• Korean Journal of Agricultural Science
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• v.2 no.1
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• pp.61-100
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• 1975

This study has been made to find out the possibilty of successfully using the following $K_2O$ recommended equation $K_2O\;kg/10a=(Ko/\sqrt{Ca+Mg}-Ks/\sqrt{Ca+Mg})sqrt{Ca+Mg}.\;47.\;B\;D$. where $Ko/sqrt{Ca+Mg}=0.03518+0.0007658\;Sio_2/O.M$. $K_Ssqrt{Ca+Mg}$=Exchangeable K me/100g/$\sqrt{Total\;soluble(Ca+Mg)me/100g\;in\;Soil}$ B. D. =Bulk density of top soil, when the dose of Nitrogen for rice is estimated from the following equation: $N\;kg/10a=(4.2+0.096\;SiO_2/O.M).F$ where $F=0.907+0.263x-0.013x^2$ $SiO_2/O.M=(available\;SiO_2=ppm)/(organic\;matter\;%)$in soil For this. two field experiments. one in sandy and the other in clay paddy soil. have been conducted using 3 levels of wollastonite (0, 500, 100kg/10a) as main treatments; 3 levels of $K_2O$ application were used as sub-plots. These were as follows : (1) 8kg of $K_2O$/10a regardless of the K activity-$K/\sqrt{Ca+Mg}$; (2) kg of $K_2O$/10a estimated from the above equation. and (3) same as (2) above plus additional 30% of $K_2O$. The dose of N kg/ 10a was determined from the above equation based on the value of $SiO_2$/O.M. ratio in each treatment. There were three replications. The leading variety of rice in Chung Chong Nam Do area. Akibare (introduced from Japan) was used. The data obtained. through soil and plant analysis and growth and yield observations. have been throughly examined to attain the following summarized conclusions. 1. The nitrogen dose. estimated from the above equation. was in excess for optimum growth of the rice variety Akibare; indicating the necessity of modification onthe value of "F" or the constants in the equation. The concept of using $SiO_2$/O.M. in the equation was shown to be applicable. 2. The dose of potash. estimated from the respective equation given above. also was in excess of the rice requirements indicating the necessity of minor change in the estimation of $Ko/\sqrt{Ca+Mg}$ value and some great modification in the calculation of $Ks/\sqrt{Ca+Mg}$ value for the equation; however the concept of using $K/\sqrt{Ca+Mg}$ as a basis of $K_2O$ recommendation was shown to be quite reasonable. 3. It was found. from the correlation study using the data of paddy yield and amount of $K_2O$ absorbed by rice plants that the substitution of the value of $Ks/\sqrt{Ca+Mg}$ in the equation for the vaule $Ks/\sqrt{Ca+Mg}=0.037+0.78K\;me/100g$ soil was much more applicable than using the value calculated from the data of soil and wollastonite analysis.

• 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.

• Korean Journal of Heritage: History & Science
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• v.51 no.3
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• pp.4-31
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• 2018

It is difficult to ascertain exactly when the Hongjuupseong (Town Wall) was first constructed, due to it had undergone several times of repair and maintenance works since it was piled up newly in 1415, when the first year of the reign of King Munjong (the 5th King of the Joseon Dynasty). Parts of its walls were demolished during the Japanese occupation, leaving the wall as it is today. Hongseong region is also susceptible to historical earthquakes for geological reasons. There have been records of earthquakes, such as the ones in 1978 and 1979 having magnitudes of 5.0 and 4.0, respectively, which left part of the walls collapsed. Again, in 2010, heavy rainfall destroyed another part of the wall. The fortress walls of the Hongjuupseong comprise various rocks, types of facing, building methods, and filling materials, according to sections. Moreover, the remaining wall parts were reused in repair works, and characteristics of each period are reflected vertically in the wall. Therefore, based on the vertical distribution of the walls, the Hongjuupseong was divided into type I, type II, and type III, according to building types. The walls consist mainly of coarse-grained granites, but, clearly different types of rocks were used for varying types of walls. The bottom of the wall shows a mixed variety of rocks and natural and split stones, whereas the center is made up mostly of coarse-grained granites. For repairs, pink feldspar granites was used, but it was different from the rock variety utilized for Suguji and Joyangmun Gate. Deterioration types to the wall can be categorized into bulging, protrusion of stones, missing stones at the basement, separation of framework, fissure and fragmentation, basement instability, and structural deformation. Manually and light-wave measurements were used to check the amount and direction of behavior of the fortress walls. A manual measurement revealed the sections that were undergoing structural deformation. Compared with the result of the light-wave measurement, the two monitoring methods proved correlational. As a result, the two measuring methods can be used complementarily for the long-term conservation and management of the wall. Additionally, the measurement system must be maintained, managed, and improved for the stability of the Hongjuupseong. The measurement of Nammunji indicated continuing changes in behavior due to collapse and rainfall. It can be greatly presumed that accumulated changes over the long period reached the threshold due to concentrated rainfall and subsequent behavioral irregularities, leading to the walls' collapse. Based on the findings, suggestions of the six grades of management from 0 to 5 have been made, to manage the Hongjuupseong more effectively. The applied suggested grade system of 501.9 m (61.10%) was assessed to grade 1, 29.5 m (3.77%) to grade 2, 10.4 m (1.33%) to grade 3, 241.2 m (30.80%) and grade 4. The sections with grade 4 concentrated around the west of Honghwamun Gate and the east of the battlement, which must be monitored regularly in preparation for a potential emergency. The six-staged management grade system is cyclical, where after performing repair and maintenance works through a comprehensive stability review, the section returned to grade 0. It is necessary to monitor thoroughly and evaluate grades on a regular basis.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.73-95
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• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.

• Korean journal of applied entomology
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• v.13 no.4 s.21
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• pp.181-204
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• 1974

The study has been carried out to investigate the occurrence, damage, host range, transmission and control of rice stripe virus in Korea since 1965. 1 Disease occur「once and damage : The virus infection during the seedling stage ranged from 1.3 to $8\%$. More symptom expression was found in regrowth of clipped rice than infected intact plants, and the greater infection took place in early seasonal culture than in ordinary seasonal culture. A higher incidence of the disease was found on the rows close to the bank, and gradually decreased toward the centre of the rice paddy. Disease occurrence and plant maturity was highly correlated in that the most japonica rice types were diseased when they were inoculated within 3 to 7 leaf stage, and$50\%$, $20\%$ and no diseaseb were found if they were inoculated at 9, 11 and 13 leaf stages, respectively. Symptom expression required 7-15 days when the plants were inoculated during 3-7 leaf stages, while it was 15-30days in the plants inoculated during 9-15 leaf stages. On Tongil variety the per cent disease was relatively higher when the plants were infected within 1.5-5 leaf stages than those at 9 leaf stage, and no disease was found on the plants infected after 15 leaf stage. The disease resulted in lowered growth rates, maturity and sterility of Tongil variety although the variety is known as tolerant to the virus. 2. Host range: Thirty five species of crops, pasture grasses and weeds were tested for their susceptibility to the virus. Twenty one out of 35 species tested were found to be susceptible. and 3 of them, Cyperus amuricus Maximowics var. laxus, Purcereus sanguinolentus Nees and Eriocaulon robustius Makino, were found as new hosts of the virus. 3. Transmission: The vector of the virus, Laodelphax striatellus, produces 5 generations a year. The peak of second generation adults occurred at June 20th and those of third was at about July 30th in Suweon area. In Jinju area the peak of second generation adult proceeded the peak at Suweon by 5-7 days. The peaak of third generation adult was higher than the second at Jinju, but at Suweon the reverse was true. The occurrence of viruliferous Laodelphax striatellus was 10-15, 9, 17, 8 and about $10\%$ from overwintered nymph, 1st generation nymph, 2nd generation adult, End generation nymph and the remaining generations, respectively. More viruliferous L. striatellus were found in the southern area than in the central area of Korea. The occurrence of viruliferous L. striatellus depended on the circumstances of the year. The per cent viruliferous vectors gin 2nd and 3rd generation adult, however, was consistantly higher than that of other generations. Matings of viruliferous L. striatellus resulted in $90\%$ viruliferous progenies, and the 3rd, 4th and 5th instars of the vector had higher infectiviey than the rest of the vector stages. The virus acquisition rate of non-viruliferous L. striatellus was $7-9\%$, These viruliferous L. striatellus, however, could not transmit the virus for more than 3 serial times. The optimum temperature for the transmission of the viru3 was $25-30^{\circ}C$, while rare transmission occurred when the temperature was below $15^{\circ}C$. The per cent of L. striatellus parasitization by Haplogonatopus atratus were $5-48\%$ during the period from June to the end of August, and the maximum parasitization was $32-48\%$ at around July 10. 4. Control: 1) Cultural practices; The deeper the depth of transplanting more the disease occurrence was found. The higher infection rate, $1.5-3.5\%$, was observed during the late stages of seedling beds, and the rate became lower, $1.0-2.0\%$, in the early period of paddy field in southern area. Early transplanting resulted in more infection than early seasonal culture, and the ordinary seasonal culture showed the lowest infection. The disease also was favored by earlier transplanting even under tile ordinary seasonal culture. The higher the nitrogen fertilizer level the more the disease occurrence was found in the paddy field. 2) Resistant varieties; Tongil varieties shelved the resistant reaction to the virus in greenhouse tests. In the tests for resistance on 955 varieties most japonica types shelved susceptible reactions, while the resistant varieties were found mostly from introduced varietal groups. 3) Chemical control; Earlier applications of chemicals, Disyston and Diazinon, showed better results when the test was made 4 days after inoculation in the greenhouse even though none of the insecticides shelved the complete control of the disease. Three serial applications of chemicals on June 14, June 20 and June 28 showed bettor results than one or two applications at any other dates under field conditions.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.5 no.1
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• pp.1-35
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• 1969

Attempts were made to obtain the fundamental knowledge on the quantitative constitution status of leaves and stem of elongating node-part, and the relationships between these morphological characteristics along with the nitrogen contents of leaves and grain yield were examined varing application amounts of nitrogen in rice plant. I. The agronomic characteristics of leaves and nodes of elongation node-part (4-node parts from the top of stem) were observed at heading stage with 20 leading rice varieties of Kang Won district. The results are summarized as follows: 1. Leaf area magnitude of the flag and the fourth leaf was smaller than that of the second and the third with the average value of flag leaf 18.61 $cm^2$, the second leaf 21.84 $cm^2$, the third 21.52 $cm^2$ and the fourth 18.56 $cm^2$. The weight of leaf blade showed an isotonic tendency with the magnitude of leaf area with the value of the flag leaf 97.0 mg, the second leaf 117.1 mg, the third 115.4 mg, and the fourth 95.3 mg. The weight of each leaf sheath was remarkably larger at the higher node-part than at the lower node-part of the stem with the value of flag leaf sheath 176.3 mg, the second 163.7 mg, the third 163.4 mg and the fourth 123.9 mg. Accordingly, the total leaf weight of each part was larger at the second and the third leaf than at the first and the fourth. Total plant weight of each part (weight of leaf blade, leaf sheath, and culm) also was larger at the middle node-part. 2. Coefficients of variation for the varietal differences of the morphological characteristics of elongating node-part were 12.75% for the leaf area, 15.29% for the weight of leaf blade, 15.90%, for the weight of leaf sheath, 11.42% for the weight of internode, 15.45% for the leaf weight (leaf blade ＆ leaf sheath) and 13.24% for the straw weight. And these coefficient values of the most characteristics were, on the whole, smaller at the second and the third node-part than at the first and the fourth node-part, but the coefficient value of the internode weight was rather small at the third and fourth node-part. 3. Constitutional ratio of each plant organ to the total plant weight in term of dry matter weight (excluding head and root wight) was 39.2% for the leaf sheath, 34.2% for the culm, 26.6% for the leaf blade. And ocnstitutional ratio of leaf sheath in term of dry matter weight was larger at the higher position in contrast with that of culm. 4. Average weight ration of leaf blade to culm, leaf sheath to culm, leaf blades to sheath and the leaf blades to culm plus leaf sheath were 77.7 %, 114.5%, 67.9% and 36.2%, respectively. With regard to the position of the plant organ, the weight ratio of leaf blade to culm and that of leaf sheath to culm were larger at higher part in contrast with that of leaf blade to leaf sheath. 5. Generally, there founded deep relationships between grain yield and each morphological characteristics of plant organ of elongating node-part as follows; Correlation coefficient between total area of 4 leaves (from flag to the fourth leaf) and grain yield was ${\gamma}$=0.666$^{**}$ In regard to the position of leaves, correlation coefficient values of flag, the second, the third and the fourth leaf were ${\gamma}$=0.659$^{**}$, ${\gamma}$=0.609$^{**}$, ${\gamma}$=0.464$^{*}$ and ${\gamma}$=0.523$^{*}$, respectively. Correlation coefficient between total weight of leaf blades and the grain yield was ${\gamma}$=0.678$^{**}$. In regard to the position of leaves, that of flag leaf was ${\gamma}$=0.691$^{**}$, and ${\gamma}$=0.654$^{**}$ for the second leaf, ${\gamma}$=0.570$^{**}$ for the third, and ${\gamma}$=0.544$^{**}$ for the fourth. Correlation between the weight of leaves (blade weight plus sheath weight) and the grain yield showed similar values. In the relationship between plant weight and grain yield there also was significant correlation, but with highly significant value only for the first node-part. There appeared correlation between total weight of leaf sheath and grain yield with the value of ${\gamma}$=0.572$^{**}$ and in regard to the position of each leaf sheath the values were ${\gamma}$=0.623$^{**}$ for the flag leaf, ${\gamma}$=0.486$^{**}$ for the second leaf, ${\gamma}$=0.513$^{**}$ for the third, ${\gamma}$=0.450$^{**}$ for the fourth. However, there was no significant correlation between culm weight and grain yield. 6. With respect to in gain yield, varietal differences in magnitude of leaf area, weight of leaf blade, leaf weight per unit area, weight of leaf sheath, culm weight, total leaf and stem weight were larger in the case of high yielding varieties and decreased in accordance with decreasing yield. And this tendency also was shown in the varietal differences of magnitude of each part. Variation in magnitude of each part for the leaf area, weight of leaf blade, culm weight was significantly small in high yielding varieties compared to low yielding varieties. 7. Plant constitutional ratio of each organ of the elongating node-part in term of weight magnitnde varied to som extent according to varieties indicating leaf blade 27.6%, leaf sheath 39.5%, culm 32.9% in the case of high yielding varieties, leaf blade 25.5%, leaf sheath 38.1%, culm 36.4% in the case of low yielding varieties, and medium yielding varieties showed intermadiate values. 8. Far higher values of the weight ration of leaf blade to culm and leaf sheath to culm were given to the high yielding varieties compared to low yielding varieties. And medium yielding varieties showed intermadiate values. II. Effects of application rate of nitrogen on the morphological characteristics of the elongating node-part, nitrogen content of leaf blade, and their relation with the grain yield of the rice were observed with 3 rice varieties; Shin No.2, Shirogane, and Jinheung varying application amounts of nitrogen as 8kg, 12kg and 16kg per 10 are. 1. As for the variation of morphological magnitude s affected by the amounts of nitrogen application, total leaf area (4 leaves from the flag leaf) increased to 16.5% at 12kg N plot, and about 30% at 16kg N polt compared to 8kg N plot and total weight of leaf blade also increased to similar extent, respectively, in contrast with weight of leaf sheath increasing 4.9% and 7.8%, respectively. However, the weight of culm decreased to 1.5% and 11.2%at the 12kg N plot and 16kg N plot, respectively, and these decreasing rate was noted at the nodes of lower part. 2. As for the verietal differences in variation of morphological magnitude as affected by the amount of nitrogen fertilization, leaf area coefficient value of variation of the total leaf area was 15.40% for Shin No. 2, 12.87% for Shirogane, and 10.99% for Jinheung. With respect to the position of nodes, the largest variation of leaf blade magnitude was observed at the fourth for Shin No. 2, the second for Shirogan, and flag leaf for Jinheung. And there also was an isotonic varietal difference in the weight of leaf blade. Variation in total culm weight showed varietal differences with the coefficient value of 7.72% for Shin No.2, 12.11% for Shirogane, and 0.94% for Jinheung. There also was varietal differences in the variation according to the position of nodes. 3. Variation of each elongating node-part related to the fertilization amount decreased with the increase of fertilization amount in the items of leaf area, weight of leaf sheath, culm weight, but weight of leaf sheath varied more at heavier fertilization than at others. 4. Constitutional ratio of each organ excluding head also varied with fertilization amount; constitutional ratio of leaf blade increased much with the increasing amount of fertilization in contrast with the response of culm eight. However, constitutional ration of the weight of leaf sheath was not much affected. 5. Lower value of the ration of leaf blade to culm was given to the 8kg N per 10 are plot, and the ratio of leaf blade to leaf sheath decreased with the increasing amount of fertilization in contrast with the increase in the ratio of leaf sheath to culm. however, the ration of leaf blade to culm plus leaf sheath decreased. 6. With the increase of nitrogen fertilization, leaf area, weight of leaf blade and leaf sheath increased. Accordingly, grin yield also increased to some extent. It was noted that culm weight was changed inversely to the changes in grain yield, but the degree of this variation varied with varietal characteristics. 7. Nitrogen content of leaves at heading and fruiting stage varied with the fertilization amount, and average nitrogen content of leaves of the varieties used 2.19%, 2.49% and 2.74% at the plot of 8kg N, and 12kg N and 16kg N per 10 are, respectively, at heading time, and 0.80%, 0.92% and 1.03% at each plot at fruiting stage. Thus, nitrogen content of leaves increased much with the increasing amount of fertilization, and higher value was given to the leaves on the higher position of elongating node-part. 8. There also was variation of nitrogen content of leaves in accordance with the varieties. However higher grain yield was obtained from the plants retaining higher nitrogen content in leaves at heading or fruiting stage.