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An improved DeepLabv3 + railway track extraction algorithm based on densely connected and attention mechanisms.
Sci Rep
January 2025
School of Computer Science, Hunan University of Technology, Tianyuan District, Zhuzhou, 412007, China.
The railway track extraction using unmanned aerial vehicle (UAV) aerial images suffers from issues such as low extraction accuracy and high time consumption. In response to these problems, this paper presents a lightweight algorithm DA-DeepLabv3 + based on densely connected and attention mechanisms. Firstly, the lightweight MobileNetV2 network is employed to replace the Xception feature extraction network, thereby reducing the number of model parameters.
View Article and Find Full Text PDFExperimental Study on the Elastic Support in a Discrete Rail Fastening System Used in Ballastless Tram Track Structures.
Materials (Basel)
January 2025
Faculty of Civil Engineering, Warsaw University of Technology, Al. Armii Ludowej 16, 00-637 Warsaw, Poland.
This paper presents an experimental study on the elastic support in a discrete rail fastening system used in a ballastless tram track structure. The study focuses on the elastic support of the anchor element, specifically the Pm49 baseplate. These elements significantly influence environmental pollution along tram routes, such as vibration (at low frequencies) or noise (at high frequencies), as well as static and dynamic rail deflections.
View Article and Find Full Text PDFSecuring the Future of Railway Systems: A Comprehensive Cybersecurity Strategy for Critical On-Board and Track-Side Infrastructure.
Sensors (Basel)
December 2024
IMT Atlantique, Campus De Rennes 2 r Châtaigneraie, 35510 Cesson Sévigné, France.
The growing prevalence of cybersecurity threats is a significant concern for railway systems, which rely on an extensive network of onboard and trackside sensors. These threats have the potential to compromise the safety of railway operations and the integrity of the railway infrastructure itself. This paper aims to examine the current cybersecurity measures in use, identify the key vulnerabilities that they address, and propose solutions for enhancing the security of railway infrastructures.
View Article and Find Full Text PDFIdentification Method for Railway Rail Corrugation Utilizing CEEMDAN-PE-SPWVD.
Sensors (Basel)
December 2024
College of Railway Transportation, Hunan University of Technology, Zhuzhou 412007, China.
Rail corrugation intensifies wheel-rail vibrations, often leading to damage in vehicle-track system components within affected sections. This paper proposes a novel method for identifying rail corrugation, which combines Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), permutation entropy (PE), and Smoothed Pseudo Wigner-Ville Distribution (SPWVD). Initially, vertical acceleration data from the axle box are decomposed using CEEMDAN to extract intrinsic mode functions (IMFs) with distinct frequencies.
View Article and Find Full Text PDFClinical Perspectives on the Pathophysiology of Facial Synkinesis: A Narrative Review.
JAMA Otolaryngol Head Neck Surg
January 2025
Department of Plastic Surgery, The University of Texas Southwestern Medical Center, Dallas.
Importance: Facial synkinesis refers to pathologic cocontraction and baseline hypertonicity of muscles innervated by the facial nerve, commonly attributed to the aberrant regeneration of nerve fibers following injury. The pathomechanism and optimal treatment of facial synkinesis remain unclear. The goal of this review is to highlight current understanding of the epidemiology, pathophysiology, clinical presentation, assessment, and treatment of facial synkinesis.
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