In this work, we study the security performance of a double intelligent reflecting surface non-orthogonal multiple access (DIRS-NOMA) wireless communication system supporting communication for a group of two NOMA users (UEs) at the edge, with the existence of an eavesdropping device (ED). We also assume that there is no direct connection between the BS and the UEs. From the proposed model, we compute closed-form expressions for the secrecy outage probability (SOP) and the average security rate (ASR) for each UE. After that, we discuss and analyze the system security performance according to the NOMA power allocation for each user and the number of IRS counter-emission elements. In addition, we analyze the SOP of both the considered DIRS-NOMA and conventional NOMA systems to demonstrate that DIRS-NOMA systems have much better security than conventional NOMA systems. Based on the analytical results, we develop an ASR optimization algorithm using the alternating optimization method, combining NOMA power allocation factor optimization and IRS passive beam optimization through the Lagrange double transform. The derived analytical expressions are validated through Monte Carlo simulations.
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http://dx.doi.org/10.3390/s25041274 | DOI Listing |
JMIRx Med
March 2025
Stelmith, LLC, 2333 Aberdeen Pl, Carollton, TX, 75007, United States, 1 9459001314.
Background: The increasing integration of artificial intelligence (AI) systems into critical societal sectors has created an urgent demand for robust privacy-preserving methods. Traditional approaches such as differential privacy and homomorphic encryption often struggle to maintain an effective balance between protecting sensitive information and preserving data utility for AI applications. This challenge has become particularly acute as organizations must comply with evolving AI governance frameworks while maintaining the effectiveness of their AI systems.
View Article and Find Full Text PDFJ Biomol Struct Dyn
March 2025
School of Mechatronic Engineering and automation, Shanghai University, Shanghai, China.
Prediction of protein-ligand interactions is critical for drug discovery and repositioning. Traditional prediction methods are computationally intensive and limited in modeling structural changes. In contrast, data-driven deep learning methods significantly reduce computational costs and offer a more efficient approach for drug discovery.
View Article and Find Full Text PDFNanomaterials (Basel)
February 2025
School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin 150001, China.
The formation of ice due to global climate change poses challenges across multiple industries. Traditional anti-icing technologies often suffer from low efficiency, high energy consumption, and environmental pollution. Photothermal and hydrophobic surfaces with nano-micro structures (PHS-NMSs) offer innovative solutions to these challenges due to their exceptional optical absorption, heat conversion capabilities, and unique surface water hydrophobic characteristics.
View Article and Find Full Text PDFDisabil Rehabil
March 2025
Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), Centre Intégré Universitaire de Santé et de Services Sociaux de la Capitale Nationale (CIUSSS-CN), Quebec City, Canada.
Purpose: In Sub-Saharan Africa, family caregivers (FCs) almost systematically-and sometimes indefinitely-assist stroke survivors with activities of daily living and the stroke rehabilitation process. This study explored the experiences of FCs of stroke survivors in Burkina Faso.
Materials And Methods: A descriptive qualitative study was conducted with FCs recruited through convenience sampling.
Med Trop Sante Int
December 2024
Institut supérieur des techniques médicales de Lubumbashi (ISTM-Lubumbashi), République démocratique du Congo.
Objectives: The aim of this study was to determine the prevalence of respiratory symptoms, their determinants, and the state of respiratory function in millers exposed to cassava, maize, and soybean dust in Lubumbashi, Democratic Republic of Congo (DRC), compared with a group of unexposed workers.
Methods: A descriptive and analytical cross-sectional study was conducted in 2015 on 288 millers and 118 agents (n = 406) from a security agency (control group) in Lubumbashi, DRC. Participants were examined at their place of work.
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