• Journal of Forest and Environmental Science
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• v.10 no.1
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• pp.8-24
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• 1994

Because of the underground existence of roots, a few studies have been reported on root system. The developmental information of roots should be understood for the studies of specific tree traits and the influence of such traits on the soil surface fixation. In order to clarify the specific character of pine forest in Kangwon Province, the investigation on the form and distribution of root system of pine trees were carried out for 5 trees in the Campus Forest, Kangwon National Univ.. Root form was very well in flat root. As soil depth was approximatly 50cm, fine roots were very sparsly distributed(+), roots of 0.2cm in diameter were most common and roots > 0.2cm were very rare, also thickness thined. 60~70% all the roots were developed at the depth of 0~30cm, where big roots were below 0.9cm in diameter and fine roots were higly sparse(+).

• Journal of Convergence for Information Technology
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• v.7 no.1
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• pp.55-60
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• 2017

In order to provide intelligent services without human intervention in the Internet of Things environment, it is necessary to analyze the big data generated by the IoT device and learn the normal pattern, and to predict the abnormal symptoms such as faulty or malfunction based on the learned normal pattern. The purpose of this study is to implement a machine learning model that can predict product failure by analyzing big data generated in various devices of product process. The machine learning model uses the big data analysis tool R because it needs to analyze based on existing data with a large volume. The data collected in the product process include the information about product faulty, so supervised learning model is used. As a result of the study, I classify the variables and variable conditions affecting the product failure, and proposed a prediction model for the product failure based on the decision tree. In addition, the predictive power of the model was significantly higher in the conformity and performance evaluation analysis of the model using the ROC curve.

• Journal of People, Plants, and Environment
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• v.23 no.2
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• pp.233-243
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• 2020

This study collects social big data used in various fields in the past 9 years and explains the patterns of major keywords of the arboretums and botanical gardens to use as the basic data to establish operational strategies for future arboretums and botanical gardens. A total of 6,245,278 cases of data were collected: 4,250,583 from blogs (68.1%), 1,843,677 from online cafes (29.5%), and 151,018 from knowledge search engine (2.4%). As a result of refining valid data, 1,223,162 cases were selected for analysis. We came up with keywords through big data, and used big data program Textom to derive keywords of arboretums and botanical gardens using text mining analysis. As a result, we identified keywords such as 'travel', 'picnic', 'children', 'festival', 'experience', 'Garden of Morning Calm', 'program', 'recreation forest', 'healing', and 'museum'. As a result of keyword analysis, we found that keywords such as 'healing', 'tree', 'experience', 'garden', and 'Garden of Morning Calm' received high public interest. We conducted word cloud analysis by extracting keywords with high frequency in total 6,245,278 titles on social media. The results showed that arboretums and botanical gardens were perceived as spaces for relaxation and leisure such as 'travel', 'picnic' and 'recreation', and that people had high interest in educational aspects with keywords such as 'experience' and 'field trip'. The demand for rest and leisure space, education, and things to see and enjoy in arboretums and botanical gardens increased than in the past. Therefore, there must be differentiation and specialization strategies such as plant collection strategies, exhibition planning and programs in establishing future operation strategies.

• The Korean Journal of Ecology
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• v.26 no.1
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• pp.34-38
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• 2003

An analysis of tree ring series of a lace-bark pine (Pinus bungeana Zuccarini) was carried out to find out the exact age of the tree, to describe life history of the tree affected by the change of past environmental factors, and to explain the relationships between the growth fluctuation of the tree and the change of environmental factors of the past. This study explicitly showed that the tree was about 300 years old in 1992 and that the previous estimate of the age to be about 630 years old has no ground to be justified. This was also ascertained by the close correspondence of the tree growth fluctuation to the fluctuation of soil moisture related environmental factors for the last 80 years in Seoul. Although it is clear that the tree suffered from slow growth for about 30 years initiating from the 1910s, it is not sure whether the soil moisture deficits or droughts during the years of 1910-1913 played a major role in causing the decline of the trees afterwards. Discussion was further extended for defining active roles for the Cultural Properties Administration of Korea in management and research to effectively protect the Old and Big Trees under the category of Natural Monument of Korea.

• Korean Journal of Environmental Agriculture
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• v.38 no.3
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• pp.145-153
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• 2019

BACKGROUND: The 'Gamhong' cultivar, middle season apple with big fruit size and high soluble solid content, has been bred in Korea. However, it was hard to cultivate the cultivar in Korea by serious bitter pit. The relationships between shoot growth, fruit size, and bitter pit may be affected by crop load. This study was conducted for 2 years (7~8 years after planting) to investigate vegetative growth, fruit quality, bitter pit incidence, return bloom, and gross income for optimum crop load of 'Gamhong'/M.9 adult apple tree. METHODS AND RESULTS: The crop load was assigned to 4 different object ranges as follow: 45~64, 65~84, 85~104, and 105~124 fruits per tree. The vegetative growth, average fruit weight, percentage of fruits heavier than 375 g, soluble solid content, and return bloom increased significantly at the crop load range of 45~64 fruits. However, the lowest total gross income per tree may have been caused by the highest bitter pit incidence and the lowest yield per tree in any other crop load range. The total gross income and yield per tree increased significantly at the crop load range of 105~124 fruits and return bloom dropped to 40%, and hence it was possible to occur biennial bearing. It was 85~104 fruits that biennial bearing did not occur and total gross income was as high as the crop load range of 105~124 fruits. Also, the yield of high grade fruits per tree, with fruit weight of 400~499 g and none bitter pit on fruit surface, was highest at the crop load range of 85~104 fruits, compared to other crop load range. CONCLUSION: In considering fruit size, bitter pit incidence, return bloom, and gross income, the optimum crop load range of 'Gamhong'/M.9 adult apple tree in high density orchard was 85~104 fruits per tree.

• Journal of Agricultural Extension & Community Development
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• v.13 no.1
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• pp.49-67
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• 2006

The purpose of this study was to suggest development strategies of a village of Hwaseong-si where several programs using it's traditional items have been operated since 2003 according to the policy of Rural Traditional Thema Village Development implemented by Rural Development Administration(RDA). The village is located in Yodang-ri, Yanggam-myun, hwaseong-si in Gyounggi province. The village is called as 'Eunheng Namu Maeul' which means 'ginkgo tree village' since the tree is almost 350 years old and beautifully huge. Including this big tree there are much more traditional items such as organic dairy farming, hand-made cheese, legends and traditional plays. Using this items and government subsidies, the village has managed various tour programs and other income increasing projects. This study analyzed the strengths, weaknesses, opportunities and threats of the current situation of the village with the related materials and data to find out development strategies for the village-based programs and projects. This study recommended the followings as a major result of this study. The huge ginkgo tree at the village could be a better traditional attractive item when paths and wood of ginkgo trees will be built up especially utilizing the original huge one around the village. Like this, the item of hand made cheese could be a much more valuable traditional item when there will be an advanced facility for the people's working together. The social actives of the village have been weakened because of few young dwellers living there, therefore there needs a special subsidizing project for the village to hire a young manager having some social skills and knowledges. The situation being urbanized in front of the village needs precisely checking and implementing the Hwaseong-si's urbanization policy so that the urbanization could be harmonized with the maintenance and development of the traditional items of the village.

• Journal of the Korea Fashion and Costume Design Association
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• v.19 no.1
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• pp.135-145
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• 2017

In order to analysis on color difference of yellow natural dyes, I have dyed cellulose and protein fabrics. The results of experiment have been analysed by wavelength of maximum absorption, amounts of dye uptake, color difference, Hunter's value and Munsell's value. The results from these analyses are as follows : Bud of pagoda tree, Amur cork, and Curcuma showed greenish yellow color, Gardenia Jasminoides showed reddish yellow color. Barberry root showed reddish yellow color with post-mordanting method on cellulose fabric. Moreover, Dupioni silk was dyed in reddish yellow color by Barberry root and Rhubarb. In addition to Chroma index, Gardenia Jasminoides and Curcuma showed clear color overall. However, dyeing rayon and silk by Barberry root, and dyeing silk by Rhubarb showed clear color. Comparing all the results to actual dyed materials, Bud of pagoda tree had small dye uptake, and both ${\Delta}a$ and ${\Delta}b$ value were short which can't recognized the yellow color easily. Dye uptake of Amur cork and Gardenia Jasminoides was small just like Bud of pagoda tree. However, ${\Delta}b$ value order was Gardenia Jasminoides>Amur cork>Bud of pagoda tree. Therefore, Gardenia Jasminoides recognized reddish yellow because of big value of red color and yellow color. In case of Barberry root and Rhubarb which have larger dye uptake, Baberry root recognized yellow color on rayon only, and couldn't recognized yellow color on bleached cotton fabric, ramie, silk, and dupioni silk. Rhubarb recognized yellow color on rayon with pre-mordanting method only, but recognized silk and dupioni silk as brown like color. Moreover, we could not analyze color by dye uptake, Lab, and H(v/c) for Barberry root and Rhubarb. As a result, I think we need to attach color table for the research paper which handled the color of dyeing materials.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.595-601
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• 2014

With the advent of the Smart information-communication era, the number of data has increased exponentially. Accordingly, figuring out and analyzing in which area and circumstance the data has been created becomes one of the factors for prompt actions. In this paper identifies how to analyze the data by implementing a route from the lowest module to highest one in an inverse order for the part judgement for the particular data. The script first identifies cluster analisys, paralizes the analysis using the sum of each factors of the cluster with the tree structure, and finally transpose the answer into number. Also, it is designed to place priority on particular answer, thereafter, draws the wanted answer real-time.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.21-41
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• 2019

Thanks to the rapid development of information technologies, the data available on Internet have grown rapidly. In this era of big data, many studies have attempted to offer insights and express the effects of data analysis. In the tourism and hospitality industry, many firms and studies in the era of big data have paid attention to online reviews on social media because of their large influence over customers. As tourism is an information-intensive industry, the effect of these information networks on social media platforms is more remarkable compared to any other types of media. However, there are some limitations to the improvements in service quality that can be made based on opinions on social media platforms. Users on social media platforms represent their opinions as text, images, and so on. Raw data sets from these reviews are unstructured. Moreover, these data sets are too big to extract new information and hidden knowledge by human competences. To use them for business intelligence and analytics applications, proper big data techniques like Natural Language Processing and data mining techniques are needed. This study suggests an analytical approach to directly yield insights from these reviews to improve the service quality of hotels. Our proposed approach consists of topic mining to extract topics contained in the reviews and the decision tree modeling to explain the relationship between topics and ratings. Topic mining refers to a method for finding a group of words from a collection of documents that represents a document. Among several topic mining methods, we adopted the Latent Dirichlet Allocation algorithm, which is considered as the most universal algorithm. However, LDA is not enough to find insights that can improve service quality because it cannot find the relationship between topics and ratings. To overcome this limitation, we also use the Classification and Regression Tree method, which is a kind of decision tree technique. Through the CART method, we can find what topics are related to positive or negative ratings of a hotel and visualize the results. Therefore, this study aims to investigate the representation of an analytical approach for the improvement of hotel service quality from unstructured review data sets. Through experiments for four hotels in Hong Kong, we can find the strengths and weaknesses of services for each hotel and suggest improvements to aid in customer satisfaction. Especially from positive reviews, we find what these hotels should maintain for service quality. For example, compared with the other hotels, a hotel has a good location and room condition which are extracted from positive reviews for it. In contrast, we also find what they should modify in their services from negative reviews. For example, a hotel should improve room condition related to soundproof. These results mean that our approach is useful in finding some insights for the service quality of hotels. That is, from the enormous size of review data, our approach can provide practical suggestions for hotel managers to improve their service quality. In the past, studies for improving service quality relied on surveys or interviews of customers. However, these methods are often costly and time consuming and the results may be biased by biased sampling or untrustworthy answers. The proposed approach directly obtains honest feedback from customers' online reviews and draws some insights through a type of big data analysis. So it will be a more useful tool to overcome the limitations of surveys or interviews. Moreover, our approach easily obtains the service quality information of other hotels or services in the tourism industry because it needs only open online reviews and ratings as input data. Furthermore, the performance of our approach will be better if other structured and unstructured data sources are added.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.33 no.1
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• pp.1-5
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• 2020

In this study, the objective is to improve the criteria used for statistical comparison of the VLF tanδ (TD) database and failure rate according to water-tree degradation in underground distribution power cables. The aging condition of the KEPCO criteria is divided into 6 levels using the Weibull distribution, and the "failure imminent" condition is quantified by using the statistical end-point of the lifetime parameter of the VLF big-data group obtained from KEPCO. Moreover, new criteria with a 2-dimensional combination of TD, DTD, and a statistical normalized factor are suggested. These criteria exhibit high reproducibility for the detection of cables in an imminent failure state. Consequently, it is expected that the adoption of the extended VLF-2019 criteria will reduce the asset management cost of cable replacement compared to the VLF-2012 criteria of KEPCO.