• Proceedings of the PSK Conference
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• 2001.10a
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• pp.290.1-290.1
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• 2001

• The Korean Journal of Applied Statistics
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• v.31 no.2
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• pp.253-263
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• 2018

Internet addiction in adolescents is an important social issue. In this study, sparse partial least-squares regression (SPLS) was applied to internet addiction data in Korean adolescent samples. The internet addiction score and various clinical and psychopathological features were collected and analyzed from self-reported questionnaires. We considered three PLS methods and compared the performance in terms of prediction and sparsity. We found that the SPLS method with the hierarchical likelihood penalty was the best; in addition, two aggression features, AQ and BSAS, are important to discriminate and explain latent features of the SPLS model.

• Analytical Science and Technology
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• v.15 no.3
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• pp.243-247
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• 2002

A rapid and simple determination of diazepam in intact diazepam tablets has been investigated using the near infrared spectroscopy(NIRS) combined with partial least squares regession. The separate calibration curves of 2 mg and 5 mg diazepam tablets were studied, as well as the linearity, concentration range and reproducibility of those calibration curves were evaluated. The correlation coefficients of calibration curves of 2 mg and 5 mg diazepam tablets are 0.9416 and 0.9159, respectively and the standard errors of calibration curves(SEC) are 0.018% and 0.032%, respectively.

• YAKHAK HOEJI
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• v.42 no.6
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• pp.545-551
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• 1998

Near Infrared transmittance Spectroscopy (NIRS) was used to evaluate and quantify the pharmaceutical active compounds. In the paper, taurine (2-Aminoethanesulfonic acid) was quantitatively analyzed in commercial pharmaceutical preparations. For calibration a central composite factorial design was used to determine concentrations of ingredients in reference samples. For the quantitative analysis of taurine, the most suitable data analysis method includes the calculation of second derivatives and a partial least squares regression (PLSR) model. By NIR spectrometry, combined with PLSR, the taurine concentration was successfully predicted with a relative standard error of prediction (SEP) lower than 1.04%.

• Environmental Analysis Health and Toxicology
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• v.15 no.1_2
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• pp.39-43
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• 2000

Linear alkyl sulfonates (LAS) constitute a large fraction of the surfactants used in cleaning processes in households, trade and industry Despite the industrial significance and the possible environmental impact of these compounds, the fast and inexpensive determination of LAS concentrations is still a difficult task. In this study, near infrared (NIR) spectroscopy which is a rapid spectroscopic analysis method compared with a traditional analytical method for the measurement of LAS concentration such as HPLC, GC and standard wet chemistry method. NIR spectra of LAS between 0.313 and 25.0% (w/v) in water were utilized to develop a calibration model. The best results (R ＝ 0.998, SEP ＝ 0.244% (w/v)) obtained by using partial least-squares regression with spectral data treatment and 2nd derivatization were comparable to the results (SEC ＝ 0.186% (w/v), SEP ＝ 0.206% (w/v)) obtained by using multiple linear least-squares regression (MLR). However, models based on derivative spectra have no significant advantage with MLR.

• Analytical Science and Technology
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• v.15 no.2
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• pp.102-107
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• 2002

This paper describes a rapid determination of phenobarbital in intact phenobarbital tablets using partial least squares regression(PLSR) method of transmittance spectrum of near infrared (NIR) compared with the analytical data of liquid chromatograpy. The linearity, concentration range and precision of this analytical method are studied. The correlation coefficient of the calibration curve is 0.9983 and the standard error of calibration(SEC) is 0.14 %. Intra-day precision and Inter-day precision obtained in this method are CV = 0.45, CV =0.56, respectively.

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.227-239
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• 1997

PLSR is a powerful multivariate statistical tool that has been successfully applied to the quantitative analyses of data in spectroscopy, chemistry, and industrial process control. Data in spectorscopy is represented by spectrum matrix measured in many wavelengths. Problems of many kinds of noise in data and itercorrelation between wavelengths are quite common in such data. PLSR utilizes whole data set measured in many wavelengths to the analysis, and handles such problems through data compression method. We investigated the PLSR theory, and applied this method to the data for spectroscopic diagnosis of Total Hemoglobin in whole blood.

• Food Science of Animal Resources
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• v.40 no.4
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• pp.649-658
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• 2020

This study compared aroma compositions and sensory aroma attributes of raw and cooked Tenebrio molitor larvae (mealworms). Main sensory aroma attributes of raw mealworms were strong wet-soil-like, and less-intense oily, shrimp-like and sweet-corn-like. Quantitatively, the major aroma components of raw mealworms were hydrocarbons and aldehydes. As cooking proceeded, sweet-corn-like, roasted, and fried-oil-like sensory attributes were increasingly perceived with steaming, roasting, and frying, respectively. Some pyrazines, pyrrolidines, and carbonyls increased or appeared in roasted and fried mealworms. Partial least squares regression also showed differences in raw and cooked mealworms based on aroma components and their sensory attributes. Unlike raw mealworms, steamed mealworms had a relatively strong sweet-corn-like aroma attribute, which was related to 2,4,6-trimethyl-heptane, 2,4-dimethyl-dodecane, and 3,5-dihydroxy-6-methyl-2,3-dihydropyran-4-one. In comparison, roasted and fried mealworms exhibited roasted, shrimp-like, and fried-oil-like aroma attributes, which were associated with intermediates of the Maillard reaction and lipid oxidation, such as pyrazines, alcohols, and aldehydes. This result during thermal reactions was very similar to those of meat and/or seafood. The use of mealworms as a savory-type flavor enhancer can be expected.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1276-1276
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• 2001

Polycyclic aromatic hydrocarbons(PAHs) are widely distributed in the environment and are often implicated as potential carcinogens. The chromatographic methods of detection and quantitative determination of PAHs in environmental samples are costly, time consuming, and do not account for all kinds of PAHs. This work describes a quantitative spectroscopic method for the analysis of mixtures of eight PAHs using multivariate calibration models for Fourier transform near infrared(FT-NIR) spectral data. The NIR spectra of mixtures of PAHs (anthracene, pyrene, 1,2-benzanthracene, perylene, chrysene, benzo(a)pyrene, 1-methylanthracene and benzo(ghi)perylene) were measured in the wavelength range from 1100 nm to 2500 nm. The spectral data were processed using a partial least squares regression. We have studied the spectral characteristics of NIR spectra of mixtures of PAHs. It was possible to determine each PAM used in this study at the environmental level(mg L-1) in the laboratory samples. Further development may lead to the rapid determination of more PAHs in typical environmental samples.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.5
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• pp.1-6
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• 2006

The purpose of this study is to develop to portable near infrared analyzer measuring the sugar content of the fruits on a tree before harvesting ones. The portable near infrared system consists of a tungsten lamp, a coaxial optical fiber bundle and a multi-channel detector, which has 256 pixels and a concave transmission grating. Reflectance NIR spectra of orange were recorded by using a coaxial optical fiber bundle. The spectra were collected over the spectral range $400{\sim}1100nm$. Partial least squares regression(PLSR) was applied for a calibration and validation for determination of sugar contents. The multiple correlation coefficient was 0.99 and standard errors of calibration(SEC) was 0.069 brix. The calibration model predicted the sugar content for validation set with standard errors of prediction(SEP) of 0.092 brix. The sugar content in fruits was successfully quantified using the portable near infrared analyzer.