The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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v.5
no.1
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pp.37-46
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2000
We investigated the temporal and spatial variations in heterotrophic dinoflagellates (hereafter HTD) and ciliates from June to September 1997 in the waters off Kohung, Korea where red tides dominated by harmful dinoflagellates had occurred from August to October since 1995. We took water samples five times from 5-7 depths at 3 stations in this study period. A total of 17 HTD species were present and of these species in the genus Protoperidinium were 11. The species number of tintinnids (hereafter TIN) present totalled 15 and several naked ciliate (hereafter NC) species were observed. The species numbers of HTD and TIN rapidly increased between August 1st and 21st and then reached to the maximum numbers of 13 and 10, respectively, on August 27 when red tides dominated by Gyrodinium impudicum were first observed in the study area. However the species numbers drastically decreased on September 22. The maximum densities of HTD, TIN, and NC were 45, 39, 57 cells $ml^{-1}$, respectively. ADAS, calculated by averaging the densities of a certain species in the all samples collected from all depths and stations at a sampling period, most increased between August 1st and 21st and then reached to the maximum density of f cells $ml^{-1}$ on August 27 for HTD, while did between August 21st and 27th and up to 7 cells $ml^{-1}$ for TIN. Unlike ADAS of HTD and TIN, that of NC did not change much with the maximum of 8 cells $ml^{-1}$ on August 27th. The pattern of the temperal variation in the species number and ADAS of HTD was similar to that of diatoms and the distributions of Protoperidinium spp. and diatoms had a strong positive correlation. This evidence suggests that HTD, in particular Protoperidinium spp. be a grazer on diatom. In general, the densities of HTD, TIN, and NC decreased with going to stations located in the outer bay. Therefore, the availability of suitable prey and distance from the coastal line might be responsible for the distribution of HTD, TIN, and NC. The results of the present study provide a basis for further experiments for the feeding by dominant HTD, TIN, and NC on dominant phytoplankton including red tide species and for understanding food webs in the planktonic community before, during, and after the red tide outbreak.
An algicidal bacterium, Micrococcus sp. LG-5 against the harmful dinoflagellate, Cochlodinium polykrikoides was isolated. The optimal conditions for the highest algicidal activity of bacterial culture filtrate showed in the range of $20{\~}30^{\circ}C$, at pH 7.0 and $3.0{\%}$ of NaCl concentration. In addition, $IC_(50)(mean of 50{\%} inhibitory concentration)$ of the culture filtrate against C. polykrikoides after incubation of 5 days was $0.482{\%}$. To investigate heat and pH stability of the culture filtrate of Micrococcus sp. LG-5, the culture filtrate ($pore size, 0.1 {\mu}m$) was heated to $121^{\circ}C for 15 min$ and adjusted pH from 2.0 to 10.0. There were no significant changes in algicidal activity by heat treatment and the pH change between pH from 5.0 to 10.0. The algicidal substances produced from Micrococcus sp. LG-5 were mainly detected in the fraction of $10,000{\~}1,000$ MWCO (molecular weight cut-off). The culture filtrate of Micrococous sp. LG-5 showed antimicrobial activity against Enterococcus faecalis, Escheiichia coli, Uebsiella pneunioniae and Vibrio altinolyticus, but did not show against Pseudomonas aeminosa, P. Buorescens, Salmonella typhi, Staphylococcus aureus, V. cholerae and V parahaemolyicus. The culture filtrate of Micrococcus sp. LG-5 was examined against 16 phytoplankton species and showed the algicidal activity against Ajexandzium tuarense, Eutreptiella Drnnastin, Gymnodinium catenatum, G. mikimotoi, G. sanguineum, eyodinium impuaicum, Heterocapsa triquetra, Heterosipa akashiwo, Prorocentrum micans and Pyraminonas sp.. However no algicidal effects of Micrococcus sp. LG-5 were observed against Chlamydomonas sp., Cylindrotheoa closterium, P. mininum, P. triestimum, Pseudonieschia sp. and Sczipuiella trochoidea. On the other hand, algicidal activity on the tested marinelivefood was not detected except for Isochrysis galbana. In addition, physiological responses of cultured olive flounder (Paralichthys oliraceus) exposed to $1 and 10{\%}$ of the culture filtrate of Micrococcus sp. LG-5 were measured. There were no clear changes in AST, GGT, creatinine, urea, total cholesterol, total protein, albumine, $Mg^(+2), Ca^(+2), Na^+, K^+, and Cl^-$. These results indicate that olive flounders were not affected when they were exposed to the culture filtrate of Micrococcus sp. LG-5.
The flag and lower leaves (4th or 5th) of rice plant from the field of NPK simple trial and from three low productive area were analyzed in order to find out certain diagnostic criteria of nutritional status at harvest. 1. Nutrient contents in the leaves from no fertilizer, minus nutrient and fertilizer plots revealed each criterion for induced deficiency (severe deficient case induced by other nutrients), deficiency (below the critical concentration), insufficiency (hidden hunger region), sufficiency (luxuary consumption stage) and excess (harmful or toxic level). 2. Nitrogen contents for the above five status was less than 1.0%, 1.0 to 1.2, 1.2 to 1.6, 1.6 to 1.9 and greater than 1.9, respectively. 3. It was less than 0.3%, 0.3 to 0.4, 0.4 to 0.55 and greater than 0.55 for phosphorus $(P_2O_5)$ but excess level was not clear. 4. It was below 0.5%, 0.5 to 0.9, 0.9 to 1.2, 1.2 to 1.4 and above 1.4 for potassium. 5. It was below 4%, 4 to 6, 6 to 11 and above 11 for silicate $(SiO_2)$ and no excess was appeared. 6. Potassium in flag leaf seemed to crow out nitrogen to ear resulting better growth of ear by the inhibition of overgrowth of flag leaf. 7. Phosphorus accelerated the transport of Mg, Si, Mn and K in this order from lower leaf to flag, and retarded that of Ca and N in this order at flowering while potassium accelerated in the order of Mn, and Ca, and retarded in the order of Mg, Si, P and N at milky stage. 8. Transport acceleration index (TAI) expressed as (F_2L_1-F_1L_2)\;100/F_1L_1$ where F and L stand for other nutrient cotents in flag and lower leaf and subscripts indicate the rate of a nutrient applied, appears to be suitable for the effect of the nutrient on the translocation of others. 9. The content of silicate $(SiO_2)$ in the flag was lower than that of lower leaf in the early season cultivation indicating hinderance in translocation or absorption. It was reverse in the normal season cultivation. 10. The infection rate of Helminthosporium frequently occurred in the potassium deficient field seemed to be related more to silicate and nitrogen content than potassium in the flag leaf. 11. Deficiency of a nutrient occured simultaniously with deficiency of a few other ones. 12. Nutritional disorder under the field condition seems mainly to be attributed to macronutrients and the role of micronutrient appears to be none or secondary.
This study was conducted to formulate management guidelines for Natural monumental old trees in Korea through survey of tree vigor and analysis of growing environments. A total of 20 old trees designated as natural monuments in Seoul, Incheon, and Gyeonggi Province were surveyed. The biological characteristics were surveyed with 4 items of species, ages and height of trees. The surrounding environments were surveyed with 2 items of location types and surroundings. The root conditions were surveyed with 2 items of denudation and molding depth. The health conditions were surveyed with 5 items of withering rate, cavity size, bark breakaway rate, damages by blight and insects, and growing tips. The soil conditions were surveyed with 6 items of PH, organic contents, valid phosphoric acid, transposal cations(K, Ca) and soil compaction. On the basis of outcomes of these research items, mutual relations among locations, growings and soil conditions of old trees were analyzed by carring out cross tabulation, correlation, and simple and multiple regression. Management guidelines were presented searching the factors effecting on the health of the monumental old trees. On the biological characteristics, the old trees designated as natural monuments were Pinus bungeana(4 trees), Juniperus chinensis(3 trees), Ginkgo biloba(3 trees), Poncirus trifoliata(2 trees). Actinidia arguta, Wisteria floribunda, Thuja orientalis, Quercus mongolica, Sophora japonica, Fraxinus rhynchophylla, Zelkova serrata, and Pinus densiflora. The tree height ranged from 4.2 to 39.2m, and root collar rounds ranged from 1.01 to 15.2m. On the surrounding environments, The location types ; Gardens(4), historical sites(5), residental sections(3) open agricultural fields(3), mountain hills(3), and near ocean beaches(1) and stream site(1). The surroundings ; 75% denudation of roots, molded more than 10cm except 4 trees(25%). On the health conditions, 1)Withering rate ; Ginkgo biloba(20%) in Yongmoon temple, (5%) in Saki-ri, kanwha-gun, and others had no withering rate. 2) Cavity size ; all subject had $5{\sim}100cm^3$ of cavity. 3) Bark breakaway rate ; Pinus bungeana in Soosong-dong, in the shrine of Confucius, in Samchung-dong, especially high rate of cavity(5~50%) in Seoul area and in Saki-ri, Kangwha-gun were high 45% brakeaway rate. 4) Damages by blight and insects was slight due to managements. 5Growing tips ; In cases of Juniperus chinensis in Changdeok palace and SunnogDang, seoul, growing tips were 1/2, presumably cause by air pollution, and in cases of Fraxinus rhynchophylla in Paju city and Pinus densiflora in BacksaDorip-ri, Icheon city, growing tips were fine, presumably because there were no moldings. On the Soil conditions, Soil pH ranged from 5.2 to 8.3, organic matter contents from 12% to 56%, phosphorus contents from 104 to 618ppm, soil compaction ranged from 7 to 28mm( among them, Denudation was severe with 21~28mm soil compactions in cases of Pinus bungeana in Soosong -dong, Thuja orientalis in Samchung -dong, Ginkgo biloba in the shrine of Confucius and in Yongmoon temple.) Results of cross tabulation, correlation, and regression analysis showed that molding depth was the most serious factor to deteriorate the tree vigor and cambium conductivity. In addition, soil acidity, organic matter contents, disease and insect damages and cambial detachment were also related to the tree vigor. Additional research of these relationships will be needed to conduct more detailed studies. Based on the relationships between the tree vigor and growing environments, it is considered that old trees should be managed to give them more growing spaces and less abuses. Also, molded soils should be removed and further soil-molding around the tree collar should be prohibited. For the construction of systematic management and removal of harmful factors, appropriative management according to spices, persistent monitering of damaged cases and construction of management system through the accumulation of data on the relationships of soil conditions are required.
The government recently announced various policies for developing big-data and artificial intelligence fields to provide a great opportunity to the public with respect to disclosure of high-quality data within public institutions. KSURE(Korea Trade Insurance Corporation) is a major public institution for financial policy in Korea, and thus the company is strongly committed to backing export companies with various systems. Nevertheless, there are still fewer cases of realized business model based on big-data analyses. In this situation, this paper aims to develop a new business model which can be applied to an ex-ante prediction for the likelihood of the insurance accident of credit guarantee. We utilize internal data from KSURE which supports export companies in Korea and apply machine learning models. Then, we conduct performance comparison among the predictive models including Logistic Regression, Random Forest, XGBoost, LightGBM, and DNN(Deep Neural Network). For decades, many researchers have tried to find better models which can help to predict bankruptcy since the ex-ante prediction is crucial for corporate managers, investors, creditors, and other stakeholders. The development of the prediction for financial distress or bankruptcy was originated from Smith(1930), Fitzpatrick(1932), or Merwin(1942). One of the most famous models is the Altman's Z-score model(Altman, 1968) which was based on the multiple discriminant analysis. This model is widely used in both research and practice by this time. The author suggests the score model that utilizes five key financial ratios to predict the probability of bankruptcy in the next two years. Ohlson(1980) introduces logit model to complement some limitations of previous models. Furthermore, Elmer and Borowski(1988) develop and examine a rule-based, automated system which conducts the financial analysis of savings and loans. Since the 1980s, researchers in Korea have started to examine analyses on the prediction of financial distress or bankruptcy. Kim(1987) analyzes financial ratios and develops the prediction model. Also, Han et al.(1995, 1996, 1997, 2003, 2005, 2006) construct the prediction model using various techniques including artificial neural network. Yang(1996) introduces multiple discriminant analysis and logit model. Besides, Kim and Kim(2001) utilize artificial neural network techniques for ex-ante prediction of insolvent enterprises. After that, many scholars have been trying to predict financial distress or bankruptcy more precisely based on diverse models such as Random Forest or SVM. One major distinction of our research from the previous research is that we focus on examining the predicted probability of default for each sample case, not only on investigating the classification accuracy of each model for the entire sample. Most predictive models in this paper show that the level of the accuracy of classification is about 70% based on the entire sample. To be specific, LightGBM model shows the highest accuracy of 71.1% and Logit model indicates the lowest accuracy of 69%. However, we confirm that there are open to multiple interpretations. In the context of the business, we have to put more emphasis on efforts to minimize type 2 error which causes more harmful operating losses for the guaranty company. Thus, we also compare the classification accuracy by splitting predicted probability of the default into ten equal intervals. When we examine the classification accuracy for each interval, Logit model has the highest accuracy of 100% for 0~10% of the predicted probability of the default, however, Logit model has a relatively lower accuracy of 61.5% for 90~100% of the predicted probability of the default. On the other hand, Random Forest, XGBoost, LightGBM, and DNN indicate more desirable results since they indicate a higher level of accuracy for both 0~10% and 90~100% of the predicted probability of the default but have a lower level of accuracy around 50% of the predicted probability of the default. When it comes to the distribution of samples for each predicted probability of the default, both LightGBM and XGBoost models have a relatively large number of samples for both 0~10% and 90~100% of the predicted probability of the default. Although Random Forest model has an advantage with regard to the perspective of classification accuracy with small number of cases, LightGBM or XGBoost could become a more desirable model since they classify large number of cases into the two extreme intervals of the predicted probability of the default, even allowing for their relatively low classification accuracy. Considering the importance of type 2 error and total prediction accuracy, XGBoost and DNN show superior performance. Next, Random Forest and LightGBM show good results, but logistic regression shows the worst performance. However, each predictive model has a comparative advantage in terms of various evaluation standards. For instance, Random Forest model shows almost 100% accuracy for samples which are expected to have a high level of the probability of default. Collectively, we can construct more comprehensive ensemble models which contain multiple classification machine learning models and conduct majority voting for maximizing its overall performance.
Salted Cabbage products purchased from different companies at 4 different districts in South Korea were detected in this study. Cabbage and salt are the main materials for kimchi manufacture. The results of general bacteria contaminated in the samples were $1.4{\times}10^5$, $6.4{\times}10^5$, $1.7{\times}10^7$, $3.6{\times}10^7$ CFU/g in cabbage and $2.7{\times}10^3$ CFU/g in salt, respectively. The results of coliforms were detected as $2.4{\times}10^4$ CFU/g, and there was no Escherichia coli in any sample. Staphylococcus aureus was detected in cabbage as $9.9{\times}10^2$, $8.0{\times}10^1$, and $3.0{\times}10^3$ CFU/g, Bacillus cereus was also found in cabbage as $4.1{\times}10^3$ and $1.0{\times}10^1$ CFU/g. The results of Campylobacter jejuni and Vibrio paraheamolyticus were $2.4{\times}10^6$ and $1.0{\times}10^4$ CFU/g in cabbage, respectively. $1.0{\times}10^3$ CFU/g for Yersinia enterocolitica was determined in salt. In case of Listeria monocytogenes, the results were $1.5{\times}10^1$, $1.1{\times}10^2$, and $4.5{\times}10^1$ CFU/g in cabbage. Total batcteria ranged from $1.4{\times}10^1$ to $4.4{\times}10^5$ CFU/g were detected in salting solution, from $1.5{\times}10^4$ to $1.2{\times}10^8$ CFU/g in dehydrated salted-cabbage, from $9.4{\times}10^4{\sim}1.3{\times}10^8$ CFU/g in minced salted-cabbage. The results of E. coli in samples from different companies were different from one to anther. The results of the contamination of S. aureus and B. cereus showed positive in salting solution and dehydrated salted-cabbage at a portion of companies. V. paraheamolyticus was detected in salting solution. The contamination of Y. enterocolitica ranged from $9.5{\times}10^2$ to $1.8{\times}10^3$ CFU/g in salting solution, from $1.7{\times}10^1$ to $2.7{\times}10^2$ CFU/g in dehydrated salted-cabbage, from $1.2{\times}10^2$ to $1.3{\times}10^8$ CFU/g in minced salted-cabbage. The contamination of L. monocytogenes ranged from $8.0{\times}10^2$ to $1.7{\times}10^4$ CFU/g in salting solution, from $2.8{\times}10^2$ to $1.2{\times}10^4$ CFU/g in dehydrated salted-cabbage. During the manufacture processing of Kim chi, microorganisms were detected in cabbages salted in different concentrations of salt solution at 8%, 10%, 12% and 15% for 5-20 hours. As the results, $3.5{\times}10^5-1.7{\times}10^6$, $3.4{\times}10^5-2.5{\times}10^6$, $5.4{\times}10^5-2.3{\times}10^6$, $4.0{\times}10^5-2.3{\times}10^6$ CFU/g were detected for E. coli in samples at different treatment conditions. $1.9{\times}10^4-4.1{\times}10^4$, $4.1{\times}10^3-2.8{\times}10^4$, $1.5{\times}10^3-7.8{\times}10^3$, $2.2{\times}10^4-6.6{\times}10^4$ CFU/g were detected for S. aureus in samples at different treatment conditions. Salmonella typhimurium was detected in salted cabbage with various salt concentration after salting for 5 hrs, the result ranged from $2.5{\times}10^5$ to $3.8{\times}10^6$ CFU/g, and change of microorganism was the smallest in salted cabbage under the concentration of salting solution at 10% for 15 hours. The cabbage salted in 10% salting solution for 15 hours were washed with water for 2 and 3 times, with chlorine for 3 times, and with acetic acid for 3 times. E. coli was detected in the samples washed with water for 2 and 3 times, washed with chlorine for 3 times. The contamination of S. aureus was $3.0{\times}10^5$ CFU/g in the samples washed with water for 2 times, $5.6{\times}10^3$ CFU/g in the samples washed with acetic acid for 3 times, $3.6{\times}10^5$ CFU/g in the samples washed with water for 3 times and same amount in the samples washed with chlorine for 3 times. According to the results, the contamination of S. aureus was $5.6{\times}10^3$ CFU/g lower in samples washed with chlorine and acetic acid than that in samples washed with water. In case of S. typhimurium, it has been detected in samples washed with water and chlorine, $3.0{\times}10^1$ CFU/g as the lowest concentration among all the samples was measured in the samples washed with acetic acid for 3 times.
Internet commerce has been growing at a rapid pace for the last decade. Many firms try to reach wider consumer markets by adding the Internet channel to the existing traditional channels. Despite the various benefits of the Internet channel, a significant number of firms failed in managing the new type of channel. Previous studies could not cleary explain these conflicting results associated with the Internet channel. One of the major reasons is most of the previous studies conducted analyses under a specific market condition and claimed that as the impact of Internet channel introduction. Therefore, their results are strongly influenced by the specific market settings. However, firms face various market conditions in the real worlddensity and disutility of using the Internet. The purpose of this study is to investigate the impact of various market environments on a firm's optimal channel strategy by employing a flexible game theory model. We capture various market conditions with consumer density and disutility of using the Internet.
shows the channel structures analyzed in this study. Before the Internet channel is introduced, a monopoly manufacturer sells its products through an independent physical store. From this structure, the manufacturer could introduce its own Internet channel (MI). The independent physical store could also introduce its own Internet channel and coordinate it with the existing physical store (RI). An independent Internet retailer such as Amazon could enter this market (II). In this case, two types of independent retailers compete with each other. In this model, consumers are uniformly distributed on the two dimensional space. Consumer heterogeneity is captured by a consumer's geographical location (ci) and his disutility of using the Internet channel (${\delta}_{N_i}$).
shows various market conditions captured by the two consumer heterogeneities.
(a) illustrates a market with symmetric consumer distributions. The model captures explicitly the asymmetric distributions of consumer disutility in a market as well. In a market like that is represented in
(c), the average consumer disutility of using an Internet store is relatively smaller than that of using a physical store. For example, this case represents the market in which 1) the product is suitable for Internet transactions (e.g., books) or 2) the level of E-Commerce readiness is high such as in Denmark or Finland. On the other hand, the average consumer disutility when using an Internet store is relatively greater than that of using a physical store in a market like (b). Countries like Ukraine and Bulgaria, or the market for "experience goods" such as shoes, could be examples of this market condition.
summarizes the various scenarios of consumer distributions analyzed in this study. The range for disutility of using the Internet (${\delta}_{N_i}$) is held constant, while the range of consumer distribution (${\chi}_i$) varies from -25 to 25, from -50 to 50, from -100 to 100, from -150 to 150, and from -200 to 200.
summarizes the analysis results. As the average travel cost in a market decreases while the average disutility of Internet use remains the same, average retail price, total quantity sold, physical store profit, monopoly manufacturer profit, and thus, total channel profit increase. On the other hand, the quantity sold through the Internet and the profit of the Internet store decrease with a decreasing average travel cost relative to the average disutility of Internet use. We find that a channel that has an advantage over the other kind of channel serves a larger portion of the market. In a market with a high average travel cost, in which the Internet store has a relative advantage over the physical store, for example, the Internet store becomes a mass-retailer serving a larger portion of the market. This result implies that the Internet becomes a more significant distribution channel in those markets characterized by greater geographical dispersion of buyers, or as consumers become more proficient in Internet usage. The results indicate that the degree of price discrimination also varies depending on the distribution of consumer disutility in a market. The manufacturer in a market in which the average travel cost is higher than the average disutility of using the Internet has a stronger incentive for price discrimination than the manufacturer in a market where the average travel cost is relatively lower. We also find that the manufacturer has a stronger incentive to maintain a high price level when the average travel cost in a market is relatively low. Additionally, the retail competition effect due to Internet channel introduction strengthens as average travel cost in a market decreases. This result indicates that a manufacturer's channel power relative to that of the independent physical retailer becomes stronger with a decreasing average travel cost. This implication is counter-intuitive, because it is widely believed that the negative impact of Internet channel introduction on a competing physical retailer is more significant in a market like Russia, where consumers are more geographically dispersed, than in a market like Hong Kong, that has a condensed geographic distribution of consumers.