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Harnessing advanced hybrid deep learning model for real-time detection and prevention of man-in-the-middle cyber attacks.
Sci Rep
January 2025
Department of Electronics and Communication Engineering, Panimalar Engineering College, Chennai, India.
Article Synopsis
- The increasing use of connected devices in smart homes has heightened security risks, particularly from Man-in-the-Middle (MitM) attacks, which can go undetected.
- Traditional security methods struggle to manage these complex threats, highlighting the need for more advanced intrusion detection systems.
- The AEXB Model, a hybrid deep learning approach combining AutoEncoder for feature extraction and XGBoost for classification, achieves 97.24% accuracy in detecting MitM attacks, while also enabling real-time threat responses and continuous protection.
Engineered sulfonated porous carbon/cellulose nanofiber hybrid membrane for high-efficiency osmotic energy conversion applications.
Int J Biol Macromol
January 2025
Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, Nanjing Forestry University, Nanjing 210037, China; International Innovation Center for Forest Chemicals and Materials, Nanjing Forestry University, Nanjing 210037, China. Electronic address:
Harnessing ionic gradients to generate electricity has inspired the development of nanofluidic membranes with charged nanochannels for osmotic energy conversion. However, achieving high-performance osmotic energy output remains elusive due to the trade-off between ion selectivity and nanochannel membrane permeability. In this study, we report a homogeneous nanofluidic membrane, composed of sulfonated nanoporous carbon (SPC) and TEMPO-oxidized cellulose nanofibers (T-CNF), engineered to overcome these limitations.
View Article and Find Full Text PDFReconstruction of Optical Coherence Tomography Images from Wavelength Space Using Deep Learning.
Sensors (Basel)
December 2024
Institute of Optical Materials and Technologies, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria.
Conventional Fourier domain Optical Coherence Tomography (FD-OCT) systems depend on resampling into a wavenumber () domain to extract the depth profile. This either necessitates additional hardware resources or amplifies the existing computational complexity. Moreover, the OCT images also suffer from speckle noise, due to systemic reliance on low-coherence interferometry.
View Article and Find Full Text PDFPorter 6: Protein Secondary Structure Prediction by Leveraging Pre-Trained Language Models (PLMs).
Int J Mol Sci
December 2024
School of Computer Science, University College Dublin (UCD), D04 V1W8 Dublin, Ireland.
Accurately predicting protein secondary structure (PSSP) is crucial for understanding protein function, which is foundational to advancements in drug development, disease treatment, and biotechnology. Researchers gain critical insights into protein folding and function within cells by predicting protein secondary structures. The advent of deep learning models, capable of processing complex sequence data and identifying meaningful patterns, offer substantial potential to enhance the accuracy and efficiency of protein structure predictions.
View Article and Find Full Text PDFHarnessing nature's therapeutic potential: A review of natural products in prostate cancer management.
Urol Oncol
January 2025
Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD. Electronic address:
Prostate cancer is the most commonly diagnosed cancer and the second leading cause of cancer-related death among men in the United States. The global burden of this disease is rising, placing significant strain on healthcare systems worldwide. Although definitive therapies like surgery and radiation are often effective, prostate cancer can recur and progress to castration-resistant prostate cancer in some cases.
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