• Journal of Environmental Impact Assessment
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• v.27 no.6
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• pp.635-646
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• 2018

This study sought to identify the characteristics of seasonal concentration differences of particulate matter influenced by land cover types associated with particulate matter emission and reductions, namely forest and urbanized regions. PM10 and PM2.5 was measured with quantitative concentration in 2016 on 23 urban air monitoring stations in Seoul, classified the stations into 3 groups based on the ratio of urbanized and forest land covers within a range of 3km around station, and analysed the differences in particulate matter concentration by season. The center values for the urbanized and forest land covers by group were 53.4% and 34.6% in Group A, 61.8% and 16.5% in Group B, and 76.3% and 6.7% in Group C. The group-specific concentration of PM10 and PM2.5 by season indicated that the concentration of Group A, with high ratio of forests, was the lowest in all seasons, and the concentration of Group C, with high ratio of urbanized regions, had the highest concentration from spring to autumn. These inter-group differences were statistically significant. The concentration of Group C was lower than Group B in the winter; however, the differences between Groups B to C in the winter were not statistically significant. Group A concentration compared to the high-concentration groups by season was lower by 8.5%, 11.2%, 8.0%, 6.8% for PM10 in the order of spring, summer, autumn and winter, and 3.5%, 10.0%, 4.1% and 3.3% for PM2.5. The inter-group concentration differences for both PM10 and PM2.5 were the highest in the summer and grew smaller in the winter, this was thought to be because the forests' ability to reduce particulate matter emissions was the most pronounced during the summer and the least pronounced during the winter. The influence of urbanized areas on particulate matter concentration was lower compared to the influence of forests. This study provided evidence that the particulate matter concentration was lower for regions with higher ratios of forests, and subsequent studies are required to identify the role of green space to manage particulate matter concentration in cities.

• (The) Research of the performance art and culture
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• no.36
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• pp.289-312
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• 2018

Pansori has been passed down over several generations and over time have undergone continued change in accordance with the times, as well as the skills and ability of the singer. Policies regarding intangible cultural treasures were established to preserve and promote the continuing tradition of art forms including Pansori and thus must spare no effort in supporting and preserving the genre. As such, for proper implementation of the newly legislated law, it is necessary to review the agents who pass down the tradition of Pansori and whether there are any areas that need to be changed in terms of our perception of culture in general. Pansory in the $21^{st}$ century features both contemporary aspects and mass appeal and have undergone many changes in how it is enjoyed. It is our responsibility therefore, to establish how the art and universality of Pansori should be promoted. From this perspective, this study reviewed the evolution of law on intangible cultural treasures, the current status of intangible cultural treasures being passed down with a focus on national treasures and those of Jeonbuk Province to shed light on issues. Diversification is needed in the number of those who carry this intangible cultural treasure, as well as the number of categories. To that end, a survey index or practical ability index must be taken into account for the application and designation of intangible cultural treasures. The study also noted issues of the categories for designation as intangible cultural treasures and discussed directions for improvement. In the case of Pansori, suggestions for improvement were presented for the designation of skilled artists by school, regular surveys and regular application, increased role of artists for increased mass appeal, survey of regional singers, supervision and monitoring of skilled artists and establishment of a manual for the education on how to pass down the art form. In doing so, efforts should be made to make the passing down of Pansori more active and related education more systematic. Since we are in the early years of the law on intangible cultural treasures being implemented, areas of improvement will continue to be identified. It is however certain that the proper support for the art form to be handed down should be done in a way where law and culture are complementary given that Pansori is not just a Korean tradition, but a tradition of mankind.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.47-64
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• 2021

The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.177-192
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• 2021

The Development Assistance Committee of the Organization for Economic Cooperation and Development discusses the reorganization of the five evaluation criteria of the Public Development Assistance Committee, which are used internationally, and the five evaluation criteria including adequacy, efficiency, effectiveness, impact, and sustainability when assessing public development assistance in 1991. This study is to derive alternatives by applying the evaluation criteria of the Development Assistance Committee of the Organization for Economic Cooperation and Development in the evaluation of the inclusive business program being implemented in Nepal since 2019. As a result of the study, the adequacy of Nepal's inclusive business program was consistent with continuous employment and job creation for vulnerable groups such as disabled and orphan women. Efficiency can be said to be efficient in that processes such as work order and work confirmation are made with an electronic management tool, and delivery of the result is transmitted online, saving time and cost compared to other industries. The effectiveness of this project can be said to be an effective program in that it provides high-quality jobs such as providing specialized computer graphics education for the vulnerable, such as disabled and orphan women in Nepal, and hiring graduates as employees. Sustainability is the point that KOICA's inclusive business program has enabled vulnerable groups in the existing fields of agriculture and manufacturing to engage in the computer graphics industry, and the scalability of movies, characters, education businesses, and role models in other countries.However, considering that the scale of public development assistance will continue to increase in the future, it is necessary to establish a systematic monitoring system and a recirculation system so that the project between the donor and recipient countries can continue.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.1-16
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• 2023

As the Intergovernmental Panel on Climate Change (IPCC) emphasized the transition to a carbon-neutral society globally by 205 0, major countries such as Korea, Japan, and Europe declared carbon-neutral goals. The agricultural sector is a carbon-absorbing sector, and its importance has increased as the General Assembly of the Parties to the Climate Change Convention (COP 26) held in the UK in November 2021 emphasized the role of agriculture to discuss climate change. However, GHG reduction projects in the agricultural sector are not properly monitored considering the domestic situation, and a system for quantitative evaluation of the effectiveness or basis of implementing the project program is not in place. Therefore, a priori study is needed to understand the current status of existing policies and to review matters that need to be improved in order to facilitate policy design, implementation, and monitoring for GHG reduction in the agricultural sector. The purpose of this study is to examine the opinions of stakeholders by applying a semi-structured interview method to diagnose the current status of Korea's GHG reduction policy in the agricultural sector and identify factors that hinder policy implementation. As a result of the semi-structured interview, this study presented factors that hinder the promotion of GHG reduction policies in the agricultural sector according to four types of data and technology, finance, institutions, and perceptions. Some stakeholders also stressed that the pilot project could be helpful as a way to comprehensively consider the implications of this study, such as securing technology data, establishing a system for verifying effectiveness, and providing incentives and promoting them. Rather than drawing specific conclusions, this study is an exploratory study that diagnoses and reviews the progress of GHG reduction policies, and it can be used as useful basic data if it secures enough interview respondents and balances the number of samples by group.

• Tuberculosis and Respiratory Diseases
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• v.53 no.3
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• pp.294-308
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• 2002

Background : The cell-mediated immune response plays an important role in tuberculosis. After being activated by mycobacterial antigens, T lymphocytes express a high affinity receptor (IL-2R) for interleukin-2 (IL-2) on their own surface and release a soluble fraction of the IL-2 receptor (sIL-2R) from the cell membrane into the circulation. Neopterin is a metabolite of guanosine-triphosphate, which is produced by stimulated macrophages under the influence of IFN-$\gamma$ with a T lymphocyte origin. Therefore, the utility of sIL-2R, IFN-$\gamma$ and the neopterin levels as immunologic indices of the cell-mediated immune response and severity of disease in patients with pulmonary tuberculosis was assessed. Methods : The serum sIL-2R, IFN-$\gamma$ and neopterin levels were measured in 39 patients with pulmonary tuberculosis, 6 patients with tuberculous lymphadenitis prior to treatment and 10 healthy subjects. The serum and pleural sIL-2R, neopterin and ADA levels were measured in 22 patients with tuberculous pleurisy. The patients with pulmonary tuberculosis were divided into a mild, moderate and severe group according to the severity by ATS guidelines. To compare the results from these patients with those of the pretreatment levels, the sIL-2R, IFN-$\gamma$ and neopterin levels were measured in 36 of the 39 patients(1 patient, expired; 2 patients were referred to a sanitarium) with pulmonary tuberculosis after 2 months of treatment. Results : 1) the serum sIL-2R and IFN-$\gamma$ levels were elevated in patients with tuberculosis when compared to those of healthy subjects (p>0.05). The neopterin concentration in the serum was significantly lower in patients with pulmonary tuberculosis($2967{\pm}2132.8$ pg/ml) than in healthy controls($4949{\pm}1242.1$ pg/ml)(p<0.05). 2) In the pulmonary tuberculosis group, the serum sIL-2R and IFN-$\gamma$ levels were higher in patients with severe disease than those in patients with mild and moderate disease. However, the neopterin levels declined as the pulmonary tuberculosis became more severe (p<0.01). 3) The mean serum sIL-2R and IFN-$\gamma$ levels declined from $1071{\pm}1139.4$ U/ml to $1023{\pm}1920.9$ U/ml(p>0.05), $41{\pm}52.8$ pg/ml to $22{\pm}23.9$ gm/ml(p<0.05), respectively, after 2 month of treatment. The mean serum neopterin levels increased from $3158{\pm}2272.6$ pg/ml to $3737{\pm}2307.5$ pg/ml(p>0.05) after a 2 month of treatment. These findings were remarkable in the severe group of pulmonary tuberculosis with a clinical correlation. 4) In the patients with tuberculous pleurisy, the serum sIL-2R and ADA were significantly higher than those in the pleural fluid, However, the neopterin levels in the sera and pleural effusion were similar. Conclusion : On the basis of this study, sIL-2R, IFN-$\gamma$ and neopterin measurements may not only provide an insight into the present state of the cell-mediated immune response, but also serve as parameters monitoring of the prognosis of the disease, particularly in patients with severe pulmonary tuberculosis. In addition, an assay of the pleural sIL-2R levels might signal a stimulated local immunity including T cell activation in the tuberculous pleural effusion.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.1-33
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• 2019

The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.127-148
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• 2020

The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.