• Korean Journal of Environmental Biology
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• v.17 no.4
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• pp.521-527
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• 1999

To investigate the variations of environmental and microbial populations in six stations at water region of Gangjin Bay, nutritive salts, water temperature, COD, DO, pH, heterotrophic bacteria, fungi and facal coliform bacteria were analysed four imes from February to November, 1998. These data were subjected to simple statistics, correlation analysis and principal factor analysis. Ecosystem of Gangiin Bay was regulated by 2∼4 factors during four seasons. We estimated that it was mainly influenced by inflow of fresh water, nutrient salts, suspended solids, salinity and variation of water temperature. These results suggested that influences of environmental factor of Gangiin Bay was relatively less than those of other bays.

• Proceedings of the KSEEG Conference
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• 2007.04a
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• pp.549-551
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• 2007

• Korean Journal of Construction Engineering and Management
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• v.12 no.5
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• pp.127-136
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• 2011

The purpose of this study is analyzed the importance ratio factors of sales price for apartment building construction projects. For this Study, Nine apartment buildings that sold in Seoul, Gyenggi, Chuncheong is selected. The study suggested eight influence factors through interview with experts, research related references, and analysis of cases. Based on those factors, Importance analysis is performed by using AHP method. The result of this study are as follows: 1) Influence factors of sales price are drawn as cost, site, housing, transportation, region, ground, policy, investment factor. 2) In the case of Seoul, The priority order of price influence factors consist of investment factor(16.0%), policy factor(14.6%), and cost factor(13.9%). In the case of Gyenggi, The priority order of sales price influence factors consist of region factor(15.9%), transportation factor(13.8%), and investment factor(13.4%). In the case of Chungcheong, The priority order of sales price influence factors consist of region factor(17.1%), transportation factor(16.4%), and housing factor(14.9%).

• Journal of Korean Society of Forest Science
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• v.59 no.1
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• pp.1-8
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• 1983

Classification on the group of Salix pseudo-lasiogyne growing in Korea, was conducted using cluster analysis, factor analysis, and principal component analysis. Thirty-six characters(Table 2) of the 5 basis species were measured. The phenograms and ordination plot showing the relationships between the species were made by applying the cluster analysis and principal component analysis. Five important factors, such as leaf blade width, number of right serration, angle of leaf apex, number of flowers in an ament, and the ratio of petiole length to width, were inferred from the rotated factor matrix, and their state values were presented in polygonal diagram. Salix pseduo-lasiogyne and S. babylonica were similarly correlated and linked in one group, S. dependens and S. matsudana for tortuosa were secondarily linked in the other group. S. koreensis appeared as an aliemated species from each of the two groups.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.4
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• pp.24-29
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• 2020

Measuring the torque of the wheel loader of a driving device is a preemptive task to ensure its performance. In this study, wireless torque measurements were successfully conducted. Moreover, based on the experimental results and the adopted design method, the key factor of torque generation, which is the main load in driving devices, was analyzed. Other data not analyzed in this paper will be the basis for the logical design of wheel loader-based driving devices.

• The Journal of the Korea Contents Association
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• v.7 no.9
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• pp.127-138
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• 2007

Due to the development of internet technology and the steady increase of turnover at B2C market many companies put a lot of work into maintaining a good relationship with internet customers. Particularly, analyzing and understanding specific customer groups are essential for effective CRM and marketing strategy Thus, this paper proposes the method to define the customers of online bookstore into several meaningful groups. Five important factors and factor scores for each respondent are obtained by Factor Analysis. Six groups are classified by Cluster Analysis and Analysis of Variance(ANOVA) is used to verify the difference between each group.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.107-109
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• 2021

본 연구는 당뇨병 환자의 자기조절에 대한 주관적 유형과 특성을 분석하고자 시도되었으며, 당뇨병 환자의 주관성을 연구하는데 효과적인 Q방법론을 적용하였다. 대상자는 제2형 당뇨병을 진단받은 사람으로서 경구약이나 인슐린 주사로 치료받고 있으나 현재는 입원한 싱태가 아닌 사람 38명으로 구성하였으며, Q표본 40개의 진술문을 가장 부정(-4)에서 가장 긍정(+4) 범위의 9점 척도 상에 분류하도록 하였다. Q분류된 자료는 QUANL PC program을 이용하여 주요인분석(principal component factor analysis)과 배리맥스 회전(varimax rotation)을 통해 Q 요인분석이 행해졌다. 분석결과 당뇨병환자 자기조절에 대학여 제 1유형은 근거기반 순응형, 제2유형은 위기의식 자립거부형, 제3유형은 정보기반 관계지향형, 제4유형은 자기신뢰 실천형, 제5유형은 주관적 결핍 기반 반응 행동형으로 5가지 유형의 관점을 보여주었다. 따라서 당뇨병 환자 효율적 관리방법을 위해 당뇨병 환자의 질병 관리의 부정적 행위 성향을 이해하고, 당뇨지식 교육, 당뇨관리 정보 및 긍정적 심리를 통한 자기조절 프로그램을 개발 할 필요가 있다.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.373-384
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• 2014

Data mining is to clarify pattern or correlation of mass data of complicated structure and to predict the diverse outcomes. This technique is used in the fields of finance, telecommunication, circulation, medicine and so on. In this paper, we selected risk factors of respiratory diseases in the field of medicine. The data we used was divided into respiratory diseases group and health group from the Gyeongsangbuk-do database of Community Health Survey conducted in 2012. In order to select major risk factors, we applied data mining techniques such as neural network, logistic regression, Bayesian network, C5.0 and CART. We divided total data into training and testing data, and applied model which was designed by training data to testing data. By the comparison of prediction accuracy, CART was identified as best model. Depression, smoking and stress were proved as the major risk factors of respiratory disease.

• The Journal of the Korea Contents Association
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• v.12 no.11
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• pp.338-357
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• 2012

This study investigated any possible financial attributes of the CDS spreads of a firm belonging to financial industries headquartered in the Republic of Korea. There were few studies on this issue, especially for the firms located in emerging capital markets. Coupled with the models such as a multiple regression and a principal component analysis(PCA), this research has identified that only two explanatory variables such as SLOPE and INTER3 (i.e. interaction effect between the BETA and the SLOPE) consistently showed their statistically significant influence on the CDS spreads through the 'selected' model without and with applying a stepwise regression procedure for the robustness. Given the rapid developments of sophisticated financial derivatives, this study may suggest a valuable insight to foreign and domestic investors to identify the possible determinants of CDS spreads at the firm- and/or the industry-level.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.65-80
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• 2023

In this study, a classification analysis was performed based on the type of traffic situation. The purpose was to derive the major variable factors that could represent the traffic situation. The TTI(Travel Time Index) was used as a criterion for determining traffic conditions, and analysis was performed using data generally detected by the Vehicle Detecting System(VDS). First, the major factors influencing the traffic situation were selected through factor analysis, and traffic conditions were clustered through a cluster analysis of the major factors. After that, variance analysis for each cluster was performed based on the TTI, and similar clusters were merged to categorize the type of traffic situation. The analysis derived, the maximum queue length and occupancy as major factors that could represent the traffic situation. Through this study, it is expected that efficient management of traffic congestion would be possible by just concentrating on the main variable factors that affect the traffic situation.