Flow updating: fault-tolerant aggregation for dynamic networks

Documento submetido para revisão pelos pares. A publicar em Journal of Parallel and Distributed Computing. ISSN 0743-7315

Epidemic store for massive scale systems

The MAP-i doctoral program of the Universities of Minho, Aveiro and Porto

Monitoring energy consumption in android applications

Dissertação de Mestrado em Engenharia Informática

Spectrum-based energy leak localization

Dissertação de Mestrado em Engenharia Informática

Mineralizações associadas a shear zone networking na vertente oriental da Serra de Arga (Minho, Portugal)

Dissertação de mestrado em Ordenamento e Valorização de Recursos Geológicos

Aplicação móvel android de apoio a gestão de empréstimos e reservas das bibliotecas da Universidade do Minho

Dissertação de mestrado integrado em Engenharia de Telecomunicações e Informática

Avaliação quantitativa da geodiversidade: desenvolvimento de instrumentos metodológicos com aplicação ao ordenamento do território

Tese de Doutoramento em Ciências (Especialidade de Geologia)

A study of risk-aware program transformation

In the trend towards tolerating hardware unreliability, accuracy is exchanged for cost savings. Running on less reliable machines, functionally correct code becomes risky and one needs to know how risk propagates so as to mitigate it. Risk estimation, however, seems to live outside the average programmer’s technical competence and core practice. In this paper we propose that program design by source-to-source transformation be risk-aware in the sense of making probabilistic faults visible and supporting equational reasoning on the probabilistic behaviour of programs caused by faults. This reasoning is carried out in a linear algebra extension to the standard, `a la Bird-Moor algebra of programming. This paper studies, in particular, the propagation of faults across standard program transformation techniques known as tupling and fusion, enabling the fault of the whole to be expressed in terms of the faults of its parts.

Pervasive adaptive data acquisition gateway for critical healthcare

The data acquisition process in real-time is fundamental to provide appropriate services and improve health professionals decision. In this paper a pervasive adaptive data acquisition architecture of medical devices (e.g. vital signs, ventilators and sensors) is presented. The architecture was deployed in a real context in an Intensive Care Unit. It is providing clinical data in real-time to the INTCare system. The gateway is composed by several agents able to collect a set of patients’ variables (vital signs, ventilation) across the network. The paper shows as example the ventilation acquisition process. The clients are installed in a machine near the patient bed. Then they are connected to the ventilators and the data monitored is sent to a multithreading server which using Health Level Seven protocols records the data in the database. The agents associated to gateway are able to collect, analyse, interpret and store the data in the repository. This gateway is composed by a fault tolerant system that ensures a data store in the database even if the agents are disconnected. The gateway is pervasive, universal, and interoperable and it is able to adapt to any service using streaming data.