• Journal of Sensor Science and Technology
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• v.17 no.2
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• pp.120-126
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• 2008

Glucose concentrations in the interstitial fluid were measured based on optical spectroscopy. Prediction of glucose concentrations was made using partial least squares regression and accuracy improvement was achieved by data preprocessing as well as by selecting an optimal wavelength region. For this purpose, artificial interstitial fluid samples were prepared where their glucose levels varied between 0 and 10 g/dl. Infrared spectral regions where glucose absorption lies were investigated. A region of 1000 - 1500 $cm^{-1}$ produced the best accuracy among the regions of 1000 - 1500 $cm^{-1}$, 4000 - 4545 $cm^{-1}$1 and 5500 - 6500 $cm^{-1}$. Further accuracy improvement in 1000 - 1500 $cm^{-1}$ was achieved by selecting specific wavelength bands based on a loading vector analysis method. For the samples whose glucose concentrations ranged between 0 and 0.5 g/dl, SEP= 0.0266 g/dl and R =0.9863 were achieved with 1000 - 1500 $cm^{-1}$. However, the loading vector optimized band of 1002 - 1095 $cm^{-1}$ reduced the prediction error up to 47 % (SEP =0.0125 g/dl and R=0.9970).

• The Korean Journal of Food And Nutrition
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• v.29 no.5
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• pp.605-609
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• 2016

This study aimed to find the optimum instrumental test conditions for the Texture Profile Analysis (TPA) of cooked rice in order to predict the sensory texture attributes (hardness, adhesiveness, chewiness). Sensory evaluation was performed for three kinds of instant cooked rice with university students in their twenties and the results of the sensory evaluation were compared to instrumental TPA patterns. Using partial least squares regression, the instrumental TPA results at a cross-head speed of 1.0 mm/sec and a compression ratio of 70% proved to be an excellent predictor of the sensory attributes of hardness ($R^2=0.99$) and chewiness ($R^2=0.99$). The results at a cross-head speed of 0.5 mm/sec and compression ratio of 30% provided an excellent model for the prediction of sensory adhesiveness ($R^2=0.83$). In this experimental range, sensory hardness and chewiness showed a high correlation with instrumental TPA parameters (hardness, cohesiveness, adhesiveness, springiness, chewiness) with a high cross-head speed and compression ratio, while sensory adhesiveness showed a high correlation with the TPA parameters with a low cross-head speed and compression ratio.

• YAKHAK HOEJI
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• v.47 no.3
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• pp.148-153
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• 2003

Skin moisture is an important factor in skin health. Measurement of moisture content can provide diagnostic information on the condition of skin. In this study, a portable near-infrared (NIR) system was newly integrated with a photo diode array detector that has no moving parts, and this system has been successfully applied for the evaluation of human skin moisture. Diffuse reflectance spectra were collected and transformed to absorbance using 1 nm step size over the wavelength range of 1100 nm to 2200 nm. Partial least squares regression (PLSR) was applied to develop a calibration model. For practical use for the evaluation of human skin moisture, the PLS model for human skin moisture was developed in vivo using the portable NIR system on the basis of the relative water content values of stratum corneum from the conventional capacitance method. The PLS model showed a good correlation. The calibration with the use of PLS model predicted human moisture with a standard error of prediction (SEP) of 3.5 at 1120∼1730 nm range. This study showed the possibility of skin moisture measurement using portable NIR system.

• Journal of the Ergonomics Society of Korea
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• v.19 no.3
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• pp.23-37
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• 2000

Usability is one of the most important factors that affect customers' decision to purchase a product. Several studies have been conducted to model the relationship between the product design variables and the product usability. Since there could be hundreds of design variables to be considered in the model, a variable screening method is required. Traditional variable screening methods are based on expert opinions (Expert screening) in most Kansei engineering studies. Suggested in this study are statistical methods for screening important design variables by using the principal component regression(PCR), cluster analysis, and partial least squares(PLS) method. Product variables with high effect (PCR screening and PLS screening) or representative variables (Cluster screening) can be used to model the usability. Proposed variable screening methods are used to model the usability for 36 audio/visual products. The three analysis methods (PCR, Cluster, and PLS) show better model performance than the Expert screening in terms of $R^2$, the number of variables in the model, and PRESS. It is expected that these methods can be used for screening the product design variables efficiently.

• YAKHAK HOEJI
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• v.49 no.2
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• pp.115-121
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• 2005

In this study, the performance of a portable NIR system and a FT NIR spectrometer were compared to determine water content of hairless mouse skin. The stratum corneum parts wer e separated from the epidermal tissues by trypsin solution. NIR diffuse reflectance spectra of hairless mouse skin were acquired using a fiber optic probe. In the near infrared, water molecules show two clear absorption bands at 1450 nm from first overtone of O-H stretching and 1940 nm from the combination involving O-H stretching and O-H deformation. It was found that the variations of O-H absorption band according to water content. Partial least squares regression (PLSR) was applied to develop a calibration model. The PLS model showed a good correlation between NIR predicted value and the absolute water content of separated hairless mouse skin, in vitro. For both the portable and the FT NIR spectrometer, These studies showed the possibility of a rapid and nondestructive skin moisture measurement using NIR spectroscopy. The portable NIR spectrometer with a photodiode arrays-microsensor could be more rapidly applied for the determination of water content with comparable accuracy with the performance of a FT spectrometer .

• Journal of Environmental Science International
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• v.29 no.5
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• pp.445-455
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• 2020

Fine dust is one of the most critical environmental issues in Korea, and the government recognizes the need to establish customized reduction policies based on regional characteristics. Several studies on air pollutants investigate whether factories affect the distribution of fine dust in a particular region. However, understanding the impact of the entire industry sector requires further investigation. This study identifies the impacts of industrial characteristics on fine dust levels of 141 municipalities across Korea in 2016. A total of 23 variables were used, of which 12 referred to industries and 11 to general characteristics of each city. Due to the high correlation between independent variables, partial least squares (PLS) regression models were used. The analysis identified 14 significant variables for PM10 and 13 for PM2.5. Therefore, the results suggest that local industrial characteristics can significantly influence fine dust levels and provide suggestions for establishing customized reduction policies based on local characteristics.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.44-44
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• 2017

The objective of this study was to evaluate firmness, and sweetness index (SI) of tomatoes (Lycopersicum esculentum) by using hyperspectral imaging (HSI) in the range of 1000-1400 nm. The mean spectra of the 95 matured tomato samples were extracted from the hyperspectral images, and the reference firmness and sweetness index of the same sample were measured and calibrated with their corresponding spectral data by partial least squares (PLS) regression with different preprocessing method. The results showed that the regression model developed by PLS regression based on Savitzky-Golay (S-G) second-derivative preprocessed spectra resulted in better performance for firmness, and SI of tomatoes compared to models developed by other preprocessing methods, with correlation coefficients (rpred) of 0.82, and 0.74 with standard error of prediction (SEP) of 0.86 N, and 0.63 respectively. Then, the feature wavelengths were identified using model-based variable selection method, i.e., variable important in projection (VIP), resulting from the PLS regression analyses and finally chemical images were derived by applying the respective regression coefficient on the spectral image in a pixel-wise manner. The resulting chemical images provided detailed information on firmness, and sweetness index (SI) of tomatoes. Therefore, these research demonstrated that HIS technique has a potential for rapid and non-destructive evaluation of the firmness and sweetness index of tomatoes.

• Bulletin of the Korean Chemical Society
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• v.20 no.2
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• pp.159-162
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• 1999

Three different chemical compositions of total paraffin, total naphthene, total aromatic content in naphtha have been successfully analyzed using FT-Raman spectroscopy. Partial least squares (PLS) regression has been utilized to develop calibration models for each composition from Raman spectral bands. The PLS calibration results showed Blood correlation with those of gas chromatography (GC). Using PLS regression, the spectral information related to each composition has been successfully extracted from highly overlapped Raman spectra of naphtha.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6347-6350
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• 2013

Post-transplant lymphoproliferative disorder (PTLD) is a common complication of therapeutic immunosuppression after organ transplantation. Gene expression profile facilitates the identification of biological difference between Epstein-Barr virus (EBV) positive and negative PTLDs. Previous studies mainly implemented variance/regression analysis without considering unaccounted array specific factors. The aim of this study is to investigate the gene expression difference between EBV positive and negative PTLDs through partial least squares (PLS) based analysis. With a microarray data set from the Gene Expression Omnibus database, we performed PLS based analysis. We acquired 1188 differentially expressed genes. Pathway and Gene Ontology enrichment analysis identified significantly over-representation of dysregulated genes in immune response and cancer related biological processes. Network analysis identified three hub genes with degrees higher than 15, including CREBBP, ATXN1, and PML. Proteins encoded by CREBBP and PML have been reported to be interact with EBV before. Our findings shed light on expression distinction of EBV positive and negative PTLDs with the hope to offer theoretical support for future therapeutic study.

• Korean Journal of Agricultural Science
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• v.45 no.4
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• pp.823-837
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• 2018

The objective of this study was to evaluate the firmness and the sweetness index (SI) of tomatoes with a hyperspectral imaging (HSI) technique within the wavelength range of 1000 - 1550 nm. The hyperspectral images of 95 tomatoes were acquired with a push-broom hyperspectral reflectance imaging system, from which the mean spectra of each tomato were extracted from the regions of interest. The reference firmness and sweetness index of the same sample was measured and calibrated with their corresponding spectral data by partial least squares (PLS) regression with different preprocessing methods. The calibration model developed by PLS regression based on the Savitzky-Golay second-derivative preprocessed spectra resulted in a better performance for both the firmness and the SI of the tomatoes compared to models developed by other preprocessing methods. The correlation coefficients ($R_{pred}$) were 0.82, and 0.74 with a standard error of prediction of 0.86 N, and 0.63, respectively. Then, the feature wavelengths were identified using a model-based variable selection method, i.e., variable importance in projection, from the PLS regression analyses. Finally, chemical images were derived by applying the respective regression coefficients on the spectral image in a pixel-wise manner. The resulting chemical images provided detailed information on the firmness and the SI of the tomatoes. The results show that the proposed HSI technique has potential for rapid and non-destructive evaluation of firmness and the sweetness index of tomatoes.