• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.4A
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• pp.291-300
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• 2002

In this paper, a way of constituting optimized S box and G function was suggested in the block cipher whose structure is similar to SEED, which is KOREA standard of 128-bit block cipher. S box can be formed with nonlinear function and an affine transform. Nonlinear function must be strong with differential attack and linear attack, and it consists of an inverse number over GF(2$\^$8/) which has neither a fixed point, whose input and output are the same except 0 and 1, nor an opposite flexed number, whose output is one's complement of the input. Affine transform can be constituted so that the input/output correlation can be the lowest and there can be no fixed point or opposite fixed point. G function undergoes diffusive linear transform with 4 S-box outputs using the matrix of 4$\times$4 over GF(2$\^$8/). G function can be constituted so that MDS(Maximum Distance Separable) code can be formed, SAC(Strict Avalanche Criterion) can be met, there can be no weak input, where a fried point, an opposite fried point, and output can be two's complement of input, and the construction of hardware can be made easy. The S box and G function suggested in this paper can be used as a constituent of the block cipher with high security, in that they are strong with differential attack and linear attack with no weak input and they are excellent at diffusion.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.2
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• pp.7-13
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• 1999

This paper propose a fuzzy regression method using fuzzy neural networks when a membership value is attached to each input -output pair. First, an architecture of fuzzy neural networks with fuzzy weights and fuzzy biases is shown. Next, a cost function is defined using the fuzzy output from the fuzzy neural network and the corresponding target output with a membership value. A learning algorithm is derived from the cost function. The derived learning algorithm trains the fuzzy neural network so that the level set of the fuzzy output includes the target output. Last, the proposed method is applied to the quality evaluation problem of injection molding

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.217-220
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• 2022

본 논문에서는 CCTV 영상 화질을 향상하고 해상도를 높이기 위해 딥 러닝(Deep Learning)을 이용하여 잡음 제거(Denoising) 와 초해상도(Super-resolution) 작업을 수행한다. 데이터 증강(Data Augmentation)을 통한 초해상도 성능 향상을 위해서 잡음 제거 네트워크의 출력 영상을 초해상도 네트워크의 입력으로 사용하는 순차적 작업을 사용한다. 또한 딥 러닝을 이용한 영상처리에서 발생하는 평균 밝기 오차 문제를 해결하기 위한 손실함수(Loss Function)와 두 가지 이상의 순차적인 딥 러닝 작업에서 발생하는 문제점을 극복하기 위한 손실함수를 제안한다. 제안하는 손실함수는 네트워크의 출력 영상과 타겟 영상의 밝기 오차를 줄이는 것이 가능하고, 순차적 작업에서 보다 정확한 모델 성능 판단이 가능하다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.375-377
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• 2024

본 논문에서는 OpenAI Gym 환경에서 프로그램으로 간단한 제어가 가능한 Mountain-Car-v0 게임에 대해 DQN(Deep Q-Networks) 강화학습을 진행하였다. 본 논문에서 적용한 DQN 네트워크는 입력층 1개, 은닉층 3개, 출력층 1개로 구성하였고, 입력층과 은닉층에서의 활성화함수는 ReLU를, 출력층에서는 Linear함수를 활성화함수로 적용하였다. 실험은 Mountain-Car-v0에 대해 DQN 강화학습을 진행했을 때 각 에피소드별로 획득한 보상 결과를 살펴보고, 보상구간에 포함된 횟수를 분석하였다. 실험결과 전체 100회의 에피소드 중 보상을 50 이상 획득한 에피소드가 85개로 나타났다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.57-60
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• 2003

본 논문에서는 사용자가 Windows 상에서 자신의 알고리즘을 반영시킨 flowchart를 작성하면 그에 해당하는 C프로그램을 생성시켜 주는 시스템을 구현하였다. 사용자가 그린 flowchart 기호들과 흐름선 및 기호 안에 기술된 문자정보를 연결형 리스트를 사용하여 표현하였다. 기술된 문자 정보를 검색하여, 사용된 함수에 따라 해당 헤더 파일을 추가하고, 입ㆍ출력 함수에 대한 변환을 행한다. 그려진 flowchart기호에 대하여 흐름선의 개수나 연결기호를 이용한 변환 알고리즘을 적용하여 C코드로 변환하여 화면상에 출력시키고, 파일로 저장하였다. 본 시스템을 다양한 알고리즘에 적용시켜서 만족한 결과를 얻을 수 있었다.

• Journal of Energy Engineering
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• v.4 no.3
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• pp.402-406
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• 1995

다리우스 풍력터빈의 속도설정을 터빈이 만드는 토크와 발전기가 요구하는 토크의 \평형을 통해 찾아 낼 수 있음을 검토하였다. 풍속에 따른 속도-토크곡선에서 일정충력곡선이 만나는 점이 터빈의 동작점으로 되며 이는 안정 및 불안정이 될 수도 있다. 풍속과 출력이 각각 변할 때 이 동작점이 어떻게 이동되는가 하는 점을 제시하였다. 또한 터빈의 속도에 관한 제어 블록선도를 제시하여 그 출력변화에 따른 속도변화의 전달함수를 알아내고 이의 형태는 1차 시지연 함수로 유도된다.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.185-190
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• 2005

A systematic output tracking control design technique for robust control of Takagi-Sugeno (T-S) fuzzy systems with norm bounded uncertainties is developed. The uncertain T-S fuzzy system is first represented as a set of uncertain local linear systems. The tracking problem is then converted into the stabilization problem for a set of uncertain local linear systems thereby leading to a more feasible controller design procedure. A sufficient condition for robust asymptotic output tracking is derived in terms of a set of linear matrix inequalities. A stability condition on the traversing time instances is also established. The output tracking control simulation for a flexible-joint robot-arm model is demonstrated, to convincingly show the effectiveness of the proposed system modeling and controller design.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1996.11a
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• pp.365-368
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• 1996

카오스 함수인 베이커 함수를 이용하여 불규칙한 상태에 의해 카오스적인 패턴을 발생시키는 패턴 발생기를 구현하였다. 카오스적인 패턴 발생기는 예측할 수 있는 패턴들을 발생시킨다는 점에서 기존의 패턴 발생기와 흡사하지만, 패턴요소의 출력 순서는 결정론적 카오스 함수에 따른다.

• Nuclear Engineering and Technology
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• v.16 no.4
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• pp.181-194
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• 1984

The in-core fuel management problem was studied by use of the calculus of variations. Two functions of interest to a public power utility, the profit function and the cost function, were subjected to the constraints of criticality, the reactor turnup equations and an inequality constraint on the maximum allowable power density. The variational solution of the initial profit rate demonstrated that there are two distinct regions of the reactor, a constant power region and a minimum inventory or flat thermal flux region. The transition point between these regions is dependent on the relative importance of the profit for generating power and the interest charges for the fuel. The fuel cycle cost function was then used to optimize a three equal volume region reactor with a constant fuel enrichment. The inequality constraint on the maximum allowable power density requires that the inequality become an equality constraint at some points in the reactor. and at all times throughout the core cycle. The finite difference equations for reactor criticality and fuel burnup in conjunction with the equality constraint on power density were solved, and the method of gradients was used to locate an optimum enrichment. The results of this calculation showed that standard non-linear optimization techniques can be used to optimize a reactor when the inequality constraints are properly applied.

• Journal of the Korea Society for Simulation
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• v.21 no.3
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• pp.11-16
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• 2012

Simulation is the imitation of the operation of a real-world process or system over time. It concerns the study of the operating characteristics of real systems. Typically, a simulation project consists of several steps such as data collection, coding, model verification, model validation, experimental design, output data analysis, and implementation. Among these steps of a simulation study this paper focus on statistical analysis methods of simulation output data. Specially, we explain how to develop confidence interval estimators for mean ${\mu}$ in terminating and non-terminating simulation cases. We, then, explore the estimation techniques for $f({\mu})$, where the function $f({\bullet})$ is a nonlinear that is continuously differentiable in a neighborhood of ${\mu}$ with $f'({\mu}){\neq}0$.