• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2000년도 춘계공동학술대회 논문집
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• pp.107-110
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• 2000

화학 박막 증착용(CVD : Chemical Vapor Deposition) 클러스터 장비는 다양한 공정 경로가 가능하며 물류 흐름이 매우 복잡해질 수 있다. 또한, 공정이 종료된 웨이퍼는 제한 시간 내에 챔버에서 꺼내져야만 한다. 클러스터 장비는 두 개의 팔을 가진 로봇이며, 빈 쪽 팔을 이용하여 공정이 종료된 웨이퍼를 꺼낸 후, 다른 쪽 팔을 이용하여 이전 공정에서 가져온 웨이퍼를 해당 공정에 넣어 주는 스왑(SWAP) 방식으로 운영된다. 이러한 스왑 방식에서는 로봇 작업 순서가 결정되어 진다. 그러나, 로봇의 팔 이외에 임시버퍼가 없고, 각 챔버는 엄격한 체제 시간 제약(Residency Time Constraint)을 가지고 있기 때문에 로봇의 작업 시점의 제어가 필요하다. 본 논문에서는 간단한 Earliest Starting 방식으로 로봇의 작업 시점을 제어한다고 가정했을 때, 스왑 방식을 운용하면서 체제 시간 제약을 만족하는 공정 시간들의 조건을 제시한다. 공정 시간은 엔지니어에 의해 다소 조정이 가능하므로 공정 시간들의 조건은 엔지니어에게 스케줄 가능한 공정 시간을 결정할 수 있도록 지원해 주는 시스템에 활용 가능하다. 또한, 본 논문에서는 FSM(Finite State Machine)을 이용하여 CTC(Cluster Tool Controller) 내부의 실시간 스케줄러 구현 방법을 제안한다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 컴퓨터소사이어티 추계학술대회논문집
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• pp.45-48
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• 2003

We can easily buy network system for high performance micro-processor, progress computer architecture is caused of high bandwidth and low delay time. Coupling PC-based commodity technology with distributed computing methodologies provides an important advance in the development of single-user dedicated systems. Lately Network is joined PC or workstation by computers of high performance and low cost. Than it make intensive that Cluster system is resembled supercomputer. Unix, Linux, BSD, NT(Windows series) can use Cluster system OS(operating system). I'm chosen linux gain low cost, high performance and open technical documentation. This paper is benchmark performance of Beowulf clustering by UltraSPARC-1K(64bit-RISC processor). Benchmark tools use MPI(Message Passing Interface) and NetPIPE. Beowulf is a class of experimental parallel workstations developed to evaluate and characterize the design space of this new operating point in price-performance.

• 한국정밀공학회지
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• 제28권4호
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• pp.404-409
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• 2011

Report on the notion of uncertainty is important. The reason is that the measured value includes a lot of uncertain factors. Reliable results can't be derived without the notion of uncertainty. The mathematical model to evaluate uncertainty considering the quality of vibration is important to evaluate uncertainty, and it must contain the every quantity which contributes significantly to uncertainty in the measured results. In this paper, the evaluation of uncertainty analysis about rotor vibration measurements of machine tools is presented to evaluate the most important factors of uncertainty.

• 산업클러스터
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• 제3권1호
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• pp.26-38
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• 2009

많은 지역개발 관련 정책결정자들이 클러스터 이론과 분석을 지역경제개발을 위한 일반적인 어프로치로 이해하는 경우가 많다. 이러한 관점은 흔히 정책결정자들로 하여금 실제 자신들의 지역이 처한 고유한 환경과 도전을 무시한 일률적인 정책 개입을 야기시킨다. 본 연구는 지역개발 정책에 있어 이론 뿐 아니라 경험과 직관, 분석 등을 종합적으로 중시하는 전략기획의 중요성에 초점을 맞추고 있다. 클러스터 이론과 분석은 이러한 전략기획의 과정에서 유용한 정보를 제공한다. 그러나 이것이 전략기획 과정을 아우르는 유일한 프레임이 되어서는 안된다는 점을 유념할 필요가 있다.

• 대한가정학회지
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• 제48권8호
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• pp.1-12
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• 2010

The purpose of this study was to explore and examine the relationship between mother-child emotional availability and preschoolers' story stem narrative response. Eighty two 4-year-old preschoolers and their mothers participated in this study. This study used the following translated evaluation tools: Emotional Availability Scales(EA, 3rd edition) designed by Biringen and colleagues(1998) to examine the quality of the emotional relationship between mother and her child, and the MacArthur Story Stem Battery(MSSB) developed by Bretherton and colleagues with the MacArthur Narrative Group(1990) to measure preschoolers' narrative responses. The following statistical analyses were preformed descriptive, cluster analysis, and One-way ANOVA. The findings were as follows: First, 4 clusters of the narrative responses of 4-year-old preschoolers were prosocial story tellers, avoidant/dysregulated story tellers, constrained story tellers, and anxious story tellers. Second, the preschoolers in the prosocial cluster showed a high level of mother-child emotional availability and the preschoolers in the avoidant/dysregulated cluster showed a low level of mother-child emotional availability.

• Communications for Statistical Applications and Methods
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• 제8권3호
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• pp.643-650
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• 2001

Some classical plots like scatterplot matrices and parallel coordinates are valuable tools for data visualization. These tools are extensively used in the modern data mining softwares to explore the inherent data structure, and hence to visually classify or cluster the database into appropriate groups. However, the interpretation of these plots are very sensitive to the arrangement of variables. In this work, we introduce two methods to arrange the variables for data visualization. First method is based on the work of Wegman (1999), and this is to arrange the variables using minimum distance among all the pairwise permutation of the variables. Second method is using the idea of principal components. We Investigate the effectiveness of these methods with parallel coordinates using real data sets, and show that each of the two proposed methods has its own strength from different aspects respectively.

• Genomics & Informatics
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• 제4권4호
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• pp.173-181
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• 2006

Pattern finding is one of the important tasks in a protein or DNA sequence analysis. Alignment is the widely used technique for finding patterns in sequence analysis. BLAST (Basic Local Alignment Search Tool) is one of the most popularly used tools in bio-informatics to explore available DNA or protein sequence databases. BLAST may generate a huge output for a large sequence data that contains various sequence patterns. However, BLAST does not provide a tool to summarize and analyze the patterns or matched alignments in the BLAST output file. BLAST lacks of general and robust parsing tools to extract the essential information out from its output. This paper presents a pattern summary system which is a powerful and comprehensive tool for discovering pattern structures in huge amount of sequence data in the BLAST. The pattern summary system can identify clusters of patterns, extract the cluster pattern sequences from the subject database of BLAST, and display the clusters graphically to show the distribution of clusters in the subject database.

• Communications for Statistical Applications and Methods
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• 제16권6호
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• pp.959-969
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• 2009

결정나무는 데이터마이닝에서 데이터를 분류하는 기법으로 가장 많이 사용되고 있으며, 데이터 탐색 소프트웨어 DAVIS에서는 동적 기능을 사용하여 데이터 시각화를 하는 것이 가능하다. 본 논문에서는 동적 데이터 분석의 기본 원리와 이를 결정나무에 적용하는 방법을 소개하고, 생성되는 동적 결정나무의 효율성과 유용성을 실제 데이터를 사용하여 분석한다.

• 산업기술연구
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• 제20권B호
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권10호
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• pp.3571-3587
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• 2021

For accurately analysing and forecasting the social networks of China's political, economic and social power elites, it is necessary to develop a database that collates their information. The development of such a database involves three stages: data definition, data collection and data quality maintenance. The present study recommends distinctive solutions in overcoming the challenges that occur in existing comparable databases. We used organizational and event factors to identify the Chinese power elites to be included in the database, and used their memberships, social relations and interactions in combination with flows data collection methodologies to determine the associations between them. The system can be used to determine the optimal relationship path (i.e., the shortest path) to reach a target elite and to identify of the most important power elite in a social network (e.g., degree, closeness and eigenvector centrality) or a community (e.g., a clique or a cluster). We have used three social network analysis tools (i.e., R, UCINET and NetMiner) in order to find the important nodes in the network. We compared the results of centrality rankings of each tool. We found that all three tools are providing slightly different results of centrality. This is because different tools use different algorithms and even within the same tool there are various libraries which provide the same functionality (i.e., ggraph, igraph and sna in R that provide the different function to calculate centrality). As there are chances that the results may not be the same (i.e. centrality rankings indicating the most important nodes can be varied), we recommend a comparison test using different tools to get accurate results.