• Journal of Korean Society of Rural Planning
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• v.23 no.3
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• pp.1-12
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• 2017

The purpose of this study is to reveal network potential among agricultural villages focused on landscape and amenity resources. For this study, we conducted Social Network Analysis (SNA) utilizing existing landscape resource database. As a result of the study, major landscape types shared among villages were found for each city. For example, agricultural and residential landscapes were identified as major types for Danjin city. Add to major landscape resources, in Dangjin city, Habduk village were recognized as a core. Seokmun, Daehoji, Woogang, and Sunseong villages were widely found as the sub core group. For Seosan city, Jigok, Palbong, and Kobuk villages were widely recognized as core group. Most of villages which indicated the highest degree centrality were superior in terms of the number of total landscape resources as well as landscape type diversity. These results can be useful for initial planning process when considering major theme for landscape-based network organization. Also, this information will be helpful for planning stage through the specification of the potential role of each village in overall network.

• Journal of the Korean Operations Research and Management Science Society
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• v.37 no.4
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• pp.211-223
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• 2012

This study purposed to evaluate the influences of rival hospitals on the number of patients who visited the a study territory hospital. Spatial analysis technique was used to measure the impact of rival hospitals in study region. Selected hospitals were all medical school affiliated hospitals which were located in Daejeon metropolitan city and Chungchungnamdo. Patient data was collected from the claims data of the study hospital, and the number of inpatient and outpatients who visited the study hospital between January and June in 2008 were calculated on the smallest administrative district, Eup, Myeon, and Dong, in study region. To control the differences of regional characteristics among Eup, Myeon, Dong, socio-economic variables (total population, number of people aged over 65, number of basic livelihood security recipients, distance from the study hospital to the centroid point of each Eup, Myeon, Dong, number of business, and number of employees) were included in analysis model. These variables were collected from the annual year book of city as well as county located in study region. Cluster analysis classified the study region into three groups by using the difference of between th actual number of inpatient/outpatient and the predicted number of inpatient/outpatient in Eup, Myeon, and Dong. Most areas around the rivalry hospitals were categorized into same group. Multiple regression analysis indicated that areas around rivalry hospitals had statistically significantly negative relationship with the number of inpatients and outpatients who visited the study hospital. As the buffer size was increased from 5Km to 10Km, the standardized regression coefficients were decreased. These study results confirmed that rivalry hospitals in region had negative impacts on the performance of hospitals. It suggests that hospitals will require not only to select their location to minimize the effects of rivalry hospitals, but also to establish their strategy to cope with the rivalry's threats in their region.

• The Korean Journal of Mycology
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• v.41 no.1
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• pp.47-51
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• 2013

Yeasts isolated from wild flowers of Gyejoksan in Daejeon city, Oseosan in Chungchungnamdo, and Baekamsan in Jeollabukdo, Korea were identified by comparison of nucleotide sequences for PCR-amplified D1/D2 region of 26S rDNA or internal transcribed spacer (ITS) 1 and 2 including 5.8S rDNA using BLAST. Twelve yeast strains of ten species and seventeen yeast strains of ten species were isolated from wild flowers of Gyejoksan and Oseosan, respectively. And thirty seven yeast strains of twenty four species were isolated from wild flowers of Baekamsan. Total thirty four yeast species were isolated from three different sample collection areas, but only nine species were overlapped from the at least two different sampling areas: Cryptococcus sp., Cryptococcus aureus, Cryptococcus flavescens, Cryptococcus flavus, Metschnikowia sp., Pseudozyma aphidis, Rhodotorula glutinis, Sporobolomyces carnicolor, and Sporobolomyces ruberrimus. Among them only Cryptococcus aureus was occurred from all three different collection sites. Other twenty five species were restricted to specific collection site suggesting that each area has distinctive yeast flora.