self-assemble/disassemble in a precisely predicted manner, thus controlling compartmentalization, transport and delivery. Finally, we discuss whether recent advances in the design and preparation of supramolecular delivery systems have been sufficient to drive real translation towards a clinical impact. 

Optimization of magnetoelectric composites based on electroactive polymers for energy harvesting and sensor application

Tese de Doutoramento em Engenharia de Materiais.

Hand gesture recognition system based in computer vision and machine learning: Applications on human-machine interaction

Tese de Doutoramento em Engenharia de Eletrónica e de Computadores

Type 2 diabetes-related variants influence the risk of developing multiple myeloma: results from the IMMEnSE consortium

Type 2 diabetes (T2D) has been suggested to be a risk factor for multiple myeloma (MM), but the relationship between the two traits is still not well understood. The aims of this study were to evaluate whether 58 genome-wide-association-studies (GWAS)-identified common variants for T2D influence the risk of developing MM and to determine whether predictive models built with these variants might help to predict the disease risk. We conducted a case–control study including 1420 MM patients and 1858 controls ascertained through the International Multiple Myeloma (IMMEnSE) consortium. Subjects carrying the KCNQ1rs2237892T allele or the CDKN2A-2Brs2383208G/G, IGF1rs35767T/T and MADDrs7944584T/T genotypes had a significantly increased risk of MM (odds ratio (OR)=1.32–2.13) whereas those carrying the KCNJ11rs5215C, KCNJ11rs5219T and THADArs7578597C alleles or the FTOrs8050136A/A and LTArs1041981C/C genotypes showed a significantly decreased risk of developing the disease (OR=0.76–0.85). Interestingly, a prediction model including those T2D-related variants associated with the risk of MM showed a significantly improved discriminatory ability to predict the disease when compared to a model without genetic information (area under the curve (AUC)=0.645 vs AUC=0.629; P=4.05×10-06). A gender-stratified analysis also revealed a significant gender effect modification for ADAM30rs2641348 and NOTCH2rs10923931 variants (Pinteraction=0.001 and 0.0004, respectively). Men carrying the ADAM30rs2641348C and NOTCH2rs10923931T alleles had a significantly decreased risk of MM whereas an opposite but not significant effect was observed in women (ORM=0.71 and ORM=0.66 vs ORW=1.22 and ORW=1.15, respectively). These results suggest that TD2-related variants may influence the risk of developing MM and their genotyping might help to improve MM risk prediction models.

The Portuguese version of the Psychological Adjustment to Separation Test-Part A (PAST-A): a study with recently and non-recently divorced adults

Past research has demonstrated that divorced adults show more health problems and psychological distress than married adults. Considering the high prevalence rates of divorce among Western countries, new and robust measures should be developed to measure psychological distress after this specific transition in adulthood. The aim of this study was to adapt and validate a Portuguese version of the Psychological Adjustment to Separation Test-Part A (PAST-A; Sweeper and Halford in J Family Psychol 20(4):632–640, 2006). PAST-A is a self-report measure that assesses two key dimensions of separation adjustment problems: lonely-negativity and former partner attachment. Psychometric properties of the Portuguese version of PAST-A were assessed in terms of factor structure, internal consistency, and convergent and divergent validity, in an online convenience sample with divorced adults (N = 460). The PAST-A two-factor structure was confirmed by exploratory and confirmatory factor analyses, with each factor demonstrating very satisfactory internal consistency and good convergence. In terms of discriminant validity, the Portuguese PAST-A reveals a distinct factor from psychological growth after divorce. The results provided support for the use of the Portuguese PAST-A with divorced adults and also suggested that the explicative factors of the psychological adjustment to divorce may be cross-cultural stable. The non-existence of validated divorce-related well-being measures and its implications for divorce research are also discussed.

Pervasive decision support to predict football corners and goals by means of data mining

Football is considered nowadays one of the most popular sports. In the betting world, it has acquired an outstanding position, which moves millions of euros during the period of a single football match. The lack of profitability of football betting users has been stressed as a problem. This lack gave origin to this research proposal, which it is going to analyse the possibility of existing a way to support the users to increase their profits on their bets. Data mining models were induced with the purpose of supporting the gamblers to increase their profits in the medium/long term. Being conscience that the models can fail, the results achieved by four of the seven targets in the models are encouraging and suggest that the system can help to increase the profits. All defined targets have two possible classes to predict, for example, if there are more or less than 7.5 corners in a single game. The data mining models of the targets, more or less than 7.5 corners, 8.5 corners, 1.5 goals and 3.5 goals achieved the pre-defined thresholds. The models were implemented in a prototype, which it is a pervasive decision support system. This system was developed with the purpose to be an interface for any user, both for an expert user as to a user who has no knowledge in football games.