• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1996년도 추계학술대회 논문
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• pp.133-137
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• 1996

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have bevome increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking arre indispensable capabilities for their versatile application. the need to meet demanding control requirement in increasingly complex dynamical control systems under sygnificant uncertainties leads toward design of implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme the ntworks intrduced are neural nets with dynamic neurouns whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure fast in computation and suitable for implementation of real-time control, Performance of the neural controller is illustrated by simulation and experimental results for a SCAEA robot.

• 센서학회지
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• 제20권3호
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• pp.151-155
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• 2011

A variety of pattern recognition algorithms including neural networks may be applicable to the identification of odors. In this paper, an identification technique for an electronic odor sensing system applicable to wound state monitoring is presented. The performance of the radial basis function(RBF) network is highly dependent on the choice of centers and widths in basis function. For the fine tuning of centers and widths, those parameters are initialized by an ill-conditioned genetic fuzzy c-means algorithm, and the distribution of input patterns in the very first stage, the stochastic gradient(SG), is adapted. The adaptive RBF network with singular value decomposition(SVD), which provides additional adaptation capabilities to the RBF network, is used to process data from array-based gas sensors for early detection of wound infection in burn patients. The primary results indicate that infected patients can be distinguished from uninfected patients.

• 한국컴퓨터산업교육학회:학술대회논문집
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• 한국컴퓨터산업교육학회 2003년도 제4회 종합학술대회 논문집
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• pp.119-126
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• 2003

Computer simulation has used to a area of military training from about several years ago. War game model(or computer simulation) endow a military man with field training such as combat experience without operating combat strength or capabilities. To samely construct simulation environment against actual combat environment is to well construct DB to operate war game model, associate among federates on network. Thus, we construct virtual combat environment enabling to efficiently manage network traffic among federates(or active nodes) on active network that construct virtual military training space such as urgent combat field needed to rapidly transfer combat information including image and video.

• 한국경영과학회지
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• 제37권2호
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• pp.1-16
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• 2012

NCW(Network Centric Warfare) offers BSEs(Battelspace-Entities) the capabilities of sharing information through C4ISRCommand, Control, Communications, Computers and Intelligence, Surveillance and Reconnaissance) network and it also improves their combat powers based on information superiority with awareness of common situation in battlefield and self-synchronization. Although the concept of NCW was developed at the end of 1990 and there have been various studies for NCW from the development of its concept, the effort for measuring the synergistic effect of NCW is insufficient at the present time. Therefore, in this paper we reviewed literatures concerning the effectiveness measurement of NCW. The category of our survey is network effect, metrics, simulation, battlefield information, social network analysis and mathematical model. The main purpose of this study is to suggest future researchers a research direction by analyzing the aspects and limitations of existing studies about the quantitative measurement of NCW.

• 한국통신학회논문지
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• 제16권11호
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• pp.1201-1209
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• 1991

일반적으로 기존의 추적 알고리즘은 표적의 수에 따른 계산량의 기하학적 증가로 실시간 처리 등 실제 응용에 커다란 제한이 되고 있다. 따라서, 본 논문에서는 고밀도 상호 연결 구조와 대규모 병렬 처리로 실시간 처리가 가능한 새로운 신경회로망 이동 표적 추적 시스템에 대한 이론적 분석과 실험을 하였다. 분석 결과, 신경회로망 알고리즘을 이용한 추적 시스템은 표적 정보의 병력 및 집적 연산이 가능하여 표적이 증가한 경우에도 계산량이 크게 증가하지 않고, 학습을 통한 추적의 최적화가 가능하며, 표적의 여러 이동 정보가 상호 연결 강도에 저장되어 다량의 정합 필터 효과를 가질 수 있으므로 신경회로망을 이용한 새로운 표적 추적 시스템의 실시간 응용 가능성을 제시하였다.

• Structural Engineering and Mechanics
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• 제15권3호
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• pp.285-297
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• 2003

Complementing recent advances made in the field of structural health monitoring and damage detection, the concept of a wireless sensing network with distributed computational power is proposed. The fundamental building block of the proposed sensing network is a wireless sensing unit capable of acquiring measurement data, interrogating the data and transmitting the data in real time. The computational core of a prototype wireless sensing unit can potentially be utilized for execution of embedded engineering analyses such as damage detection and system identification. To illustrate the computational capabilities of the proposed wireless sensing unit, the fast Fourier transform and auto-regressive time-series modeling are locally executed by the unit. Fast Fourier transforms and auto-regressive models are two important techniques that have been previously used for the identification of damage in structural systems. Their embedment illustrates the computational capabilities of the prototype wireless sensing unit and suggests strong potential for unit installation in automated structural health monitoring systems.

• 한국화재소방학회:학술대회논문집
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• 한국화재소방학회 2011년도 춘계학술논문발표회 논문집
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• pp.9-15
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• 2011

This study aims to validate predictive capabilities of FDS for the pool fire in three rooms connected to ventilation network. The three rooms in real scale fire test facility are configured to be similar to that of nuclear power plant in size, ventilation condition, construction material, etc. Basically three rooms are confined to the other area except two open doors and two ventilation duct in each room. The real scale fire test was conducted with these conditions and the predictive capabilities of FDS will be validated by comparing FDS simulation results with experimental data from the temperature, heat flux, and concentration point of view. This study concludes that temperature from FDS is about 25 % lower deviation from the experiment, and heat flux from FDS is about 5% deviation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권10호
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• pp.4849-4864
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• 2019

Modern applications such as augmented reality, connected vehicles, video streaming and gaming have stringent requirements on latency, bandwidth and computation resources. The explosion in data generation by mobile devices has further exacerbated the situation. Mobile Edge Computing (MEC) is a recent addition to the edge computing paradigm that amalgamates the cloud computing capabilities with cellular communications. The concept of MEC is to relocate the cloud capabilities to the edge of the network for yielding ultra-low latency, high computation, high bandwidth, low burden on the core network, enhanced quality of experience (QoE), and efficient resource utilization. In this paper, we provide a comprehensive overview on different traits of MEC including its use cases, architecture, computation offloading, security, economic aspects, research challenges, and potential future directions.

• Transactions on Control, Automation and Systems Engineering
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• 제3권1호
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• pp.43-50
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• 2001

In this paper, we propose the design procedure of advance Polynomial Neural Networks(PNN) architecture for optimal model identification of complex and nonlinear system. The proposed PNN architecture is presented as the generic and advanced type. The essence of the design procedure dwells on the Group Method of Data Handling(GMDH). PNN is a flexible neural architecture whose structure is developed through learning. In particular, the number of layers of the PNN is not fixed in advance but is generated in a dynamic way. In this sense, PNN is a self-organizing network. With the aid of three representative numerical examples, compari-sons show that the proposed advanced PNN algorithm can produce the model with higher accuracy than previous other works. And performance index related to approximation and generalization capabilities of model is evaluated and also discussed.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.685-686
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• 2007

This paper presents an application of power system fault diagnostic algorithm for the PEFP Proton Accelerator Research Center using neural network. Proposed fault diagnostic system is constructed by the radial basis function (RBF) neural network because it has the capabilities of the pattern classification and function approximation of any nonlinear function. Proposed system identifies faulted section in the power system based on information about the operation of protection devices such as relays and circuit breakers. In this paper, parameters of the RBF neural networks are tuned by the GA-TS algorithm, which has the global optimal solution searching capabilities. To show the validity of the proposed method, proposed algorithm has been tested with a practical power system in Proton Accelerator Research Center of PEFP.