• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.4
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• pp.723-733
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• 2016

This study aims to analyze the effects of urban characteristics on the amount of damage caused by natural disasters. It is focused on the areas of a municipal level in Korea. Also, it takes into account the spatial autocorrelation of the damage caused by natural disasters. Moran's I statistics was estimated to examine the spatial autocorrelation in the damage from the study area. Subsequent to evaluating the suitability for spatial regression models and the OLS regression model, the spatial lag model was employed as an empirical analysis for the study. It showed that the increase in residential area leads to the decrease in the amount of natural disaster damage. On the other hand, the increase in green area and river basin is associated with the increase in the damage. As a result of empirical analysis, appropriate policy establishment and implementation about the damage-adding factors is needed in order to reduce the amount of damage in the future.

• Journal of Mushroom
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• v.13 no.2
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• pp.114-118
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• 2015

Mycoleptodonoides aitchisonii has been used a culinary material and traditional medicine for a long time in worldwide and recently the researches to find biological effects have been increased such as dopamine activation, preventive effect against phytopathogens, inhibitive effect against erythrocyte coagulation, anti-oxidative effect, anti-tumorigenic effect, etc. However it is hard to cultivate Mycoleptodonoides aitchisonii it is impossible to be mass-produced and in order to solve the problem in this study we found the appropriate cultivation period and the harvest point for it. For life cycle (from primordium formation to harvest) the morphology, weight, and quantity of polysaccharide of Mycoleptodonoides aitchisonii were measured using with 5 bodies per a day and it could be divided for 4 stages; primordium formation, growth, needle maturation, and aging. And then from the results the Zeide nonlinear growth curve could be gotten. At 13th day after cultivation there is the relation between the change of media weight and body weight and at 14th day after cultivation the rate of polysaccharide in the body was 11 %. However in the case of O2 insufficient supply the malformation of them was observed.

• Journal of the Korean Society of Radiology
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• v.12 no.3
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• pp.351-357
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• 2018

During radiation therapy, the patient is exposed to secondary radiation by scattered and leakage radiation. For the diagnostic radiation, guidelines for reducing the patient's exposure as the diagnostic reference level are provided. However, in the case of therapeutic radiation, even though the radiation dose by the secondary radiation is considerable, the prescription dose is not limited because of the reason of the therapeutic efficiency. The purpose of this study was to evaluate the secondary radiation that the patient could be received at the peripheral tissue during the radiotherapy using the linear accelerator with the radiophotoluminescent glass dosimeter. In addition, we measured the degree of saturation of the luminescent amount according to the build-up characteristic of the radiophotoluminescent glass dosimeter. As a result of carrying out this study, the exposure dose decreased drastically farther away from the treatment field. When the head was irradiated with 1 Gy, the neck could be exposed to 18.45 mGy. When the same dose was irradiated at the neck, 15.55 mGy of the head and irradiated at the chest, 14.26 mGy of the neck and irradiated at the pelvis, 1.14 mGy of the chest were exposed separately. The degree of saturation of the luminescent intensity could be overestimated by 1.8 ~ 4.8% depending on time interval for 3 days.

• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.17-30
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• 2002

Incident duration prediction is one of the most important steps of the overall incident management process. An accurate and reliable estimate of the incident duration can be the main difference between an effective incident management operation and an unacceptable one since, without the knowledge of such time durations, traffic impact can not be estimated or calculated. This research presents several multiple linear regression models for incident duration prediction using data consisting of 384 incident cases. The main source of various incident cases was the Traffic Incident Reports filled out by the Motorist Assistant Units of the Korea Highway Corporation. The models were proposed separately according to the time of day(daytime vs. nighttime) and the fatality/injury incurred (fatality/injury vs. property damage only). Two models using an integrated dataset, one with an intercept and the other without it, were also calibrated and proposed for the generality of model application. Some findings are as follows ; ?Variables such as vehicle turnover, load spills, the number of heavy vehicles involved and the number of blocked lanes were found to significantly affect incident duration times. ?Models, however, tend to overestimate the duration times when a dummy variable, load spill, is used. It was simply because several of load spill incidents had excessively long clearance times. The precision was improved when load spills were further categorized into "small spills" and "large spills" based on the size of vehicles involved. ?Variables such as the number of vehicles involved and the number of blocked lanes found not significant when a regression model was calibrated with an intercept. whereas excluding the intercept from the model structure signifies those variables in a statistical sense.

• Journal of Korean Society of Transportation
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• v.34 no.3
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• pp.278-290
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• 2016

Maximum traffic flow rate is an important performance measure of operational status in transport networks, and has been considered as a key parameter for transportation operation since a bottleneck in congestion decreases maximum traffic flow rate. Although previous studies for traffic flow analysis have been widely conducted, a detection method for changes in dynamic traffic flow has been still veiled. This paper explores the dynamic traffic flow detection that can be utilized for various traffic operational strategies. Turning point analysis (TPA), as a statistical method, is applied to detect the changes in traffic flow rate. In TPA, Bayesian approach is employed and vehicle arrival is assumed to follow Poisson distribution. To examine the performance of the TPA method, traffic flow data from Jayuro urban expressway were obtained and applied. We propose a novel methodology to detect turning points of dynamic traffic flow in real time using TPA. The results showed that the turning points identified in real-time detected the changes in traffic flow rate. We expect that the proposed methodology has wide application in traffic operation systems such as ramp-metering and variable lane control.

• Journal of Technology Innovation
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• v.24 no.4
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• pp.221-248
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• 2016

In this study, we conducted an in-depth literature review of the innovation characteristics of nuclear technology. We understood that the main issue may be a transition of fourth generation nuclear energy technology. We also analyzed a present status of Korean policy on nuclear energy technology and identified some implications for a successful settlement of the fourth generation nuclear energy technology. This study could provide some policy implications for maintaining the sustainable competitiveness of the fourth generation nuclear energy technology in Korea. According to our study, the factors that influence on a transition of nuclear energy technology are a policy-induced market for technical application and demonstration, stable and long-term resource allocation, constant interaction among stakeholders of innovation, accumulation of skill and know-how for an entire system. In addition, we conducted a case analysis on policy for Korean fourth generation nuclear energy technology. According to this case study, it would be necessary for Korea to pursue systematic training of human resources, active response to a social acceptance and reaction, establishment of specific plan for technical demonstration, long-term policy suggestion, and active promotion of constant interaction between stakeholders.

• Journal of Technology Innovation
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• v.27 no.4
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• pp.21-48
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• 2019

In the basic research field, quantitative expansion is carried out with active support from the government, but there is no research and policy data suggesting systematic investment plans or data-based financial requirements yet. Therefore, this study predicted future financial requirements of basic research support programs by using time series prediction model. In order to consider various factors including the characteristics of the basic research field, we selected the ARIMAX model which can reflect the effect of multi valuable factors rather than the ARIMA model which predicts the value of single factor over time. We compared the predictions of ARIMAX and ARIMA models for model suitability and found that the ARIMAX model improves the prediction error rate. Based on the ARIMAX model, we predicted the fiscal spending of basic research support programs for five years from 2017 to 2021. This study has significance in that it considers the financial requirements of the basic research support programs as a pilot research conducted by applying a time series model, which is a statistical approach, and multi-variate rather than single-variate. In addition, considering the policy trends that emphasize the importance of basic research investment such as 'the expansion of basic research budget twice', which is the current government's national policy task, it can be used as reference data in establishing basic research investment strategy.

• Journal of the Korean Wood Science and Technology
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• v.48 no.2
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• pp.121-135
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• 2020

This study aims to evaluate applicability for the continuous drying process using saturated and superheated steam for large-square timber. During drying of the boxed heart square timber, changes in moisture content were examined through the slices of the surface, inner and core layers. The results showed that there was a large moisture content difference between the surface and inner layers during saturated steam drying and between the inner and core layers during superheated steam drying. However, despite the moisture content difference between the layers, no surface check occurred, and an internal check occurred only near the pith or juvenile parts of the wood. The maximum value of the drying stress of the dried larch boxed heart square timber, calculated from the elastic strain of the slice and the tangential elastic modulus of the larch, was 1.30 MPa. The tangential tensile strength of the larch was estimated at 5.21 MPa under temperature and moisture content conditions when drying stress was at a maximum. That is, in the continuous drying process, the saturated and superheated steam did not generate a check in the surface because the drying stress of the wood did not exceed the tangential tensile strength. In further studies, the superheated steam drying conditions will need to be relaxed to suppress the occurrence of internal checks. Such studies would make the continuous drying process using saturated and superheated steam available for the drying of large-square timber.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.3
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• pp.303-314
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• 2020

The hydrological characteristics of watersheds and hydraulic systems of urban and river floods are highly nonlinear and contain uncertain variables. Therefore, the predicted time series of rainfall-runoff data in flood analysis is not suitable for existing neural networks. To overcome the challenge of prediction, a NARX (Nonlinear Autoregressive Exogenous Model), which is a kind of recurrent dynamic neural network that maximizes the learning ability of a neural network, was applied to forecast a flood in real-time. At the same time, NARX has the characteristics of a time-delay neural network. In this study, a hydrological model was constructed for the Taehwa river basin, and the NARX time-delay parameter was adjusted 10 to 120 minutes. As a result, we found that precise prediction is possible as the time-delay parameter was increased by confirming that the NSE increased from 0.530 to 0.988 and the RMSE decreased from 379.9 ㎥/s to 16.1 ㎥/s. The machine learning technique with NARX will contribute to the accurate prediction of flow rate with an unexpected extreme flood condition.

• The Journal of the Korea Contents Association
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• v.17 no.3
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• pp.42-52
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• 2017

Panorama image is a single image obtained by combining images taken at several viewpoints through matching of corresponding points. Existing panoramic image generation methods that find the corresponding points are extracting local invariant feature points in each image to create descriptors and using descriptor matching algorithm. In the case of video sequence, frames may be a lot, so therefore it may costs significant amount of time to generate a panoramic image by the existing method and it may has done unnecessary calculations. In this paper, we propose a method to quickly create a single panoramic image from a video sequence. By assuming that there is no significant changes between frames of the video such as in locally, we use the FAST algorithm that has good repeatability and high-speed calculation to extract feature points and the Lucas-Kanade algorithm as each feature point to track for find the corresponding points in surrounding neighborhood instead of existing descriptor matching algorithms. When homographies are calculated for all images, homography is changed around the center image of video sequence to warp images and obtain a planar panoramic image. Finally, the spherical panoramic image is obtained by performing inverse transformation of the spherical coordinate system. The proposed method was confirmed through the experiments generating panorama image efficiently and more faster than the existing methods.