We employ a Genetic Algorithm for the purpose of minimization of the maximum differential modal gain (DMG) over all the supported signal modes (at the same wavelength) of cladding-pumped four-mode and six-mode-group EDFAs. The optimal EDFA designs found through the algorithm provide less than 1 dB DMG across the C-band (1530-1565 nm) whilst achieving more than 20 dB gain per mode. We then analyze the sensitivity of the DMG to small variations from the optimal value of the erbium doping concentration and the structural parameters, and estimate the fabrication tolerance for reliable amplifier performance.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1364/OE.22.021499 | DOI Listing |
Microsc Res Tech
January 2025
AIDA Lab. College of Computer and Information Sciences (CCIS), Prince Sultan University, Riyadh, Saudi Arabia.
The development of deep learning algorithms has transformed medical image analysis, especially in brain tumor recognition. This research introduces a robust automatic microbrain tumor identification method utilizing the VGG16 deep learning model. Microscopy magnetic resonance imaging (MMRI) scans extract detailed features, providing multi-modal insights.
View Article and Find Full Text PDFIn this work, a five-mode erbium-doped waveguide amplifier with low differential modal gain (DMG) is first proposed. A novel, to the best of our knowledge, gain equalization scheme for synergistic reconfiguration of refractive index and concentration doping is adopted to equalize the modal gains based on the dual-layer ring core structure. NaYF:5%Gd,20%Yb,2%Er@NaYF nanoparticles are synthesized by annealing treatment to improve the emission spectral properties and the concentration doped in a host core material.
View Article and Find Full Text PDFNat Ment Health
January 2025
Methods of Plasticity Research, Department of Psychology, University of Zurich, Zurich, Switzerland.
Atypical face processing is commonly reported in autism. Its neural correlates have been explored extensively across single neuroimaging modalities within key regions of the face processing network, such as the fusiform gyrus (FFG). Nonetheless, it is poorly understood how variation in brain anatomy and function jointly impacts face processing and social functioning.
View Article and Find Full Text PDFJ Orthop Case Rep
January 2025
Department of Orthopaedic Surgery, Maulana Azad Medical College, Bahadur Shah Marg, New Delhi, India.
Introduction: Tumoral calcinosis is a rare hereditary condition characterized by the deposition of calcium phosphate and hydroxyapatite in periarticular soft tissues. First described by Giard and Duret in 1898 and later detailed by Inclan in 1943, this condition has often been confused with other forms of periarticular calcification. Tumoral calcinosis predominantly affects young males and is typically found around major joints, such as the shoulder, elbow, hip, ankle, and wrist.
View Article and Find Full Text PDFSensors (Basel)
January 2025
State Key Laboratory of Intelligent Vehicle Safety Technology, Chongqing 401133, China.
With the advancement of federated learning (FL), there is a growing demand for schemes that support multi-task learning on multi-modal data while ensuring robust privacy protection, especially in applications like intelligent connected vehicles. Traditional FL schemes often struggle with the complexities introduced by multi-modal data and diverse task requirements, such as increased communication overhead and computational burdens. In this paper, we propose a novel privacy-preserving scheme for multi-task federated split learning across multi-modal data (MTFSLaMM).
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!