Non-destructive and rapid detection of blood quality in blood bags based on modified ACO wavelength selection algorithm

2020 ◽  
Author(s):  
Xingwei Hou ◽  
Ling Lin ◽  
Gang Li ◽  
Jing Chen
Keyword(s):  
Rapid Detection ◽  
Selection Algorithm ◽  
Wavelength Selection ◽  
Non Destructive

Microplasma synthesized gold nanoparticles for surface enhanced Raman spectroscopic detection of methylene blue

2021 ◽  
Author(s):  
Xuanhe Li ◽  
Liangliang Lin ◽  
Wei-Hung Chiang ◽  
Kuan Chang ◽  
Hujun Xu
Keyword(s):  
Rapid Detection ◽  
Chemical Species ◽  
Spectroscopic Technique ◽  
Trace Level ◽  
Raman Spectroscopic ◽  
Non Invasive ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Enhanced Raman Scattering ◽  
Non Destructive

Surface enhanced Raman scattering (SERS) is a powerful and sensitive spectroscopic technique that allows for rapid detection of trace-level chemical species in a non-invasive and non-destructive manner. In the present...

Rapid detection of metal impurities on the surfaces of intact objects with irregular shapes using electrochemical mass spectrometry

The Analyst ◽  
2019 ◽  
Vol 144 (11) ◽  
pp. 3505-3510 ◽  
Author(s):  
Lili Song ◽  
Jiaquan Xu ◽  
Dacai Zhong ◽  
Konstantin Chingin ◽  
Ying Qu ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Rapid Detection ◽  
Spectrometry Method ◽  
Mass Spectrometry Method ◽  
Metal Impurities ◽  
Irregular Shapes ◽  
Non Destructive

An electrochemical mass spectrometry method was developed for the rapid and non-destructive detection of metal impurities on irregular intact objects.

New Near Infrared Wavelength Selection Algorithm Based on Monte-Carlo Method

2010 ◽  
Vol 30 (12) ◽  
pp. 3637-3642 ◽  
Author(s):  
洪明坚 Hong Mingjian ◽  
温泉 Wen Quan ◽  
温志渝 Wen Zhiyu
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Near Infrared ◽  
Selection Algorithm ◽  
Wavelength Selection ◽  
Infrared Wavelength

Non-destructive and rapid detection of the internal chemical composition of granules samples by spectral transfer

2021 ◽  
Vol 208 ◽  
pp. 104174
Author(s):  
Yachao Liu ◽  
Yongyu Li ◽  
Yankun Peng ◽  
Shuai Yan ◽  
Xinlong Zhao ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Rapid Detection ◽  
Non Destructive

Peak-hopping stepwise wavelength selection algorithm

1999 ◽  
Author(s):  
Michael J. McShane ◽  
Brent D. Cameron ◽  
Gerard L. Cote ◽  
Clifford H. Spiegelman
Keyword(s):  
Selection Algorithm ◽  
Wavelength Selection

Flexible Ag SERS substrate for non-destructive and rapid detection of toxic materials on irregular surface

2021 ◽  
Vol 23 ◽  
pp. 100995
Author(s):  
Xueyan Bian ◽  
Jiangtao Xu ◽  
Jing Yang ◽  
Ka-lam Chiu ◽  
Shouxiang Jiang
Keyword(s):  
Rapid Detection ◽  
Sers Substrate ◽  
Irregular Surface ◽  
Toxic Materials ◽  
Non Destructive

Hyperspectral Imaging for Tomato Bruising Damage Assessment of Simulated Harvesting Process Impact Using Wavelength Interval Selection and Multivariate Analysis

2020 ◽  
Vol 36 (4) ◽  
pp. 533-547
Author(s):  
Jinshi Cui ◽  
Myongkyoon Yang ◽  
Daesik Son ◽  
Seong-In Cho ◽  
Ghiseok Kim
Keyword(s):  
Multivariate Analysis ◽  
Hyperspectral Imaging ◽  
Imaging System ◽  
Classification Model ◽  
Fast Method ◽  
Wavelength Selection ◽  
Internal Damage ◽  
Discrimination Analysis ◽  
Interval Selection ◽  
Non Destructive

Highlights The hidden internal damage of falling impact on tomatoes will reduce the quality of products. Hyperspectral imaging and VIS/NIR spectrum analysis, including wavelength selection and classification model construction, have the possibility as a non-destructive and fast method to predict the effect of drop impact grades on tomato bruising damage. Abstract . Mechanical damage usually causes hidden internal damage to tomatoes (Solanum lycopersicum L.), which can reduce the product quality and can cause economic losses to farmers. The visible and near-infrared (VIS/NIR) spectra of tomato fruits were analyzed by using the wavelength selection algorithm (the combination of ant colony optimization and variable importance in projection), and the influence of impact grades of simulated transport on tomato fruit bruising was evaluated. A VIS/NIR hyperspectral imaging system was developed to capture hyperspectral images of tomatoes from 392–1034 nm spectral region and the part used in actual data analysis was 442-984 nm. Multivariate analysis classifier models (partial least squares discrimination analysis and ANN) were set up based on the original spectral dataset. On the basis of selected wavelength intervals, multivariate analysis classifier models were re-established. The overall classification accuracies of all models in the validation set are good, ranging from 64.29% to 100%. Especially in the two types of classification (bruising and normal), the range of correct accuracy is 89.29% to 100%, which shows very high predicted performance. The prediction performance of the model based on the selected wavelengths decreases slightly, but the prediction time is shortened by more than 70%. The results demonstrated that hyperspectral imaging and VIS/NIR spectrum analysis, including wavelength selection and classification model construction, have the possibility as a non-destructive and fast method to predict the effect of drop impact grades on tomato bruising damage. Keywords: ANN, Ant colony optimization (ACO), Partial least squares discrimination analysis (PLS-DA), Variable importance in projection (VIP), VIS/NIR hyperspectral imaging system, wavelength interval selection.

scholarly journals Optimal wavelength selection algorithm of non-spherical particle size distribution based on the light extinction data

2012 ◽  
Vol 16 (5) ◽  
pp. 1353-1357 ◽  
Author(s):  
Hong Tang
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Approximation Method ◽  
Spherical Particles ◽  
Selection Algorithm ◽  
Wavelength Selection ◽  
Anomalous Diffraction ◽  
Optimal Wavelength ◽  
Anomalous Diffraction Approximation

In this paper, the anomalous diffraction approximation method is improved for calculating the extinction efficiency of non-spherical particles. Through this step, the range of the refractive index of particles can be enlarged, and the improved anomalous diffraction approximation method can be applied easily to the calculation of extinction efficiency for the most kinds of non-spherical particles. Meanwhile, an optimal wavelength selection algorithm is proposed for the inversion of non-spherical particle size distribution in the dependent mode. Through the improved anomalous diffraction approximation method, the computation time is substantially reduced compared with the rigorous methods, and a more accurate inversion result of particle size distribution is obtained using the optimal wavelength selection method.

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