• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.247-249
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• 2004

마이크로어레이 기술은 근래에 개발된 신기술로써 동시에 수천-수만 개의 유전자 발현을 측정할 수 있어 다양한 생물학적 연구에 이용되고 있다. 여러 단계의 실험 과정과 이를 통해 얻은 다량의 데이터를 처리하기 위해서는 이를 효율적으로 관리. 저장, 분석할 수 있는 통할 정보 관리 시스템을 필요로 한다. 현재 외국에서는 몇몇 관리시스템이 개발되어 있고. 국내에서도 WEMA 등이 있지만 아직 데이터 관리부분에 기능이 치우쳐 있다. 따라서 우리는 복잡한 자료구조를 가지는 마이크로어레이의 실험 정보와 각 단계별 처리 정보 등을 사용자의 관점에서 효과적이고 체계적으로 관리할 수 있고, 데이터 정규화 및 다양한 통계적 분석 기능을 갖춰 불필요한 시간과 비용을 줄임으로써 마이크로어레이 연구에 도움을 주고자 통합 분석관리 시스템 cMAMS (cDNA Microarray Analysis and Management System)를 개발하였다. 웹 기반으로 구현된 cMAMS는 데이터를 저장, 관리하는 부분과 데이터를 분석하는 부분, 그리고 모든 관련 점보가 저장되는 데이터베이스 부분으로 구성되어 있다 데이터관리부분에서는 WEMA의 계층적 데이터구조론 도입해 관리의 효율성을 높이고 시스템의 이용자를 시스템운영자, 프로젝트관리자, 일반사용자로 구분하여 데이터 접근을 제한함으로써 보안성을 높였다. 통계처리 언어 R로 구현된 데이터분석 부분은 7 단계의 다양한 분석(전처리 정규화, 가시화, 군집분석. 판별분석, 특이적 발현 유전자 선뿐, 마이크로어레이 간의 상판분석)이 가능하도록 구현하였고, 분석결과는 데이터베이스에 저장되어 추후에 검토 및 연구자간의 공유가 가능하도록 하였다. 데이터베이스는 실험정보가 저장된 데이터베이스, 분석결과가 저장된 데이터베이스, 그리고 유전자 정보 탐색을 위한 데이터베이스로 분류해 데이터를 효율적으로 관리할 수 있게 하였다. 본 시스템은 LiNUX를 운영체계로 하고 데이터베이스는 MYSQL로 하여 JSP, Perl. 통계처리 언어인 R로 구현되었다.

• KOMUNHWA
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• no.70
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• pp.109-132
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• 2007

Taking the Yosu Peninsula where prestige goods were prevalent and more dolmen were excavated and surveyed than other regions as object of the research, this dissertation investigated the hierarchy of dolmen society. The dolmen groups were excavated and surveyed at some 20 positions in Yosu Peninsula Analyzing the number, weight of upper stone, location, the buried relics of dolmen, the hierarchy for each dolmen group can be summarized as follows. It seems that the large group with a lot of dolmen and big upper stone which is located on the plane with stream or on the lower part of hill might be the central group with abundant buried relics. However, the size of individual upper stone does not coincide with buried relics sometimes. Thus, it is required to review the entirety of dolmen group rather than individual upper stone in the relation between the scale of upper stone and buried relics. Then the scale of tomb is proportionate to the prestige goods. Meanwhile, the discrepancy between dolmens can be verified by the difference among upper stone, tomb, burial accessories, etc in the unit dolmen group. Since dolmen is the tomb of some inhabitants in the Bronze Age, the existence of stone coffin tomb with buried bronze sword, jade or stone sword compared to the stone coffin with no relics means that there was powerful representative of one generation even in one kindred group on the basis of wealth or authority. It can be concluded that the upper stone or large tomb or prestige goods among the persons buried in dolmen were fixed as high class, those with relatively small stone coffin with no or scanty burial accessories were fixed as medium class and multitudinous class who were not buried in dolmen were fixed as low class. Therefore, the dolmen society in Yosu Peninsula shows that there was division of class in the unit dolmen group as well as hierarchy in the group.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.1
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• pp.26-41
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• 2012

This study investigates the time-space characteristics of intra-urban passenger flows in the Metropolitan Seoul area. In particular, we analyze the relationships between transit ridership and land use through the use of the subway passenger flow data obtained from the transit transaction databases. For this purpose, the strength of each subway station, i.e., the number of total in-coming and out-going passengers at each station, in the morning, afternoon, and evening, is calculated and visualized, which reflects urban land use patterns. Then the subway stations are classified into four groups via a hierarchical analysis of the in-coming and out-going passenger flows at 353 stations. Each group appears to have characteristic properties according to the region, e.g., residential areas and central business districts. This has been confirmed by the analysis which probes explicitly the relationship between the local socio-economic variables and station groups. This analysis, disclosing the inter-relationship between the subway network and urban land use, may be useful at various stages in urban as well as transportation planning, and provides analytical tools for a wide spectrum of applications ranging from impact evaluation to decision-making and planning support.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1136-1140
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• 2009

지상강우 관측망을 이용한 강우량 측정의 대안으로서 사용되는 기상 레이더를 활용한 강우량 추정의 경우, Z-R 방정식을 이용하여 반사도를 강우량으로 환산하는 방법을 일반적으로 사용한다. 이때 발생하는 각종 오차는 레이더 장비가 가지는 기계적인 오차뿐만 아니라 Z-R 방정식이 가지는 오차 등이 있으며, 이를 보정하기 위해서 레이더를 활용하여 추정된 강우량에 지상강우량계와 레이더강우량과의 비율인 G/R비를 보정하는 방법을 일반적으로 사용한다. 본 연구에서는 이와 같이 레이더 강우량을 보정하기 위해서 사용되는 G/R비를 산정하는데 미치는 지형적인 효과를 고려하기 위해서 광덕산 레이더 유효범위 100km 내(군사분계선 이북 미포함)의 지역에 대하여 군집분석을 실시하여 크게 산악지역과 평야지역으로 구분하고, 각각 구분된 지역에 대하여 G/R 비를 산정하여 초기추정 레이더 강우량에 곱하는 mean-field bias 보정을 실시하였다. 광덕산 레이더 기상관측소의 유효범위 100km 내의 2007년, 2008년 홍수기(6/21${\sim}$9/20)기간 동안 94개 Automatic Weather Station(AWS)지점에 대하여 크게 산악지역과 평야지역으로 지역화 시키는 방법은 비계층적 군집분석 기법 중 fuzzy-c mean 방법을 적용하였다. 또한 광덕산 레이더 반사도 기본 자료는 차폐영역으로 생기는 반사도 데이터 누락을 보완하기 위하여 0도와 1.5도 sweep 합성 10분단위 uf 자료를 사용하였으며, AWS와 보정이 이루어지는 레이더 격자의 크기는 최대 4km${\times}$4km로 선정하였다. 본 연구에 있어서 검증방법은 지역을 구분하기 전과 후를 AWS 실측 관측값과 절대상대오차, 평균제곱근 오차로써 비교하였다.

• Korean Journal of Ecology and Environment
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• v.57 no.2
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• pp.83-91
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• 2024

This study utilizes association rule learning and clustering analysis to explore the co-occurrence and relationships within ecosystems, focusing on the endangered brackish-water snail Clithon retropictum, classified as Class II endangered wildlife in Korea. The goal is to analyze co-occurrence patterns between brackish-water snails and other species to better understand their roles within the ecosystem. By examining co-occurrence patterns and relationships among species in large datasets, association rule learning aids in identifying significant relationships. Meanwhile, K-means and hierarchical clustering analyses are employed to assess ecological similarities and differences among species, facilitating their classification based on ecological characteristics. The findings reveal a significant level of relationship and co-occurrence between brackish-water snails and other species. This research underscores the importance of understanding these relationships for the conservation of endangered species like C. retropictum and for developing effective ecosystem management strategies. By emphasizing the role of a data-driven approach, this study contributes to advancing our knowledge on biodiversity conservation and ecosystem health, proposing new directions for future research in ecosystem management and conservation strategies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5534-5541
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• 2012

This paper classifies cities in the metropolitan area based on natural hazard vulnerability. The procedure of our empirical analysis is divided into three parts as follows: First, it summarizes variables related to natural hazard vulnerability to significant factors, carrying out principal component analysis. Second, it classifies cities in the metropolitan area, conducting cluster analysis using factor scores. Lastly, it proposes differential measures for natural hazard mitigation for classified cities in the metropolitan area, based on natural hazard vulnerability.

• Journal of The Korean Association For Science Education
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• v.6 no.2
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• pp.53-62
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• 1986

본 연구의 목적은 한국 중 고등학교 학생들의 지적 발달의 특성을 조사 분석함으로써 교과서 및 교육과정의 개발에 필요한 기초자료를 얻으려는 것이다. 지역, 학년, 연령, 성 및 가정의 사회 경제적 지위에 따른 인지 발달 특성을 조사하였다. 연구의 대상은 전국을 대도시, 중 소도시, 농촌으로 유층화한 유층군집 표집방법에 의해 표집한 중학교 1학년부터 고등학교 2학년까지의 남 녀 학생이었다. 표집학생 수는 중학교가 18개교 54학급 3,164명이었고, 고등학교가 18개교 36학급 1,981명이었다. 가정의 사회 경제적 지위는 가정의 경제적 형편, 부의 직업, 부의 학력, 가정의 수입 정도를 고려하여 4계층으로 구분하였다. 사용된 도구는 지적 영역의 조사에 Piaget의 인지발달이론에 따른 논리발달 검사를 이용했다. 분석된 결과를 요약하면 다음과 같다. 첫째, 명제논리, 확률논리, 조합논리, 변인조작개념은 연령과 학년이 높아질수록, 대도시로 갈수록, 사회 경제적 지위가 높을수록 더욱 발달하는 경향이다. 둘째, 개념의 발달경향에 있어서 이원추리와 조합논리개념의 발달이 확률논리와 명제논리 개념의 발달보다 빠른 경향이다. 셋째, 한국의 중등학생 중에서 12세의 64.6%, 13세의 58.1%, 14세의 43.8%, 15세의 30.1%, 16세의 22.6%가 구체적 조작 후기에 도달해 있다. 넷째, 중등학생의 학년별 인지발달경향을 보면 중1의 69.8%, 중2의 51.1%, 중3의 47.4%, 고1의 21.6%, 고2의 21.7%가 구체적 후기의 발달수준이다.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.111-125
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• 2011

Clustering is a process of grouping similar or relevant documents into a cluster and assigning a meaningful concept to the cluster. By this process, clustering facilitates fast and correct search for the relevant documents by narrowing down the range of searching only to the collection of documents belonging to related clusters. For effective clustering, techniques are required for identifying similar documents and grouping them into a cluster, and discovering a concept that is most relevant to the cluster. One of the problems often appearing in this context is the detection of a complex concept that overlaps with several simple concepts at the same hierarchical level. Previous clustering methods were unable to identify and represent a complex concept that belongs to several different clusters at the same level in the concept hierarchy, and also could not validate the semantic hierarchical relationship between a complex concept and each of simple concepts. In order to solve these problems, this paper proposes a new clustering method that identifies and represents complex concepts efficiently. We developed the Hierarchical Overlapping Clustering (HOC) algorithm that modified the traditional Agglomerative Hierarchical Clustering algorithm to allow overlapped clusters at the same level in the concept hierarchy. The HOC algorithm represents the clustering result not by a tree but by a lattice to detect complex concepts. We developed a system that employs the HOC algorithm to carry out the goal of complex concept detection. This system operates in three phases; 1) the preprocessing of documents, 2) the clustering using the HOC algorithm, and 3) the validation of semantic hierarchical relationships among the concepts in the lattice obtained as a result of clustering. The preprocessing phase represents the documents as x-y coordinate values in a 2-dimensional space by considering the weights of terms appearing in the documents. First, it goes through some refinement process by applying stopwords removal and stemming to extract index terms. Then, each index term is assigned a TF-IDF weight value and the x-y coordinate value for each document is determined by combining the TF-IDF values of the terms in it. The clustering phase uses the HOC algorithm in which the similarity between the documents is calculated by applying the Euclidean distance method. Initially, a cluster is generated for each document by grouping those documents that are closest to it. Then, the distance between any two clusters is measured, grouping the closest clusters as a new cluster. This process is repeated until the root cluster is generated. In the validation phase, the feature selection method is applied to validate the appropriateness of the cluster concepts built by the HOC algorithm to see if they have meaningful hierarchical relationships. Feature selection is a method of extracting key features from a document by identifying and assigning weight values to important and representative terms in the document. In order to correctly select key features, a method is needed to determine how each term contributes to the class of the document. Among several methods achieving this goal, this paper adopted the $x^2$�� statistics, which measures the dependency degree of a term t to a class c, and represents the relationship between t and c by a numerical value. To demonstrate the effectiveness of the HOC algorithm, a series of performance evaluation is carried out by using a well-known Reuter-21578 news collection. The result of performance evaluation showed that the HOC algorithm greatly contributes to detecting and producing complex concepts by generating the concept hierarchy in a lattice structure.

• Journal of Convergence for Information Technology
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• v.11 no.2
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• pp.130-137
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• 2021

The purpose of this study is to explore methods to prevent and improve the problem of overdependence on smartphones by analyzing the differences in satisfaction with college life satisfaction of freshmen. For this, data on freshmen of KCYPS were extracted and used. The data were analyzed using non-hierarchical cluster(K-means) analysis, T-test, one-way ANOVA, and Scheffé tests. The results of this study are as follows. First, it has been shown that freshmen who are overdependent on smartphones experience inconvenience in their daily life, withdrawal and anxiety, and resistance. Second, there is no significant difference in the level of satisfaction with college life according to gender(t=-.015, p<.05). Third, it is shown that the level of satisfaction with college life of overdependent freshmen on smartphone is significantly lower compared to that of average and moderate dependent freshmen. Based on the results, it was suggested that university-level efforts such as emotional support and learning strategy support are needed for freshmen who are overdependent on smartphones.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.110-118
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• 2020

Social media data serves as a proxy indicator to understand the problems and the future of public opinion in Korean society. This research used 109,015 news data from 2016 to 2018 to analyze the sensitivity of the elderly and employment in Korean society, and explored the possibility of expanding the labor force in Korean society, which is facing a cliff between the elderly and the population. Topic keywords for employment of the elderly include "elderly*employment", "elderly*employment", and "elderly*wage". As a result of the analysis, positive sensitivity prevails for most of the period, and it is possible to expand the working-age population. Positive feelings about expanding employment opportunities for the elderly and negative feelings about low wages have brought to light the reality of the elderly who are still poor despite their work. In this study, social big data was used to analyze the perceptions and sensibilities of Korean society related to the elderly and employment through hierarchical crowd analysis and related text mining analysis.