• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.2
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• pp.33-51
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• 2022

This study analyzes newly listed companies on KOSDAQ from 2011 to 2020 for both firms having experience in attracting venture investment before listing (VI) and those without having experience in attracting venture investment (NVI) by examining differences between two groups (VI and NVI) with respect to both the level of listing performance and that of firm performance (growth) after the listing. This paper conducts descriptive statistics, mean difference, and multiple regression analysis. Independent variables for regression models include VC investment, firm age at the time of listing, firm type, firm location, firm size, the age of VC, the level of expertise of VC, and the level of fitness of VC with investment company. Throughout this paper, results suggest that listing performance and post-listed growth are better for VI than NVI. VC investment shows a negative effect on the listing period and a positive effect on the sales growth rate. Also, the amount of VC investment has negative effects on the listing period and positive effects on the market capitalization at the time of IPO and on sales growth among growth indicators. Our evidence also implies a significantly positive effect on growth after listing for firms which belong to R&D specialized industries. In addition, it is statistically significant for several years that the firm age has a positive effect on the market capitalization growth rate. This shows that market seems to put the utmost importance on a long-term stability of management capability. Finally, among the VC characteristics such as the age of VC, the level of expertise of VC, and the level of fitness of VC with investment company, we point out that a higher market capitalization tends to be observed at the time of IPO when the level of expertise of anchor VC is high. Our paper differs from prior research in that we reexamine the venture ecosystem under the outbreak of coronavirus disease 2019 which stimulates the degradation of the business environment. In addition, we introduce more effective variables such as VC investment amount when examining the effect of firm type. It enables us to indirectly evaluate the validity of technology exception policy. Although our findings suggest that related policies such as the technology special listing system or the injection of funds into the venture ecosystem are still helpful, those related systems should be updated in a more timely fashion in order to support growth power of firms due to the rapid technological development. Furthermore, industry specialization is essential to achieve regional development, and the growth of the recovery market is also urgent.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.423-446
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• 2023

Shield TBM tunnel linings are segmented into segments and rings. This study investigates the response characteristics of the stress and displacement of the segment lining under seismic waves through modeling that considers the interface behavior between segments by applying a shell interface element to the contact surface between segments and rings. And there is no management criteria for ovaling deformation of segment linings in Korea. So, this study the ovality criteria and meaning of segment lining. The results of study showed that the distribution patterns of stress and displacement under seismic waves were similar between continuous linings and segment linings. However, the maximum values of stress and displacement showed differences from segment linings. The stress distribution of the continuous lining modeled as a shell type has a stress distribution that has continuity in the 3D cylindrical shape, but the segment lining is concentrated outside the segment, and the largest stress occurs at the location where the contact surface between the segment and the ring is concentrated. This intermittent and localized stress distribution shows an increasing as the ovality of the lining increases at seismic waves. The ovality at which the increase in stress distribution begins to show irregularity and localization is about 150‰. Ovality of 150‰ is an unrealistic value that cannot represent actual lining deformation. Therefore, the ovality of the segment lining increase with depth, but it does not have a significant impact on the stability caused by seismic load.

• The Korean Journal of Petroleum Geology
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• v.8 no.1_2 s.9
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• pp.1-43
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• 2000

A comparison study for understanding a stratigraphic response to tectonic evolution of sedimentary basins in the Yellow Sea and adjacent areas was carried out by using an integrated stratigraphic technology. As an interim result, we propose a stratigraphic framework that allows temporal and spatial correlation of the sedimentary successions in the basins. This stratigraphic framework will use as a new stratigraphic paradigm for hydrocarbon exploration in the Yellow Sea and adjacent areas. Integrated stratigraphic analysis in conjunction with sequence-keyed biostratigraphy allows us to define nine stratigraphic units in the basins: Cambro-Ordovician, Carboniferous-Triassic, early to middle Jurassic, late Jurassic-early Cretaceous, late Cretaceous, Paleocene-Eocene, Oligocene, early Miocene, and middle Miocene-Pliocene. They are tectono-stratigraphic units that provide time-sliced information on basin-forming tectonics, sedimentation, and basin-modifying tectonics of sedimentary basins in the Yellow Sea and adjacent area. In the Paleozoic, the South Yellow Sea basin was initiated as a marginal sag basin in the northern margin of the South China Block. Siliciclastic and carbonate sediments were deposited in the basin, showing cyclic fashions due to relative sea-level fluctuations. During the Devonian, however, the basin was once uplifted and deformed due to the Caledonian Orogeny, which resulted in an unconformity between the Cambro-Ordovician and the Carboniferous-Triassic units. The second orogenic event, Indosinian Orogeny, occurred in the late Permian-late Triassic, when the North China block began to collide with the South China block. Collision of the North and South China blocks produced the Qinling-Dabie-Sulu-Imjin foldbelts and led to the uplift and deformation of the Paleozoic strata. Subsequent rapid subsidence of the foreland parallel to the foldbelts formed the Bohai and the West Korean Bay basins where infilled with the early to middle Jurassic molasse sediments. Also Piggyback basins locally developed along the thrust. The later intensive Yanshanian (first) Orogeny modified these foreland and Piggyback basins in the late Jurassic. The South Yellow Sea basin, however, was likely to be a continental interior sag basin during the early to middle Jurassic. The early to middle Jurassic unit in the South Yellow Sea basin is characterized by fluvial to lacustrine sandstone and shale with a thick basal quartz conglomerate that contains well-sorted and well-rounded gravels. Meanwhile, the Tan-Lu fault system underwent a sinistrai strike-slip wrench movement in the late Triassic and continued into the Jurassic and Cretaceous until the early Tertiary. In the late Jurassic, development of second- or third-order wrench faults along the Tan-Lu fault system probably initiated a series of small-scale strike-slip extensional basins. Continued sinistral movement of the Tan-Lu fault until the late Eocene caused a megashear in the South Yellow Sea basin, forming a large-scale pull-apart basin. However, the Bohai basin was uplifted and severely modified during this period. h pronounced Yanshanian Orogeny (second and third) was marked by the unconformity between the early Cretaceous and late Eocene in the Bohai basin. In the late Eocene, the Indian Plate began to collide with the Eurasian Plate, forming a megasuture zone. This orogenic event, namely the Himalayan Orogeny, was probably responsible for the change of motion of the Tan-Lu fault system from left-lateral to right-lateral. The right-lateral strike-slip movement of the Tan-Lu fault caused the tectonic inversion of the South Yellow Sea basin and the pull-apart opening of the Bohai basin. Thus, the Oligocene was the main period of sedimentation in the Bohai basin as well as severe tectonic modification of the South Yellow Sea basin. After the Oligocene, the Yellow Sea and Bohai basins have maintained thermal subsidence up to the present with short periods of marine transgressions extending into the land part of the present basins.

• Journal of Soil and Groundwater Environment
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• v.13 no.1
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• pp.1-12
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• 2008

The purpose of this study is to characterize the hydrogeochemical characteristics of hot spring waters and to interpret the source of noble gases and the geochemical environment of the hot spring waters distributed along the eastern area of the Korean peninsula. For this purpose, We carried out the chemical, stable isotopic and noble gas isotopic analyses for eleven hot spring water and fourteen hot spring gas samples collected from six hot spring sites. The hot spring waters except the Osaek hot spring water show the pH range of 7.0 to 9.1. However, the Osaek $CO_2$-rich hot spring water shows a weak acid of pH 5.7. The temperature of hot spring waters in the study area ranges from $25.7^{\circ}C$ to $68.3^{\circ}C$. Electrical conductivity of hot spring waters varies widely from 202 to $7,130{\mu}S/cm$. High electrical conductivity (av., $3,890{\mu}S/sm$) by high Na and Cl contents of the Haeundae and the Dongrae hot spring waters indicates that the hot spring waters were mixed with seawater in the subsurface thermal system. The type of hot springs in the viewpoint of dissolved components can be grouped into three types: (1) alkaline Na-$HCO_3$ type including sulfur gas of the Osaek, Baekam, Dukgu and Chuksan hot springs, and (2) saline Na-Cl type of the Haeundae and Dongrae hot springs, and (3) weak acid $CO_2$-rich Na-$HCO_3$ type of Osaek hot spring. Tritium ratios of the Haeundae and the Dongrae hot springs indicate different residence time in their aquifers of older water of $0.0{\sim}0.3$ TU and younger water of $5.9{\sim}8.8$ TU. The ${\delta}^{18}O$ and ${\delta}D$ values of hot spring waters indicate that they originate from the meteoric water, and that the values also reflect a latitude effect according to their locations. $^3He/^4He$ ratios of the hot spring waters except Osaek $CO_2$-rich hot spring water range from $0.1{\times}10^{-6}$ to $1.1{\times}10^{-6}$ which are plotted above the mixing line between air and crustal components. It means that the He gas in hot spring waters was originated mainly from atmosphere and crust sources, and partly from mantle sources. The Osaek $CO_2$-rich hot spring water shows $3.3{\times}10^{-6}$ in $^3He/^4He$ ratio that is 2.4 times higher than those of atmosphere. It provides clearly a helium source from the deep mantle. $^{40}Ar/^{36}Ar$ ratios of hot spring water are in the range of an atmosphere source.

• Journal of the korean academy of Pediatric Dentistry
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• v.26 no.2
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• pp.339-349
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• 1999

The dental structure substituted by restorative materials may produce discomfort resulting from hot or cold stimuli. To investigate the effects of this stimuli on the human teeth, thermal analysis was carried out by calculation of general heat conduction equation in a modeled tooth using numerical method. The method has been applied to axisymmetric and two-dimensional model, analyzing the effects of constant temperature $4^{\circ}C\;and\;60^{\circ}C$. That thermal shock was provided for 2 seconds and 4 seconds, respectively and recovered to normal condition of $20^{\circ}C$ until 10 seconds. The thermal behavior of tooth covered with a crown of gold or stainless steel was compared with that of tooth without crown. At the same time, the effects of restorative materials(amalgam, gold and zinc oxide-eugenol(ZOE)) on the temperature of PDJ(pulpo-dentinal junction) has been studied. The geometry used for thermal analysis so far has been limited to two-dimensional as well as axisymmetric tooth models. But the general restorative tooth forms a cross shaped cavity which is no longer two-dimensional and axisymmetric. Therefore, in this study, the three-dimensional model was developed to investigate the effect of shape and size of cavity. This three-dimensional model might be used for further research to investigate the effects of restorative materials and cavity design on the thermal behavior of the real shaped tooth. The results were as follows; 1. When cold temperature of $4^{\circ}C$ was applied to the surface of the restored teeth with amalgam for 2 seconds and recovered to ambient temperature of $20^{\circ}C$, the PDJ temperature decreased rapidly to $29^{\circ}C$ until 3 seconds and reached to $25^{\circ}C$ after 9 seconds. This temperature decreased rather slowly with stainless steel crown, but kept similar temperature within $1^{\circ}C$ differences. Using the gold as a restorative material, the PDJ temperature decreased very fast due to the high thermal conductivity and reached near to $25^{\circ}C$ but the temperature after 9 seconds was similar to that in the teeth without crown. The effects of coldness could be attenuated with the ZOE situated under the cavity. The low thermal conductivity caused a delay in temperature decrease and keeps $4^{\circ}C$ higher than the temperature of other conditions after 9 seconds. 2. The elapse time of cold stimuli was increased also until 4 seconds and recovered to $20^{\circ}C$ after 4 seconds to 9 seconds. The temperature after 9 seconds was about $2-3^{\circ}C$ lower than the temperature of 2 seconds stimuli, but in case of gold restoration, the high thermal conductivity of gold caused the minimum temperature of $21^{\circ}C$ after 5 seconds and got warm to $23^{\circ}C$ after 9 seconds. 3. The effects of hot stimuli was also investigated with the temperature of $60^{\circ}C$. For 2 seconds stimuli, the temperature increased to $40^{\circ}C$ from the initial temperature of $35^{\circ}C$ after 3 seconds of stimuli and decreased to $30^{\circ}C$ after 9 seconds in the teeth without crown. This temperature was sensitive to surface temperature in the teeth with gold restoration. It increased rapidly to $41^{\circ}C$ from the initial temperature of $35^{\circ}C$ after 2 seconds and decreased to $28^{\circ}C$ after 9 seconds, which showed $13^{\circ}C$ temperature variations for 9 seconds upon the surface temperature. This temperature variations were only in the range of $5^{\circ}C$ by using ZOE in the bottom of cavity and showed maximum temperature of $37^{\circ}C$ after 3 seconds of stimuli.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.59-77
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• 2012

This study focuses on predicting which firms will increase capital by issuing new stocks in the near future. Many stakeholders, including banks, credit rating agencies and investors, performs a variety of analyses for firms' growth, profitability, stability, activity, productivity, etc., and regularly report the firms' financial analysis indices. In the paper, we develop predictive models for rights issues using these financial analysis indices and data mining techniques. This study approaches to building the predictive models from the perspective of two different analyses. The first is the analysis period. We divide the analysis period into before and after the IMF financial crisis, and examine whether there is the difference between the two periods. The second is the prediction time. In order to predict when firms increase capital by issuing new stocks, the prediction time is categorized as one year, two years and three years later. Therefore Total six prediction models are developed and analyzed. In this paper, we employ the decision tree technique to build the prediction models for rights issues. The decision tree is the most widely used prediction method which builds decision trees to label or categorize cases into a set of known classes. In contrast to neural networks, logistic regression and SVM, decision tree techniques are well suited for high-dimensional applications and have strong explanation capabilities. There are well-known decision tree induction algorithms such as CHAID, CART, QUEST, C5.0, etc. Among them, we use C5.0 algorithm which is the most recently developed algorithm and yields performance better than other algorithms. We obtained data for the rights issue and financial analysis from TS2000 of Korea Listed Companies Association. A record of financial analysis data is consisted of 89 variables which include 9 growth indices, 30 profitability indices, 23 stability indices, 6 activity indices and 8 productivity indices. For the model building and test, we used 10,925 financial analysis data of total 658 listed firms. PASW Modeler 13 was used to build C5.0 decision trees for the six prediction models. Total 84 variables among financial analysis data are selected as the input variables of each model, and the rights issue status (issued or not issued) is defined as the output variable. To develop prediction models using C5.0 node (Node Options: Output type = Rule set, Use boosting = false, Cross-validate = false, Mode = Simple, Favor = Generality), we used 60% of data for model building and 40% of data for model test. The results of experimental analysis show that the prediction accuracies of data after the IMF financial crisis (59.04% to 60.43%) are about 10 percent higher than ones before IMF financial crisis (68.78% to 71.41%). These results indicate that since the IMF financial crisis, the reliability of financial analysis indices has increased and the firm intention of rights issue has been more obvious. The experiment results also show that the stability-related indices have a major impact on conducting rights issue in the case of short-term prediction. On the other hand, the long-term prediction of conducting rights issue is affected by financial analysis indices on profitability, stability, activity and productivity. All the prediction models include the industry code as one of significant variables. This means that companies in different types of industries show their different types of patterns for rights issue. We conclude that it is desirable for stakeholders to take into account stability-related indices and more various financial analysis indices for short-term prediction and long-term prediction, respectively. The current study has several limitations. First, we need to compare the differences in accuracy by using different data mining techniques such as neural networks, logistic regression and SVM. Second, we are required to develop and to evaluate new prediction models including variables which research in the theory of capital structure has mentioned about the relevance to rights issue.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.195-220
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• 2018

In this study, we conducted an empirical analysis of the factors that affect the change of Bitcoin Closing Price. Previous studies have focused on the security of the block chain system, the economic ripple effects caused by the cryptocurrency, legal implications and the acceptance to consumer about cryptocurrency. In various area, cryptocurrency was studied and many researcher and people including government, regardless of country, try to utilize cryptocurrency and applicate to its technology. Despite of rapid and dramatic change of cryptocurrencies' price and growth of its effects, empirical study of the factors affecting the price change of cryptocurrency was lack. There were only a few limited studies, business reports and short working paper. Therefore, it is necessary to determine what factors effect on the change of closing Bitcoin price. For analysis, hypotheses were constructed from three dimensions of consumer, industry, and macroeconomics for analysis, and time series data were collected for variables of each dimension. Consumer variables consist of search traffic of Bitcoin, search traffic of bitcoin ban, search traffic of ransomware and search traffic of war. Industry variables were composed GPU vendors' stock price and memory vendors' stock price. Macro-economy variables were contemplated such as U.S. dollar index futures, FOMC policy interest rates, WTI crude oil price. Using above variables, we did times series regression analysis to find relationship between those variables and change of Bitcoin Closing Price. Before the regression analysis to confirm the relationship between change of Bitcoin Closing Price and the other variables, we performed the Unit-root test to verifying the stationary of time series data to avoid spurious regression. Then, using a stationary data, we did the regression analysis. As a result of the analysis, we found that the change of Bitcoin Closing Price has negative effects with search traffic of 'Bitcoin Ban' and US dollar index futures, while change of GPU vendors' stock price and change of WTI crude oil price showed positive effects. In case of 'Bitcoin Ban', it is directly determining the maintenance or abolition of Bitcoin trade, that's why consumer reacted sensitively and effected on change of Bitcoin Closing Price. GPU is raw material of Bitcoin mining. Generally, increasing of companies' stock price means the growth of the sales of those companies' products and services. GPU's demands increases are indirectly reflected to the GPU vendors' stock price. Making an interpretation, a rise in prices of GPU has put a crimp on the mining of Bitcoin. Consequently, GPU vendors' stock price effects on change of Bitcoin Closing Price. And we confirmed U.S. dollar index futures moved in the opposite direction with change of Bitcoin Closing Price. It moved like Gold. Gold was considered as a safe asset to consumers and it means consumer think that Bitcoin is a safe asset. On the other hand, WTI oil price went Bitcoin Closing Price's way. It implies that Bitcoin are regarded to investment asset like raw materials market's product. The variables that were not significant in the analysis were search traffic of bitcoin, search traffic of ransomware, search traffic of war, memory vendor's stock price, FOMC policy interest rates. In search traffic of bitcoin, we judged that interest in Bitcoin did not lead to purchase of Bitcoin. It means search traffic of Bitcoin didn't reflect all of Bitcoin's demand. So, it implies there are some factors that regulate and mediate the Bitcoin purchase. In search traffic of ransomware, it is hard to say concern of ransomware determined the whole Bitcoin demand. Because only a few people damaged by ransomware and the percentage of hackers requiring Bitcoins was low. Also, its information security problem is events not continuous issues. Search traffic of war was not significant. Like stock market, generally it has negative in relation to war, but exceptional case like Gulf war, it moves stakeholders' profits and environment. We think that this is the same case. In memory vendor stock price, this is because memory vendors' flagship products were not VRAM which is essential for Bitcoin supply. In FOMC policy interest rates, when the interest rate is low, the surplus capital is invested in securities such as stocks. But Bitcoin' price fluctuation was large so it is not recognized as an attractive commodity to the consumers. In addition, unlike the stock market, Bitcoin doesn't have any safety policy such as Circuit breakers and Sidecar. Through this study, we verified what factors effect on change of Bitcoin Closing Price, and interpreted why such change happened. In addition, establishing the characteristics of Bitcoin as a safe asset and investment asset, we provide a guide how consumer, financial institution and government organization approach to the cryptocurrency. Moreover, corroborating the factors affecting change of Bitcoin Closing Price, researcher will get some clue and qualification which factors have to be considered in hereafter cryptocurrency study.

• MISULJARYO - National Museum of Korea Art Journal
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• v.104
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• pp.10-39
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• 2023

Seongjusa Temple was founded in Boryeong in Chungcheongnam-do Province by Monk Muyeom (800-888), better known as Nanghye Hwasang. After returning from studying in China, Muyeom stayed in the Silla capital city of Gyeongju for a period. He later settled in a temple that was managed by the descendants of Kim In-mun (629-694). He then restored a burned-out temple and opened it in 847 as a Seon (Zen) temple named Seongjusa. It prospered and grew to become a large-scale temple with several halls within its domains. The influence of Seongjusa in the region can be seen in the Historical Record of Seongjusa Temple on Sungamsan Mountain, which relates that there were seventy-three rooms within the domains of the temple. What is most notable in the record is that the temple is referred to as "栴檀林九間," which means either "a structure with nine rooms built with Chinese juniper wood" or "a place that houses Chinese juniper wood and has nine rooms." Regardless of the interpretation, Seongjusa Temple had a large amount of juniper wood. Around this time, the term "juniper" referred to the olibanum tree (Boswellia sacra) native to the islands of Java and Sumatra in Southeast Asia. It is presumed that at some point after the death of Jang Bogo, the maritime forces that controlled the southwestern coast of Korea may have acquired a large amount of Southeast Asian olibanum wood and offered it to Seongjusa Temple. During the reign of King Munseong, Kim Yang (808-857) patronized Seongjusa Temple and its head monk Muyeom, who enjoyed a lofty reputation in the region. He sought to strengthen his own position as a member of the royal lineage of King Muyeol and create a bridge between the royal family and Seongjusan Buddhist sect. The court of King Wonseong designated Seongjusa Temple as a regional base for the support of royal authority in an area where anti-royal sentiment remained strong. Monk Muyeom is believed to have created an iron Buddha to protect the temple, enlighten the people, and promote regional stability. Given that the Seongjusa community had expanded to include more than 2,000 followers, the iron Buddha at Seongjusa Temple would have been perceived as an image that rallied the local residents. It is assumed that there were two iron Buddhas at Seongjusa Temple. The surviving parts of these Buddhas and the size of their pedestals suggest that they were respectively enshrined in the Geumdang Main Hall and the Samcheonbuljeon Hall of Three Thousand Buddhas. It is presumed that the first iron Buddha in Geumdang was a large statue over two meters in height and the second one was medium-sized with the height over one meter. The Historical Record of Seongjusa Temple on Sungamsan Mountain contains the phrase "改創選法堂五層重閣" which indicates that a multistoried Geumdang was newly built to enshrine a large Buddha sculpture like the first iron Buddha when Seongjusa Temple was founded. Also, according to the Stele of Seongjusa Temple and the surviving finger fragments, the first Buddha was making the fear-not and wish-granting (abhayavarada) mudras. The main Buddha of Seongjusa Temple is possibly Nosana Buddha, just like the main Buddhas at the contemporaneous temples Silsangsa, Borimsa, and Samhwasa. Given that Monk Muyeom studied Hwaeom teachings in his early years and received royal patronage upon his return, it is believed that the retro tendencies of the Hwaeom school, centered on the royal family of the Silla Dynasty, were reflected in Seongjusa temple.

• Journal of radiological science and technology
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• v.31 no.1
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• pp.17-23
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• 2008

Purpose : Because there is a difference depending on the environment as for an inspection equipment the important part of bone density scan and the precision/accuracy of a tester, the management of quality must be made systematically. The equipment failure caused by overload effect due to the aged equipment and the increase of a patient was made frequently. Thus, the replacement of equipment and additional purchases of new bonedensity equipment caused a compatibility problem in tracking patients. This study wants to know whether the clinical changes of patient's bonedensity can be accurately and precisely reflected when used it compatiblly like the existing equipment after equipment replacement and expansion. Materials and methods : Two equipments of GE Lunar Prodigy Advance(P1 and P2) and the Phantom HOLOGIC Spine Road(HSP) were used to measure equipment precision. Each device scans 20 times so that precision data was acquired from the phantom(Group 1). The precision of a tester was measured by shooting twice the same patient, every 15 members from each of the target equipment in 120 women(average age 48.78, 20-60 years old)(Group 2). In addition, the measurement of the precision of a tester and the cross-calibration data were made by scanning 20 times in each of the equipment using HSP, based on the data obtained from the management of quality using phantom(ASP) every morning (Group 3). The same patient was shot only once in one equipment alternately to make the measurement of the precision of a tester and the cross-calibration data in 120 women(average age 48.78, 20-60 years old)(Group 4). Results : It is steady equipment according to daily Q.C Data with $0.996\;g/cm^2$, change value(%CV) 0.08. The mean${\pm}$SD and a %CV price are ALP in Group 1(P1 : $1.064{\pm}0.002\;g/cm^2$, $%CV=0.190\;g/cm^2$, P2 : $1.061{\pm}0.003\;g/cm^2$, %CV=0.192). The mean${\pm}$SD and a %CV price are P1 : $1.187{\pm}0.002\;g/cm^2$, $%CV=0.164\;g/cm^2$, P2 : $1.198{\pm}0.002\;g/cm^2$, %CV=0.163 in Group 2. The average error${\pm}$2SD and %CV are P1 - (spine: $0.001{\pm}0.03\;g/cm^2$, %CV=0.94, Femur: $0.001{\pm}0.019\;g/cm^2$, %CV=0.96), P2 - (spine: $0.002{\pm}0.018\;g/cm^2$, %CV=0.55, Femur: $0.001{\pm}0.013\;g/cm^2$, %CV=0.48) in Group 3. The average error${\pm}2SD$, %CV, and r value was spine : $0.006{\pm}0.024\;g/cm^2$, %CV=0.86, r=0.995, Femur: $0{\pm}0.014\;g/cm^2$, %CV=0.54, r=0.998 in Group 4. Conclusion: Both LUNAR ASP CV% and HOLOGIC Spine Phantom are included in the normal range of error of ${\pm}2%$ defined in ISCD. BMD measurement keeps a relatively constant value, so showing excellent repeatability. The Phantom has homogeneous characteristics, but it has limitations to reflect the clinical part including variations in patient's body weight or body fat. As a result, it is believed that quality control using Phantom will be useful to check mis-calibration of the equipment used. A value measured a patient two times with one equipment, and that of double-crossed two equipment are all included within 2SD Value in the Bland - Altman Graph compared results of Group 3 with Group 4. The r value of 0.99 or higher in Linear regression analysis(Regression Analysis) indicated high precision and correlation. Therefore, it revealed that two compatible equipment did not affect in tracking the patients. Regular testing equipment and capabilities of a tester, then appropriate calibration will have to be achieved in order to calculate confidential BMD.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.18
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• pp.88-123
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• 1975

To obtain useful fundamental informations for improving cultural practices of barley, an investigation was made on the influences of different fertilizer level and seeding rate as well as seeding date on yield and yield components and their balancing procedure using barley variety Suwon ＃ 18, and at the same time, 8 varieties including Suwon ＃ 18 were also tested to clarify the varietal responses in terms of their yield and yield components under different seeding date at Crop Experiment Station, Suwon, during the period of 1969 and 1970. The results obtained were summarized as follows; 1. Days to emergence of barley variety Suwon ＃ 18 at Suwon, took 8 to 19 days in accordance with given different seeding date (from Sept. 21 to Oct. 31). Earlier emergence was observed by early seeding and most of the seeds were emerged at 15$0^{\circ}C$ cumulated soil temperature at 5cm depth from surface under the favorable condition. 2. Degree of cold injury in different seeding date was seemed to be affected by the growth rate of seedlings and climatic condition during the wintering period. Over growth and number of leaves less than 5 to 6 on the main stem before wintering were brought in severe cold damage during the wintering period. 3. Even though the number of leaves on the main stem were variable from 11 to 16 depending upon the seeding date. this differences were occurred before wintering and less variation was observed after wintering. Particularly, differences of the number of main stem leaves from September 21 to October 11 seeding date were occurred due to the differences of number of main stem leaves before wintering. 4. Dry matter accumulation before wintering was high in early seeded plot and gradually decreased in accordance with delayed seeding date and less different in dry matter weight was observed after wintering. However, the increment rate of this dry matter was high from regrowth to heading time and became low during the ripening period. 5. Number of tillers per $\m^2$ was higher in early seeding than late one and dense planting was higher in the number of tillers than sparse planting. Number of tillers per plant was lower in number and variation in dense planting, and reverse tendency was observed in sparse planting. By increasing seedling rate in early seeding date the number of tiller per plant was remarkably decreased, but the seeding rate didn't affect the individual tillering capacity in the late seeding date. 6. Seedlings were from early planting reached maximum tillering stage earlier than those from the late planting and no remarkable changes was observed due to increased seeding rate. However. increased seeding rate tends to make it earlier the maximum tillering stage early. 7. Stage of maximum tillering was coincided with stage of 4-5 main stem leaves regardless the seeding date. 8. Number of heads per $\m^2$ was increased with increased seeding rate but considerable year variation in number of heads was observed by increased fertilizer level. Therefore, it was clear that there is no difficulties in increasing number of heads per $\m^2$ through increasing both fertilizer level and seeding rate. This type of tendency was more remarkable at optimum seeding time. In the other hand, seeding at optimum time is more important than increasing seeding rate, but increasing seeding rate was more effective in late seeding for obtaining desirable number of heads per $\m^2$. 9. Number of heads per $\m^2$ was decreased generally in all varieties tested in late seeding, but the degree of decrease by late seeding was lower in Suwon ＃ 18. Yuegi, Hangmi and Buheung compared with Suwon ＃ 4, Suwon ＃ 6, Chilbo and Yungwolyukak. 10. Highly significant positive correlations were obtained between number of head and tillers per $\m^2$ from heading date in September 21 seeding, from before-wintering in October 1 seeding and in all growth period from October 11 to October 31 seeding. However, relatively low correlation coefficient was estimated between number of heads and tillers counted around late March to early April in any seeding date. 11. Valid tiller ratio varied from 33% to 76% and highest yield was obtained when valid tiller ratio was about 50%. Therefore, variation of valid tiller ratio was greater due to seeding date differences than due to seeding rate. Early seeding decreased the valid tiller ratio and gradually increased by delaying seeding date but decreased by increasing seeding rate. Among the varieties tested Suwon ＃ 18, Hangmi, Yuegi as well as Buheung should be high valid tiller ratio not only in late seeding but also in early seeding. In contrast to this phenomena, Chilbo, Suwon ＃ 4, Suwon ＃ 6 and Yungwolyukak expressed low valid tiller ratio in general, and also exhibited the same tendency in late seeding date. 12. Number of grains per spike was increased by increasing fertilizer level and decreased by increasing seeding rate. Among the seeding date tested. October 21 (1969) and October 11 (1970) showed lowest number of grains per spike which was increased in both early seeding and late seeding date. There were no definite tendencies observed along with seeding date differences in respective varieties tested. 13. Variation of 1000 grain weight due to fertilizer level applied, seeding date and seeding rate was not so high as number of grains per spike and number of heads per $\m^2$, but exhibited high year variation. Increased seeding rate decreased the 1000 grain weight. Among the varieties tested Chilbo and Buheung expressed heavy grain weight, while Suwon ＃ 18, Hangmi and Yuegi showed comparatively light grain weight. 14. Optimum seeding date in Suwon area was around October 1 to October 11. Yield was generally increased by increasing fertilizer level. Yield decrease due to early seeding was compensated in certain extent by increased fertilizer application. 15. Yield variations due to seeding rate differences were almost negligible compare to the variations due to fertilizer level and seeding date. In either early seeding or law fertilizer level yield variation due to seeding rate was not so remarkable. Increment of fertilizer application was more effective for yield increase especially at increased seeding rate. And also increased seeding rate fairly compensated the decrease of yield in late seeding date. 16. Optimum seeding rate was considered to be around 18-26 liters per 10a at N-P-K=10.5-6-6 kg/10a fertilizer level considering yield stabilization. 17. Varietal differences in optimum seeding date was quite remarkable Suwon ＃ 6, Suwon ＃ 4. Buheung noted high yield at early seeding and Suwon ＃ 18, Yuegi and Hangmi yielded higher in seeding date of October 10. However, Buheung showed late seeding adaptability. 18. Highly significant positive correlations were observed between yield and yield components in all treatments. However, this correlation coefficient was increased positively by increased fertilizer level and decreased by increased seeding rate. Significant negative correlation coefficients were estimated between yield and number of grains per spike, since increased number of heads per m2 at the same level of fertilizer tends to decrease the number of grains per spike. Comparatively low correlation coefficients were estimated between 1000 grain weight and yield. 19. No significant relations in terms of correlation coefficients was observed between number of heads per $\m^2$ and 1000 grain weight or number of grains per head.