• Journal of Life Science
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• v.33 no.1
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• pp.73-81
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• 2023

In the present study, we prepared hot water extracts and the subsequent organic solvent fractions of methanol extracts of Houttuynia cordata (HC) and Lespedeza cuneata (LC), and investigated their anti-inflammatory effects on lipopolysaccharide-stimulated RAW264.7 cells. Among the treated samples, hexane, chloroform, and ethyl-acetate fractions of HC and LC inhibited nitric oxide (NO) production in a dose-dependent manner, and decreased inducible nitric oxide synthase (iNOS) protein expression. And, we analyzed the flavonoid contents of the ethyl-acetate fraction of HC and LC, and chose apigenin for the further experiments because apigenin was one of flavonoids commonly found in HC and LC. Apigenin dramatically inhibited NO production in a dose-dependent manner without affecting cell viability and decreased iNOS and cyclooxygenase-2 (COX-2) expression. In addition, apigenin suppressed the phosphorylation of p38 and Jun N-terminal kinase (JNK) indicating that apigenin exerts anti-inflammatory activity via the mitogen-activated protein kinase (MAPK) signaling pathway. Subsequently, we conducted RNA-sequencing analysis to detect differentially expressed genes upon apigenin treatment. Among the down-regulated genes, four cytokine genes (interleukin (IL)-1α, IL-1β, IL-6, and colony stimulating factor 2 (CSF2)) were selected for the further analysis, and the reduction of their expression by apigenin was confirmed with quantitative real-time polymerase chain reaction. Overall, our results suggest that Houttuynia cordata and Lespedeza cuneata have the anti-inflammatory effects and apigenin can be the one of key molecules responsible for their anti-inflammatory activities.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3D
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• pp.295-302
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• 2010

Since the late 1990s, the BOT mode in China has been extensively used in the water sector in order to attract private investment, improve technical and operational efficiency, and expand the coverage of water services. The BOT mode has been hailed as this provides a win-win structure between the government and private players through formalized procedures and an optimal risk allocation. However, recent market analyses show that some foreign investors are reluctant to participate in the market or even retreat due to uncertainties and risks in the market. This study aims to explore various risks in the Chinese water BOT market based on the thorough literature review, fieldwork, and the case studies on the two wholly foreign-owned BOT water projects: the Chengdu No. 6 and the Shanghai Dachang Water Supply BOT projects. The research results indicate that the Chinese BOT market embraces high risks in political, institutional and legal, and financial systems. The key to a successful takeoff of the BOT mode in the Chinese water market depends on the extent to which the government will be able to remove risky factors in political, institutional and legal, and financing systems. This research outcome will provide a useful reference to the Korean construction companies which consider expanding business to overseas water markets in the form of public private partnership.

• Convergence Security Journal
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• v.24 no.1
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• pp.51-57
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• 2024

Although industrial control systems (ICSs) recently keep evolving with the introduction of Industrial IoT converging information technology (IT) and operational technology (OT), it also leads to a variety of threats and vulnerabilities, which was not experienced in the past ICS with no connection to the external network. Since various control command messages are sent to field devices of the ICS for the purpose of monitoring and controlling the operational processes, it is required to guarantee the message integrity as well as control center authentication. In case of the conventional message integrity codes and signature schemes based on symmetric keys and public keys, respectively, they are not suitable considering the asymmetry between the control center and field devices. Especially, compromised node attacks can be mounted against the symmetric-key-based schemes. In this paper, we propose message authentication scheme based on double hash chains constructed from cryptographic hash function without introducing other primitives, and then propose extension scheme using Merkle tree for multiple uses of the double hash chains. It is shown that the proposed scheme is much more efficient in computational complexity than other conventional schemes.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.6
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• pp.67-84
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• 2023

In some areas of the Republic of Korea, the designation and management of conservation areas do not adequately reflect regional characteristics and often impose behavioral regulations without considering the local context. One prominent example is the Busan EDC area. As a result, conflicts may arise, including large-scale civil complaints, regarding the conservation and utilization of these areas. Therefore, for the efficient designation and management of protected areas, it is necessary to consider various ecosystem factors, changes in land use, and regional characteristics. In this study, we specifically focused on the Busan EDC area and applied machine learning techniques to analyze the habitat of regional species. Additionally, we employed Explainable Artificial Intelligence techniques to interpret the results of our analysis. To analyze the regional characteristics of the waterfront area in the Busan EDC district and the habitat of migratory birds, we used bird observations as dependent variables, distinguishing between presence and absence. The independent variables were constructed using land cover, elevation, slope, bridges, and river depth data. We utilized the XGBoost (eXtreme Gradient Boosting) model, known for its excellent performance in various fields, to predict the habitat probabilities of 11 bird species. Furthermore, we employed the SHapley Additive exPlanations technique, one of the representative methodologies of XAI, to analyze the relative importance and impact of the variables used in the model. The analysis results showed that in the EDC business district, as one moves closer to the river from the waterfront, the likelihood of bird habitat increases based on the overlapping habitat probabilities of the analyzed bird species. By synthesizing the major variables influencing the habitat of each species, key variables such as rivers, rice fields, fields, pastures, inland wetlands, tidal flats, orchards, cultivated lands, cliffs & rocks, elevation, lakes, and deciduous forests were identified as areas that can serve as habitats, shelters, resting places, and feeding grounds for birds. On the other hand, artificial structures such as bridges, railways, and other public facilities were found to have a negative impact on bird habitat. The development of a management plan for conservation areas based on the objective analysis presented in this study is expected to be extensively utilized in the future. It will provide diverse evidential materials for establishing effective conservation area management strategies.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.139-160
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• 2017

Technology commercialization creates effective economic value by linking the company's R & D processes and outputs to the market. This technology commercialization is important in that a company can retain and maintain a sustained competitive advantage. In order for a specific technology to be commercialized, it goes through the stage of technical planning, technology research and development, and commercialization. This process involves a lot of time and money. Therefore, the duration and cost of technology commercialization are important decision information for determining the market entry strategy. In addition, it is more important information for a technology investor to rationally evaluate the technology value. In this way, it is very important to scientifically estimate the duration and cost of the technology commercialization. However, research on technology commercialization is insufficient and related methodology are lacking. In this study, we propose an evaluation model that can estimate the duration and cost of R & D technology commercialization for small and medium-sized enterprises. To accomplish this, this study collected the public data of the National Science & Technology Information Service (NTIS) and the survey data provided by the Small and Medium Business Administration. Also this study will develop the estimation model of commercialization duration and cost of R&D performance on using these data based on the market approach, one of the technology valuation methods. Specifically, this study defined the process of commercialization as consisting of development planning, development progress, and commercialization. We collected the data from the NTIS database and the survey of SMEs technical statistics of the Small and Medium Business Administration. We derived the key variables such as stage-wise R&D costs and duration, the factors of the technology itself, the factors of the technology development, and the environmental factors. At first, given data, we estimates the costs and duration in each technology readiness level (basic research, applied research, development research, prototype production, commercialization), for each industry classification. Then, we developed and verified the research model of each industry classification. The results of this study can be summarized as follows. Firstly, it is reflected in the technology valuation model and can be used to estimate the objective economic value of technology. The duration and the cost from the technology development stage to the commercialization stage is a critical factor that has a great influence on the amount of money to discount the future sales from the technology. The results of this study can contribute to more reliable technology valuation because it estimates the commercialization duration and cost scientifically based on past data. Secondly, we have verified models of various fields such as statistical model and data mining model. The statistical model helps us to find the important factors to estimate the duration and cost of technology Commercialization, and the data mining model gives us the rules or algorithms to be applied to an advanced technology valuation system. Finally, this study reaffirms the importance of commercialization costs and durations, which has not been actively studied in previous studies. The results confirm the significant factors to affect the commercialization costs and duration, furthermore the factors are different depending on industry classification. Practically, the results of this study can be reflected in the technology valuation system, which can be provided by national research institutes and R & D staff to provide sophisticated technology valuation. The relevant logic or algorithm of the research result can be implemented independently so that it can be directly reflected in the system, so researchers can use it practically immediately. In conclusion, the results of this study can be a great contribution not only to the theoretical contributions but also to the practical ones.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.75-95
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• 2020

With the growth of social networks, various forms of SNS have emerged. Based on various motivations for use such as interactivity, information exchange, and entertainment, SNS users are also on the fast-growing trend. Facebook is the main SNS channel, and companies have started using Facebook pages as a public relations channel. To this end, in the early stages of operation, companies began to secure a number of fans, and as a result, the number of corporate Facebook fans has recently increased to as many as millions. from a corporate perspective, Facebook is attracting attention because it makes it easier for you to meet the customers you want. Facebook provides an efficient advertising platform based on the numerous data it has. Advertising targeting can be conducted using their demographic characteristics, behavior, or contact information. It is optimized for advertisements that can expose information to a desired target, so that results can be obtained more effectively. it rethink and communicate corporate brand image to customers through contents. The study was conducted through Facebook advertising data, and could be of great help to business people working in the online advertising industry. For this reason, the independent variables used in the research were selected based on the characteristics of the content that the actual business is concerned with. Recently, the company's Facebook page operation goal is to go beyond securing the number of fan pages, branding to promote its brand, and further aiming to communicate with major customers. the main figures for this assessment are Facebook's 'OK', 'Attachment', 'Share', and 'Number of Click' which are the dependent variables of this study. in order to measure the outcome of the target, the consumer's response is set as a key measurable key performance indicator (KPI), and a strategy is set and executed to achieve this. Here, KPI uses Facebook's ad numbers 'reach', 'exposure', 'like', 'share', 'comment', 'clicks', and 'CPC' depending on the situation. in order to achieve the corresponding figures, the consideration of content production must be prior, and in this study, the independent variables were organized by dividing into three considerations for content production into three. The effects of content material, content structure, and message styles on Facebook's user behavior were analyzed using regression analysis. Content materials are related to the content's difficulty, company relevance, and daily involvement. According to existing research, it was very important how the content would attract users' interest. Content could be divided into informative content and interesting content. Informational content is content related to the brand, and information exchange with users is important. Interesting content is defined as posts that are not related to brands related to interesting movies or anecdotes. Based on this, this study started with the assumption that the difficulty, company relevance, and daily involvement have an effect on the dependent variable. In addition, previous studies have found that content types affect Facebook user activity. I think it depends on the combination of photos and text used in the content. Based on this study, the actual photos were used and the hashtag and independent variables were also examined. Finally, we focused on the advertising message. In the previous studies, the effect of advertising messages on users was different depending on whether they were narrative or non-narrative, and furthermore, the influence on message intimacy was different. In this study, we conducted research on the behavior that Facebook users' behavior would be different depending on the language and formality. For dependent variables, 'OK' and 'Full Click Count' are set by every user's action on the content. In this study, we defined each independent variable in the existing study literature and analyzed the effect on the dependent variable, and found that 'good' factors such as 'self association', 'actual use', and 'hidden' are important. Could. Material difficulties', 'actual participation' and 'large scale * difficulties'. In addition, variables such as 'Self Connect', 'Actual Engagement' and 'Sexual Sexual Attention' have been shown to have a significant impact on 'Full Click'. It is expected that through research results, it is possible to contribute to the operation and production strategy of company Facebook operators and content creators by presenting a content strategy optimized for the purpose of the content. In this study, we defined each independent variable in the existing research literature and analyzed its effect on the dependent variable, and we could see that factors on 'good' were significant such as 'self-association', 'reality use', 'concernal material difficulty', 'real-life involvement' and 'massive*difficulty'. In addition, variables such as 'self-connection', 'real-life involvement' and 'formative*attention' were shown to have significant effects for 'full-click'. Through the research results, it is expected that by presenting an optimized content strategy for content purposes, it can contribute to the operation and production strategy of corporate Facebook operators and content producers.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.83-102
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• 2021

The government recently announced various policies for developing big-data and artificial intelligence fields to provide a great opportunity to the public with respect to disclosure of high-quality data within public institutions. KSURE(Korea Trade Insurance Corporation) is a major public institution for financial policy in Korea, and thus the company is strongly committed to backing export companies with various systems. Nevertheless, there are still fewer cases of realized business model based on big-data analyses. In this situation, this paper aims to develop a new business model which can be applied to an ex-ante prediction for the likelihood of the insurance accident of credit guarantee. We utilize internal data from KSURE which supports export companies in Korea and apply machine learning models. Then, we conduct performance comparison among the predictive models including Logistic Regression, Random Forest, XGBoost, LightGBM, and DNN(Deep Neural Network). For decades, many researchers have tried to find better models which can help to predict bankruptcy since the ex-ante prediction is crucial for corporate managers, investors, creditors, and other stakeholders. The development of the prediction for financial distress or bankruptcy was originated from Smith(1930), Fitzpatrick(1932), or Merwin(1942). One of the most famous models is the Altman's Z-score model(Altman, 1968) which was based on the multiple discriminant analysis. This model is widely used in both research and practice by this time. The author suggests the score model that utilizes five key financial ratios to predict the probability of bankruptcy in the next two years. Ohlson(1980) introduces logit model to complement some limitations of previous models. Furthermore, Elmer and Borowski(1988) develop and examine a rule-based, automated system which conducts the financial analysis of savings and loans. Since the 1980s, researchers in Korea have started to examine analyses on the prediction of financial distress or bankruptcy. Kim(1987) analyzes financial ratios and develops the prediction model. Also, Han et al.(1995, 1996, 1997, 2003, 2005, 2006) construct the prediction model using various techniques including artificial neural network. Yang(1996) introduces multiple discriminant analysis and logit model. Besides, Kim and Kim(2001) utilize artificial neural network techniques for ex-ante prediction of insolvent enterprises. After that, many scholars have been trying to predict financial distress or bankruptcy more precisely based on diverse models such as Random Forest or SVM. One major distinction of our research from the previous research is that we focus on examining the predicted probability of default for each sample case, not only on investigating the classification accuracy of each model for the entire sample. Most predictive models in this paper show that the level of the accuracy of classification is about 70% based on the entire sample. To be specific, LightGBM model shows the highest accuracy of 71.1% and Logit model indicates the lowest accuracy of 69%. However, we confirm that there are open to multiple interpretations. In the context of the business, we have to put more emphasis on efforts to minimize type 2 error which causes more harmful operating losses for the guaranty company. Thus, we also compare the classification accuracy by splitting predicted probability of the default into ten equal intervals. When we examine the classification accuracy for each interval, Logit model has the highest accuracy of 100% for 0~10% of the predicted probability of the default, however, Logit model has a relatively lower accuracy of 61.5% for 90~100% of the predicted probability of the default. On the other hand, Random Forest, XGBoost, LightGBM, and DNN indicate more desirable results since they indicate a higher level of accuracy for both 0~10% and 90~100% of the predicted probability of the default but have a lower level of accuracy around 50% of the predicted probability of the default. When it comes to the distribution of samples for each predicted probability of the default, both LightGBM and XGBoost models have a relatively large number of samples for both 0~10% and 90~100% of the predicted probability of the default. Although Random Forest model has an advantage with regard to the perspective of classification accuracy with small number of cases, LightGBM or XGBoost could become a more desirable model since they classify large number of cases into the two extreme intervals of the predicted probability of the default, even allowing for their relatively low classification accuracy. Considering the importance of type 2 error and total prediction accuracy, XGBoost and DNN show superior performance. Next, Random Forest and LightGBM show good results, but logistic regression shows the worst performance. However, each predictive model has a comparative advantage in terms of various evaluation standards. For instance, Random Forest model shows almost 100% accuracy for samples which are expected to have a high level of the probability of default. Collectively, we can construct more comprehensive ensemble models which contain multiple classification machine learning models and conduct majority voting for maximizing its overall performance.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.11
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• pp.1615-1634
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• 2004

A review was undertaken to obtain information on the sustainability of pig free-range production systems including the management, performance and health of pigs in the system. Modern outdoor rearing systems requires simple portable and flexible housing with low cost fencing. Local pig breeds and outdoor-adapted breeds for certain environment are generally more suitable for free-range systems. Free-range farms should be located in a low rainfall area and paddocks should be relatively flat, with light topsoil overlying free-draining subsoil with the absence of sharp stones that can cause foot damage. Huts or shelters are crucial for protecting pigs from direct sun burn and heat stress, especially when shade from trees and other facilities is not available. Pigs commonly graze on strip pastures and are rotated between paddocks. The zones of thermal comfort for the sow and piglet differ markedly; between 12-22$^{\circ}C$ for the sow and 30-37$^{\circ}C$ for piglets. Offering wallows for free-range pigs meets their behavioural requirements, and also overcomes the effects of high ambient temperatures on feed intake. Pigs can increase their evaporative heat loss via an increase in the proportion of wet skin by using a wallow, or through water drips and spray. Mud from wallows can also coat the skin of pigs, preventing sunburn. Under grazing conditions, it is difficult to control the fibre intake of pigs although a high energy, low fibre diet can be used. In some countries outdoor sows are fitted with nose rings to prevent them from uprooting the grass. This reduces nutrient leaching of the land due to less rooting. In general, free-range pigs have a higher mortality compared to intensively housed pigs. Many factors can contribute to the death of the piglet including crushing, disease, heat stress and poor nutrition. With successful management, free-range pigs can have similar production to door pigs, although the growth rate of the litters is affected by season. Piglets grow quicker indoors during the cold season compared to outdoor systems. Pigs reared outdoors show calmer behaviour. Aggressive interactions during feeding are lower compared to indoor pigs while outdoor sows are more active than indoor sows. Outdoor pigs have a higher parasite burden, which increases the nutrient requirement for maintenance and reduces their feed utilization efficiency. Parasite infections in free-range pigs also risks the image of free-range pork as a clean and safe product. Diseases can be controlled to a certain degree by grazing management. Frequent rotation is required although most farmers are keeping their pigs for a longer period before rotating. The concept of using pasture species to minimise nematode infections in grazing pigs looks promising. Plants that can be grown locally and used as part of the normal feeding regime are most likely to be acceptable to farmers, particularly organic farmers. However, one of the key concerns from the public for free-range pig production system is the impact on the environment. In the past, the pigs were held in the same paddock at a high stocking rate, which resulted in damage to the vegetation, nutrient loading in the soil, nitrate leaching and gas emission. To avoid this, outdoor pigs should be integrated in the cropping pasture system, the stock should be mobile and stocking rate related to the amount of feed given to the animals.

• Journal of the Korean Geographical Society
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• v.29 no.2
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• pp.117-136
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• 1994

Contemporary global space economy is so dynamic that any one specific structural force can not explain the whole dynamic processes or trajectories of spatial industrial development. The major purpose of this paper is extending the traditional notion of industrial districts to functioning and development of new industrial districts with relation to the development of high technology industries. Several dynamic forces, which are dominated in new industrial districts in the modern space economy, are incorporated in the formation and dynamic aspects of new industrial districts. Even though key forces governing Marshallian industrial district are localization of small firms, division of labor between firms, constructive cooperation, and industrial atmosphere, Marshall points out a possibility of growing importance of large firms and non-local networks in the districts with changes of external environments. Some of Italian industrial districts can be regarded as Marshallian industrial districts in broader context, but the role of local authorities or institutions and local embeddedness seem to be more important in the Italian industrial districts. More critical implication form the review of Marshallian industrial districts and Italian industrial districts is that the industrial districts are not a static concept but a dynamic one: small firm based industrial districts can be regarded as only a specific feature evolved over time. Dynamic aspects of new industrial districts are resulting from coexistence of contrasting forces governing the functioning and formation of the districts in contemporary global space economy. The contrasting forces governing new industrial districts are coexistence of flexible and mass production systems, local and global networks, local and non-local embeddedness, and small and large firms. Because of these coexistence of contrasting forces, there are various types of new industrial districts. Nine types of industrial districts are identified based on local/non-local networks and intensity of networks in both suppliers and customers linkages. The different types of new industrial districts are described by differences in production systems, embeddedness, governance, cooperation and competition, and institutional factors. Out of nine types of industrial districts, four types - Marshallian; suppliers hub and spoke; customers hub and spoke; and satellite - are regarded as distinctive new industrial districts and four additional types - advanced hub and spoke types (suppliers and customers) and mature satellites (suppliers and customers) - can be evolved from the distinctive types and may be regarded as hybrid types. The last one - pioneering high technology industrial district - can be developed from the advanced hub and spoke types and this type is a most advanced modern industrial district in the era of globalization and high technology. The dynamic aspects of the districts are related with the coexistence of the contrasting forces in the contemporary global space economy. However, the development trajectory is not a natural one and not all the industrial districts can develop to the other hybrid types. Traditionally, localization of industries was developed by historical chances. In the process of high technology industrial development in contemporary global space economy, however, policy and strategies are critical for the formation and evolution of new industrial districts. It needs formation of supportive tissues of institutions for evolution of dyamic pattern of high technology related new industrial districts. Some of the original distinctive types of new industrial districts can not follow the path or trajectory suggested in this paper and may be declined without advancing, if there is no formation of supportive social structure or policy. Provision of information infrastructure and diffusion of an entrepreneurship through the positive supports of local government, public institutions, universities, trade associations and industry associations are important for the evolution of the dynamic new industrial districts. Reduction of sunk costs through the supports for training and retraining of skilled labor, the formation of flexible labor markets, and the establishment of cheap and available telecommunication networks is also regarded as a significant strategies for dynamic progress of new industrial districts in the era of high technology industrial development. In addition, development of intensive international networks in production, technology and information is important policy issue for formation and evolution of the new industrial districts which are related with high technology industrial development.

• Journal of Nutrition and Health
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• v.41 no.6
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• pp.561-572
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• 2008

Currently, Korea is facing dramatic nutrition transition among children, which may increase risk of degenerative diseases due to excessive intakes of fats, sugars and sodium. Promotion of eating healthier foods among children is difficult because the present nutrition label is not easily understood. Therefore, to promote healthier foods this study was aimed at developing guidance of standard amounts of high, medium and low levels of sugars, sodium, fats and other components contained in foods or drinks that are promoted to or formulated for consumption by children. Multipronged approach was used to collecting information, including key word searches in Medline and other databases, internet searches, reports from world organization, and contact of key individuals who work in organizations. We reviewed dietary reference intakes for Koreans, nutrient reference values, nutrient content claims of nutrition labeling, guideline daily amounts of United Kingdom, dietary guidelines and consumption data of nutrients, and selected components for labeling. And we decided goals of guideline daily amounts for children and nutrient criteria to underpin the high, medium and low content of each component. Then we collected data on processed foods sold at 12 middle schools and 11 high schools in Seoul, and classified processed foods into food category. Sales per one student per day were in the order of snacks, breads, and non-carbonated drinks. One hundred forty five mostly consumed products were selected and classified into criteria of high, medium and low total fat or sodium. Eighty five(58.6%) were classified into high fat food and only 11(7.6%) into high sodium food, in case that the base is chosen per 100 g or 100 mL. In conclusion, the nutrient criteria and choice of 100 g base, which we suggest in this study, need to be tested by simulation with more processed foods and refined in view of the practical issues suggested by stakeholders in future.