• Journal of Chest Surgery
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• v.34 no.1
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• pp.1-34
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• 2001

• Journal of Chest Surgery
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• v.33 no.5
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• pp.343-376
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• 2000

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.115-117
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• 2004

Recently, mining far association rules in distributed database environments is a central problem in knowledge discovery area. While the data are located in different share-nothing machines, and each data site grows by time. Mining global frequent itemsets is hard and not efficient in large number of distributed sewen. In many distributed databases. time component(which is usually attached to transactions in database), contains meaningful time-related rules. In this paper, we design a new DTA(distributed temporal association) algorithm that combines temporal concepts inside distributed association rules. The algorithm confirms the time interval for applying association rules in distributed databases. The experiment results show that DTA can generate interesting correlation frequent itemsets related with time periods.

• Genomics & Informatics
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• v.4 no.2
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• pp.65-70
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• 2006

Peptide mass mapping is the matching of experimentally generated peptides masses with the predicted masses of digested proteins contained in a database. To identify proteins by matching their constituent fragment masses to the theoretical peptide masses generated from a protein database, the peptide mass fingerprinting technique is used for the protein identification. Thus, it is important to know the theoretical mass distribution of the database. However, few researches have reported the peptide mass distribution of a database. We analyzed the peptide mass distribution of non-redundant protein sequence database in the NCBI after digestion with 15 different types of enzymes. In order to characterize the peptide mass distribution with different digestion enzymes, a power law distribution (Zipfs law) was applied to the distribution. After constructing simulated digestion of a protein database, rank-frequency plot of peptide fragments was applied to generalize a Zipfs law curve for all enzymes. As a result, our data appear to fit Zipfs law with statistically significant parameter values.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.399-400
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• 2009

As a part of the era of human centric applications people started to care about their well being utilizing any possible mean. This paper proposes a framework for real time on-body sensor health-care system, addresses the current issues in such systems, and utilizes an enhanced online divisive agglomerative clustering algorithm (EODAC); an algorithm that builds a top-down tree-like structure of clusters that evolves with streaming data to rationally cluster on-body sensor data and give accurate diagnoses remotely, guaranteeing high performance, and scalability. Furthermore it does not depend on the number of data points.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.375-376
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• 2009

트리기반 빈발 항목 집합 알고리즘들은 전체적으로 밀집 빈발 항목 집합에는 효율적이고 빠르게 빈발 항목 집합을 탐색하나 희소 빈발 항목 집합에는 효율적이지 않고 빈발 항목 집합을 빠르게 탐색하지 못한다. 반면에 배열기반 빈발 항목 집합 알고리즘은 희소 빈발 항목 집합에 효율적이고 빠르게 빈발 항목 집합을 탐색하나 밀집 빈발 항목 집합에는 효율적이지 않고 빈발 항목 집합을 빠르게 탐색하지 못한다. 밀집 및 희소 빈발 항목 집합 모두 효율적으로 빈발 항목 집합을 탐색 하고자 하는 시도가 있었으나 두 가지 종류의 알고리즘을 동시에 사용하므로 각각의 알고리즘을 사용할 정확한 기준 제시가 어렵고, 두 가지 알고리즘의 단점을 내포한다. 따라서 본 논문에서는 단일 알고리즘을 사용하여 밀집 빈발 항목 집합 및 희소 빈발 항목 집합 모두에 대해 작은 메모리 공간을 사용하면서도 효율적이고 빠르게 빈발 항목 집합을 탐색할 수 있는 CPFP-Tree라는 새로운 자료구조와 탐색 방법을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.902-904
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• 2010

본 논문에서는 개인 특화된 의료를 위한 진단, 치료선택, 예후 추정을 지원하기 위한 정보를 전문 의료인에게 효과적으로 제공하기 위한 데이터베이스 설계와 구축을 제시한다. 내원 환자들의 유전자 수준의 미시 데이터, 임상학적 거시 데이터, 가족력, 유사 질환군 등의 연관정보 데이터를 통합 연계하여 이력으로 관리하고, 데이터의 점진적 누적이 가능한 통합의료시스템을 위한 데이터베이스 설계의 프레임워크를 구축하였다.

• Asian Journal for Public Opinion Research
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• v.7 no.2
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• pp.75-93
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• 2019

Background: Since 2010, Korea has maintained a DNA database of those convicted of or awaiting trial for certain crimes. There have been proposals to expand the list of crimes included in this database, or conversely, omit certain crimes if they are committed during protests. An understanding of the feelings of the public as we consider the ethical, legal, and social aspects of a DNA database and as revisions to laws are made is required. Methodology: Questions related to the DNA database were included in the nationally representative Korean Academic Multimode Open Survey (KAMOS) panel (June-August 2016). Results: Of 2,000 randomly selected panel members, 1,013 respondents participated in this survey, including 89.2% who supported the existence of a criminal DNA database. The current system of storing DNA profiles until a suspect's acquittal or a convict's death was supported by 79.5% of respondents. In addition, 70.8% of respondents agreed with the expansion of crime categories included in the criminal database. Many (93.4%) respondents favored genetic testing and data storage to determine the identity and cause of death for people who die of unnatural causes. Some differences in attitude related to social class were noted, with those who self-identified as members of the upper class more likely to support the database and its expansion to include additional crimes than those who self-identified as middle or lower class. Conclusion: Our findings suggest that Koreans generally support the criminal DNA database.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.372-374
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• 2003

전력 계통에서의 안정적인 전기 공급과 전기 품질 수준의 유지 관리를 위해 전압 측정 Database를 이용한 분석이 필요하게 된다. 본 논문에서는 실 배전 계통에서 측정될 수 있는 RMS 간과 사고 시 전압을 저가형 전력 품질 모니터링 시스템을 통해 서버 컴퓨터로 데이터를 전송하여 Database에 저장 처리 할 수 있는 프로그램을 Delphi 언어로 개발하였다. 이는 구축된 Database를 이용 전력 품질을 분석하고 진단하는데 사용된다.

• Proceedings of the Korean Society of Life Science Conference
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• 2008.10a
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• pp.67.2-67.2
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• 2008