• 대한수학회논문집
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• 제36권1호
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• pp.51-62
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• 2021

Variational method has played an important role in solving problems of uniqueness and existence of the nonlinear works as well as analysis. It will also be extremely useful for researchers in all branches of natural sciences and engineers working with non-linear equations economy, optimization, game theory and medicine. Recently, the existence of infinitely many weak solutions for some non-local problems of Kirchhoff type with Dirichlet boundary condition are studied [14]. Here, a suitable method is presented to treat the elliptic partial derivative equations, especially (p(x), q(x))-Laplacian-like systems. This kind of equations are used in the study of fluid flow, diffusive transport akin to diffusion, rheology, probability, electrical networks, etc. Here, the existence of infinitely many weak solutions for some boundary value problems involving the (p(x), q(x))-Laplacian-like operators is proved. The method is based on variational methods and critical point theory.

• 대한전자공학회논문지
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• 제20권5호
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• pp.8-15
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• 1983

컴퓨터 네트워크에 C-또는 P-암호법을 도입함으로써 도청되기 쉬운 통신선상의 정보를 보호할 수 있다. 본 논문에서는 이용자가 많은 컴퓨터 네트워크에 이 두 암호법을 동시에 도입하여 시스템 안전성이 높은 CP-암호시스템을 제안하고 제시된 프로토콜에 의해 이 CP-암호 시스템의 모든 이용자가 비밀통신 뿐 아니라 서명도 할 수 있음을 보여 준다.

• 대한전자공학회논문지
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• 제4권3호
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• pp.2-8
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• 1967

불완전하게 규제된 순서회로의 내부상태를 간단화하는 방법을 논하였다. 본논문의 간단화절차는 원흐름표의 내부상태를 피복하는 최대병립유집합을 거점으로 하여 세 규칙을 적용하여 직접 극소피복을 얻는 것이다. P.I.표나 C.C표에 의한 간단화방법은 이를 채택하지 않았다. 본논문에서는 몇가지 문제에 대하여 간단화방법을 적용할 수 있는 것으로 믿는 바이다.

• 전기학회논문지P
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• 제56권1호
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• pp.28-36
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• 2007

Sensor networks are usually composed of tens or thousands of tiny devices with limited resources. Because of their limited resources, many researchers have studied on the energy management in the WSNs(Wireless Sensor Networks), especially taking into account communications efficiency. For effective data transmission and sensor fault detection in sensor network environment, a new remote monitoring system based on PCA(Principle Component Analysis) and AANN(Auto Associative Neural Network) is proposed. PCA and AANN have emerged as a useful tool for data compression and identification of abnormal data. Proposed system can be effectively applied to sensor network working in LEA2C(Low Energy Adaptive Connectionist Clustering) routing algorithms. To verify its applicability, some simulation studies on the data obtained from real WSNs are executed.

• Korean Journal of Hydrosciences
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• 제2권
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• pp.85-98
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• 1991

This paper is focused on the development of the RIVNET1 model, which is a dynamic wave model, for flood analysis in dendritic river networks with arbitrary cross-sections. This model adopted the $-point implicit RDM and utilized a relaxation algorithim in order to solve the governing equations. The double-sweep method was used to reduce the C.P.U. time to solve the matrix system of the model. This model is applied the analyze flood waves of the Ohid river in the U.S.A. and the Keum river in Korea. The results of analysis obtained from this model are compared with those of the DWOPER and observed data.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2007년도 7th International Meeting on Information Display 제7권1호
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• pp.897-899
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• 2007

Transparent electrodes for a flexible display based on the liquid crystal (LC) were formed by carbon nanotubes (CNTs) on polyethylene terephthalate (PET) substrates. The thin multi wall carbon nanotubes (t-MWNTs) networks for electrodes were obtained by filtration- transfer method from welldispersed CNTs solution.

• 제어로봇시스템학회논문지
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• 제16권12호
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• pp.1150-1158
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• 2010

In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problem. First, in preprocessing part, we use a CCD camera to obtain a picture frame in real-time. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. We use an AdaBoost algorithm proposed by Viola and Jones, which is exploited for the detection of facial image area between face and non-facial image area. As the feature extraction algorithm, PCA method is used. In this study, the PCA method, which is a feature extraction algorithm, is used to carry out the dimension reduction of facial image area formed by high-dimensional information. Secondly, we use pRBFNNs to identify the ID by recognizing unique pattern of each person. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. Coefficients of connection weight identified with back-propagation using gradient descent method. The output of pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of the Particle Swarm Optimization. The proposed pRBFNNs are applied to real-time face recognition system and then demonstrated from the viewpoint of output performance and recognition rate.

• 충청수학회지
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• 제22권4호
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• pp.789-797
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• 2009

Invertible transformations over n-bit words are essential ingredients in many cryptographic constructions. When n is large (e.g., n = 64) such invertible transformations are usually represented as a composition of simpler operations such as linear functions, S-P networks, Feistel structures and T-functions. Among them we will study T-functions which are probably invertible transformation and are very useful in stream ciphers. In this paper we will show that $f(x)=x+(g(x)^2{\vee}C)$ mod $2^n$ is a permutation with a single cycle of length $2^n$ if both the least significant bit and the third significant bit in the constant C are 1, where g(x) is a T-function.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2006년도 제26회 춘계학술대회논문집
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• pp.213-217
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• 2006

PW206C 터보 축 엔진을 위해 신경회로망을 이용한 지능형 성능 진단 프로그램이 제안되었다. 이 엔진은 항공우주연구원에서 개발 중에 있는 틸트 로터 타입 스마트 무인기의 추진시스템으로 선정되었다. 1개의 은닉층, 입력층, 출력층을 가지는 BPN(Back Propagation Network)이 신경회로망을 훈련시키기 위해 이용되었다. 입력층은 7개의 뉴런을 가지는데 SHP, MF, P2, T2, P4, T4 및 T5와 같은 측정파라미터이며 출력층은 6개의 뉴런으로 구성되어 있으며 각각은 압축기, 압축기 터빈, 동력 터빈의 유량 함수 및 효율이다. 신경망을 훈련하고 테스트하기 위한 데이터 베이스는 가스터빈 성능모사 프로그램을 이용하여 구성하였다. 훈련된 신경망을 PW206C 터보 축 엔진의 진단에 적용한 결과 제안된 진단 알고리즘이 압축기 오염과 압축기 터빈의 침식과 같은 단일 손상을 탐지하는데 유용함을 확인하였다.

• 정보처리학회논문지C
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• 제13C권5호
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• pp.549-558
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• 2006

홈 네트워크가 활성화되기 위해서는 보안 서비스의 제공이 필수적이며 특히 사용자에 대한 접근제어는 안전하고 차별화 된 홈 네트워크 서비스의 제공을 가능하게 한다. 그러나 기존의 흠 네트워크 보안 기술은 접근제어를 거의 고려하지 않거나 특정 미들웨어에 종속적인 구조를 가진다. 따라서 본 논문에서는 상호 호환성 및 확장성이 뛰어난 차세대 접근제어 표준인 extensible Access Control Markup Language(XACML)를 이용하여 흠 네트워크에서 통합적인 접근제어를 제공하기 위한 방안을 제시하고 이를 바탕으로 XACML 접근제어 시스템을 설계하고 구현한다. 또한 구현된 XACML 접근제어 시스템을 OSGi기반 UPnP 프락시 시스템에 적용하여 다양한 정책에 대한 실험을 수행함으로써 기존 홈 네트워크 시스템과의 호환성을 검증하였다.