In this paper, we propose a new and efficient ferroelectric nanostructure metal oxide lithium niobate [(Li1.075Nb0.625Ti0.45O3), (LNTO)] solid film as a saturable absorber (SA) for modulating passive Q-switched erbium-doped fiber laser (EDFL). The SA is fabricated as a nanocomposite solid film by the drop-casting process in which the LNTO is planted within polyvinylidene fluoride-trifluoroethylene [P(VDF-TrFE)] as host copolymer. The optical and physical characteristics of the solid film are experimentally established. The SA is incorporated within the cavity of EDFL to examine its capability for producing multi-wavelength laser. The experimental results proved that a multi-wavelength laser is produced, where stable four lines with central

Receipt date:3/13/2021 accepted date:5/26/2021 Publication date:12/31/2021

 This work is licensed under a Creative Commons Attribution 4.0 International License.

energy is one of the strategic resources within international politics, and this is through the existing competition between the international powers on it, and the global powers have begun to rely on interest in new areas, such as import, depending on new projects an

Aluminum plasma was generated by the irradiation of the target
with Nd: YAG laser operated at a wavelength of 1064 nm. The
effect of laser power density and the working pressure on spectral
lines generating by laser ablation, were detected by using optical
spectroscopy. The electron density was measured using the Stark
broadening of aluminum lines and the electron temperature by
Boltzmann plot method it is one of the methods that are used. The
electron temperature Te, electron density ne, plasma frequency
and Debye length increased with increasing the laser peak
power. The electron temperature decrease with increasing gas
pressure.

This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K

Researchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model wa

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