• Journal of the East Asian Society of Dietary Life
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• v.10 no.2
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• pp.116-128
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• 2000

The purpose of this study is to analyze the nutrient intakes and growth development of rural middle school students provided with and without the national school lunch program(NSLP). The subjects consisted of 340 rural middle school students provided with(n=177) and without(n=163) NSLP. Anthropometric measurements were taken for body weight, height, triceps skinfold thickness and percentage of body fat, and nutrient intakes were assessed by food record method. The results of this study were summarized as follows: There was no significant difference in the height, body weight girls provided with (155.8cm 47.2kg) and without (156.0cm, 49.7kg) NSLP. Total energy intakes of boys were 2123kca1 in with NSLP and 1857kca1 in without NSLP. Total energy intakes of girls were 1913kca1 in with NSLP and 1814kca1 in without NSLP. Total daily energy was provided in the ratio of 19.1%, 39.8%, 32.4% and 8.7% by breakfast, lunch, dinner and snacks in the with NSLP and 17.5%, 32.0%, 34.8% and 15.7% in without NSLP, respectively. Phosphorus, vitamin A, vitamin E, ascorbic acid, thiamin, riboflavin, niacin intakes were above the RDA in with NSLP. In without NSLP, phosphorus, vitamin E, thiamin intakes were above the RDA. however, calcium. iron, vitamin A, vitamin B$_{6}$ were less than the RDA. The study showed that total daily energy and nutrient intakes were significantly higher in students provided with than without school-lunch. Thus, the school-lunch program is recommended and necessary to improve the nutritional status of middle school students.

• Asian Journal of Turfgrass Science
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• v.17 no.1
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• pp.1-12
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• 2003

Research was Initiated to investigate germination characteristics of cool-season grasses (CSG). Several turfgrasses were tested in different experiments. Experiments I and III were conducted under a room temperature condition of 16$^{\circ}C$ to 23 $^{\circ}C$ and under a constant light condition at 25 $^{\circ}C$, respectively. An alternative environment condition that is a requirement for a CSG germination test by International Seed Testing Association (ISTA) was applied in the Experiment II, consisting of 8-hr light at 25 $^{\circ}C$ and 16-hr dark at 15 $^{\circ}C$. In each experiment, data such as early germinating vigor, germination speed and germination rate were evaluated. Six turfgrass entries were comprised of two varieties each from Kentucky bluegrass (KB, Poa pratensis L.), perennial ryegrass (PR, Lolium perenne L.), and tall fescue (TF, Festuca arundinacea Schreb.), respectively. Significant differences were observed in early germinating vigor, germination speed and germination rate. Early germinating vigor as measured by days to 70% seed germination was variable according to environment conditions, turfgrasses and varieties. It was less than 6 days in PR and 6 to 9 days in TF. However, KB resulted in 11 to 13 days under an alternative condition and 11 to 28 days under a room temperature condition. The germination speed was fastest in PR of 7 to 10 days and slowest in KB of 14 to 21 days. However, intermediate speed of 10 to 14 days was associated with TF. There were considerable variations in germination rate among turfgrasses according to different conditions. Generally, PR and TF germinated well, regardless of environment conditions. However, a great difference was observed among KB varieties, when compared with others. Under a room temperature condition, total germination rate was 71.0% in Midnight and 77.7% in Award. And it increased under an alternative condition, which was 81.7% and 91.7% in Award and Midnight, respectively. However, the poorest rate was found under a constant temperature condition, resulting in 18.0% in Award and 15.3% in Midnight. These results suggest that an intensive germination test required by ISTA be needed prior to the decision of seeding rate, including early germinating vigor and germination speed as well as total germination rate. KB is very sensitive to environment conditions and thus its variety selection should be based on a careful expertise.

• 한국지구물리탐사학회:학술대회논문집
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• 2002.09a
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• pp.139-162
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• 2002

Since weak zones or geological lineaments are likely to be eroded, weak zones may develop beneath rivers, and a careful evaluation of ground condition is important to construct structures passing through a river. Dc resistivity surveys, however, have seldomly applied to the investigation of water-covered area, possibly because of difficulties in data aquisition and interpretation. The data aquisition having high quality may be the most important factor, and is more difficult than that in land survey, due to the water layer overlying the underground structure to be imaged. Through the numerical modeling and the analysis of case histories, we studied the method of resistivity survey at the water-covered area, starting from the characteristics of measured data, via data acquisition method, to the interpretation method. We unfolded our discussion according to the installed locations of electrodes, ie., floating them on the water surface, and installing at the water bottom, since the methods of data acquisition and interpretation vary depending on the electrode location. Through this study, we could confirm that the dc resistivity method can provide the fairly reasonable subsurface images. It was also shown that installing electrodes at the water bottom can give the subsurface image with much higher resolution than floating them on the water surface. Since the data acquired at the water-covered area have much lower sensitivity to the underground structure than those at the land, and can be contaminated by the higher noise, such as streaming potential, it would be very important to select the acquisition method and electrode array being able to provide the higher signal-to-noise ratio data as well as the high resolving power. The method installing electrodes at the water bottom is suitable to the detailed survey because of much higher resolving power, whereas the method floating them, especially streamer dc resistivity survey, is to the reconnaissance survey owing of very high speed of field work.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.

• The Korean Journal of Archival Studies
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• no.26
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• pp.103-149
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• 2010

Documentation strategy has been experimented in various subject areas and local regions since late 1980's when it was proposed as archival appraisal and selection methods by archival communities in the United States. Though it was criticized to be too ideal, it needs to shed new light on the potentialities of the strategy for documenting local regions in digital environment. The purpose of this study is to analyse the implementation issues of documentation strategy and to suggest the directions for documenting local regions of Korea through the application of the strategy. The documentation strategy which was developed more than twenty years ago in mostly western countries gives us some implications for documenting local regions even in current digital environments. They are as follows; Firstly, documentation strategy can enhance the value of archivists as well as archives in local regions because archivist should be active shaper of history rather than passive receiver of archives according to the strategy. It can also be a solution for overcoming poor conditions of local archives management in Korea. Secondly, the strategy can encourage cooperation between collecting institutions including museums, libraries, archives, cultural centers, history institutions, etc. in each local region. In the networked environment the cooperation can be achieved more effectively than in traditional environment where the heavy workload of cooperative institutions is needed. Thirdly, the strategy can facilitate solidarity of various groups in local region. According to the analysis of the strategy projects, it is essential to collect their knowledge, passion, and enthusiasm of related groups to effectively implement the strategy. It can also provide a methodology for minor groups of society to document their memories. This study suggests the directions of documenting local regions in consideration of current archival infrastructure of Korean as follows; Firstly, very selective and intensive documentation should be pursued rather than comprehensive one for documenting local regions. Though it is a very political problem to decide what subject has priority for documentation, interests of local community members as well as professional groups should be considered in the decision-making process seriously. Secondly, it is effective to plan integrated representation of local history in the distributed custody of local archives. It would be desirable to implement archival gateway for integrated search and representation of local archives regardless of the location of archives. Thirdly, it is necessary to try digital documentation using Web 2.0 technologies. Documentation strategy as the methodology of selecting and acquiring archives can not avoid subjectivity and prejudices of appraiser completely. To mitigate the problems, open documentation system should be prepared for reflecting different interests of different groups. Fourth, it is desirable to apply a conspectus model used in cooperative collection management of libraries to document local regions digitally. Conspectus can show existing documentation strength and future documentation intensity for each participating institution. Using this, documentation level of each subject area can be set up cooperatively and effectively in the local regions.

• Journal of Food Hygiene and Safety
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• v.34 no.1
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• pp.22-29
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• 2019

Validamycin A is an aminoglycoside fungicide produced by Streptomyces hygroscopicus that inhibits trehalase. The purpose of this study was to develop a method for detecting validamycin A in agricultural samples to establish MRL values for use in Korea. The validamycin A residues in samples were extracted using methanol/water (50/50, v/v) and purified with a hydrophilic-lipophilic balance (HLB) cartridges. The analyte was quantified and confirmed by liquid chromatograph-tandem mass spectrometer (LC-MS/MS) in positive ion mode using multiple reaction monitoring (MRM). Matrix-matched calibration curves were linear over the calibration ranges (0.005~0.5 ng) into a blank extract with $R^2$ > 0.99. The limits of detection and quantification were 0.005 and 0.01 mg/kg, respectively. For validation validamycin A, recovery studies were carried out three different concentration levels (LOQ, $LOQ{\times}10$, $LOQ{\times}50$, n = 5) with five replicates at each level. The average recovery range was from 72.5~118.3%, with relative standard deviation (RSD) less than 10.3%. All values were consistent with the criteria ranges requested in the Codex guidelines (CAC/GL 40-1993, 2003) and the NIFDS (National Institute of Food and Drug Safety) guideline (2016). Therefore, the proposed analytical method is accurate, effective and sensitive for validamycin A determination in agricultural commodities.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.

• The Korean Journal of Nuclear Medicine Technology
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• v.22 no.2
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• pp.67-73
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• 2018

$[^{11}C]PIB$ synthesis has been performed by a loop-methylation and HPLC purification in our lab. However, this method is time-consuming and requires complicated systems. Thus, we developed an on-cartridge method which simplified the synthetic procedure and reduced time greatly by removing HPLC purification step. We compared 6 different cartridges and evaluated the $[^{11}C]PIB$ production yields and specific activities. $[^{11}C]MeOTf$ was synthesized by using TRACERlab FXC Pro and was transferred into the cartridge by blowing with helium gas for 3 min. To remove byproducts and impurities, cartridges were washed out by 20 mL of 30% EtOH in 0.5 M $NaH_2PO_4$ solution (pH 5.1) and 10 mL of distilled water. And then, $[^{11}C]PIB$ was eluted by 5 mL of 30% EtOH in 0.5 M $NaH_2PO_4$ into the collecting vial containing 10 mL saline. Among the 6 cartridges, only tC18 environmental cartridge could remove impurities and byproducts from $[^{11}C]PIB$ completely and showed higher specific activity than traditional HPLC purification method. This method took only 8 ~ 9 min from methylation to formulation. For the tC18 environmental cartridge and conventional HPLC loop methods, the radiochemical yields were $12.3{\pm}2.2%$ and $13.9{\pm}4.4%$, respectively, and the molar activities were $420.6{\pm}20.4GBq/{\mu}mol$ (n=3) and $78.7{\pm}39.7GBq/{\mu}mol$ (n=41), respectively. We successfully developed a facile on-cartridge methylation method for $[^{11}C]PIB$ synthesis which enabled the procedure more simple and rapid, and showed higher molar radio-activity than HPLC purification method.

• The Journal of Korean Philosophical History
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• no.23
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• pp.99-128
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• 2008

This research analyzes some Korean historical figures and presents the core values of their leaderships so that we can bring up the theory of leadership which would be compatible with the current circumstances around Korea. Through this work, we expected that we would not only find out typical examples among historical leaders but also reaffirm our identities in our history. As a result of the research, it was possible to classify some figures in history into several patterns and discover their archetypal qualities. Those qualities were 'transform(實事)', 'challenge(決死)', 'energize(風流)', 'create(創案)', and 'envision(開新)' respectively. Among the qualities, this research concentrated on the quality of 'challenge', exclusively 'death-defying spirit'. This spirit is the one with which historical leaders could sacrifice their lives for their great causes. This research selected twelve figures as incarnations of death-defying spirit, who are Gyebaek(階伯), Ganggamchan(姜邯贊), Euljimundeok(乙支文德), Choeyoung(崔瑩),ChungMongju(鄭夢周), Seongsammun (成三問), Yisunsin(李舜臣), Gwakjaewoo(郭再祐), Choeikhyeon(崔益鉉), Anjunggeun(安重根), Yunbonggil(尹奉吉), Yijun(李儁). Through analyzing their core values and abilities and categorizing some historical cases into four spheres such as a private sphere, relations sphere, a community sphere, and a society sphere, we came to find a certain element in common among those figures. It was that they eventually took the lead by showing the goal and the ideal to their people at all times. Moreover, their goals were always not only obvious but also unwavering. In the second chapter, I described the core value in a private sphere, so called '志靑靑'. It implies that a leader should set his ultimate goal and then try to attain it with an unyielding will. Obvious self-confidence and unfailing self-creed are core values in a private sphere. In the third chapter, I described the core value in a relative sphere, the relationship between one and others. It is '守信結義'. It indicates that a leader should win confidence from others by discharging his duties in the relation with others. Confidence is the highest leveled affection to others. Thus, mutual reliance should be based on truthful sincerity and affection toward others. Stubbornness and strictness are needed not to be prompted by pity simultaneously. In the fourth chapter, I described the core value in a community sphere. It is '丹心合力'. For this value, what are required to a leader are both his community spirit and his loyalty to one's community. Moreover, the strong sense of responsibility and the attitude of taking an initiative among others are also required. Thus, it can be said that the great power to conduct the community is so called fine teamwork. What's more, the attitude of the leader can exert a great influence on his community. In the fifth chapter, I described the core value of death defying spirit in the society sphere. This value might be more definite and explicit than other ones described above. A leader should prepare willingly for one's death to fulfill his great duties. 'What to do' is more important for a leader than 'how to do'. That is to say, a leader should always do righteous things. Efficiency is nothing but one of his interests. A leader must be the one who behaves himself always according to righteousness. Unless a leader's behaviors are based on righteousness, it is absolutely impossible that a leader exerts his leadership toward people very efficiently. Thus, it can be said that a true leader is the one not only who is of morality and but also who tries to fulfill his duties.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.19-42
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• 2012

Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.