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Fernando Morgado-Dias

Researcher at Madeira Interactive Technologies Institute

Publications -  108
Citations -  1451

Fernando Morgado-Dias is an academic researcher from Madeira Interactive Technologies Institute. The author has contributed to research in topics: Artificial neural network & Computer science. The author has an hindex of 15, co-authored 91 publications receiving 819 citations. Previous affiliations of Fernando Morgado-Dias include University of Madeira.

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Economic feasibility analysis of small scale PV systems in different countries

TL;DR: In this paper, the authors analyzed a representative set of countries, including Australia, Brazil, China, Germany, India, Iran, Italy, Japan, Portugal, South Africa, Spain, United Kingdom, and the United States of America, to identify the ones with the best investment opportunities considering the new regulations.
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A Review of Obstructive Sleep Apnea Detection Approaches

TL;DR: The objective of this review is to analyze already existing algorithms that have not been implemented on hardware but have had their performance verified by at least one experiment that aims to detect obstructive sleep apnea to predict trends.
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Particle Swarm Optimisation: A Historical Review Up to the Current Developments

TL;DR: A systematic literature review about variants and improvements of the Particle Swarm Optimisation algorithm and its extensions to other classes of optimisation problems, taking into consideration the most important ones is made.
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A systematic review of detecting sleep apnea using deep learning

TL;DR: The goal of this work is to analyze the published research in the last decade, providing an answer to the research questions such as how to implement the different deep networks, what kind of pre-processing or feature extraction is needed, and the advantages and disadvantages of different kinds of networks.
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Devices for home detection of obstructive sleep apnea: A review

TL;DR: The objective of this research is to review publications that show the performance of different devices for ambulatory diagnosis of sleep apnea, and to determine the sensors that provided the best results.