• Journal of Korean Society for Atmospheric Environment
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• v.18 no.6
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• pp.437-452
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• 2002

The Metropolitan Tracer Experiment (METREX) was performed over the Washington, D.C. area using two inert, non-deposition perfluorocarbon gases for over 1 year period (November 1983∼December 1984). Two perfluorocarbon gas tracers (PDCH, PMCH) were released simultaneously at intervals of every 36 hours for 6 hours, regardless of the meteorological conditions in metropolitan area. Samples were collected continuously for 8 hours at a central downtown and two adjacent suburban locations. Monthly air samples were collected at 93 sites across the whole region (at urban, suburban, and rural locations). The purpose of this study is to simulate INPUFF and ISCST model using METREX data, and to compare calculated and observed concentrations. In the case of INPUFF simulation, two meteorological input data were used. One is result data from wind field model which was calculated by diagnostic wind model (DWM), the other is meteorological data observed at single station. Here, three kinds of model calculation were performed during April and July 1984; they include (1) INPUFF model using DWM data (2) INPUFF model using single meteorological data (3) ISCST model. The monthly average concentration data were used for statistic analysis and to draw their horizontal distribution patterns. Eight-hour-averaged concentration was used to describe movement of puff during the episode period. The results showed that the concentrations calculated by puff model (INPUFF) were better than plume model (ISCST). In the case of puff model (INPUFF), a model run using wind field data produced better results than that derived by single meteorological data.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.22 no.7
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• pp.606-611
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• 2009

AC loss is one of the important factors for commercialization of a high temperature superconducting (HTS) cable from an economic point of view. But AC loss characteristics of the HTS-cable are not elucidated completely because of its complex structure. As an earlier stage of analyzing the AC loss in the 22.9 kV/50 MVA, 100m HTS-cable system of Korea Electric Power Corporation (KEPCO) which is now in collaboration with us, a two-dimensional (2D) numerical model, which takes into account the nonlinear conductivity properties of a high temperature superconductor, has been developed. In order to examine our 2D model, we have prepared several single-layer cable samples whose AC losses are sufficiently reliable due to their simple structure. The AC losses of the samples were experimentally investigated and then compared with our 2D model. The results show that the numerically calculated AC losses are not in good agreement with the measured ones for the cylindrical cable and deca-cable samples with low critical current density. However, the numerically calculated and measured AC losses are relatively in good agreement for the deca-cable and hex-cable samples with high critical current density, although the difference between these two loss data in the deca-cable sample tends to increase in the low current region.

• Journal of radiological science and technology
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• v.43 no.6
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• pp.503-509
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• 2020

This study aims to develop a patient-specific radiation exposure dose prediction model based on anthropometric data that can be easily measurable during CT examination, and to be used as basic data for DRL setting and radiation dose management system in the future. In addition, among the machine learning algorithms, the most suitable model for predicting exposure doses is presented. The data used in this study were chest CT scan data, and a data set was constructed based on the data including the patient's anthropometric data. In the pre-processing and sample selection of the data, out of the total number of samples of 250 samples, only chest CT scans were performed without using a contrast agent, and 110 samples including height and weight variables were extracted. Of the 110 samples extracted, 66% was used as a training set, and the remaining 44% were used as a test set for verification. The exposure dose was predicted through random forest, linear regression analysis, and SVM algorithm using Orange version 3.26.0, an open software as a machine learning algorithm. Results Algorithm model prediction accuracy was R^2 0.840 for random forest, R^2 0.969 for linear regression analysis, and R^2 0.189 for SVM. As a result of verifying the prediction rate of the algorithm model, the random forest is the highest with R^2 0.986 of the random forest, R^2 0.973 of the linear regression analysis, and R^2 of 0.204 of the SVM, indicating that the model has the best predictive power.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.17 no.1
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• pp.64-80
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• 1991

The SKINTEX Method is based on a two-compartment physico-chemical model which includes a Biomembrane Barrier in compartment one and an organized macromolecular matrix in compartment two. Test samples absorb onto or permeate through the keratin/collagen Biomembrane Barrier and then can interact with the organized macromolecular matrix. Changes in the integrity of the barrier release a dye indicator: Changes in the matrix can alter its transparency. The sum of these two responses is read spectrophotometrically at 470nm. An early investigation of 950 chemicals and formulations in the SKINTEX System produced results which were 89% concordance to in vivo Draize dermal irritation results obtained with 24-hour occluded application of test samples with-out abrasion and standard scoring. Alkaline materials were analyzed in a specialized SKINTEX AMA Protocol. In this early study, the model did not distinguish nonirritant test materials and formulation with PDII(Primary Dermal Irritation Index)in the range from 0 to 1.2, A High Sensitivity Assay Protocol(HSA)was developed to amplify the changes in both compartments of this model and provide more accurate calibration of these changes. A study of 60 low irritation test samples including cosmetics, household products, chemicals and petro-chemicals distinguished nonirritants with PDII $\leq$ 0.7 for 26 of 30 nonirritants. A second protocol was developed to evaluate the SKINTEX model predictability with respect to human irritation. The Human Response Assay (HRA )has been optimized based on differences in penetration and irritation responses in humans and rabbits. An additional 32 test materials with different mechanisms and degrees of dermal toxicity were evaluated by the HRA. These in vitro results were 86% concordant to human patch test results. In order to further evaluate this model, a Standard Chemical Labelling (SCL) Protocol was developed to optimize this system to predict Draize dermal irritation results after a 4-hour application of the test material. In a study of 52 chemicals including acids, bases, solvents, salts, surfactants and preservatives, the SCL results demonstrated 85% concordance to Draize results for a 4-hour application of test samples on non-abraded rabbit skin. The SKINTEX System, including three specialized protocols, provided results which demonstrated good correlation to the endpoint of dermal irritation in man and rabbits at different application times.

• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.11-18
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• 2012

Debris flow deposition model is a model to predict affected areas by debris flow and random walk model (RWM) was used to build the model. Although the model was proved to be effective in the prediction of affected areas, the model has several free parameters decided experimentally. There are several well-known methods to estimate parameters, however, they cannot be applied directly to the debris flow problem due to the small size of training data. In this paper, a modified neural network, called pseudo sample neural network (PSNN), was proposed to overcome the sample size problem. In the training phase, PSNN uses pseudo samples, which are generated using the existing samples. The pseudo samples smooth the solution space and reduce the probability of falling into a local optimum. As a result, PSNN can estimate parameter more robustly than traditional neural networks do. All of these can be proved through the experiments using artificial and real data sets.

• Safety and Health at Work
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• v.14 no.2
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• pp.237-242
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• 2023

Background: This study evaluated occupational exposure levels of doxorubicin in healthcare workers performing rotational intraperitoneal pressurized aerosol chemotherapy (PIPAC) procedures. Methods: All samples were collected during PIPAC procedures applying doxorubicin to an experimental animal model (pigs). All procedures were applied to seven pigs, each for approximately 44 min. Surface samples (n = 51) were obtained from substances contaminating the PIPAC devices, surrounding objects, and protective equipment. Airborne samples were also collected around the operating table (n = 39). All samples were analyzed using ultra-high performance liquid chromatography-mass spectrometry. Results: Among the surface samples, doxorubicin was detected in only five samples (9.8%) that were directly exposed to antineoplastic drug aerosols in the abdominal cavity originating from PIPAC devices. The telescopes showed concentrations of 0.48-5.44 ng/cm² and the trocar showed 0.98 ng/cm² in the region where the spraying nozzles were inserted. The syringe line connector showed a maximum concentration of 181.07 ng/cm², following a leakage. Contamination was not detected on the surgeons' gloves or shoes. Objects surrounding the operating table, including tables, operating lights, entrance doors, and trocar holders, were found to be uncontaminated. All air samples collected at locations where healthcare workers performed procedures were found to be uncontaminated. Conclusions: Most air and surface samples were uncontaminated or showed very low doxorubicin concentrations during PIPAC procedures. However, there remains a potential for leakage, in which case dermal exposure may occur. Safety protocols related to leakage accidents, selection of appropriate protective equipment, and the use of disposable devices are necessary to prevent occupational exposure.

• Journal of Sasang Constitutional Medicine
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• v.22 no.3
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• pp.87-97
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• 2010

1. Objectives: In SCM, a personal Sasang constitution must be determined accurately before any Sasang treatment. The purpose of this study is to develop an objective method for classification of Sasang constitution. 2. Methods: We collected samples from 5 centers where SCM is practiced, and applied two-stage decision tree analysis on these samples. We recruited samples from 5 centers. The collected data were from subjects whose response to herbal medicine was confirmed according to Sasang constitution. 3. Results: The two-stage decision tree model shows higher classification power than a simple decision tree model. This study also suggests that gender must be considered in the first stage to improve the accuracy of classification. 4. Conclusions: We identified important factors for classifying Sasang constitutions through two-stage decision tree analysis. The two-stage decision tree model shows higher classification power than a simple decision tree model.

• Journal of Magnetics
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• v.5 no.2
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• pp.27-34
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• 2000

The structure of a series of Cu/Ni is characterized by using a program, SUPREX, to model the x-ray diffraction patterns, multilayers. The samples had nominal layer thickness of 3/3, 7/7, 13.5/13.5, 20/20, 30/30, 50/50, 80/80, 100/100, and 200/200 Angstroms. The diffraction patterns were taken around the (111) peak for the two constituent materials. A kinematical model is used to characterize the diffraction patterns and the parameters for the model are described. An initial model is calculated using initial guesses for the parameters. The model is then fit to the data by reducing $x^2$using the Levenberg-Marquardt algorithm. The samples are shown to be high quality supperlattices.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.190-197
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• 2022

The purpose of this study is to investigate the effect of consumer's authenticity perception on brand repurchase intention and word-of-mouth intention through customer satisfaction and brand attachment. For this purpose, a structural equation model was established based on previous studies and an empirical study was conducted. The survey was conducted offline and online, and samples were collected using a convenient sampling method. A total of 267 questionnaires were sampled, and 255 questionnaires were used as final valid samples, except for 12 questionnaires with errors. For the final data, SPSS Win ver. 23.0 and AMOS 20.0 statistical programs were used to analyze the personal characteristics of the subjects, verify the research model, and confirm the reliability and validity of the measurement model and the suitability of the research model.As a result, all six hypotheses were adopted, and the correlation between each factor was observed in the research model.

• Structural Engineering and Mechanics
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• v.86 no.2
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• pp.237-247
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• 2023

Fourier series-based models in the time domain are frequently established to represent individual bouncing loads, which neglects the stochastic property of human bouncing activity. A power spectral density (PSD) model in the frequency domain for individual bouncing loads is developed herein. An experiment was conducted on individual bouncing loads, resulting in 957 records linked to form long samples to achieve a fine frequency resolution. The Welch method was applied to the linked samples to obtain the experimental PSD, which was normalized by the bouncing frequency and the harmonic order. The energy, energy distribution center, and energy distribution shape of the experimental PSD were investigated to establish the PSD model. The proposed model was used to analyze structural vibration responses using stochastic vibration theory, which was verified via field measurements. It is believed that this framework can evaluate the vibration capacity of structures excited by bouncing crowds, such as concert halls and grandstands.