2015
Autores
Ferreira, LL; Pinho, LM; Albano, M; Teixeira, C;
Publicação
SIGBED Rev.
Abstract
2015
Autores
Pinho, LM;
Publicação
Ada User Journal
Abstract
2015
Autores
Mesquita Brandao, RFM; Beleza Carvalho, JAB; Maciel Barbosa, FPM;
Publicação
2015 IEEE EINDHOVEN POWERTECH
Abstract
New generations of turbines have lower repair and maintenance costs than the previous generation. This is justified by the development of new components and materials. As the power of newer turbines is usually substantially larger, it is possible to get an economy of scale and lower maintenance costs per kW of rated power. This is simply because it is not needed to service a large turbine more often than a small one. New methods of earlier detection of faults are needed. The use of all information from SCADA (Supervisory Control and Data Acquisition) system can be useful, but it is necessary to develop tools to deal with bigger amount of information. Neural networks can help and turn possible new maintenance and operation schemes.
2015
Autores
de Abreu Silva, B; Cuminato, LA; Delbem, ACB; Diniz, PC; Bonato, V;
Publicação
IET Computers and Digital Techniques
Abstract
This study describes and evaluates an automated technique that exploits the potential of heterogeneous multi-core processor (HMP) systems when customised with respect to the number of cores and L1 cache memory sizes using a field programmable gate array fitted with LEON3 cores at its base. The authors evaluated the real energy consumption of the HMP system tuned for a set of 50 application codes using a data-mining tool for finding code similarities and selecting HMP configurations. The selected HMP system configuration requires a small cache configuration and consumes less energy when compared to a homogeneous system with the same number of cores and only with a very modest increase in execution time. © The Institution of Engineering and Technology 2015.
2015
Autores
Oliveira, CC; da Silva, JM;
Publicação
PROCEEDINGS OF THE 2015 IEEE 20TH INTERNATIONAL MIXED-SIGNAL TESTING WORKSHOP (IMSTW)
Abstract
A new methodology for fault detection on wearable medical devices is proposed. The main strategy relies on correctly classifying the captured physiological signals, in order to distinguish whether the actual cause is a wearer health abnormality or a system functional flaw. Data fusion techniques, namely fuzzy logic, are employed to process the captured data, like the electrocardiogram and blood pressure, to increase the trust levels with which diagnostics are made. Concerning the wearer condition, additional information is provided after classifying the set of signals into normal or abnormal (e.g. arrhythmia, chest angina, and stroke). As for the monitoring system, once an abnormal situation is detected in its operation or in the sensors, a set of tests is run to check if actually the wearer shows a degradation of his health condition or if the system is reporting erroneous values.
2015
Autores
Farkat Diogenes, JRF; Bordalo da Costa, DMB; Pecas Lopes, JAP; Barbosa Pereira Queiroz, FCBP; Queiroz, JV;
Publicação
PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON ENERGY & ENVIRONMENT: BRINGING TOGETHER ENGINEERING AND ECONOMICS
Abstract
This article identifies and classifies the key obstacles to wind energy development, in order to better understand these barriers and provide guidelines to help public managers to develop and share new energy policies. The methodology used was a case study with documentary research, carried out through an analysis of the Global Wind Report - Annual Market Update, 2009 to 2013, published by Global Wind Energy Council - GWEC. The results showed a significant occurrence of technological and operational obstacles, especially concerning electricity grids. The results lead to the conclusion that the biggest issue for wind energy development is concentrated in technological and operational obstacles, especially concerning the management of transmission networks. In addition, the results indicate the possibility of countries, with common obstacles, to improve their energy policies in partnership, or share their successful expertises.
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