• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.127-139
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• 2013

With an advent of recent knowledge-based society, the interest in intellectual property has increased. Firms have tired to result in productive outcomes through continuous innovative activity. Especially, ICT firms which lead high-tech industry have tried to manage intellectual property more systematically. Firm's interest in the patent has increased in order to manage the innovative activity and Knowledge property. The patent involves not only simple information but also important values as information of technology, management and right. Moreover, as the patent has the detailed contents regarding technology development activity, it is regarded as valuable data. The patent which reflects technology spread and research outcomes and business performances are closely interrelated as the patent is considered as a significant the level of firm's innovation. As the patent information which represents companies' intellectual capital is accumulated continuously, it has become possible to do quantitative analysis. The advantages of patent in the related industry information and it's standardize information can be easily obtained. Through the patent, the flow of knowledge can be determined. The patent information can analyze in various levels from patent to nation. The patent information is used to analyze technical status and the effects on performance. The patent which has a high frequency of citation refers to having high technological values. Analyzing the patent information contains both citation index analysis using the number of citation and network analysis using citation relationship. Network analysis can provide the information on the flows of knowledge and technological changes, and it can show future research direction. Studies using the patent citation analysis vary academically and practically. For the citation index research, studies to analyze influential big patent has been conducted, and for the network analysis research, studies to find out the flows of technology in a certain industry has been conducted. Social network analysis is applied not only in the sociology, but also in a field of management consulting and company's knowledge management. Research of how the company's network position has an impact on business performances has been conducted from various aspects in a field of network analysis. Social network analysis can be based on the visual forms. Network indicators are available through the quantitative analysis. Social network analysis is used when analyzing outcomes in terms of the position of network. Social network analysis focuses largely on centrality and structural holes. Centrality indicates that actors having central positions among other actors have an advantage to exert stronger influence for exchange relationship. Degree centrality, betweenness centrality and closeness centrality are used for centrality analysis. Structural holes refer to an empty place in social structure and are defined as efficiency and constraints. This study stresses and analyzes firms' network in terms of the patent and how network characteristics have an influence on business performances. For the purpose of doing this, seventy-four ICT companies listed in S&P500 are chosen for the sample. UCINET6 is used to analyze the network structural characteristics such as outdegree centrality, betweenness centrality and efficiency. Then, regression analysis test is conducted to find out how these network characteristics are related to business performance. It is found that each network index has significant impacts on net income, i.e. business performance. However, it is found that efficiency is negatively associated with business performance. As the efficiency increases, net income decreases and it has a negative impact on business performances. Furthermore, it is shown that betweenness centrality solely has statistically significance for the multiple regression analysis with three network indexes. The patent citation network analysis shows the flows of knowledge between firms, and it can be expected to contribute to company's management strategies by analyzing company's network structural positions.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.177-193
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• 2014

Over the past decade, there has been a rapid diffusion of electronic commerce and a rising number of interconnected networks, resulting in an escalation of security threats and privacy concerns. Electronic commerce has a built-in trade-off between the necessity of providing at least some personal information to consummate an online transaction, and the risk of negative consequences from providing such information. More recently, the frequent disclosure of private information has raised concerns about privacy and its impacts. This has motivated researchers in various fields to explore information privacy issues to address these concerns. Accordingly, the necessity for information privacy policies and technologies for collecting and storing data, and information privacy research in various fields such as medicine, computer science, business, and statistics has increased. The occurrence of various information security accidents have made finding experts in the information security field an important issue. Objective measures for finding such experts are required, as it is currently rather subjective. Based on social network analysis, this paper focused on a framework to evaluate the process of finding experts in the information security field. We collected data from the National Discovery for Science Leaders (NDSL) database, initially collecting about 2000 papers covering the period between 2005 and 2013. Outliers and the data of irrelevant papers were dropped, leaving 784 papers to test the suggested hypotheses. The co-authorship network data for co-author relationship, publisher, affiliation, and so on were analyzed using social network measures including centrality and structural hole. The results of our model estimation are as follows. With the exception of Hypothesis 3, which deals with the relationship between eigenvector centrality and performance, all of our hypotheses were supported. In line with our hypothesis, degree centrality (H1) was supported with its positive influence on the researchers' publishing performance (p<0.001). This finding indicates that as the degree of cooperation increased, the more the publishing performance of researchers increased. In addition, closeness centrality (H2) was also positively associated with researchers' publishing performance (p<0.001), suggesting that, as the efficiency of information acquisition increased, the more the researchers' publishing performance increased. This paper identified the difference in publishing performance among researchers. The analysis can be used to identify core experts and evaluate their performance in the information privacy research field. The co-authorship network for information privacy can aid in understanding the deep relationships among researchers. In addition, extracting characteristics of publishers and affiliations, this paper suggested an understanding of the social network measures and their potential for finding experts in the information privacy field. Social concerns about securing the objectivity of experts have increased, because experts in the information privacy field frequently participate in political consultation, and business education support and evaluation. In terms of practical implications, this research suggests an objective framework for experts in the information privacy field, and is useful for people who are in charge of managing research human resources. This study has some limitations, providing opportunities and suggestions for future research. Presenting the difference in information diffusion according to media and proximity presents difficulties for the generalization of the theory due to the small sample size. Therefore, further studies could consider an increased sample size and media diversity, the difference in information diffusion according to the media type, and information proximity could be explored in more detail. Moreover, previous network research has commonly observed a causal relationship between the independent and dependent variable (Kadushin, 2012). In this study, degree centrality as an independent variable might have causal relationship with performance as a dependent variable. However, in the case of network analysis research, network indices could be computed after the network relationship is created. An annual analysis could help mitigate this limitation.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.1
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• pp.108-119
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• 2015

Recently, the ways in which individual communities own and manage parks have been both discussed and realized in America and England. Some benefits of these asset transfers are that local governments can reduce the financial cost of management as well as improve the service of the parks. In addition, communities can develop these parks as unique assets. Ultimately, this is a new understanding of parks as community commons. This study examines the policy of park asset transfers to communities in England. These transfers, which involve reallocating land and building management and/or ownership from the public sector to a community group, are part of a policy agenda known as "Big Society", which aims to create a "small government" within a "big society". The agenda is pursued by both the English Conservative and Unionist Party governments. Eight case studies of community park asset transfers in England were examined in this study, under three categories-transfer process, partnership among stakeholders, and financial structure-and synthesized along three issues-financial contribution, level of public transparency, and closeness of the relationship between park and community. In some cases, new community groups were created specifically to receive park assets, while in other communities, existing groups became the park trustees. For most parks, community groups raise park maintenance funding through diverse methods; however, these groups are often not entirely financially independent from local government. Thus, many park trustees have already created, or are planning to create, other assets from which parks can benefit. Second, some efforts for public transparency include trusts that are registered as charities, of which their public nature is admitted officially. These trusts resolve important decisions through boards of trustees, in an effort to promote income-generating business while not excluding users. Ultimately, a close relationship between park and community empowers the community to participate in managing and maintaining the park; in turn, the park's capacities are improved. Current struggles include the many limits involved in communities accepting ownership and management of a park, and a lack of local government experience regarding public-private management and maintenance of a public asset. This study, however, details interesting policy implications for Korean community involvement as well as diverse financial methods to facilitate park management.

• Journal of Applied Biological Chemistry
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• v.62 no.3
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• pp.287-292
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• 2019

Pseudomonas tolaasii causes brown blotch disease on the oyster mushroom (Pleurotus ostreatus). Various pathogenic strains of P. tolaasii were isolated and divided into three subtypes, $P1{\alpha}$, $P1{\beta}$, and $P1{\gamma}$. For phage therapy, bacteriophages against to these subtype strains were applied to mushroom cultivation and very successful to prevent from the disease. In this study, bacteriophages were isolated against the representative strains of subtype pathogens and their polyclonal antibodies were synthesized to investigate structural relationship among capsid proteins of phages. Phage preparations over $10^{10}pfu/mL$ were injected to rabbit thigh muscle and polyclonal antibodies were obtained after three times of boost injection. Titers of the antibodies obtained were over $2{\times}10^7Ab/mL$ for the phage ${\phi}6264$, $1{\times}10^6Ab/mL$ for the phage ${\phi}HK2$, and $1{\times}10^7Ab/mL$ for the phage ${\phi}HK19$ and phage ${\phi}HK23$. High specific activities were observed between antibodies and the corresponding bacteriophages. Some cross-reactivities between the antibodies and non-corresponding bacteriophages were also measured. Antibody $Ab{\phi}6264$ inactivated all phages of $P1{\alpha}$ subtype and only phage ${\phi}HK16$ among $P1{\beta}$ subtype phages. Antibody $Ab{\phi}HK23$ of $P1{\gamma}$ subtype neutralized all phages of $P1{\beta}$ subtype as well as the phage ${\phi}HK23$, showing the widest phage-inactivation range. When the structural-similarity studies of phages were investigated by using phage antibodies, closeness obtained by phylogenetic analysis of 16S rRNA genes of pathogenic strains were quite different from that of polyclonal antibody-specific structural similarity of phage capsid proteins. In conclusion, there is weak correlation between the host strain specificity of bacteriophage and its capsid structural similarity measured by phage antibodies.

• Korean Journal of Culture and Social Issue
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• v.10 no.2
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• pp.103-137
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• 2004

This study examines the basis of trust in relationships by adolescents and their parents using the indigenous psychological approach. Using the indigenous methodology, adolescents were asked the reasons why they trusted their mother, father, friends, and teachers. Parents were asked why they trusted their children, spouse and their children's teachers. A total of 1,737 participants completed an open-ended survey: 579 adolescents (274 middle school and 305 high school students) and their parents (579 fathers) and (579 mothers). The results indicate that adolescents trust their parents because of their sacrifice, followed by consanguinity (i.e., blood relationship), respect, their trust in me, dependability, and their advice and counseling. The reasons why adolescents trust their teachers is because of the academic guidance they provide, unconditional trust of teachers, their concern and care, respect for teachers, advice and counseling they provide, they are like parents, and because of their sacrifice for the students. The reasons for trusting their friends are as follows: Dependability, closeness, unconditional trust of friends, their understanding of me, and their emotional support. The reasons why parents trust their children are: Children's sincerity, honesty, consanguinity, parents' expectation and communication with the children, children's obedience, and since they are diligent in their schoolwork. The reasons for trusting one's spouse are reported to be sincerity, their sacrifice for the family, honesty, unconditional trust of a spouse, and because of mutual support. The reasons why parents trust their children's teachers are reported as follows: Unconditional trust of teachers, their sacrifice for the students, and their sincerity. There were no significant differences across the type of school and academic grades in terms of trust of parents. However, middle school students are more likely to trust their teachers, and high school students are more likely trust their friends. The male students rather than female students and those students with higher academic grades are more likely to trust their parents, friends, and teachers. For parents, there were no significant differences across age, sex, and educational status concerning the trust of their children, spouse, and children's teachers. There was a positive correlations between parents' trust of their spouse and children and their children's trust of their parents. There was also a positive correlations of mothers' trust of children's teachers and the children's trust of their teachers.

• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.4
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• pp.86-93
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• 2009

This study analyzes the systematic visual images and factors in and outside of the main courtyard in Byungsan-seowon. The results are as follows; In terms of space distribution, Ip-kyo-dang is located at an elevation of 85m and the distance to Byung-san is 365m. Byung-san with the mean gradient over $50^{\circ}$ looked so stiff, and the east side of that cliff is higher than west. In terms of the angle of elevation relationship between Man-dae-ru and Byung-san draw 10.5 degree and it suits with human scale. The D/H ratio of 1:3 makes the given place very spacious but the linear stiff shape of Byung-san may cause the feeling of closeness. The results of the visual image analysis of the main yard facing Byung-san is very positive with a score of 1.70 in openness, 1.78 in wideness, 1.96 in beauty, 1.96 in harmony for the spacious arrangement which overall, makes the seowon beautiful with many open spaces. There are 4 main implicated factors analyzed which are uniqueness, aesthetic, openness and nature. Out of the total variables, these factors' descriptive ability is 55.90% and the remaining 44.10% is error and peculiarities variables. The factor which contributed most to Byungsan-seowon's main yard's visual preference was the 'aesthetic' with B-values of 0.661 and 0.455 in the nature category.

• Journal of Practical Agriculture & Fisheries Research
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• v.22 no.2
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• pp.99-114
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• 2020

In this study we examined the topic analysis and correlation analysis by text mining from the self introduction letter of freshman at Korea National College of Agriculture and Fisheries(KNCAF) in 2020. The analysis items of the 3rd question were and the 4th question were the motivation for applying to college, the academic plan and the career plan. The text mining to the 3rd question showed that the frequency of 'friends' was overwhelmingly high, followed by keywords such as 'thought', 'time', 'opinion', 'activity', and 'club'. In the 4th question, keyword frequency such as 'thought', 'agriculture', 'KNCAF', 'farm', 'father' was high. The result of association rules analysis for each question showed that the relationship with the highest support level, which means the frequency and importance of the rule, was the {friend} <=> {thought}, {thought} <=> {KNCAF}. The confidence level of a correlation between keywords was the highest in the rules of {teacher}=>{friend}, {agriculture, KNCAF}=>{thought}. Also the lift level that indicates the closeness of two words was the highest in the rules of {friend} <=> {teacher}, {knowledge} <=> {professional}. These keywords are found to play a very important roles in analyzing betweenness centrality and analyzing degree centrality between keywords. The results of frequency analysis and association analysis were visualized with word cloud and correlation graphs to make it easier to understand all the results.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.101-123
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• 2013

Recently due to the advancements of science and information technology, the socio-economic business areas are changing from the industrial economy to a knowledge economy. Furthermore, companies need to do creation of new value through continuous innovation, development of core competencies and technologies, and technological convergence. Therefore, the identification of major trends in technology research and the interdisciplinary knowledge-based prediction of integrated technologies and promising techniques are required for firms to gain and sustain competitive advantage and future growth engines. The aim of this paper is to understand the recent research trend in management of technology (MOT) and to foresee promising technologies with deep knowledge for both technology and business. Furthermore, this study intends to give a clear way to find new technical value for constant innovation and to capture core technology and technology convergence. Bibliometrics is a metrical analysis to understand literature's characteristics. Traditional bibliometrics has its limitation not to understand relationship between trend in technology management and technology itself, since it focuses on quantitative indices such as quotation frequency. To overcome this issue, the network focused bibliometrics has been used instead of traditional one. The network focused bibliometrics mainly uses "Co-citation" and "Co-word" analysis. In this study, a keywords network analysis, one of social network analysis, is performed to analyze recent research trend in MOT. For the analysis, we collected keywords from research papers published in international journals related MOT between 2002 and 2011, constructed a keyword network, and then conducted the keywords network analysis. Over the past 40 years, the studies in social network have attempted to understand the social interactions through the network structure represented by connection patterns. In other words, social network analysis has been used to explain the structures and behaviors of various social formations such as teams, organizations, and industries. In general, the social network analysis uses data as a form of matrix. In our context, the matrix depicts the relations between rows as papers and columns as keywords, where the relations are represented as binary. Even though there are no direct relations between papers who have been published, the relations between papers can be derived artificially as in the paper-keyword matrix, in which each cell has 1 for including or 0 for not including. For example, a keywords network can be configured in a way to connect the papers which have included one or more same keywords. After constructing a keywords network, we analyzed frequency of keywords, structural characteristics of keywords network, preferential attachment and growth of new keywords, component, and centrality. The results of this study are as follows. First, a paper has 4.574 keywords on the average. 90% of keywords were used three or less times for past 10 years and about 75% of keywords appeared only one time. Second, the keyword network in MOT is a small world network and a scale free network in which a small number of keywords have a tendency to become a monopoly. Third, the gap between the rich (with more edges) and the poor (with fewer edges) in the network is getting bigger as time goes on. Fourth, most of newly entering keywords become poor nodes within about 2~3 years. Finally, keywords with high degree centrality, betweenness centrality, and closeness centrality are "Innovation," "R&D," "Patent," "Forecast," "Technology transfer," "Technology," and "SME". The results of analysis will help researchers identify major trends in MOT research and then seek a new research topic. We hope that the result of the analysis will help researchers of MOT identify major trends in technology research, and utilize as useful reference information when they seek consilience with other fields of study and select a new research topic.