• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.3
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• pp.273-283
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• 2020

Because of climate change, the occurrence of localized and heavy rainfall is increasing. It is important to predict floods in urban areas that have suffered inundation in the past. For flood prediction, not only numerical analysis models but also machine learning-based models can be applied. The LSTM (Long Short-Term Memory) neural network used in this study is appropriate for sequence data, but it demands a lot of data. However, rainfall that causes flooding does not appear every year in a single urban basin, meaning it is difficult to collect enough data for deep learning. Therefore, in addition to the rainfall observed in the study area, the observed rainfall in another urban basin was applied in the predictive model. The LSTM neural network was used for predicting the total overflow, and the result of the SWMM (Storm Water Management Model) was applied as target data. The prediction of the inundation map was performed by using logistic regression; the independent variable was the total overflow and the dependent variable was the presence or absence of flooding in each grid. The dependent variable of logistic regression was collected through the simulation results of a two-dimensional flood model. The input data of the two-dimensional flood model were the overflow at each manhole calculated by the SWMM. According to the LSTM neural network parameters, the prediction results of total overflow were compared. Four predictive models were used in this study depending on the parameter of the LSTM. The average RMSE (Root Mean Square Error) for verification and testing was 1.4279 ㎥/s, 1.0079 ㎥/s for the four LSTM models. The minimum RMSE of the verification and testing was calculated as 1.1655 ㎥/s and 0.8797 ㎥/s. It was confirmed that the total overflow can be predicted similarly to the SWMM simulation results. The prediction of inundation extent was performed by linking the logistic regression with the results of the LSTM neural network, and the maximum area fitness was 97.33 % when more than 0.5 m depth was considered. The methodology presented in this study would be helpful in improving urban flood response based on deep learning methodology.

• Journal of Korean Society of Forest Science
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• v.76 no.3
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• pp.181-192
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• 1987

The purpose of this study is to develop the method of stand volume estimation by the plotless sampling method. The required data were obtained from 164 sampling plots in the red pine(Pinus densiflora) stands which were located in Kyeong-gi, Chung-nam, Chung-buk and Kang-won areas, and related factors were measured actually. The method of stand volume estimation and several tables were drivel from these data. 1. The relationship between the values of stand average height, basal area per ha, and basal area height obtained from the plotless sampling method and values measured actually could be described by the equation Y=bx, where b approached nearly 1.0 and there were no significant differences between them. Therefore stand volumes could be estimated by the plotless sampling method. 2. The estimated equations of the stand voulumes, which were estimated using factors to be measured by dendrometer, are as follows ; logV=-0.0208+0.8497 logGH, logV=-0.0028+0.7981 logG+0.9313 logH. Stand volume tables by these estimated equations were shown in table 4, 5 and estimation error percentages were 9.16% and 8.50% respectively. FH=D/(1.5205+0.0994D) logFH=0.0451+0.2429 logD+0.3474 logH logFG=-0.0380+0.7758logG-0.0066logH F=H/ (-5.1697+2.6013H) F=FH/(-3.1256+2.7611FH) logF=-0.0634-0.0848 logGH-0.1224 logDi 4. Stand form height tables(table7, 8), form basal area tables(table 9), and stand form factor tables(table 10, 11) were prepared using the above estimated equations, and the estimation error percentages were less than 10%.

• Journal of Global Scholars of Marketing Science
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• v.19 no.2
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• pp.17-26
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• 2009

As the lifestyle of consumers changes and the need for various products increases, new products are being developed in the market. Each household owns various home appliances which are purchased through the choice of a decision maker. These appliances include not only large-sized products such as TV, refrigerator, and washing machine, but also small-sized products such as microwave oven and air cleaner. There exists latent correlation among possession of home appliances, even though they are purchased independently. The purpose of this research is to analyze the effect of demographic factors on the purchase and possession of each home appliances, and to derive some relationships among various appliances. To achieve this purpose, the present status on the possession of each home appliances are investigated through consumer survey data on the electric and energy product. And a multivariate probit(MVP) model is applied for the empirical analysis. From the estimation results, some appliances show a substitutive or complementary pattern as expected, while others which look apparently unrelated have correlation by co-incidence. This research has several advantages compared to previous literatures on home appliances. First, this research focuses on the various products which are purchased by each household, while previous researches such as Matsukawa and Ito(1998) and Yoon(2007) focus just on a particular product. Second, the methodology of this research can consider a choice process of each product and correlation among products simultaneously. Lastly, this research can analyze not only a substitutive or complementary relationship in the same category, but also the correlation among products in the different categories. As the data on the possession of home appliances in each household has a characteristic of multiple choice, not a single choice, a MVP model are used for the empirical analysis. A MVP model is derived from a random utility model, and has an advantage compared to a multinomial logit model in that correlation among error terms can be derive(Manchanda et al., 1999; Edwards and Allenby, 2003). It is assumed that the error term has a normal distribution with zero mean and variance-covariance matrix ${\Omega}$. Hence, the sign and value of correlation coefficients means the relationship between two alternatives(Manchanda et al., 1999). This research uses the data of 'TEMEP Household ICT/Energy Survey (THIES) 2008' which is conducted by Technology Management, Economics and Policy Program in Seoul National University. The empirical analysis of this research is accomplished in two steps. First, a MVP model with demographic variables is estimated to analyze the effect of the characteristics of household on the purchase of each home appliances. In this research, some variables such as education level, region, size of family, average income, type of house are considered. Second, a MVP model excluding demographic variables is estimated to analyze the correlation among each home appliances. According to the estimation results of variance-covariance matrix, each households tend to own some appliances such as washing machine-refrigerator-cleaner-microwave oven, and air conditioner-dish washer-washing machine and so on. On the other hand, several products such as analog braun tube TV-digital braun tube TV and desktop PC-portable PC show a substitutive pattern. Lastly, the correlation map of home appliances are derived using multi-dimensional scaling(MDS) method based on the result of variance-covariance matrix. This research can provide significant implications for the firm's marketing strategies such as bundling, pricing, display and so on. In addition, this research can provide significant information for the development of convergence products and related technologies. A convergence product can decrease its market uncertainty, if two products which consumers tend to purchase together are integrated into it. The results of this research are more meaningful because it is based on the possession status of each household through the survey data.

• Progress in Medical Physics
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• v.25 no.1
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• pp.37-45
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• 2014

The accuracy and uniformity of CT numbers are the main causes of radiation dose calculation error. Especially, for the dose calculation based on kV-Cone Beam Computed Tomography (CBCT) image, the scatter affecting the CT number is known to be quite different by the object sizes, densities, exposure conditions, and so on. In this study, the scatter impact on the CBCT based dose calculation was evaluated to provide the optimal condition minimizing the error. The CBCT images was acquired under three scatter conditions ("Under-scatter", "Over-scatter", and "Full-scatter") by adjusting amount of scatter materials around a electron density phantom (CIRS062, Tissue Simulation Technology, Norfolk, VA, USA). The CT number uniformities of CBCT images for water-equivalent materials of the phantom were assessed, and the location dependency, either "inner" or "outer" parts of the phantom, was also evaluated. The electron density correction curves were derived from CBCT images of the electron density phantom in each scatter condition. The electron density correction curves were applied to calculate the CBCT based doses, which were compared with the dose based on Fan Beam Computed Tomography (FBCT). Also, 5 prostate IMRT cases were enrolled to assess the accuracy of dose based on CBCT images using gamma index analysis and relative dose differences. As the CT number histogram of phantom CBCT images for water equivalent materials was fitted with a gaussian function, the FHWM (146 HU) for "Full-scatter" condition was the smallest among the FHWM for the three conditions (685 HU for "under scatter" and 264 HU for "over scatter"). Also, the variance of CT numbers was the smallest for the same ingredients located in the center and periphery of the phantom in the "Full-scatter" condition. The dose distributions calculated with FBCT and CBCT images compared in a gamma index evaluation of 1%/3 mm criteria and in the dose difference. With the electron density correction acquired in the same scatter condition, the CBCT based dose calculations tended to be the most accurate. In 5 prostate cases in which the mean equivalent diameter was 27.2 cm, the averaged gamma pass rate was 98% and the dose difference confirmed to be less than 2% (average 0.2%, ranged from -1.3% to 1.6%) with the electron density correction of the "Full-scatter" condition. The accuracy of CBCT based dose calculation could be confirmed that closely related to the CT number uniformity and to the similarity of the scatter conditions for the electron density correction curve and CBCT image. In pelvic cases, the most accurate dose calculation was achievable in the application of the electron density curves of the "Full-scatter" condition.

• Geophysics and Geophysical Exploration
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• v.19 no.1
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• pp.1-10
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• 2016

The hypocenter distribution of microseismic events generated by hydraulic fracturing for shale gas development provides essential information for understanding characteristics of fracture network. In this study, we evaluate how inaccurate velocity models influence the inversion results of two widely used location programs, hypoellipse and hypoDD, which are developed based on an iterative linear inversion. We assume that 98 stations are densely located inside the circle with a radius of 4 km and 5 artificial hypocenter sets (S0 ~ S4) are located from the center of the network to the south with 1 km interval. Each hypocenter set contains 25 events placed on the plane. To quantify accuracies of the inversion results, we defined 6 parameters: difference between average hypocenters of assumed and inverted locations, $d_1$; ratio of assumed and inverted areas estimated by hypocenters, r; difference between dip of the reference plane and the best fitting plane for determined hypocenters, ${\theta}$; difference between strike of the reference plane and the best fitting plane for determined hypocenters, ${\phi}$; root-mean-square distance between hypocenters and the best fitting plane, $d_2$; root-mean-square error in horizontal direction on the best fitting plane, $d_3$. Synthetic travel times are calculated for the reference model having 1D layered structure and the inaccurate velocity model for the inversion is constructed by using normal distribution with standard deviations of 0.1, 0.2, and 0.3 km/s, respectively, with respect to the reference model. The parameters $d_1$, r, ${\theta}$, and $d_2$ show positive correlation with the level of velocity perturbations, but the others are not sensitive to the perturbations except S4, which is located at the outer boundary of the network. In cases of S0, S1, S2, and S3, hypoellipse and hypoDD provide similar results for $d_1$. However, for other parameters, hypoDD shows much better results and errors of locations can be reduced by about several meters regardless of the level of perturbations. In light of the purpose to understand the characteristics of hydraulic fracturing, $1{\sigma}$ error of velocity structure should be under 0.2 km/s in hypoellipse and 0.3 km/s in hypoDD.

• Journal of Korean Society of Forest Science
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• v.98 no.6
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• pp.791-798
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• 2009

The role of forest and soil carbon under global climate change is getting important as a carbon sink and it is necessary to research on applicable forest models as well as in the field for a study of these dynamics. On this study, historical annual litter dataset as a major input data for the forest soil carbon model, Yasso was established using a dendrochronological reconstruction method, and the soil carbon dynamics of a Pinus densiflora forest in Gwangneung, Korea was simulated using Yasso. The amount of litter (needle, branch, stem and fine root) production, which was estimated using the dendrochronological method, has increased continuously from 1971 to 2006. Furthermore, there was no significant error between estimated and measured values of litter production (needle and branch) in 2006. The average of simulated soil carbon stock up to 30 cm depth was $46.30{\pm}4.28tCha^{-1}$, which accounted for 53% of carbon stock in trees of the forest, and had no significant difference and error with measured soil carbon stock. Under the climate change trend in Korea according to IPCC A1B scenario, it was estimated that the simulated soil carbon stock in the region would increase continuously from 1971 to 2041 and then decreased until 2100. Compared to the result of the scenario that there is no climate change, the soil carbon stock could be decreased up to 7.58% at 2100. It was inferred the dendrochronological reconstruction method and simulation of Yasso model are useful to estimate soil carbon dynamics of the natural P. densiflora forest. Follow-up researches, such as improvement of the dendrochronological method and Yasso model and their application and validation in various environment, are needed to produce more reliable results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.87-95
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• 2016

This study examined the characteristics of the hourly demand of city gas in Korea and proposed multiple regression models to obtain precise estimates of the hourly demand of city gas. Forecasting the hourly demand of city gas with accuracy is essential in terms of safety and cost. If underestimated, the pipeline pressure needs to be increased sharply to meet the demand, when safety matters. In the opposite case, unnecessary inventory and operation costs are incurred. Data analysis showed that the hourly demand of city gas has a very high autocorrelation and that the 24-hour demand pattern of a day follows the previous 24-hour demand pattern of the same day. That is, there is a weekly cycle pattern. In addition, some conditions that temperature affects the hourly demand level were found. That is, the absolute value of the correlation coefficient between the hourly demand and temperature is about 0.853 on average, while the absolute value of the correlation coefficient on a specific day improves to 0.861 at worst and 0.965 at best. Based on this analysis, this paper proposes a multiple regression model incorporating the hourly demand ahead of 24 hours and the hourly demand ahead of 168 hours, and another multiple regression model with temperature as an additional independent variable. To show the performance of the proposed models, computational experiments were carried out using real data of the domestic city gas demand from 2009 to 2013. The test results showed that the first regression model exhibits a forecasting accuracy of MAPE (Mean Absolute Percentage Error) around 4.5% over the past five years from 2009 to 2013, while the second regression model exhibits 5.13% of MAPE for the same period.

• Journal of radiological science and technology
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• v.34 no.4
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• pp.277-285
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• 2011

To determine the quality control of UGIS, we acquired 105 patients sampling image at 21 general screening centers. The results of image quality evaluation table containing two countries's UGIS showed that the mean of image qualified education table of our country was 73.3 and the standard error was 4.49; In addition, 19 organizations of 21 general screening centers were given appropriate judgement. The average of image qualified education table of Japan was 58 and the standard error was 4.45. Only 8 organizations were given appropriate judgement. Although we made the image quality evaluation tables with same images, there were many differences in the result of two tables. We figured out the problem about the description of whole stomach and photograph skills. Furthermore, we analysed the situation of the UGIS at each general screening center with the acquired images. The biggest problem of the UGIS of our country was that the procedures were performed without clear medical methods. Methods of UGIS were different at every 21 general screening centers, and most of them did not take exam of anterior surface of stomach of the UGIS. In addition, some general screening centers did not include mucosal relief method or esophagography which is required to include in the image qualified education table of our country. Because polisography is used in the same body position, the problem occured about indiscreet exposure dose of patients. Therefore we have to make an effort to get X-ray images which have enough diagnosis information by the quality control of UGIS.

• Journal of Korea Water Resources Association
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• v.47 no.6
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• pp.537-546
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• 2014

Surface image velocimetry was introduced as an efficient and sage alternative to conventional river flow measurement methods during floods. The conventional surface image velocimetry uses a pair of images to estimate velocity fields using cross-correlation analysis. This method is appropriate to analyzing images taken with a short time interval. It, however, has some drawbacks; it takes a while to analyze images for the verage velocity of long time intervals and is prone to include errors or uncertainties due to flow characteristics and/or image taking conditions. Methods using spatio-temporal images, called STIV, were developed to overcome the drawbacks of conventional surface image velocimetry. The grayscale-gradient tensor method, one of various STIVs, has shown to be effectively reducing the analysis time and is fairly insusceptible to any measurement noise. It, unfortunately, can only be applied to the main flow direction. This means that it can not measure any two-dimensional flow field, e.g. flow in the vicinity of river structures and flow around river bends. The present study aimed to develop a new method of analyzing spatio-temporal images in two-dimension using cross-correlation analysis. Unlike the conventional STIV, the developed method can be used to measure two-dimensional flow substantially. The method also has very high spatial resolution and reduces the analysis time. A verification test using artificial images with lid-driven cavity flow showed that the maximum error of the method is less than 10 % and the average error is less than 5 %. This means that the developed scheme seems to be fairly accurate, even for two-dimensional flow.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.147-157
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• 2010

With the immergence of the iPhone, the interest in Smartphones is getting higher as services can be provided directly between service providers and consumers without the network operators. As the number of international tourists increase, individual tourists are also increasing. According to the WTO's (World Tourism Organization) prediction, the number of international tourists will be 1.56 billion in 2020,and the average growth rate will be 4.1% a year. Chinese tourists, in particular, are increasing rapidly and about 100 million will travel the world in 2020. In 2009, about 7.8 million foreign tourists visited Korea and the Ministry of Culture, Sports and Tourism is trying to attract 12 million foreign tourists in 2014. A research institute carried out a survey targeting foreign tourists and the survey results showed that they felt uncomfortable with communication (about 55.8%) and directional signs (about 21.4%) when they traveled in Korea. To solve this inconvenience for foreign tourists, multilingual servicesfor traffic signs, tour information, shopping information and so forth should be enhanced. The appearance of the Smartphone comes just in time to provide a new service to address these inconveniences. Smartphones are especially useful because every Smartphone has GPS (Global Positioning System) that can provide users' location to the system, making it possible to provide location-based services. For improvement of tourists' convenience, Seoul Metropolitan Government hasinitiated the u-tour service using Kiosks and Smartphones, and several Province Governments have started the u-tourpia project using RFID (Radio Frequency IDentification) and an exclusive device. Even though the u-tour or u-tourpia service used the Smartphone and RFID, the tourist should know the location of the Kiosks and have previous information. So, this service did not give the solution yet. In this paper, I developed a new convenient service which can provide location based information for the individual tourists using GPS, WiFi, and 3G. The service was tested at Insa-dong in Seoul, and the service can provide tour information around the tourist using a push service without user selection. This self-tour service is designed for providing a travel guide service for foreign travelers from the airport to their destination and information about tourist attractions. The system reduced information traffic by constraining receipt of information to tourist themes and locations within a 20m or 40m radius of the device. In this case, service providers can provide targeted, just-in-time services to special customers by sending desired information. For evaluating the implemented system, the contents of 40 gift shops and traditional restaurants in Insa-dong are stored in the CMS (Content Management System). The service program shows a map displaying the current location of the tourist and displays a circle which shows the range to get the tourist information. If there is information for the tourist within range, the information viewer is activated. If there is only a single resultto display, the information viewer pops up directly, and if there are several results, the viewer shows a list of the contents and the user can choose content manually. As aresult, the proposed system can provide location-based tourist information to tourists without previous knowledge of the area. Currently, the GPS has a margin of error (about 10~20m) and this leads the location and information errors. However, because our Government is planning to provide DGPS (Differential GPS) information by DMB (Digital Multimedia Broadcasting) this error will be reduced to within 1m.