• Journal of Intelligence and Information Systems
• /
• v.26 no.3
• /
• pp.37-50
• /
• 2020

Information security has become an important issue in the world. Various information and communication technologies, such as the Internet of Things, big data, cloud, and artificial intelligence, are developing, and the need for information security is increasing. Although the necessity of information security is expanding according to the development of information and communication technology, interest in information security investment is insufficient. In general, measuring the effect of information security investment is difficult, so appropriate investment is not being practice, and organizations are decreasing their information security investment. In addition, since the types and specification of information security measures are diverse, it is difficult to compare and evaluate the information security countermeasures objectively, and there is a lack of decision-making methods about information security investment. To develop the organization, policies and decisions related to information security are essential, and measuring the effect of information security investment is necessary. Therefore, this study proposes a method of constructing an investment portfolio for information security measures using game theory and derives an optimal defence probability. Using the two-person game model, the information security manager and the attacker are assumed to be the game players, and the information security countermeasures and information security threats are assumed as the strategy of the players, respectively. A zero-sum game that the sum of the players' payoffs is zero is assumed, and we derive a solution of a mixed strategy game in which a strategy is selected according to probability distribution among strategies. In the real world, there are various types of information security threats exist, so multiple information security measures should be considered to maintain the appropriate information security level of information systems. We assume that the defence ratio of the information security countermeasures is known, and we derive the optimal solution of the mixed strategy game using linear programming. The contributions of this study are as follows. First, we conduct analysis using real performance data of information security measures. Information security managers of organizations can use the methodology suggested in this study to make practical decisions when establishing investment portfolio for information security countermeasures. Second, the investment weight of information security countermeasures is derived. Since we derive the weight of each information security measure, not just whether or not information security measures have been invested, it is easy to construct an information security investment portfolio in a situation where investment decisions need to be made in consideration of a number of information security countermeasures. Finally, it is possible to find the optimal defence probability after constructing an investment portfolio of information security countermeasures. The information security managers of organizations can measure the specific investment effect by drawing out information security countermeasures that fit the organization's information security investment budget. Also, numerical examples are presented and computational results are analyzed. Based on the performance of various information security countermeasures: Firewall, IPS, and Antivirus, data related to information security measures are collected to construct a portfolio of information security countermeasures. The defence ratio of the information security countermeasures is created using a uniform distribution, and a coverage of performance is derived based on the report of each information security countermeasure. According to numerical examples that considered Firewall, IPS, and Antivirus as information security countermeasures, the investment weights of Firewall, IPS, and Antivirus are optimized to 60.74%, 39.26%, and 0%, respectively. The result shows that the defence probability of the organization is maximized to 83.87%. When the methodology and examples of this study are used in practice, information security managers can consider various types of information security measures, and the appropriate investment level of each measure can be reflected in the organization's budget.

• KIPS Transactions on Computer and Communication Systems
• /
• v.11 no.9
• /
• pp.317-322
• /
• 2022

The rapid development of information technology is also bringing about many changes in the medical environment. In particular, it is leading the rapid change of medical image information systems using big data and artificial intelligence (AI). The prescription delivery system (OCS), which consists of an electronic medical record (EMR) and a medical image storage and transmission system (PACS), has rapidly changed the medical environment from analog to digital. When combined with multiple solutions, PACS represents a new direction for advancement in security, interoperability, efficiency and automation. Among them, the combination with artificial intelligence (AI) using big data that can improve the quality of images is actively progressing. In particular, AI PACS, a system that can assist in reading medical images using deep learning technology, was developed in cooperation with universities and industries and is being used in hospitals. As such, in line with the rapid changes in the medical image information system in the medical environment, structural changes in the medical market and changes in medical policies to cope with them are also necessary. On the other hand, medical image information is based on a digital medical image transmission device (DICOM) format method, and is divided into a tomographic volume image, a volume image, and a cross-sectional image, a two-dimensional image, according to a generation method. In addition, recently, many medical institutions are rushing to introduce the next-generation integrated medical information system by promoting smart hospital services. The next-generation integrated medical information system is built as a solution that integrates EMR, electronic consent, big data, AI, precision medicine, and interworking with external institutions. It aims to realize research. Korea's medical image information system is at a world-class level thanks to advanced IT technology and government policies. In particular, the PACS solution is the only field exporting medical information technology to the world. In this study, along with the analysis of the medical image information system using big data, the current trend was grasped based on the historical background of the introduction of the medical image information system in Korea, and the future development direction was predicted. In the future, based on DICOM big data accumulated over 20 years, we plan to conduct research that can increase the image read rate by using AI and deep learning algorithms.

• Korean journal of applied entomology
• /
• v.16 no.4 s.33
• /
• pp.199-208
• /
• 1977

Activities of various hydrolytic enzymes produced by three plant pathogenic fungi, Sclerotium rolfsii Sacc., Sclerotinia sclerotiorum (Lieb.) deBary and Helminthosporium sigmoideum var. irregulare Crallery et Tullius, were measured. Activties and amounts of the enzymes in mycelia, cultural filtrates, and sclerotia(except of sclerotia of H. sigmoideum var. irregulare) were estimated at various pH levels in order to find out optimal pH for their enzymatic activities. Enzymes such as cellulase (ex), invertase, xylanase, $\beta-amylase$, polymethylgalacturonase, polygalacturonase, phosphatase and protease were estimated. Culture solution for production of enzymes was prepared by adding of 10g, D-glucose, 1.3g $NH_4NO_3,\; 0.5g\; MgSO_4,\;7H_2O,\; and\; 1.0g\; KH_2PO_4$ into 1 liter of potato decoction plus 2ml of micro element solution consisting of 0.2mg. Fe, 0.2mg Zn, and 0.1mg Mn as the sulphates into 1 liter of distilled water. All tested mycelia and cultural filtrates were obtained from the cultures incubarted in previous solution for ten days at $25^{\circ}C$, and sclerotia were harvested from PDA plates of 3. days old, The crude enzyme solutions were prepared according to the method of Miyazaki etal. Ten days after incubation, activities of Cx produced by Scl. sclerotiorum were higher than those of the other fung and each of Cx from three fungi showed different pH optima, such as S. rolfsii and Scl. schlerotiorum in acid side (around pH 3.0), H. sigmoideum var. irregulare in neutral side (around pH 6.3). Invertase activities of S. rolfsii were 20 times higher than those of the other fungi in all samples. All tested fungi, however, showed no significant difference between the enzymatic activities of their cultural filtrate and mycelia and the activities in sclerotia of S. rolfsii and Scl. sclerotiorum were hardly recognized. There were multiple peaks on the xylanase activity curves of three fungi in terms of pH values. High activities of the xylanase were revealed in sclerotia of S. rolfsii and Scl. sclerotiorum, and in mycelia of H. sigmoideum var. irregulare. The highest activities of $\beta-amylase$ were shown both in mycelia and cultural filtrate of H. sigmoideum var. irregulae among the tested fungi, and their optimal pH was 6.2 in both mycelia and cultural filtrate. In the S. rofsii and Sel. sclerotiorum, however, the activities of cultural filtrates were higher than those of the other fungi, and optimal pH was 3.0 and 6.2 for cultural filtrate and both mycelia and sclerotia, respectively. Activities of PMG were high in cultural filtrates of all tested fungi, especially in Scl. sclerotiorum and H. sigmoideum var. irregulare. Mycelia of themalso showed the considerable activities. Optimal pH for enzymatic activities were variable with thekind of fungi or with the samples measured. The highest activities of PG were presented by mycelia of S. rolfsii and Scl. sclerotiorum. $9.l\mu /min.\; and\; 9.5\mu g/min.$, respectively. Optimal pH for activity of PG in mycelia was around 4.5 in S. rolfsii and around 3.0 in Scl. sclerotiorum. Phosphatase of S. rolfsii and Scl. sclerotiorum was more active in acid side (optimal PH3. 5) and that of H. sigmoideum var. irregulare showed one peak each in acid, neutral and alkaline side. But the highest peak was at pH 9.5. Protease of all tested fungi was more active at pH 10.0, especially that of the cultural filtrate of H. sigmoideum var. irregualre.

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

• Journal of Intelligence and Information Systems
• /
• v.18 no.2
• /
• pp.29-45
• /
• 2012

Bond rating is regarded as an important event for measuring financial risk of companies and for determining the investment returns of investors. As a result, it has been a popular research topic for researchers to predict companies' credit ratings by applying statistical and machine learning techniques. The statistical techniques, including multiple regression, multiple discriminant analysis (MDA), logistic models (LOGIT), and probit analysis, have been traditionally used in bond rating. However, one major drawback is that it should be based on strict assumptions. Such strict assumptions include linearity, normality, independence among predictor variables and pre-existing functional forms relating the criterion variablesand the predictor variables. Those strict assumptions of traditional statistics have limited their application to the real world. Machine learning techniques also used in bond rating prediction models include decision trees (DT), neural networks (NN), and Support Vector Machine (SVM). Especially, SVM is recognized as a new and promising classification and regression analysis method. SVM learns a separating hyperplane that can maximize the margin between two categories. SVM is simple enough to be analyzed mathematical, and leads to high performance in practical applications. SVM implements the structuralrisk minimization principle and searches to minimize an upper bound of the generalization error. In addition, the solution of SVM may be a global optimum and thus, overfitting is unlikely to occur with SVM. In addition, SVM does not require too many data sample for training since it builds prediction models by only using some representative sample near the boundaries called support vectors. A number of experimental researches have indicated that SVM has been successfully applied in a variety of pattern recognition fields. However, there are three major drawbacks that can be potential causes for degrading SVM's performance. First, SVM is originally proposed for solving binary-class classification problems. Methods for combining SVMs for multi-class classification such as One-Against-One, One-Against-All have been proposed, but they do not improve the performance in multi-class classification problem as much as SVM for binary-class classification. Second, approximation algorithms (e.g. decomposition methods, sequential minimal optimization algorithm) could be used for effective multi-class computation to reduce computation time, but it could deteriorate classification performance. Third, the difficulty in multi-class prediction problems is in data imbalance problem that can occur when the number of instances in one class greatly outnumbers the number of instances in the other class. Such data sets often cause a default classifier to be built due to skewed boundary and thus the reduction in the classification accuracy of such a classifier. SVM ensemble learning is one of machine learning methods to cope with the above drawbacks. Ensemble learning is a method for improving the performance of classification and prediction algorithms. AdaBoost is one of the widely used ensemble learning techniques. It constructs a composite classifier by sequentially training classifiers while increasing weight on the misclassified observations through iterations. The observations that are incorrectly predicted by previous classifiers are chosen more often than examples that are correctly predicted. Thus Boosting attempts to produce new classifiers that are better able to predict examples for which the current ensemble's performance is poor. In this way, it can reinforce the training of the misclassified observations of the minority class. This paper proposes a multiclass Geometric Mean-based Boosting (MGM-Boost) to resolve multiclass prediction problem. Since MGM-Boost introduces the notion of geometric mean into AdaBoost, it can perform learning process considering the geometric mean-based accuracy and errors of multiclass. This study applies MGM-Boost to the real-world bond rating case for Korean companies to examine the feasibility of MGM-Boost. 10-fold cross validations for threetimes with different random seeds are performed in order to ensure that the comparison among three different classifiers does not happen by chance. For each of 10-fold cross validation, the entire data set is first partitioned into tenequal-sized sets, and then each set is in turn used as the test set while the classifier trains on the other nine sets. That is, cross-validated folds have been tested independently of each algorithm. Through these steps, we have obtained the results for classifiers on each of the 30 experiments. In the comparison of arithmetic mean-based prediction accuracy between individual classifiers, MGM-Boost (52.95%) shows higher prediction accuracy than both AdaBoost (51.69%) and SVM (49.47%). MGM-Boost (28.12%) also shows the higher prediction accuracy than AdaBoost (24.65%) and SVM (15.42%)in terms of geometric mean-based prediction accuracy. T-test is used to examine whether the performance of each classifiers for 30 folds is significantly different. The results indicate that performance of MGM-Boost is significantly different from AdaBoost and SVM classifiers at 1% level. These results mean that MGM-Boost can provide robust and stable solutions to multi-classproblems such as bond rating.

• The Journal of Natural Sciences
• /
• v.4
• /
• pp.103-142
• /
• 1991

These studies were carried out to select somatic hybrid using selectable marker genes of Nicotiana glauca transformed by NPTII gene and Solanum tuberosum transformed by T- DNA, and to study characteristics of transformant. The results are summarized as follows. 1. Crown gall tumors and hairy roots were formed on potato tuber disc infected by A. tumefaciens Ach5 and A. rhizogenes ATCC15834. These tumors and roots could be grown on the phytohormone free media. 2. Callus formation from hairy root was prompted on the medium containing 2, 4 D 2mg/I with casein hydrolysate lg/l. 3. The survival ratio of crown gall tumor callus derived from potato increased on the medium containing the activated charcoal 0. 5-2. 0mg/I because of the preventions on the other hand, hairy roots were necrosis on the same medium. 4. Callus derived from hairy root were excellently grown for a short time by suspension culture on liquid medium containing 2, 4-D 2mg/I and casein hydrolysate lg/l. 5. The binary vector pGA643 was mobilized from E. coli MC1000 into wild type Agrobacteriurn tumefaciens Ach5, A. tumefaciens $A_4T$ and disarmed A. tuniefaciens LBA4404 using a triparental mating method with E. ccli HB1O1/pRK2013. Transconjugants were obtained on the minimal media containing tetracycline and kanamycin. pGA643 vectors were confirmed by electrophoresis on 0.7% agarose gel. 6. Kanamycin resistant calli were selected on the media supplemented with 2, 4-D 0.5mg/1 and kanamycin $100\mug$/ml after co- cultivating with tobacco stem explants and A. tumefaciens LBA4404/pGA643, and selected calli propagated on the same medium. 7. The multiple shoots were regenerated from kanamycin resistant calli on the MS medium containing BA 2mg/l. 8. Leaf segments of transformed shoot were able to grow vigorusly on the medium supplemented with high concentration of kanamycin $1000\mug$/ml. 9. Kanamycin resistant shoots were rooting and elongated on medium containing kanamycin $100\mug$/ml, but normal shoot were not. 10. For the production of protoplast from potato calli transformed by T-DNA and mesophyll tissue transformed by NPTII gene, the former was isolated in the enzyme mixture of 2.0% celluase Onozuka R-10, 1.0% dricelase, 1.0% macerozyme. and 0.5M mannitol, the latter was isolated in the enzyme mixture 1.0% Celluase Onozuka R-10, 0.3% macerozyme, and 0.7M mannitol. 11. The optimal concentrationn of mannitol in the enzyme mixture for high protoplast yield was 0.8M at both transformed tobacco mesophyll and potato callus. The viabilities of protoplast were shown above 90%, respectively. 12. Both tobacco mesophyll and potato callus protoplasts were fused by using PEG solution. Cell walls were regenerated on hormone free media supplemented with kanamycin after 5 days, and colonies were observed after 4 weeks culture.

• Economic and Environmental Geology
• /
• v.47 no.5
• /
• pp.467-477
• /
• 2014

Naturally occurring asbestos (NOA) occurs in rocks and soils as a result of natural weathering and human activities. The asbestos have been associated with ultramafic and mafic rocks, and carbonate rock. The previous studies on NOA were mainly limited to ultramafic and mafic rock-hosted asbestos in Korea. But, studies on carbonatehosted asbestos are relatively rare. Therefore, the purposes of this study were to investigate mineralogical characteristics of carbonate-hosted and metapelite-hosted NOA and to examine genesis of NOA occurred in the both rocks. The study area was Daerori, Seosan, Chungnam Province, Korea. The major rock formation consisted of limestone and schist which have been known to contain asbestos. Sampling was performed at outcrop which contained carbonate rock showing acicular asbestos crystals as well as pegmatitic intrusion that contacted with carbonate rock. PLM, XRD, EPMA, and EDS analyses were used to characterize mineral assemblages, mineralogical characteristics, and crystal habits of amphiboles and other minerals. BSEM images were also used to examine the genesis of asbestos minerals. The amphibole group was observed in all of the carbonate rocks, and actinolite and tremolite were identified in all rocks. These mineral habits were mainly micro-acicular crystals or secondary asbestiform minerals on the surface of non-asbestiform minerals appearing split end of columnar crystals produced by weathering. BSEM images showed residual textures of samples. The residual textures of carbonate rocks showed dolomite-tremolite-diopside mineral assemblages that formed during prograde metasomatism stage. Some carbonate rock also showed diopside-tremolite-talc mineral assemblages which were formed during retrograde metasomatism stage, as the residual textures. In result the presence of asbestos actinolite-tremolite in the carbonate rocks were confirmed in the areas where actinolite-tremolite asbestos was influenced by low temperature hydrothermal solution during metasomatism stage. These asbestos minerals showed the acicular asbestiform minerals, but even non-asbestiform minerals, a bundle or columnar shape, could transform to asbestiform minerals as potential NOA by weathering because the end of columnar shape of non-asbestiform minerals appeared as multiple acicular shaped fibers.

• Health Policy and Management
• /
• v.27 no.4
• /
• pp.273-275
• /
• 2017

It has been forty years since the implementation of National Health Insurance (NHI) in South Korea. Following the 1977 legislature mandating medical insurance for employees and dependents in firms with more than 500 employees, South Korea expanded its health insurance to urban residents in 1989. Resultantly, total expenses of the National Health Insurance Service (NHIS) have greatly increased from 4.5 billion won in 1977 to 50.89 trillion won in 2016. With multiple insurers merging into the NHI system in 2000, a single-payer healthcare system emerged, along with separation policy of prescribing and dispensing. Following such reform, an emerging financial crisis required injections from the National Health Promotion Fund. Forty years following the introduction of the NHI system, both praise and criticism have been drawn. In just 12 years, the NHI achieved the fastest health population coverage in the world. Current medical expenditure is not high relative to the rest of the Organization for Economic Cooperation and Development. The quality of acute care in Korea is one of the best in the world. There is no sign of delayed diagnosis and/or treatment for most diseases. However, the NHI has been under-insured, requiring high-levels of out-of-pocket money from patients and often causing catastrophic medical expenses. Furthermore, the current environmental circumstances of the NHI are threatening its sustainability. Low birth rate decline, as well as slow economic growth, will make sustainment of the current healthcare system difficult in the near future. An aging population will increase the amount of medical expenditure required, especially with the baby-boomer generation of those born between 1955 and 1965. Meanwhile, there is always the problem of unification for the Korean Peninsula, and what role the health insurance system will have to play when it occurs. In the presidential election, health insurance is a main issue; however, there is greater focus on expansion and expenditure than revenue. Many aspects of Korea's NHI system (1977) were modeled after the German (1883) and Japanese (1922) systems. Such systems were created during an era where infections disease control was most urgent and thus, in the current non-communicable disease (NCD) era, must be redesigned. The Korean system, which is already forty years old, must be redesigned completely. Although health insurance benefit expansion is necessary, financial measures, as well as moral hazard control measures, must also be considered. Ultimately, there are three aspects that we must consider when attempting redesign of the system. First, the health security system must be reformed. NHI and Medical Aid must be amalgamated into one system for increased effectiveness and efficiency of the system. Within the single insurer system of the NHI must be an internal market for maximum efficiency. The NHIS must be separated into regions so that regional organizers have greater responsibility over their actions. Although insurance must continue to be imposed nationally, risk-adjustment must be distributed regionally and assessed by different regional systems. Second, as a solution for the decreasing flow of insurance revenue, low premium level must be increased to an appropriate level. Likewise, the national reserve fund (No. 36, National Health Insurance Act) must be enlarged for re-unification preparation. Third, there must be revolutionary reform of benefit package. The current system built a focus on communicable diseases which is inappropriate in this NCD era. Medical benefits must not be one-time events but provide chronic disease management. Chronic care models, accountable care organization, patient-centered medical homes, and other systems that introduce various benefit packages for beneficiaries must be implemented. The reimbursement system of medical costs should be introduced to various systems for different types of care, as is the case with part C (Medicare Advantage Program) of America's Medicare system that substitutes part A and part B. Pay for performance must be expanded so that there is not only improvement in quality of care but also medical costs. Moreover, beneficiaries of the NHI system must be aware of the amount of their expenditure through a deductible payment system so that spending can be profiled and monitored. The Moon Jae-in Government has announced its plans to expand the NHI system; however, it is important that a discussion forum is created so that more accurate analysis of the NHI, its environments, and current status of health care system, can take place for reforming NHI.

• Korean journal of food and cookery science
• /
• v.18 no.6
• /
• pp.644-654
• /
• 2002

Brown color characteristics and antioxidizing activities were investigated for Doenjang under different processing conditions. Doenjang A was prepared directly from Meju and saline solution whereas Doenjang B was Prepared after separating soy sauce by soaking for 45 days. Both Doenjangs were aged for up to 180 days. Antioxidizing activity was studied in relation to the brown color characteristics using fat-soluble extract and water-soluble extract of Doenjang. The intensity of brown color was higher in the water-soluble Doenjang extract than the fat-soluble Doenjang extract. In the UV-VIS scanning spectra, water-soluble Doenjang extracts showed significant changes as the aging proceeded, but fat-soluble Doenjang extract did not. Antioxidizing activity of fat-soluble Doenjang extract increased as the aging period extended; however, no significant difference was detected in the water-soluble extract. Overall, Doenjang A showed higher contents of amino acids, reducing sugar, brown color, and antioxidizing activity, and the antioxidizing ability was higher in water-soluble Doenjang extract rather than in the fat-soluble Doenjang extract.

• Cartoon and Animation Studies
• /
• s.24
• /
• pp.223-246
• /
• 2011

Today, cultural content industry could be defined to service business rather than manufacturing business because of its own trait. Also, it has the realistic restriction that it can't hold the dominant position in the market competition when it can't provide consumers satisfaction regardless of its quality or degree of completion. In other word, it can only expect great success when the business plan and the activities get the perfect balance with its best quality and perfect of completion. As the result, it emphasizes the importance of business competition in the global market. In briefly, there is no doubt that the creativeness of content is very important in the cultural content industry but in the future, making system to maintain the distribution process and share the profits fairly will be taken more important role. Especially, animation genre has the feature, which compares to other genres, such as film or TV drama, would be free from cultural barriers, and it is a great advantage. So to speak, animation can get little influence from cultural discount. However, Korean animation can't use the advantage properly for the foreign distribution because of its poor infrastructure and short of professional human resources. For those reasons, it has been needed to set up the realistic and specific action plan to overcome the situation. Therefore, considering those needs and the situations of Korean animation facing, making B2B online marketplace could be a great solution. The online marketplace stands for taking more efficient and broad distribution channel instead of the passive way, which we have now. If we have the B2B online marketplace, we can share all the information about the Korean animation with the potential customers whom live outside of Korea at real time. It also could be use to the windows of multiple distribution, which can make additional profits and activate the optional markets for the Korean animation. Through the method, Korean animation would be expected to get the higher international competitiveness, and it would be developed in quality and quantity of the business. Finally, it would be a great chance to Korean animation, which can get the unique brand power by improving the backward distribution circumstances.