• Analytical Science and Technology
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• v.17 no.2
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• pp.130-144
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• 2004

Recently, the air pollution in A and B industrial area has become one of the most important issues, then 60 VOCs in the area were measured using a highly sensitive method. The VOCs were adsorbed onto Carbotrap using air sampler and subsequently desorbed by a thermal desorber system into gas chromatograph-mass spectrometry (TDS-GC-MS). The peaks of all compounds had good chromatographic properties and offered very sensitive response for the EI-MS (SIM). Method detection limits (MDL) ranged from 0.01 to 0.1 ppt(v/v), and linearities of calibration curves were over 0.995. We analyzed total 90 atmosphere air samples of A and B industrial complex using the method. Benzene, toluene, ethylbenzene, xylene, n-hexane, fluorotrichloromethane, carbon tetrachloride, 1,2-dichloroethane, 1,1,1-trichloroethane, trichloroethylene, tetrachloroethylene, styrene, 1,3,5-trimethylbenzene, 1,2,4-trimethylbenzene, sec-butylbenzene and naphthalen were identified as the major compounds in the air, and their average concentrations were 0.81, 5.02 1.30, 3.0, 0.81, 37.9, 0.07, 0.15, 0.15, 0.79, 0.06, 0.33, 0.03, 0.12, 0.23, and 0.35 ppb(v/v), respectively. The concentrations of VOCs were low in summer and high in fall or winter. When the concentrations detected in air compare with WHO's norm, no case exceed it.

• Proceedings of the Ginseng society Conference
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• 2002.10a
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• pp.491-501
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• 2002

A cross-examination between KT&G Central Research Institute and Guangzhou Institute for Drug Control was carried out in order to select optimum conditions for extraction, separation and determination of ginsenosides in red ginseng and to propose a better method for the quantitative analysis of ginsenosides. The optimum extraction conditions of ginsenosides from red ginseng were as follows: the extraction solvent, $70\%$ methanol; the extraction temperature, $100^{\circ}C;$ the extraction time, 1 hour for once; and the repetition of extraction, twice. The optimum separation conditions of ginsenosides on the SepPak $C_{18}$ cartridge were as follows: the loaded amount, 0.4 g of methanol extract; the washing solvents, distilled water of 25 ml at first and then $30\%$ methanol of 25 ml; the elution solvent, $90\%$ methanol of 5 ml. The optimum HPLC conditions for the determination of ginsenosides were as follows: column, Lichrosorb $NH_2(25{\times}0.4cm,$ 5${\mu}m$, Merck Co.); mobile phase, a mixture of acetonitrile/water/isopropanol (80/5/15) and acetonitrile/water/isopropanol (80/20/15) with gradient system; and the detector, ELSD. On the basis of the optimum conditions a method for the quantitative analysis of ginsenosides were proposed and another cross-examination was carried out for the validation of the selected analytical method conditions. The coefficient of variances (CVs) on the contents of ginsenoside-$Rg_{1}$, -Re and $-Rb_1$ were lower than $3\%$ and the recovery rates of ginsenosides were $89.4\~95.7\%,$ which suggests that the above extraction and separation conditions may be reproducible and reasonable. For the selected HPLC/ELSD conditions, the CVs on the detector responses of ginsenoside-Rg, -Re and $-Rb_1$) were also lower than $3\%$, the regression coefficients for the calibration curves of ginsenosides were higher than 0.99 and two adjacent ginsenoside peaks were well separated, which suggests that the above HPLC/ELSD conditions may be good enough for the determination of ginsenosides.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.279-286
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• 2021

Recently, We are carrying out a policy of physical distancing of at least 1m from each other to prevent the spreading of COVID-19 disease in public places. In this paper, we propose a method for measuring distances between people in real time and an automation system that recognizes objects that are within 1 meter of each other from stereo images acquired by drones or CCTVs according to the estimated distance. A problem with existing methods used to estimate distances between multiple objects is that they do not obtain three-dimensional information of objects using only one CCTV. his is because three-dimensional information is necessary to measure distances between people when they are right next to each other or overlap in two dimensional image. Furthermore, they use only the Bounding Box information to obtain the exact coordinates of human existence. Therefore, in this paper, to obtain the exact two-dimensional coordinate value in which a person exists, we extract a person's key point to detect the location, convert it to a three-dimensional coordinate value using Stereo Vision and Camera Calibration, and estimate the Euclidean distance between people. As a result of performing an experiment for estimating the accuracy of 3D coordinates and the distance between objects (persons), the average error within 0.098m was shown in the estimation of the distance between multiple people within 1m.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.359-365
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• 2021

GEO-KOMPSAT-2A (GK2A) AMI (Advanced Meteorological Imager) Best Detector Select (BDS) map is pre-determined and uploaded before the satellite launch. After the launch, there is some possibility of a detector performance change driven by an abrupt temperature variation and thus the status of BDS map needs to be evaluated and updated if necessary. To investigate performance of entire elements of the detectors, AMI BDS analyses were conducted based on a technical note provided from the AMI vendor (L3HARRIS). The concept of the BDS analysis is to investigate the stability of signals from detectors while they are staring at targets (deep space and internal calibration target). For this purpose, Long Time Series (LTS) and Output Voltage vs. Bias Voltage (V-V) methods are used. The LTS for 30 secs and the V-V for two secs are spanned respectively for looking at the targets to compute noise components of detectors. To get the necessary data sets, these activities were conducted during the In-Orbit Test (IOT) period since a normal operation of AMI is stopped and special mission plans are commanded. With collected data sets during the GK2A IOT, AMI BDS map was intensively examined. It was found that about 1% of entire detector elements, which were evaluated at the ground test, showed characteristic changes and those degraded elements are replaced by alternative best ones. The stripping effects on AMI raw images due to the BDS problem were clearly removed when the new BDS map was applied.

• Analytical Science and Technology
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• v.32 no.2
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• pp.35-47
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• 2019

In this study, high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) was employed to detect 26 antidiabetic compounds in adulterated dietary supplements using a simple, selective method. The work presented herein may help prevent incidents related to food adulteration and restrict the illegal food market. The best separation was obtained on a Shiseido Capcell Pak(R) C18 MG-II ($2.0mm{\times}100mm$, $3{\mu}m$), which improved the peak shape and MS detection sensitivity of the target compounds. A gradient elution system composed of 0.1 % (v/v) formic acid in distilled water and methanol at a flow rate of 0.3 mL/min for 18 min was utilized. A triple quadrupole mass spectrometer with an electrospray ionization source operated in the positive or negative mode was employed as the detector. The developed method was validated as follows: specificity was confirmed in the multiple reaction monitoring mode using the precursor and product ion pairs. For solid samples, LOD ranged from 0.16 to 20.00 ng/mL and LOQ ranged from 0.50 to 60.00 ng/mL, and for liquid samples, LOD ranged from 0.16 to 20.00 ng/mL and LOQ ranged from 0.50 to 60.00 ng/mL. Satisfactory linearity was obtained from calibration curves, with $R^2$ > 0.99. Both intra and inter-day precision were less than 13.19 %. Accuracies ranged from 80.69 to 118.81 % (intra/inter-day), with a stability of less than 14.88 %. Mean recovery was found to be 80.6-119.0 % and less than 13.4 % RSD. Using the validated method, glibenclamide and pioglitazone were simultaneously determined in one capsule at concentrations of 1.52 and 0.53 mg (per capsule), respectively.

• Economic and Environmental Geology
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• v.54 no.1
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• pp.151-160
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• 2021

2:1 clay minerals such as smectite incorporating ammonium were extracted to investigate the ammonium behavior and nitrogen isotope characteristics for two different sediment cores which were collected from shimmering sites on seafloor of the Wakamiko crater, southwestern Japan. Inorganic nitrogen contents in clay fraction were estimated by calibration curve based on consistently decreasing carbon and nitrogen ratio during the treatment to decompose organic materials, after removing inorganic carbon. The results show that the proportions of inorganic nitrogen for total nitrogen in clay fraction of SWS site(Core#1094MR: av. 18.2%) are higher than those in SES site(Core#1093MG: av. 11.5%). Relatively good crystallinity of the former suggests that exchangeable ammonium was transformed to non-exchangeable ammonium during more evolving diagenetic process. Nitrogen isotope variance of clay fraction(SES site: Core#1093MG: -4.4 ~ +0.2 ‰, av. -2.4 ‰; SWS site: Core#1094MR: -0.7 ~ +3.0 ‰, av. +1.5 ‰) during sequential decomposition of exchangeable ammonium suggests that heat flow derived from deep magma led to nitrogen isotope fractionation between dissolved ammonium and ammonia in the fluids involved in the formation of 2:1 clay mineral incorporating ammonium with local temperature variation.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.944-953
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• 2020

Object detection plays a crucial role in a self-driving system. With the advances of image recognition based on deep convolutional neural networks, researches on object detection have been actively explored. In this paper, we proposed a lightweight model of the mask R-CNN, which has been most widely used for object detection, to efficiently predict location and shape of various objects on the road environment. Furthermore, feature maps are adaptively re-calibrated to improve the detection performance by applying an attention module to the neural network layer that plays different roles within the mask R-CNN. Various experimental results for real driving scenes demonstrate that the proposed method is able to maintain the high detection performance with significantly reduced network parameters.

• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.269-282
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• 2021

As the distribution of 3D content such as augmented reality and virtual reality increases, the importance of real-time computer animation technology is increasing. However, the computer animation process consists mostly of manual or marker-attaching motion capture, which requires a very long time for experienced professionals to obtain realistic images. To solve these problems, animation production systems and algorithms based on deep learning model and sensors have recently emerged. Thus, in this paper, we study four methods of implementing natural human movement in deep learning model and kinect camera-based animation production systems. Each method is chosen considering its environmental characteristics and accuracy. The first method uses a Kinect camera. The second method uses a Kinect camera and a calibration algorithm. The third method uses deep learning model. The fourth method uses deep learning model and kinect. Experiments with the proposed method showed that the fourth method of deep learning model and using the Kinect simultaneously showed the best results compared to other methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.446-452
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• 2021

As a higher standard for food consumption is required, the consumption of chicken meat that can satisfy the subdivided food preferences is increasing. In March 2003, the quality criteria for chicken carcasses notified by the Livestock Quality Assessment Service suggested quality grades according to fecal contamination and the size and weight of blood and bruises. On the other hand, it is too difficult for human inspection to qualify mass products, which is key to maintaining consistency for grading thousands of chicken carcasses. This paper proposed the computer vision algorithm as a non-destructive inspection, which can identify chicken carcass parts according to the detailed standards. To inspect the chicken carcasses conveyed at high speed, the image calibration was involved in providing robustness to the side effect of external lighting interference. The separation between chicken and background was achieved by a series of image processing, such as binarization based on Expectation Maximization, Erosion, and Labeling. In terms of shape analysis of chicken carcasses, the features are presented to reveal geometric information. After applying the algorithm to 78 chicken carcass samples, the algorithm was effective in segmenting chicken carcass against a background and analyzing its geometric features.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1493-1507
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• 2020

The LEOP Cal/Val (Launch and Early Operation Phase Calibration/Validation) was carried out during 6 months after KOMPSAT-3A (KOMPSAT-3A Korea Multi-Purpose Satellite-3A) was launched in March 2015. After LEOP Cal/Val was successfully completed, high resolution KOMPSAT-3A has been successfully distributing to users over the past 8 years. The sub-meter high-resolution satellite image data obtained from KOMPSAT-3A is used as basic data for qualitative and quantitative information extraction in various fields such as mapping, GIS (Geographic Information System), and national land management, etc. The KARI (Korea Aerospace Research Institute) periodically checks and manages the quality of KOMPSAT-3A's product and the characteristics of satellite hardware to ensure the accuracy and reliability of information extracted from satellite data of KOMPSAT-3A. To minimize the deterioration of image quality due to aging of satellite hardware, payload and attitude sensors of KOMPSAT-3A, continuous improvement of image quality has been carried out. In this paper, the Cal/Val work-flow defined in the KOMPSAT-3A development phase was illustrated for the period of before and after the launch. The MTF, SNR, and location accuracy are the key parameters to estimate image quality and the methods of the measurements of each parameter are also described in this work. On the basis of defined quality parameters, the performance was evaluated and measured during the period of after LEOP Cal/Val. The current status and characteristics of MTF, SNR, and location accuracy of KOMPSAT-3A from 2016 to May 2020 were described as well.