• 대한산업공학회지
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• 제42권2호
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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.

• 한국통신학회논문지
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• 제32권6B호
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• pp.358-366
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• 2007

최근 FCC(Federal Communications Commission)에서는 통신 채널의 부족을 극복하기 위해 기존의 허가된 사용자의 무선 주파수에 대한 비 허가 사용자의 사용을 고려하고 있다. 이에 채널을 실시간으로 감지하고 선택하는 CR의 개념이 도입되어 IEEE 802.22 WRAN(Wireless Regional Area Networks) 워킹 그룹에서 CR(Cognitive Radio)의 기술개발을 진행 중에 있다. CR의 기술을 사용함에 있어서 채널을 선택하는 기준에 따라 네트워크의 통신 효율에 상당한 영향을 미치기 때문에 최적의 채널을 선택하는 방법이 중요하다. 따라서 본 논문에서는 효율적인 통신을 위해 무선인지 기술 기반의 정책에 따른 동적 채널 선택 구조(Policy-based Dynamic Channel Selection Architecture for Cognitive Radio Network)를 제안한다. 제안하는 동적 주파수 선택 방법에는 가중치 채널 선택 방법(weighted channel selection)과 순차적 채널 선택 방법(sequential channel selection)곡 혼합 채널 선택 방법(combined channel selection)의 세 가지 방법이 있으며 제안하는 방법을 사용함으로써 최적의 채널 리스트를 구성해 줄 수 있을 뿐만 아니라 동적으로 채널을 할당해 줄 수 있다.

• 한국정밀공학회지
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• 제16권6호
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• pp.133-140
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• 1999

In this study, a monitoring method to detect chip disposal state in drilling system based on neural network was proposed and its performance was evaluated. If chip flow is bad during drilling, not only the static component but also the fluctuation of dynamic component of drilling. Drilling torque is indirectly measured by sensing spindle motor power through a AC spindle motor drive system. Spindle motor power being measured drilling, four quantities such as variance/mean, mean absolute deviation, gradient, event count were calculated as feature vectors and then presented to the neural network to make a decision on chip disposal state. The selected features are sensitive to the change of chip disposal state but comparatively insensitive to the change of drilling condition. The 3 layerd neural network with error back propagation algorithm has been used. Experimental results show that the proposed monitoring system can successfully recognize the chip disposal state over a wide range of drilling condition even though it is trained under a certain drilling condition.

• Management Science and Financial Engineering
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• 제18권1호
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• pp.39-48
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• 2012

This article presents a way of tackling a special class of space optimization problems that arise in a number of practical applications in industry and elsewhere. It presents an elegant solution to a problem that was considered by (Das, 2005) in optimizing storage space in warehouse of a footwear manufacturing company. In (Das, 2005), the problem was formulated as a nonlinear programming problem. In this article, it is shown that the problem can be formulated as a generalized transportation problem which is a special case of generalized network flow problems. Further, an elegant scheme is devised to handle the dynamic situation of warehousing problem which can be easily translated into a decision support system for the warehouse management system. Also, the article points out certain obscurities and gaps in (Das, 2005).

• 대한안전경영과학회지
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• 제14권4호
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• pp.153-168
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• 2012

It has been recognized as an important issue to design optimally a firm's logistics network for minimizing logistics cost and maximizing customer service. It is, however, not easy to get an optimal solution by analyzing trade-off of cost factors, dynamic and interdependent characteristics in the logistics network decision making. Although there has been some developments in a system which helps decision making for logistics analysis, it is true that there is no system for enterprise-wise's on-site support and methodical logistics decision. Specially, E-biz process along with information technology has been made dramatic advance in a various industries, there has been much need for practical education closely resembles on-site work. The software developed by this study materializes efficient algorithm suggested by recent studies in key topics of logistics such as location and allocation problem, traveling salesman problem, and vehicle routing problem and transportation and distribution problem. It also supports executing a variety of experimental design and analysis in a way of the most user friendly based on Java. In the near future, we expect that it can be extended to integrated supply chain solution by adding decision making in production in addition to a decision in logistics.

• 한국지능시스템학회논문지
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• 제14권4호
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• pp.390-395
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• 2004

반도체 공정은 많은 단위 공정으로 이루어진 복잡하고 동적인 공정이다. 그 중 에칭공정은 반도체 생산에서 중요한 공정중 하나이다. 본 논문에서는 데이터 마이닝과 지식 획득을 통한 의사지원시스템으로 생산성과 수율을 높일 수 있는 시스템을 구성하고자 하였다. 제안된 방법은 퍼지 논리와 신경망으로 구성되는데, 신경망으로 에칭공정의 품질을 나타내는 품질에 대한 결과를 예측하고, 예측된 결과를 퍼지 추론 시스템으로 분류하는 과정으로 수행된다. 퍼지 논리에 사용된 규칙은 전문가의 지식에 기반 하여 도출되거나 데이터로부터 도출된다. 본 시스템을 통해 공정의 최적 조건을 찾아 효율을 높이는 것이 본 연구의 주요 목표이다.

• Journal of Information Processing Systems
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• 제6권3호
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• pp.269-294
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• 2010

The interconnection of mobile devices in urban environments can open up a lot of vistas for collaboration and content-based services. This will require setting up of a network in an urban environment which not only provides the necessary services to the user but also ensures that the network is secure and energy efficient. In this paper, we propose a secure, energy efficient dynamic routing protocol for heterogeneous wireless sensor networks in urban environments. A decision is made by every node based on various parameters like longevity, distance, battery power which measure the node and link quality to decide the next hop in the route. This ensures that the total load is distributed evenly while conserving the energy of battery-constrained nodes. The protocol also maintains a trusted population for each node through Dynamic Trust Factor (DTF) which ensures secure communication in the environment by gradually isolating the malicious nodes. The results obtained show that the proposed protocol when compared with another energy efficient protocol (MMBCR) and a widely accepted protocol (DSR) gives far better results in terms of energy efficiency. Similarly, it also outdoes a secure protocol (QDV) when it comes to detecting malicious nodes in the network.

• 제어로봇시스템학회논문지
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• 제6권12호
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• pp.1079-1085
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• 2000

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). An immune system is the living bodys self-protection and self-maintenance system. these features can be applied to decision making of the optimal swarm behavior in a dynamically changing environment. For applying immune system to DARS, a robot is regarded as a B-cell, each environmental condition as an antigen, a behavior strategy as an antibody, and control parameter as a T-cell, respectively. When the environmental condition (antigen) changes, a robot selects an appropriate behavior strategy (antibody). And its behavior strategy is stimulated and suppressed by other robots using communication (immune network). Finally, much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and immune network hypothesis, and it is used for decision making of the optimal swarm strategy. Adaptation ability of the robot is enhanced by adding T-cell model as a control parameter in dynamic environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권11호
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• pp.5631-5652
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• 2019

The existing defense strategy selection methods based on game theory basically select the optimal defense strategy in the form of mixed strategy. However, it is hard for network managers to understand and implement the defense strategy in this way. To address this problem, we constructed the incomplete information stochastic game model for the dynamic analysis to predict multi-stage attack-defense process by combining Bayesian game theory and the Markov decision-making method. In addition, the payoffs are quantified from the impact value of attack-defense actions. Based on previous statements, we designed an optimal defense strategy selection method. The optimal defense strategy is selected, which regards defense effectiveness as the criterion. The proposed method is feasibly verified via a representative experiment. Compared to the classical strategy selection methods based on the game theory, the proposed method can select the optimal strategy of the multi-stage attack-defense process in the form of pure strategy, which has been proved more operable than the compared ones.

• Journal of Communications and Networks
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• 제18권4호
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• pp.540-550
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• 2016

Since energy efficiency has become a significant concern for network infrastructure, next-generation network devices are expected to have embedded advanced power management capabilities. However, how to effectively exploit the green capabilities is still a big challenge, especially given the high heterogeneity of devices and their internal architectures. In this paper, we introduce a hierarchical power management architecture (HPMA) which represents physical components whose power can be monitored and controlled at various levels of a device as entities. We use energy aware state (EAS) as the power management setting mode of each device entity. The power policy controller is capable of getting information on how many EASes of the entity are manageable inside a device, and setting a certain EAS configuration for the entity. We propose the optimal local control policy which aims to minimize the router power consumption while meeting the performance constraints. A first-order Markov chain is used to model the statistical features of the network traffic load. The dynamic EAS configuration problem is formulated as a Markov decision process and solved using a dynamic programming algorithm. In addition, we demonstrate a reference implementation of the HPMA and EAS concept in a NetFPGA frequency scaled router which has the ability of toggling among five operating frequency options and/or turning off unused Ethernet ports.