• 전기전자학회논문지
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• 제16권2호
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• pp.102-108
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• 2012

3D-IC는 2D-IC와 비교하여 전력 공급 네트워크 설계 시에 더 큰 공급 전류와 더 많은 전력 공급 경로들 때문에 몇 가지 문제점을 가지고 있다. 전력 공급 네트워크는 전력 범프와 전력 TSV로 구성되고, 각 노드의 전압 강하는 전력 범프와 전력 TSV의 개수와 위치에 따라 다양한 값을 가지게 된다. 그래서 칩이 정상적으로 동작하기 위해서는 전압 강하 조건을 만족시키면서 전력 범프와 전력 TSV를 최적화하는 것이 중요하다. 본 논문에서는 3D-IC 전력 공급 네트워크에서 최적의 전력 메시 구조를 통한 전력 범프와 전력 TSV 최적화를 제안한다.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2010년도 하계학술대회 논문집
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• pp.308-308
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• 2010

실리콘 나이트라이드 박막의 굴절률과 lifetime을 유전자 알고리즘과 일반화된 회귀 신경망을 이용하여 모델링하였다. 종래의 모델링에서 평가한 Spread Range 범위보다 더 작은 0.04~1.0 범위에서 평가를 수행하였다. 통계적 실험계획법을 적용해서 수집한 데이터가 이용되었다. 평가결과 보다 낮은 spread range에서 보다 우수한 예측모델이 개발될 수 있음을 확인하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 추계학술대회 논문집 학회본부
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• pp.55-58
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• 1995

An optimum design method of electric machines using neural network is presented. In this method, two multi - layer perceptrons of analysis and design neural network are used in optimizing process. A preliminary model of linear induction motor for subway is designed by the electric and magnetic loading distribution method and then optimized by presented method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.56-60
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• 2002

The paper presents the optimum design of a linear induction motor(LIM) using Genetic algorithm, Neural Network and SUMT. The design variables are optimized by three different optimization methods and the results are discussed.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1995년도 추계학술대회 학술발표 논문집
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• pp.45-51
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• 1995

A novel definition for fuzzy mathematical morphology is described The generalized-mean operator plays the key role for this definition. Several hard constraints for standard generalized-mean have been eliminated. Complete mathematical description for obtaining fuzzy erosion and dilation is provided. The definitions are well suited for neural network implementation. Therefore, the parameters for the fuzzy definition can be optimized using neural network learning paradigm.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2003년도 봄 학술발표논문집 Vol.30 No.1 (C)
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• pp.337-339
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• 2003

NGN 시대가 될수록 이동성을 지원하면서 네트워크를 효율적으로 이용하는 기술이 요구된다. Mobile Ipv6은 이와 같은 요구조건을 만족시키는 좋을 방법이다. 본 논문에서는 이동호스트가 핸드오버를 수행할 때 발생하는 Triangle Routing 오버헤드를 감소시키는 핸드오버 프로토콜을 제안한다. 제안된 핸드 오버 프로토콜은 Previous Access Router(PAR)가 Binding Update(BU) 메시지를 전송하게 함으로써 PAR에서 New Access Router(NAR)로 포워딩되는 패킷의 개수를 감소시킨다. 제안된 핸드오버는 NS-2(network simulation)에서 시뮬레이션 되었고, 멀티미디어 데이터 통신에 사용되는 UDP를 이용하였다.

• Journal of Mechanical Science and Technology
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• 제16권8호
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• pp.1033-1038
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• 2002

Genetic alsorithm (GA) , compared to the gradient-based optimization, has advantages of convergence to a global optimized solution. The genetic algorithm requires so many number of analyses that may cause high computational cost for genetic search. This paper proposes a personal computer network programming based on TCP/IP protocol and client-server model using socket, to improve processing speed of the genetic algorithm for optimization of composite laminated structures. By distributed processing for the generated population, improvement in processing speed has been obtained. Consequently, usage of network-based genetic algorithm with the faster network communication speed will be a very valuable tool for the discrete optimization of large scale and complex structures requiring high computational cost.

• Journal of information and communication convergence engineering
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• 제9권6호
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• pp.683-688
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• 2011

The wireless sensor network (WSN) is well known for an enabling technology for the ubiquitous environment such as real-time surveillance system, habitat monitoring, home automation and healthcare applications. However, the WSN featuring wireless communication through air, a resource constraints device and irregular network topology, is threatened by malicious nodes such as eavesdropping, forgery, illegal modification or denial of services. For this reason, security in the WSN is key factor for utilizing the sensor network into the commercial way. There is a series of symmetric cryptography proposed by laboratory or industry for a long time. Among of them, recently proposed HUMMINGBIRD algorithm, motivated by the design of the well-known Enigma machine, is much more suitable to resource constrained devices, including smart card, sensor node and RFID tags in terms of computational complexity and block size. It also provides resistance to the most common attacks such as linear and differential cryptanalysis. In this paper, we implements ultra-lightweight cryptography, HUMMINGBIRD algorithm into the resource constrained device, sensor node as a perfectly customized design of sensor node.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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• pp.1949-1950
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• 2006

In this paper, a direct controller for nonlinear plants using a neural network is presented. The controller is composed of an approximate controller and a neural network auxiliary controller. The approximate controller gives the rough control and the neural network controller gives the complementary signal to further reduce the output tracking error. This method does not put too much restriction on the type of nonlinear plant to be controlled. In this method, a RBF neural network is trained and the system has a stable performance for the inputs it has been trained for. Simulation results show that it is very effective and can realize a satisfactory control of the nonlinear system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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• pp.2075-2076
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• 2006

In this paper, we propose a new architecture of Genetic Algorithms(GAs)-based Backpropagation(BP). The conventional BP does not guarantee that the BP generated through learning has the optimal network architecture. But the proposed GA-based BP enable the architecture to be a structurally more optimized network, and to be much more flexible and preferable neural network than the conventional BP. The experimental results in BP neural network optimization show that this algorithm can effectively avoid BP network converging to local optimum. It is found by comparison that the improved genetic algorithm can almost avoid the trap of local optimum and effectively improve the convergent speed.