• 한국멀티미디어학회논문지
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• 제18권11호
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• pp.1261-1267
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• 2015

The problem of underwater target detection and classification has been attracted a substantial amount of attention and studied from many researchers for both military and non-military purposes. The difficulty is complicate due to various environmental conditions. In this paper, we study classifier ensemble methods for active sonar target classification to improve the classification performance. In general, classifier ensemble method is useful for classifiers whose variances relatively large such as decision trees and neural networks. Bagging, Random selection samples, Random subspace and Rotation forest are selected as classifier ensemble methods. Using the four ensemble methods based on 31 neural network classifiers, the classification tests were carried out and performances were compared.

• 전기학회논문지P
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• 제58권4호
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• pp.385-390
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• 2009

This paper presents a novel active noise control (ANC) system using least mean square (LMS) algorithm and neural network approach for decreasing acoustic noise signals inside high-speed trains. We construct a LMS framework as a nominal ANC system and additionally design an artificial single-layered perceptron model as an auxiliary ANC which is aimed to reduce real-time residuary noise due to its nonstationary and uncertain nature. Parameter vector of the hybrid ANC is determined through online estimation to realize an adaptive ANC configuration by means of the steepest descent algorithm. We achieve simulation experiment to demonstrate the proposed ANC system employing realistic acoustic noise signals measured in Korea Train eXpress (KTX).

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2012년도 한국컴퓨터종합학술대회논문집 Vol.39 No.1(D)
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• pp.407-409
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• 2012

기존 IP-USN 및 RFID 기술의 장점을 접목시킨 Active IP-RFID 기술은, IP 인프라와 IP-USN과 RFID 인프라 간 시너지 효과를 극대화하기 위해 RFID 태그에 IP를 탑재하여 확장성과 이동성을 보장하고 태그의 직접적인 관리 및 제어도 가능하게 하는 기술이다. 본 논문에서는 Active IP-RFID 시스템이 Semi-Mobility 기반에서 IP-TAG가 적은량의 에너지를 사용하여 보다 장시간 통신을 하기위한 Advanced Low Power Listening 기법을 제안하고, Always On 방식과 제안한 Advanced Low Power Listening 기법의 전류 소모 차이를 비교하였다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 춘계학술대회논문집
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• pp.286-290
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• 2000

Optimal neuro-control algorithm is extended to the control of a multi-degree-of-freedom structure. An active mass driver(AMD) system on the top roof is used as an exciter. The control signals are made by a multi-layer perceptron(MLP) which is trained by minimizing a sub-optimal performance index. The performance index is a function of both the output responses and the control signals. Structure having nonlinear hysteretic behavior is also trained and controlled by using proposed control algorithm. In training neuro-controller, emulator neural network is not used. Instead, sensitivity-test data are used. Therefore, only one neural network is used for the control system. Both the time delay effect and the dynamics of hydraulic actuator are included in the simulation. Example shows that optimal neuro-control algorithm can be applicable to the multi-degree of freedom structures.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2005년도 춘계학술발표대회
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• pp.1307-1310
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• 2005

$IP^2$(IP based-IMT Network Platform)은 유비쿼터스 플랫폼으로서 백본 망에서 IP 를 IPha(IP host address)와 IPra(IP routing address)으로 두 가지를 사용하여서 이동성을 지원한다. 그리고 MN(Mobile Node)도 Active 상태와 Dormant 상태로 두 가지 상태로 나뉘는데 Dormant 상태에서 상대방이 통신을 요청하면 페이징(Paging) 과정을 통해서 Active 상태로 전이된다. 페이징을 할 때 LA(Location Area)에 속해있는 모든 셀(Cell)에 페이징 메시지를 전송하게 됨으로서 네트워크의 자원을 과도하게 사용하게 된다. 이것을 해결하기 위해서 프럭시(Proxy) 를 두는 방안을 제안하였다. 프럭시에서 MN 들이 존재하는 셀 정보를 유지 함으로서 페이징 요청이 있을 때 정확한 셀에 메시지를 전송하게 되기 때문에 네트워크 자원의 낭비를 줄일 수 있다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권2호
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• pp.178-186
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• 2003

Recently, many researchers have been interested in biometric systems such as fingerprint, handwriting, key-stroke patterns and human iris. From the viewpoint of reliability and robustness, iris recognition is the most attractive biometric system. Moreover, the iris recognition system is a comfortable biometric system, since the video image of an eye can be taken at a distance. In this paper, we discuss human iris recognition, which is based on accurate iris localization, robust feature extraction, and Neural Network classification. The iris region is accurately localized in the eye image using a multiresolution active snake model. For the feature representation, the localized iris image is decomposed using wavelet transform based on dyadic Haar wavelet. Experimental results show the usefulness of wavelet transform in comparison to conventional Gabor transform. In addition, we present a new method for setting initial weight vectors in competitive learning. The proposed initialization method yields better accuracy than the conventional method.

• 한국통신학회논문지
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• 제21권3호
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• pp.753-762
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• 1996

In this paper, aperture coupled stacked microstrip array antennas are proposed and their operating characteristics are analyzed based on analytical. In order to evaluate mutual coupling between slot-coupled microstrip patches in finite array, analysis uses the reciprocity theorem and the spectral domain Green's functions for dielectric slab in a moment method solution for the unknown patches and solts current distrbution. By introducing an N-port equivalent network, the impedance matrix of an affay of N-element slot-coupled patches is evaluated directly from its network current matix of order N$^{2}$, and it can be programmed to be run on a PC. Numerical results show mutual coupling, radiation pattern, active reflection coefficient versus scan angle, radiation efficiency and active element gain pattern.

• 정보교육학회논문지
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• 제1권2호
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• pp.1-15
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• 1997

In this paper we present database model for Intelligent Peripheral (IP) of Advanced Intelligent Network (AIN). The new model is developed through four phase. (1) An information of AIN IP is classified that would be stored in AIN IP database as specialized resources, service. schema and system information. (2) The modeling criteria are developed that would be used to model information classified. (3) Object-oriented concepts are used in modelifl8 classified information according to modeling criteria captured. (4) Methods applied to developed model are grouped, and active-based mechnisms such as trigger and constraints are developed. These selected methods and attributes are encapsulated into objects. Consequently they compose an active object-oriented AIN IP database model.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2003년도 춘계학술발표논문집 (하)
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• pp.2213-2216
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• 2003

단일 호스트 환경에 특화되어 설계되어온 기존 침입탐지 시스템(Intrusion Detection System: IDS)은 침입 시 도메인의 보호만을 그 목적으로 하는 수동적인 성격으로써, 새로운 공격 기법에 대한 탐지 및 대응, 그리고 보다 그 규모가 큰 네트워크로의 확장 면에서 구조적인 결함을 가지고 있다. 이러한 IDS의 구조적 문제점의 해결방안으로 액티브 네트워크 기반의 IDS 에 관한 연구가 진행되고 있다. 액티브 네트워크(Active network)란 패킷 스위칭 네트워크 상에 프로그램 가능한 라우터 등인 액티브 노드들을 배치하고, 사용자의 요구에 상응하는 적절한 연산을 위한 데이터와 프로그램으로 구성된 스마트 패킷(smart packet)에 대하여 수행 가능하게 하는 접근 방법이다. 본 논문에서는 이를 기반으로 자율적이며 지능적인 에이전트로 구성된 멀티 에이전트 기술을 액티브 노드에 적용함으로써 기존 IDS 보안메커니즘에서 보다 러 진보된 능동적이고 적극적인 대응을 위한 보안 메커니즘을 제공하여 네트워크 공격에 의한 피해 최소화와 신속한 대응이 가능한 멀티 에이전트 기반 공격 대응 메커니즘을 제시하고, 이를 적용 가능한 액티브 네트워크 기반 프레임 설계를 제안한다.

• Structural Engineering and Mechanics
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• 제49권6호
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• pp.687-703
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• 2014

This paper develops a new nonlinear model for active control of three-dimensional (3D) irregular building structures. Both geometrical and material nonlinearities with a neuro-controller training algorithm are applied to a multi-degree-of-freedom 3D system. Two dynamic assembling motions are considered simultaneously in the control model such as coupling between torsional and lateral responses of the structure and interaction between the structural system and the actuators. The proposed control system and training algorithm of the structural system are evaluated by simulating the responses of the structure under the El-Centro 1940 earthquake excitation. In the numerical example, the 3D three-story structure with linear and nonlinear stiffness is controlled by a trained neural network. The actuator dynamics, control time delay and incident angle of earthquake are also considered in the simulation. Results show that the proposed control algorithm for 3D buildings is effective in structural control.