• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.16 no.4
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• pp.223-237
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• 2011

The intermittent freshwater discharge has an critical influence upon the biophysical environments and the ecosystems of the Yeongsan Estuary where the estuary dam altered the continuous mixing of saltwater and freshwater. Though freshwater discharge is controlled by human, the extreme events are mainly driven by the heavy rainfall in the river basin, and provide various impacts, depending on its magnitude and frequency. This research aims to evaluate the magnitude and frequency of extreme freshwater discharges, and to establish the magnitude-frequency relationships between basin-wide rainfall and freshwater inflow. Daily discharge and daily basin-averaged rainfall from Jan 1, 1997 to Aug 31, 2010 were used to determine the relations between discharge and rainfall. Consecutive daily discharges were grouped into independent events using well-defined event-separation algorithm. Partial duration series were extracted to obtain the proper probability distribution function for extreme discharges and corresponding rainfall events. Extreme discharge events over the threshold 133,656,000 $m^3$ count up to 46 for 13.7y years, following the Weibull distribution with k=1.4. The 3-day accumulated rain-falls which occurred one day before peak discharges (1day-before-3day -sum rainfall), are determined as a control variable for discharge, because their magnitude is best correlated with that of the extreme discharge events. The minimum value of the corresponding 1day-before-3day-sum rainfall, 50.98mm is initially set to a threshold for the selection of discharge-inducing rainfall cases. The number of 1day-before-3day-sum rainfall groups after selection, however, exceeds that of the extreme discharge events. The canonical discriminant analysis indicates that water level over target level (-1.35 m EL.) can be useful to divide the 1day-before-3day-sum rainfall groups into discharge-induced and non-discharge ones. It also shows that the newly-set threshold, 104mm, can just separate these two cases without errors. The magnitude-frequency relationships between rainfall and discharge are established with the newly-selected lday-before-3day-sum rainfalls: $D=1.111{\times}10^8+1.677{\times}10^6{\overline{r_{3day}}$, (${\overline{r_{3day}}{\geqq}104$, $R^2=0.459$), $T_d=1.326T^{0.683}_{r3}$, $T_d=0.117{\exp}[0.0155{\overline{r_{3day}}]$, where D is the quantity of discharge, ${\overline{r_{3day}}$ the 1day-before-3day-sum rainfall, $T_{r3}$ and $T_d$, are respectively return periods of 1day-before-3day-sum rainfall and freshwater discharge. These relations provide the framework to evaluate the effect of freshwater discharge on estuarine flow structure, water quality, responses of ecosystems from the perspective of magnitude and frequency.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.147-168
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• 2017

There have been many studies on accurate stock market forecasting in academia for a long time, and now there are also various forecasting models using various techniques. Recently, many attempts have been made to predict the stock index using various machine learning methods including Deep Learning. Although the fundamental analysis and the technical analysis method are used for the analysis of the traditional stock investment transaction, the technical analysis method is more useful for the application of the short-term transaction prediction or statistical and mathematical techniques. Most of the studies that have been conducted using these technical indicators have studied the model of predicting stock prices by binary classification - rising or falling - of stock market fluctuations in the future market (usually next trading day). However, it is also true that this binary classification has many unfavorable aspects in predicting trends, identifying trading signals, or signaling portfolio rebalancing. In this study, we try to predict the stock index by expanding the stock index trend (upward trend, boxed, downward trend) to the multiple classification system in the existing binary index method. In order to solve this multi-classification problem, a technique such as Multinomial Logistic Regression Analysis (MLOGIT), Multiple Discriminant Analysis (MDA) or Artificial Neural Networks (ANN) we propose an optimization model using Genetic Algorithm as a wrapper for improving the performance of this model using Multi-classification Support Vector Machines (MSVM), which has proved to be superior in prediction performance. In particular, the proposed model named GA-MSVM is designed to maximize model performance by optimizing not only the kernel function parameters of MSVM, but also the optimal selection of input variables (feature selection) as well as instance selection. In order to verify the performance of the proposed model, we applied the proposed method to the real data. The results show that the proposed method is more effective than the conventional multivariate SVM, which has been known to show the best prediction performance up to now, as well as existing artificial intelligence / data mining techniques such as MDA, MLOGIT, CBR, and it is confirmed that the prediction performance is better than this. Especially, it has been confirmed that the 'instance selection' plays a very important role in predicting the stock index trend, and it is confirmed that the improvement effect of the model is more important than other factors. To verify the usefulness of GA-MSVM, we applied it to Korea's real KOSPI200 stock index trend forecast. Our research is primarily aimed at predicting trend segments to capture signal acquisition or short-term trend transition points. The experimental data set includes technical indicators such as the price and volatility index (2004 ~ 2017) and macroeconomic data (interest rate, exchange rate, S&P 500, etc.) of KOSPI200 stock index in Korea. Using a variety of statistical methods including one-way ANOVA and stepwise MDA, 15 indicators were selected as candidate independent variables. The dependent variable, trend classification, was classified into three states: 1 (upward trend), 0 (boxed), and -1 (downward trend). 70% of the total data for each class was used for training and the remaining 30% was used for verifying. To verify the performance of the proposed model, several comparative model experiments such as MDA, MLOGIT, CBR, ANN and MSVM were conducted. MSVM has adopted the One-Against-One (OAO) approach, which is known as the most accurate approach among the various MSVM approaches. Although there are some limitations, the final experimental results demonstrate that the proposed model, GA-MSVM, performs at a significantly higher level than all comparative models.

• Information Systems Review
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• v.16 no.3
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• pp.161-177
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• 2014

Corporate credit rating assessment consists of complicated processes in which various factors describing a company are taken into consideration. Such assessment is known to be very expensive since domain experts should be employed to assess the ratings. As a result, the data-driven corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has received considerable attention from researchers and practitioners. In particular, statistical methods such as multiple discriminant analysis (MDA) and multinomial logistic regression analysis (MLOGIT), and AI methods including case-based reasoning (CBR), artificial neural network (ANN), and multiclass support vector machine (MSVM) have been applied to corporate credit rating.2) Among them, MSVM has recently become popular because of its robustness and high prediction accuracy. In this study, we propose a novel optimized MSVM model, and appy it to corporate credit rating prediction in order to enhance the accuracy. Our model, named 'GAMSVM (Genetic Algorithm-optimized Multiclass Support Vector Machine),' is designed to simultaneously optimize the kernel parameters and the feature subset selection. Prior studies like Lorena and de Carvalho (2008), and Chatterjee (2013) show that proper kernel parameters may improve the performance of MSVMs. Also, the results from the studies such as Shieh and Yang (2008) and Chatterjee (2013) imply that appropriate feature selection may lead to higher prediction accuracy. Based on these prior studies, we propose to apply GAMSVM to corporate credit rating prediction. As a tool for optimizing the kernel parameters and the feature subset selection, we suggest genetic algorithm (GA). GA is known as an efficient and effective search method that attempts to simulate the biological evolution phenomenon. By applying genetic operations such as selection, crossover, and mutation, it is designed to gradually improve the search results. Especially, mutation operator prevents GA from falling into the local optima, thus we can find the globally optimal or near-optimal solution using it. GA has popularly been applied to search optimal parameters or feature subset selections of AI techniques including MSVM. With these reasons, we also adopt GA as an optimization tool. To empirically validate the usefulness of GAMSVM, we applied it to a real-world case of credit rating in Korea. Our application is in bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. The experimental dataset was collected from a large credit rating company in South Korea. It contained 39 financial ratios of 1,295 companies in the manufacturing industry, and their credit ratings. Using various statistical methods including the one-way ANOVA and the stepwise MDA, we selected 14 financial ratios as the candidate independent variables. The dependent variable, i.e. credit rating, was labeled as four classes: 1(A1); 2(A2); 3(A3); 4(B and C). 80 percent of total data for each class was used for training, and remaining 20 percent was used for validation. And, to overcome small sample size, we applied five-fold cross validation to our dataset. In order to examine the competitiveness of the proposed model, we also experimented several comparative models including MDA, MLOGIT, CBR, ANN and MSVM. In case of MSVM, we adopted One-Against-One (OAO) and DAGSVM (Directed Acyclic Graph SVM) approaches because they are known to be the most accurate approaches among various MSVM approaches. GAMSVM was implemented using LIBSVM-an open-source software, and Evolver 5.5-a commercial software enables GA. Other comparative models were experimented using various statistical and AI packages such as SPSS for Windows, Neuroshell, and Microsoft Excel VBA (Visual Basic for Applications). Experimental results showed that the proposed model-GAMSVM-outperformed all the competitive models. In addition, the model was found to use less independent variables, but to show higher accuracy. In our experiments, five variables such as X7 (total debt), X9 (sales per employee), X13 (years after founded), X15 (accumulated earning to total asset), and X39 (the index related to the cash flows from operating activity) were found to be the most important factors in predicting the corporate credit ratings. However, the values of the finally selected kernel parameters were found to be almost same among the data subsets. To examine whether the predictive performance of GAMSVM was significantly greater than those of other models, we used the McNemar test. As a result, we found that GAMSVM was better than MDA, MLOGIT, CBR, and ANN at the 1% significance level, and better than OAO and DAGSVM at the 5% significance level.

• Journal of Distribution Research
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• v.17 no.1
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• pp.87-115
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• 2012

Introduction: In these days, a loyalty program is one of the most common marketing mechanisms (Lacey & Sneath, 2006; Nues & Dreze, 2006; Uncles et al., 20003). In recent years, Coalition Loyalty Program is more noticeable as one of progressed forms. In the past, loyalty program was operating independently by single product brand or single retail channel brand. Now, companies using Coalition Loyalty Program share their programs as one single service and companies to participate to this program continue to have benefits from their existing program as well as positive spillover effect from the other participating network companies. Instead of consumers to earn or spend points from single retail channel or brand, consumers will have more opportunities to utilize their points and be able to purchase other participating companies products. Issues that are related to form of loyalty programs are essentially connected with consumers' perceived view on convenience of using its program. This can be a problem for distribution companies' strategic marketing plan. Although Coalition Loyalty Program is popular corporate marketing strategy to most companies, only few researches have been published. However, compared to independent loyalty program, coalition loyalty program operated by third parties of partnership has following conditions: Companies cannot autonomously modify structures of program for individual companies' benefits, and there is no guarantee to operate and to participate its program continuously by signing a contract. Thus, it is important to conduct the study on how coalition loyalty program affects companies' success and its process as much as conducting the study on effects of independent program. This study will complement the lack of coalition loyalty program study. The purpose of this study is to find out how consumer loyalty affects affiliated brands, its cause and mechanism. The past study about loyalty program only provided the variation of performance analysis, but this study will specifically focus on causes of results. In order to do these, this study is designed and to verify three primary objects as following; First, based on opinions of Switching Barriers (Fornell, 1992; Ping, 1993; Jones, et at., 2000) about causes of loyalty of coalition brand, 'brand attractiveness' and 'brand switching cost' are antecedents and causes of change in 'brand loyalty' will be investigated. Second, influence of consumers' perception and attitude prior to joining coalition loyalty program, influence of program in retail brands, brand attractiveness and spillover effect of switching cost after joining coalition program will be verified. Finally, the study will apply 'prior brand preference' as a variable and will provide a relationship between effects of coalition loyalty program and prior preference level. Hypothesis Hypothesis 1. After joining coalition loyalty program, more preferred brand (compared to less preferred brand) will increase influence on brand attractiveness to brand loyalty. Hypothesis 2. After joining coalition loyalty program, less preferred brand (compared to more preferred brand) will increase influence on brand switching cost to brand loyalty. Hypothesis 3. (1)Brand attractiveness and (2)brand switching cost of more preferred brand (before joining the coalition loyalty program) will influence more positive effects from (1)program attractiveness and (2)program switching cost of coalition loyalty program (after joining) than less preferred brand. Hypothesis 4. After joining coalition loyalty program, (1)brand attractiveness and (2)brand switching cost of more preferred brand will receive more positive impacts from (1)program attractiveness and (2)program switching cost of coalition loyalty program than less preferred brand. Hypothesis 5. After joining coalition loyalty program, (1)brand attractiveness and (2)brand switching cost of more preferred brand will receive less impacts from (1)brand attractiveness and (2)brand switching cost of different brands (having different preference level), which joined simultaneously, than less preferred brand. Method : In order to validate hypotheses, this study will apply experimental method throughout virtual scenario of coalition loyalty program if consumers have used or available for the actual brands. The experiment is conducted twice to participants. In a first experiment, the study will provide six coalition brands which are already selected based on prior research. The survey asked each brand attractiveness, switching cost, and loyalty after they choose high preference brand and low preference brand. One hour break was provided prior to the second experiment. In a second experiment, virtual coalition loyalty program "SaveBag" was introduced to participants. Participants were informed that "SaveBag" will be new alliance with six coalition brands from the first experiment. Brand attractiveness and switching cost about coalition program were measured and brand attractiveness and switching cost of high preference brand and low preference brand were measured as same method of first experiment. Limitation and future research This study shows limitations of effects of coalition loyalty program by using virtual scenario instead of actual research. Thus, future study should compare and analyze CLP panel data to provide more in-depth information. In addition, this study only proved the effectiveness of coalition loyalty program. However, there are two types of loyalty program, which are Single and Coalition, and success of coalition loyalty program will be dependent on market brand power and prior customer attitude. Therefore, it will be interesting to compare effects of two programs in the future.

• Korean Journal of Environmental Agriculture
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• v.25 no.3
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• pp.217-227
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• 2006

Micronutrient status in soils and crops of plastic film house and their relationship were investigated. Total 203 plastic film houses were selected (red pepper, 66; cucumber, 63; tomato, 74) in Yeongnam region and soil and leaf samples were collected. Hot-water extractable B and 0.1 N HCl extractable Cu, Zn, Fe, and Mn in soil samples and total micronutrients in leaf samples were analyzed. Contents Zn, Fe, and Mn in most of the investigated soils were higher than the upper limits of optimum level for general crop cultivation. Contents of Cu in most soils of cucumber and tomato cultivation were higher than the upper limit of optimum level, but Cu contents in about 30% of red pepper cultivation soils were below the sufficient level. Contents of B in most soils of cucumber and tomato were above the sufficient level but in 48% of red pepper cultivation soils B were found to be deficient. Micronutrient contents in leaf of investigated crops were much variable. Contents of B, Fe, and Mn were mostly within the sufficient levels, while in 71% of red pepper samples Cu was under deficient level and in 44% of cucumber samples Cu contents were higher than the upper limit of sufficient level. Contents of Zn in red pepper and cucumber samples were mostly within the sufficient level but in 62% of tomato samples Zn contents were under deficient condition. However, any visible deficiency or toxicity symptoms of micronutrients were not found in the crops. No consistent relationships were found between micronutrient contents in soil and leaf, and this indicates that growth and absorption activity of root and interactions among the nutrients in soil might be important factors in overall micronutrient uptake of crops. For best management of micronutrients in plastic film house, much attention should be focused on the management of soil and plant characteristics which control the micronutrient uptake of crops.

• Journal of Preventive Medicine and Public Health
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• v.30 no.4 s.59
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• pp.669-685
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• 1997

Previous studies, reporting the inverse relationship between osteoarthritis and osteoporosis suggest the existence of possible pathophysiologic mechanisms between them. To examinine the hypothesis that 'bone mineral densities of women with osteoarthritis are significantly higher than that of women without osteoarthritis in Korea', subjects from the health and nutritional examination survey in Kuri city were sampled. Samples were selected through multi-stage sampling frame using established clusters in Kuri city. From August 18 to September 10,1997, the survey was conducted. Among the. total number of selected sample population (1,656 people), response .ate was 52.4 percent (348 men and 519 women). 420 women who took BMD measurement, radiologic exam, and anthropometric exam were selected for the analysis. The analytic results are as follows. 1. General characteristics: Mean BMD was $0.493g/cm^2$, mean age was 43.0, mean BMI was $23.9kg/m^2$. The number of women who experienced menopause was 106, hysterectomy was 19. There were 0 case of osteoarthritis of hip, 64 cases of osteoarthritis of knee, and 2 cases of osteoarthritis of hand. 2. Univariate analysis results: Mean BMD of women with the osteoarthritis of knee was significantly lower than that of women without the osteoarthritis of knee(0.4269 vs. $0.5057g/cm^2$). But, there were too few cases of osteoarthritis of hip and hand, so comparative studies of BMD in osteoarthritis of hip and hand could not be conducted. There were significant differences of BMD among pre-menopause group(0.5204), post-menopause group(0.4206), and hysterectomy group(0.4881). Additionally, there were significant differences of BMD among diabetes group(0.4297), impaired glucose tolerance group(0.4874), and normal group(0.5057). Furthermore, age, parity, BMI, bioimpedance were significantly related with BMD. 3. Multivariate analysis results: To examinine the relationship between osteoarthritis and BMD while controlling the other variables' effects which were significant in the univariate analyses, multiple linear regression analysis was done. But, it was found that osteoarthritis of knee was not a significant variable to BMD anymore. While age and menopause had significant negative relationship with BMD. Diabetes, parity, BMI, and bioimpedance did not have significant relationships with BMD. After stratification of subjects according to menopause, multiple linear regression analyses were done to each strata. Consequently, age in post-menopause group, age and osteoarthritis of knee in hysterectomy group showed significant negative relationship with BMD. The results did not support the many results of other previous studies done with white men and women. further studies of biological plausibility to Korean women are recommended. Also it is suggested that longitudinal study to verify the relationship between osteoarthritis and BMD will be valuable.

• Journal of Chest Surgery
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• v.36 no.8
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• pp.545-558
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• 2003

Adult respiratory distress syndrome (ARDS) is of particular interest because of its severity of the associated lung injury and its high mortality. However, the pathophysiologies of ARDS in infant and childhood groups are still not well clarified inspite of many previous investigations. To investigate the time course of pathophysiology of ARDS in infant and childhood groups, this study was designed with experimental endotoxin-induced ARDS model using young rabbits (8 week-old). Material and Method: Rabbits were divided into the control group (n=8) and the endotoxin-treated group (n=32). The endotoxin group was subdivided into 4 groups by the sampling times as 3, 6, 12 and 24 hr-groups (G- $E_{3,6,12,24,}$ each n=8). The experimental ARDS was made by a bolus injection of endotoxin (Escherichia coli serotype 055 : B5, 0.50 mg/kg) via rabbit ear vein. For evaluation of the hematologic and inflammatory markers, and superoxide dismutase (SOD) concentrations, the blood samples were taken from the heart. The bronchoalveolar lavage fluid (BALF) were obtained for analysis of the leukocytes and protein concentration. With biopsy of the lung, histopathologic changes of the lung were also evaluated. Result: In the endotoxin groups, significant leukopenia (owing to pancytopenia) occurred in 3 and 6-hr groups, which was followed by significant leukocytosis (owing to neutrophilia) in the 12 and 24-hr groups (p<0.05). Serum levels of tumor necrosis factor-$\alpha$ (TNF-$\alpha$) and interleukin-1 $\beta$ (IL-1 $\beta$) in the endotoxin groups were higher than those of control group (p<0.05). Serum levels of superoxide dismutase (SOD) of G- $E_{3}$ and G- $E_{6}$ were higher than those of control group, whereas those of G- $E_{12}$ were lower than those of control groups (p<0.05). Total leukocyte counts and protein con-centrations in BALF were significantly elevated in the endotoxin groups compared to the control group (p < 0.05). The hemorrhagic pattern of BALF showed occurred in the endotoxin groups. The endotoxin groups (in G- $E_{6}$) had severe infiltration of inflammatory cells (lymphocyte and monocyte) in the pulmonary interstitium and parenchyma, migrations of neutrophil and eosinophil into alveolar spaces and interstitial widening, which are the evidences of acute lung injury. In the endotoxin groups, there were significant positive correlations between the BALF findings and the immunologic markers (TNF-$\alpha$, IL-1$\beta$, SOD) (p<0.05). Conclusion: Severe acute lung injury occurred in all the endotoxin-treated rabbits. The pathophysiologic findings were so progressive until 6-hr by time dependant pattern, and then recovered slowly, Variable hematologic, immuno-logic, and pathologic factors were well correlated in the development and progression of endoxin-induced lung injury. The pathophysiologic responses were sensitive and rapid in young rabbit Young rabbit seemed to be a useful experimental animal model for infant and childhood groups.roups.

• Korean Journal of Weed Science
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• v.1 no.1
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• pp.69-77
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• 1981

Six herbicides were evaluated to investigate the phytotoxicity of rice plant and the weeding efficacy influenced by the time of application in mechically transplanted paddy field. The amount of each chemical applied was 3 kg, a. i, /ha. Chlormethoxynil : Rotala indica KOEHNE and Lindernia pyxuiaria PHILCOX were effectively controlled when applied on the 12th day after transplanting (12 DAT) and this herbicide was excellent for the control of Echinochloa crusgalli P. BEAUV, Monochoria vaginalis PRESL and Sagittaria pygmaea MIQ, when applied early (7 days after puddling) but its weeding effect for these weeds decreased greatly as the application time became later. It had a controlling effect for Potamogeton distinctus A. BENN, Cyperus serotinus ROTTB and Scirpus hotarui ROXB at the initial period at the earlier application time. Butachlor was effective in controlling E. crusgalli, R. indica and L. pyxidaria at 12 days after transplanting (DAT) but was not effective in controlling P. distinctus and S. pygmaea even at the early application time. M. vaginalis, C. serotinus and S. hotarui were effectively controlled by the butachlor treatment at 7 days after final puddling (2 DBT-SDAT) but this weeding effect decreased at the late application time. A combination of butachlor and naproanilide excellently controlled E. crusgalli, R. indica, L. pyxidaria and S. pygmaea regardless of the application time. For the control of M. vaginalis, C. serotinus and P. distinctus, the weeding effect of this mixtures was much greater than that of the single treatment of butachlor. Perfluidone was excellent for the control of E. crusgalli, R. indica, L. pyxidaria, M. vaginalis and S. pygmaea at either application time tested. P. distinctus, C. serorinus and S. hotarui could be controlled by this chemicals until the time of first observation (23 DAT) but the effect for these weeds somewhat decreased as time passed. The effect of pyrazolate on E. crusgalli, M. vaginalis, S. hotarui and P. distinctus was very excellent regardless of the application time but R. indica and L. pyxidaria could not be completely eliminated by this chemical. This chemical was effective in controlling C. serotinus when applied at 7-9 days after final puddling and showed a controlling effect for S. hotaruionly at the initial period. Piperophos + dimethametryn was very excellent for the control of all the annual weeds and P. distinctus. It showed a controlling effect on S. pygmaea, C. serotinus and S. hotarui only at the initial period. There was no difference in the effects on phytotoxicity and yield between chlormethoxynil and pyrazolate at either times of application tested. The later the application time was, the less the phytotoxicity of butachlor and piperophos+dimethametryne was. The phytotoxicity of butachlor + naproanilide and perfluidone decrease in the plots treated at the later application time. When the last two chemicals were treated at 2 days before transplanting (DBT) the yield decreased as compared with the hand weeded plot.

• Radiation Oncology Journal
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• v.16 no.2
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• pp.99-106
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• 1998

Purpose : We conducted clonogenic assay using human cancer cell lines (MKN-45, PC-14, Y-79, HeLa) to investigate a correlation between the parameters of radiosensitivity. Materials and Methods : Human cancer cell lines were irradiated with single doses of 1, 2, 3, 5, 7 and 10Gy for the study of radiosensitivity and subrethal damage repair capacity was assessed with two fractions of 5Gy separated with a time interval of 0, 1, 2, 3, 4, 6 and 24 hours. Surviving fraction was assessed with clonogenic assay using $Sperman-H\"{a}rbor$ method and mathematical analysis of survival curves was done with linear-quadratic (LQ) , multitarget-single hit(MS) model and mean inactivation dose$(\v{D})$. Results : Surviving fractions at 2Gy(SF2) were variable among the cell lines, ranged from 0.174 to 0.85 The SF2 of Y-79 was lowest and that of PC-14 was highest(p<0.05, t-test). LQ model analysis showed that the values of $\alpha$ for Y-79, MKN-45, HeLa and PC-14 were 0.603, 0.356, 0.275 and 0.102 respectively, and those of $\beta$ were 0.005, 0.016, 0.025 and 0.027 respectively. Fitting to MS model showed that the values of Do for Y-79. MKN-45, HeLa and PC-14 were 1.59. 1.84. 1.88 and 2.52 respectively, and those of n were 0.97, 1.46, 1.52 and 1 69 respectively. The $\v{D}s$ calculated by Gauss-Laguerre method were 1.62, 2.37, 2,01 and 3.95 respectively So the SF2 was significantly correlated with $\alpha$, Do and $\v{D}$. Their Pearson correlation coefficiencics were -0.953 and 0,993. 0.999 respectively(p<0.05). Sublethal damage repair was saturated around 4 hours and recovery ratios (RR) at plateau phase ranged from 2 to 3.79. But RR was not correlated with SF2, ${\alpha}$, ${\beta}$, Do, $\v{D}$. Conclusion : The intrinsic radiosensitivity was very different among the tested human cell lines. Y-79 was the most sensitive and PC-l4 was the least sensitive. SF2 was well correlated with ${\alpha}$, Do, and $\v{D}$. RR was high for MKN-45 and HeLa but had nothing to do with radiosensitivity parameters. These basic parameters can be used as baseline data for various in vitro radiobiological experiments.

• Economic and Environmental Geology
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• v.12 no.3
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• pp.147-176
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• 1979

The Yeonhwa II zinc-lead mine is characterized by a dozen of moderately dipping tabular orebodies of skarn and zinc-lead sulfides, developed in accordance with the ENE-trending bedding thrusts and bedding planes of the Pungchon Limestone and underlying Myobong Formation, mostly along the contacts of a ENE-trending sill and a NW-trending dike of quartz mononite porphyry. The orebodies occur in three groups: (1) the footwall Wolgok orebodies with respect to the sill, (2) the hangingwall Wolgok orebodies, and (3) the Seongok orebodies extended from dike contacts into carbonate beds. Mineral compositions of these orebodies are dominated by calc-silicates (skarn) associated with ore minerals of sphalerite, galena, and chalcopyrite, as well as sulfide gangue of pyrrhotite. A pair of exo- and endo-skerns in the Wolgok footwall contact aureole between the Pungchon Limestone and quartz monzonite porphyry on the -120 level represents a well-developed symmetrical pattern of mineral zoning: a garnet/quartz zone in the center of exoskarn, two zones of pyroxene with ore minerals on both sides of the garnet/quartz zone, further outwards-an epidote/chlorite-bearing hornfelsic zone in the Myobong slate beyond a zone of unaffected limestone, and an epidote-dominated zone of endo skarn on the opposite side toward fresh quartz monzonite porphyry. These features indicate a combination of two effects on the skarn formation: (1) differences in composition of the host rocks(sedimentary and ignous), and (2) progressive outward migration of inner zones on outer zones on the course of metasomatic replacement of the pre-existing minerals. Microprobe analyses of garnet, pyroxene, pyroxenoids, epidote, and chlorite for nine major elements on a total of 23 mineral grains revealed that: the pyroxenes are hedenbergitic, in most zones, with a gradual decrease of Fe- and Mn-contents toward the central zone, whereas the garnets are andraditic in outer zones, but are grossularitic in the central zone. This indicates a reverse relationship of Fe-contents between pyroxene and garnet across the exoskarn zones. Pyroxenoids are lacking in wollastonite but are dominated by pyroxmangite, rhodonite and bustamite, indicating a Mn-rich nature in bulk chemistry. Pseudomorphic fluorite after garnet occurs abundantly reflecting a fluorine-enhanced evidence of the skarn-forming fluids. Epidote contains 0.19-0.25mole fraction of pistacite, and chlorite is Mn-rich but is Mg-poor. Sulfide mineralization took place with the most Fe-rich pyroxene rather than with garnet as indicated by the fact that the highest value of hedenbergite mole fraction occurs in the ore-bearing pyroxene zone. The Yeonhwa II ores are characterized by high zinc and low lead in metal grade, with minor quantity of copper content in almost constant grade. The hangingwall Wolgok and Seongok orebodies, that formed in a more open environment with respect to their local configurations of geologic setting, are more variable in metal grades and ratios, than are the footwall Wolgok orebodies formed in a more closed condition in a narrow interval of sedimentary beds.