• Journal of Communications and Networks
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• v.3 no.4
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• pp.342-350
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• 2001

The Internet routing instability, or the rapid fluctuation of network reachability information, is an important problem currently facing the Internet engineering community. High levels of network instability can lead to packet loss, increased network latency, and delayed routing convergence. At the extreme, high levels of routing instability can lead to the loss of internal connectivity in wide-area networks. In this paper, we investigate the variation of domain degree and domain count of the inter-domain network over time by using linear regression model in order to analyze the topology variation of inter-domain network. We Also propose an efficient policy management model to reduce the instability in the inter-domain routing system. The proposed model can be used to identify whether a routing policy is adequate to reduce convergence time that is required to return to a normal state when BGP routing instability happens. Experimental analysis shows that the proposed model can be used to set up routing policy in domains for the purpose of minimizing the effects and the propagation of BGP routing instability.

• Journal of Contemporary Eastern Asia
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• v.15 no.1
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• pp.41-63
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• 2016

Energy policy is known to have higher path dependency among policy fields (Kuper and van Soest, 2003; OECD, 2012; Kikkawa, 2013) and is a critical component of the infrastructure development undertaken in the early stages of nation building. Actor roles, such as those played by interest groups, are firmly formed, making it unlikely that institutional change can be implemented. In resource-challenged Japan, energy policy is an especially critical policy area for the Japanese government. In comparing energy policy making in Japan and Germany, Japan’s policy community is relatively firm (Hartwig et al., 2015), and it is improbable that institutional change can occur. The Japanese government’s approach to energy policy has shifted incrementally in the past half century, with the most recent being the 2012 implementation of the “Feed-In Tariff Law” (Act on Special Measures Concerning Procurement of Renewable Electric Energy by Operators of Electric Utilities), which encourages new investment in renewable electricity generation and promotes the use of renewable energy. Yet, who were the actors involved and the factors that influenced the establishment of this new law? This study attempts to assess the factors associated with implementing the law as well as the roles of the relevant major actors. In answering this question, we focus on identifying the policy networks among government, political parties, and interest groups, which suggests that success in persuading key economic groups could be a factor in promoting the law. Our data is based on the “Global Environmental Policy Network Survey 2012-2013 (GEPON2)” which was conducted immediately after the March 11, 2011 Great East Japan Earthquake with respondents including political parties, the government, interest groups, and civil society organizations. Our results suggest that the Feed in Tariff (FIT) Law’s network structure is similar to the information network and support network, and that the actors at the center of the network support the FIT Law. The strength of our research lays in our focus on political networks and their contributing mechanism to the law’s implementation through analysis of the political process. From an academic perspective, identifying the key actors and factors may be significant in explaining institutional change in policy areas with high path dependency. Close examination of this issue also has implications for a society that can promote renewable and sustainable energy resources.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.8B
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• pp.525-534
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• 2005

This paper proposes the architecture and the methods of security network management for auto-configuration of security systems by extending the existing policy-based network management architecture. The architecture and the methods proposed in this paper enable a security management sewer to automatically decide the best-suited security policy to apply to a security system and the most effective and efficient security system to perform security policy rule, based on the role and capability information of security systems and the role and time information of security policy. For integrated control of network system and security system, this paper also proposes SNMP protocol based security network topology map generator. To show the excellence of the proposed architecture and methods, we simulate and evaluate the automatic response against attacks.

• Journal of Korean Society of Transportation
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• v.29 no.1
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• pp.81-93
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• 2011

This research deals with the multi-modal continuous network design problem to resolve the transportation policy problems for constructing and operating transportation facilities with considering the mutual decision-making process between transportation operator and user in the multi-modal network. Particularly, in the consideration of changes in travel pattern between transport modes due to the changes in transportation policy, road network for passenger car and transit network for public transportation are considered together. In the development of network design model, more rational Stackelberg equilibrium(cooperative game) rather than more general Nash equilibrium(non-cooperative game) approach is used and sensitivity analysis considering transport mode is used. A multi-modal continuous network design model in this study is developed for the arbitrary continuous network design parameters(${\epsilon},\hat{\epsilon},p$) of transportation policy decisions. As examples of application and evaluation for these design parameters, the developed model is applied to calculate 1)the optimal capacity of road link in the road transport policy, 2)the optimal frequency of transit line in public transport policy and 3)the optimal modal split in transport modal share policy.

• Journal of Digital Convergence
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• v.14 no.9
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• pp.301-308
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• 2016

Writing high-quality papers and publishing them at prestigious academic journals would be something that every scholar strives for. This study made a network with nine academic journals in South Korea in the field of public administration and public policy and analyzed the influence of academic journals through social network analysis. Using centrality measures, such as degree centrality, beta centrality, and eigenvector centrality, this study found that Korean Public Administration Review has the highest influence on the journal network, followed by Korean Public Studies Review. However, different choice of centrality measure led to different ranking of journals in terms of their influence.

• Asian Journal of Innovation and Policy
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• v.9 no.3
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• pp.339-359
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• 2020

The policy change in the Data 3 Act is one of the issues that should be noted at a time when non-face-to-face business strategies become important after COVID-19. The Data 3 Act was implemented in South Korea on August 5, 2020, calling 'Big Data 3 Act' and 'Data Economy 3 Act,' and so personal information that was not able to identify a particular individual could be utilized without the consent of the individual. With the implementation of the Data 3 Act, it is possible to establish a fair economic ecosystem by ensuring fair access to data and various uses. In this paper, the law on the protection of personal information, which is the core of the Data 3 Act, was compared around Korea, the European Union and the United States, and the implications were derived through network analysis of keywords.

• Journal of the Korea Society of Computer and Information
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• v.22 no.10
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• pp.73-81
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• 2017

In this paper, we propose an analysis framework to capture the trends of information security incidents and evaluate the security policy based on the incident analysis. We build a big data from news media collecting security incidents news and policy news, identify key trends in information security from this, and present an analytical method for evaluating policies from the point of view of incidents. In more specific, we propose a network-based analysis model that allows us to easily identify the trends of information security incidents and policy at a glance, and a cosine similarity measure to find important events from incidents and policy announcements.

• Asian Journal of Innovation and Policy
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• v.9 no.2
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• pp.145-163
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• 2020

The COVID-19 is a pandemic that affects all facets of our life and will change many patterns in science technology and innovation. A qualitative study was conducted using Focus Group Interview involving ten industry-academia-research experts with the objective of identifying changes in Korea's national innovation system and science & technology policy after the COVID-19. Eight questions were designed, based on the major components of the national innovation system, such as companies, universities, and research institutes, to discuss the changes in the national innovation system and science & technology policy. Also, keyword analysis and cluster analysis were performed using the network analysis program VOSviewer. It is predicted that, in the wake of the COVID-19, Korea's national innovation system will shift to a new paradigm that is more decentralized, responsive, and autonomous. Furthermore, several policy agendas that can turn these changes into positive momentum of change in science & technology policy are presented.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.2
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• pp.138-150
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• 2016

This study aims to analyze the structure and characteristics of the domestic online game industry using network analysis. In particular, two-mode network analysis is employed to measure the network structure, centrality, and cluster for two types of online game platforms, online games and mobile games, from 1996 to 2014. We also conduct a dynamic analysis to capture the structural changes in the ecosystem by internal and external environmental changes before and after turning point for each online game platform. It is revealed that the online game econsystem has the higher number of clusters and higher concentration ratio than those of mobile game ecosystem. In dynamic analysis, both platforms exhibit similar trends over time with the increasing number of clusters, enlargement of largest cluster's size, and decreasing concentration ratio. This study is expected to provide fruitful implications for strategic decision making of online game companies and policy making for the online game industry.

• Journal of the Korea Society of Computer and Information
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• v.23 no.1
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• pp.9-15
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• 2018

Policy polls, which investigate the degree of support that the policy has for policy implementation, play an important role in making decisions. As the number of Internet users increases, the public is actively commenting on their policy news stories. Current policy polls tend to rely heavily on phone and offline surveys. Collecting and analyzing policy articles is useful in policy surveys. In this study, we propose a method of analyzing comments using deep learning technology showing outstanding performance in various fields. In particular, we designed various models based on the recurrent neural network (RNN) which is suitable for sequential data and compared the performance with the support vector machine (SVM), which is a traditional machine learning model. For all test sets, the SVM model show an accuracy of 0.73 and the RNN model have an accuracy of 0.83.