• Tuberculosis and Respiratory Diseases
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• v.66 no.3
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• pp.192-197
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• 2009

Background: Despite the benefits of home oxygen therapy in patients suffering chronic respiratory failure, previous reports in Korea revealed lower compliance to oxygen therapy and a shorter time for oxygen use than expected. However, these papers were published before oxygen therapy was covered by the national insurance system. Therefore, this study examined whether there were some changes in compliance, using time and other clinical features of home oxygen therapy after insurance coverage. Methods: This study reviewed the medical records of patients prescribed home oxygen therapy in our hospital from November 1, 2006 to September 31, 2008. The patients were interviewed either in person or by telephone to obtain information related to oxygen therapy. Results: During study period, a total 105 patients started home oxygen therapy. The mean age was 69 and 60 (57%) were male. The mean oxygen partial pressure in the arterial blood was 54.5 mmHg and oxygen saturation was 86.3%. Primary diseases that caused hypoxemia were COPD (n=64), lung cancer (n=14), Tb destroyed lung (n=12) and others. After oxygen therapy, more than 50% of patients experienced relief of their subjective dyspnea. The mean daily use of oxygen was 9.8${\pm}$7.3 hours and oxygen was not used during activity outside of their home (mean time, 5.4${\pm}$3.7 hours). Twenty four patients (36%) stopped using oxygen voluntarily 7${\pm}$4.7 months after being prescribed oxygen and showed a less severe pulmonary and right heart function. The causes of stopping were subjective symptom relief (n=11), inconvenience (n=6) and others (7). Conclusion: The prescription of home oxygen has increased since national insurance started to cover home oxygen therapy. However, the mean time for using oxygen is still shorter than expected. During activity of outside their home, patients could not use oxygen due to the absence of portable oxygen. Overall, continuous education to change the misunderstandings about oxygen therapy, more economic support from national insurance and coverage for portable oxygen are needed to extend the oxygen use time and maintain oxygen usage.

• Journal of agricultural medicine and community health
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• v.18 no.2
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• pp.141-151
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• 1993

This study was done about 371 tuberculosis(TB) patients composed 195 newly registered at Kyungju Gun Health Center from May 1989 to April 1990 (Group A) and 176 being treated at hospitals or private clinics from January 1988 to November 1989(Group B). When Group A patients visited and newly registered at Health Center, data was obtained by interviewing with a prepared questionnaire paper. And well trained inquirer visited Group B patients and obtained data by the same method from February 1990 to April 1990. The results are as follows ; Group A was generally lower than Group B in socioeconomic status and in family history of TB, the rate of Group A was 24.1% and higher than 11.9% in Group B(p<0.05). Knowledge about TB was improved more than past, but those who answered that TB is 'a communicable disease' were 59.5% in Group A and 51.7% in Group B(p<0.05). Those answered that TB is 'a inherited disease' were 9.2% and 11.4% each. And 1.7% of Group B answered that TB is 'a incurable disease'. Knowledge about TB treatment also was improved more than past, but in the rate of those who answered that TB is a curable disease provided by well treatment Group B(77.8%) was worse than Group A(91.3%). The rate of those who answered that TB were been able to cure by regularly anti-TB medication were 98.0% in Group A and 89.8% in Group B. Its difference was statistically significant. The rate that patients took the first diagnosis and wanted to receive treatments at the same organ were 34.9% of Group A at Health Center and 72.2% of Group B at hospitals or private clinics. And its difference was statistically significant. In the reasons that Group B knew Health Center treated pulmonary TB but they was treated at hospitals or private clinics, unreliability to Health Center was 48.1%. The reasons that Group A was treated at Health Center were 'because of trust' 63.1%, 'because of low cost' 50.3%, 'because of low cost except trust' 9.3%, 'no specific reasons' 27.7%. In the courses of knowing that TB was controlled at Health Center, 'by neighborhood, health worker and doctors' were 84.9% in Group A and 69.0% in Group B. But 'by TV or radio' were 8.2% in Group A and 14.7% in Group B, 'by school education' 2.5% in Group A and 6.2% in Group B. Conclusively, Group A patients were lower than Group B in socioeconomic status, but better than in knowledge about TB. Its reasons was suggested that Health Center had controlled TB patients better than hospitals and private clinics. But considering, that difference in the rate of the same organ for the first diagnosis and treatment, that the only 63.0% of Group A have treated due to 'reliability to Health Center', and that 48.1% of Group B knew that Health Center treated pulmonary TB but didn't visit it due to 'unreliability to Health Center', that public relations(PR) about use Health Center for pulmonary TB and health education for TB was thought to have to strengthened.

• KDI Journal of Economic Policy
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• v.13 no.4
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• pp.91-116
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• 1991

Market liberalization progressing simultaneously with high and rapidly rising domestic wages has created an adverse business environment for domestic firms. Korean firms are losing their international competitiveness in comparison to firms from LDC(Less Developed Countries) in low-tech industries. In high-tech industries, domestic firms without government protection (which is impossible due to the liberalization policy and the current international status of the Korean economy) are in a disadvantaged position relative to firms from advanced countries. This paper examines the division of roles between the private sector and the government in order to achieve a successful structural adjustment, which has become the impending industrial policy issue caused by high domestic wages, on the one hand, and the opening of domestic markets, on the other. The micro foundation of the economy-wide structural adjustment is actually the restructuring of business portfolios at the firm level. The firm-level business restructuring means that firms in low-value-added businesses or with declining market niches establish new major businesses in higher value-added segments or growing market niches. The adjustment of the business structure at the firm level can only be accomplished by accumulating firm-specific managerial assets necessary to establish a new business structure. This can be done through learning-by-doing in the whole system of management, including research and development, manufacturing, and marketing. Therefore, the voluntary cooperation among the people in the company is essential for making the cost of the learning process lower than that at the competing companies. Hence, firms that attempt to restructure their major businesses need to induce corporate-wide participation through innovations in organization and management, encourage innovative corporate culture, and maintain cooperative labor unions. Policy discussions on structural adjustments usually regard firms as a black box behind a few macro variables. But in reality, firm activities are not flows of materials but relationships among human resources. The growth potential of companies are embodied in the human resources of the firm; the balance of interest among stockholders, managers, and workers of the company' brings the accumulation of the company's core competencies. Therefore, policymakers and economists shoud change their old concept of the firm as a technological black box which produces a marketable commodities. Firms should be regarded as coalitions of interest groups such as stockholders, managers, and workers. Consequently the discussion on the structural adjustment both at the macroeconomic level and the firm level should be based on this new paradigm of understanding firms. The government's role in reducing the cost of structural adjustment and supporting should the creation of new industries emphasize the following: First, government must promote the competition in domestic markets by revising laws related to antitrust policy, bankruptcy, and the promotion of small and medium-sized companies. General consensus on the limitations of government intervention and the merit of deregulation should be sought among policymakers and people in the business world. In the age of internationalization, nation-specific competitive advantages cannot be exclusively in favor of domestic firms. The international competitiveness of a domestic firm derives from the firm-specific core competencies which can be accumulated by internal investment and organization of the firm. Second, government must build up a solid infrastructure of production factors including capital, technology, manpower, and information. Structural adjustment often entails bankruptcies and partial waste of resources. However, it is desirable for the government not to try to sustain marginal businesses, but to support the diversification or restructuring of businesses by assisting in factor creation. Institutional support for venture businesses needs to be improved, especially in the financing system since many investment projects in venture businesses are highly risky, even though they are very promising. The proportion of low-value added production processes and declining industries should be reduced by promoting foreign direct investment and factory automation. Moreover, one cannot over-emphasize the importance of future-oriented labor policies to be based on the new paradigm of understanding firm activities. The old laws and instititutions related to labor unions need to be reformed. Third, government must improve the regimes related to money, banking, and the tax system to change business practices dependent on government protection or undesirable in view of the evolution of the Korean economy as a whole. To prevent rational business decisions from contradicting to the interest of the economy as a whole, government should influence the business environment, not the business itself.

• The Journal of Korean Academy of Prosthodontics
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• v.46 no.5
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• pp.528-534
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• 2008

Purpose: Marginal fit is one of the important components for the successful prosthodontic restoration. Poor fitting margin of the restoration causes hypersensitivity, secondary caries, and plaque accumulation, which later result in prosthodontic failure. CAD/CAM zirconia all-ceramic restorations, such as $LAVA^{(R)}$ (3M ESPE, St.Paul, MN) and $EVEREST^{(R)}$ (KaVo Dental GmbH, Biberach, Germany) systems were recently introduced in Korea. It is clinically meaningful to evaluate the changes of the marginal fit of the CAD/CAM zirconia systems before and after build-up. The purposes of this study are to compare the marginal fit of the two CAD/CAM all-ceramic systems with that of the ceramometal restoration, before and after porcelain build-up Material and methods: A maxillary first premolar dentiform tooth was prepared with 2.0 mm occlusal reduction, 1.0 mm axial reduction, chamfer margin, and 6 degree taperness in the axial wall. The prepared dentiform die was duplicated into the metal abutment die. The metal die was placed in the dental study model, and the full arch impressions of the model were made. Twenty four copings of 3 groups which were $LAVA^{(R)}$, $EVEREST^{(R)}$, and ceramometal restorations were fabricated. Each coping was cemented on the metal die with color-mixed Fit-checker $II^{(R)}$ (GC Cor., Tokyo, Japan). The marginal opening of each coping was measured with $Microhiscope^{(R)}$ system (HIROX KH-1000 ING-Plus, Seoul, Korea. X300 magnification). After porcelain build-up, the marginal openings of $LAVA^{(R)}$, $EVEREST^{(R)}$,and ceramometal restorations were also evaluated in the same method. Statistical analysis was done with paired t-test and one-way ANOVA test. Results: In coping states, the mean marginal opening for $EVEREST^{(R)}$ restorations was $52.00{\pm}11.94\;{\mu}m$ for $LAVA^{(R)}$ restorations $56.97{\pm}10.00\;{\mu}m$, and for ceramometal restorations $97.38{\pm}18.54\;{\mu}m$. After porcelain build-up, the mean marginal opening for $EVEREST^{(R)}$ restorations was $61.69{\pm}19.33\;{\mu}m$, for $LAVA^{(R)}$ restorations $70.81{\pm}12.99\;{\mu}m$, and for ceramometal restorations $1115.25{\pm}23.86\;{\mu}m$. Conclusion: 1. $LAVA^{(R)}$ and $EVEREST^{(R)}$ restorations in comparison with ceramometal restorations showed better marginal fit, which had significant differences (P < 0.05) in coping state and also after porcelain build-up . 2. The mean marginal opening values between $LAVA^{(R)}$ and $EVEREST^{(R)}$ restorations did not showed significant differences after porcelain build-up as well as in coping state (P > .05). 3. $EVEREST^{(R)}$, $LAVA^{(R)}$ and ceramometal restorations showed a little increased marginal opening after porcelain build-up, but did not show any statistical significance (P > .05).

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.147-168
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• 2017

There have been many studies on accurate stock market forecasting in academia for a long time, and now there are also various forecasting models using various techniques. Recently, many attempts have been made to predict the stock index using various machine learning methods including Deep Learning. Although the fundamental analysis and the technical analysis method are used for the analysis of the traditional stock investment transaction, the technical analysis method is more useful for the application of the short-term transaction prediction or statistical and mathematical techniques. Most of the studies that have been conducted using these technical indicators have studied the model of predicting stock prices by binary classification - rising or falling - of stock market fluctuations in the future market (usually next trading day). However, it is also true that this binary classification has many unfavorable aspects in predicting trends, identifying trading signals, or signaling portfolio rebalancing. In this study, we try to predict the stock index by expanding the stock index trend (upward trend, boxed, downward trend) to the multiple classification system in the existing binary index method. In order to solve this multi-classification problem, a technique such as Multinomial Logistic Regression Analysis (MLOGIT), Multiple Discriminant Analysis (MDA) or Artificial Neural Networks (ANN) we propose an optimization model using Genetic Algorithm as a wrapper for improving the performance of this model using Multi-classification Support Vector Machines (MSVM), which has proved to be superior in prediction performance. In particular, the proposed model named GA-MSVM is designed to maximize model performance by optimizing not only the kernel function parameters of MSVM, but also the optimal selection of input variables (feature selection) as well as instance selection. In order to verify the performance of the proposed model, we applied the proposed method to the real data. The results show that the proposed method is more effective than the conventional multivariate SVM, which has been known to show the best prediction performance up to now, as well as existing artificial intelligence / data mining techniques such as MDA, MLOGIT, CBR, and it is confirmed that the prediction performance is better than this. Especially, it has been confirmed that the 'instance selection' plays a very important role in predicting the stock index trend, and it is confirmed that the improvement effect of the model is more important than other factors. To verify the usefulness of GA-MSVM, we applied it to Korea's real KOSPI200 stock index trend forecast. Our research is primarily aimed at predicting trend segments to capture signal acquisition or short-term trend transition points. The experimental data set includes technical indicators such as the price and volatility index (2004 ~ 2017) and macroeconomic data (interest rate, exchange rate, S&P 500, etc.) of KOSPI200 stock index in Korea. Using a variety of statistical methods including one-way ANOVA and stepwise MDA, 15 indicators were selected as candidate independent variables. The dependent variable, trend classification, was classified into three states: 1 (upward trend), 0 (boxed), and -1 (downward trend). 70% of the total data for each class was used for training and the remaining 30% was used for verifying. To verify the performance of the proposed model, several comparative model experiments such as MDA, MLOGIT, CBR, ANN and MSVM were conducted. MSVM has adopted the One-Against-One (OAO) approach, which is known as the most accurate approach among the various MSVM approaches. Although there are some limitations, the final experimental results demonstrate that the proposed model, GA-MSVM, performs at a significantly higher level than all comparative models.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.3
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• pp.425-430
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• 2014

Foods contain various nutrients such as carbohydrates, protein, oil, vitamins, and minerals. Among them, carbohydrates, protein, and oil are the main constituents of foods. Usually, these constituents are analyzed by the Kjeldahl and Soxhlet method and so on. However, these analytical methods are complex, costly, and time-consuming. Thus, this study aimed to rapidly and effectively analyze carbohydrate, protein, and oil contents with near-infrared reflectance spectroscopy (NIRS). A total of 517 food samples were measured within the wavelength range of 400 to 2,500 nm. Exactly 412 food calibration samples and 162 validation samples were used for NIRS equation development and validation, respectively. In the NIRS equation of carbohydrates, the most accurate equation was obtained under 1, 4, 5, 1 (1st derivative, 4 nm gap, 5 points smoothing, and 1 point second smoothing) math treatment conditions using the weighted MSC (multiplicative scatter correction) scatter correction method with MPLS (modified partial least square) regression. In the case of protein and oil, the best equation were obtained under 2, 5, 5, 3 and 1, 1, 1, 1 conditions, respectively, using standard MSC and standard normal variate only scatter correction methods with MPLS regression. Calibrations of these NIRS equations showed a very high coefficient of determination in calibration ($R^2$: carbohydrates, 0.971; protein, 0.974; oil, 0.937) and low standard error of calibration (carbohydrates, 4.066; protein, 1.080; oil, 1.890). Optimal equation conditions were applied to a validation set of 162 samples. Validation results of these NIRS equations showed a very high coefficient of determination in prediction ($r^2$: carbohydrates, 0.987; protein, 0.970; oil, 0.947) and low standard error of prediction (carbohydrates, 2.515; protein, 1.144; oil, 1.370). Therefore, these NIRS equations can be applicable for determination of carbohydrates, proteins, and oil contents in various foods.

• Information Systems Review
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• v.16 no.3
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• pp.161-177
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• 2014

Corporate credit rating assessment consists of complicated processes in which various factors describing a company are taken into consideration. Such assessment is known to be very expensive since domain experts should be employed to assess the ratings. As a result, the data-driven corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has received considerable attention from researchers and practitioners. In particular, statistical methods such as multiple discriminant analysis (MDA) and multinomial logistic regression analysis (MLOGIT), and AI methods including case-based reasoning (CBR), artificial neural network (ANN), and multiclass support vector machine (MSVM) have been applied to corporate credit rating.2) Among them, MSVM has recently become popular because of its robustness and high prediction accuracy. In this study, we propose a novel optimized MSVM model, and appy it to corporate credit rating prediction in order to enhance the accuracy. Our model, named 'GAMSVM (Genetic Algorithm-optimized Multiclass Support Vector Machine),' is designed to simultaneously optimize the kernel parameters and the feature subset selection. Prior studies like Lorena and de Carvalho (2008), and Chatterjee (2013) show that proper kernel parameters may improve the performance of MSVMs. Also, the results from the studies such as Shieh and Yang (2008) and Chatterjee (2013) imply that appropriate feature selection may lead to higher prediction accuracy. Based on these prior studies, we propose to apply GAMSVM to corporate credit rating prediction. As a tool for optimizing the kernel parameters and the feature subset selection, we suggest genetic algorithm (GA). GA is known as an efficient and effective search method that attempts to simulate the biological evolution phenomenon. By applying genetic operations such as selection, crossover, and mutation, it is designed to gradually improve the search results. Especially, mutation operator prevents GA from falling into the local optima, thus we can find the globally optimal or near-optimal solution using it. GA has popularly been applied to search optimal parameters or feature subset selections of AI techniques including MSVM. With these reasons, we also adopt GA as an optimization tool. To empirically validate the usefulness of GAMSVM, we applied it to a real-world case of credit rating in Korea. Our application is in bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. The experimental dataset was collected from a large credit rating company in South Korea. It contained 39 financial ratios of 1,295 companies in the manufacturing industry, and their credit ratings. Using various statistical methods including the one-way ANOVA and the stepwise MDA, we selected 14 financial ratios as the candidate independent variables. The dependent variable, i.e. credit rating, was labeled as four classes: 1(A1); 2(A2); 3(A3); 4(B and C). 80 percent of total data for each class was used for training, and remaining 20 percent was used for validation. And, to overcome small sample size, we applied five-fold cross validation to our dataset. In order to examine the competitiveness of the proposed model, we also experimented several comparative models including MDA, MLOGIT, CBR, ANN and MSVM. In case of MSVM, we adopted One-Against-One (OAO) and DAGSVM (Directed Acyclic Graph SVM) approaches because they are known to be the most accurate approaches among various MSVM approaches. GAMSVM was implemented using LIBSVM-an open-source software, and Evolver 5.5-a commercial software enables GA. Other comparative models were experimented using various statistical and AI packages such as SPSS for Windows, Neuroshell, and Microsoft Excel VBA (Visual Basic for Applications). Experimental results showed that the proposed model-GAMSVM-outperformed all the competitive models. In addition, the model was found to use less independent variables, but to show higher accuracy. In our experiments, five variables such as X7 (total debt), X9 (sales per employee), X13 (years after founded), X15 (accumulated earning to total asset), and X39 (the index related to the cash flows from operating activity) were found to be the most important factors in predicting the corporate credit ratings. However, the values of the finally selected kernel parameters were found to be almost same among the data subsets. To examine whether the predictive performance of GAMSVM was significantly greater than those of other models, we used the McNemar test. As a result, we found that GAMSVM was better than MDA, MLOGIT, CBR, and ANN at the 1% significance level, and better than OAO and DAGSVM at the 5% significance level.

• Progress in Medical Physics
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• v.22 no.1
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• pp.42-51
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• 2011

Nuclear medicine images (SPECT, PET) were widely used tool for assessment of myocardial viability and perfusion. However it had difficult to define accurate myocardial infarct region. The purpose of this study was to investigate methodological approach for automatic measurement of rat myocardial infarct size using polar map with adaptive threshold. Rat myocardial infarction model was induced by ligation of the left circumflex artery. PET images were obtained after intravenous injection of 37 MBq $^{18}F$-FDG. After 60 min uptake, each animal was scanned for 20 min with ECG gating. PET data were reconstructed using ordered subset expectation maximization (OSEM) 2D. To automatically make the myocardial contour and generate polar map, we used QGS software (Cedars-Sinai Medical Center). The reference infarct size was defined by infarction area percentage of the total left myocardium using TTC staining. We used three threshold methods (predefined threshold, Otsu and Multi Gaussian mixture model; MGMM). Predefined threshold method was commonly used in other studies. We applied threshold value form 10% to 90% in step of 10%. Otsu algorithm calculated threshold with the maximum between class variance. MGMM method estimated the distribution of image intensity using multiple Gaussian mixture models (MGMM2, ${\cdots}$ MGMM5) and calculated adaptive threshold. The infarct size in polar map was calculated as the percentage of lower threshold area in polar map from the total polar map area. The measured infarct size using different threshold methods was evaluated by comparison with reference infarct size. The mean difference between with polar map defect size by predefined thresholds (20%, 30%, and 40%) and reference infarct size were $7.04{\pm}3.44%$, $3.87{\pm}2.09%$ and $2.15{\pm}2.07%$, respectively. Otsu verse reference infarct size was $3.56{\pm}4.16%$. MGMM methods verse reference infarct size was $2.29{\pm}1.94%$. The predefined threshold (30%) showed the smallest mean difference with reference infarct size. However, MGMM was more accurate than predefined threshold in under 10% reference infarct size case (MGMM: 0.006%, predefined threshold: 0.59%). In this study, we was to evaluate myocardial infarct size in polar map using multiple Gaussian mixture model. MGMM method was provide adaptive threshold in each subject and will be a useful for automatic measurement of infarct size.

• Journal of the Korean Society of Food Science and Nutrition
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• v.35 no.6
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• pp.698-707
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• 2006

Precise and correct assessment of nutrient intake using appropriate dietary intake method is necessary to improve the nutritional status of the target people group. It is more likely so in elderly people since their dietary habits and inadequate nutrient intakes are of special concern even worse in rural areas. Two popular methods of gathering dietary intake are 24-hour recall and food frequency method (or food frequency questionnaire). In the present study, we conducted both 24-hour recall and food frequency method on 120 rural elderly people $(aged\;65{\sim}74\;years)$, 62 male and 58 female. The dietary intakes were analyzed and the correlation of the dietary intake between 24-hour recall and food frequency method to determine the reliability between two methods. Also each nutrient intake was compared to recommended dietary allowance (RDA) or nutrient reference value (NRV) as appropriate. Even correlation did not show significance between the two methods except for dietary fiber intake (0.65 at p<0.01) and energy-yielding nutrients which mostly showed similar results with nutrient intake level. These support the possible reliability between 24-hours record and food frequency method that is also shown on the cases of most mineral and vitamin intakes. Thus, the food frequency method used in this study for the assessment of nutrient intakes of the elderly people would be reliable for the assessment of the nutrient intake along with the 24-hour recall. Also, the present study results suggested that rural female elderly people would be under optimal nutriture status due to the lower food intake measured by 24-hour recall. The optimal food frequency method would be considered to be developed for the precise nutrient assessment.

• Proceedings of the Korean DIstribution Association Conference
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• 2005.05a
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• pp.383-405
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• 2005

The traditional market is foremost a regionally positioned place, wherein the market directly represents regional and cultural centered traits while it plays an important role in the circulation of facilities through reciprocal, informative and cultural exchanges while sewing to form local communities. The traditional market in Korea is one of representative retail businesses and premodern marketing techniques by family owned business of less than five members such as product management, purchase method, and marketing patterns etc. Since the 1990s, the appearance of new circulation-type businesses and large discount convenience stores escalated the loss of traditional competitiveness, increased the living standard of customers, changed purchasing patterns, and expanded the ubiquity of the Internet. All of these changes in external circulation circumstances have led the traditional markets to lose their place in the economy. The traditional market should revive on a regional site basis through the formation of a community of regional neighbors and through knowledge-sharing that leads to the creation of wealth. For the purpose of creating a wealth in a place, the following components are necessary: 1) a facility suitable for the spatial place of the present, 2)trust built through exchanges within the changing market environment, which would simultaneously satisfy customer's desires, 3) international bench marking on cases such as regionally centered TCM (England), BID (USA), and TMO (Japan) so that the market unit of store placement transfers from a spot policy to a line policy, 4)conversion of communicative conception through a surface policy approach centered around a macro-region perspective. The budget of the traditional market funding policy was operational between 2001 and 2004, serving as a counter move to solve the problem of the old traditional market through government intervention in regional economies to promote national economic strength. This national treasury funding project was centered on environmental improvement, research corps, and business modernization through the expenditure of 3,853 hundred million won (Korean currency). However, the effectiveness of this project has yet to be to proven through investigation. Furthermore, in promoting this funding support project, a lack of professionalism among merchants in the market led to constant limitations in comprehensive striving strategies, reduced capabilities in middle-and long-term plan setup, and created reductions in voluntary merchant agreement solutions. The traditional market should go beyond mere physical place and ordinary products creative site strategies employing the communicative approach must accompany these strategies to make the market a new regional and spatial living place. Thus, regarding recent paradigm changes and the introduction of region-based site functions into the traditional market, acquiring a conversion of direction into the newly developed project is essential to reinvestigate the traditional market composed of cultural and economic meanings, for the purpose of the research. Excavating social policy demands through the comparative analysis of domestic and international cases as well as innovative and expert management leadership development for NPO or NGO civil entrepreneurs through advanced case research on present promotion methods is extremely important. Discovering the seeds of the cultural contents industry cored around regional resource usages, commercializing regionally reknowned products, and constructing complex cultural living places for regional networks are especially important. In order to accelerate these solutions, a comprehensive and systemized approach research operated within a mentor academy system is required, as research will reveal distinctive traits of the traditional market in the aging society.