• KDI Journal of Economic Policy
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• v.12 no.3
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• pp.27-45
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• 1990

Two opposing views prevail regarding the economic impact of rural out-migration on the rural areas of origin. The optimistic neoclassical view argues that rapid rural out-migration is not detrimental to the income and welfare of the rural areas of origin, whereas Lipton (1980) argues the opposite. We developed our own alternative model for rural to urban migration, appropriate for rapidly developing economies such as Korea's. This model, which adopts international trade theories of nontraded goods and Dutch Disease to rural to urban migration issues, argues that rural to urban migration is caused mainly by two factors: first, the unprofitability of farming, and second, the decrease in demand for rural nontraded goods and the increase in demand for urban nontraded goods. The unprofitability of farming is caused by the increase in rural wages, which is induced by increasing urban wages in booming urban manufacturing sectors, and by the fact that the cost increases in farming cannot be shifted to consumers, because farm prices are fixed worldwide and because the income demand elasticity for farm products is very low. The demand for nontraded goods decreases in rural and increases in urban areas because population density and income in urban areas increase sharply, while those in rural areas decrease sharply, due to rapid rural to urban migration. Given that the market structure for nontraded goods-namely, service sectors including educational and health facilities-is mostly in monopolistically competitive, and that the demand for nontraded goods comes only from local sources, the urban service sector enjoys economies of scale, and can thus offer services at cheaper prices and in greater variety, whereas the rural service sector cannot enjoy the advantages offered by scale economies. Our view concerning the economic impact of rural to urban migration on rural areas of origin agrees with Lipton's pessimistic view that rural out-migration is detrimental to the income and welfare of rural areas. However, our reasons for the reduction of rural income are different from those in Lipton's model. Lipton argued that rural income and welfare deteriorate mainly because of a shortage of human capital, younger workers and talent resulting from selective rural out-migration. Instead, we believe that rural income declines, first, because a rapid rural-urban migration creates a further shortage of farm labor supplies and increases rural wages, and thus reduces further the profitability of farming and, second, because a rapid rural-urban migration causes a further decline of the rural service sectors. Empirical tests of our major hypotheses using Korean census data from 1966, 1970, 1975, 1980 and 1985 support our own model much more than the neoclassical or Lipton's models. A kun (county) with a large out-migration had a smaller proportion of younger working aged people in the population, and a smaller proportion of highly educated workers. But the productivity of farm workers, measured in terms of fall crops (rice) purchased by the government per farmer or per hectare of irrigated land, did not decline despite the loss of these youths and of human capital. The kun having had a large out-migration had a larger proportion of the population in the farm sector and a smaller proportion in the service sector. The kun having had a large out-migration also had a lower income measured in terms of the proportion of households receiving welfare payments or the amount of provincial taxes paid per household. The lower incomes of these kuns might explain why the kuns that experienced a large out-migration had difficulty in mechanizing farming. Our policy suggestions based on the tests of the currently prevailing hypotheses are as follows: 1) The main cause of farming difficulties is not a lack of human capital, but the in­crease in production costs due to rural wage increases combined with depressed farm output prices. Therefore, a more effective way of helping farm economies is by increasing farm output prices. However, we are not sure whether an increase in farm output prices is desirable in terms of efficiency. 2) It might be worthwhile to attempt to increase the size of farmland holdings per farm household so that the mechanization of farming can be achieved more easily. 3) A kun with large out-migration suffers a deterioration in income and welfare. Therefore, the government should provide a form of subsidization similar to the adjustment assistance provided for international trade. This assistance should not be related to the level of farm output. Otherwise, there is a possibility that we might encourage farm production which would not be profitable in the absence of subsidies. 4) Government intervention in agricultural research and its dissemination, and large-scale social overhead projects in rural areas, carried out by the Korean government, might be desirable from both efficiency and equity points of view. Government interventions in research are justified because of the problems associated with the appropriation of knowledge, and government actions on large-scale projects are justified because they required collective action.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.17-35
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• 2015

Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase for a certain period of time. Developing precise forecasting models are considered important since corporates can make strategic decisions on new markets based on future demand estimated by the models. Many studies have developed market growth curve models, such as Bass, Logistic, Gompertz models, which estimate future demand when a market is in its early stage. Among the models, Bass model, which explains the demand from two types of adopters, innovators and imitators, has been widely used in forecasting. Such models require sufficient demand observations to ensure qualified results. In the beginning of a new market, however, observations are not sufficient for the models to precisely estimate the market's future demand. For this reason, as an alternative, demands guessed from those of most adjacent markets are often used as references in such cases. Reference markets can be those whose products are developed with the same categorical technologies. A market's demand may be expected to have the similar pattern with that of a reference market in case the adoption pattern of a product in the market is determined mainly by the technology related to the product. However, such processes may not always ensure pleasing results because the similarity between markets depends on intuition and/or experience. There are two major drawbacks that human experts cannot effectively handle in this approach. One is the abundance of candidate reference markets to consider, and the other is the difficulty in calculating the similarity between markets. First, there can be too many markets to consider in selecting reference markets. Mostly, markets in the same category in an industrial hierarchy can be reference markets because they are usually based on the similar technologies. However, markets can be classified into different categories even if they are based on the same generic technologies. Therefore, markets in other categories also need to be considered as potential candidates. Next, even domain experts cannot consistently calculate the similarity between markets with their own qualitative standards. The inconsistency implies missing adjacent reference markets, which may lead to the imprecise estimation of future demand. Even though there are no missing reference markets, the new market's parameters can be hardly estimated from the reference markets without quantitative standards. For this reason, this study proposes a case-based expert system that helps experts overcome the drawbacks in discovering referential markets. First, this study proposes the use of Euclidean distance measure to calculate the similarity between markets. Based on their similarities, markets are grouped into clusters. Then, missing markets with the characteristics of the cluster are searched for. Potential candidate reference markets are extracted and recommended to users. After the iteration of these steps, definite reference markets are determined according to the user's selection among those candidates. Then, finally, the new market's parameters are estimated from the reference markets. For this procedure, two techniques are used in the model. One is clustering data mining technique, and the other content-based filtering of recommender systems. The proposed system implemented with those techniques can determine the most adjacent markets based on whether a user accepts candidate markets. Experiments were conducted to validate the usefulness of the system with five ICT experts involved. In the experiments, the experts were given the list of 16 ICT markets whose parameters to be estimated. For each of the markets, the experts estimated its parameters of growth curve models with intuition at first, and then with the system. The comparison of the experiments results show that the estimated parameters are closer when they use the system in comparison with the results when they guessed them without the system.

• The Korean Journal of Food And Nutrition
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• v.19 no.1
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• pp.79-90
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• 2006

This study was performed to investigate the dietary behaviors and food intake patterns of university students according to the obesity index(OI). The subjects were 349 students(107 males and 242 females) who were assigned to one of the following groups based on the percentage of ideal body weight: underweight(OI< 90%), normal ($90%{\leq}Ol<10%$) and overweight($OI{\geq}110%$). The dietary behaviors and food intake patterns were evaluated by questionnaires and 24 hour recall method. The results were summarized as follows. The rates of underweight, normal, and overweight students were 33.8%, 61.0%, and 5.2% respectively. The ratios of underweight was higher than overweight, especially in case of female. The 60.46% of subjects responded that they had an irregular eating habits, especially in overweight group(72.22%). The 52.44% of subjects showed skipping mealtime more than one time per day. The overweight group had a tendency to overeat themselves than other groups. The normal group had less unbalanced dietary pattern than the other groups(p<0.0019). Most subjects had a snack(96.27%). The percentage of those who drank and smoked were 86.74% and 19.54%, respectively. The smoking value was significantly higher in the overweight group(p<0.0009). The food consumption frequency by food groups was not different among the groups except instant and fast food. More than 50% subjects consumed fish, legumes & its products, and vegetables everyday. There was significantly less rate of the instant and fast food consumption frequency in the normal group(p<0.0177). The 3/4 subjects that showed the lower consumed level in RDA(< 75%) were under-nutritional state in the Fe and Ca. In case of Ca, there was a higher NAR value in the overweight group(p<0.0257) significantly, and Fe, protein, vitamin $B_1$, vitamin $B_2$, and niacin showed similar tendencies. The INQ of Fe was significantly higher in the overweight group than other groups(p<0.0335).

• Korean journal of food and cookery science
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• v.6 no.4 s.13
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• pp.69-83
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• 1990

Gynostemma pentaphyllum Makino is a kind of perennial liana plant belonging to the Cucurbitaceae family. Since it was first discovered and reported to the Japanese academy in 1977, it came to be widely known to China and Southeast Asia areas as well as Japan. In Korea its name began to appear in the first half of 1980's, and it is now being nationwidely cultivated and popularized as tea stuffs. Gynostemma pentaphyllum Makino has remarkably strong propagation power. In addition. since it contains a great quantity of beneficial components, especially saponin it is believed to have excellent medical effects, too. This study was undertaken to examine the value of Gynostemma pentaphyllum Makino as a health-promotint tea, by investigating the components creating the flaver of tea and the saponin ingredient making medical effects as well as by inspecting whether Gynostemma pentaphyllum Makino products show different component arrangements according to their growing districts. As raw materials of the experiment, three kinds of Gynostemma pentaphyllum Makino samples produced in Suwon, Geochang and Uleungdo were taken. To accomplish the formerly stated goals, the contained quantity of the proximate composition, free sugar, reducing sugar, free amino acid, minerals, tannin, caffeine and vitamin C were measured respectively and compared between the samples, while the saponin content was compared with heat extracted from panax ginseng. The results of the experiment are as follows: 1. In the case of the proximate composition, the crude fat content was the highest in the Gymostemma pentaphyllum Makino material from Geochang (1.62%), the second in that from Suwon (1.56%), and the lowest in that from Uleungdo (1.0%). In addition the Geochang: produced sample had the greatest quantity of the crude protein and ash contents: the order of the crude Protein content was the Geochang produced (17.83%), the Suwon-produced (15.87%), and the Uleungdo-produced(12.28%), while that of the ash content was the Geochang-produced (14.80%), the Uleungdo-produced(10.17%), and the Suwon-produced(9.34%). 2. As for the reducing sugar contents, the Suwon-produced scored the highest of the three (3.3%), while the Geochang-produced was 1.3% and the Uleungdo-produced 0.5%. The total content of free sugar was 1.07% (the Suwon-produced), and 0.49% (the Geochang-produced) respectively but the sample from Uleungdo showed almost no free sugar content. The contained quantity of fructose and glucose was the highest among the kinds of free sugar both in the Suwon-produced and in the Geochang-produced. 3. The content of amino acid was the highest in the Suwon-produced(1.41%), the second in the Geochang-produced(1.37%), and the lowest in the Uleungdo-produced(0.53%). In the experiment, sixteen kinds of amino acid were extracted-Asp. Thr. Ser. Glu. Gly. Ala. Val. Het. Ileu. Leu. Tyr. Phe. Lys. His. Arg. Try. All of them except glutamic acid and methionine showed the highest quantity score in the Suwon-produced, while the glutamic acid content was the higest in the Uleungdo-produced and the methionine content in the Geochang-produced. The sequential arrangement of the sixteen contents according to their magnitude ranged from glycine, aspartic acid, and glutamic acid (the highest) to tryptophan, serine and lysine (the lowest). 4. Ten kinds of mineral were detected-Ca, Mn, Cd, K, Na, Pb, Mg, Fe, Zn, Cu. Among them, the content of Cd, Na, Mg, Zn and Fe was the highest in the Geochang-produced and that of K in the Suwon-produced. 5. The Geochang-produced materials contained much a larger quantity of tannin (6.3%) than the Suwon-produced (2.6%). Neither caffeine nor vitamin C was detected in the three kinds of materials. 6. In the case of the saponin content the Geochang-produced showd 2.39%, the Uleungdo-produced 1.77% and the Suwon-produced 1.49% respectively. However, it was found also that the saponin content of Gymostemma pentaphyllum Makino was the same kind as that of panax ginseng.

• Journal of the Korean Society of Food Science and Nutrition
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• v.41 no.3
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• pp.408-417
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• 2012

This study examined the satisfaction of a school milk program as well as the preference of school milk and flavored milk. The subjects of this study were $4^{th}$ , $5^{th}$ and $6^{th}$ grade students in 4 different elementary schools, who were attending the school milk program in Ulsan. The survey was conducted from April 10, 2009 to April 30, 2009. Of the 403 questionnaires distributed, 347 responded and analyzed (usage rate: 86%). The results were as follows. Of the 347 respondents, 53.9% were boys and 46.1% were girls. 34%, 31.1% and 34.9% of the students were $4^{th}$, $5^{th}$ and $6^{th}$ graders, respectively. Second, 80.1% of the students reported 'have milk everyday', and 89.9% of the students reported 'have milk as it is'. Third, the overall satisfaction with the school milk program was 3.32 based on a 5-point likert scale, the 'guidance of nutrition teachers and class teacher' was 3.21 and 'taste of school milk' was 3.37. There were significant positive correlations between the school milk satisfaction variables and overall satisfaction (p<0.01). Fourth, the preference for school milk was 3.33. The preference for flavored-milk were 3.63 (coffee milk), 4.44 (chocolate milk), 4.16 (strawberry milk), 4.26 (banana milk) and 3.53 (black bean milk). Fifth, to improve the school milk program, 85.9% of students wanted a provision for flavored milk. In conclusion, schools need to find a way to increase the satisfaction of the school milk program and the preference of school milk to increase the milk intake of students. Nutrition education for students and parents should be conducted systematically and choices for various kinds of milk and milk products should be given to the students.

• Restorative Dentistry and Endodontics
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• v.32 no.2
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• pp.138-150
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• 2007

The purpose of this study was to evaluate the difference of surface roughness of composite resin according to composite resin type, polishing methods, and use of resin sealant. Two hundred rectangular specimens, sized $8{\times}3{\times}2mm$, were made of Micro-new (Bisco, Inc., Schaumburg, IL, U.S.A) and Filtek Supreme (3M ESPE Dental Products, St. Paul, MN, U.S.A.), and divided into two groups; Micronew-M group, Filtek Supreme-S group. Specimens for each composite group were subdivided into five groups by finishing and polishing instruments used; M1 & S1(polyester strip), M2 & S2 (Sof-Lex disc), M3 & S3 (Enhance disc and polishing paste), M4 & S4(Astropol) and M5 & S5 (finishing bur), Polished groups were added letter B after the application of resin surface sealant (Biscover), eg, M1B and S1B. After specimens were stored with distilled water for 24hr, average surface roughness (Ra) was taken using a surface roughness tester. Representative specimens of each group were examined by FE-SEM (S-4700: Hitachi High Technologies Co., Tokyo, Japan). The data were analysed using paired t-test, ANOVA and Duncan's tests at the 0.05 probability level. The results of this study were as follows ; 1. The lowest Ra was achieved in all groups using polyester strip and the highest Ra was achieved in M5, S5 and M5B groups using finishing bur. On FE-SEM, M1 and S1 groups provided the smoothest surfaces, M5 and S5 groups were presented the roughest surfaces and voids by debonding of filler on the polished specimens. 2. There was no significant difference in Ra between Micronew and Filtek Supreme before the application of resin sealant, but Micronew was smoother than Filek Supreme after the application of resin sealant. 3. There was significant corelation between Ra of type of composite resin and polishing methods before the application of resin sealant (p=0.000), but no significant interaction between them after the application of resin sealant. On FE-SEM, most of composite resin surfaces were smooth after the application of resin sealant on the polished specimens. 4. Compared with before and after the application of resin sealant in group treated in the same composite and polishing methods, Ra of M4B and M5B was statistically lower than that of M4 and M5, and S5B was lower than that of S5, respectively (p<0.05). In conclusion, surface roughness by polishing instruments was different according to type of composite resin. Overall, polyester strip produced the smoothest surface, but finishing bur produced the roughest surface. Application of resin sealant provided the smooth surfaces in specimens polished with Enhance, Astropol and finishing bur, but not provided them in specimens polished with Sof-Lex disc.

• The Korean Journal of Pesticide Science
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• v.18 no.3
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• pp.130-140
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• 2014

Recently, some of the previous studies reported that tolclofos-methyl is still exist in ginseng cultivated soil, even though it is has been banned for ginseng. Therefore, the current study was aimed to examine the levels of absorption and translocation of tolclofos-methyl from ginseng cultivated soil to ginseng root and leaf stem for the period of 1 year. For this study, ginseng plants were transplanted in pots and treated with $5.0mg\;kg^{-1}$ of tolclofos-methyl (50% WP). At the end of each interval periods (every three months) the samples (soil, roots and leaf stems) were collected and analyzed the absorption and translocation levels of tolclofos-methyl using gas chromatography and mass spectrometry (GC-MS). The limit of quantitation of tolclofos-methyl was found to be $0.02mg\;kg^{-1}$ and 70.0~120.0% recovery was obtained with coefficient of variation of less than 10% regardless of sample types. In this study, a considerable amount of translocation of tolclofos-methyl residues were found in soil (4.28 to $0.06mg\;kg^{-1}$), root (7.09 to $1.54mg\;kg^{-1}$) and leaf stem (0.79 to $0.69mg\;kg^{-1}$). The results show that the tolclofos-methyl was absorbted and translocated from ginseng cultivated soil to ginseng root and ginseng leaf stem and found to be decreased time-coursely. Secondly, we were also analyzed soil, root and leaf stems samples from Hongcheon, Cheorwon, Punggi and Geumsan by GC-MS/MS (172 pesticides), LC-MS/MS (74 pesticides). In this study, 43 different pesticides were detected ($0.01{\sim}7.56mg\;kg^{-1}$) in soil, root and leaf stem. Further, tolclofos-methyl was detected 4 times separately in root sample alone which is less ($0.01{\sim}0.05mg\;kg^{-1}$) than their maximum residual limit (MRL) in ginseng. Consequently, the results from both studies indicate the residues of tolclofos-methyl found in ginseng cultivated soil and ginseng ensuring their safety level. Moreover, long-term evaluations are needed in order to protect the soil as well as ginseng free from tolclofos-methyl residues.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.137-148
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• 2014

Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used