• 전자공학회논문지B
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• 제31B권11호
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• pp.151-162
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• 1994

다차원 시스템(multidimensional system)에 대한 정확한 모델링을 위해 “자율 분산 신경망(Self-organized Distirbuted Networks, SODN)”을 제안하였다. 제안한 신경망은 자율 신경망(Self-organized Networks)과 다수의 소규모 다층 신경망(Multilayer Neural Networks)이 조합되어 지역적 병렬 학습을 수행하는 부분 학습망으로서 학습 속도가 빠르고 학습의 정밀도를 높일 수 있으며 타 부분망 학습에서 문제가 되는 과다한 학습 메모리 소요와 학습되니 않은 영역에 대한 낮은 일반화능력 등의 문제가 보완된 새로운 신경망이다. 학습 실험 결과, 제안한 신경망은 기존의 다층 신경망과 RBF(Radial Basis Function) 신경망에 비해서 우수한 성능을 보였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.94.5-94
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• 2002

The current study of complex dynamical networks is pervading all kinds of sciences today, ranging from physical to biological, even to social sciences. its impact on modern engineering and technology is prominent and will be far-reaching. Typical complex dynamical networks include the World Wide Web, the Internet, various wireless communication networks, meta-bolic networks, biological neural networks, social connection networks, scientific cooperation and citation networks, and so on. Research on fundamental properties and dynamical features of such complex networks have become overwhelm ing. This talk will provide a brief overview of some basic concepts about com plex dynamical netwo...

• 지식경영연구
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• 제12권4호
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• pp.17-40
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• 2011

This study examines the differences of enacting models and influential causes of benefit-sharing practices between Korean automobile networks and the Japanese networks. The case study method is chosen for this research because only small numbers of supply networks adopt benefit-sharing practices. I employ semi-structured interviews with managers from four automobile manufacturers and eight of their suppliers in South Korea and Japan. I find that Japanese automobile networks have adopted a higher level of trust-demanding, with a higher level of value-creating models such as supplier development, joint-new-product development. Whereas, the Korean networks have adopted the lower trust demanding, also less profitable models such as supplier's suggestion and buyer's suggestion. In terms of work-related cultural values, I find that Japanese networks emphasized collectivism. Both buyers and suppliers in the Japanese networks are supposed to have common causes. In contrast, Korean networks emphasized individualism. Both buyers and suppliers of Korea generally do not identify that they are common group members with a common cause. I also find that a slight differences of the enacting models and the causes between foreign-owned networks and domestic-owned networks within each country. Foreign-owned networks have adopted lower trust demanding, also less profitable models. The findings demonstrate that the cultural values have a decisive influence on the adoption of benefit sharing models for the networks in Japan, and South Korea.

• Smart Structures and Systems
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• 제11권5호
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• pp.497-510
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• 2013

Quick, accurate damage monitoring is strongly required for damage assessment in the aftermath of a large natural disaster. Wireless sensor networks are promising technologies to acquire damage information in a citywide area. The wireless sensor networks, however, would be faced with difficulty to collect data in real-time and to expand the scalability of the networks. This paper discusses a scheme of network architecture to cove a whole city in multi-tier heterogeneous networks, which consist of wireless sensor networks, access networks and a backbone network. We first review previous studies for citywide damage monitoring, and then discuss the feature of multi-tier heterogeneous networks to cover a citywide area.

• 정보보호학회지
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• 제26권6호
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• pp.42-50
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• 2016

Critical infrastructure (CI) such as the electrical grid, transportation systems and water resource systems are controlled by Industrial Control and SCADA (Supervisory Control and Data Acquisition) networks. During the last few years, cyber attackers have increasingly targeted such CI systems. This is of great concern because successful attacks have wide ranging impact and can cause widespread destruction and loss of life. As a result, there is a critical requirement to develop enhanced algorithms and tools to detect cyber threats for SCADA networks. Such tools have key differences with the tools utilized to detect cyber threats in regular IT networks. This paper discusses key factors which differentiate network security for SCADA networks versus regular IT networks. The paper also presents various approaches used for SCADA security and some of the advancements in the area.

• Journal of Information Processing Systems
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• 제14권2호
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• pp.455-468
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• 2018

The concepts of graph theory are applied to model and analyze dynamics of computer networks, biochemical networks and, semantics of social networks. The analysis of dynamics of complex networks is important in order to determine the stability and performance of networked systems. The analysis of non-stationary and nonlinear complex networks requires the applications of ordinary differential equations (ODE). However, the process of resolving input excitation to the dynamic non-stationary networks is difficult without involving external functions. This paper proposes an analytical formulation for generating solutions of nonlinear network ODE systems with functional decomposition. Furthermore, the input excitations are analytically resolved in linearized dynamic networks. The stability condition of dynamic networks is determined. The proposed analytical framework is generalized in nature and does not require any domain or range constraints.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2004년도 하계학술대회 논문집 Vol.5 No.2
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• pp.1234-1238
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• 2004

A Controlled neural networks are proposed in order to measure nonlinear environments in adaptive and in realtime. The structure of it is similar to recurrent neural networks: a delayed output as the input and a delayed error between tile output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by backpropagation and each weights are updated by RLS(Recursive Least Square). Consequently, this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. This new neural networks is Error Estimated Neural Networks. We can estimate nonlinear models in realtime by the proposed networks and control nonlinear models. To show the performance of this one, we have various experiments. And this controller call prove effectively to be control in the environments of various systems.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2008년도 하계학술대회 논문집 Vol.9
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• pp.525-526
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• 2008

For measuring nonlinear Vehicle Modeling based on 7-Depth Sensor, the neural networks are proposed m adaptive and in realtime. The structure of it is similar to recurrent neural networks; a delayed output as the input and a delayed error between the output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by backpropagation and each weights are updated by RLS(Recursive Least Square). Consequently, this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. This new neural networks is Error Estimated Neural Networks. We can estimate nonlinear models in realtime by the proposed networks and control nonlinear models.

• 한국멀티미디어학회논문지
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• 제15권12호
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• pp.1456-1463
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• 2012

In this paper, we study the ON/OFF control policy of base stations in two-tier heterogeneous cellular networks to minimize the total power consumption of the system. Using heterogeneous cellular networks is a potential approach of providing higher throughput and coverage compared to conventional networks with only macrocell deployment, but in fact heterogeneous cellular networks often operates regardless of total power consumption, which is a very important issue of modern cellular networks. We propose a policy that controls the activation/deactivation of base stations in heterogeneous cellular networks to minimize total power consumption. Under this policy, the total power consumed can be significantly reduced when the traffic is low while the QoS requirement is satisfied.

• Journal of information and communication convergence engineering
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• 제19권4호
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• pp.205-213
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• 2021

The properties of a scale-free network are little known; its node degree following a power-law distribution is among its few known properties. By selecting real-field scale-free networks from a network dataset and comparing them to other networks, such as random and non-scale-free networks, the topology characteristics of scale-free networks are identified. The assortative coefficient is identified as a key metric of a scale-free network. It is also identified that most scale-free networks have negative assortative coefficients. Traditional generation models of scale-free networks are evaluated based on the identified topology characteristics. Most representative models, such as BA and Holme&Kim, are not effective in generating real-field scale-free networks. A link-rewiring method is suggested that can control the assortative coefficient while preserving the node degree sequence. Our analysis reveals that it is possible to effectively reproduce the assortative coefficients of real-field scale-free networks through link-rewiring.