• Economic and Environmental Geology
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• v.47 no.3
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• pp.205-217
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• 2014

As Mt. Backdu is expected to erupt, the social and economic impacts of the eruption on the Korean peninsula as well as on the world become a research topic of interest. If the volcano erupts, South Korea can be directly impacted by volcanic ash, which will bring out secondary damages in various ways. Given that the direct damage is a basis to estimate indirect and secondary damages, this paper was to review a method to estimate direct damages, called catastrophe risk models, and estimate the direct damages of available eruption scenarios of Mt. Baekdu. Based on the results, the damages by volcanic ash will occur mostly around Gangwon province if the Mt. Backdu erupts. Thus the inventory lists and their damage functions of Gangwon provinces were collected. In particular agricultural and forestry products were surveyed based on the land use. Direct damages were estimated using volcanic ash distribution of eruption scenarios, inventory information and their damage functions. In result, a scenario in winter caused the damage of 299.8 billion KRW (20.4% of total agricultural production in 2010) and 28.9 billion KRW (9.0% of total forestry production in 2010) in agriculture and forestry, respectively. The damages in agriculture was larger, and it is due to the damage functions which show the agricultural products are more vulnerable to volcanic ash than forestry products. Also the agricultural production (1,471.7 billion KRW in 2010) are more than 4.5 times the forestry production (322.3 billion KRW in 2010) in Gangwon province. Inje and Gangnung had the most damages in the scenario in winter. Inje had the most damage due to the thick ash deposit (8.5 mm in average) despite the low production. On the other hand, Goseong had a low damage compared to the ash thickness larger than 20mm, owing to the low production. The direct damage estimated through this process can be used to estimate indirect damages.

• Cartoon and Animation Studies
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• s.29
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• pp.129-149
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• 2012

The purpose of this study was to investigate the clustering and Big Five Personality domains in discriminating groups by level of school-related adjustment, as experienced by Social Sims game users. Social Games are based on web that has simple rules to play in fictional time and space background. This paper is to analyze the relationships between social networks and user behaviors through the social games . In general, characteristics of social games are simple, fun and easy to play, popular to the public, and based on personal connections in reality. These features of social games make themselves different from video games with one player or MMORPG with many unspecific players. Especially Social Game show a noticeable characteristic related to social learning. The object of this research is to provide a possibility that game that its social perspective can be strengthened in social game environment and analyze whether it actually influences on problem solving of real life problems, therefore suggesting its direction of alternative play means and positive simulation game. Data was collected by administering 4 questionnaires (the short version of BFI, Satisfaction with life, Career Decision-.Making Self-.Efficacy, Depression) to the participants who were 20 people in Seoul and Daejeon. For the purposes of the data analysis, both Stepwise Discriminant analysis and Cluster analysis was employed. Neuroticism, Openness, Conscientiousness within the Big Five Personality domains were seen to be significant variables when it came to discriminating the groups. These findings indicated that the short version of the BFI may be useful in understanding for game user behaviors When it comes to cultural research, digital game takes up a significant role. We can see that from the fact that game, which has only been considered as a leisure activity or commercial means, is being actively research for its methodological, social role and function. Among digital game's several meanings, one of the most noticeable ones is the research on its critical, social participating function. According to Jame Paul gee, the most important merit of game is 'projected identity'. This means that experiences from various perspectives is possible.[1] In his recent autobiography , he described gamer as an active problem solver. In addition, Gonzalo Francesca also suggested an alternative game developing method through 'game that conveys critical messages by strengthening critical reasons'. [2] They all provided evidences showing game can be a strong academic tool. Not only does a genre called social game exist in the field of media and Social Network Game, but there are also some efforts to positively evaluate its value Through these kinds of researches, we can study how game can give positive influence along with the change in its general perception, which would eventually lead to spreading healthy game culture and enabling fresh life experience. This would better bring out the educative side of the game and become a social communicative tool. The object of this game is to provide a possibility that the social aspect can be strengthened within the game environment and analyze whether it actually influences the problem solving of real life problems. Therefore suggesting it's direction of alternative play means positive game simulation.

• Korean Security Journal
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• no.59
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• pp.37-69
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• 2019

According to viewpoints of researchers and stakeholders, various opinions can be suggested on self-governing police system. Therefore, success of Korean self-governing police system will be defending on how to balance among conflicting values such as Empowerment, Political neutrality, Financial issues, Comprehensive competence in maintaining public safety. Before the launching of self-governing police system nation-wide, the experience of Jeju provincial police will be valuable model case. In specific, enlargement of work scope of self-governing police in Jeju province which has been introduced since last year will be a useful reference. There is more pessimism about self-governing police of Jeju province so far. However, this perspective is mostly based on the issue regarding hardwares such as manpower, equipment, law and organization. Issues regarding softwares such as organizational culture, operation system and work process need more attention to evaluate self-governing police system properly. To mark the first year after enlargement of work scope of Jeju police, this study demonstrate the overall result and implications of self-governing police of Jeju province based on documents, statistics, reports and media reports. In result, several preconditions are needed to implement the self-governing police system nation-wide successfully. 1. Strengthen the link between local government and local police 2. Establish the foundation for collaboration of state and local police 3. Enhance the aspect of citizen autonomy in local level 4. Reinforcing the capability of handling situation of state and local police 5. Invigorating the inter-organizational working group to operate self-governing police system effectively. The self-governing police system is unclosed topic to discuss. After this study, in-depth studies should be followed with more resources. Particularly, additional perspective including redundancy and equity need to be considered regarding self-governing police. By getting with the changes of macroscopic trends - lowbirth and aging, the fourth industrial revolution and possible reunification of north and south Koreas - these studies should suggest the long-term blueprint of self-governing police system of Korea.

• The Journal of Society for e-Business Studies
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• v.17 no.4
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• pp.69-93
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• 2012

Various influence-related relationships in Social Network Services (SNS) among users, posts, and user-and-post, can be expressed using links. The current research evaluates the influence of specific users or posts by analyzing the link structure of relevant social network graphs to identify influential users. We applied the concept of mutual interactions proposed for ranking semantic web resources, rather than the voting notion of Page Rank or HITS, to blogosphere, one of the early SNS. Through many experiments with network models, where the performance and validity of each alternative approach can be analyzed, we showed the applicability and strengths of our approach. The weight tuning processes for the links of these network models enabled us to control the experiment errors form the link weight differences and compare the implementation easiness of alternatives. An additional example of how to enter the content scores of commercial or spam posts into the graph-based method is suggested on a small network model as well. This research, as a starting point of the study on identifying influential users in SNS, is distinctive from the previous researches in the following points. First, various influence-related properties that are deemed important but are disregarded, such as scraping, commenting, subscribing to RSS feeds, and trusting friends, can be considered simultaneously. Second, the framework reflects the general phenomenon where objects interacting with more influential objects increase their influence. Third, regarding the extent to which a bloggers causes other bloggers to act after him or her as the most important factor of influence, we treated sequential referencing relationships with a viewpoint from that of PageRank or HITS (Hypertext Induced Topic Selection).

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.24-38
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• 2019

Due to the dramatic spatial changes caused by industrialization, environmental problems such as air pollution and urban heat island phenomenon, etc. are occurring in cities. In this case, the wind corridor, which is a passage through which fresh and cool air generated in forests outside cities move to the downtown, can be used as a spatial planning method for improving urban environmental problems. Cold air is determined by the characteristics of the flow depending on the topography and land use of cities, and based on this, the medium- and long-term plan should be established. Therefore, this study analyzed the flow of cold air at night through the KLAM_21 model in Suwon-si, Gyeonggi-do, to prepare the basic data required to apply the wind corridors. As a result, it turned out that cold air of Suwon-si was mainly generated from Gwanggyo Mountain that is a large mountain area in the north, and flowed into the urbanization promotion area, and about three hours after sunset, cold air flowed into the downtown. By district, the depth, wind speed, and direction of the cold air layer were formed differently according to the characteristics of the topography and land use. In the areas where large forests were adjacent, the flow of cold air was active. There are three main wind corridors where cold air flows to the downtown of Suwon-si, all of which are formed around rivers. Especially, if the connection between rivers and the surrounding green areas is high, the effect of wind corridors is found to be significant. In order to utilize the wind corridors of Suwon-si, based on the results of this study, it is necessary to make climate maps through actual survey and complex analysis of cold air flow and establish mid-to-long-term plans for the conservation and expansion of major wind corridors.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.1-19
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• 2018

Since stock movements forecasting is an important issue both academically and practically, studies related to stock price prediction have been actively conducted. The stock price forecasting research is classified into structured data and unstructured data, and it is divided into technical analysis, fundamental analysis and media effect analysis in detail. In the big data era, research on stock price prediction combining big data is actively underway. Based on a large number of data, stock prediction research mainly focuses on machine learning techniques. Especially, research methods that combine the effects of media are attracting attention recently, among which researches that analyze online news and utilize online news to forecast stock prices are becoming main. Previous studies predicting stock prices through online news are mostly sentiment analysis of news, making different corpus for each company, and making a dictionary that predicts stock prices by recording responses according to the past stock price. Therefore, existing studies have examined the impact of online news on individual companies. For example, stock movements of Samsung Electronics are predicted with only online news of Samsung Electronics. In addition, a method of considering influences among highly relevant companies has also been studied recently. For example, stock movements of Samsung Electronics are predicted with news of Samsung Electronics and a highly related company like LG Electronics.These previous studies examine the effects of news of industrial sector with homogeneity on the individual company. In the previous studies, homogeneous industries are classified according to the Global Industrial Classification Standard. In other words, the existing studies were analyzed under the assumption that industries divided into Global Industrial Classification Standard have homogeneity. However, existing studies have limitations in that they do not take into account influential companies with high relevance or reflect the existence of heterogeneity within the same Global Industrial Classification Standard sectors. As a result of our examining the various sectors, it can be seen that there are sectors that show the industrial sectors are not a homogeneous group. To overcome these limitations of existing studies that do not reflect heterogeneity, our study suggests a methodology that reflects the heterogeneous effects of the industrial sector that affect the stock price by applying k-means clustering. Multiple Kernel Learning is mainly used to integrate data with various characteristics. Multiple Kernel Learning has several kernels, each of which receives and predicts different data. To incorporate effects of target firm and its relevant firms simultaneously, we used Multiple Kernel Learning. Each kernel was assigned to predict stock prices with variables of financial news of the industrial group divided by the target firm, K-means cluster analysis. In order to prove that the suggested methodology is appropriate, experiments were conducted through three years of online news and stock prices. The results of this study are as follows. (1) We confirmed that the information of the industrial sectors related to target company also contains meaningful information to predict stock movements of target company and confirmed that machine learning algorithm has better predictive power when considering the news of the relevant companies and target company's news together. (2) It is important to predict stock movements with varying number of clusters according to the level of homogeneity in the industrial sector. In other words, when stock prices are homogeneous in industrial sectors, it is important to use relational effect at the level of industry group without analyzing clusters or to use it in small number of clusters. When the stock price is heterogeneous in industry group, it is important to cluster them into groups. This study has a contribution that we testified firms classified as Global Industrial Classification Standard have heterogeneity and suggested it is necessary to define the relevance through machine learning and statistical analysis methodology rather than simply defining it in the Global Industrial Classification Standard. It has also contribution that we proved the efficiency of the prediction model reflecting heterogeneity.

• The Journal of Korean Institute for Practical Engineering Education
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• v.3 no.1
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• pp.1-8
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• 2011

In this paper, as a new educational cooperation model, seeking the problems and the directions of progress on GPOE(Gyeonggi Provincial Office of Education)'s innovational education district project, recognizing the various points of issue of SVHS(specialized vocational high schools) faced now, suggesting the contents and standards of the program as measures of enhancing competitiveness of SVHS, analyzing the strengths and weaknesses of project of innovational education district and finding the plans for progress. According to the result of the advanced study and analysis, it shows that the aid as well as the supporting object of helping the SVHS's students find a job don't reach a certain level. As the aid supports across the general elementary and secondary schools, it tends to show much more emotional software-based support required by elementary school, middle school and general high school as universal education welfare rather than hardware-based support required by SVHS. Despite the competent evaluation on the survey about the supporting method from SVHS's parents teachers and students, the survey includes that teachers who ask the balancing support are increasing, some students suspect its effect of education and some parents as a residential position ask the regional growth rather than education So there are a lot of confusions among the teachers, students and parents yet. To overcome these problems, we ensure the internal stability of local education community and GPOE and local government get out large scale constructions with trust and belief to make a revolution of public education in supporting the administrative task and finance and to accomplish the program that best suits our SVHS's state to be supported without dividing educational software and hardware, should reflect the demand of field by for expert group being built and attended when build the local revolution community. Also plan to make full use of local human and property infrastructure should be added. To this end, as programs to build a pool of guest lecturers are provided to teachers who carry out innovative education programs, we seek the reformations to give students opportunities to widen participation in other school programs.

• Journal of Radiation Protection and Research
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• v.40 no.3
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• pp.124-131
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• 2015

Radiation exposure to humans can be caused by the gamma rays emitted from natural radioactive elements(such as uranium, thorium and potassium and any of their decay products) of Naturally Occurring Radioactive Materials(NORM) or Technologically Enhanced Naturally Occurring Radioactive Materials(TENORM) added consumer products. In this study, assume that activity of radioactive elements is $^{238}U$, $^{235}U$, $^{232}Th$ $1Bq{\cdot}g^{-1}$, $^{40}K$ $10Bq{\cdot}g^{-1}$ and the gamma rays emitted from these natural radioactive elements radioactive equilibrium state. In this study, reflected End-User circumstances and evaluated annual exposure dose for products based on ICRP reference voxel phantoms and ICRP Recommendation 103 using the Monte Carlo Method. The consumer products classified according to the adhere to the skin(bracelet, necklace, belt-wrist, belt-ankle, belt-knee, moxa stone) or not(gypsum board, anion wallpaper, anion paint), and Geometric Modeling was reflected in Republic of Korea "Residential Living Trend-distributions and Design Guidelines For Common Types of Household.", was designed the Room model($3m{\times}4m{\times}2.8m$, a closed room, conservatively) and the ICRP reference phantom's 3D segmentation and modeling. The end-user's usage time assume that "Development and Application of Korean Exposure Factors." or conservatively 24 hours; in case of unknown. In this study, the results of the effective dose were 0.00003 ~ 0.47636 mSv per year and were confirmed the meaning of necessary for geometric modeling to ICRP reference phantoms through the equivalent dose rate of belt products.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.2
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• pp.19-32
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• 2020

The purpose of this study was to investigate the influence factors of the university level centering on the entrepreneurial performance of the university students and full-time faculties in the situation of increasing interest in entrepreneurial university. In order to achieve the purpose of the study, a panel data was established from 2015 to 2018 on the basis of the university notification data. The panel data included universities with data on the number of university students and full-time faculty founders for at least two years. Through this, four year data from 154 universities were used for analysis. As an analysis method, frequency analysis and descriptive statistics were conducted to understand the characteristics of the university. Since then, panel negative binomial regression analysis has been conducted in consideration of the longitudinal features and distribution of the data. Also, based on the Hausman test results, the results were interpreted based on random effect model. The results of this study are as follows. First, as a result of the analysis of the entrepreneurial performance and the change trend of the domestic university from 2015 to 2018, the entrepreneurial performance of the university has been steadily increasing in the last four years, and the increase in the number of university student entrepreneurs was relatively higher than the full-time faculties. Second, economic and educational approaches need to be combined to promote university students' start-ups. The university factors that promote the start-up of university students were found to be scholarships, start-up grants, startup lectures, and startup clubs. Third, the openness and regional characteristics of the univeristy can promote the establishment of university students. Fourth, the establishment of a research environment and support for start-ups for full-time faculty members can enhance their start-up performance. The university factors that promote the start-up of full-time faculty were research funds and staffes who support start-up. The conclusions drawn from these findings are as follows. First, overall efforts are needed to develop into an entrepreneurial university. Second, in order to change into an entrepreneurial university, direct support for entrepreneurship is needed. Third, as an entrepreneurial university, it is necessary to find a way to bridge the gap by university according to region and size. Fourth, it is necessary to reinforce the support for linking the research results of universities to start-ups. Fifth, it is necessary to improve the atmosphere for full-time faculty members to be entrepreneur.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.6
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• pp.750-763
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• 2018

This study conducted 10 sampling sites survey 4 times to determine the trophic structure and energy flow of marine ecosystems for Uljin marine ranching area, Korean East Sea from March to October 2013. Based on the ecological characteristics of biological species, one used the non-Metric Multidimensional Scaling method based on the similarity of species. A total of 19 classified species groups formed categories including, top predators, seabirds, large pelagic fishes, small pelagic fishes, rockfishes, pleuronectiformes, benthic fishes, semi-benthic fishes, cephalopods, benthic feeders, epifauna, bivalves, abalone, Cnidaria, zooplankton, benthic algae, microalgae, phytoplankton and detritus. The biomass, production/biomass, consumption/biomass, diet composition data of each species groups to input data used in Ecopath mode estimated the trophic structure and energy flow of marine ecosystems in the Uljin marine ranching area. One estimated each species groups on the trophic level from 1 to 5.687. The sum of all consumption was estimated at $229.7t/km^2/yr$ and the sum of all exports was as estimated $3,432.4t/km^2/yr$. Total system throughput was at $6,796.2t/km^2/yr$, and the sum of all production was estimated at $3,613.1t/km^2/yr$. Net system production according to these results was estimated at $3,490.3t/km^2/yr$ and total biomass (excluding detritus) was estimated at $167.3t/km^2/yr$ in the Uljin marine ranching area.