• Journal of Korean Academy of Nursing
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• v.39 no.2
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• pp.217-228
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• 2009

Purpose: Guided by Newman's theory of health as expanding consciousness, this study was done to explore the health experience of adolescents having depression. Methods: The researcher engaged in six to eight in-depth interviews with six adolescents. To begin the dialog, the researcher asked each participant to recount the first important memory he/ she had. All the narrative and diagram sharing between the researcher and participants were summarized according to recognized patterns and later elaborated in following interviews based on Newman's praxis methodology. Results: The significant individual pattern of early health experience was during the binding stage. At the turning point, individual patterns for participants revealed a personal journey of self-discovery and then emergence of reflecting behaviors. After the turning point, the participants changed as they evolved from the initial period of disruption and disorganization to organization at a higher level. The results suggest that adolescents who are depressive find new ways of relating to friends, family, healthcare providers, and the community by expanding their consciousness. Conclusion: Newman's praxis methodology is a good way of helping and studying adolescents with depression because it emphasizes participant-nurse/researcher partnership and pattern recognition as nursing practice.

• Journal of the Korean Data and Information Science Society
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• v.20 no.1
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• pp.109-115
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• 2009

Many internet companies are holding marketing activity through customer relationship management to satisfy complicated and diversified consumer demands. Use of customer lifetime value as a marketing metric tends to place greater emphasis on customer service and long-term customer satisfaction, rather than on maximizing short term sales. And so many internet companies have been interested in customer lifetime value, which is a primary key for discovery customer values to promote the competitive power in their business fields. In this paper, we apply a life table technique to lifetime analysis of internet site customers by membership pattern and provide the opportunity using revised life tables in several kinds of internet companies.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.760-765
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• 2006

디자인 패턴의 사용은 시스템을 좀 더 유연하고, 이해하기 쉽고, 재사용 가능하게 만든다. 개발이 완료된 시스템이 명확하게 문서화가 되어 있으면, 시스템의 내부 구조를 이해하기 쉽고, 향후 유지 보수의 비용이 적게 든다. 하지만, 대부분 시스템의 경우 개발된 시스템의 문서화가 잘 되어 있지 않기 때문에, 시스템에 문제가 생겨 수정 하고자 하거나, 새로운 모듈을 추가하여 시스템의 기능을 확장하고자 할 때, 전체 소스코드를 분석하여 시스템을 이해해야 하는 어려움이 있다. 이러한 문제점을 해결하기 위해서 소스코드에서 자동적으로 디자인 패턴을 인식하여 문서화를 증진시킬 수 있다. 따라서 신뢰할 만한 디자인 패턴 인식 시스템이 중요하다. 지금까지 디자인 패턴 인식 방법은 시스템의 구조적인 특징만을 이용하여 패턴을 인식하여 왔다. 그래서 본 논문은 구조적인 특징뿐만 아니라 동적인 분석, 그리고 자동학습(machine learning)에 기반하여 소스코드로부터 디자인 패턴을 인식하는 방법을 제안하고자 한다. 그리고 전 작업에서 만든 자바로 쓰여진 에이전트 개발 툴을 대상으로 실시하여 인식한 디자인 패턴에 대한 평가를 하였다.

• Journal of the Korean Data and Information Science Society
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• v.16 no.3
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• pp.529-538
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• 2005

Data mining is the method to find useful information for large amounts of data in database. It is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are association rules, decision tree, clustering, neural network and so on. Association rule mining searches for interesting relationships among items in a riven large data set. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. There are three primary quality measures for association rule, support and confidence and lift. We analyze Gyeongnam social indicator survey data using association rule technique for environmental information discovery. We can use to environmental preservation and environmental improvement by association rule outputs.

• 한국경영정보학회:학술대회논문집
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• 2008.06a
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• pp.153-170
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• 2008

Customers' needs change every moment. Profitability of stores can't be increased anymore with an existing standardized chain store management. Accordingly, a personalized store management tool needs through prediction of customers' preference. In this study, we propose a recommending procedure using dynamic customers' preference by analyzing the transaction database. We utilize self-organizing map algorithm and association rule mining which are applied to cluster the chain stores and explore purchase sequence of customers. We demonstrate that the proposed methodology makes an effect on recommendation of products in the market which is characterized by a fast fashion and a short product life cycle.

• The KSFM Journal of Fluid Machinery
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• v.6 no.4 s.21
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• pp.58-65
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• 2003

Stall inception means the phenomena of rotating stall initiation. The initiation mechanism of rotating stall, the existence of stall precursor, the behavior of stall precursor, stall warning scheme and control scheme are the main interests in stall inception research. Compared to the studies on rotating stall which has long history, the stall inception has been studied for about recent 20 years. After the first discovery of stall precursor in about 20 years ago, many studies were reported on stall inception phenomena. The inception pattern of 'mode' and 'spike' were found, and some of its characteristics are known. And now the stall inception has become one of the fascinating fields in turbomachinery. The development stall control scheme which apply the reliable stall warning scheme will play a great role in future compressor and aeroengine. This paper reviews the results and analysis methods on stall inception studies.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.427-430
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• 2006

Clustering for gene expression data without filtering out noise genes may be distorted or derived inappropriate inference. Identifying significant genes and deleting noise before major analysis is necessary fur meaningful discovery from genes expression pattern. We proposed a new method of finding significant genes using factor analysis which is done on transposed data matrix. We construct significance score that is sum of factor loadings for declared significant number of factor, and set threshold through replication. Our proposed method works well for simulated time-course data for finding significant genes even though variance level gets larger.

• Journal of Korean Medical classics
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• v.26 no.4
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• pp.89-94
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• 2013

Objective : To collect cosmetology text in Shang Han Za Bing Lun(伤寒杂病论), to analyze theory and prescription about cosmetology before HAN(漢) dynasty, so to allow records for modern cosmetology of Traditional Chinese Medicine. Method : Through the systematize for all terms about cosmetology, to reveal the regularity about cosmetology before HAN(漢) dynasty. Result : There were damage-appearance disease in HAN(漢) dynasty, there are lots of ideas about cosmetology in Shang Han Za Bing Lun(伤寒杂病论). Conclusion : Shang Han Za Bing Lun(伤寒杂病论) is a monograph about pattern identification and treatment, and is an important ancient book for research of cosmetology of Traditional Chinese Medicine. In the further, we will research in knowledge discovery about cosmetology of Traditional Chinese Medicine. to strengthen the guidance of the theory of Zhang Zhongjing(张仲景) for clinical practice of cosmetology of Traditional Chinese Medicine.

• 한국데이터정보과학회:학술대회논문집
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• 2004.10a
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• pp.115-124
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• 2004

Data mining is the method to find useful information for large amounts of data in database. It is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are association rules, decision tree, clustering, neural network and so on. Association rule mining searches for interesting relationships among items in a given large data set. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. There are three primary quality measures for association rule, support and confidence and lift. We analyze Gyeongnam social indicator survey data using association rule technique for environmental information discovery. We can use to environmental preservation and environmental improvement by association rule outputs.

• Korean Journal of Biological Psychiatry
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• v.8 no.2
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• pp.203-207
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• 2001

The genome sequencing project has generated and will continue to generate enormous amounts of sequence data including 5 eukaryotic and about 60 prokaryotic genomes. Given this ever-increasing amounts of sequence information, new strategies are necessary to efficiently pursue the next phase of the genome project-the elucidation of gene expression patterns and gene product function on a whole genome scale. In order to assign functional information to the genome sequence, DNA chip(or gene microarray) technology was developed to efficiently identify the differential expression pattern of independent biological samples. DNA chip provides a new tool for genome expression analysis that may revolutionize many aspects of biotechnology including new drug discovery and disease diagnostics.