Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Raouf Ketata"'
Autor:
Maha Ben Ayed, Moncef Soualhi, Raouf Ketata, Nicolas Mairot, Sylvian Giampiccolo, Noureddine Zerhouni
Publikováno v:
International Journal of Prognostics and Health Management, Vol 15, Iss 1 (2024)
Data-driven Prognostics and Health Management (PHM) become a crucial layer in the realm of predictive maintenance (PM). However, many industries develop PM technologies based on the monitoring of machine data to anticipate failures without considerin
Externí odkaz:
https://doaj.org/article/9d260f1f2d34473381f2cd271cc1ee14
Publikováno v:
International Journal of Emerging Technology and Advanced Engineering. 11:147-160
Recently, the Quality Management System (QMS) control supports organizations managers identifying the best practices to upgrade the efficiency and effectiveness. This control has become a successful tool to improve the organization decision-making pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d6977e5c38fa34e5e19d8e926a42ea6c
https://doi.org/10.46338/ijetae1121_17
https://doi.org/10.46338/ijetae1121_17
Autor:
Hela Lassoued, Raouf Ketata
Publikováno v:
2022 5th International Conference on Advanced Systems and Emergent Technologies (IC_ASET).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::21690271b34ff9e7133985acc9063d4f
https://doi.org/10.1109/ic_aset53395.2022.9765913
https://doi.org/10.1109/ic_aset53395.2022.9765913
This paper presents a data driven system used for cardiac arrhythmia classification. It applies the Neuro-Fuzzy Inference System (ANFIS) to classify MIT-BIH arrhythmia database electrocardiogram (ECG) recordings into five (5) heartbeat types. In fact
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2659::026745ed669ff1f4e3bc76781b6937d7
https://zenodo.org/record/5751490
https://zenodo.org/record/5751490
Autor:
Tanvir Ahmed, Honglin An, Mohammad Reza Askari, Md. Assad-Uz-Zaman, Alireza Bahramian, Joanna Balbus, Mohamed Benrejeb, Olfa Boubaker, Brahim Brahmi, Rachel Brandt, Catherine Jiayi Cai, Xinchen Cai, Ines Chihi, Ali Cinar, Ong Kwok Chin Douglas, Iman Hajizadeh, Nicole Hobbs, Juan J. Huaroto, Md Rasedul Islam, Sajad Jafari, Ernest N. Kamavuako, Raouf Ketata, Krystian Kubica, Seenivasan Lalithkumar, Abir Lassoued, Hela Lassoued, Chwee Ming Lim, Phoebe Lim, Mohammad Habibur Rahman, Krishna Ramachandra, Mudassir Rashid, Hongliang Ren, Fathalla A. Rihan, Nouran F. Rihan, Mert Sevil, Etsel Suárez, Leoni Goh Yi Ting, Farzad Towhidkhah, Zion Tszho Tse, Emir A. Vela
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b3e06e66a1afd8eed6c633fa44254d4c
https://doi.org/10.1016/b978-0-12-821350-6.09996-0
https://doi.org/10.1016/b978-0-12-821350-6.09996-0
Autor:
Hela Lassoued, Raouf Ketata
Publikováno v:
Control Theory in Biomedical Engineering ISBN: 9780128213506
This chapter presents a cardiac arrhythmia classification method that is based on the fuzzy logic controller (FLC) and the genetic algorithm (GA). Firstly, the baseline shift is removed from the electrocardiogram (ECG) signals. Then, several morpholo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ee9ce141338e75df7046039ac32a5560
https://doi.org/10.1016/b978-0-12-821350-6.00005-6
https://doi.org/10.1016/b978-0-12-821350-6.00005-6
Publikováno v:
International Journal on Smart Sensing and Intelligent Systems, Vol 11, Iss 1 (2018)
The success of an Electrocardiogram (ECG) Decision Support System (DSS) requires the use of an optimum machine learning approach. For this purpose, this paper investigates the use of three feedforward neural networks; the Multilayer Perceptron (MLP),
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39a3ba78449afd3d147798e501700569
https://doi.org/10.21307/ijssis-2018-029
https://doi.org/10.21307/ijssis-2018-029
Autor:
Hela Lassoued, Raouf Ketata
Publikováno v:
2018 International Conference on Advanced Systems and Electric Technologies (IC_ASET).
The main objective of this paper is to prepare a Clinical Decision Support System (CDSS) for a multi-class classification of ElectroCardioGram (ECG) signals into certain cardiac diseases. This CDSS is based on Artificial Neural Network (ANN) as a mac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c72664593a6daa9fc57ecf3ded04ce06
https://doi.org/10.1109/aset.2018.8379901
https://doi.org/10.1109/aset.2018.8379901
Publikováno v:
Computers in Industry. 62:460-466
In recent years, steering a quality-management system (QMS) has become a key strategic consideration in businesses. Indeed, companies constantly need to optimize their industrial tools to increase their productivity and to permanently improve the eff
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::25feb4cdbe0020c3732e16da292b5081
https://doi.org/10.1016/j.compind.2010.12.010
https://doi.org/10.1016/j.compind.2010.12.010
Publikováno v:
Applied Soft Computing. 11:166-178
In this paper, we propose a new approach that guarantees the stability and robustness of an adaptive control law of a nonlinear system. The control diagram proposed contains a Takagi-Sugeno-Kang fuzzy controller (TSK-FC) and a training block allowing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::47717969124f70662170649171f402b7
https://doi.org/10.1016/j.asoc.2009.11.007
https://doi.org/10.1016/j.asoc.2009.11.007