CORDIS provides links to public deliverables and publications of HORIZON projects.
Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .
Exploitable results
ELECTRO-NET aims to improve communication and exchange of high voltage electrical network data between both electric power utilities and electric power system suppliers. ELECTRO-NET demonstrator/pilot implementation allows exchanges between application software packages for system planning and operational planning.
ELECTRO-NET establishes a neutral data representation for generation and transmission in electric power systems, to be used for planning and operations analysis. It facilitates data exchange between and within organizations in the electricity supply industry by creating an open system market for power systems software to ease the implementation of specialized applications into existing information systems. The impact and benefits of the results differ for utilities and software suppliers. The utilities will incorporate the new standard in their applications. The greater ease of network data exchange between systems and between associated organizations will: Lead to improved efficiency with substantial savings in time and costs. Improve collaboration between the European utilities and encourage joint ventures. Facilitate benchmark comparisons between different systems.
The adoption of the agreed ELECTRO-NET data model and standard will create an open market in electrical network analysis software which will facilitate the integration of specialized planning and analysis software with their own information systems. These advantages will become available for all European utilities, those involved in the project constitute only the front-line.
Project URL : http://www.eus.ee.ethz.ch/electronet/public
Functional cardiac imaging methods are important diagnostic tools in the evaluation of heart disease. Conventional methods of imaging are limited in their accuracy and may involve the use of ionizing radiation. Magnetic Resonance Imaging (MRI) is a non-invasive high quality imaging technique. MR images of cardiac function can now be routinely acquired, however it is current practice to perform qualitative interpretation only. Quantitative analysis has been limited by the lack of affordable, robust, systems for automatic processing and analysis of the images in a clinically acceptable time frame, that is, while the patient remains in the scanner. Quantitative analysis of images will increase diagnostic confidence resulting in improved patient care and ultimately lower costs.
Such productivity improvements can be achieved, at a reasonable cost, through the application of High Performance Computing and Networking (HPCN) techniques to the processing of scanner data using existing, but computationally demanding algorithms. These algorithms allow quantitative diagnostic analysis; for example the volume of blood pumped by the heart can be quantitatively estimated.
CAMRA (Cardiac Magnetic Resonance Analysis) demonstrates high performance, low cost analysis of cardiac MR images on multi-processor PC-compatible systems running under Windows NT. CAMRA increases the performance of the ANALYZE biomedical image analysis package by parallelizing existing serial algorithms. This will allow a shift in clinical diagnosis from qualitative to quantitative interpretation of images with resultant improvements in patient care.
Project URL : http:://www.epcc.ed.ac.uk/TTN/CAMRA/index.html
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