• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2005년도 추계 종합학술대회 논문집
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• pp.371-375
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• 2005

기존 Hybrid P2P 방식에서 사용자가 검색시 예약어 등록 기능을 추가해 사용자가 원하는 컨텐츠를 소유한 피어가 네트워크에 참여했을 시 목록을 비교하여 예약어를 등록한 사용자에게 알람 기능을 제공함으로써 재검색에 소요되는 수고를 덜어 주고자한다.

• 경영과학
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• 제13권3호
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• pp.187-198
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• 1996

The traveling salesman problem has been studied for many years since the model can be used for various applications such as vehicle routing, job sequencing, clustering a data array, and so on. In this paper one of the typical exact algorithms for TSP, Minty's, will be modified to improve the performance of the algorithm on the applications without losing simplicity. The Little's algorithm gives good results, however, the simple and plain Minty's algorithm for solving shortest-route problems has the most intuitive appeal. The suggested Minty's modification is based on the creation of penalty-values on the matrix of a TSP. Computer experiments are made to verify the effectiveness of the modification.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2008년도 한국컴퓨터종합학술대회논문집 Vol.35 No.1 (C)
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• pp.429-434
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• 2008

원하는 정보를 보다 빠르게 찾기 위해서 활용하는 방법 중에 하나가 군집화이다. 군집화를 보다 효과적으로 할 수 있다면, 군집화내에서 원하는 정보를 보다 쉽게 얻을 수가 있다. 따라서, 본 논문에서는 군집화하기 위한 여러 가지 방법 중에서 TSP(Traveling Salesman Problem)을 이용해서 문서를 보다 정교하게 군집화하는 알고리즘을 제안하고, 제한된 알고리즘을 온톨로지 기반으로 실험하여 그 효율성을 입증하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권3호
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• pp.208-215
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• 2016

The lithography hotspot detection process is crucial for semiconductor design development process. But, the lithography hotspot detection using optical simulation method takes much time and it slowdown the layout design development cycle. Though the geometry based approach is introduced as an alternative, it still revealed low detection performance and sophisticated framework. To solve this problem, we introduce a deep convolutional neural network based hotspot detection method. Our method made better results in ICCCAD 2012 dataset. To reach this score, we used lots of technical effort to improve the result in addition to just utilizing the nature of convolutional neural network. Inspection region reduction, data augmentation, DBSCAN clustering helped our work more stable and faster.

• International Journal of Contents
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• 제5권4호
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• pp.55-61
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• 2009

In this paper, we propose a hierarchical method for segmenting a given 3D mesh, which hierarchically clusters sharp vertices of the mesh using the metric of geodesic distance among them. Sharp vertices are extracted from the mesh by analyzing convexity that reflects global geometry. As well as speeding up the computing time, the sharp vertices of this kind avoid the problem of local optima that may occur when feature points are extracted by analyzing the convexity that reflects local geometry. For obtaining more effective results, the sharp vertices are categorized according to the priority from the viewpoint of cognitive science, and the reasonable number of clusters is automatically determined by analyzing the geometric features of the mesh.

• 품질경영학회지
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• 제20권2호
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• pp.129-136
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• 1992

This paper aims to develope an algorithm to minimize the total production time, sum of group formation times and processing times, under the balanced workload among the machines by grouping parts with machine loading in FMS. The algorithm of this study is composed of four step procedures ; (1) Parts grouping by Group Technology(GT) (2) Minimizing total processing time in loading problem (3) Machine workload balancing, including above(2) (4) Group formation time, including above(3) For parts grouping, Rank Order Clustering(ROC) algorithm developed by King(1980) is used and this algorithm is programmed by using the MACRO functions of QUATTRO Pro, one of the spreadsheet packages. The structure for loading model is solved by using the Hyper-LINDO. As a case study, numerical examples are demonstrated to show the effectiveness of the proposed machine loading procedure.

• Communications for Statistical Applications and Methods
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• 제25권5호
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• pp.559-568
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• 2018

Gene classification can involve complex order-restricted inference. Examining gene expression pattern across groups with order-restriction makes standard statistical inference ineffective and thus, requires different methods. For this problem, Roy's union-intersection principle has some merit. The M-estimator adjusting for outlier arrays in a microarray study produces a robust test statistic with distribution-insensitive clustering of genes. The M-estimator in conjunction with a union-intersection principle provides a nonstandard robust procedure. By exact permutation distribution theory, a conditionally distribution-free test based on the proposed test statistic generates corresponding p-values in a small sample size setup. We apply a false discovery rate (FDR) as a multiple testing procedure to p-values in simulated data and real microarray data. FDR procedure for proposed test statistics controls the FDR at all levels of ${\alpha}$ and ${\pi}_0$ (the proportion of true null); however, the FDR procedure for test statistics based upon normal theory (ANOVA) fails to control FDR.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1988년도 전기.전자공학 학술대회 논문집
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• pp.529-532
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• 1988

This paper proposes a graph matching algorithm based on simulated annealing, which assures the globally optimal solution for circuit partitioning for the placement in the rectilinear region occurring as a result of the pre-placement of some macro cells, or onto the nonplanar surface in some military or space applications. The circuit graph ($G_{C}$) denoting the circuit topology is formed by a hierarchical bottom-up clustering of cells, while another graph called region graph ($G_{R}$) represents the geometry of a planar rectilinear region or a nonplanar surface for circuit placement. Finding the optimal many-to-one vertex mapping function from $G_{C}$ to $G_{R}$, such that the total mismatch cost between two graphs is minimal, is a combinatorial optimization problem which was solved in this work for various examples using simulated annealing.

• 전자공학회논문지C
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• 제34C권2호
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• pp.50-60
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• 1997

Reconfiguration of a memory array using spare rows and columns has been known to be a useful technique to improve the yield. When the numbers of spare rows and scolumns are limited, respectively, the repair problem is known to be NP-complete. In this paper, we propose the reconfiguration algorithm for an array of memory cells using faulty cel clustering, which removes rows and columns algrithm is the simplest reconfiguration method with the time complexity of $O(n^2)$, where n is the number of faulty cells, however the repair rate is very low. Whereas the exhaustive search algorithm has a high repair rate, but the time complexity is $O(2^n)$. The proposed algorithm provides the same repair rate as the exhaustive search algorithm for almost all cases and runs as fast as the greedy method. It has the time complexity of $O(n^3)$ in the worst case. We show that the propsed algorithm provides more efficient solutions than other algorithms using simulations.

• KIEE International Transaction on Systems and Control
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• 제2D권2호
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• pp.125-134
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• 2002

This paper proposes a method for identifying temporal pattern clusters to predict events in time series. Instead of predicting future values of the time series, the proposed method forecasts specific events that may be arbitrarily defined by the user. The prediction is defined by an event characterization function, which is the target of prediction. The events are predicted when the time series belong to temporal pattern clusters. To identify the optimal temporal pattern clusters, fuzzy goal programming is formulated to combine multiple objectives and solved by an adaptive differential evolution technique that can overcome the sensitivity problem of control parameters in conventional differential evolution. To evaluate the prediction method, five test examples are considered. The adaptive differential evolution is also tested for twelve optimization problems.