• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.288-291
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• 2010

본 연구에서는 한강유역 109개 지점의 강우관측소에서 관측된 지속기간별 연최대강우량을 산정하고 지역빈도해석을 적용하기 위하여 한강유역에 대하여 지역구분을 실시하였다. 지역구분은 군집분석 방법인 Ward 방법, 평균연결법, Fuzzy-c means 방법, Two-Step 방법을 적용하였으며 군집분석을 수행하기 위해서 한강유역의 지점별 기상학적 인자와 지형학적 인자를 이용하여 군집분석을 수행하였다. 그 중 Fuzzy-c means 방법을 이용한 지역구분이 적합한 것으로 나타났다. 또한 모든 지속기간에 대하여 적합성 척도를 산정한 결과 GLO 분포형이 적정분포형으로 나타났으며, 지역빈도해석 방법인 지수홍수법을 이용하여 산정한 확률강우량과 지점빈도해석으로 산정한 확률강우량과 비교하여 적용성을 판단하였다.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.541-548
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• 2014

In this paper, we introduce a second version of modified binary particle swarm optimization using a concept of genotype-phenotype in genetic algorithms. Particle swarm optimization uses an information of difference between a position of the best solution and one's own position in the process of searching optimum. To obtain this difference of positions, the first version of modified binary particle swarm optimization uses a phenotype but the proposed second version uses a genotype. We can represent the solution space in large search space by using a genotype which provides continuous whole space as search space compared to a phenotype which provides only binary information. Experimental results in 10 De Jong benchmark function show that the second version outperforms the first version in six functions which has a broad search space and many local optima.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.63-66
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• 2003

본 논문에서는 범주형(categorical) 데이터의 분류를 위한 새로운 기법을 제시한다. 기존의 대표적인 퍼지 군집화 방법인 fuzzy k-modes 알고리즘은 군집 (cluster)의 중심을 단일값으로 표현한 반면, 제안하는 기법에서는 이를 퍼지값으로 정의한다. 이와 같은 퍼지 중심 표현기법을 도입함으로써 범주형 데이터의 분류시에 발생하는 불확실성을 최소화할 수 있다. 기존의 대표적인 방법들과의 비교실험으로 통해 제안한 방법의 성능을 검증하였다.

• The Korean Journal of Applied Statistics
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• v.19 no.2
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• pp.271-282
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• 2006

The aim of this study is to propose a tree-structured clustering for mixed data. We suggest a scaling method to reduce the variable selection bias among categorical variables. In numerical examples such as credit data, German credit data, we note several differences between tree-structured clustering and K-means clustering.

• Journal of Convergence for Information Technology
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• v.10 no.12
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• pp.126-131
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• 2020

This study analyzed the inflow and outflow patterns of emergency department patients, to identify changes in regional types in cities, counties, and districts in Jeonlado, Korea. Data of areas in Jeonlado for 2014 to 2018 were extracted from the National Emergency Department Information System. The extracted data includes the patients' and emergency medical institution addresses, which were used to calculate the relevance index (RI) and commitment index (CI). The calculated indices were classified into regional types by applying cluster analysis. A non-parametric method, Kruskal-Wallis test, was employed to examine the differences between years for RI and CI by regional types. The results of cluster analysis using the relevance and commitment indices revealed three regional types. Regions in cluster 1 were classified as outflow type, in cluster 2 as inflow type, and in cluster 3 as self-sufficient. RI and CI were calculated for each cluster or regional type. There were no significant differences between years in cluster 2 (inflow type) and cluster 3 (self-sufficient type). In cluster 1 (outflow type), there were no significant differences in CI between the years; however, there were significant differences in RI between 2014 and 2017, and 2014 and 2018. It is difficult to see that the emergency medical environment has improved due to the increased concentration of emergency medical care.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.12
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• pp.981-988
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• 2021

This paper presents a decentralized guidance algorithm for swarm flight of fixed-wing UAVs (Unmanned Aerial Vehicles). Considering swarm flight missions, we assume four representative swarm tasks: gathering, loitering, waypoint/path following, and individual task. Those tasks require several distinct maneuvers such as path following, flocking, and collision avoidance. In order to deal with the required maneuvers, this paper proposes an integrated guidance algorithm based on vector field, augmented Cucker-Smale model, and potential field methods. Integrated guidance command is synthesized with heuristic weights designed for each guidance method. The proposed algorithm is verified through flight tests using up to 19 small fixed-wing UAVs.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.24 no.1
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• pp.128-138
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• 2019

Effects of feeding type and food resource availability on community structure of mollusks inhabiting hard-bottom subtidal areas were investigated. By following guidance from several references, mollusks observed in this study were divided into 5 groups according to feeding type - 1) grazing, 2) filter feeding, 3) deposit feeding, 4) omnivorous and 5) predation. The results showed that both grazing and filter feeders were the most numerous, explaining grazing type in the East Sea accounting for 47.9%, 32.6% in the South Sea and 29.6% for filter feeding, and filter feeding as a dominant feeding type in Yellow Sea accounting for 42.3%. Results of this study showed distinctive difference in community structure depending on mechanism of feeding type and geographical areas where sampling took place. With the results, attempts were made to understand whether community structure could be affected by feeding type or feeding availability and found out that community structure depended heavily on food resource availability. In the East Sea where marine algal density was high, the algal community in the forms of thick-leathery and sheet often occurred in water column with high transparency which provides proper environment for growth. In the South Sea where grazing and filter feeding types were predominated similarly, the algal density was high, but had the relative highest phytoplankton density. Whereas in the Yellow Sea showing the lowest algal biomass compared to the one in the East and the South Sea, and phytoplankton density was similar to those. It might be a adequate environment for filter feeders than grazers. This study concluded that community structure of mollusks showing high abundance was present where food resource availability with types and quantity was high.

• Culinary science and hospitality research
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• v.17 no.2
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• pp.74-84
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• 2011

The purpose of this study is to understand the relationship between educational environment services offered and student satisfaction with them. A survey was conducted to 314 students in a cooking and food service program. To achieve the purpose of this study, SPSS 17.0, a statistics program, was used for a descriptive analysis, a frequency analysis, a factor analysis, a multiple regression analysis, a cluster analysis and a One-Way ANOVA analysis. The hypothesis test result of the effect of educational environment services on satisfaction showed that there was a partially significant effect in satisfaction with facilities and lecturers(p<0.01) as well as administrative services (p<0.01). In the cluster analysis of educational environment services, cluster 1 was classified as a mistry cluster, cluster 2 as a satisfied cluster, cluster 3 as a dissatisfied cluster and cluster 4 as a positive cluster. They showed a statistically meaningful result in the one-way ANOV A(p<0.01).

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2006.06a
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• pp.463-484
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• 2006

본 연구는 많은 기업들이 SCM의 중요성을 인식하고 도입하여 활용을 하고 있는 정보시스템의 발전 단계에서 공급사슬에 참여하고 있는 기업이 어떻게 SCM을 활용하고 있는지에 초점을 둔 연구라 할 수 있다. 기존 연구에서 도출한 SCM 활용 목적에 대한 설문 항목을 중심으로 기업이 활용하고 있는 SCM 활용 패턴을 도출하였다. 군집 분석 방법을 활용하여 집단에 특성을 배정하여 동일 집단에 속한 대상의 유사성을 갖게 함으로써 집단 간의 차이를 명확하게 하였다. 군집 분석 결과 효율성을 추구 형, 군집, Business process 정확성 추구형 집단과 환경 변화 대응 추구형 군집으로 패턴을 나눌 수 있었다. 응답 기업을 Miles와 Snow의 전략유형으로 분류하여 응답 기업의 전략 유형을 판별한 결과 분석자형 40.6%, 방어자형 15.1%, 공격자형 37.2%, 반응자형 6.9%로 조사되었다. 위에서 유형화한 SCM의 활용 패턴과 전략유형을 Matrix화하여 가설인 SCM 활용 패턴과 전략유형의 적합도와 SCM 성과 만족도와의 관계를 검증하였다. 연구를 수행한 결과 기업이 SCM을 활용할 때, SCM 활용 패턴 및 전략 유형에 따라 SCM 성과 만족도가 다르게 나타난다는 것을 알 수 가 있다.

• The Journal of Korean Association of Computer Education
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• v.22 no.5
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• pp.51-65
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• 2019

This study aims to provide educational implications for more strategic online software education by the types of online learning according to learners' self-regulated learning characteristics in the online software education environment and examining the characteristics of each type. For this, variables related to self-regulated learning characteristic were extracted from the log data of 809 students participating in the online software learning program of K University, and then analyzed using hierarchical cluster analysis. Based on hierarchical cluster analysis learner clusters according to the characteristics of self-regulated learning were derived and the differences between learners' learning characteristics and learning results according to cluster types were examined. As a result, the types of self-regulated learning of online software learners were classified as 'high level self-regulated learning type (group 1)', 'medium level self-regulated learning type (group 2)', and 'low level self-regulated learning type (group 3)'. The achievement level was found to be highest in 'high-level self-regulated learning type (group 1)' and 'low-level self-regulated learning type (group 3)' was the lowest. Based on these results, the implications for effective online software education were suggested.