AIMC Topic: Spectrum Analysis
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An ML-Enhanced Laser-Based Methane Slip Sensor Using Wavelength Modulation Spectroscopy.
ACS sensors
Jan 15, 2025
Natural gas (NG) is a promising alternative to diesel for sustainable transport, potentially reducing GHG and air quality emissions significantly. However, the GHG benefits hinge on managing methane slip, the unburned methane in the exhaust of NG eng...
Classification of soil contamination by heavy metals (Cr, Ni, Pb, Zn) in wildfire-affected areas using laser-induced breakdown spectroscopy and machine learning.
Environmental science and pollution research international
Jan 8, 2025
The assessment of soil contamination by heavy metals is of high importance due to its impact on the environment and human health. Standard high-sensitivity spectroscopic techniques for this task such as atomic absorption spectrometry (AAS) and induct...
Non-invasive screening for laryngeal cancer using the oral cavity as a proxy for differentiation of laryngeal cancer versus leukoplakia: A novel application of ESS technology and artificial intelligence supported statistical modeling.
American journal of otolaryngology
Dec 24, 2024
OBJECTIVE: This preliminary study tested whether non-invasive, remote Elastic Scattering Spectroscopy (ESS) measurements obtained in the oral cavity can be used as a proxy to accurately differentiate between patients with laryngeal cancer versus lary...
A noninvasive blood glucose detection method with strong time adaptability based on fuzzy operator decision fusion and dynamic spectroscopy characteristics of PPG signals.
Analytical methods : advancing methods and applications
Dec 19, 2024
PPG signals are a new means of non-invasive detection of blood glucose, but there are still shortcomings of poor time adaptability and low prediction accuracy of blood glucose quantitative models. Few studies discuss prediction accuracy in the case o...
Integration of spectroscopic techniques and machine learning for optimizing Phaeodactylum tricornutum cell and fucoxanthin productivity.
Bioresource technology
Dec 16, 2024
The development of sustainable and controlled microalgae bioprocesses relies on robust and rapid monitoring tools that facilitate continuous process optimization, ensuring high productivity and minimizing response times. In this work, we analyse the ...
Detecting Collagen by Machine Learning Improved Photoacoustic Spectral Analysis for Breast Cancer Diagnostics: Feasibility Studies With Murine Models.
Journal of biophotonics
Nov 26, 2024
Collagen, a key structural component of the extracellular matrix, undergoes significant remodeling during carcinogenesis. However, the important role of collagen levels in breast cancer diagnostics still lacks effective in vivo detection techniques t...
Stacked Ensemble with Machine Learning Regressors on Optimal Features (SMOF) of hyperspectral sensor PRISMA for inland water turbidity prediction.
Environmental science and pollution research international
Nov 25, 2024
Leveraging hyperspectral data across various domains yields substantial benefits, yet managing many spectral bands and identifying the essential ones poses a formidable challenge. This study identifies the most relevant bands within a hyperspectral d...
Insights into the characteristics and toxicity of microalgal biochar-derived dissolved organic matter by spectroscopy and machine learning.
The Science of the total environment
Nov 20, 2024
Microalgal biochar has potential applications in various fields; however, there is limited research on the properties and risks of microalgal biochar-derived dissolved organic matter (MBDOM). This study examined how different pyrolysis temperatures (...
Microfluidic Optical Aptasensor for Small Molecules Based on Analyte-Tuned Growth of Gold Nanoseeds and Machine Learning-Enhanced Spectrum Analysis: Rapid Detection of Mycotoxins.
ACS sensors
Nov 7, 2024
Natural toxins, mainly small molecules, are a category of chemical hazards in agri-food systems that pose threats to both public health and food security. Current standard methods for monitoring these toxins, predominantly based on liquid chromatogra...
Towards high-performance deep learning architecture and hardware accelerator design for robust analysis in diffuse correlation spectroscopy.
Computer methods and programs in biomedicine
Oct 28, 2024
This study proposes a compact deep learning (DL) architecture and a highly parallelized computing hardware platform to reconstruct the blood flow index (BFi) in diffuse correlation spectroscopy (DCS). We leveraged a rigorous analytical model to gener...
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