• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.2
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• pp.89-97
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• 2012

This study was conducted to estimate forest site productivity and productive areas of Quercus acutissima and Quercus mongolica using environmental factors including climatic variables. Using the data set from digital forest site map and forest climatic map, a total of 42 environmental variables were regressed on site index for developing the best site index equations for Quercus acutissima and Quercus mongolica. Five to six environmental factors by species were selected as independent variables in the best site index equations. For the site index equations, three evaluation statistics (i.e., mean difference, standard deviation of difference, and standard error of difference) were applied to the test data set for the validation of the results, The site index equations fitted well to the test data set with relatively low bias and variation. As a result, it was concluded that the site index equations by species were well capable of estimating site quality. Finally, based on the site index equations, the productive areas by species were estimated by applying GIS technique to the digital forest maps. In addition, the distribution of productive areas by species was illustrated.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.8
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• pp.2043-2050
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• 2014

As most the scanning systems developed until now provide radiation scan plane images of the inspected objects, there has been a limitation in judging exactly the shape of the objects inside a logistics container exactly with only 2-D radiation image information. As a radiation image is just the density information of the scanned object, the direct application of general stereo image processing techniques is inefficient. So we propose that a new volume-based 3-D reconstruction algorithm. Experimental results show the proposed new volume based reconstruction technique can provide more efficient visualization for X-ray inspection. For validation of the proposed shape reconstruction algorithm using volume, 15 samples were scanned and reconstructed to restore the shape using an X-ray stereo inspection system. Reconstruction results of the objects show a high degree of accuracy compared to the width (2.56%), height (6.15%) and depth (7.12%) of the measured value for a real object respectively. In addition, using a K-Mean clustering algorithm a detection efficiency of 97% is achieved. The results of the reconstructed shape information using the volume based shape reconstruction algorithm provide the depth information of the inspected object with stereo X-ray inspection. Depth information used as an identifier for an automated search is possible and additional studies will proceed to retrieve an X-ray inspection system that can greatly improve the efficiency of an inspection.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.205-215
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• 2008

As static traffic assignment has reached its limitation with ITS policy applications and due to the increase of interest in studies of ITS policies since the late 1980's, dynamic traffic assignment has been considered a tool to overcome such limitations. This study used the Dynameq program, which simulates route choice behavior by macroscopic modeling and dynamic network loading and traffic flow by microscopic modeling in consideration of the feasibility of the analysis of practical traffic policy. The essence of this study is to evaluate the feasibility for analysis in practical transportation policy of using the dynamic traffic assignment technique. The study involves the verification of the values estimated from the dynamic traffic assignment with South Korea's expressway network and dynamic O/D data by comparing results with observed link traffic volumes. This study used dynamic O/D data between each toll booth, which can be accurately obtained from the highway Toll Collection System. Then, as an example of its application, exclusive bus-lane policies were analyzed with the dynamic traffic assignment model while considering hourly variations.

• Biomolecules & Therapeutics
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• v.6 no.2
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• pp.219-224
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• 1998

The bioequivalence of two clarithromvcin products was evaluated with 16 normal male volunteers (age 23-28 yr, body weight 57.5-75.517g) following single oral dose. Test product was ReYon Clarithromycin tablets (ReYon Pharm. Corp., Korea) and reference product was Klarici $d_{R}$ tablets (Abbott Korea). Both products contain 250 mg of clarithromucin. One tablet of the test or the reference product was administered to the volunteers, respectively, by randomized two period cross-over study (2$\times$2 Latin square method). The determination of clarithromycin was accomplished using a modified agar well diffusion bioassay. As a result of the assay validation, the quantification of clarithromycin in human serum by this technique was possible down to 0.03$\mu$g/ml using 100$\mu$l of serum. The coefficient of variation (C.V.) was less than 10%. Average drug concentrations at each sampling time and pharmacokinetic parameters calculated were not significantly different between two products P>0.05); the area under the curve to last sampling time (24 hr) (AU $Co_{24hr}$ (8.10$\pm$ 1.26 vs 8.22$\pm$ 1.627g . hr/ml), AUC from time zero to infinite (AU $Co_{\infty}$) (8.61 $\pm$ 1.28 vs 8.84$\pm$ 1.71 $\mu$g . hr/ml), maximum plasma concentration ( $C_{msx}$) (0.87$\pm$0.22 vs 0.88$\pm$0.19 $\mu$g/ml) and time to maximum plasma concentration ( $T_{max}$) (2.69 $\pm$0.48 vs 2.56$\pm$ 0.51 hr). The differences of mean AU $Co_{24h}$, $C_{msx}$ and $T_{msx}$ between the two products (1.44, 1.39, and 4.65%, respectively) were less than 20%. The power (1-$\beta$) and treatment difference ($\Delta$) for AU $Co_{24hr}$, and $C_{max}$ were more than 0.8 and less than 0.2, respectivly. Although the power for $T_{max}$ was under 0.8, $T_{max}$. of the two products was not significantly different each other (p>0.05). These results suggest that the bioavailability of ReYon Clarithromycin tablets is not significantly different from that of Klarici $d_{R}$ tablets. Therefore, two products are bioequivalent based on the current results. results.sults.sults.s.s.s.s.s.s.s.

• 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 Remote Sensing
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• v.20 no.5
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• pp.289-305
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• 2004

Atmospheric correction of Landsat Visible and Near Infrared imagery (VIS/NIR) over aquatic environment is more demanding than over land because the signal from the water column is small and it carries immense information about biogeochemical variables in the ocean. This paper introduces two methods, a modified dark-pixel substraction technique (path--extraction) and our spectral shape matching method (SSMM), for the correction of the atmospheric effects in the Landsat VIS/NIR imagery in relation to the retrieval of meaningful information about the ocean color, especially from Case-2 waters (Morel and Prieur, 1977) around Korean peninsula. The results of these methods are compared with the classical atmospheric correction approaches based on the 6S radiative transfer model and standard SeaWiFS atmospheric algorithm. The atmospheric correction scheme using 6S radiative transfer code assumes a standard atmosphere with constant aerosol loading and a uniform, Lambertian surface, while the path-extraction assumes that the total radiance (L/sub TOA/) of a pixel of the black ocean (referred by Antoine and Morel, 1999) in a given image is considered as the path signal, which remains constant over, at least, the sub scene of Landsat VIS/NIR imagery. The assumption of SSMM is nearly similar, but it extracts the path signal from the L/sub TOA/ by matching-up the in-situ data of water-leaving radiance, for typical clear and turbid waters, and extrapolate it to be the spatially homogeneous contribution of the scattered signal after complex interaction of light with atmospheric aerosols and Raleigh particles, and direct reflection of light on the sea surface. The overall shape and magnitude of radiance or reflectance spectra of the atmospherically corrected Landsat VIS/NIR imagery by SSMM appears to have good agreement with the in-situ spectra collected for clear and turbid waters, while path-extraction over turbid waters though often reproduces in-situ spectra, but yields significant errors for clear waters due to the invalid assumption of zero water-leaving radiance for the black ocean pixels. Because of the standard atmosphere with constant aerosols and models adopted in 6S radiative transfer code, a large error is possible between the retrieved and in-situ spectra. The efficiency of spectral shape matching has also been explored, using SeaWiFS imagery for turbid waters and compared with that of the standard SeaWiFS atmospheric correction algorithm, which falls in highly turbid waters, due to the assumption that values of water-leaving radiance in the two NIR bands are negligible to enable retrieval of aerosol reflectance in the correction of ocean color imagery. Validation suggests that accurate the retrieval of water-leaving radiance is not feasible with the invalid assumption of the classical algorithms, but is feasible with SSMM.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.97-117
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• 2021

Predicting term deposit subscriptions is one of representative financial marketing in banks, and banks can build a prediction model using various customer information. In order to improve the classification accuracy for term deposit subscriptions, many studies have been conducted based on machine learning techniques. However, even if these models can achieve satisfactory performance, utilizing them is not an easy task in the industry when their decision-making process is not adequately explained. To address this issue, this paper proposes an explainable scheme for term deposit subscription forecasting. For this, we first construct several classification models using decision tree-based ensemble learning methods, which yield excellent performance in tabular data, such as random forest, gradient boosting machine (GBM), extreme gradient boosting (XGB), and light gradient boosting machine (LightGBM). We then analyze their classification performance in depth through 10-fold cross-validation. After that, we provide the rationale for interpreting the influence of customer information and the decision-making process by applying Shapley additive explanation (SHAP), an explainable artificial intelligence technique, to the best classification model. To verify the practicality and validity of our scheme, experiments were conducted with the bank marketing dataset provided by Kaggle; we applied the SHAP to the GBM and LightGBM models, respectively, according to different dataset configurations and then performed their analysis and visualization for explainable term deposit subscriptions.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1111-1124
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• 2021

Mudflats are crucial for understanding the ecological structure and biological function of coastal ecosystem because of its high primary production by microalgae. There have been many studies on measuring primary productivity of tidal flats for the estimation of organic carbon abundance, but it is relatively recent that optical remote sensing technique, particularly hyperspectral sensing, was used for it. This study investigates hyperspectral sensing of chlorophyll concentration on a tidal flat surface, which is a key variable in deriving primary productivity. The study site is a mudflat in Geunso bay, South Korea and field campaigns were conducted at ebb tide in April and June 2021. Hyperspectral reflectance of the mudflat surfaces was measured with two types of hyperspectral sensors; TriOS RAMSES (directionalsensor) and the Specim-IQ (camera sensor), and Normal Differenced Vegetation Index (NDVI) and Contiuum Removal Depth (CRD) were used to estimate Chl-a from the optical measurements. The validation performed against independent field measurements of Chl-a showed that both CRD and NDVI can retrieve surface Chl-a with R² around 0.7 for the Chl-a range of 0~150 mg/m² tested in this study.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1149-1161
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• 2021

With a trend of the utilization of computer vision for satellite images, cloud detection using deep learning also attracts attention recently. In this study, we conducted a U-Net cloud detection modeling using SPARCS (Spatial Procedures for Automated Removal of Cloud and Shadow) Cloud Dataset with the image data augmentation and carried out 10-fold cross-validation for an objective assessment of the model. Asthe result of the blind test for 1800 datasets with 512 by 512 pixels, relatively high performance with the accuracy of 0.821, the precision of 0.847, the recall of 0.821, the F1-score of 0.831, and the IoU (Intersection over Union) of 0.723. Although 14.5% of actual cloud shadows were misclassified as land, and 19.7% of actual clouds were misidentified as land, this can be overcome by increasing the quality and quantity of label datasets. Moreover, a state-of-the-art DeepLab V3+ model and the NAS (Neural Architecture Search) optimization technique can help the cloud detection for CAS500 (Compact Advanced Satellite 500) in South Korea.

• Toxicological Research
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• v.35 no.1
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• pp.37-44
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• 2019

A major predictor of the efficacy of natural or synthetic cannabinoids is their binding affinity to the cannabinoid type I receptor ($CB_1$) in the central nervous system, as the main psychological effects of cannabinoids are achieved via binding to this receptor. Conventionally, receptor binding assays have been performed using isotopes, which are inconvenient owing to the effects of radioactivity. In the present study, the binding affinities of five cannabinoids for purified $CB_1$ were measured using a surface plasmon resonance (SPR) technique as a putative non-isotopic receptor binding assay. Results were compared with those of a radio-isotope-labeled receptor binding assay. The representative natural cannabinoid ${\Delta}^9$-tetrahydrocannabinol and four synthetic cannabinoids, JWH-015, JWH-210, RCS-4, and JWH-250, were assessed using both the SPR biosensor assay and the conventional isotopic receptor binding assay. The binding affinities of the test substances to $CB_1$ were determined to be (from highest to lowest) $9.52{\times}10^{-3}M$ (JWH-210), $6.54{\times}10^{-12}M$ (JWH-250), $1.56{\times}10^{-11}M$ (${\Delta}^9$-tetrahydrocannabinol), $2.75{\times}10^{-11}M$ (RCS-4), and $6.80{\times}10^{-11}M$ (JWH-015) using the non-isotopic method. Using the conventional isotopic receptor binding assay, the same order of affinities was observed. In conclusion, our results support the use of kinetic analysis via SPR in place of the isotopic receptor binding assay. To replace the receptor binding affinity assay with SPR techniques in routine assays, further studies for method validation will be needed in the future.