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The European Centre for Soft Computing was a research and development centre promoted by the Foundation for the Advancement of Soft Computing located in Mieres, Asturias (Spain). Our main objectives were to carry out basic and applied research in the field of Soft Computing as well as to transfer technology to industrial applications of intelligent systems to solve real-world problems. The activities and programs of the ECSC were guided by an international Scientific Committee. Besides, the Centre became a meeting point for worldwide experts and young researchers where they developed advanced research and training activities. The center was active from February 2006 to January 2016. In 2007 the ECSC began offering specialized courses focused on promoting the dissemination of new trends, developments and applications of the different areas of Soft Computing among international students from different backgrounds. Furthermore, with the idea of serving as a way to transfer knowledge to society, there were roundtables and conferences open to the public aimed at showing the application of these techniques to solve real-world problems. The teaching staff of these courses is made up of researchers of the Centre, Scientific Committee members and other international experts. Soft Computing is a discipline that deals with the design of hybrid intelligent systems which, in contrast to classical hard computing techniques, are tolerant to imprecision, uncertainty, partial truth, and approximation. Thus tractable, robust, and low cost solutions to real-world problems are achieved. The main constituents of Soft Computing are fuzzy logic, neural networks, evolutionary computation, and probabilistic reasoning. Since the term Soft Computing was coined at the beginning of the 90s, this area has experienced a rapid development of its fundamentals as well as its applications. The summer course reviewed the fundamentals of this discipline, described many real-world applications, and, in particular, treated new trends and future directions of the field. Participants gained insight into the potential of soft computing techniques and the state of the art in the area. To achieve this, the lecturers were selected from the leaders of the different branches of Soft Computing. The summer course was supported by the "Future Directions in Fuzzy Sets and Systems" Task Force, Fuzzy Systems Technical Committee, IEEE Computational Intelligence Society, several members of which participate in the course. The second edition of the ECSC Summer Course titled "Intelligent Data Analysis", had a great success with students from different parts of the world (Finland, Egypt, Italy, Portugal, etc.) and many from the Spanish Universities. Besides, given the relevancy for the industrial and bussiness areas that have the Intelligent Data Analysis, we counted with members of technology centers and companies, as CARTIF Foundation, UNIOVA and LEIA Foundation. The development of new reasoning and decision making tools that can deal with uncertainty and imprecision leads to considerable scientific and technical progress. This training school brought different approaches, research lines and applications together and permitted the trainees to explore synergies between different computational and mathematical methods, to structure promising new ideas and research projects, to develop new research lines, to generate scientific and technical knowledge and to increase the multidisciplinary of European researchers. The training school plan balanced topics from basic research lines and real-world applications. The main objective of the COST action IC0702 "Combining Soft Computing Techniques and Statistical Methods to Improve Data Analysis Solutions" was to strengthen the dialogue between the statistics and soft computing research communities in order to cross-pollinate both fields and generate mutual improvement activities. Soft computing, as an engineering science, and statistics, as a branch of mathematics, emphasize different aspects of data analysis. Soft computing focuses on obtaining working solutions quickly, accepting approximations and unconventional approaches. Its strength lies in its flexibility to create models that suit the needs arising in applications (context of discovery, model generation). In addition, it emphasizes the need for intuitive and interpretable models, which are tolerant to imprecision and uncertainty. Statistics is more rigorous and focuses on establishing objective conclusions based on experimental data by analysing the possible situations and their (relative) likelihood (context of justification, model validation). It emphasizes the need for mathematical methods and tools to assess solutions and guarantee performance. Bringing the two fields closer together will enhance the robustness and generalisability of data analysis methods, while preserving the flexibility to solve real-world problems efficiently and intuitively. The lectures and tutorials in this summer course pointed out the potential that lies in joint solutions and the transfer of ideas from one field to the other. They were intended to stimulate young researchers to explore methods from that field - soft computing or statistics - they were not so familiar with yet in order to broaden their view and trigger new ideas for fruitful interdisciplinary research. The ECSC coordinated the 7FP Marie Curie Initial Training Network "Medical Imaging using Bio-inspired and Soft Computing" (www.mibisoc-itn.eu) . This network aimed to create a multidisciplinary training programme where 16 enrolled early-stage researchers (ESRs) were exposed to a wide variety of Bio-Inspired (BC) and Soft Computing (SC) techniques, and to the challenge of applying them in the development of flexible application-oriented solutions to current Medical Imaging (MI) problems. The MIBISOC partnership consisted of world-wide recognized researchers from 8 scientific institutions (ECSC, Ghent University, Université Libre de Bruxelles, University of Nottingham, Università degli Studi di Parma, University of Granada, Henesis, and Universitätsklinikum Freiburg), and 4 high quality technical partners (General Electrics Healthcare, CNRS, Hospital Central de Asturias, and Treelogic). Within this training programme a first technical course was organized in July 2011. It was focused on SC and BC-based intelligent system design to solve real-world MI problems. A detailed summary of real-world applications was taught by outstanding experts, including topics such as image reconstruction in MI modalities, filtering and processing of medical images, segmentation and feature extraction in MI, range and multimodal image registration. There are 100 Researchers who are taking responsibility of academic courses.
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