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  • CA3 - Computational Intelligence Research Group
    from the very early stage of requirements engineering Architecture models are related to requirements models in an ad hoc fashion and implementation tends to rely on pre processors which are inadequate substitute for proper programming language support for variability Nor is there any systematic traceability framework for relating variations across a SPL engineering lifecycle AMPLE will combine AOSD and MDD techniques to not only address variability at each stage in the SPL engineering lifecycle but also manage variations in associated artifacts such as requirements documents Furthermore it aims to bind the variation points in various development stages and dimensions into a coherent variability framework across the life cycle thus providing effective forward and backward traceability of variations and their impact This makes it possible to develop resilient yet adaptable SPL architectures for exploitation in industrial SPL engineering processes Research Areas AOSD Aspect Oriented Software Development MDD Model Driven development SPL Software Product Lines Partners Lancaster University UK Dramstadt University of Technoly Germany Universidade Nova de Lisboa Portugal ARMINES and Ecole des Mines de Nantes France University of Twente Netherlands HOLOS Lisboa Universidad de Malaga Spain SAP AG Germany Siemens AG Germany Publications 2009 Afonso Pimentel Multi criteria Analysis for Architectural

    Original URL path: http://www.ca3-uninova.org/project_ample (2016-02-17)
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  • CA3 - Computational Intelligence Research Group
    IP or Wiegand connection the device is able to communicate with the access control software in order to deny the exit of any employee that didn t store his her card on the machine as well as an assiduity input terminal The users are identified by biometric data fingerprint and a four digit Personal Identification Number PIN in order to obtain their card Research Areas Biometric Systems Systems integration and

    Original URL path: http://www.ca3-uninova.org/project_arinca (2016-02-17)
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  • CA3 - Computational Intelligence Research Group
    of the ESA Earth Explorer missions designed to measure changes in the Earth s land and marine ice cover CryoSat along with the GOCE mission is also the first of the ESA missions relying on Spacecraft Operators single shift per day for monitoring and control tasks during the routine phase CryoSat is a low earth orbit satellite visible for approximately 10 minutes every 100 minutes from the Kiruna ground station the only GS used for this mission and completes approximately 14 orbits per day Of these roughly 10 11 are visible from the Kiruna ground station Due to the non sun synchronous orbit and the fact that SPACON coverage is not 24 hours not all of the passes are manned in the control room Because of this some events may occur in the non manned periods that can go unnoticed and potentially lead to problems The main objective of this project consists in the development of a flexible reporting tool to provide the CryoSat Flight Control Team with status summary reports for the mission describing events performance and the S C status during non manned periods Further it will provide when available diagnosis evaluations of the inference result as well

    Original URL path: http://www.ca3-uninova.org/project_certain (2016-02-17)
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  • CA3 - Computational Intelligence Research Group
    such as the EEG A bioprofile is a personal fingerprint that fuses together a person s current and past medical history biopatterns and prognosis It combines data analysis and predications of possible susceptibility to diseases BIOPATTERN proposes to provide novel computational intelligent techniques for biopattern analysis and a pan European integrated intelligent analysis of an individual s bioprofile Information from distributed databases will be made available securely over the Internet to provide on line algorithms libraries and processing facilities for such analysis BIOPATTERN integrates the research efforts of 31 institutions across Europe to tackle and reduce fragmentation in the new field of biopattern and bioprofile analysis which will underpin eHealthcare in the post genome era It brings together leading researchers in medical informatics and bioinformatics from academia the healthcare sector and industry in a new way harnessing expertise and information to put Europe at the forefront of eHealth Research Areas Healthcare Information Systems Intelligent Medical Image Processing Decision Support Tools Partners UNINOVA Instituto De Desenvolvimento De Novas Tecnologias Portugal University of Plymouth UK Plymouth NHS trust Hospitals UK Neoventor Medicinsk Innovation AB Sweden Technological Educational Institute of Crete Greece Dipartimento Di Sistemi E Informatica Dell Universita Degli Studi Di Firenze Italy Synapsis S R L Italy Dipartimento Di Informatica Universita Degli Studi Di Pisa Italy Aston University UK Katholieke Universiteit Leuven Research Development Belgium Stichting Katholieke Universiteit Netherlands University of Athens Medical School Greece Telecommunication Systems Institute Greece Aristotelio Panepistimio Thessalonikis Greece Liverpool John Moores University UK Gap Infomedia Ltd UK University of Crete Medical Division Research Clinical Neurophysiological Laboratory Greece Sheffield Hallam University UK Istituto Nazionale Per Lo Studio Cura Dei Tumori Milano Italy Universita Degli Studi Di Milano Italy University of Liverpool UK University of Nottingham UK Ecological University of Bucharest Romania Hellenic Telecommunications Telematics Applications Company SA

    Original URL path: http://www.ca3-uninova.org/project_biopattern (2016-02-17)
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  • CA3 - Computational Intelligence Research Group
    sized yellow spots To evaluate therapy effectiveness ophthalmologists usually do a visual inspection what is fastidious and not reproducible Published data shows that the agreement between medical specialists in Drusen identification is only 67 The goal of this project is the development of a methodology for automatic unsupervised detection and modeling of Drusen spots using image processing techniques The methodology will be validated with a software prototype that will certainly improve the detection and quantification of Drusen It is also a main objective for the project to do a clinical validation of it to compare the results with the ones obtained by ophthalmologists Research Areas Intelligent Medical Image Processing Decision Support Tools Partners Uninova Cefitec Centro de Fisica e Investigação Tecnológica Faculdade de Ciências Médicas da Universidade Nova de Lisboa University of Aberdeen Publications A Mora P Vieira J Fonseca MODELLING OF DRUSEN DEPOSITS BASED ON RETINA IMAGE TRIDIMENSIONAL INFORMATION CIMED 2005 Second International Conference on Computacional Intelligence in Medicine and Healthcare Costa da Caparica Lisbon Portugal 29th June to 1st July 2005 Mora A Fonseca J Vieira P Drusen Deposits Modeling with Illumination Correction in Proc Biomed 2005 Innsbruck Austria 16 18 February 2005 A Mora P Vieira J

    Original URL path: http://www.ca3-uninova.org/project_drusas (2016-02-17)
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  • CA3 - Computational Intelligence Research Group
    develop an autonomous dynamic and adaptable multi criteria model to choose the best candidate landing site This model will be based in existing fuzzy multi criteria approaches Chen Hwang 1992 in terms of knowledge representation but it will be extended to answer the specific requirements of being autonomous dynamic and adaptable We will develop a prototype in Matlab including the modules described in Figure 1 The prototype will be used with case studies provided by ASTRIUM e g Moon Mars Mercury In order to test and validate our approach the tests and validation will consider the following aspects The understandability of the concept design decision algorithm Expected simulated performances computational load is critical for real time Preliminary tests small examples and trade offs a set of roughly 10 cases will be provided different terrains and trajectories The required output information ranked alternative sites and information about the values of the criteria for each site Proposed Architecture Research Areas Fuzzy multicriteria decision making Aggregation operators Partners Publications 2008 Devouassoux Y Reynaud S Jonniaux G Ribeiro R A and Pais T C 2008 Hazard avoidance developments for planetary exploration In GNC 2008 7th International ESA Conference on Guidance Navigation Control Systems Pais

    Original URL path: http://www.ca3-uninova.org/project_impacted (2016-02-17)
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  • CA3 - Computational Intelligence Research Group
    for investigating Monitoring Diagnosis technologies is based on the complex nature of remote exploration characterised by restricted communication links and hostile environment The uncertainty of the environment and the need for safety in response to low level anomalies limit the use of sequential tasking Monitoring Diagnosis is a base technology for autonomy together with Planning Scheduling requiring AI techniques in order to reproduce the expertise of humans and performed advanced FDIR Fault Detection Isolation and Recovery Unmanned exploration units as well as the control units of manned space vehicles and habitats must be able to predict failures by monitoring their own evolving behaviour and detecting subtle deviations over time Monitoring Diagnosis Monitoring Diagnosis capabilities have found little industrial application in space because of a lack of clear need despite a good basis of theoretical studies on the usage of fuzzy logic or model based FDIR But a Monitoring Diagnosis tools based on fuzzy logics is already running operational at ESOC monitoring the gyroscopes of ENVISAT 2 3 This shows that the technology is mature if applied on well known systems and implemented on ground The suitability of Monitoring Diagnosis in the frame of Aurora Mars missions is expected but still to be demonstrated Can software monitor a complex mechanical devices of a robotic payload If yes can this be performed on board MODI Objectives The aim of the MODI activity is two answer these two questions taking as a case study the Monitoring Diagnosis of the most complex subsystem taken on board the payload of the two first ESA Exploration missions ExoMars and Mars Sample Return i e a drilling and sampling system The goal of this activity is thus to assess the feasibility of on board or on ground monitoring and diagnosis of devices of a drilling and sampling

    Original URL path: http://www.ca3-uninova.org/project_modi (2016-02-17)
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  • CA3 - Computational Intelligence Research Group
    mission to be considered is that of Near Earth environment from the orbit range of LEO to GEO including all the inclinations The main goal of the SESS project is to provide Telecom and Navigation Mission operators project teams development engineers and scientists with a completely operational prototype capable of supplying in a structured manner information on the space environment and its effects on the spacecraft Although conceptually SESS shall

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