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Organizations, companies and start-ups need to cope with constant changes on the market which are difficult to predict. Therefore, the development of new systems to detect significant future changes is vital to make correct decisions in an organization and to discover new opportunities. A system based on business intelligence techniques is proposed to detect weak signals, that are related to future transcendental changes. While most known solutions are based on the use of structured data, the proposed system quantitatively detects these signals using heterogeneous and unstructured information from scientific, journalistic and social sources, applying text mining to analyze the documents and natural language processing to extract accurate results. The main contributions are that the system has been designed for any field, using different input datasets of documents, and with an automatic classification of categories for the detected keywords. In this research paper, results from the future of remote sensors are presented. Remote sensing services are providing new applications in observation and analysis of information remotely. This market is projected to witness a significant growth due to the increasing demand for services in commercial and defense industries. The system has obtained promising results, evaluated with two different methodologies, to help experts in the decision-making process and to discover new trends and opportunities.

Independent component analysis (ICA) is an emerging technique for multidimensional signal processing. In recent years, these techniques have been proposed for solving a large number of biomedical applications. This work reviews current knowledge on ICA in electrocardiographic (ECG) analysis. The benefits that ICA can bring to clinical practice are illustrated with four relevant clinical applications: foetal ECG extraction from maternal ECG recordings, analysis of atrial fibrillation, ECG denoising and removal of pacemaker artefacts.

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Mirroring the RV evaluation, we suggest including LVEF and LV dyssynchrony to improve the diagnosis of AC. Two independent mechanisms can be claimed in AC patients with LV involvement: 1) decreased myocardial deformation with global LV affectation and 2) delayed myocardial contraction at localized regions.