• Korean System Dynamics Review
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• v.12 no.2
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• pp.69-94
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• 2011

Daejeon, encompassing Daedeok Science Town and Daedeok Innopolis, possesses the advantage of portraying relatively higher regional innovation capacity and facilitating network formation among regional professional research organizations. Applying the Social Network Analysis(SNA) techniques, this paper focuses on divulging structural and spatial characteristics of the Daejeon Information and Communication(ICT) industry network, analyzing co-research projects implemented by the Daejeon-based universities. For the analytical tool, it depends on NETMINER 3.0. Furthermore, based on the Systems Thinking approaches, this study suggests a couple of policy implications. Judging from the Korea Standard Industrial Classification principles, the existing ICT industry is subdivided into 11 sub-industries. The highest degree centralization value comes from the Mobile Communication sub-industry(188.668%), indicating that Mobile Communication sub-industry exerts the most significant impact on the regional innovation networking in Daejeon. Among various stakeholders, Korea Advanced Institute of Science and Technology(KAIST) records the top ranking in most categories, conspicuously leading the institute-industry linkage. In terms of the ICT spatial distribution, the intra-regional cooperation examples present the strongest linkage values, followed by Daejeon-the Capital Region ones. Finally, as well shown in a series of causal loop analyses, this study recommends that Daejeon should put top policy priority in strengthening the internal ICT network within Daejeon proper. Here, Daejeon should keep in mind the fact that there exist reinforcing loops between Daejeon's attractiveness and the entering of new ICT firms.

• Journal of the Economic Geographical Society of Korea
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• v.8 no.1
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• pp.31-50
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• 2005

The purpose of this study is to analyse the role of the inter-regional knowledge network in the knowledge based economic development of regions, using regional data collected over the IMF financial crisis between 1996 and 2001. In particular, the major questions about the inter-regional knowledge network in terms of regional innovation are as follows. First, how can be distinguished the inter-regional knowledge networks among the regions? Secondly, what is the relationship between the real object economy and the inter-regional knowledge network? To answer rho questions listed above, the social network analysis is used to examine the association between the intra-regional knowledge linkage structure and the change of the real object economy. For the empirical analyses, regional labour data for 16 Metropolitan Areas(Si) and Provinces(Do) from 1996 to 2001 are used. The findings of the study suggest that there is a significant positive relationship between the concentration of the inter-regional knowledge linkage and a rate of economic growth of the real object economy and that there is a negative correlation between the density and the standard deviation of the inter-regional knowledge linkage and the rate.

• Asia-Pacific Journal of Business
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• v.10 no.4
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• pp.49-63
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• 2019

The export regulation of semiconductor core materials, which began with the recent revision of the export management regulations of Japan, raises the need for a new cooperation network. A hierarchical management network that was effective in the fast-follower system requires organic cooperation between the public sector and industry through a multilateral network that emphasizes horizontal co-operation among innovation actors. This study focused on the relational capital that exists among members of a business association such as an association that has been relatively marginalized from previous studies. In addition, this study aimed to analyze the effect of network activity characteristics such as industry-university linkage and informal exchange on technological innovation. Through this, I would like to draw implications for enhancing the effectiveness of the government's R & D support and innovation performance of R & D companies. Based on the results of the SMEs R & D survey, this study found that relational capital, informal exchange had a positive effect on technological innovation performance. However, if the relational capital exceeds a certain level, it is analyzed that there is a negative effect due to group think and lock-in effect. This means that informal exchange channels should be expanded for innovation and enhancement, and relational capital should be managed in consideration of the negative effects that may occur when certain levels are exceeded.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.79-89
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• 1999

A counting rule that allows an element to be linked to more than one enumeration unit is called a multiplicity counting rule. Sample designs that use multiplicity counting rules are called network samples. Defining a network to be a set of observation units with a given linkage pattern, a network may be linked with more than one selection unit, and a single selection unit may be linked with more than one network. This paper considers allocation for multivariate stratified random sampling with multiplicity.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.429-433
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• 2007

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and ststor resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.2
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• pp.293-300
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• 2011

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and stator resistance and adaptive fuzzy learning contrroller(AFLC) for speed control in IPMSM Drives. AFLC is chaged fuzzy rule base by rule base modifier for robust control of IPMSM. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator and AFLC is confirmed by comparing to conventional algorithm.

• Journal of the Korean Geographical Society
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• v.50 no.2
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• pp.203-216
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• 2015

This paper examined the changes of urban system through the network and the flow pattern reflected in daily movement in Korea. Because daily movement reflects trip pattern, urban system formed by inter-city linkages can be recognized in terms of living sphere. While population movements between cities have the number of linkage systems of city network and the number of traffic regions composed of the origin and destination has increased respectively. Nevertheless, spatial extent of Capital region and Busan region has been expanded. In Gangwon-do in which Seoul-oriented high-speed transportation network has developed, separation of living sphere between Yeongdong area and the Soyanggang cultural region formed around Chuncheon was intensified. Living sphere that includes Daejeon and the surrounding cities has been expanded to the southern Gyeonggi-do. The existing living sphere formed in Jeollanam-do was fragmented into the east and west around Mokpo and Suncheon due to the weakened centrality of Gwangju. Living spheres formed by spatial interaction were consistent with regional administrative boundary. Considering the increased interaction between Seoul and its surrounding cities, the development of global city-region centered on Seoul is expected.

• Journal of the Economic Geographical Society of Korea
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• v.8 no.2
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• pp.217-236
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• 2005

This paper aims to analysis the production linkage relationships between large firm and its subcontracting firms, especially focus on the spatial network and collaboration network. For the purpose of it, the division of semiconductor in Samsung Electronics and its most important subcontracting firms are picked up for the case study. The empirical study show that the location distribution pattern of Samsung Electronic's subcontracting firms is concentrated very highly on the Kyeong-Ki Province and Chung-Nam Province in Korea, which is the location sites of Samsung Electronic's key plants as well as the best environment for business in Korea. And the major subcontracting firms seems to be in the hierarchic and vertical relationship with Samsung Electronics rather than horizontal and good collaboration network in this case.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.5
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• pp.332-337
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• 2004

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and stator resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying. parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.207-209
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• 2006

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and ststor resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.