• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.7
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• pp.9-16
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• 2008

For the efficient routing on a Sensor Network, one may consider a deployment problem to interconnect the sensor nodes optimally. There is an analogous theoretic problem: the Steiner Tree problem of finding the tree that interconnects given points on a plane optimally. One may use the approximation algorithm for the problem to find out the deployment that interconnects the sensor nodes almost optimally. However, the Steiner Tree problem is to interconnect mathematical set of points on a Euclidean plane, and so involves particular cases that do not occur on Sensor Networks. Thus the approach of using the algorithm does not make a proper way of analysis. Differently from the randomly given locations of mathematical points on a Euclidean plane, the locations of sensors on Sensor Networks are assumed to be physically dispersed over some moderate distance with each other. By designing an approximation algorithm for the Sensor Networks in terms of that physical property, one may produce the execution time and the approximation ratio to the optimality that are appropriate for the problem of interconnecting Sensor Networks.

• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.127-137
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• 2009

A practical algorithm of generating most probable states in decreasing order of probability of the network system state is suggested for approximating the performance of multi-mode network system using algebraic structure of the system states. Most complex system having network structure with multi-mode unit state is difficult to evaluate the performance or reliability due to exponentially increasing size of state space. Hence not an exact computing method but an approximated one is reasonable approach to solve the problem. To achieve the goal we should enumerate the network system states in order as a pre-processing step. In this paper, we suggest an improved algorithm of generating most probable multi-mode states to get the ordered system states efficiently. The method is compared with the previous algorithms in respective to memory requirement and empirical computing time. From the experiment proposed method has some advantages with regard to the criterion of algorithm performance. We investigate the advantages and disadvantage by illustrating experiment examples.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.909-912
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• 2012

An automated cell tracking system is automatically to analyze and track changes of cell behaviors in time-lapse cell images acquired from microscope in the cell culture. In this paper, we proposed and developed an ellipse fitting based algorithm for separating very small size overlapping cells in a cell image consisted of thousands or ten thousands cells. We were extracted contours of clusters and divided them into line segments and then produced their fitted ellipses for each line segment. By experimentations, our algorithm was separated clusters with average 91% precision for two overlapping cells and average 84% precision for three overlapping cells respectively.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.191-198
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• 2014

This paper proposes a simple linear function approximation method to solve an economic load dispatch problem with complex non-smooth generating cost function. This algorithm approximates a non-smooth power cost function to a linear approximate function and subsequently shuts down a generator with the highest operating cost and reduces the power of generator with more generating cost in order to balance the generating power and demands. When applied to the most prevalent benchmark economic load dispatch cases, the proposed algorithm is found to dramatically reduce the power cost than does heuristic algorithm. Moreover, it has successfully obtained results similar to those obtained through a quadratic approximate function method.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.06a
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• pp.212-215
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• 2001

본 논문에서는 평면 형상에 대한 새로운 계층적 표현 방법을 소개하였다. 제안한 방법에서는 근사화 과정의 근사화 오차(approximation error)를 근사화 순서와 정도를 결정하는 중요한 척도로 활용하였으며, 제안한 오차 조절 알고리즘을 통해 보다 자연스러운 근사화 표현이 가능하도록 하였다. 그리고 최소 경계 사각형(MBR: Minimum Bounding Rectangle)을 단순 확장한 최소 경계 팔각형(MBO: Minimum Bounding Octangle)을 지역화에 응용하였으며, 이는 다른 지역화 방법들과 비교하였을 때 상대적으로 더 효율적인 방법임을 확인할 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05a
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• pp.367-370
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• 2003

과학자나 공학자들은 빛이나 소리와 같이 주기적인 특성을 갖는 현상을 연구하는 경우가 많다. Fourier 변환은 이러한 주기함수의 근사 함수를 구할 때 유용하게 이용되고 있다. 본 논문에서는 극좌표 표현되는 함수의 근사 함수를 구하는 문제를 다룬다 일반적으로 컴퓨터 상에 구현하기 위해서는 이산형 Fourier 급수전개를 이용하는데 지금까지는 근사 함수를 컴퓨터 상에서 구할 때 이산화 표본수를 경험에 의해 임의로 결정하여 이용하였으나 본 연구에서는 Fourier 변환의 성질을 이용하여 주어진 함수에 따라 필요한 이산화 표본 수를 자동적으로 결정하는 알고리즘을 제안한다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04d
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• pp.28-30
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• 2003

COMA셀룰라 시스템의 용량은 간섭의 양에 따라 결정되므로 이 간섭량을 정확히 계산해야 시스템 성능 평가를 정확히 할 수 있다. 본 논문은 COMA셀룰라 시스템의 역방향 타셀 간섭량을 계산하기 위해 Riemann-Zeta 함수를 이용하여 임의의 전파 감쇄 지수에도 적용할 수 있는 근사식을 제시하고 시abf레이션 결과와 비교하여 그 효용을 살펴 보았다. 제안된 근사식을 이용해 계산한 시스템 용량 상한식은 시뮬레이션을 통해 얻은 용량과 근사한 결과를 얻을 수 있었다. 제안된 타셀 간섭 근사식은 복합적인 전파 환경이 고려되어야 할 계층셀 시스템에서의 간섭 일 용량 계산과 알고리즘 검증에 유용하게 사용될 수 있을 것으로 생각된다.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.5
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• pp.98-106
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• 1998

This paper proposes an efficient learning algorithm for improving the training performance of the neural network. The proposed method improves the training performance by applying the backpropagation algorithm of a global optimization method which is a hybrid of a stochastic approximation and a conjugate gradient method. The approximate initial point for f a ~gtl obal optimization is estimated first by applying the stochastic approximation, and then the conjugate gradient method, which is the fast gradient descent method, is applied for a high speed optimization. The proposed method has been applied to the parity checking and the pattern classification, and the simulation results show that the performance of the proposed method is superior to those of the conventional backpropagation and the backpropagation algorithm which is a hyhrid of the stochastic approximation and steepest descent method.

• Journal of KIISE:Databases
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• v.28 no.4
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• pp.545-557
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• 2001

In this paper we propose a hierarchical classification algorithm based on rough membership function which can reason a new object approximately. We use the fuzzy reasoning method that substitutes fuzzy membership value for linguistic uncertainty and reason approximately based on the composition of membership values of conditional sttributes Here we use the rough membership function instead of the fuzzy membership function It can reduce the process that the fuzzy algorithm using fuzzy membership function produces fuzzy rules In addition, we transform the information system to the understandable minimal decision information system In order to do we, study the discretization of continuous valued attributes and propose the discretization algorithm based on the rough membership function and the entropy of the information theory The test shows a good partition that produce the smaller decision system We experimented the IRIS data etc. using our proposed algorithm The experimental results with IRIS data shows 96%~98% rate of classification.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.374-375
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• 2011

보행자 탐지를 위해 많은 알고리즘들이 제안되었고 그 중 HOG 알고리즘은 가장 좋은 성능을 보이는 알고리즘으로 알려져 있다. 하지만 HOG(Histogram of Oriented Gradients) 알고리즘은 연산량이 많아 계산 속도가 느려 실시간 시스템에 적용하기는 힘들다. 본 논문은 HOG 알고리즘으로 얻어진 특징 벡터를 이용해 보행자를 인식하는 방법의 속도 개선에 대하여 연구하였다. 기존 HOG 알고리즘에서 계산량이 많은 곳이 어느 부분인지 분석하고, 그 중 기울기와 방향을 계산하는 부분의 근사화를 통해 계산 속도를 높이는 방법을 제안한다.