Browsing by Author "Silva, Bruno"
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- Auditoria Interna: contributos para a melhoria contínua no IPSPublication . Cordeiro, João Pedro Pina; Gonçalves, Helena; Rolo, Ana; Rosado, Cláudia; Silva, Bruno
- As expetativas dos alunos no ensino da guitarra clássica em regime de ensino articuladoPublication . Silva, Bruno; Carvalho, HelenaDe forma a reforçar as competências cientificas e pedagógicas necessárias para a obtenção da habilitação profissional para a docência, conferidas pelo ciclo de estudos do Mestrado em Ensino da Música do ISEIT – Almada, é proposto e estabelecido o objetivo de realizar este projeto de investigação. Inserido no âmbito da Unidade Curricular (UC) de Prática de Ensino Supervisionada (PES), este trabalho organiza-se em duas partes. A primeira compreende o relatório de estágio realizado na Academia de Amadores de Música (doravante, AAM), onde é feita a caracterização da escola, assim como a descrição das atividades desenvolvidas, tendo em conta as dimensões da ação docente (CCAP, 2010). A segunda parte é integralmente dedicada ao projeto de investigação desenvolvido. O projeto de investigação terá como escopo essencial o desenvolvimento de uma pesquisa que procure identificar a relação entre aquilo que são as expetativas dos alunos de guitarra clássica (portanto, o maior ou menor grau de verificação e efetivação das mesmas) e o consequente nível de motivação e de resultados escolares demonstrados, pelos mesmos, ao longo da sua formação musical . Ou seja, pretende-se saber se há – e em que medida - uma correspondência e direta entre aquilo que são as expetativas dos alunos no momento em que ingressam no conservatório e a realidade que vêm, posteriormente, a encontrar. Caso se identifique uma desconformidade entre estes dois distintos planos (expetativas vs. realidade), procurar-se-á perceber se esta é uma causa real e relevante de desmotivação nos alunos, eventualmente capaz de provocar, em último caso, a sua desistência e abandono do curso. Com base no resultados obtidos e se tal tendência efetivamente se comprovar, procurar-se-á no final formular uma proposta de solução - caso se demonstre necessária - que procure indicar um caminho para a revisão e reformulação do atual modelo de ensino do articulado, nos aspetos que possam específica e diretamente influir nessa situação.
- Interrupted aortic arch in a 58-year-old patientPublication . Rodrigues, Ricardo C.; Correia, André; Silva, Bruno; Gomes, Susana; Pereira, DécioA 58-year-old male patient was evaluated in the cardiology outpatient setting after an episode of hypertension and atrial fibrillation. He was also an ex-moker.Echocardiogram revealed slight left ventricular dilation with diastolic dysfunction and a systolic function in the lower normality level, as well as a rheumatic valvar disease with moderate mitral stenosis and slight aortic valve involvement, atrial enlargement and pulmonary hypertension. After an episode of acute pulmonar oedema the patient was referred for coronary catheterization. A right femoral approach was attempted and progression of the guidewire was not possible due to na interrupted aortic arch (IAA) (figure 1A), that was confirmed by right radial approach (figure 1B). The coronary arteries had no ignificant stenosis but the circumflex artery had an anomalous origin. A CT-scan confirmed an interrupted aortic arch (IAA) in the descending aorta, 27 mm below the left subclavian artery, and a short, 15-mm occluded segment Interrupted aortic arch in a 58-year-old patientcharacterized, originating from the right coronary Valsalva sinus and separated from the right coronary artery (figure 1D, arrow; figure 1F). The patient was submitted to cardiac correction surgery with the implantation of an intrapericardial Dacron conduit connecting both aortic ends. The periprocedural period was uneventful and at 1-year follow-up the patient was clinically stable with no cardiac complications. This IAA was an incidental finding, and it may have arisen from progression of an undiagnosed coarctation of the aorta while the absence of the ductus arteriosus was probably due to a progressive occlusion.
- KAsH Score predicts long term mortality after acute myocardialPublication . Monteiro, Joel Ponte; Sousa, João Adriano; Sousa Mendonça, Flávio; Neto, Micaela; Rodrigues, Ricardo; Gomes Serrão, Marco; Silva, Bruno; Mendonça, Maria Isabel; Faria, Ana Paula; Henriques, Eva; Drumond Freitas, AntónioIntroduction: Complex risk scores have limited applicability in the assessment of patients with myocardial infarction (MI). In this work, the authors aimed to develop a simple to use clinical score to stratify the in-hospital mortality risk of patients with MI at first medical contact. Methods: In this single-center prospective registry assessing 1504 consecutively admitted patients with MI, the strongest predictors of in-hospital mortality were selected through multivariate logistic regression. The KAsH score was developed according to the following formula: KAsH=(Killip class×Age×Heart rate)/systolic blood pressure. Its predictive power was compared to previously validated scores using the DeLong test. The score was categorized and further compared to the Killip classification. Results: The KAsH score displayed excellent predictive power for in-hospital mortality, superior to other well-validated risk scores (AUC: KAsH 0.861 vs. GRACE 0.773, p<0.001) and robust in subgroup analysis. KAsH maintained its predictive capacity after adjustment for multiple confounding factors such as diabetes, heart failure, mechanical complications and bleeding (OR 1.004, 95% CI 1.001-1.008, p=0.012) and reclassified 81.5% of patients into a better risk category compared to the Killip classification. KAsH’s categorization displayed excellent mortality discrimination (KAsH 1: 1.0%, KAsH 2: 8.1%, KAsH 3: 20.4%, KAsH 4: 55.2%) and better mortality prediction than the Killip classification (AUC: KAsH 0.839 vs. Killip 0.775, p<0.0001). Conclusion: KAsH, an easy to use score calculated at first medical contact with patients with MI, displays better predictive power for in-hospital mortality than existing scores. © 2019 Sociedade Portuguesa de Cardiologia. Published by Elsevier Espa˜na, S.L.U. This is na open access article under the CC BY-NC-ND license
- Simulating Price Interactions by Mining Multivariate Financial Time SeriesPublication . Silva, Bruno; Cavique, Luis; Marques, NunoThis position paper proposes a framework based on a feature clustering method using Emergent Self-Organizing Maps over streaming data (Ubi-SOM) and Ramex-Forum – a sequence pattern mining model for financial time series modeling based on observed instantaneous and long term relations over market data. The proposed framework aims at producing realistic monte-carlo based simulations of an entire portfolio behavior over distinct market scenarios, obtained from models generated by these two approaches.
- Ubiquitous Self-Organizing MapsPublication . Silva, Bruno; Marques, NunoKnowledge discovery in ubiquitous environments are usually conditioned by the data stream model, e.g., data is potentially infinite, arrives continuously and is subject to concept drift. These factors present additional challenges to standard data mining algorithms. Artificial Neural Networks (ANN) models are still poorly explored in these settings. State-of-the-art methods to deal with data streams are single-pass modifications of standard algorithms, e.g., Kmeans for clustering, and involve some relaxation of the quality of the results, i.e., since the data cannot be revisited to refine the models, the goal is to achieve good approximations [Gama, 2010]. In [Guha et al., 2003] an improved single pass k-means algorithm is proposed. However, k-means suffers from the problem that the initial k clusters have to be set either randomly or through other methods. This has a strong impact on the quality of the clustering process. CluStream [Aggarwal et al., 2003] is a framework that targets high-dimensional data streams in a two-phased approach, where an online phase produces micro-clusterings of the incoming data, while producing on-demand offline models of data also with k-means. In this position paper we address the use of Self-Organizing Maps (SOM) [Kohonen, 1982] and argue its strengths over current methods and directions to be explored on its adaptation to ubiquitous environments, which involve dynamic estimation of the learning parameters based on measuring concept drift on, usually, non-stationary underlying distributions. In a previous work [Silva and Marques, 2012] we presented a neural network-based framework for data stream mining that explored the two-phased methodology, where the SOM produced offline models. In this paper we advocate the development of a standalone Ubiquitous SOM (UbiSOM), that is capable of producing models in an online fashion, to be integrated in the framework. This allows derived knowledge to be accessible at any time.