Um modelo para a gestão do conhecimento organizacional no contexto dos serviços partilhados com recurso à utilização do e-Learning

Tese de Doutoramento em Tecnologias e Sistemas de Informação

Narrative innovations predict symptom improvement: Studying innovative moments in narrative therapy of depression

Objective:Innovative moments (IMs) are moments in the therapeutic dialog that constitute exceptions toward the client's problems. These narrative markers of meaning transformation are associated with change in different models of therapy and diverse diagnoses. Our goal is to test if IMs precede symptoms change, or, on the contrary, are a mere consequence of symptomatic 15 change. Method: For this purpose, IMs and symptomatology (Outcome Questionnaire-10.2) were assessed at every session in a sample of 10 cases of narrative therapy for depression. Hierarchical linear modeling was conducted to explore whether (i) IMs in a given session predict patients' symptoms in the following session and/or (ii) symptoms in a given session predict IMs in the next session. Results: Results suggested that IMs are better predictors of symptoms than the reverse. Conclusions: These results are discussed considering the contribution of meanings and narrative processes' changes to symptomatic improvement.

Using balanced scorecards to evaluate the data warehouse system utility

Dissertação de mestrado em Systems Engineering

Sistema de apoio à decisão clínica: quality of life system

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Development of an intelligent earthwork optimization system

Tese de Doutoramento em Engenharia Civil.

Microfluidic based on aqueous two-phase system for plasmidic DNA purification

Dissertação de mestrado em Bioquímica Aplicada (área de especialização em Biotecnologia)

Numerical methods in multibody system dynamics

"Series: Solid mechanics and its applications, vol. 226"

On the frictional contacts in multibody system dynamics

"Series title: Computational methods in applied sciences, ISSN1871-3033, vol. 42"

A Real-Time intelligent system for tracking patient condition

Hospitals have multiple data sources, such as embedded systems, monitors and sensors. The number of data available is increasing and the information are used not only to care the patient but also to assist the decision processes. The introduction of intelligent environments in health care institutions has been adopted due their ability to provide useful information for health professionals, either in helping to identify prognosis or also to understand patient condition. Behind of this concept arises this Intelligent System to track patient condition (e.g. critic events) in health care. This system has the great advantage of being adaptable to the environment and user needs. The system is focused in identifying critic events from data streaming (e.g. vital signs and ventilation) which is particularly valuable for understanding the patient’s condition. This work aims to demonstrate the process of creating an intelligent system capable of operating in a real environment using streaming data provided by ventilators and vital signs monitors. Its development is important to the physician because becomes possible crossing multiple variables in real-time by analyzing if a value is critic or not and if their variation has or not clinical importance.