Melhoria e normalização de ferramentas de apoio à produção aplicando ferramentas Lean

Dissertação de mestrado integrado em Engenharia e Gestão Industrial

Performance assessment of electrically small antennas for implantable microsystems with wireless power and communications

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

Avaliação da camada intermetálica em placas de circuito impresso com acabamento superficial HASL com diferentes processos de soldagem

Dissertação de mestrado integrado em Engenharia de Materiais

Repository power: how repositories can support Open Access mandates

Many funding agencies have Open Access mandates in place, but how often are scientific publications as outputs linked to funding details? The benefits of linking funding information to publications as part of the deposit workflow can assist in adhering to Open Access mandates. This paper examines how OpenAIRE – Open Access Infrastructure for Research in Europe – can ease monitoring Open Access and reporting processes for funders, and presents some results and opportunities. It also outlines how it relies on cleaned and curated repository content, a vital cog in the ever turning wheel of the global scholarly landscape, and the benefits it brings.

Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue

Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactorygustatory sensations). However, it is not guaranteed that trained panelist can correctly classify monovarietal extra-virgin olive oils according to olive cultivar. In this work, the potential application of human (sensory panelists) and artificial (electronic tongue) sensory evaluation of olive oils was studied aiming to discriminate eight single-cultivar extra-virgin olive oils. Linear discriminant, partial least square discriminant, and sparse partial least square discriminant analyses were evaluated. The best predictive classification was obtained using linear discriminant analysis with simulated annealing selection algorithm. A low-level data fusion approach (18 electronic tongue signals and nine sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination.

Titanium oxide adhesion layer for high temperature annealed Si/Si3N4/TiOx/Pt/LiCoO2 battery structures

This work describes the influence of a high annealing temperature of about 700C on the Si(substrate)/Si3N4/TiOx/Pt/LiCoO2 multilayer system for the fabrication of all-solid-state lithium ion thin film microbatteries. Such microbatteries typically utilize lithium cobalt oxide (LiCoO2) as cathode material with a platinum (Pt) current collector. Silicon nitride (Si3N4) is used to act as a barrier against Li diffusion into the substrate. For a good adherence between Si3N4 and Pt, commonly titanium (Ti) is used as intermediate layer. However, to achieve crystalline LiCoO2 the multilayer system has to be annealed at high temperature. This post-treatment initiates Ti diffusion into the Pt-collector and an oxidation to TiOx, leading to volume expansion and adhesion failures. To solve this adhesion problem, we introduce titanium oxide (TiOx) as an adhesion layer, avoiding the diffusion during the annealing process. LiCoO2, Pt and Si3N4 layers were deposited by magnetron sputtering and the TiOx layer by thermal oxidation of Ti layers deposited by e-beam technique. Asdeposited and annealed multilayer systems using various TiOx layer thicknesses were studied by scanning electron microscopy (SEM) and time-of-flight secondary ion mass spectrometry (ToF-SIMS) and x-ray photoelectron spectroscopy (XPS). The results revealed that an annealing process at temperature of 700C leads to different interactions of Ti atoms between the layers, for various TiOx layer thicknesses (25–45 nm).

Effect of argon ion energy on the performance of silicon nitridemultilayer permeation barriers grown by hot-wire CVD on polymers

One of the authors (S.M.) acknowledges Direction des Relations Extérieures of Ecole Polytechnique for financial support.

Optical properties of zirconium oxynitride films: the effect of composition, electronic and crystalline structures

tThis work is devoted to the investigation of zirconium oxynitride (ZrOxNy) films with varied opticalresponses prompted by the variations in their compositional and structural properties. The films wereprepared by dc reactive magnetron sputtering of Zr, using Ar and a reactive gas mixture of N2+ O2(17:3).The colour of the films changed from metallic-like, very bright yellow-pale and golden yellow, for low gasflows to red-brownish for intermediate gas flows. Associated to this colour change there was a significantdecrease of brightness. With further increase of the reactive gas flow, the colour of the samples changedfrom red-brownish to dark blue or even to interference colourations. The variations in composition dis-closed the existence of four different zones, which were found to be closely related with the variationsin the crystalline structure. XRD analysis revealed the change from a B1 NaCl face-centred cubic zirco-nium nitride-type phase for films prepared with low reactive gas flows, towards a poorly crystallizedover-stoichiometric nitride phase, which may be similar to that of Zr3N4with some probable oxygeninclusions within nitrogen positions, for films prepared with intermediate reactive gas flows. For highreactive gas flows, the films developed an oxynitride-type phase, similar to that of -Zr2ON2with someoxygen atoms occupying some of the nitrogen positions, evolving to a ZrO2monoclinic type structurewithin the zone where films were prepared with relatively high reactive gas flows. The analysis carriedout by reflected electron energy loss spectroscopy (REELS) revealed a continuous depopulation of thed-band and an opening of an energy gap between the valence band (2p) and the Fermi level close to 5 eV.The ZrN-based coatings (zone I and II) presented intrinsic colourations, with a decrease in brightness anda colour change from bright yellow to golden yellow, red brownish and dark blue. Associated to thesechanges, there was also a shift of the reflectivity minimum to lower energies, with the increase of thenon-metallic content. The samples lying in the two last zones (zone III, oxynitride and zone IV, oxide films)revealed a typical semi-transparent-optical behaviour showing interference-like colourations only dueto the complete depopulation of the d band at the Fermi level. The samples lying in these zones presentedalso an increase of the optical bandgap from 2 to 3.6 eV.

Controlo de qualidade e inspeção visual por imagem: definição de uma aplicação para registo de alterações e avaliação de desempenho

Dissertação de mestrado em Engenharia e Gestão da Qualidade

Modelação de governo electrónico para países emergentes: O caso de São Tomé e Príncipe

Tese de Doutoramento em Tecnologias e Sistemas de Informação

Intraaortic balloon pump support during coronary angioplasty. Initial experience

OBJECTIVE: To evaluate the use of the intraaortic balloon (IAoB) in association with coronary angioplasty in high-risk patients. METHODS: Fourteen high-risk patients unresponsive to clinical therapy and with formal contraindication to surgical revascularization were treated by coronary angioplasty, most of which was followed by stenting. All procedures were performed with circulatory support with the IAoB. This study reports the early results and the late findings after 12 months of follow-up. Six patients had multivessel coronary disease; of these, four had left main equivalent lesions and two had unprotected left main coronary artery disease, one of whom had severe "end-vessel" stenosis and the other was a patient with Chagas' disease with single-vessel lesion. Eleven patients had a left ventricular ejection fraction <30%. RESULTS: In 100% of the patients, the procedures were initially successful. Two patients had severe bleeding during the withdrawal of the left femoral sheath. At the end of twelve months, 4 patients were asymptomatic and the others were clinically controlled. There were two late deaths in the 7th and 11th months. CONCLUSION: The combined use of the intraaortic balloon pump and percutaneous coronary angioplasty in high-risk patients with acute ischemic syndromes provides the necessary hemodynamic stability to successfully perform the procedures.

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.

Step towards to improve the voluntary interruption of pregnancy by means of business intelligence

With the implementation of Information and Communication Technologies in the health sector, it became possible the existence of an electronic record of information for patients, enabling the storage and the availability of their information in databases. However, without the implementation of a Business Intelligence (BI) system, this information has no value. Thus, the major motivation of this paper is to create a decision support system that allows the transformation of information into knowledge, giving usability to the stored data. The particular case addressed in this chapter is the Centro Materno Infantil do Norte, in particular the Voluntary Interruption of Pregnancy unit. With the creation of a BI system for this module, it is possible to design an interoperable, pervasive and real-time platform to support the decision-making process of health professionals, based on cases that occurred. Furthermore, this platform enables the automation of the process for obtaining key performance indicators that are presented annually by this health institution. In this chapter, the BI system implemented in the VIP unity in CMIN, some of the KPIs evaluated as well as the benefits of this implementation are presented.

Real-Time decision support using data mining to predict blood pressure critical events in intensive medicine patients

Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%.