Entity

Time filter

Source Type


Kosinski W.,Polish-Japanese Institute of Information Technology | Kosinski W.,Kazimierz Wielki University in Bydgoszcz | Wegrzyn-Wolska K.,Ecole Superieure dIngenieurs en Informatique et Genie des Telecommunications
Studies in Computational Intelligence | Year: 2012

Ordered fuzzy numbers as generalization of convex fuzzy numbers are defined together with four algebraic operations. For defuzzification operators, that play the main role when dealing with fuzzy controllers and fuzzy inference systems, new representation formulae are given. Step ordered fuzzy numbers are considered. Approximation method based on forward neural networks is presented for determining defuzzification functionals when training sets of data are given. Results of approximation are given. © 2012 Springer-Verlag Berlin Heidelberg. Source


Grant
Agency: Cordis | Branch: FP7 | Program: CP | Phase: ICT-2007.7.1 | Award Amount: 10.72M | Year: 2008

CompanionAble adresses the issues of social inclusion and homecare of persons suffering from chronic cognitive disabilities prevalent among the elderly, a rapidly increasing population group. Those people need support of carers and are at risk of social exclusion, yet this problem not well addressed by ICT technology, but would lead to a social and economical pressure for staying at home as long as possible.\n\nThe main unique selling point of the CompanionAble project lies in the synergetic combination of the strengths of a mobile robotic companion with the advantages of a stationary smart home, since neither of those approaches alone can accomplish the demanding tasks to be solved. Positive effects of both individual solutions shall be combined to demonstrate how the synergies between a stationary smart home solution and an embodied mobile robot companion can make the care and the care persons interaction with her assistive system significantly better. \n\nStarting with a profound requirements engineering for ICT-supported care and therapy management for the care persons, basic technologies for multimodal user observation and human-machine interaction will provide the fundamentals for the development of a stationary smart home assistive system and a mobile robot assistant, building the cornerstones of the overall system integrating the promising solutions of both parts. Substantial support comes from the research activities focusing on an architectural framework, allowing such a complex care scenario solution be achievable. After the realization of the respective scenarios, long lasting field experiments will be carried out to evaluate and test the system, and both scenarios can be evaluated to show their strength and weaknesses. This will initiate the development of an overall, integrated care scenario (smart home with embedded robot companion). \nThe realization of this integrated care concept is to be seen as the in-principal vision of CompanionAble.


Ecole Superieure dIngenieurs en Informatique et Genie des Telecommunications | Entity website

Merci de remplir les champs obligatoires (indiqus par *)


Ecole Superieure dIngenieurs en Informatique et Genie des Telecommunications | Entity website

French engineering education is recognized around the world for its diversity and richness, and for its ability to produce highly competent engineers. France plays a central role in Europe, combining the best of its academic and professional training to create an exceptional and multicultural educational environment from which new talents emerge ...


Aguilar P.A.C.,Orange S.A. | Boudy J.,Orange S.A. | Istrate D.,Ecole Superieure dIngenieurs en Informatique et Genie des Telecommunications | Medjahed H.,Ecole Superieure dIngenieurs en Informatique et Genie des Telecommunications | And 5 more authors.
International Journal of E-Health and Medical Communications | Year: 2013

The multi-sensor fusion can provide more accurate and reliable information compared to information from each sensor separately taken. Moreover, the data from multiple heterogeneous sensors present in the medical surveillance systems have different degrees of uncertainty. Among multi-sensor data fusion techniques, Bayesian methods and Evidence theories such as Dempster-Shafer Theory (DST) are commonly used to handle the degree of uncertainty in the fusion processes. Based on a graphic representation of the DST called Evidential Networks, we propose a structure of heterogeneous multi-sensor fusion for falls detection. The proposed Evidential Network (EN) can handle the uncertainty present in a mobile and a fixed sensor-based remote monitoring systems (fall detection) by fusing them and therefore increasing the fall detection sensitivity compared to the a separated system alone. Copyright © 2013, IGI Global. Source

Discover hidden collaborations