• Journal of the Korean Society for Marine Environment & Energy
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• v.10 no.4
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• pp.187-192
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• 2007

Impact on cylindrical surface caused by plunging breaking waves is investigated experimentally. The breaking waves are generated in a wave flume by decreasing the wave maker frequencies linearly and focusing the generated wave components at one specific location. The breaking wave packets are based on constant wave steepness spectrum. Three inclination angles of cylinder are applied to examine the effect of contact angle between cylinder and front surface of breaking waves. Also, the effect of cylinder diameter on pressure distribution and its peak value is investigated by adopting three cylinders with different diameters. The longitudinal location of cylinder is slightly moved in eight different points to find out a probable maximum value of impact pressure. The pressures and total force on cylinder surface are measured by piezo-electric pressure sensors and 3-components load cell with 30kHz sampling rate. The variation of peak impact pressures and forces is analyzed in terms of cylinder diameter, inclination angle and location. Also, the pressure distribution on cylindrical surface is examined. The cylinder location and surface position are more important parameters that govern the magnitude and shape of peak pressures, while the cylinder diameter and inclined angle are relatively insignificant. In a certain conditions, the impact phenomenon becomes very unstable which results in a large variation of measured valves in repeated runs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.687-693
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• 2017

This research analyzed cell survival rate according to antioxidative effect and cytotoxicity using Sasa quelpaertensis and Ethanol extracts. Sasa quelpaertensis used extracts of $95^{\circ}C$ boiled-water extract and 70% ethanol liquid each. For total polyphenol content, tannin content, and flavonoid content, polyphenol content of $95^{\circ}C$ boiled-water extract was 26.6 mg/g while that of 70% ethanol extract liquid was 22.3 mg/g, which means polyphenol content was higher in $95^{\circ}C$ boiled-water extract. Tannin content was 72.1 mg/g in $95^{\circ}C$ boiled-water extract which was higher than 61.2 mg/g in 70% ethanol extract liquid. Total flavonoid content was higher in 70% ethanol extract liquid (25.4 mg/g) than in $95^{\circ}C$ boiled-water extract (17.8 mg/g). Further, the researcher measured DPPH radical elimination and ABTS radical elimination. As a result, as the concentration of each extract increased, DPPH radical elimination and ABTS radical elimination increased. In the DPPH radical elimination, L-ascorbic acid was eliminated at 500 ppm and showed no change even though the concentration increased, whereas it increased in BHT and Sasa quelpaertensis leaf extracts according to concentration. ABTS radical elimination indicated the similar phenomenon, whereas BHT showed maximum elimination at 500 ppm and decreased gradually as the concentration increased. On the other hand, it gradually increased in Sasa quelpaertensis leaf extract and showed 90% elimination at 10,000 pm, and it increased in $95^{\circ}C$ boiled-water extract. Using human skin fibroblasts (3T3) to check the cell survival rate of Sasa quelpaertensis leaves showed that cell survival rate decreased between 85.6 and 66.6% in $95^{\circ}C$ boiled-water extract. The cell survival rate was between 95.4 and 92.1% when using 70% ethanol extracts. Sasa quelpaertensis has efficacy as a natural antioxidant as well as a material hyangjang.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.94-100
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• 2010

Purpose: We can evaluate function of kidney by Glomerular Filtration Rate (GFR) test using $^{99m}Tc$-DTPA which is simple. This test is influenced by several parameter such as net syringe count, kidney depth, corrected kidney count, acquisition time and characters of gamma camera. In this study, we evaluated predose count according to matrix size in the GFR test using $^{99m}Tc$-DTPA. Materials and Methods: Gamma camera of Infinia in GE was used, and LEGP collimator, three types of matrix size ($64{\times}64$, $128{\times}128$, $256{\times}256$) and 1.0 of zoom factor were applied. We increased radioactivity concentration from 222 (6), 296 (8), 370 (10), 444 (12) up to 518 MBq (14 mCi) respectively and acquired images according to matrix size at 30 cm distance from detector. Lastly, we evaluated these values and then substituted them for GFR formula. Results: In $64{\times}64$, $128{\times}128$ and $256{\times}256$ of matrix size, counts per second was 26.8, 34.5, 41.5, 49.1 and 55.3 kcps, 25.3, 33.4, 41.0, 48.4 and 54.3 kcps and 25.5, 33.7, 40.8, 48.1 and 54.7 kcps respectively. Total counts for 5 second were 134, 172, 208, 245 and 276 kcounts from $64{\times}64$, 127, 172, 205, 242, 271 kcounts from $128{\times}128$, and 137, 168, 204, 240 and 273 kcounts from $256{\times}256$, and total counts for 60 seconds were 1,503, 1,866, 2,093, 2,280, 2,321 kcounts, 1,511, 1,994, 2,453, 2,890 and 3,244 kcounts, and 1,524, 2,011, 2,439, 2,869 and 3,268 kcounts respectively. It is different from 0 to 30.02 % of percentage difference in $64{\times}64$ of matrix size. But in $128{\times}128$ and $256{\times}256$, it is showed 0.60 and 0.69 % of maximum value each. GFR of percentage difference in $64{\times}64$ represented 6.77% of 222 MBq (6 mCi), 42.89 % of 518 MBq (14 mCi) at 60 seconds respectively. However it is represented 0.60 and 0.63 % each in $128{\times}128$ and $256{\times}256$. Conclusion: There was no big difference in total counts of percentage difference and GFR values acquiring from $128{\times}128$ and $256{\times}256$ of matrix size. But in $64{\times}64$ of matrix size when the total count exceeded 1,500 kcounts, the overflow phenomenon was appeared differently according to predose radioactivity of concentration and acquisition time. Therefore, we must optimize matrix size and net syringe count considering the total count of predose to get accurate GFR results.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.101-124
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• 2018

Recently, most of the technologies have been developed in various forms through the advancement of single technology or interaction with other technologies. Particularly, these technologies have the characteristic of the convergence caused by the interaction between two or more techniques. In addition, efforts in responding to technological changes by advance are continuously increasing through forecasting promising convergence technologies that will emerge in the near future. According to this phenomenon, many researchers are attempting to perform various analyses about forecasting promising convergence technologies. A convergence technology has characteristics of various technologies according to the principle of generation. Therefore, forecasting promising convergence technologies is much more difficult than forecasting general technologies with high growth potential. Nevertheless, some achievements have been confirmed in an attempt to forecasting promising technologies using big data analysis and social network analysis. Studies of convergence technology through data analysis are actively conducted with the theme of discovering new convergence technologies and analyzing their trends. According that, information about new convergence technologies is being provided more abundantly than in the past. However, existing methods in analyzing convergence technology have some limitations. Firstly, most studies deal with convergence technology analyze data through predefined technology classifications. The technologies appearing recently tend to have characteristics of convergence and thus consist of technologies from various fields. In other words, the new convergence technologies may not belong to the defined classification. Therefore, the existing method does not properly reflect the dynamic change of the convergence phenomenon. Secondly, in order to forecast the promising convergence technologies, most of the existing analysis method use the general purpose indicators in process. This method does not fully utilize the specificity of convergence phenomenon. The new convergence technology is highly dependent on the existing technology, which is the origin of that technology. Based on that, it can grow into the independent field or disappear rapidly, according to the change of the dependent technology. In the existing analysis, the potential growth of convergence technology is judged through the traditional indicators designed from the general purpose. However, these indicators do not reflect the principle of convergence. In other words, these indicators do not reflect the characteristics of convergence technology, which brings the meaning of new technologies emerge through two or more mature technologies and grown technologies affect the creation of another technology. Thirdly, previous studies do not provide objective methods for evaluating the accuracy of models in forecasting promising convergence technologies. In the studies of convergence technology, the subject of forecasting promising technologies was relatively insufficient due to the complexity of the field. Therefore, it is difficult to find a method to evaluate the accuracy of the model that forecasting promising convergence technologies. In order to activate the field of forecasting promising convergence technology, it is important to establish a method for objectively verifying and evaluating the accuracy of the model proposed by each study. To overcome these limitations, we propose a new method for analysis of convergence technologies. First of all, through topic modeling, we derive a new technology classification in terms of text content. It reflects the dynamic change of the actual technology market, not the existing fixed classification standard. In addition, we identify the influence relationships between technologies through the topic correspondence weights of each document, and structuralize them into a network. In addition, we devise a centrality indicator (PGC, potential growth centrality) to forecast the future growth of technology by utilizing the centrality information of each technology. It reflects the convergence characteristics of each technology, according to technology maturity and interdependence between technologies. Along with this, we propose a method to evaluate the accuracy of forecasting model by measuring the growth rate of promising technology. It is based on the variation of potential growth centrality by period. In this paper, we conduct experiments with 13,477 patent documents dealing with technical contents to evaluate the performance and practical applicability of the proposed method. As a result, it is confirmed that the forecast model based on a centrality indicator of the proposed method has a maximum forecast accuracy of about 2.88 times higher than the accuracy of the forecast model based on the currently used network indicators.

• Journal of the Korean earth science society
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• v.23 no.3
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• pp.280-293
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• 2002

In this study, we analyzed the long-term distribution patterns of $CH_4$ determined from the Moo-Ahn (MAN) observatory in relation with those derived from the world major background monitoring sites. Comparison of the data were made using those data sets collected for the period between Aug. 1995 to Dec. 1991. The mean $CH_4$ concentration of MAN observatory was measured to be 1898${\pm}$85.3 ppb, recording the highest concentration of all the monitoring sites. When the concentration of $CH_4$ for different stations was compared over latitudinal scale, its concentration appeared to increase systematically as a function of latitude with an exception of MAN (and the other Korean monitoring site at Tae Ahn). Moreover, such phenomenon was more distinctive in Northern than Southern Hemisphere. According to the analysis of the monthly distribution patterns of $CH_4$ at MAN observatory, its concentration level began to increase from the months of February/March and peaked during August. In addition, when the level of oscillation in monthly concentrations (between the maximum and minimum values) was checked, differences were significant between MAN and other monitoring stations. If the rate of concentration change was checked using the data sets collected for this limited time period in terms of linear regression analysis, results for MAN showed the highest annual increasing rate of 16.5 ppb. It is hence suggested that the largest variability in the $CH_4$ distribution patterns at MAN observatory may be reflected by the high irregularity in its source/sink processes.

• Journal of the Korean Geotechnical Society
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• v.29 no.9
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• pp.5-15
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• 2013

In this paper, the unsaturated slope stability analysis considering suction stress (Lu and Godt, 2008) was introduced and the results applied for a certain sand slope were analyzed. The unsaturated slope stability analysis considering suction stress can analyze both conditions of steady infiltration and no infiltration, and it can estimate the safety factor of slope as a function of soil depth. Also, the influence of weathering phenomenon at a certain depth from the ground surface can be considered. The stability analysis considering suction stress was applied to the unsaturated infinite slope composed of sand with the relative density of 60%. The suction stress under no infiltration condition was affected by ground water table until a certain influencing depth. However, the suction stress under steady infiltration condition was affected by seepage throughout the soils. Especially, the maximum suction stress was displayed around ground surface. The factor of safety in the infinite slope under no infiltration condition rapidly increased and decreased within the influence zone of ground water table. As a result of slope stability analysis, the factor of safety is less than 1 at the depth of 2.4 m below the ground surface. It means that the probability of slope failure is too high within the range of depths. The factor of safety under steady infiltration condition is greater than that under no infiltration condition due to the change of suction stress induced by seepage. As the steady infiltration rate of precipitation was getting closer to the saturated hydraulic conductivity, the factor of safety decreased. In case of the steady infiltration rate of precipitation with $-1.8{\times}10^{-3}cm/s$, the factor of safety is less than 1 at the depths between 0.2 m and 3 m below the ground surface. It means that the probability of slope failure is too high within the range of depths, and type of slope failure is likely to be shallow landslides.