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  • CA3 - Computational Intelligence Research Group
    the safe landing of a planetary mission IPSIS Intelligent Planetary SIte Selection is a multi criteria dynamic decision level data fusion algorithm which takes into account historical information for the selection of landing sites which meet mission safety and reachability requirements in the scope of a planetary mission Developed by UNINOVA 3MSF Tiered multi sensors fusion methodology is an approach that operates at the information level and performs multi sensor information fusion using a tiered sensor grouping approach that is based on the availability of different sensors at different altitudes Terrain features are integrated using principles of reasoning under uncertainty It combines 3 methodologies to infer landing safety Fuzzy Reasoning Probabilistic Reasoning and Evidential Reasoning Developed by JPL USA Research areas Fuzzy logic Evidential reasoning Image processing Multi criteria decision making Partners Relevant Publications T C Pais R A Ribeiro L F Simões Uncertainty in dynamically changing input data In Computational Intelligence in Complex Decision Systems DaRuan Ed Atlantis Computational Intelligent Systems Vol 2 Chapter 2 World Scientific 2010 ISBN 9789078677277 Simoes L Bourdarias C and Ribeiro R A Real Time Planetary Landing Site Selection A Non Exhaustive Approach Acta Futura 5 2012 pp 39 52 http dx doi org

    Original URL path: http://www.ca3-uninova.org/project_fusion (2016-02-17)
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  • CA3 - Computational Intelligence Research Group
    mathematical model which combines concepts from multi criteria decision making concepts with evolutionary optimization algorithms thus providing a novel robust and efficient approach to the problematic of safe landing with hazard avoidance IPSIS has been tried and tested within the space domain in Astrium ST simulator one direct contract and one project financed by ESA and also by Deimos Eng on the scope of the Lunar Lander phase B LuLaB project Spin Works the customer already develops UAV s with embedded guidance navigation and control systems as well as for ESA GNC and Hazard Detection and Avoidance HDA algorithms both for planetary missions as well as other commercial applications Increasing safety security and efficiency is one of the main drivers for the use of UAVs by civil users Hence the use of IPSIS technology could definitely bring added value to current UAV s by ensuring autonomous and safe landing while reducing operational costs Research areas Fuzzy logic Image processing Multi criteria decision making Partners Relevant Publications T C Pais R A Ribeiro L F Simões Uncertainty in dynamically changing input data In Computational Intelligence in Complex Decision Systems DaRuan Ed Atlantis Computational Intelligent Systems Vol 2 Chapter 2 World Scientific

    Original URL path: http://www.ca3-uninova.org/project_iluv (2016-02-17)
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  • CA3 - Computational Intelligence Research Group
    of Universidade Nova Lisboa New University of Lisbon UNINOVA was formed in 1986 by FCT UNL Faculty of Sciences and Technology of the New University of Lisbon AIP Portuguese Industrial Association IEFP Employment and Vocational Training Institute a financial holding named IPE and other companies and organisations The CA3 is one of the research groups within the Centre for Technology and Systems CTS at UNINOVA The following figure depicts the

    Original URL path: http://www.ca3-uninova.org/position_within_uninova (2016-02-17)
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  • CA3 - Computational Intelligence Research Group
    algorithms for solving multicriteria decision making and dynamic decision making problems and developing applications with special emphasis in the Space domain CA3 Relevant papers in this topic are for more papers and downloads see publication section Campanella G Ribeiro R A 2012 A Framework for dynamic multiple criteria decision making Decision Support Systems December 2012 Vol 52 pp 52 60 T C Pais R A Ribeiro L F Simões Uncertainty in dynamically changing input data In Computational Intelligence in Complex Decision Systems DaRuan Ed Atlantis Computational Intelligent Systems Vol 2 Chapter 2 World Scientific 2010 Simões L Bourdarias C Ribeiro R 2012 Real Time Planetary Landing Site Selection A Non Exhaustive Approach Acta Futura Vol 5 pp 39 52 Campanella G Ribeiro R A Varela L R 2011 A Model for B2B Supplier Selection Vol Vol 107 pp 221 228 Series on Advances in Intelligent and Soft Computing Springer G Campanella A Pereira R A Ribeiro and L R Varela Collaborative Dynamic Decision Making a Case Study from B2B Supplier Selection In Decision Support Systems Collaborative Models and Approaches in Real Environments Hernández J E Zarate P Dargam F Deliba ic B Liu S and Ribeiro R Eds Lecture Notes

    Original URL path: http://www.ca3-uninova.org/intelligent_decision_making (2016-02-17)
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  • CA3 - Computational Intelligence Research Group
    non fuzzy are computerized systems that employ human knowledge on a given domain captured in software to solve problems from that specific domain When we extend the classical inference to the fuzzy logic domain we have the added value of being able to represent imprecision and to perform approximate reasoning within uncertain environments thus creating flexible and adaptable systems This is the research scope in this topic CA3 Relevant papers in this topic are for more papers and downloads see publication section Coelho C Serra P Ribeiro R Pereira R M Dietz A Donati A 2008 Fuzzy alarm system for laser gyroscopes degradation Autosoft Intelligent Automation and Soft Computing International Journal Vol 14 No 3 pp 351 365 Pais T Devouassoux Y Reynaud S Ribeiro R 2008 Regions rating for selecting spacecraft landing sites 8th International Conference on Computational Intelligence in Decision and Control FLINS08 Madrid Spain September 2008 Ribeiro R Nunes I 2008 Interfaces Usability for Monitoring Systems Encyclopedia of Decision Making and Decision Support Technologies Vol 2 Information Science Reference Serra P Ribeiro R Marques Pereira R Steel R Niezette M Donati A 2008 Fuzzy Thermal Alarm System for Venus Express Encyclopedia of Decision Making and Decision Support

    Original URL path: http://www.ca3-uninova.org/monitoring (2016-02-17)
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  • CA3 - Computational Intelligence Research Group
    feature extraction and segmentation The Computational Intelligence Research group of UNINOVA CA3 main mission is to actively participate in applied research supported by projects by defining new concepts methods and algorithms capable of solving real world problems Computer aided diagnostic

    Original URL path: http://www.ca3-uninova.org/computer_aided_diagnostic (2016-02-17)
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  • CA3 - Computational Intelligence Research Group
    capable of solving real world problems Data fusion In general we can say that Data Fusion is any process of aggregating data from multiple sources into a single composite with higher information quality This is a recent topic of research within CA3 and at this stage we mainly concentrate on information fusion which is a type of data fusion The goal of information fusion is to combine heterogeneous information to obtain a single composite of potential comparable alternative solutions that can be classified and ranked The crux of information fusion which is a type of data fusion is three folded i data must be comparable and numerical using some normalization process ii imprecision in data must be taken in consideration iii an appropriate aggregation function to combine values into a single score must be selected Recently the application of computational intelligence concepts and techniques to perform data information fusion is emerging as a versatile tool and our research work follows this direction CA3 Relevant papers in this topic are for more papers and downloads see publication section R A Ribeiro A Falcão A Mora J M Fonseca FIF A Fuzzy information fusion algorithm based on multi criteria decision making Knowledge

    Original URL path: http://www.ca3-uninova.org/data_fusion (2016-02-17)
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  • CA3 - Computational Intelligence Research Group
    This research aims to develop techniques for analyzing and tracking features e g solar sunspots and to develop a framework for their identification characterization and tracking The framework is being developed in a modular way to increase its extendibility and reusability This research puts a special emphasis on solutions using evolutionary algorithms e g hybrid of swarm intelligence and snake model algorithms and fuzzy sets theory to allow optimizing the tracking of objects along time The snake model also known as active contour model is able to find the precise boundary of objects and it is widely used in segmentation shape modeling stereo matching and object tracking CA3 Relevant papers in this topic are for more papers and downloads see publication section Shahamatnia E Dorotovic I Ribeiro R Fonseca J 2012 Towards an automatic sunspot tracking Swarm intelligence and snake model hybrid Acta Futura Vol 5 pp 151 159 Shahamatnia E Ayanzadeh R et al 2011 Adaptive Imitation Scheme for Memetic Algorithms In Technological Innovation for Sustainability Springer pp 109 116 Shahamatnia E Dorotovic I et al 2011 Swarm intelligence and snake model for automatic sunspot tracking In AI in space Intelligence beyond planet Earth workshop 22nd International Joint Conference

    Original URL path: http://www.ca3-uninova.org/image_tracking (2016-02-17)
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