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Robustly detecting mpox and non-mpox using a deep learning framework based on image inpainting.
Sci Rep
January 2025
School of Mathematics and Systems Science, Guangdong Polytechnic Normal University, No. 293, Zhongshan Avenue West, Tianhe District, Guangzhou, 510665, China.
Due to the lack of efficient mpox diagnostic technology, mpox cases continue to increase. Recently, the great potential of deep learning models in detecting mpox and non-mpox has been proven. However, existing methods are susceptible to interference from various noises in real-world settings, require diverse non-mpox images, and fail to detect abnormal input, which makes them unsuitable for practical deployment and application.
View Article and Find Full Text PDFInflammatory Biomarkers and Tinnitus in Older Adults.
Noise Health
January 2025
Associate Postgraduation Program UEL/UNOPAR, Curitiba, Paraná, Brazil.
Background: Tinnitus refers to a common disorder affecting older adults frequently. This condition can disturb mental health and psychological well-being and contribute to cognitive decline. Despite recent advances in research, its pathophysiology remains incompletely understood.
View Article and Find Full Text PDFEffects of face protector devices on acoustic parameters of voice.
Acta Otorhinolaryngol Ital
December 2024
Audiology and Phoniatrics Service, ENT Department, University of Modena e Reggio Emilia, Modena, Italy.
Objectives: The SARS-CoV-2 pandemic required the use of personal protective equipment (PPE) in medical and social contexts to reduce exposure and prevent pathogen transmission. This study aims to analyse possible changes in voice and speech parameters with and without PPE.
Methods: Speech samples using different types of PPE were obtained.
A study on Pufferfish privacy algorithm based on Gaussian mixture models.
Sci Rep
January 2025
IRC-ISS, King Fahd University of Petroleum and Minerals, Dhahran, 34463, Saudi Arabia.
In real-world scenarios, mixture models are frequently employed to fit complex data, demonstrating remarkable flexibility and efficacy. This paper introduces an innovative Pufferfish privacy algorithm based on Gaussian priors, specifically designed for Gaussian mixture models. By leveraging a sophisticated masking mechanism, the algorithm effectively safeguards data privacy.
View Article and Find Full Text PDFHarnessing unlabeled data: Enhanced rare earth component content prediction based on BiLSTM-Deep autoencoder.
ISA Trans
January 2025
School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, 330013, Jiangxi, China; Key Laboratory of Advanced Control & Optimization of Jiangxi Province, Nanchang, 330013, Jiangxi, China. Electronic address:
Traditional data-driven models for predicting rare earth component content are primarily developed by relying on supervised learning methods, which suffer from limitations such as a lack of labeled data, lagging, and poor usage of a major amount of unlabeled data. This paper proposes a novel prediction approach based on the BiLSTM-Deep autoencoder enhanced traditional LSSVM algorithm, termed BiLSTM-DeepAE-LSSVM. This approach thoroughly exploits the implicit information contained in copious amounts of unlabeled data in the rare earth production process, thereby improving the traditional supervised prediction method and increasing the accuracy of component content predictions.
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