• Title/Summary/Keyword: cluster method

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Discrete Event System with Bounded Random Time Variation (제한된 시간변동을 갖는 시간제약 이산사건시스템의 스케줄링 분석)

  • Kim Ja Hui;Lee Tae Eok
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2002.05a
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    • pp.923-929
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    • 2002
  • We discuss scheduling analysis for a discrete event system with time windows of which firing or holding time delays are subject to random variation within some finite range. To do this, we propose a modified p-lime Petri net, named p+-time Petri net. We develop a condition for which a synchronized transition does not have a dead token, that is, the firing epochs do not violate the time window constraints. We propose a method of computing the feasible range of the token sojourn time at each place based on a time difference graph. We also discuss an application for analyzing wafer residency times within the process chambers for a dual-armed cluster tool for chemical vapor deposition.

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A Robust Behavior Planning technique for Mobile Robots (이동 로봇의 강인 행동 계획 방법)

  • Lee, Sang-Hyoung;Lee, Sang-Hoon;Suh, Il-Hong
    • The Journal of Korea Robotics Society
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    • v.1 no.2
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    • pp.107-116
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    • 2006
  • We propose a planning algorithm to automatically generate a robust behavior plan (RBP) with which mobile robots can achieve their task goal from any initial states under dynamically changing environments. For this, task description space (TDS) is formulated, where a redundant task configuration space and simulation model of physical space are employed. Successful task episodes are collected, where $A^*$ algorithm is employed. Interesting TDS state vectors are extracted, where occurrence frequency is used. Clusters of TDS state vectors are found by using state transition tuples and features of state transition tuples. From these operations, characteristics of successfully performed tasks by a simulator are abstracted and generalized. Then, a robust behavior plan is constructed as an ordered tree structure, where nodes of the tree are represented by attentive TDS state vector of each cluster. The validity of our method is tested by real robot's experimentation for a box-pushing-into-a-goal task.

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Message and Data Passing Method in VIA-based Multimedia Cluster System (VIA기반의 멀티미디어 클러스트 시스템의 데이터를 동반한 메시지 전송 기법)

  • 박시용;박성호;정기동
    • Proceedings of the Korean Information Science Society Conference
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    • 2000.10c
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    • pp.647-649
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    • 2000
  • 본 논문에서는 클러스트의 프로토콜 스택 오버헤드를 줄인 VIA(Virtual Interface Architecture)를 이용한 멀티미디어 클러스트 시스템을 제안하고 제안된 VIA 기반의 멀티미디어 클러스트 시스템의 각 서버들간의 통신 및 데이터 전송을 위한 메시지들을 효율적으로 전송하기 위해서 이중 버퍼를 사용하는 방법을 고려하였다. 그리고 프로토콜 스택 오버헤드를 줄이기 위해서 간단한 프로토콜만을 제공하는 VIA의 명세에서는 제공하지 않는 재전송 메커니즘을 제안하여 시스템의 안정성을 높였다. 본 논문에서 제안한 시스템의 실험 결과 중 버퍼를 이용한 데이터 전송의 경우 순차적인 전송 기법보다 데이터의 양이 많을수록 더 좋은 성능을 보였다. 그리고 적절한 데이터 전송 횟수와 버퍼량을 구하기 위한 실험 결과 총전송량을 10Mbyte로 고정시키고 버퍼의 양과 전송 횟수를 변화시킨 결과 1Mbyte를 10번 전송할 때 보다 0.1Mbyte를 100번 전송할 경우 네트웍 대역폭은 2배 이상 높게 나타났다.

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An Analysis on the factor affecting eMarketing performance with customer activity analysis in Insurance Industry (보험업에서 고객 활동분석이 eMarketing 활동에 미치는 영향도 분석)

  • Yeo, Sung-Joo;Kim, Ji-Won;Lee, Hae-Gu;Wang, Gi-Nam
    • 한국IT서비스학회:학술대회논문집
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    • 2008.11a
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    • pp.112-115
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    • 2008
  • CRM is one of fields that come into the spotlight in academic circles. A Marked changes of business environment makes it get a various information about competitive products unlike in the past and makes it understand the customer needs. Also, Market boundary become to be uncleared. Insurance industry is lied in the age of limitless competition due to uncleared market boundary. Channels for getting customer information and understandings become to be various. In this study, we collect the customer information using various channel and we analyze out a primary factor. Using this results, we present the method that cluster target customers. It is the object of this paper that analyze out the effects when we execute the One-to-One-Marketing using clustered target customer based customer pattern.

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A Study for Time Standard Estimation with Activity Sampling Method (가동샘플링기법에 의한 표준시간추정에 관한 연구)

  • 이근희
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.6 no.9
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    • pp.1-5
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    • 1983
  • This study takes over the application of survey sampling theory to activity sampling and the application of activity sampling to time standard estimation. Cluster, stratified, and multistage sampling are studied in conjunction with random and systematic sampling. Estimation procedures that will maximize the information obtained per cost expended on the study and specification of the procedure to be used to estimate the accuracy of the estimates for the adopted procedure are considered. The use of multiple regression md linear programming to estimate standard element performance time from typical job lot production data is also considered.

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Recovery Method Using Extendable Hashing Based Log in A Shared-Nothing Spatial Database Cluster (비공유 공간 데이터베이스 클러스터에서 확장성 해싱 기반의 로그를 이용한 회복 기법)

  • 장일국;장용일;박순영;배해영
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2004.03a
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    • pp.7-10
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    • 2004
  • 회복기법은 비공유 공간 데이터베이스 클러스터에서 고가용성을 위해 매우 중요하게 고려되고 있다. 일반적으로 데이터베이스 클러스터의 회복기법은 노드의 오류가 발생한 경우 로컬 로그와는 별도로 클러스터 로그를 생성하며, 이를 기반으로 해당 노드에서의 회복과정을 수행한다. 그러나, 기존의 기법은 하나의 레코드를 위해 다수의 갱신정보를 유지함으로써 클러스터 로그의 크기가 증가되고, 전송비용이 증가된다. 이는 회복노드에서 하나의 레코드에 대해 털러 번의 불필요한 연산을 실행하여 회복시간이 증가되고, 전체적인 시스템의 부하를 증가시키는 문제를 발생시킨다. 본 논문에서는 비공유 공간 데이터베이스 클러스터에서 확장성 해싱 기반의 로그를 이용한 회복기법을 제안한다. 제안기법에서의 클러스터 로그는 레코드 키값을 이용한 확장성 해싱을 기반으로 레코드의 변경사항과 실제 데이터를 가리키는 포인터 정보로 구성된다. 확장성 해싱 기반의 클러스터 로그는 크기와 전송비용이 감소하며, 회복노드는 하나의 레코드에 대해 한번의 갱신연산만 실행하므로 빠른 회복이 가능하다. 따라서 제안 기법은 확장성 해싱 기반의 클러스터 로그를 이용하여 효율적인 회복처리를 수행하며, 시스템의 가용성을 향상시킨다.

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A High-Dimensional Index Structure Based on Singular Value Decomposition (Singular Value Decomposition 기반 고차원 인덱스 구조)

  • Kim, Sang-Wook;Aggarwal, Charu;Yu, Philip S.
    • Journal of Industrial Technology
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    • v.20 no.B
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    • pp.213-218
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    • 2000
  • The nearest neighbor query is an important operation widely used in multimedia databases for finding the object that is most similar to a given query object. Most of techniques for processing nearest neighbor queries employ multidimensional indexes for effective indexing of objects. However, the performance of previous multidimensional indexes, which use N-dimensional rectangles or spheres for representing the capsule of the object cluster, deteriorates seriously as the number of dimensions gets higher. This paper proposes a new index structure based singular value decomposition resolving this problem and the query processing method using it. We also verify the superiority of our approach through performance evaluation by performing extensive experiments.

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An Optimal Clustering using Hybrid Self Organizing Map

  • Jun, Sung-Hae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.6 no.1
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    • pp.10-14
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    • 2006
  • Many clustering methods have been studied. For the most part of these methods may be needed to determine the number of clusters. But, there are few methods for determining the number of population clusters objectively. It is difficult to determine the cluster size. In general, the number of clusters is decided by subjectively prior knowledge. Because the results of clustering depend on the number of clusters, it must be determined seriously. In this paper, we propose an efficient method for determining the number of clusters using hybrid' self organizing map and new criterion for evaluating the clustering result. In the experiment, we verify our model to compare other clustering methods using the data sets from UCI machine learning repository.

Twostep Clustering of Environmental Indicator Survey Data

  • Park, Hee-Chang
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.1
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    • pp.1-11
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    • 2006
  • Data mining technique is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. Clustering is the process of grouping the data into clusters so that objects within a cluster have high similarity in comparison to one another. It has been widely used in many applications, such that pattern analysis or recognition, data analysis, image processing, market research on off-line or on-line and so on. We analyze Gyeongnam social indicator survey data by 2001 using twostep clustering technique for environment information. The twostep clustering is classified as a partitional clustering method. We can apply these twostep clustering outputs to environmental preservation and improvement.

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Variance estimation for distribution rate in stratified cluster sampling with missing values

  • Heo, Sunyeong
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.2
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    • pp.443-449
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    • 2017
  • Estimation of population proportion like the distribution rate of LED TV and the prevalence of a disease are often estimated based on survey sample data. Population proportion is generally considered as a special form of population mean. In complex sampling like stratified multistage sampling with unequal probability sampling, the denominator of mean may be random variable and it is estimated like ratio estimator. In this research, we examined the estimation of distribution rate based on stratified multistage sampling, and determined some numerical outcomes using stratified random sample data with about 25% of missing observations. In the data used for this research, the survey weight was determined by deterministic way. So, the weights are not random variable, and the population distribution rate and its variance estimator can be estimated like population mean estimation. When the weights are not random variable, if one estimates the variance of proportion estimator using ratio method, then the variances may be inflated. Therefore, in estimating variance for population proportion, we need to examine the structure of data and survey design before making any decision for estimation methods.