Fetal-Maternal Electrocardiograms Mixtures Characterization Based on Time Analysis

Ziani, Said; Hassouani, Y. El

doi:10.1109/icoa.2019.8727619

Cited by 20 publications

(6 citation statements)

References 6 publications

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“…The authors of [24] investigate the optimization of processing time and computing resources in a mobile edge computing node. Finally, this study's results highlight the integrated data analysis techniques often used in biomedical signal processing, such as ICA-NMF-SVD-PCA [25]- [28] with wavelets to further enhance the effectiveness of the methods as mentioned earlier.…”

Section: Discussion Of Resultsmentioning

confidence: 56%

Permanent magnet synchronous motor control performed using PI-backstepping with a model of harmonics reduction

Ziani¹,

Ghmary

Zorgani³

2023

IJPEDS

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This paper focuses on the control of permanent magnet synchronous motors (PMSMs) utilizing a non-linear adaptive PI-Backstepping design and a model of harmonics reduction approach that uses an active shunt filter followed by a cascade bandpass filter. While conventional backstepping may assure the system's stability, it is often imprecise. It creates a significant amount of static error, which has a detrimental effect on the system's behavior, such as disruptions and loads that might arise in industrial settings. We can assure minimum fixed errors and considerable interaction with uncertainty by integrating the PI controller with adaptive backstepping through robust Lyapunov functions. Numerical simulations are used to demonstrate the proposed controller's effectiveness.

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Section: Discussion Of Resultsmentioning

confidence: 56%

Permanent magnet synchronous motor control performed using PI-backstepping with a model of harmonics reduction

Ziani¹,

Ghmary

Zorgani³

2023

IJPEDS

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show abstract

“…This also appears to be applicable to synchronous motors using wavelets packets [48]- [49]. This study's findings also emphasize the need to use wavelets [50]- [52], integrated with data analysis techniques often employed in biomedical signal processing, such as ICA-NMF-SVD-PCA [53], [54] to further improve the aforementioned techniques' efficacy.…”

Section: Resultsmentioning

confidence: 63%

Solar panels overheating protection: a review

Laabab

Ziani

Benami

2022

IJEECS

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Reduced energy consumption is a direct result of building optimization. Solar panels and heat detectors can provide the necessary power. After years of refinement and development, methods for regulating solar panels' output are finally finding their way into everyday life, where they are having a dramatic impact on the foundations of sustainability. This document provides an up-to-date assessment of several strategies for preventing solar panels from overheating, all of which serve to boost their efficiency and prolong their service life. It begins with a brief background on protection technologies before moving on to a survey of recently filed patent applications that address this topic. The study concludes with a proposed assessment of the strengths and shortcomings of these safeguards. We anticipate that the information included in this review paper will be an invaluable tool for scholars and researchers.

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“…Another criterion that is very important in this comparison is the prediction in real time, since our system is supposed to be used in VR systems [23] for example, so we made a test with an external camera to see the performance of all the models in real time, and from this test we concluded that the ResNet50 model has a better performance in the prediction in real time of all the emotion classes. As indicated in the aforementioned literature [24][25][26], the method provided in this paper may be designed and implemented utilizing image segmentation techniques based on wavelet transformations.…”

Section: Accuracy = True Positive True Positive + False Positivementioning

confidence: 99%

Improved Methods for Automatic Facial Expression Recognition

Echoukairi¹,

Ghmary²,

Ziani³

et al. 2023

Int. J. Interact. Mob. Technol.

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Facial expressions constitute one of the most effective and instinctive methods that allow people to communicate their emotions and intentions. In this context, the both Machine Learning (ML) and Convolutional Neural Networks (CNNs) have been used for emotion recognition. Efficient recognition systems are required for good human-computer interaction. However, facial expression recognition is related to several methods that impact the performance of facial recognition systems. In this paper, we demonstrate a state-of-the-art of 65% accuracy on the FER2013 dataset by leveraging numerous techniques from recent research and we also proposed some new methods for improving accuracy by combining CNN architectures such as VGG-16 and Resnet-50 with auxiliary datasets such as JAFFE and CK. To predict emotions, we used a second approach based on geometric features and facial landmarks to calculate and transmit the feature vector to the SVM model. The results show that the ResNet50 model outperforms all other emotion prediction models in real time by maximizing.

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Fetal-Maternal Electrocardiograms Mixtures Characterization Based on Time Analysis

Cited by 20 publications

References 6 publications

Permanent magnet synchronous motor control performed using PI-backstepping with a model of harmonics reduction

Permanent magnet synchronous motor control performed using PI-backstepping with a model of harmonics reduction

Solar panels overheating protection: a review

Improved Methods for Automatic Facial Expression Recognition

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