• International Journal of Contents
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• v.5 no.3
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• pp.57-64
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• 2009

Korea has relied on top down development method, in which companies, research and education institutions move into the industrial complexes established by the government. However, to improve local competitiveness, the paradigm is shifting from the government initiated industrial complex to the clusters based on the cooperative network of the region. Representative case is 'Samcheok-si Fire & Emergency industry cluster construction project' that begun in 2007. AHP technique analysis results on first-stage showed that priority was on policy and network elements, and the results of second-stage analysis show that priority was on Policy incentives to internationalize the cluster and strengthen link,. Cluster branding, Sharing of organizational culture to cope with changes in environment, Creation of group learning culture. The subject of this research is limited to Samcheok-si's the Fire and Emergency Industry cluster formation project. Therefore, the research area and standard should be expanded to increase generality in further researches.

• Journal of Communications and Networks
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• v.17 no.1
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• pp.47-57
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• 2015

With the ever growing demand of data applications, the joint macro-relay networks are emerging as a promising heterogeneous deployment to provide coverage extension and throughput enhancement. However, the current cellular networks are usually designed to be performance-oriented without enough considerations on the traffic variation, causing substantial energy waste. In this paper, we consider a joint macro-relay network with densely deployed relay stations (RSs), where the traffic load varies in both time and spatial domains. An energy-efficient scheme is proposed to dynamically adjust the RS working modes (active or sleeping) according to the traffic variations, which is called traffic-aware relay sleep control (TRSC). To evaluate the performance of TRSC,we establish an analytical model using stochastic geometry theory and derive explicit expressions of coverage probability, mean achievable rate and network energy efficiency (NEE). Simulation results demonstrate that the derived analytic results are reasonable and the proposed TRSC can significantly improve the NEE when the network traffic varies dynamically.

• ETRI Journal
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• v.42 no.5
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• pp.712-720
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• 2020

Recently, to make the best use of limited and precious spectrum resources, spectrum sharing between satellite and cellular networks has received much interest. In this study, we mathematically analyze the success probability of a fixed (satellite) earth station (FES) based on a stochastic geometry framework. Both the FES and base stations (BSs) are assumed to be equipped with a directional antenna, and the location and the number of BSs are modeled based on the Poisson point process. Furthermore, an exclusion zone is considered, in which the BSs are prohibited from locating in a circular zone with a certain radius around the FES to protect it from severe interference from the cellular BSs. We validate the analytical results on the success probability of the cognitive satellite-terrestrial network with directional antennas by comparing it using extensive computer simulations and show the effect of the exclusion zone on the success probability at the FES. It is shown that the exclusion zone-based interference mitigation technique significantly improves the success probability as the exclusion zone increases.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.115-123
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• 2017

The purpose of this study was to develop an indicator for the selection of urban regeneration areas through an analytical network process. Therefore, this study derived five criteria and 58 indicators based on previous studies. Five criteria and 16 indicators were derived by taking into account the region and city characteristics of Gong-ju. Next, a survey from 63 urban regeneration experts was performed. The weight values of the criteria were calculated using the super decisions 2.0 program. As a result, population characteristics (0.244) was the most important criteria, followed by the industry economy (0.218), condition of promotion policy (0.193), social culture (0.188), and physical environment (0.158). These results will be used to select potential urban regeneration areas, and will contribute to overall effective urban regeneration.

• Journal of the Korean Geographical Society
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• v.51 no.5
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• pp.667-690
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• 2016

This paper reviews the evolution process of global production network(GPN) discourse, from its origin to the recent theorization, namely GPN 2.0. In so doing, the discursive formation of global production networks is introduced in comparison with a competing discourse global commodity/value chains, with particular attention to conceptual and analytical lacunae in the latter. This article also outlines how the global production network perspective has become a useful discursive and practical tool that allows the examination of the nexus of global economy, transnational corporations, and regional development. Subsequently, a theoretical dearth in the approach is discussed in reference to key critiques, and in this context Yeung and Coe's recent theorization GPN 2.0, which is centered on casual mechanisms and network configurations is reviewed. This paper suggests that the theory adequately addresses the problem of casuality lacking in its precedented conceptual framework, and that it helps exploring the formation and evolution processes of varied production networks(including intrafirm coordination, interfirm control, strategic partnership, and extrafirm bargaining) in connection with competitive dynamics and risky environments. As a result of the theorization, the difference between GPN and the chain approaches has become more apparent, and the idea of extrafirm bargaining is particularly important in the differentiation. Extrafirm bargaining is seen to be a comprehensive networking form inclusive of such GPN 1.0 analytical concepts as value, embeddeness, and power, and research attentive to, and engaging with, the extrafirm networks is expected to help transcending the chain governance approaches' analytical excess of interfirm linkages and industry-centeredness.

• Proceedings of the Korean Society of Crop Science Conference
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• 2006.04a
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• pp.40-54
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• 2006

It's not easy to detect the high quality and functional compounds for control quality of food materials. The electronic nose was an instrument, which comprised of an array of electronic chemical sensors with partial specificity and an appropriate pattern recognition system, capable of recognizing simple or complex odors. It can conduct fast analysis and provide simple and straightforward results and is best suited for quality control and process monitoring in the field of functional foods. Numbers of applications of an electronic nose in the functional food industry include discrimination of habitats for medicinal food materials, monitoring storage process, lipid oxidation, and quality control of food and/or processing with principal component analysis, neural network analysis and the electronic nose based on GC-SAW sensor. The electronic nose would be possibly useful for a wide variety of quality control in the functional food and plant cultivation when correlating traditional analytical instrumental data with sensory evaluation results or electronic nose data.

• Korean Journal of Food Science and Technology
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• v.37 no.6
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• pp.1048-1064
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• 2005

Detection of specific compounds influencing food flavor quality is not easy. Electronic nose, comprised of electronic chemical sensors with partial specificity and appropriate pattern recognition system, is capable of recognizing simple and complex volatiles. It provides fast analysis with simple and straightforward results and is best suited for quality control and process monitoring of flavor in food industry. This review examines application of electronic nose in food analysis with brief explanation of its principle. Characteristics of different sensors and sensor drift. and solutions to related problems are reviewed. Applications of electronic nose in food industry include monitoring of fermentation process and lipid oxidation, prediction of shelf life, identification of irradiated volatile compounds, discrimination of food material origin, and quality control of food and processing by principal component analysis and neural network analysis. Electronic nose could be useful for quality control in food industry when correlating analytical instrumental data with sensory evaluation results.

• Journal of Information Technology Applications and Management
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• v.13 no.1
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• pp.77-94
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• 2006

Case-based Reasoning (CBR) is widely used in business and industry prediction. It is suitable to solve complex and unstructured business problems. Recently, the prediction accuracy of CBR has been enhanced by not only various machine learning algorithms such as genetic algorithms, relative weighting of Artificial Neural Network (ANN) input variable but also data mining technique such as feature selection, feature weighting, feature transformation, and instance selection As a result, CBR is even more widely used today in business area. In this study, we investigated the usefulness of the CBR method in forecasting success in implementing ERP systems. We used a CBR method based on the feature weighting technique to compare the performance of three different models : MDA (Multiple Discriminant Analysis), GECBR (GEneral CBR), FWCBR (CBR with Feature Weighting supported by Analytic Hierarchy Process). The study suggests that the FWCBR approach is a promising method for forecasting of successful ERP implementation in Small and Medium sized Enterprises.

• The KIPS Transactions:PartC
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• v.12C no.2 s.98
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• pp.289-300
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• 2005

This paper proposed an analytical framework to compare and model the policy-based network management; centralized and distributed typed model. Policy-based network is introduced in various application fields, and a policy framework can offer different processing performance according to application. Therefore, we evaluated the performance and extensibility of each PBNM model when we apply the policy process to the models. The evaluated measurement metrics are policy provisioning time, traffic occurrence amount, PDP processing rate, and global conflict detection in qualitative simulation. The results show that the suitable structure is required according to the analysis for the careful application characteristics, when PBNM is adopted. The modeling framework presented in this paper is intended to quantify the merits and demerits among the currently suggested PBNM models.

• Asia pacific journal of information systems
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• v.20 no.1
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• pp.127-140
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• 2010

The benefit that a consumer derives from the use of a good often depends on the number of other consumers purchasing the same goods or other compatible items. This property, which is known as network externality, is significant in many IT related industries. Over the past few decades, network externalities have been recognized in the context of physical networks such as the telephone and railroad industries. Today, as many products are provided as a form of system that consists of compatible components, the appreciation of network externality is becoming increasingly important. Network externalities have been extensively studied among economists who have been seeking to explain new phenomena resulting from rapid advancements in ICT (Information and Communication Technology). As a result of these efforts, a new body of theories for 'New Economy' has been proposed. The theoretical bottom-line argument of such theories is that technologies subject to network effects exhibit multiple equilibriums and will finally lock into a monopoly with one standard cornering the entire market. They emphasize that such "tippiness" is a typical characteristic in such networked markets, describing that multiple incompatible technologies rarely coexist and that the switch to a single, leading standard occurs suddenly. Moreover, it is argued that this standardization process is path dependent, and the ultimate outcome is unpredictable. With incomplete information about other actors' preferences, there can be excess inertia, as consumers only moderately favor the change, and hence are themselves insufficiently motivated to start the bandwagon rolling, but would get on it once it did start to roll. This startup problem can prevent the adoption of any standard at all, even if it is preferred by everyone. Conversely, excess momentum is another possible outcome, for example, if a sponsoring firm uses low prices during early periods of diffusion. The aim of this paper is to analyze the dynamics of the adoption process in markets exhibiting network effects by focusing on two factors; switching and agent heterogeneity. Switching is an important factor that should be considered in analyzing the adoption process. An agent's switching invokes switching by other adopters, which brings about a positive feedback process that can significantly complicate the adoption process. Agent heterogeneity also plays a important role in shaping the early development of the adoption process, which has a significant impact on the later development of the process. The effects of these two factors are analyzed by developing an agent-based simulation model. ABM is a computer-based simulation methodology that can offer many advantages over traditional analytical approaches. The model is designed such that agents have diverse preferences regarding technology and are allowed to switch their previous choice. The simulation results showed that the adoption processes in a market exhibiting networks effects are significantly affected by the distribution of agents and the occurrence of switching. In particular, it is found that both weak heterogeneity and strong network effects cause agents to start to switch early and this plays a role of expediting the emergence of 'lock-in.' When network effects are strong, agents are easily affected by changes in early market shares. This causes agents to switch earlier and in turn speeds up the market's tipping. The same effect is found in the case of highly homogeneous agents. When agents are highly homogeneous, the market starts to tip toward one technology rapidly, and its choice is not always consistent with the populations' initial inclination. Increased volatility and faster lock-in increase the possibility that the market will reach an unexpected outcome. The primary contribution of this study is the elucidation of the role of parameters characterizing the market in the development of the lock-in process, and identification of conditions where such unexpected outcomes happen.