• KSCE Journal of Civil and Environmental Engineering Research
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• v.3 no.2
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• pp.119-126
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• 1983

The purposes of this study are to analyze/model the mode choice behavior of the regional traveler by express bus/express train and to offer useful source in deciding the public transportation policy. The data analyzed were trips of both modes from March, 1980 to November, 1981, between Seoul and other nineteen cities; the data were grouped as five groups according to the change of service variables. Service variables were travel time(unit: minute), cost(:won), average allocation time(:won), service hour(:hour), and dummy variables by mode. As model Logit Model with linear or log utility function were postulated. As the result of this study, some reseanable models were constructed at Model Type I(eq. 2. of this paper) based on the above data except the dummy. It was judged that the parameters calibrated by Group III and Group IV data in table 4, were optimal. Among the parameters, the parameter of travel cost was most reliable. There was a tendency preferring express bus to train in October and November. With the constructed model and Pivot-Point Method. the demand change of express train caused by the service variables' change could be forecasted over 99%.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.4
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• pp.155-168
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• 2018

This study singled out 30 smart car features and surveyed 250 respondents. Assuming that the relationship between fulfillment of a feature or a customer need and the satisfaction with that feature is not necessarily linear, this study was conducted using Kano's method. Two devices, Timko Deviation(TD) and Kano Distribution Index(KDI), were devised to help evaluate resulting Kano table quantitatively. Previous research based on Kano's original framework showed the limit to the analysis of new or unfamiliar features: more than 85% of the features surveyed turned out to be either Attractive or Indifferent attributes. This study attempted a new empirical approach by applying customer experiences, price conditions, and customer self-stated importance. The results showed that customer experience of the surveyed features affected the overall satisfaction level, signifying that Kano's method should be conducted with care when analyzing emerging technologies such as smart cars. It is expected that this study would be utilized for better understanding of the perception and trends of customers regarding new technologies. This study also suggests a new approach to the analysis of customer requirements by providing price conditions.

• Journal of Trauma and Injury
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• v.26 no.3
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• pp.198-206
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• 2013

Purpose: This study was performed to calculate and analyze the effective radiation doses from computed tomography (CT) and radiologic intervention in patients in the emergency department (ED) with trauma critical pathway (CP) activation and further to estimate the lifetime attributable risks (LARs) for the incidence of and mortality from cancers induced by the radiation dose. Methods: Through a retrospective electrical chart review of 104 injured patients who trauma critical pathway were activated from November 2012 to March 2013, we calculated effective radiologic doses by taking the product of the dose-linear product of the scan and the conversion coefficient. After a determination of the image results, we divided the patients into two groups, negative or positive, and calculated the effective dose for each group. With these results, we estimated the LARs for the incidence of and the mortality from cancers by using the table in the Biologic Effects of Ionizing Radiation (BEIR)-VII report. Results: A total of 76 patients were enrolled. The mean age was $49.0{\pm}8.5$ years. The mean injury severity score (ISS) was $12.7{\pm}8.4$. The cumulative effective dose (CED) for individual patients varied from 2.8 mSv to 238.8 mSv, and the mean was $47.6{\pm}39.9$ mSv. The CED in patients with an $ISS{\geq}16$($63.2{\pm}26.6$ mSv) was higher than that of patients whose ISS<16($33.5{\pm}23.1$ mSv) (p<0.001). The CED in patients who were treated with surgery or intervention($69.0{\pm}45.2$ mSv) was higher than that of patients who were treated conservatively($33.6{\pm}22.4$ mSv) (p<0.001). The LARs for cancer incidence and mortality were $328.5{\pm}308.6$ and $189.0{\pm}159.3$ per 100,000 people, respectively. Conclusion: The CED and the LAR for trauma CP-activated patients in the ED were significant, so efforts should be made to decrease the effective dose received by severely injured patients.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.443-453
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• 2013

The hybrid test is one of the most advanced test methods to predict the structural dynamic behavior with the interaction between a physical substructure and a numerical modeling in the hybrid control system. The purpose of this study is to perform the multi-directional dynamic test of a steel frame structure with the real-time hybrid system and to evaluate the validation of the results. In this study, FEAPH, nonlinear finite element analysis program for hybrid only, was developed and the hybrid control system was optimized. The inefficient computational time was improved with a fixed number iteration method and parallel computational techniques used in FEAPH. Furthermore, the previously used data communication method and the interface between a substructure and an analysis program were simplified in the control system. As the results, the total processing time in real-time hybrid test was shortened up to 10 times of actual measured seismic period. In order to verify the accuracy and validation of the hybrid system, the linear and nonlinear dynamic tests with a steel framed structure were carried out so that the trend of displacement responses was almost in accord with the numerical results. However, the maximum displacement responses had somewhat differences due to the analysis errors in material nonlinearities and the occurrence of permanent displacements. Therefore, if the proper material model and numerical algorithms are developed, the real-time hybrid system could be used to evaluate the structural dynamic behavior and would be an effective testing method as a substitute for a shaking table test.

• FLOWER RESEARCH JOURNAL
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• v.16 no.1
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• pp.7-11
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• 2008

In order to investigate the application of bamboo in various ways in floral designs, we analyzed 108 bamboo items from the monthly magazine 'Fleur' and from the International Flower Contest held from 2001 to 2006. We analyzed the frequency of usage of bamboos by the used parts, kind of design, type of design, and arrangement method in the design work. In terms of the used parts of the bamboo, stems took 90% of the whole work. Among the 77 designs that used stems, excluding the 20 work items presented in the International Flower Contest which has been held in April, number of the bamboo work items peaked at the beginning of the year in January and February, and during summer (July and August). Upon analyzing the type of stems that were used in the 97 works, 63% of the works used bamboo in natural state, but not processed. 48% of the works used the vertical-parallel method among the arrangement methods. Other categorized works were rounded works that were not included in the vertical, horizontal or diagonal mathod. More than 50% of the works, including the table decoration, used space decoration. Among the types of work design that used bamboo as material, 64% were decorative type, 30% graphic type, and 4% formal-linear type.

• Journal of the Korean Society of Radiology
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• v.16 no.7
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• pp.953-960
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• 2022

The measurement of branching ratio of ¹⁶⁷Yb radioactive isotopes from gamma-ray spectrum of ¹⁶⁹Tm(p,3n)¹⁶⁷Yb reaction were performed by using a 100-MeV proton linear accelerator of the Korea Multi-purpose Accelerator Complex (KOMAC). The ¹⁶⁷Yb isotope has a half-life of 17.5 minutes and decays to ¹⁶⁹Tm. The gamma rays generated from the ¹⁶⁷Yb isotope were measured using an HPGe detector gamma ray spectroscopy system. The energy calibration of the detector and the efficiency measurement of the detector were determined using a standard source. The gamma rays of known main energy (62.9, 106.2, 113.3, 143.5 and 176.3 keV) were measured. On the other hand, information about the intensity of the generated gamma rays is very inaccurate. Therefore, in this study, the decay strength of the main gamma rays was accurately measured. Overall, it was different from the previously known results, and in particular, it was found that the intensity of the main decay gamma ray, such as the 113.3 and 106.2 keV gamma ray, was overestimated, and it was found that the gamma ray, such as 62.9, 116.7 and 143.5 keV was underestimated. The present results are considered to be important information in the fields of nuclear fusion, astrophysics and nuclear physics in the future.

• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.471-476
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• 2022

The purpose of this study was to study the probability of cancer occurrence due to photoneutron dose exposure of the colon and thyroid gland, which are normal organs, in 3D CRT, IMRT 5 portals, and IMRT 9 portals, which are radiotherapy methods for prostate cancer. The total prescribed dose for prostate cancer was 6600 cGy, 220 cGy per dose, and 30 divided irradiations were applied for the total number of times. After setting up the Rando phantom on the treatment table (couch) of the medical linear accelerator used in the experiment, an optically stimulated luminescence albedo neutron dosimeter was placed on the corresponding area of the large intestine and thyroid gland of the phantom for measurement. During 3D CRT of prostate cancer, the probability of secondary cancer due to photoneutron dose to the colon and thyroid gland, which are normal organs, was 1.8 per 10,000 people. And IMRT 5 portals were 8.7 per 10,000 people, which was about 5 times larger than 3D CRT. IMRT 9 portals derived the result that there is a probability that 1.2 people per 1,000 people will develop cancer. Based on this study, the risk of secondary radiation exposure due to the dose of photoneutrons generated during radiation therapy is studied, and it is thought that it will be used as useful data for radiation protection in relation to the stochastic effect of radiation in the future.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.139-153
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• 2017

Corporate bankruptcy can cause great losses not only to stakeholders but also to many related sectors in society. Through the economic crises, bankruptcy have increased and bankruptcy prediction models have become more and more important. Therefore, corporate bankruptcy has been regarded as one of the major topics of research in business management. Also, many studies in the industry are in progress and important. Previous studies attempted to utilize various methodologies to improve the bankruptcy prediction accuracy and to resolve the overfitting problem, such as Multivariate Discriminant Analysis (MDA), Generalized Linear Model (GLM). These methods are based on statistics. Recently, researchers have used machine learning methodologies such as Support Vector Machine (SVM), Artificial Neural Network (ANN). Furthermore, fuzzy theory and genetic algorithms were used. Because of this change, many of bankruptcy models are developed. Also, performance has been improved. In general, the company's financial and accounting information will change over time. Likewise, the market situation also changes, so there are many difficulties in predicting bankruptcy only with information at a certain point in time. However, even though traditional research has problems that don't take into account the time effect, dynamic model has not been studied much. When we ignore the time effect, we get the biased results. So the static model may not be suitable for predicting bankruptcy. Thus, using the dynamic model, there is a possibility that bankruptcy prediction model is improved. In this paper, we propose RNN (Recurrent Neural Network) which is one of the deep learning methodologies. The RNN learns time series data and the performance is known to be good. Prior to experiment, we selected non-financial firms listed on the KOSPI, KOSDAQ and KONEX markets from 2010 to 2016 for the estimation of the bankruptcy prediction model and the comparison of forecasting performance. In order to prevent a mistake of predicting bankruptcy by using the financial information already reflected in the deterioration of the financial condition of the company, the financial information was collected with a lag of two years, and the default period was defined from January to December of the year. Then we defined the bankruptcy. The bankruptcy we defined is the abolition of the listing due to sluggish earnings. We confirmed abolition of the list at KIND that is corporate stock information website. Then we selected variables at previous papers. The first set of variables are Z-score variables. These variables have become traditional variables in predicting bankruptcy. The second set of variables are dynamic variable set. Finally we selected 240 normal companies and 226 bankrupt companies at the first variable set. Likewise, we selected 229 normal companies and 226 bankrupt companies at the second variable set. We created a model that reflects dynamic changes in time-series financial data and by comparing the suggested model with the analysis of existing bankruptcy predictive models, we found that the suggested model could help to improve the accuracy of bankruptcy predictions. We used financial data in KIS Value (Financial database) and selected Multivariate Discriminant Analysis (MDA), Generalized Linear Model called logistic regression (GLM), Support Vector Machine (SVM), Artificial Neural Network (ANN) model as benchmark. The result of the experiment proved that RNN's performance was better than comparative model. The accuracy of RNN was high in both sets of variables and the Area Under the Curve (AUC) value was also high. Also when we saw the hit-ratio table, the ratio of RNNs that predicted a poor company to be bankrupt was higher than that of other comparative models. However the limitation of this paper is that an overfitting problem occurs during RNN learning. But we expect to be able to solve the overfitting problem by selecting more learning data and appropriate variables. From these result, it is expected that this research will contribute to the development of a bankruptcy prediction by proposing a new dynamic model.

• Tuberculosis and Respiratory Diseases
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• v.41 no.5
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• pp.521-530
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• 1994

Background : The past studies on prediction formulas of pulmonary function parameters in healthy nonsmoking Korean adults have been performed in relatively small number of subjects and the reported results were restricted on a few parameters. Also there was no systematic investigation into the effect of smoking on pulmonary function parameters in smokers who have no respiratory symptoms. Therefore we attempted to establish prediction formulas of pulmonary function parameters and examined the effect of smoking on pulmonary function parameters. Methods We analyzed the result of parameters derived from the forced expiratory spirogram in 1,067 nonsmoking subjects from June in 1990 to December in 1991. They consisted of 306 males and 761 females and had neither respitatory symptoms nor history of respiratory disease. We derived prediction formulas by multiple linear regression method from their age, heights, and weights in each sex. To examine the effect of smoking on pulmonary function parameters, we classified 383 smoking men into three groups according to the past amount of smoking as follows : i.e. group of smokers who have smoked below 10 pack-years, 10-20 pack-years and above 20 pack-years. Regarding each group of past smoking as an independent dummy variable, we analyzed pulmonary function parameters including nonsmoking men as a baseline by multiple linear regression. We evaluated the smoking effect on pulmonary function parameters according to estimated p-value. Result : 1) Prediction formulas for pulmonary function parameters in each sex were derived. 2) The past smoking less than 10 pack-years does not give any effect on pulmonary function parameters. The past smoking of 10~20 pack-years showed significant negative correlation with $FEV_1$/FVC and FEF 25~75%, and the smoking above 20 pack years showed negative correlation with $FEV_1$ and $FEV_1$/FVC. Conclusion : We have got prediction formulas of pulmonary function parameters which is driven from forced expiratory spirogram in nonsmoking Korean adults by multiple linear regression from age, heights and weights of subjects. The past smoking more than 10 pack-years showed negative correlation with some pulmonary function parameters of airflow obstruction.

• Progress in Medical Physics
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• v.26 no.4
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• pp.215-222
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• 2015

In this work, we performed a proof-of-concept experiment for phase-contrast x-ray imaging (PCXI) based on a single antiscatter grid and a polychromatic x-ray source. We established a table-top setup which consists of a focused-linear grid having a strip density of 200 lines/inch, a microfocus x-ray tube having a focal-spot size of about $5{\mu}m$, and a CMOS-type flat-panel detector having a pixel size of $48{\mu}m$. By using our prototype PCXI system and the Fourier demodulation technique, we successfully obtained attenuation, scattering, and differential phase-contrast images of improved visibility from the raw images of several selected samples at x-ray tube conditions of $90kV_p$ and 0.1 mAs. Further, fusion image (e.g., the attenuation+the scattering) may have an advantage in displaying details of the sample's structures that are not clearly visible in the conventional attenuation image. Our experimental results indicate that single-grid-based approach seems a useful method for PCXI with great simplicity and minimal requirements on the setup alignment.