AIMC Topic: Spectroscopy, Near-Infrared

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Transfer learning for non-invasive glucose prediction under albumin interference in NIR spectroscopy.

Computers in biology and medicine
This study proposes a transfer learning framework for non-invasive glucose prediction using diffuse-reflectance near-infrared (NIR) spectroscopy, along with an in vitro phantom model that incorporates a pump-driven circulation system. Lipofundin and ...

Functional near-infrared spectroscopy for the detection of fear using parameterized quantum circuits.

Scientific reports
Excessive fear in response to certain stimuli may be a key indicator of anxiety disorders. Its detection makes it valuable for the diagnosis and treatment of such pathologies. Quantum computing has shown promising results in processing different type...

Development of a rapid detection method for patch thickness based on machine vision and near infrared spectroscopy: a case study of curcumin patch.

International journal of pharmaceutics
Patches represent a significant dosage form within transdermal drug delivery systems. In the quality control of transdermal patches, thickness not only affects the drug loading per unit area and drug release behavior but also is associated with patie...

CABNas-nir: A near-infrared classification for urban pipe network sludge on the fusion algorithm of NAS framework and active learning.

PloS one
Pipe network sludge is a complex pollutant aggregate deposited during long-term operation of urban sewage pipelines, and a key target for pollution control in environmental monitoring systems. Accurate source classification is critical for treatment ...

Improving nitrogen use efficiency in rice by estimating leaf nitrogen content with near-infrared spectroscopy and chemometric modeling.

Scientific reports
Accurate nitrogen management in rice (Oryza sativa L.) is essential for optimizing both crop productivity and environmental sustainability. This study evaluated the potential of Near-Infrared Spectroscopy (NIRS) combined with chemometric modeling to ...

From root to result: Portable NIRS-based non-destructive prediction of cassava quality traits.

PloS one
Cassava (Manihot esculenta Crantz) is a staple food and a key industrial crop across tropical regions, but traditional phenotyping for critical quality traits like dry matter content (DMC) and starch content (StC) is a laborious and low-throughput pr...

HAttFFNN: Hybridized attention mechanism-based feedforward neural network deep learning model for the plastic material classification of three stage materials on spectroscopic data.

PloS one
Classification of plastic materials based on spectroscopic data is a very crucial task in a variety of applications, including automated recycling, environmental monitoring, quality control in manufacturing, quality control of products, and analysis ...

Brain benefits of deep learning-based noise management in experienced hearing aid users using functional near infrared spectroscopy.

Scientific reports
There is growing interest in using neuroimaging to understanding listening effort in individuals with hearing loss, with a particular focus on how innovative hearing aid features impact listening effort. This study used functional near infrared spect...

The effects of combining anodal transcranial direct current stimulation with robot-assisted gait training on lower limb motor function and the motor cortex regulation of stroke patients.

Journal of neuroengineering and rehabilitation
BACKGROUND: The therapeutic effect and underlying mechanism of combining transcranial direct current stimulation (tDCS) with robot-assisted gait training (RAGT) for stroke patients remain unclear.

T10SLRE: A novel ensemble learning approach for rapid and non-destructive prediction of bread loaf volume in wheat using NIR spectroscopy.

Food chemistry
Bread loaf volume is a critical indicator of wheat processing quality, but conventional bread-making tests are laborious and time-consuming. This study evaluated near-infrared spectroscopy combined with machine learning for rapid prediction of loaf v...