• The Journal of the Korea Contents Association
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• v.14 no.6
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• pp.108-118
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• 2014

The purpose of this study is to develop a relationship of measuring method for the social security network and verify its validity and reliability and apply it to investigate the due to security life satisfaction. This study is based by setting general residents of Seoul in 2013 and using the stratified cluster random sampling method to analyze a total amount of 203 examples. The measuring methods for the social security network was developed through document research, conceptual definition and drafting the survey, experts' conference, preliminary inspection and original examination, verification of the validity and reliability of the survey. An experts' conference took pace to verify the validity of the survey, and 6 factors were extracted through exploratory factor analysis crime prevention design, street CCTV facilities, volunteer neighborhood patrol, local government security education, police public peace service, private security service. The conclusion are the following. Collected data was analyzed based on the aim of this study using SPSSWIN 18.0, and practice frequency analysis, F test, factor analysis, reliability analysis, correlation analysis, multiple regression analysis. First, the validity of the social security network measurement is very high. Thus, the factors constituting the social security network were found to be crime prevention design, street CCTV facilities, volunteer neighborhood patrol, local government security education, police public peace services, and private security services, and the crime prevention design factor was found to be most explanatory. Second, the reliability of the social security network measurement is very high. Thus, the correlation between the questions and the sector, the questions and the social security net was very high, and the internal consistency showed a Cronbach's${\alpha}$ value of over 0.865. Third, the establishment of a social security network had the biggest effect on people in their forties. Thus, when the crime prevention design, street CCTV facilities, local government security education, police public peace services are systematically established, the social anxiety of citizens was reduced.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.227-240
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• 2011

New concepts and ideas often result from extensive recombination of existing concepts or ideas. Both researchers and developers build on existing concepts and ideas in published papers or registered patents to develop new theories and technologies that in turn serve as a basis for further development. As the importance of patent increases, so does that of patent analysis. Patent analysis is largely divided into network-based and keyword-based analyses. The former lacks its ability to analyze information technology in details while the letter is unable to identify the relationship between such technologies. In order to overcome the limitations of network-based and keyword-based analyses, this study, which blends those two methods, suggests the keyword network based analysis methodology. In this study, we collected significant technology information in each patent that is related to Light Emitting Diode (LED) through text mining, built a keyword network, and then executed a community network analysis on the collected data. The results of analysis are as the following. First, the patent keyword network indicated very low density and exceptionally high clustering coefficient. Technically, density is obtained by dividing the number of ties in a network by the number of all possible ties. The value ranges between 0 and 1, with higher values indicating denser networks and lower values indicating sparser networks. In real-world networks, the density varies depending on the size of a network; increasing the size of a network generally leads to a decrease in the density. The clustering coefficient is a network-level measure that illustrates the tendency of nodes to cluster in densely interconnected modules. This measure is to show the small-world property in which a network can be highly clustered even though it has a small average distance between nodes in spite of the large number of nodes. Therefore, high density in patent keyword network means that nodes in the patent keyword network are connected sporadically, and high clustering coefficient shows that nodes in the network are closely connected one another. Second, the cumulative degree distribution of the patent keyword network, as any other knowledge network like citation network or collaboration network, followed a clear power-law distribution. A well-known mechanism of this pattern is the preferential attachment mechanism, whereby a node with more links is likely to attain further new links in the evolution of the corresponding network. Unlike general normal distributions, the power-law distribution does not have a representative scale. This means that one cannot pick a representative or an average because there is always a considerable probability of finding much larger values. Networks with power-law distributions are therefore often referred to as scale-free networks. The presence of heavy-tailed scale-free distribution represents the fundamental signature of an emergent collective behavior of the actors who contribute to forming the network. In our context, the more frequently a patent keyword is used, the more often it is selected by researchers and is associated with other keywords or concepts to constitute and convey new patents or technologies. The evidence of power-law distribution implies that the preferential attachment mechanism suggests the origin of heavy-tailed distributions in a wide range of growing patent keyword network. Third, we found that among keywords that flew into a particular field, the vast majority of keywords with new links join existing keywords in the associated community in forming the concept of a new patent. This finding resulted in the same outcomes for both the short-term period (4-year) and long-term period (10-year) analyses. Furthermore, using the keyword combination information that was derived from the methodology suggested by our study enables one to forecast which concepts combine to form a new patent dimension and refer to those concepts when developing a new patent.

• Asian Journal of Turfgrass Science
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• v.23 no.1
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• pp.151-162
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• 2009

When viewing that since the 1990s local governments have tried to build golf courses as a plan to revitalize the attraction of home and abroad tourists and to increase their tax incomes and that big companies are interested in leisure business including golf courses as a future promising business in the 21st century, golf courses seem to continuously increase in the future. On the contrary, noticing that golf courses are not only the main culprit behind the damage of natural environment and environmental pollution but also a target of real estate speculation and that golf makes a sense of incongruity between the classes of a society as a luxury sports, environment activists and local residents raise criticism to golf. Golf in our country shows a special sports phenomenon of which the pros and cons appear continuously. So, it is judged that policy for golf development direction should be set up based on verified scientific data. Thus, the research aims at deriving the location types of golf courses by looking at laws from the period of formation of the initial domestic golf courses to the recent period, grasping their distribution status according to time series and regions, conducting a questionnaire survey regarding location factors for golfers and the workers of golf courses, and dividing golf courses into several types. It is expected that the research will be a fundamental material when a golf course is built later on, contributing to the research of golf courses.

• Horticultural Science & Technology
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• v.32 no.6
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• pp.812-818
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• 2014

Raising seedlings is important for fruit crops and is especially significant for strawberries as it accounts for 80% of their cultivation. However, there are few studies on raising seedlings of strawberries by hydroponics. Since strawberries show clear differences in growth characteristics based on cultivar, it is necessary to develop suitable fertilizer formula, concentration and pH for each cultivar, and also to examine the amount of nutrient feeding appropriate for each medium type. A key to raising seedlings of strawberries by hydroponics is the development of strategies to manage the concentration of nutrient solution. The mother plants of 'Daewang' strawberries were planted on hydroponics benches filled with cocopeat on March 28, 2012. Three nutrient solution treatments were employed during the term of raising seedlings: a type that supplied EC $0.6dS{\cdot}m^{-1}$ nutrient solution for 30 days and only water for 20 days [0.6 (30) + 20]; a type that supplied EC $1.2dS{\cdot}m^{-1}$ nutrient solution for 30 days and only water for 20 days [1.2 (30) + 20]; and a type that supplied EC $1.2dS{\cdot}m^{-1}$ nutrient solution for 50 days [1.2 (50)]. The plants were then planted on hydroponics benches filled with cocopeat on September 20, and managed with EC $0.6-0.8dS{\cdot}m^{-1}$ strawberry nutrient solution developed by Yamazaki. After planting, shoot growth, flowering rate and fruit quality of the first cluster were investigated. The petiole length, leaf length, leaf width and crown diameter showed the highest grown in the [1.2 (50)] treatment, followed by [1.2 (30) + 20], and then [0.6 (30) + 20], indicating that the higher concentration of nutrient solution was preferable for raising seedlings. However, the growth differences among treatments gradually disappeared as growth continued, and the crown diameter especially grew to exhibit almost no difference at all among treatments. The point of flowering came first in [0.6 (30) + 20], followed by [1.2 (30) + 20] and then [1.2 (50)]. The [0.6 (30) + 20] treatment showed much earlier flowering than other treatments, which implies that low-concentration nutrient solution may be beneficial to the flowering of 'Daewang' strawberries while raising seedlings. There was no statistically significant difference among treatments in fruit length, fruit diameter and fruit firmness. Fruit weight in [1.2 (50)] treatment was significantly higher than other treatments. However, soluble solids of fruit was the lowest in [1.2 (50)] treatment. Together, the results of this experiment imply that it is better to supply EC $0.6dS{\cdot}m^{-1}$ solution for 30 days and then supply only water for 20 days to adequately manage concentration of nutrient solutions during the period of raising seedlings of strawberries by hydroponics.

• Korean Journal of Environmental Biology
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• v.32 no.4
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• pp.286-296
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• 2014

In this study, we investigated the macrobenthic community structure and spatiotemporal variations in Uljin Marine Ranching area, East Sea of Korea. Macrobenthos were collected using a modified van Veen grab sampler from April to September 2013. Total number of species sampled was 345 and mean density was 5,797 ind. $m^{-2}$, both of which were dominated by the polychaetes. The most dominant species were Spiophanes bombyx (53.64%), followed by Magelona sp.1 (6.96%), Cadella semitorta (2.73%), Lumbrineris longifolia (2.16%) and Alvenius ojianus (2.08%). Cluster analysis and nMDS ordination analysis based on the Bray-Curtis similarity identified 2 station groups. The group 1 (station 2, 3, 5, 6, 8 and 9) was characterized by high abundance of the polychaetes Magelona sp.1, Lumbrineris longifolia, Scoloplos armiger, Praxillella affinis, Maldane cristata and the bivalve Alvenius ojianus, with fine sediment above 30m water depth. On the other hand, the group 2 (station 1, 4, 7 and 10) was numerically dominated by the polychaete Lumbrineriopsis sp. and the bivalve Cadella semitorta, with coarse sediment below 5m water depth. Collectively, the macrobenthic community structure showed a distinct spatial trend, which seemed to be related to the water depth and sediment composition.

• Land and Housing Review
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• v.4 no.1
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• pp.77-87
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• 2013

About 1,800 villages have released from Greenbelt since Greenbelt-reform-policy for readjustment of the area was promoted after 1997. Even though the government intended to attract planned development & improvement of these lifted villages through District Unit Plan and designating the lifted area as low-rise and low-density zoning considering the characteristics of the Greenbelt region, there are still many problems to be solved: a lack of funds, insufficient capability for self-improvement and unexecuted SOCs in long-term etc. It seems that these problems are caused by focusing on the lifting areas itself instead of researching deeply the condition and characteristics of the villages and searching proper direction/plans of improvement before lifting Greenbelt In addition, the existing plan of village improvement and management was not considering physical and spacial characteristics of the areas, social and economic situation of residents and relationship between the villages and surrounding cities, though these conditions are different among each villages, and the related regulations are applied uniformly across all the villages and those have been causing many civil appeals and environmental problems. In these respects, this study aims to consider the problems of the lifted villages using the existing researches on them and to make typology by characteristics-data of the villages and to establish improvement strategies of each types. In this study, the villages were classified into 5 types as a result of cluster analysis on 424 villages among all 1,800 through variables of locational potentiality : location, accessibility, size and form of village, condition of regulations etc. According to function of the villages, they were divided into 4 types: urban-type, rural-type, industrial-type and neighborhood-centered-type. This study also drew 4 improvement-strategy-types by combination of locational potentiality and village-function : type of improving life-environment, type of improving production-infra, type of inducing-planned-improvement and type of constructing center-of living-circle. Finally, this study suggested the directions of the each 4 types to desirable improvement and management which could be used to make and complement plans for village improvement.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.93-107
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• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

• 한국노년학
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• v.38 no.4
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• pp.1057-1081
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• 2018

This study analyzed the case of elderly care cluster in Gwangjin-gu to explore the possibilities of social economy as a provider of community-based social services. Community-based means the approach by which community organizations build a voluntary and collaborative network to enhance collective problem-solving abilities. Therefore, it is very likely that the social economy that emphasizes people, labor, community, and democratic principles can contribute to community-based social services. This study analyzed social economic network by using four characteristics of social economy suggested by OECD community economy and employment program as an analysis framework. The results of this study are as follows: First, it is found that social economy would hardly supply community-based social services through network cooperation because of a large variation in community identity, investment to new product, and labor protection. Second, community users are not the consumers of the social economy and the products of the social economy stay in market products only for the organizations in social economy. In order to create good services that meet the needs of residents, community development approaches are required at the same time. The importance of community space where local residents and social economy meet is derived. Third, public support such as purchasing support has weakened the ecosystem of social economy by making the distinction between public economy and social economy more obscure. On the other hand, public investment in community infrastructure is an indirect aid to social economy to communicate with residents and to promote good supply and consumption. In the end, community-based social services need a platform where the social economy and the people meet. This type of public investment can create the ecosystem of the social economy.

• Korean Journal of Environment and Ecology
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• v.35 no.2
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• pp.135-153
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• 2021

The demilitarized zone (DMZ) is a border barrier with 248 kilometers in length and about 4 kilometers in width crossing east to west to divide the Korean Peninsula about in half. The boundary at 2 kilometers to the south is called the southern limit line. The DMZ has formed a unique ecosystem through a natural ecological succession after the Armistice Agreement and has high conservation value. However, the use of facilities for the military operation and the unchecked weeding often damage the areas in the vicinities of the southern limit line's iron-railing. This study aimed to prepare basic data for the restoration of damaged barren vegetation. As a result of classifying vegetation communities based on indicator species, 10 communities were identified as follows: Duchesnea indica Community, Hosta longipes Community, Sedum kamtschaticum-Sedum sarmentosum Community, Potentilla anemonefolia Community, Potentilla fragarioides var. major Community, Prunella vulgaris var. lilacina Community, Dendranthema zawadskii var. latilobum-Carex lanceolata Community, Dendranthema zawadskii Community, Plantago asiatica-Trifolium repens Community, and Ixeris stolonifera-Kummerowia striata Community. Highly adaptable species can characterize vegetation in barren areas to environment disturbances because artificial disturbances such as soil erosion, soil compaction, topography change, and forest fires caused by military activities frequently occur in the barren areas within the southern limit line. Most of the dominant species in the communities are composed of plants that are commonly found in the roads, roadsides, bare soil, damaged areas, and grasslands throughout South Korea. Currently, the vegetation in barren areas in the vicinities of the DMZ is in the early ecological succession form that develops from bare soil to herbaceous vegetation. Since dominant species distributed in barren land can grow naturally without special maintenance and management, the data can be useful for future restoration material development or species selection.

• 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.