• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.8A
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• pp.1231-1237
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• 2000

DMT기반 VDSL 시스템에서 채널의 주파수 특성에 따라 각 부채널에 각기 다른 비트를 할당하는 "Bit allocation algorithm"은 DMT기반 시스템의 초기화 과정에 필수적으로 사용되며 초기화 시간을 단축하기위해 이알고리즘의 고속화가 필요하다 기존의 알고리즘인 Chow Campello가제시한 알고리즘들은 ADSL과 같이 부채널수가 적은 응용분야에서는 적용 가능했으나 부채널 수가 ADSL의 16배에 이르는 VDSL과 같은 경우에는 계산량이 과다하기 때문에 실시간 적용이 어렵다. 본 논문에서는 수신단에서 계산된 SNR을 미리 계산된 기준 SNR 값과 비교하는 방법을 이용하여 계산량을 줄인 새로운 비트 할당 알고리즘을 제시한다. 제안된 알고리즘은 기존 알고리즘에서 N.log2N의 연산이 필요한 SNR을 내림차순으로 분류하는 과정을 없앴고 log2 연산 덧셈 및 나눗셈의 연산을 단순한 비교 연산으로 대체함으로서 보다 고속으로 각 부채널에 할당할 비트 수를 계산할수 있다 그리고 제안된 고속 알고리즘을 VDSL 시스템에 적용한 결과 기존의 알고리즘인 Chow 알고리즘과 동일한 성능을 보임을 확이하였다.보임을 확이하였다.

• KIISE Transactions on Computing Practices
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• v.21 no.6
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• pp.436-441
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• 2015

There are many types of clustering algorithms such as centroid, hierarchical, or density-based methods. Each algorithm has unique data grouping principles, which creates different varieties of clusters. Ordering Points To Identify the Clustering Structure (OPTICS) is a well-known density-based algorithm to analyze arbitrary shaped and varying density clusters, but the obtained clusters only correlate loosely. Hierarchical agglomerative clustering (HAC) reveals a hierarchical structure of clusters, but is unable to clearly find non-convex shaped clusters. In this paper, we provide a novel hierarchy generation framework and application which can aid users by combining the advantages of the two clustering methods.

• Communications for Statistical Applications and Methods
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• v.18 no.1
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• pp.89-102
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• 2011

The discretization process that converts continuous attributes into discrete ones is a preprocessing step in data mining such as classification. Some classification algorithms can handle only discrete attributes. The purpose of discretization is to obtain discretized data without losing the information for the original data and to obtain a high predictive accuracy when discretized data are used in classification. Many discretization algorithms have been developed. This paper presents the results of our comparative study on recently proposed representative discretization algorithms from the view point of splitting versus merging and supervised versus unsupervised. We implemented R codes for discretization algorithms and made them available for public users.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.7A
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• pp.1036-1045
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• 1999

In this paper, we proposed a causal ordering algorithms which is efficiently applicable to overlapped process group environments where one process may belong to several process groups. The ones is proposed to choose with topology of the network. We proposed receiver select algorithm in broadcast network, sender select algorithm in point-to-point network. Each algorithms removes unnecessary vector timestampes to reduce the message overhead required for the causual ordering. And, compressed vector timestamps using the locally maintained vector timestamp information of other processes and other groups to minimize the message overhead. Also, we logically proved the proposed causal ordering method, and compared the performance of the proposed algorithm with ones of other existing algorithms by computer simulation.

• The KIPS Transactions:PartD
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• v.17D no.3
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• pp.175-184
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• 2010

Experiments and research on genes have become very convenient by using DNA chips, which provide large amounts of data from various experiments. The data provided by the DNA chips could be represented as a two dimensional matrix, in which one axis represents genes and the other represents samples. By performing an efficient and good quality clustering on such data, the classification work which follows could be more efficient and accurate. In this paper, we use a bio-inspired algorithm called the Particle Swarm Optimization algorithm to propose an efficient clustering mechanism for large amounts of DNA chip data, and show through experimental results that the clustering technique using the PSO algorithm provides a faster yet good quality result compared with other existing clustering solutions.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.201-203
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• 2022

임베디드 시스템이 일상생활 및 각종 산업에 밀접하게 연관되어 개인 정보 및 국가 기술 등 지적 자산에 대한 보안의 필요성이 나타나고 있다. 이러한 문제점은 임베디드 시스템에 들어가는 소프트웨어의 역공학으로부터 초래된다. 따라서 본 논문은 소스 코드에 대해 제어 흐름 평탄화라는 난독화 알고리즘을 설계하는 방법을 제안한다. 이는 독자적으로 작성된 난독화 알고리즘이기 때문에 오픈 소스로 공개되어져 있는 다른 난독화 도구들에 비해 안전한 특징을 가진다. 제어 흐름 평탄화는 프로그램의 기능을 유지하면서 소스 코드의 정적 분석을 어렵게 하는 기법으로, 데이터를 탈취하려는 악의적인 행위를 사전에 예방할 수 있다. 본 논문에서 제안하는 제어 흐름 평탄화 알고리즘은 하나의 기본 블록으로 이루어진 단순한 소스 코드를 여러 개의 기본 블록으로 분할하고, 조건문을 통해 연결하는 방법을 사용하여 알고리즘의 복잡도를 높였다. 이처럼 새롭게 작성된 Pass를 통해 소스코드 난독화를 적용시켜 임베디드 시스템의 보안성을 향상시킬 수 있다.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.375-381
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• 2005

Usually genetic algorithms are used to design optimal system. However the performance of the algorithm is determined by the fitness function and the system environment. It is expected that a co-evolutionary algorithm, two populations are constantly interact and co-evolve, is one of the solution to overcome these problems. In this paper we propose three types of co-evolutionary algorithm to solve GA-Hard problem. The first model is a competitive co-evolutionary algorithm that solution and environment are competitively co-evolve. This model can prevent the solution from falling in local optima because the environment are also evolve according to the evolution of the solution. The second algorithm is schema co-evolutionary algorithm that has host population and parasite (schema) population. Schema population supply good schema to host population in this algorithm. The third is game model-based co-evolutionary algorithm that two populations are co-evolve through game. Each algorithm is applied to visual servoing, robot navigation, and multi-objective optimization problem to verify the effectiveness of the proposed algorithms.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.181-184
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• 2005

무수히 많은 정보 중에서 특정 사용자에게 가장 유용할 것으로 판단되는 정보를 추천하여 제공함으로써 특정 사용자의 편의를 돕는 시스템이 추천시스템이다. 이러한 추천시스템에 성공적으로 적용된 알고리즘이 협력적 필터링이며 이것은 다른 사용자로부터 먼저 평가된 웹 문서를 제공받아 이를 축적하고 다시 사용자에게 환원하는 알고리즘이다. 하지만 이 알고리즘은 초기평가, 희소성, 확장성 둥의 문제점을 내포하고 있다. 따라서 본 논문은 이러한 문제점을 해결하고 성능 향상을 하기 위해 적용된 개인화 추천시스템 관련 최신 알고리즘들을 비교하고 분석한 결과를 제시한다. 이를 위해 먼저 최근에 발표된 협력적 필터링과 최근접 이웃 알고리즘, 인공 지능기술을 이용한 알고리즘, 군집화 알고리즘 둥 각각에 대한 기술적 분석 결과를 수행한다. 그런 후 이들 다양한 알고리즘들의 조합을 통한 성능 향상 결과에 대한 비교분석과 각각의 조합에 대한 장단점 분석 결과도 또한 제시한다.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.1-14
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• 2010

The back-propagation neural network (BPN) has long been successfully applied in bankruptcy prediction problems. Despite its wide application, some major issues must be considered before its use, such as the network topology, learning parameters and normalization methods for the input and output vectors. Previous studies on bankruptcy prediction with BPN have shown that many researchers are interested in how to optimize the network topology and learning parameters to improve the prediction performance. In many cases, however, the benefits of data normalization are often overlooked. In this study, a genetic algorithm (GA)-based normalization transform, which is defined as a linearly weighted combination of several different normalization transforms, will be proposed. GA is used to extract the optimal weight for the generalization. From the results of an experiment, the proposed method was evaluated and compared with other methods to demonstrate the advantage of the proposed method.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.737-744
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• 2005

In this paper, we propose a three-level color clustering algerian for the binarization of text regions extracted from natural scene images. The proposed algorithm consists of three phases of color segmentation. First, the ordinary images in which the texts are well separated from the background, are binarized. Then, in the second phase, the input image is passed through a high pass filter to deal with those affected by natural or artificial light. Finally, the image Is passed through a low pass filter to deal with the texture in texts and/or background. We have shown that the proposed algorithm is more effective used gray-information binarization algorithm. To evaluate the effectiveness of the proposed algorithm we use a commercial OCR software ARMI 6.0 to observe the recognition accuracies on the binarized images. The experimental results on word and character recognition show that the proposed approach is more accurate than conventional methods by over $35\%$.