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Recognizing drivers' sleep onset by detecting slow eye movement using a parallel multimodal one-dimensional convolutional neural network.
Comput Methods Biomech Biomed Engin
January 2025
School of Computer Science and Artificial Intelligence, Aliyun School of Big Data, Changzhou University, Changzhou, P.R. China.
Slow eye movements (SEMs) are a reliable physiological marker of drivers' sleep onset, often accompanied by EEG alpha wave attenuation. A parallel multimodal 1D convolutional neural network (PM-1D-CNN) model is proposed to classify SEMs. The model uses two parallel 1D-CNN blocks to extract features from EOG and EEG signals, which are then fused and fed into fully connected layers for classification.
View Article and Find Full Text PDFIntegrating attention mechanism and boundary detection for building segmentation from remote sensing images.
Front Neurorobot
January 2025
College of Artificial Intelligence, Taiyuan University of Technology, Jinzhong, Shanxi, China.
Accurate building segmentation has become critical in various fields such as urban management, urban planning, mapping, and navigation. With the increasing diversity in the number, size, and shape of buildings, convolutional neural networks have been used to segment and extract buildings from such images, resulting in increased efficiency and utilization of image features. We propose a building semantic segmentation method to improve the traditional Unet convolutional neural network by integrating attention mechanism and boundary detection.
View Article and Find Full Text PDFDetecting IDH and TERTp mutations in diffuse gliomas using H-MRS with attention deep-shallow networks.
Comput Biol Med
January 2025
Institute of Biomedical Engineering, Bogazici University, Istanbul, Turkey; Center for Neuroradiological Applications and Research, Acibadem University, Istanbul, Turkey.
Background: Preoperative and noninvasive detection of isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase gene promoter (TERTp) mutations in glioma is critical for prognosis and treatment planning. This study aims to develop deep learning classifiers to identify IDH and TERTp mutations using proton magnetic resonance spectroscopy (H-MRS) and a one-dimensional convolutional neural network (1D-CNN) architecture.
Methods: This study included H-MRS data from 225 adult patients with hemispheric diffuse glioma (117 IDH mutants and 108 IDH wild-type; 99 TERTp mutants and 100 TERTp wild-type).
Two-dimensional Monte Carlo simulation coupled with multilinear regression modeling of source-specific health risks from groundwater.
J Hazard Mater
January 2025
University of Belgrade, Faculty of Technology and Metallurgy, Karnegijeva 4, Belgrade 11120, Serbia. Electronic address:
Effective protection of groundwater requires an accurate health risk assessment of contaminants; however, the diversity of pollution sources, variability, and uncertainties in exposure parameters present significant challenges in this assessment. In this study, groundwater risk estimates associated with NO, and F, along with fourteen heavy metal(loid)s (V, Cr, Mn, Fe, Ni, Cu, As, Co, Cd, Se, Pb, Hg, Zn, and Al) in an agricultural area were optimized by implementing positive matrix factorization (PMF), multilinear regression, and two-dimensional Monte Carlo simulations to characterize source-specific health risks. Groundwater pollution was analyzed considering regional variations, including differences in elevation, land use and land cover, and soil types.
View Article and Find Full Text PDFTwo-Dimensional Liquid Chromatography-Isotope Ratio Mass Spectrometry Opens New Possibilities in the Field of Compound-Specific Stable Isotope Analysis.
Anal Chem
January 2025
Instrumental Analytical Chemistry, University of Duisburg-Essen, Universitätsstraße 5, 45141 Essen, Germany.
Compound-specific stable isotope analysis (CSIA) using liquid chromatography-isotope ratio mass spectrometry (LC-IRMS) is a powerful tool for determining the isotopic composition of carbon in analytes from complex mixtures. However, LC-IRMS methods are constrained to fully aqueous eluents. Previous efforts to overcome this limitation were unsuccessful, as the use of organic eluents in LC-IRMS was deemed impossible.
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