For the past decade the Cuban Neuroscience Center has organized on behalf of the Ministry of Public Health of the Republic, a nationwide Program for the introduction of quantitative EEG (qEEG). This Program has involved a) development of standardized equipment for "paperless" EEG, qEEG and brain topography; b) establishment of a network of 21 laboratories of clinical neurophysiology; c) creation of the specialty of clinical neurophysiology which trains physicians from all provinces in both traditional and quantitative electrophysiological methods; d) introduction of standardized protocols for the collection of clinical and electrophysiological information; e) organization of a national normative and neuropsychiatric database; f) establishment of normative regression equations. Among the special issues discussed are: 1) relationship between traditional and quantitative methods; 2) evaluation of the effectiveness of the technology introduced; 3) use of qEEG in the early detection of brain dysfunction.

In this work, a new approach for Sun tracking systems is presented. Due to the current system limitations regarding costs and operational problems, a new approach based on low cost, computer vision open hardware and deep learning has been developed. The preliminary tests carried out successfully in Plataforma solar de Almería (PSA), reveal the great potential and show the new approach as a good alternative to traditional systems. The proposed approach can provide key variables for the Sun tracking system control like cloud movements prediction, block and shadow detection, atmospheric attenuation or measures of concentrated solar radiation, which can improve the control strategies of the system and therefore the system performance.

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