• Economic and Environmental Geology
• /
• v.22 no.1
• /
• pp.35-63
• /
• 1989

Geochemical characteristics of the Guryongsan (Ogcheon) uraniferous black slate show that this is an analogue to the conventional Chattanooga and Alum shales in occurrences. Whereas, its highest enrichment ratio in metals including uranium, among others, is explained by the cyclic sedimentation of the black muds and quartz-rich silts, and the uniform depositional condition with some what higher pH condition compared to the conditions of the known occurrences. The cyclic sedimentation, caused by the periodic open and close of the silled basin, has brought about the flush-out) of the uranium depleted water and the recharge with the new metal-rich sea water, which consequently contributed to the high concentration of metals in mud. The metal-rich marine black muds, which mostly occur in the early to middle Palaeozoic times, is attributed by the geologic conditions which related to the atmospheric oxygen contents, and these are scarcely met in the late Precambrian and/or with the onset of Palaeozoic era in the geologic evolution of the earth.

• Korean Journal of Soil Science and Fertilizer
• /
• v.44 no.6
• /
• pp.1071-1079
• /
• 2011

In this study, coal combustion ash (CCA) was evaluated for its stabilization effect on acidic mine waste with column experiment. Total of six treatments were installed depending on mixing ratio between coal wastes and CCA (0, 20, 40%) and mixing method (completely mixing and layered). Artificial acidic rain (pH 5.6) was used for feeding solution with flow rate of $0.05mL\;min^{-1}$. Result showed that higher pH of leachate was observed as more CCA was mixed. The highest pH in leachate was measured when 40% of CCA was mixed with coal waste (pH of 5.8). Also, complete mixing with CCA and coal waste was more effective to increase the pH of leachate than layered treatment. Regarding the reduction of soluble Fe amount, the highest efficiency (78%) was observed when 20% of coal ash was completely mixed with mine waste. Based on those result, optimum mixing ratio of coal ash with mine waste can be ranged 20-40% depending on environmental circumstances in the field.

• Korean Journal of Soil Science and Fertilizer
• /
• v.43 no.6
• /
• pp.930-936
• /
• 2010

There is very important to investigate long-term trend of soil chemical properties and quality index for sustainable agriculture and production of agricultural safety products. Monitoring on soil chemical properties in paddy soils was conducted as one cycle with 4 years from 1999 to 2007. Paddy soil samples were taken from 4,007, 1,970, 2,070 sites in 1999, 2003 and 2007, respectively. With these data, soil quality index (SQI) was evaluated by method that Yoon et al suggested in 2004. Chemical properties of paddy soils were 5.8 for pH, 24 g $kg^{-1}$ for organic matter, 132 mg $kg^{-1}$ for available phosphate, 0.29 cmol_c\; kg-1 for exchangeable potassium, 4.7 $cmol_c\;kg^{-1}$ for exchangeable calcium, 1.3 $cmol_c\;kg^{-1}$ for exchangeable magnesium and 126 mg $kg^{-1}$ for available silicate in 2007. Long-term change was shown that pH has increased gradually whereas exchangeable potassium has decreased. However, reasonably large changes were found. Exchangeable calcium and available silicate level in 1999 was 4.0 $cmol_c\;kg^{-1}$, 86 mg $kg^{-1}$, but had risen to 4.7 $cmol_c\;kg^{-1}$, 126 mg $kg^{-1}$ in 2007, respectively. The change of paddy soils quality index was increased gradually and increasement of silicate quality index was higher than other quality indicators.

• Journal of Korean Society of Forest Science
• /
• v.111 no.2
• /
• pp.311-318
• /
• 2022

We conducted this study to derive the site index, which is a criterion for the planting of Robinia pseudoacacia, a honey plant, and to investigate the diameter distribution change by derived site index. We applied the Chapman-Richards equation model to estimate the site index of the Robinia pseudoacacia stand. The site index was distributed within the range of 16-22 when the base age was 30 years. The fitness index of the site index estimation model was low, but we judged that there was no problem in the application because the residual distribution of the equation had not shifted to one side. We used the Weibull diameter distribution function to determine the diameter distribution of the Robinia pseudoacacia stand by site index. We used the mean diameter and the dominant tree height as independent variables to present the diameter distribution, and our analysis procedure was to estimate and recover the parameters of the Weibull diameter distribution function. We used the mean diameter and the dominant tree height of the Robinia pseudoacacia stand to show distribution by diameter class, and the fitness index for dbh distribution estimation was about 80.5%. As a result of schematizing the diameter distribution by site indices as a 30-year-old, we found that the higher the site index, the more the curve of the diameter distribution moved to the right. This suggests that if the plantation were to be established in a high site index stand, considering the suitable trees on the site, the growth of Robinia pseudoacacia woul d become active, and not onl y the production of wood but al so the production of honey would increase. We therefore anticipate that the site index classification table and curve of this Robinia pseudoacacia stand will become the standard for decision making in the plantation and management of this tree.

• Economic and Environmental Geology
• /
• v.5 no.4
• /
• pp.187-209
• /
• 1972

Drilling position is one of the most important factors affecting on the blasting effects. There has been many reports on several blasting factors of burn-cut by Messrs. Brown and Cook, but in this study the author tried to compare drilling positions of burn-cut to pyramid-cut, and also to correlate burn-cut effects of drilling patterns, not being dealt by Prof. Ito in his theory, which emphasized on dynamical stress analysis between explosion and free face. According to former theories, there break out additional tensile stress reflected at the free face supplemented to primary compressive stress on the blasting with one-free-face. But with these experimented new drilling patterns of burn-cut, more free faces and nearer distance of each drilling holes make blasting effects greater than any other methods. To promote the above explosive effect rationary, it has to be considered two important categories under-mentioned. First, unloaded hole in the key holes should be drilled in wider diameter possibly so that it breaks out greater stress relief. Second, key holes possibly should have closer distances each other to result clean blasting. These two important factors derived from experiments with, theories of that the larger the dia of the unloaded hole, it can be allowed wider secondary free faces and closes distances of each holes make more developed stress relief, between loaded and unloaded holes. It was suggested that most ideal distance between holes is about 4 clearance in U. S. A., but the author, according to the experiments, it results that the less distance allow, the more effective blasting with increased broken rock volume and longer drifted length can be accomplished. Developed large hole burn-cut method aimed to increase drifting length technically under the above considerations, and progressive success resulted to achieve maximum 7 blasting cycles per day with 3.1m drifting length per cycle. This achievement originated high-speed-drifting works, and it was also proven that application of Metallic AN-FO on large hole burn-cut method overcomes resistance of one-free-face. AN-FO which was favored with low price and safety handling is the mixture of the fertilizer or industrial Ammonium-Nitrate and fuel oil, and it is also experienced that it shows insensible property before the initiation, but once it is initiated by the booster, it has equal explosive power of Ammonium Nitrate Explosives (ANE). There was many reports about AN-FO. On AN-FO mixing ratio, according to these experiments, prowdered AN-FO, 93.5 : 6.5 and prilled AN-FO 94 : 6, are the best ratios. Detonation, shock, and friction sensities are all more insensitive than any other explosives. Residual gas is not toxic, too. On initation and propagation of the detonation test, prilled AN-FO is more effective than powered AN-FO. AN-FO has the best explosion power at 7 days elapsed after it has mixed. While AN-FO was used at open pit in past years prior to other conditions, the author developed new improved explosives, Metallic AN-FO and Underwater explosive, based on the experiments of these fundmental characteristics by study on its usage utilizing AN-FO. Metallic AN-FO is the mixture of AN-FO and Al, Fe-Si powder, and Underwater explosive is made from usual explosive and AN-FO. The explanations about them are described in the other paper. In this study, it is confirmed that the blasting effects of utilizing AN-FO explosives are very good.

• Korean Journal of Soil Science and Fertilizer
• /
• v.43 no.3
• /
• pp.363-373
• /
• 2010

"Curve number" (CN) indicates the runoff potential of an area. The US Soil Conservation Service (SCS)'s CN method is a simple, widely used, and efficient method for estimating the runoff from a rainfall event in a particular area, especially in ungauged basins. The use of soil maps requested from end-users was dominant up to about 80% of total use for estimating CN based rainfall-runoff. This study introduce the use of soil maps with respect to hydrologic and watershed management focused on hydrologic soil group and a case study resulted in assessing effective rainfall and runoff hydrograph based on SCS-CN method in a small watershed. The ratio of distribution areas for hydrologic soil group based on detailed soil map (1:25,000) of Korea were 42.2% (A), 29.4% (B), 18.5% (C), and 9.9% (D) for HSG 1995, and 35.1% (A), 15.7% (B), 5.5% (C), and 43.7% (D) for HSG 2006, respectively. The ratio of D group in HSG 2006 accounted for 43.7% of the total and 34.1% reclassified from A, B, and C groups of HSG 1995. Similarity between HSG 1995 and 2006 was about 55%. Our study area was located in Sosu-myeon, Goesan-gun including an approx. 44 $km^2$-catchment, Chungchungbuk-do. We used a digital elevation model (DEM) to delineate the catchments. The soils were classified into 4 hydrologic soil groups on the basis of measured infiltration rate and a model of the representative soils of the study area reported by Jung et al. 2006. Digital soil maps (1:5,000) were used for classifying hydrologic soil groups on the basis of soil series unit. Using high resolution satellite images, we delineated the boundary of each field or other parcel on computer screen, then surveyed the land use and cover in each. We calculated CN for each and used those data and a land use and cover map and a hydrologic soil map to estimate runoff. CN values, which are ranged from 0 (no runoff) to 100 (all precipitation runs off), of the catchment were 73 by HSG 1995 and 79 by HSG 2006, respectively. Each runoff response, peak runoff and time-to-peak, was examined using the SCS triangular synthetic unit hydrograph, and the results of HSG 2006 showed better agreement with the field observed data than those with use of HSG 1995.

• Journal of Distribution Research
• /
• v.16 no.1
• /
• pp.95-115
• /
• 2011

Food service is the major part of franchise business in Korea, accounting for 69.9% of the brands in the market. As the food service industry becomes mature, many franchisees have struggled to survive in the market. In general, consumers have higher levels of expectation toward service quality of franchised outlets compared that of (non-franchised) independent ones. They also tend to believe that franchisees deliver standardized service at the uniform food price, regardless of their locations. Such beliefs seem to be important reasons that consumers prefer franchised outlets to independent ones. Nevertheless, few studies examined the impact of qualify features of franchisees on customer satisfaction so far. To this end, this study examined the characteristics of various quality features of franchisees in the food service industry, regarding their relationship with customer satisfaction and dissatisfaction. The quality perception of heavy-users was also compared with that of light-users in order to find insights for developing differentiated marketing strategy for the two segments. Customer satisfaction has been understood as a one-dimensional construct while there are recent studies that insist two-dimensional nature of the construct. In this regard, Kano et al. (1984) suggested to categorize quality features of a product or service into five types, based on their relation to customer satisfaction and dissatisfaction: Must-be quality, Attractive quality, One-dimensional quality, Indifferent quality, and Reverse quality. According to the Kano model, customers are more dissatisfied when Must-be quality(M) are not fulfilled, but their satisfaction does not arise above neutral no matter how fully the quality fulfilled. In comparison, customers are more satisfied with a full provision of Attactive quality(A) but manage to accept its dysfunction. One-dimensional quality(O) results in satisfaction when fulfilled and dissatisfaction when not fulfilled. For Indifferent quality(I), its presence or absence influences neither customer satisfaction nor dissatisfaction. Lastly, Reverse quality(R) refers to the features whose high degree of achievement results in customer dissatisfaction rather than satisfaction. Meanwhile, the basic guidelines of the Kano model have a limitation in that the quality type of each feature is simply determined by calculating the mode statistics. In order to overcome such limitation, the relative importance of each feature on customer satisfaction (Better value; b) and dissatisfaction (Worse value; w) were calculated following the formulas below (Timko, 1993). The Better value indicates how much customer satisfaction is increased by providing the quality feature in question. In contrast, the Worse value indicates how much customer dissatisfaction is decreased by providing the quality feature. Better = (A + O)/(A+O+M+I) Worse = (O+M)/(A+O+M+I)(-1) An on-line survey was performed in order to understand the nature of quality features of franchisees in the food service industry by applying the Kano Model. A total of twenty quality features (refer to the Table 2) were identified as the result of literature review in franchise business and a pre-test with fifty college students in Seoul. The potential respondents of our main survey was limited to the customers who have visited more than two restaurants/stores of the same franchise brand. Survey invitation e-mails were sent out to the panels of a market research company and a total of 257 responses were used for analysis. Following the guidelines of Kano model, each of the twenty quality features was classified into one of the five types based on customers' responses to a set of questions: "(1) how do you feel if the following quality feature is fulfilled in the franchise restaurant that you visit," and "(2) how do you feel if the following quality feature is not fulfilled in the franchise restaurant that you visit." The analyses revealed that customers' dissatisfaction with franchisees is commonly associated with the poor level of cleanliness of the store (w=-0.872), kindness of the staffs(w=-0.890), conveniences such as parking lot and restroom(w=-0.669), and expertise of the staffs(w=-0.492). Such quality features were categorized as Must-be quality in this study. While standardization or uniformity across franchisees has been emphasized in franchise business, this study found that consumers are interested only in uniformity of price across franchisees(w=-0.608), but not interested in standardizations of menu items, interior designs, customer service procedures, and food tastes. Customers appeared to be more satisfied when the franchise brand has promotional events such as giveaways(b=0.767), good accessibility(b=0.699), customer loyalty programs(b=0.659), award winning history(b=0.641), and outlets in the overseas market(b=0.506). The results are summarized in a matrix form in Table 1. Better(b) and Worse(w) index indicate relative importance of each quality feature on customer satisfaction and dissatisfaction, respectively. Meanwhile, there were differences in perceiving the quality features between light users and heavy users of any specific franchise brand in the food service industry. Expertise of the staffs was labeled as Must-be quality for heavy users but Indifferent quality for light users. Light users seemed indifferent to overseas expansion of the brand and offering new menu items on a regular basis, while heavy users appeared to perceive them as Attractive quality. Such difference may come from their different levels of involvement when they eat out. The results are shown in Table 2. The findings of this study help practitioners understand the quality features they need to focus on to strengthen the competitive power in the food service market. Above all, removing the factors that cause customer dissatisfaction seems to be the most critical for franchisees. To retain loyal customers of the franchise brand, it is also recommended for franchisor to invest resources in the development of new menu items as well as training programs for the staffs. Lastly, if resources allow, promotional events, loyalty programs, overseas expansion, award-winning history can be considered as tools for attracting more customers to the business.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.83-102
• /
• 2021

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.

• Journal of agricultural medicine and community health
• /
• v.37 no.1
• /
• pp.12-22
• /
• 2012

Objectives: This study aimed to compare the nutritional risk, health status and depression levels of young-old (65-74 years) and old-old (75-84 years) women on low-income. Methods: A total of 624 elderly women, each over 65 years of age, participated in this study under the auspices of a community social center. Data were collected from June to August 2011 by means of personal interviews which employed questionnaires. The research tools used in this study were the nutritional risk measuring Mini Nutritional Assesment (MNA) by Kim (2000), perceived health status developed by Lawton et al. (1982), Elderly Depression Criterion developed by Sheikh & Yesavage (1985). The collected data were analyzed using the SPSS WIN 12.0 Program. Results: Nutritional risk, perceived health status and depression levels showed a significant difference between young-old and old-old. There was a positive correlation between nutritional risk and depression and a negative correlation between nutritional risk and perceived health status. A 38.2% variance in depression levels of young-old and a 29.7% variance in depression levels of old-old were explained by perceived health status, nutritional risk and the number of people living together. Conclusion: The findings demonstrate variances in depression levels among low - income women differing in age. As a result, the outcomes of this study ought to be employed in the development of future programs aimed at promoting the health of elderly women.

• Analytical Science and Technology
• /
• v.32 no.6
• /
• pp.243-251
• /
• 2019

Microplastics (MP) are found in large quantities in the oceans, posing a major threat to the ecosystem. In Korea, MPs have been reported to be detected in sea salts. In order to analyze MPs, information on their composition, size, and shape is required. FT-IR microscopy is used frequently to measure sizes larger than 20 ㎛. Recently, however, Raman microscopy, which can analyze ultrafine plastics below 20 ㎛, has been applied extensively. In this study, 10.0 g samples of commercially available salts were dissolved and filtered through a 45 ㎛ mesh filter with a size of 25.4 mm × 25.4 mm. These filtered samples were then analyzed by both FT-IR microscopy and Raman microscopy. A total of four MPs, including three polyethylene (PE) of size 70-100 ㎛ and a polypropylene (PP) of size 170 ㎛, were detected by FT-IR microscopy, while 10 MPs, including nine PE of size 10-120 ㎛ and one polystyrene (PS) of size 40 ㎛, were detected by Raman microscopy. Approximately, 1,000 MPs/kg was estimated, which was almost two times higher than the previous reported levels (~550-681 particles/kg in sea salts); this is because Raman microscopy can detect much smaller MPs than FT-IR microscopy. A total of 113 particles were found using Raman microscopy: Carbon (35, 31.5 %), minerals (28, 25 %), and glass (16, 14.4 %) were dominant, forming around 70% of the total, but MPs (10, 8.8 %) and cellulose (5, 4.5 %) were also found. Raman microscopy has great potential as an accurate method for measuring MPs, as it can measure smaller size MPs than FT-IR microscopy. It also has a reduced sample preparation time.