• The Transactions of the Korea Information Processing Society
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• v.5 no.5
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• pp.1162-1171
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• 1998

This paper presents a data structure that implements a mergable double-ended priority queue : namely an improved relaxed min-max-pair heap. By means of this new data structure, we suggest a parallel algorithm to merge priority queues organized in two relaxed heaps of different sizes, n and k, respectively. This new data-structure eliminates the blossomed tree and the lazying method used to merge the relaxed min-max heaps in [9]. As a result, employing max($2^{i-1}$,[(m+1/4)]) processors, this algorithm requires O(log(log(n/k))${\times}$log(n)) time. Also, on the MarPar machine, this method achieves a 35.205-fold speedup with 64 processors to merge 8 million data items which consist of two relaxed min-max heaps of different sizes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.6A
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• pp.1089-1098
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• 2001

WRR 스케줄링 알고리즘은 계산의 단순성과 저 비용 구현의 장점을 가지고 있어 고속 패킷 스위칭 네트워크에서 널리 쓰이고 있지만 버스티한 트래픽에 대해서는 입력 트래픽을 일정 비율로 스케줄링하기 때문에 효율성이 낮다는 문제점이 있다. 또한, WRR 알고리즘은 ABR 서비스 클래스의 공평성 기준의 하나인 Maximum of MCR or Max-Min share 공평성을 만족시키지 못한다. 따라서 ABR 서비스를 위한 공평성 기준을 만족시키는 스케줄링 알고리즘이 필요하다. 따라서, 본 논문에서는 ABR 서비스를 위한 5가지 공평성 기준들 중 Maximum of MCR or Max-Min share를 만족시키는 스케줄링 알고리즘을 제안한다. 제안된 알고리즘이 공평성 기준을 만족시키고, 네트워크 자원을 각 ABR VC들에게 공평하게 할당해 주는지를 컴퓨터 시뮬레이션을 통하여 WRR 알고리즘과 비교, 분석한다.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1E
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• pp.73-82
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• 1995

This paper presents a data structure that implements a mergeable double-ended priority queue ; namely, an improved relaxed min-max-pair heap. It suggests a sequential algorithm to merge priority queues organized in two relaxed min-max heaps : kheap and nheap of sizes k and n, respecrively. This new data sturuture eliminates the blossomed tree and the lazying method used to merge the relaxed min-max heaps in [8]. As a result, the suggested method in this paper requires the time complexity of O(log(log(n/k))*log(k)) and the space complexity of O(n+), assuming that $k{\leq}{\lfloor}log(size(nheap)){\rfloor}$ are in two heaps of different sizes.

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.33-38
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• 2014

The FCM based hybrid RBF network is a heterogeneous learning network model that applies FCM algorithm between input and middle layer and applies Max_Min algorithm between middle layer and output. The Max-Min neural network uses winner nodes of the middle layer as input but shows inefficient learning in performance when the input vector consists of too many patterns. To overcome this problem, we propose a dynamic learning rate control based on fuzzy logic. The proposed method first classifies accurate/inaccurate class with respect to the difference between target value and output value with threshold and then fuzzy membership function and fuzzy decision logic is designed to control the learning rate dynamically. We apply this proposed RBF network to the character recognition problem and the efficacy of the proposed method is verified in the experiment.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.9 s.174
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• pp.130-136
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• 2005

This paper presents an optimal design and the performance evaluation of two-axis nano positioning stage with round notched flexure hinges. A flexure hinge mechanism with round notched flexure hinges is to guide the linear motions of a moving plate in the nano positioning stage. A Min-Max algorithm is applied to the design of the flexure hinge mechanism for nano positioning stage. In the design process, the structure of the flexure hinge mechanism is fixed, then the radius of a round hole and the width of two round holes are chosen as design variables, and finally the do sign variables are calculated by the Min-Max algorithm. The machined flexure hinge mechanism, stack type PZTs for actuation and capacitance type displacement sensors for position measurement are assembled into the nano positioning stage. The experimental results of the manufactured nano positioning stage show the first modal resonance frequency of 197 Hz, the operating range of 40 um, and the resolution of 3 nm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1457-1464
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• 2011

In this paper, we go one step further in that the number of competitive layers is not determined by experience but can be determined by fuzzy control rules based on input pattern information. In our method, we design a set of membership functions and corresponding rules and used Max-Min reasoning proposed by Mamdani. Also, we use centroid method as a defuzzification. In experiment that has various patterns of English inputs, this new method works beautifully to determine the number of competitive layers and also efficient in overall accuracy as a result.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.1
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• pp.96-104
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• 1998

A new gray-scale thinning algorithm using local min/max operations is proposed. In this method, erosion and dilation properties of local min/max operations are using for generating new rides and detecting ridges in gray scale image, and gray-scale skeletons are gradually obtained by accumulating the detected ridges. This method can be applicable to the unsegmented image in which object are not specified, and the obtained skeletons correspond to the ridges (high gray values) of an input image.

• Proceedings of the Korean Society of Computer Information Conference
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• 2008.06a
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• pp.149-154
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• 2008

FCM 기반 RBF 네트워크는 서로 다른 학습 구조가 결합된 혼합형 모델로서, 입력층과 중간층의 학습 구조는 FCM 알고리즘을 적용하고, 중간층과 출력층 사이의 학습 구조는 Max_Min 신경망을 적용한다. 입력층과 중간층의 학습시 입력벡터와 중간층의 노드중에서 중심과 입력벡터간의 가장 가까운 노드를 승자 노드로 선택하여 출력층으로 전달한다. 그리고 중간층과 출력층 사이의 학습 구조는 Max_Min 신경망을 적용하여 중간층의 승자 뉴런이 출력층의 입력벡터로 적용한다. 하지만 많은 패턴이 입력벡터로 제시될 경우 학습 성능이 저하되는 단점이 있다. 따라서 본 논문에서는 중간층과 출력층의 학습 구조인 Max_Min 알고리즘의 학습 성능을 개선시키기 위해 퍼지 제어시스템을 이용하여 학습률을 동적으로 조정하는 퍼지 제어 기법을 이용한 FCM 기반 RBF 네트워크를 제안한다. 제안된 방법의 학습 성능을 평가하기 위하여 컨테이너 영상에서 추출한 숫자, 영문 식별자를 학습 데이터로 적용한 결과, 기존의 ART2 기반 RBF 네트워크보다 학습 시간이 적게 소요되고, 학습의 수렴성이 개선된 것을 확인하였다.

• Journal of the Korea Society of Computer and Information
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• v.17 no.10
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• pp.155-165
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• 2012

This paper suggests traveling salesman problem algorithm that have been unsolved problem with NP-Hard. The proposed algorithm is a heuristic with edge-swap method. The classical method finds the initial solution starts with first node and visits to mostly adjacent nodes then decides the traveling path. This paper selects minimum weight edge for each nodes, then perform Min-Min method that start from minimum weight edge among the selected edges and Min-Max method that starts from maximum weight edges among it. Then we decide tie initial solution to minimum path length between Min-Min and Min-Max method. To get the final optimal solution, we apply previous two-opt to initial solution. Also, we suggest extended 3-opt and 4-opt additionally. For the 7 actual experimental data, this algorithm can be get the optimal solutions of state-of-the-art with fast and correct.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.77-82
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• 2007

In this paper, we proposed the image processing techniques for extracting the cracks in a concrete surface crack image and the enhanced Max-Min neural network for recognizing the directions of the extracted cracks. The image processing techniques used are the closing operation or morphological techniques, the Sobel masking for extracting for edges of the cracks, and the iterated binarization for acquiring the binarized image from the crack image. The cracks are extracted from the concrete surface image after applying two times of noise reduction to the binarized image. We proposed the method for automatically recognizing the directions of the cracks with the enhanced Max-Min neural network. Also, we propose an enhanced Max-Min neural network by auto-tuning of learning rate using delta-bar-delta algorithm. The experiments using real concrete crack images showed that the cracks in the concrete crack images were effectively extracted and the enhanced Max-Min neural network was effective in the recognition of direction of the extracted cracks.