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Local Lidocaine-Prilocaine for Immunisation in Infants.
Vaccines (Basel)
November 2024
Third Pediatric Discipline, Faculty of Medicine, Iuliu Hațieganu University of Medicine and Pharmacy, 400124 Cluj-Napoca, Romania.
: Lidocaine-prilocaine cream effectively reduces vaccination pain, improving vaccination adherence and advocating for its routine use in healthcare settings. : This review used PRISMA guidelines and the PICOT format to structure the analysis. The focus was on paediatric patients aged 0-12 months requiring intramuscular vaccinations, comparing the application of lidocaine-prilocaine cream to other interventions or no treatment.
View Article and Find Full Text PDFNetwork Dismantling on Signed Network by Evolutionary Deep Reinforcement Learning.
Sensors (Basel)
December 2024
School of Statistics and Data Science, Nankai University, Tianjin 300074, China.
Network dismantling is an important question that has attracted much attention from many different research areas, including the disruption of criminal organizations, the maintenance of stability in sensor networks, and so on. However, almost all current algorithms focus on unsigned networks, and few studies explore the problem of signed network dismantling due to its complexity and lack of data. Importantly, there is a lack of an effective quality function to assess the performance of signed network dismantling, which seriously restricts its deeper applications.
View Article and Find Full Text PDFDepth Prediction Improvement for Near-Field iToF Lidar in Low-Speed Motion State.
Sensors (Basel)
December 2024
Department of Electronic & Computer Engineer, University of Limerick, V94 T9PX Limerick, Ireland.
Current deep learning-based phase unwrapping techniques for iToF Lidar sensors focus mainly on static indoor scenarios, ignoring motion blur in dynamic outdoor scenarios. Our paper proposes a two-stage semi-supervised method to unwrap ambiguous depth maps affected by motion blur in dynamic outdoor scenes. The method trains on static datasets to learn unwrapped depth map prediction and then adapts to dynamic datasets using continuous learning methods.
View Article and Find Full Text PDFRealisation of an Application Specific Multispectral Snapshot-Imaging System Based on Multi-Aperture-Technology and Multispectral Machine Learning Loops.
Sensors (Basel)
December 2024
Group of Quality Assurance and Industrial Image Processing, Faculty of Mechanical Engineering, Technische Universität Ilmenau, Gustav-Kirchhoff-Platz 2, 98693 Ilmenau, Germany.
Multispectral imaging (MSI) enables the acquisition of spatial and spectral image-based information in one process. Spectral scene information can be used to determine the characteristics of materials based on reflection or absorption and thus their material compositions. This work focuses on so-called multi aperture imaging, which enables a simultaneous capture (snapshot) of spectrally selective and spatially resolved scene information.
View Article and Find Full Text PDFEnergy-Efficient Dynamic Enhanced Inter-Cell Interference Coordination Scheme Based on Deep Reinforcement Learning in H-CRAN.
Sensors (Basel)
December 2024
College of AI/SW Convergence, Kyungnam University, 7 Gyeongnamdaehak-ro, Masanhappo-gu, Changwon 51767, Republic of Korea.
The proliferation of 5G networks has revolutionized wireless communication by delivering enhanced speeds, ultra-low latency, and widespread connectivity. However, in heterogeneous cloud radio access networks (H-CRAN), efficiently managing inter-cell interference while ensuring energy conservation remains a critical challenge. This paper presents a novel energy-efficient, dynamic enhanced inter-cell interference coordination (eICIC) scheme based on deep reinforcement learning (DRL).
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