• Journal of the Korean Geotechnical Society
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• v.32 no.5
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• pp.15-26
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• 2016

Dam and embankment are very important civil structures. Grouting is widely used to repair and maintain dam and embankment, and it is important to evaluate the effect of grouting for dam safety. The non-destructive method based on determination of wave velocity in the dam or embankment is effectively used to evaluate grouting effect because wave velocity is identical with stiffness and grouting increases local stiffness in a dam. In this paper, HWAW (Harmonic wavelet analysis of waves) method was applied to evaluate the grouting effect. HWAW method can determine two-dimensional shear wave velocity map with good spatial resolution and the shear velocity profile by the proposed method is sensitive to a variation of stiffness of target system. Through numerical simulation and field tests, the applicability of HWAW method in determining grouting effect is shown.

• International Journal of Highway Engineering
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• v.11 no.1
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• pp.95-104
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• 2009

This study was conducted to evaluate the relationship between the dielectric constant and air void of asphalt concrete. Standard specimens that have air voids of various range $(0%{\sim}20%)$ were used to measure the dielectric constant using parallel plate method that measures low frequency dielectric constant. From the tests, dielectric constant of asphalt concrete was tend to decrease as the frequency was increased, and the decrement slope was varied with the types of asphalt binders. Dielectric constant was decreased linearly as air void was increased from zero to twenty percent. Consequently, the effect of temperature and moisture content on dielectric constants of asphalt concrete was evaluated to develop the standard curve between dielectric constant and air void of asphalt concrete. The standard curve developed in this study can be used to calibrate or develop the algorithm of non-destructive density gauge.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.spc1
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• pp.283-291
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• 2006

To investigate seed non destructive and fast determination technique utilizing near infrared reflectance spectroscopy (NIRs) for screening ultra high oleic (C18:1) and linoleic (C18:2) fatty acid content sesame varieties among genetic resources and lines of pedigree generations of cross and mutation breeding were carried out in National Institute of Crop Science (NICS). 150 among 378 landraces and introduced cultivars were released to analyse fatty acids by NIRs and gas chromatography (GC). Average content of each fatty acid was 9.64% in palmitic acid (C16:0), 4.73% in stearic acid (C18:0), 42.26% in oleic acid and 43.38% in linoleic acid by GC. The content range of each fatty acid was from 7.29 to 12.27% in palmitic, 6.49% from 2.39 to 8.88% in stearic, 12.59% of wider range compared to that of stearic and palmitic from 37.36 to 49.95% in oleic and of the widest from 30.60 to 47.40% in linoleic acid. Spectrums analyzed by NIRs were distributed from 400 to 2,500 nm wavelengths and varietal distribution of fatty acids were appeared as regular distribution. Varietal differences of oleic acid content good for food processing and human health by NIRs was 14.08% of which 1.49% wider range than that of GC from 38.31 to 52.39%. Varietal differences of linoleic acid content by NIRs was 16.41% of which 0.39% narrower range than that of GC from 30.60 to 47.01%. Varietal differences of oleic and linoleic acid content in NIRs analysis were appeared relatively similar inclination compared with those of GC. Partial least square regression (PLSR) among multiple variant regression (MVR) in NIRs calibration statistics was carried out in spectrum characteristics on the wavelength from 700 to 2,500 nm with oleic and linoleic acids. Correlation coefficient of root square (RSQ) in oleic acid content was 0.724 of which 72.4 percent of sample varieties among all distributed in the range of 0.570 percent of standard error when calibrated (SEC) which were considerably acceptable in statistic confidence significantly for analysis between NIRs and GC. Standard error of cross validation (SECV) of oleic acid was 0.725 of which distributed in the range of 0.725 percent standard error among the samples of mother population between analyzed value by NIRs analysis and analyzed value by GC. RSQ of linoleic acid content was 0.735 of which 73.5 percent of sample varieties among all distributed in the range of 0.643 percent of SEC. SECV of linoleic acid was 0.711 of which distributed in the range of 0.711 percent standard error among the samples of mother population between NIRs analysis and GC analysis. Consequently, adoption NIR analysis for fatty acids of oleic and linoleic instead that of GC was recognized statistically significant between NIRs and GC analysis through not only majority of samples distributed in the range of negligible SEC but also SECV. For enlarging and increasing statistic significance of NIRs analysis, wider range of fatty acids contented sesame germplasm should be kept on releasing additionally for increasing correlation coefficient of RSQ and reducing SEC and SECV in the future.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.669-681
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• 2023

Studies have tried to apply remote sensing technology, a non-destructive survey method, instead of the existing destructive survey, which requires relatively large labor input and a long time to estimate chlorophyll content, which is an important indicator for evaluating the growth of fruit trees. This study was conducted to non-destructively evaluate the chlorophyll content of pear tree leaves using unmanned aerial vehicle-based hyperspectral imagery for two years(2021, 2022). The reflectance of the single bands of the pear tree canopy extracted through image processing was band rationed to minimize unstable radiation effects depending on time changes. The estimation (calibration and validation) models were developed using machine learning algorithms of elastic-net, k-nearest neighbors(KNN), and support vector machine with band ratios as input variables. By comparing the performance of estimation models based on full band ratios, key band ratios that are advantageous for reducing computational costs and improving reproducibility were selected. As a result, for all machine learning models, when calibration of coefficient of determination (R²)≥0.67, root mean squared error (RMSE)≤1.22 ㎍/cm², relative error (RE)≤17.9% and validation of R²≥0.56, RMSE≤1.41 ㎍/cm², RE≤20.7% using full band ratios were compared, four key band ratios were selected. There was relatively no significant difference in validation performance between machine learning models. Therefore, the KNN model with the highest calibration performance was used as the standard, and its key band ratios were 710/714, 718/722, 754/758, and 758/762 nm. The performance of calibration showed R²=0.80, RMSE=0.94 ㎍/cm², RE=13.9%, and validation showed R²=0.57, RMSE=1.40 ㎍/cm², RE=20.5%. Although the performance results based on validation were not sufficient to estimate the chlorophyll content of pear tree leaves, it is meaningful that key band ratios were selected as a standard for future research. To improve estimation performance, it is necessary to continuously secure additional datasets and improve the estimation model by reproducing it in actual orchards. In future research, it is necessary to continuously secure additional datasets to improve estimation performance, verify the reliability of the selected key band ratios, and upgrade the estimation model to be reproducible in actual orchards.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1522-1522
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• 2001

Beverages based on fruit juices are among the most popular commercially available drinks. There is an ever-increasing demand for these juices in the market. Orange juice is one of the most common as well as most favorite flavor. The fruit processing industries have a tremendous responsibility of quality control. For quality evaluation estimation of various components of the juice is necessary. Sucrose, glucose, fructose, citric acid and malic acid are the prime components of orange juice. Little information is available on analysis of orange juice. However, conventional and general wet chemistry procedures are currently being used which are no longer desired by the industry owing to the time involved, labor input and harmful chemicals required for each analysis. Need to replace these techniques with new, highly specific and automated sophisticated techniques viz. HPLC and spectroscopy has been realized since long time. Potential of Near Infrared Spectroscopy in quantitative analysis of different components of food samples has also been well established. A rapid, non-destructive and accurate technique based on Near Infrared Spectroscopy for determination of sugars and organic acids in orange juice will be highly useful. The current study is an investigation into the potential of Near Infrared Diffuse Reflectance Spectroscopy for rapid quantitative analysis of sucrose, glucose, fructose citric acid and malic acid in orange juice. All the Near Infrared measurements were peformed on a dispersive NIR spectrophotometer (ELICO 153) in diffuse reflectance mode. The spectral region from 1100 to 2500nm has been explored. The calibration has been performed on synthetic samples that are mixtures of sucrose, glucose, fructose, citric acid and malic acid in different concentration ranges typically encountered real orange juice. These synthetic samples are therefore considered to be representatives of natural juices. All the Near Infrared spectra of synthetic samples were subjected to mathematical analysis using Partial Least Square (PLS) algorithm. After the validation, calibration was applied to commercially available real samples and freshly squeezed natural juice samples. The actual concentrations were compared with those predicted from calibration curve. A good correlation is obtained between actual and predicted values as indicated by correlation coefficient ($R^2$) value, which is close to unity, showing the feasibility of the technique.

• Journal of Radiation Protection and Research
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• v.22 no.4
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• pp.309-317
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• 1997

The measured radioactivity of gamma-emitting radionuclides in each radioactive waste drum using the non-destructive waste assay method is underestimated than real radioactivity in radioactive waste drum because the gamma-rays are attenuated within the medium. Therefore, the measured radioactivity should be corrected for the attenuation of gamma-rays. For the correction of the attenuation of gamma-rays, the attenuation correction method should be applied differently by considering the distribution and density of medium in radioactive wastes drum generated from nuclear power plants. In this study, the model drums were fabricated for simulating five types of radioactive waste drums generated from nuclear power plant and the optimum methods of the attenuation correction were experimentally determined to analyze the activity of radionuclides in the waste drum accurately using the segmented gamma scanning system. With the determination of the attenuation correction methods from the experimental results the transmission method and the average density method for the miscellaneous waste drum, the transmission method and the differential peak absorption method for the shielded miscellaneous waste drum were used to measure the density of medium in waste drums. Also, the average density method and the differential peak absorption method for the spent resin drum, the paraffin solidified drum, and the spent filter drum were used.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.1
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• pp.61-66
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• 2022

Sesamin and sesamolin are major lignan components with a wide range of potential biological activities of sesame seeds. Near infrared reflectance spectroscopy (NIRS) is a rapid and non-destructive analysis method widely used for the quantitative determination of major components in many agricultural products. This study was conducted to develop a screening method to determine the lignan contents for sesame breeding. Sesamin and sesamolin contents of 482 sesame samples ranged from 0.03-14.40 mg/g and 0.10-3.79 mg/g with an average of 4.93 mg/g and 1.74 mg/g, respectively. Each sample was scanned using NIRS and calculated for the calibration and validation equations. The optimal performance calibration model was obtained from the original spectra using partial least squares (PLS). The coefficient of determination in calibration (R²) and standard error of calibration (SEC) were 0.963 and 0.861 for sesamin and 0.875 and 0.292 for sesamolin, respectively. Cross-validation results of the NIRS equation showed an R² of 0.889 in the prediction for sesamin and 0.781 for sesamolin and a standard error of cross-validation (SECV) of 1.163 for sesamin and 0.417 for sesamolin. The results showed that the NIRS equation for sesamin and sesamolin could be effective in selecting high lignan sesame lines in early generations of sesame breeding.

• Journal of Food Hygiene and Safety
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• v.21 no.4
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• pp.204-212
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• 2006

This study was conducted to investigate the possibility of rapid and non-des tructive evalution of AV (Acid Value), IV (Iodine Value) and fatty acids in sesame oils. The samples were scanned over the range $400\sim2500nm$ using transmittance spectrum of NIRS(Near-infrared spectroscopy). A calibration equation calculated by MPLS regression technique was developed and correlation coefficient of determination for AV, IV, palmitic acid, stearic acid, linoleic acid and linolenic acid content were 0.9907, 0.9677, 0.9527, 0.9210, 0.9829, 0.9736 and 0.9709 respectively. The validation model for measuring the AV content had R of 0.989, SEP of 0.058 and IV content had R of 0.944, SEP of 0.562 and palmitic acid content had R of 0.924, SEP of 0.194 and stearic acid content had R of 0.717, SEP of 0.168 and oleic acid content had R of 0.989, SEP of 0.221 and linoleic acid content had R of 0.967, SEP of 0.297 and linolenic acid content had R of 0.853, SEP of 0.480 by MPLS. The obtained results indicate that the NIRS procedure can potentially be used as a non-destructive analysis method for the purpose of rapid and simple measurement of AV, IV and fatty acids in sesame oils.

• Korean Journal of Agricultural Science
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• v.48 no.2
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• pp.299-310
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• 2021

Glycerol is a non-volatile compound with no aromatic properties that contributes significantly to the quality of wine by providing sweetness and richness of taste. In addition, it is also the third most significant byproduct of alcoholic fermentation in terms of quantity after ethanol and carbon dioxide. In this study, Fourier transform infrared (FT-IR) spectroscopy was employed as a fast non-destructive method in conjugation with multivariate regression analysis to build a model for the quantitative analysis of glycerol concentration in wine samples. The samples were prepared by using three varieties of red wine samples (i.e., Shiraz, Merlot, and Barbaresco) that were adulterated with glycerol in concentration ranges from 0.1 to 15% (v·v^-1), and subjected to analysis together with pure wine samples. A net analyte signal (NAS)-based methodology, called hybrid linear analysis in the literature (HLA/GO), was applied for predicting glycerol concentrations in the collected FT-IR spectral data. Calibration and validation sets were designed to evaluate the performance of the multivariate method. The obtained results exhibited a high coefficient of determination (R²) of 0.987 and a low root mean square error (RMSE) of 0.563% for the calibration set, and a R² of 0.984 and a RMSE of 0.626% for the validation set. Further, the model was validated in terms of sensitivity, selectivity, and limits of detection and quantification, and the results confirmed that this model can be used in most applications, as well as for quality assurance.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.29 no.2
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• pp.423-433
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• 1999

Purpose : To assess the methods for the clinical evaluation of the longitudinal bone changes after implantation of tooth ash-plaster mixture into the defect area of human jaws. Materials and methods : Tooth ash-plaster mixtures were implanted into the defects of 8 human jaws. 48 intraoral radiograms taken with copper step wedge as reference at soon, 1st, 2nd, 4th, and 6th week after implantation of mixture were used. X-ray taking was standardized by using Rinn XCP device customized directly to the individual dentition with resin bite block. The images inputted by Quick scanner were digitized and analyzed by NIH image program. Cu­equivalent values were measured at the implanted sites from the periodic digital images. Analysis was performed by the bidirectional subtraction with color enhancement and the surface plot of resliced contiguous image. The obtained results by the two methods were compared with Cu­equivalent value changes. Results : The average determination coefficient of Cu-equivalent equations was 0.9988 and the coefficient of variation of measured Cu values ranged from 0.08~0.10. The coefficient of variation of Cu-equivalent values measured at the areas of the mixture and the bone by the conversion equation ranged from 0.06 ~0.09. The analyzed results by the bidirectional subtraction with color enhancement were coincident with the changes of Cu-equivalent values. The surface plot of the resliced contiguous image showed the three dimensional view of the longitudinal bone changes on one image and also coincident with Cu-equivalent value changes after implantation. Conclusion : The bidirectional subtraction with color enhancement and the surface plot of the resliced contiguous image was very effective and reasonable to analyze clinically and qualitatively the longitudinal bone change. These methods are expected to be applicable to the non-destructive test in other fields.