Publications internationales

2024
Nadira Boukhatem, Kamel Messaoudi, Abdelghani Redjati, Abderraouf Fares, Fatima Brik,. (2024), Assessment of Optimization Parameters for Video Transmission over Optical Fiber using an H265/HEVC Encoder in Video Streaming Applications . journal OF NANO AND ELECTRONIC PHYSICS : https://jnep.sumdu.edu.ua/en/component/main/editors, https://jnep.sumdu.edu.ua/en/full_article/3895

Résumé: In this research, we investigated and analyzed the performance of an optical video transmission system. We combined the benefits of HEVC compression techniques and OTDM multiplexing using the Differential Phase Shift Keying (DPSK) scheme. Source and channel coding are separately designed and then cascaded. The intra-prediction module used in HEVC encoder has been implemented using the Matlab tool to show its ability to select the coding prediction threshold and block size using all prediction unit sizes and modes PUs). The obtained results have been implemented for the second contribution concerning the proposed iber transmission system using the OptiSystem software. To evaluate the proposed system, several metrics were used, including the signal-to-noise ratio (SNR), Q-factor, and bit error rate (BER). The simulation results show that the optimization criterion led to better performance in terms of transmission quality, in improving Q-factor and minimizing (BER), thus providing a significant resolution reduction of the video stream, which reduces the amount of data before being transmitted on the optical fiber.

Nadira Boukhatem 1* , Kamel Messaoudi 2 , Abdelghani Redjati 3 , Fatima Brik 4 , Amani Nasri 5 . (2024), Analysis of the Compressed Video with HEVC under Optical Link Transmission . Applied Computer Systems : https://doi.org/10.2478/acss-2024-0007, https://content.sciendo.com

Résumé: Abstract – We study the feasibility of video transmission over optical fibre to optimise bandwidth with the implementation of HEVC codec features. We use simulation (Matlab and the OptiSystem software). Different values of the CRF are used to evaluate its impact on the visual quality and the size of the encoded file, as well as its influence on the video transmission performance. The simulation results show that by adjusting the CRF, the encoders can optimise the compression of the video data to reduce the file size while preserving an acceptable visual quality. This makes it possible to adapt the transmission to the bandwidth constraints of the optical fibre, by choosing higher CRF values to reduce the size of the files and save bandwidth, or lower values to maintain optimal quality when the bandwidth is sufficient. In addition, from the optical fibre point of view, the dispersion weakens and the eye opens, and it is observed that the length of the fibres is inversely proportional to the signal transmission quality. Thus, the judicious use of different CRF values can contribute to efficient and high-quality video transmission via optical fibre.

2023
Abdelghani Redjati, Amira Boulmaiz, Mohamed Boughazi, Karima Boukari. (2023), 1.A-Novel-Deep-Learning-Model-for-Recognition-of-Endangered-Water-Bird-Species. International Journal of Sociotechnology and Knowledge Development
Saadi Mohamed Nacer1 · Bouteraa Nadia · Redjati Abdelghani · Boughazi Mohamed. (2023), A novel method for bearing fault diagnosis based on BiLSTM neural networks. The International Journal of Advanced Manufacturing Technology (2023) 125:1477–1492
2022
Amira Boulmaiz, Billel Meghni, Abdelghani Redjati, Ahmad Taher Azar, . (2022), LiTasNeT: A Bird Sound Separation Algorithm Based on Deep Learnin
2020
Z. Neili, M. Fezari, A. Redjati. (2020), ELM and K-nn machine learning in classification of Breath sounds signals

Communications internationales

2024
Karima Boukari, Amira Boulmaiz, Abdelghani Redjati and Mohamed Boughazi . (2024), Biometric system based on features extraction by CNN pretrained models of two hand datasets CNN pretrained models of two hand datasets . The 2nd International Conference on Modern Electrical Engineering and Technology ICMEET’24 December 13-14, 2024 , Souk Ahras , Algeria : Mohamed Cherif Messaidia University, Souk Ahras, Faculty of Science and Technology,
2022
A. Redjati, A. Boulmaiz, T.Hafs, K.Boukari, M.Boughazi. (2022), Vocal Control System of Weelchair for disabled people and Domotics based on the Firebase Real-time Database.
A.Boulmaiz, A. Redjati, K. Boukari, M.Boughazi, T.Hafs. (2022), ResBirdNet : An Efficient Deep Learning Model for Bird Recognition
Ala Wali Eddine Boudersa, Nadia Bouteraa, A.Redjati. (2022), A Machine Learning Approch to Fingerprint Compression : use of a Convolutional autoEncoder.
2021
Z.Neili , M. Fezari , A.Redjati and Kenneth Sundaraj. (2021), A comparative study of the VGG16 Trained from Scratch and using Transfer Learning for Lung Sounds Classification
Z.Neili , M. Fezari , A.Redjati, and Kenneth Sundaraj. (2021), VGG16, ResNet-50 and GoogleNet Deep learning Architecture for Breathing Sound Classification : A comparative Study
Z. Neili, M. Fezari, A. Redjati and Kenneth Sundaraj. (2021), Three ResNet Deep Learning Architectures Applied in Pulmonary Pathologies Classification
2019
Mounir BEKAIK Abdelghani REDJATI. (2019), Linear Quadratic Gaussian Control of three tank hydraulic System
NEILI Zakaria, Mohammed FEZARI, Abdelghani REDJATI. (2019), Classification of Breath Sounds signals using K-nn machine learning based on energy and entropy features . 4th International Conference on Embedded Systems in Telecommunications and Instrumentation ICESTI'19
2018
Zakaria Naili, Mohamed Fezari, Redjati Adelghani . (2018), Analysis of Acoustic Parametersfrom Respiratory Signal in COPD and Pneumoniapatients. 4th International Conference on Signal, Image, Vision and their Applications (SIVA’18)
2017
Mohamed-Nacer Saadi , Messaoud Boukhenaf, Abdelghani Redjati ,Noureddine Guersi. (2017), Bearing failures detection in induction motors using the stator current analysis based on Hilbert Huang transform
2016
M-N. SAADI1 , M. BOUKHENAF2 , N. GUERSI1 , G. REDJATI1 ,. (2016), Bearing Failures Detection in Induction motors using the stator current analysis based on EEMD