• The KIPS Transactions:PartC
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• v.16C no.3
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• pp.285-298
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• 2009

According to the development of ubiquitous technologies, sensor networks is used in various area. In particular, medical field is one of the significant application areas using sensor networks, and recently it has come to be more important according to standardization of the body sensor networks technology. There are special characteristics of their own for medical sensor networks, which are different from the one of sensor networks for general application or environment. In this paper, we propose a hierarchical medical sensor networks structure considering own properties of medical applications, and also introduce transmission mechanism based on hierarchical structure. Our mechanism uses the priority and threshold value for medical sensor nodes considering patient's needs and health condition. Through this way Cluster head can transmit emergency data to the Base station rapidly. We also present the new key establishment mechanism based on key management mechanism which is proposed by L. Eschenauer and V. Gligor for our proposed structure and transmission mechanism. We use key provisioning for emergency nodes that have high priority based on patients' health condition. This mechanism guarantees the emergency nodes to establish the key and transmit the urgent message to the new cluster head more rapidly through preparing key establishment with key provisioning. We analyze the efficiency of our mechanism through comparing the amount of traffic and energy consumption with analysis and simulation with QualNet simulator. We also implemented our key management mechanism on TmoteSKY sensor board using TinyOS 2.0 and through this experiments we proved that the new mechanism could be actually utilized in network design.

• Journal of Biomedical Engineering Research
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• v.21 no.4
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• pp.333-338
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• 2000

In this paper, an automated segmentation algorithm is proposed for MR brain images using T1-weighted, T2-weighted, and PD images complementarily. The proposed segmentation algorithm is composed of 3 step. In the first step, cerebrum images are extracted by putting a cerebrum mask upon the three input images. In the second step, outstanding clusters that represent inner tissues of the cerebrum are chosen among 3-dimensional(3D) clusters. 3D clusters are determined by intersecting densely distributed parts of 2D histogram in the 3D space formed with three optimal scale images. Optimal scale image is made up of applying scale space filtering to each 2D histogram and searching graph structure. Optimal scale image best describes the shape of densely distributed parts of pixels in 2D histogram and searching graph structure. Optimal scale image best describes the shape of densely distributed parts of pixels in 2D histogram. In the final step, cerebrum images are segmented using FCM algorithm with its initial centroid value as the outstanding clusters centroid value. The proposed cluster's centroid accurately. And also can get better segmentation results from the proposed segmentation algorithm with multi spectral analysis than the method of single spectral analysis.

• FLOWER RESEARCH JOURNAL
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• v.18 no.1
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• pp.33-37
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• 2010

Effects of cutting time of double flowered Hydragea serrata for. acuminata native to Korea on flowering and growth of following year were investigated in order to develop as a pot plant. Cuttings were carried out every 10th day from April to September in 2008. The cuttings were directly placed in 15 cm diameter pots. Longest plant was obtained from May cuttings and their average heights were 31.7 cm, and followed by April and July cuttings. Plant heights of August and September cuttings were 23.6 cm and 22.0 cm, respectively. In contrast, growth and height of June cutting were abnormally small. Leaf length, leaf width and petiole length of August and September cutting were reduced, but numbers of leaves were not changed. Average flower cluster numbers of May cuttings were 4 flower clusters, and July, August and September cuttings were 3 clusters while only 1 flower cluster per a plant was obtained during June. Biggest diameter of flower crown was observed from May cuttings and the size was 10.3 cm diameter; however, smaller flower crown size was observed after July cuttings. The best overall flower appearance was observed from May cuttings, and the worst was June cuttings. Even though plant height of August and September cuttings were reduced, flowering aspect and ornamental value were normal, but blooming times were retarded according to late cutting time.

• Journal of Korean Society of Forest Science
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• v.113 no.3
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• pp.271-281
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• 2024

The purpose of this study is to establish baseline data on the habitat status of Dracocephalum argunense Fisch. ex Link by identifying its vegetation structure and correlating environmental factors. A total of 9 vegetation plots (10 m×10 m) were surveyed. Cluster analysis revealed a total of three clusters: Quercus aliena (Group 1), Pinus thunbergii-Rubus parvilolius (Group 2), and Indigofera kirilowii-Zanthoxylum piperitum (Group 3). The importance value of D. argunense was the highest in Group 2, with a value of 6.19. Diversity analysis indicated a range of 2.747-3.166, but differences among the groups was not statistically significant (p>0.05). In the areas surrounding sedimentary rock zones, invasive plants were identified as indicator species, emphasizing the need for monitoring invasive species in the future. Although D. argunense exhibits good adaptability to moisture and atmospheric conditions due to its diverse habitats (forest and coast), there is a risk of decline due to interspecific competition and human activities, as analyzed in this study.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.287-296
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• 2003

There has been much research focused on collaborative filtering technique in Recommender System. However, these studies have shown the First-Rater Problem and the Sparsity Problem. The main purpose of this Paper is to solve these Problems. In this Paper, we suggest the user's predicting preference method using Bayesian estimated value and the associative user clustering for the recalculation of preference. In addition to this method, to complement a shortcoming, which doesn't regard the attribution of item, we use Representative Attribute-Neighborhood method that is used for the prediction when we find the similar neighborhood through extracting the representative attribution, which most affect the preference. We improved the efficiency by using the associative user's clustering analysis in order to calculate the preference of specific item within the cluster item vector to the collaborative filtering algorithm. Besides, for the problem of the Sparsity and First-Rater, through using Association Rule Hypergraph Partitioning algorithm associative users are clustered according to the genre. New users are classified into one of these genres by Naive Bayes classifier. In addition, in order to get the similarity value between users belonged to the classified genre and new users, and this paper allows the different estimated value to item which user evaluated through Naive Bayes learning. As applying the preference granted the estimated value to Pearson correlation coefficient, it can make the higher accuracy because the errors that cause the missing value come less. We evaluate our method on a large collaborative filtering database of user rating and it significantly outperforms previous proposed method.

• Journal of the Korean association of regional geographers
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• v.19 no.1
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• pp.45-59
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• 2013

This paper was to examine the spatial characteristics on the mobile industry's value chain based on the structure of value chain, the process of development, and the industrial linkages of mobile industry in Daegu-Gyeongbuk region. The mobile industry's value chain in Daegu-Gyeongbuk region consists of the infrastructure, mobile device, platform & embedded SW, and mobile contents sector. Among these sectors, the leading value chain sector in mobile governance is the mobile device sectors, especially the finished products sector. These sectors have developed by policies as well as networks with large enterprises such as Samsung and LG, and it forms a hub-and-spoke cluster. The infrastructure and mobile device sector are located in Gumi, Gyeongbuk, the embedded SW and mobile contents sectors are located in Daegu, which means decentralized agglomeration. The sectors of infrastructure and mobile device form the strong forward-backward linkages with firms in Daegu-Gyeongbuk region. For the embedded SW sector, the forward-backward linkages are active with firms located in Seoul metropolitan area. For mobile contents sector, the backward linkages are formed with firms in Daegu and the forward linkages are formed with firms in Seoul metropolitan area.

• Journal of Internet of Things and Convergence
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• v.7 no.4
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• pp.85-94
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• 2021

This study verified what differences in screen golf content characteristics, intention to reuse, customer satisfaction and economic value experienced by consumers according to the image feeling, expression method, and image color provided by screen golf graphic content. In addition, the purpose of this study was to analyze what kind of influence the content characteristics of screen golf have on the economic value and what kind of influence the intention to reuse and customer satisfaction have in this process. From September 1, 2021 to September 30, 2021, a survey of 225 copies of consumers using the screen golf course was conducted. For data processing, frequency analysis, factor analysis, reliability analysis, cluster analysis, chi-square analysis and 3-step mediated regression analysis were performed. The research results are as follows. First, the preferred image feeling showed a high level of clean and sophisticated feeling and the preferred expression method showed a high realistic image. In addition, the preferred image color showed a high level of green color. Second, there were differences in competitiveness, ease of use, sense of solidarity and realism according to the degree of consideration of graphic content and differences in consumer's intention to reuse, customer satisfaction, and economic value. Third, in the relationship between screen golf content characteristics and economic value, customer satisfaction and re-use intention had a mediating effect. Through this study, by providing basic data to derive the graphic design model of screen golf, the operating entity suggested a way to improve economic benefits and tried to contribute to the growth of the screen golf industry.

• Journal of Global Scholars of Marketing Science
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• v.17 no.3
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• pp.1-19
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• 2007

1. Purpose Rural tourism is made by individuals with different characteristics, needs and wants. It is important to have information on the characteristics and preferences of the consumers of the different types of existing rural accommodation. The stud aims to identify the determinants of consumer preference by type of accommodations. 2. Methodology 2.1 Sample Data were collected from 1000 people by telephone survey with three-stage stratified random sampling in seven metropolitan areas in Korea. Respondents were chosen by sampling internal on telephone book published in 2006. We surveyed from four to ten-thirty 0'clock afternoon so as to systematic sampling considering respondents' life cycle. 2.2 Two-step cluster Analysis Our study is accomplished through the use of a two-step cluster method to classify the accommodation in a reduced number of groups, so that each group constitutes a type. This method had been suggested as appropriate in clustering large data sets with mixed attributes. The method is based on a distance measure that enables data with both continuous and categorical attributes to be clustered. This is derived from a probabilistic model in which the distance between two clusters in equivalent to the decrease in log-likelihood function as a result of merging. 2.3 Multinomial Logit Analysis The estimation of a Multionmial Logit model determines the characteristics of tourist who is most likely to opt for each type of accommodation. The Multinomial Logit model constitutes an appropriate framework to explore and explain choice process where the choice set consists of more than two alternatives. Due to its ease and quick estimation of parameters, the Multinomial Logit model has been used for many empirical studies of choice in tourism. 3. Findings The auto-clustering algorithm indicated that a five-cluster solution was the best model, because it minimized the BIC value and the change in them between adjacent numbers of clusters. The accommodation establishments can be classified into five types: Traditional House, Typical Farmhouse, Farmstay house for group Tour, Log Cabin for Family, and Log Cabin for Individuals. Group 1 (Traditional House) includes mainly the large accommodation establishments, i.e. those with ondoll style room providing meals and one shower room on family tourist, of original construction style house. Group 2 (Typical Farmhouse) encompasses accommodation establishments of Ondoll rooms and each bathroom providing meals. It includes, in other words, the tourist accommodations Known as "rural houses." Group 3 (Farmstay House for Group) has accommodation establishments of Ondoll rooms not providing meals and self cooking facilities, large room size over five persons. Group 4 (Log Cabin for Family) includes mainly the popular accommodation establishments, i.e. those with Ondoll style room with on shower room on family tourist, of western styled log house. While the accommodations in this group are not defined as regards type of construction, the group does include all the original Korean style construction, Finally, group 5 (Log Cabin for Individuals)includes those accommodations that are bedroom western styled wooden house with each bathroom. First Multinomial Logit model is estimated including all the explicative variables considered and taking accommodation group 2 as base alternative. The results show that the variables and the estimated values of the parameters for the model giving the probability of each of the five different types of accommodation available in rural tourism village in Korea, according to the socio-economic and trip related characteristics of the individuals. An initial observation of the analysis reveals that none of variables income, the number of journey, distance, and residential style of house is explicative in the choice of rural accommodation. The age and accompany variables are significant for accommodation establishment of group 1. The education and rural residential experience variables are significant for accommodation establishment of groups 4 and 5. The expenditure and marital status variables are significant for accommodation establishment of group 4. The gender and occupation variable are significant for accommodation establishment of group 3. The loyalty variable is significant for accommodation establishment of groups 3 and 4. The study indicates that significant differences exist among the individuals who choose each type of accommodation at a destination. From this investigation is evident that several profiles of tourists can be attracted by a rural destination according to the types of existing accommodations at this destination. Besides, the tourist profiles may be used as the basis for investment policy and promotion for each type of accommodation, making use in each case of the variables that indicate a greater likelihood of influencing the tourist choice of accommodation.

• Journal of Korean Society of Forest Science
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• v.94 no.6
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• pp.410-419
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• 2005

Community structure of evergreen broad-leaved forest of Mt. Yeogwi in Jin-do was investigated to secure sustainable conservation of evergreen broad-leaved forest. Twenty survey plots of $20m{\times}20m$ were established along the elevation from 200 m to 390 m above the sea level in the northwestern slope. The woody species were tallied at each plots. DBH distribution of the major evergreen broad-leaved trees was investigated to find out the spatial distribution. Cluster analysis was applied to a set of vegetation data, that is, importance value to classify the forest community. Species diversity, evenness and species correlation were analysed. Canonical correspondence analysis was also applied to vegetation data and soil environmental data. Cluster analysis showed that the forests of Mt. Yeogwi were classified into 2 community groups, such as Camellia japonica community group and Quercus acuta community group. C japonica community group was subdivided into C japonica- evergreen broad-leaved trees community, C. japonica-Neolitsea sericea community, and C. japonica-deciduous broad-leaved trees community. Q. acuta community group was subdivided into Q. acuta-C. japonica community, and Q. acuta community. C. japonica, Q. acuta, N. sericea, Machilus thunbergii and Illicium religiosum were dominant evergreen broad-leaved tree species, while Styrax japonica, Lindera erythrocarpa, Cornus kousa, Prunus sargentii, Albizzia julibrisin and Quercus acutissima were major deciduous tree species. Species diversity was greater in Q. acuta community group (0.8231 for Q. acuta-C. japonica community, and 0.8135 for Q. acuta community) than in C. japonica community group (0.7674 for C. japonica-evergreen broad-leaved trees community, 0.6164 for C. japonica-N. sericea community, and 0.7931 for C. japonica-deciduous broad-leaved trees community). DBH 2 cm~10 cm of major evergreen broad-leaved trees occupied 80% of all. C. japonica of less than DBH 5 cm tended to aggregate but distribute randomly or regularly with increasing DBH. Q. acuta distributed more aggregately than C. japonica and Machilus thunbergii for more than 15 cm of DBH. C. japonica correlated negatively with Q. acuta, I. religiosum and C. kousa, but positively with N. sericea. with significance at 1% level. Q. acuta correlated negatively with C. japonica, N. sericea and M. thunbergii but positively with l. religiosum. There were also negative correlation between N. sericea and C. kousa. CCA showed that forest communities were correlated with soil variables such as CEC, soil organic matter and soil pH. With increased soil organic matter and CEC, and decreased soil pH, C. japonica was dominant and forest community and Q. acuta and N. sericea tended to develop in the evergreen broad-leaved forest.

• Journal of Yeungnam Medical Science
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• v.12 no.2
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• pp.366-385
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• 1995

Epidemiological studies are important in both the prevention and treatment of mycobacterial infections. This study was initiated to establish the pulsed-field gel electrophoresis (PFGE) method, which are not yet extensively studied. The most apprpriate restriction endonucleases included DraI, AsnI, and XbaI. The optimal PFGE condition was different according to the enzymes used. Two stage PFGE was performed, in case of DraI first stage was performed with 10 seconds of initial pulse and 15 seconds of final pulse, while the second stage was performed with 60 seconds of initial pulse and 70 seconds of final pulse. The electrophoresis time for DraI-PFGE was 14 hours for each stage. Electrophoresis was performed for 22 hours, in case of XbaI, with 3 seconds of initial pulse and 12 seconds of final pulse. Electrophoresis was performed for 22 hours, in case of AsnI, with 5 seconds of initial pulse and 25 seconds of final pulse. In all cases the voltage of the electrophoresis was maintained constantly at 200 voltage. Standard mycobacterial strains, which included Mycobacterium bovis BCG, M. tuberculosis, and M. fortuitum, could not be differentiated by PFGE analysis. PFGE analysis was performed to differentiate 9 clinically isolated M. fortuitum strains using AsnI. All M. fortuitum strains showed different genotypes except 2 strains. Cluster analysis divided M. fortuitum strains into 2 large groups. PFGE analysis was performed to further differentiate M. fortuitum isolates using XbaI. The undifferentiated 2 M. fortuitum strains showed different PFGE patterns with Xba I. Cluster analysis of the XbaI-PFGE patterns showed more complex grouping than AsnI-PFGE patterns, which showed that XbaI-PFGE analysis was better than AsnI-PFGE in M. fortuitum genotyping. The top dissimilarity values of AsnI-PFGE and XbaI-PFGE were 0.74 and 0.75, respectively. This value was higher than that of arbitrarily primed polymerase chain reaction (AP-PCR) analysis and lower than that of restriction fragment length polymorphism (RFLP) analysis. This suggested that PFGE can be used as a supportive or alternative genotyping method to RFLP analysis.