• Korean Institute of Interior Design Journal
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• v.15 no.5 s.58
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• pp.306-313
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• 2006

Digital simulation which was introduced to the architectural field due to the rapid growth of computer graphics, gave birth to a new type of contents called 'virtual reality', led by the interaction with the users and real time processing. The public attention is drawn to the virtual reality's potential as a next generational space simulation it, having the unique characteristics of 'simulation', 'interactivity', 'tole-presence', and 'immersion', is capable of taking a virtual tour of a space with a size equivalent to that of a real space, as well as proceeding with the design progress. Nonetheless, many problems impeding CPU's real time processing of an excessively loaded architectural model data have been pinpointed over the time. Yet such GPU based game engines as 'DirectX' and 'OpenGL', developed to deal with these impediments, have not been easily applied to the architectural simulation in the design process, due to the high license cost and the specific technical requirements for the system. The virtual reality has been developed and distributed centering around the gaming field, and game developers recently show a greater tendency to include level editors in the package for the expandability purpose. Thus, we plan to propose architecture simulation which utilizes level editors in this study. In addition, the compatibility of the game engine based level editors of Quake and Unreal which form the standards for the open source FPS games, based on VRML, the standard format for the virtual reality, was compared and analyzed. Taking the example of Villa Savoye of Le Corbusier, its application possibility as an architecture simulation was assessed, by measuring the extent to which the performance of such characteristic features of the virtual reality as interactivity, immersion, and tele-presence, was improved.

• Journal of Fashion Business
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• v.6 no.5
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• pp.136-150
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• 2002

In this study, we proposed a method to be standing customers as the supporting system for the improvement of fashion garment industry which was the marginal growth getting into full maturity of market. As for the customer creation method of Fashion garment company is developing a marketing program to be standing customer as customer scoring to estimate a existing customer‘s buying power, and figure out minimum fixed sales of company to use a future purchasing predict. This study was a result of data from total sixty thousands data to be created for the 11 months from september. 2000 to July. 2001. The data is part of which the company leading the Korean fashion garment industry has a lot of a customer purchasing history data. But this study used only 48,845 refined purchased data to discriminate from sixty thousands data and 21,496 customer case with the exception of overlapping purchased data among of those. The software used to handle sixty thousands data was SAS e-miner. As the analysis process is put in to operation the analysis of the purchasing customer’s profile firstly, and the second come into basket analysis to consider the buying associations for Association goods, the third estimate the customer grade of Customer loyalty by 3 ways of logit regression analysis, decision tree, Artificial Neural Network. The result suggested a method to be estimate the customer loyalty as 3 independent variables, 2 coefficients. The 3 independent variables are total purchasing amount, purchasing items per one purchase, payment amount by one purchasing item. The 2 coefficients are royal and normal for customer segmentation. The result was that this model use a logit regression analysis was valid as the method to be estimate the customer loyalty.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.185-192
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• 2022

This study investigates the effect of the semi-supervised learning(SSL) method on predicting default risk of peer-to-peer(P2P) loans. Despite its proven performance, the supervised learning(SL) method requires labeled data, which may require a lot of effort and resources to collect. With the rapid growth of P2P platforms, the number of loans issued annually that have no clear final resolution is continuously increasing leading to abundance in unlabeled data. The research data of P2P loans used in this study were collected on the LendingClub platform. This is why an SSL model is needed to predict the default risk by using not only information from labeled loans(fully paid or defaulted) but also information from unlabeled loans. The results showed that in terms of default risk prediction and despite the use of a small number of labeled data, the SSL method achieved a much better default risk prediction performance than the SL method trained using a much larger set of labeled data.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.5
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• pp.64-72
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• 2014

This study quantified the storage and annual uptake of carbon by apple trees in orchards as a production-type greenspace, and computed the annual carbon emissions from apple cultivation. Tree individuals in the study orchards were sampled to include the range of stem diameter sizes. The study measured biomass for each part including the roots of sample trees through a direct harvesting method to compute total carbon storage per tree. Annual carbon uptake per tree was quantified by analyzing the radial growth rates of stem samples at ground level. Annual carbon emissions from management practices such as pruning, mowing, irrigation, fertilization, and use of pesticides and fungicides were estimated based on maintenance data, interviews with managers, and actual measurements. Regression models were developed using stem diameter at ground level (D) as an independent variable to easily estimate storage and annual uptake of the carbon. Storage and annual uptake of carbon per tree increased as D sizes got larger. Apple trees with D sizes of 10 and 15 cm stored 9.1 and 21.0 kg of carbon and annually sequestered 1.0 and 1.6 kg, respectively. Storage and annual uptake of carbon per unit area in study orchards were 3.81 t/ha and 0.42 t/ha/yr, respectively, and annual carbon emissions were 1.30 t/ha/yr. Thus, the carbon emissions were about 3 times greater than the annual carbon uptake. The study identified management practices to reduce the carbon footprint of production-type greenspace, including efficient uses of water, pesticides, fungicides, and fertilizers. It breaks new ground by including measured biomass of roots and a detailed inventory of carbon emissions.

• Journal of Korean Society of Forest Science
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• v.98 no.6
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• pp.633-638
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• 2009

This study was conducted to develop stem taper equations and stem volume tables for Eucalyptus pellita and Acacia mangium plantations in Kalimantan, Indonesia. To derive a most adequate taper equation for the plantations, three models - Max & Burkhart, Kozak, and Lee models - were applied and their fitness were statistically analyzed by using fitness index, bias, and standard error of bias. The result showed that there is no significant difference between the three models, but the fitness index was slightly higher in the Kozak model. Therefore, the Kozak model was chosen for generating stem taper equations and stem volume tables for the Eucalyptus pellita and Acacia mangium plantations. The resulted stem volume table was compared to the local volume table used in Kalimantan regions, but no significant difference was found in the stem volume estimation. It is expected that the results of this study would provide a good information about the tree growth in abroad plantations and support a reliable decision-making for their management.

• Journal of agriculture & life science
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• v.46 no.3
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• pp.47-58
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• 2012

This study was carried out to develop assessment model for the optimal site prediction of Dendropanax morbifera, Evergreen broad-leaved trees in warm temperate zone according to climate change. It was created criterion for assessment model of the optimal site prediction by quantification method to possible analysis of quantitative and qualitative data, through study relationship between growth of tree and site environmental factors. A program of the optimal site prediction was developed using program version 3.2, an Avenue and Dialog Designer tool of ESRI as GIS(geographic information system) engine. Developed program applied to test accuracy of the optimal site prediction in study area of Wando, Jeollanam-do, having a various evergreen broad-leaved trees of warm temperate zone. In the results from analysis of the optimal site prediction on Dendropanax morbifera, the characteristics of optimal site were analyzed site environmental features with 401~500m of altitude, $15^{\circ}$ of slope, hillside of local topography, alluvium of deposit type, convex of slope type and south of aspect. The mapping area per grade of the optimal site prediction in the Dendropanax morbifera showed 1,487.2ha(25.4%) of class I, 1,020.3ha(17.4%) of class II, 2,231.8ha(38.2%) of class III and 1,110.5ha(19.0%) of class IV.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.5
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• pp.27-43
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• 2019

This study applied the LANDIS-II model to the forest vegetation of the study area in Yeongdong-gun, Korea to identify climate effects on ecosystems of forest vegetation. The main purpose of the study is to examine the long-term changes in forest aboveground biomass(AGB) under three different climate change scenarios; The baseline climate scenario is to maintain the current climate condition; the RCP 4.5 scenario is a stabilization scenario to employ of technologies and strategies for reducing greenhouse gas emissions; the RCP 8.5 scenario is increasing greenhouse gas emissions over time representative with 936ppm of $CO_2$ concentration by 2100. The vegetation survey and tree-ring analysis were conducted to work out the initial vegetation maps and data for operation of the LANDIS model. Six types of forest vegetation communities were found including Quercus mongolica - Pinus densiflora community, Quercus mongolica community, Pinus densiflora community, Quercus variabilis-Quercus acutissima community, Larix leptolepis afforestation and Pinus koraiensis afforestation. As for changes in total AGB under three climate change scenarios, it was found that RCP 4.5 scenario featured the highest rate of increase in AGB whereas RCP 8.5 scenario yielded the lowest rate of increase. These results suggest that moderately elevated temperatures and $CO_2$ concentrations helped the biomass flourish as photosynthesis and water use efficiency increased, but huge increase in temperature ($above+4.0^{\circ}C$) has resulted in the increased respiration with increasing temperature. Consequently, Species productivity(Biomass) of trees decrease as the temperature is elevated drastically. It has been confirmed that the dominant species in all scenarios was Quercus mongolica. Like the trends shown in the changes of total AGB, it revealed the biggest increase in the AGB of Quercus mongolica under the RCP 4.5 scenario. AGB of Quercus mongolica and Quercus variabilis decreased in the RCP 4.5 and RCP 8.5 scenarios after 2050 but have much higher growth rates of the AGB starting from 2050 under the baseline scenario. Under all scenarios, the AGB of coniferous species was eventually perished in 2100. In particular they were extinguished in early stages of the RCP 4.5 and RCP 8.5 scenarios. This is because of natural selection of communities by successions and the failure to adapt to climate change. The results of the study could be expected to be effectively utilized to predict changes of the forest ecosystems due to climate change and to be used as basic data for establishing strategies for adaptation climate changes and the management plans for forest vegetation restoration in ecological restoration fields.

• Journal of Korean Society of Forest Science
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• v.108 no.3
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• pp.357-363
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• 2019

This study was conducted to develop a stem volume table for Quercus acutissima in Korea by using Kozak's stem taper equation. In total, 2700 tree samples were collected around the country, and growth performance was investigated through compiling data on diameters by stem height and stem analysis. In order to test the stem taper equation's fitness, the fitness index (FI), bias, and mean absolute deviation (MAD) were analyzed. The fitness of the equation was estimated at 97%, bias as 0.017, and MAD turned out to be 1.118, respectively. Furthermore, there was a statistically significant volume difference between the current volume table and the new volume table (p = 0.0008, <0.005). The result indicates that using the new volume table that reflects the actual forest will reduce the loss when assessing wood resources and will improve the accuracy of forest statistics for national and local governments. A stem volume table, the main result of this research, which is utilized in the estimated stem taper equation, will provide growth information for Quercus acutissima, one of the main broadleaf species in Korea, and will function as a management indicator for rational forest management.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.2
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• pp.95-106
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• 2010

The performance of Community Land Model version 3.5 - Dynamic Global Vegetation Model (CLM-DGVM) was evaluated through a comparison with the observation over temperate deciduous forest in Gwangneung, Korea. Influence of plant phenology, composition of plant functional type, and climate variability on carbon exchanges was also examined through sensitivity test. To get equilibrium carbon storage, the model was run for 400 years driven by the observed atmospheric data at the deciduous forest of the year 2006. We run the model for 2006 with the equilibrium carbon storage at Gwangneung forest and compared the model output with the observation. A comparison of leaf area index (LAI) between the model and observation indicated that the simulated phenology poorly represented the timing of budburst, leaf-fall, and evolution of LAI. Senescence of the phenology was delayed about four weeks and the simulated maximum LAI (of 5.8 $m^2$ $m^{-2}$) was greater than the observed value (of 4.5 $m^2$ $m^{-2}$). The overestimated LAI contributed to overestimation of both gross primary productivity (GPP) and ecosystem respiration $(R_e)$ through increased photosynthesis and foliar autotropic respiration $(R_a)$, respectively. Despite the discrepancy between the simulated and observed LAI, the simulated tree carbon storage amounts were comparable with the reported values at the site. Change in plant phenology from the simulated to the observed reduced more than six weeks of the plant growth period, resulting in the decreased amount of GPP and $R_e$. These values, however, were still higher (~10% of GPP and 40% of $R_e$) than the observed values. The effect of change in plant functional type composition (from dominant temperate deciduous forest to the coexistence of temperate deciduous and needle leaf forests) on the estimated amount of GPP and $R_e$ was marginal. The influence of climate variability on carbon storage amounts was not significant. The simulated inter-annual variation of GPP and $R_e$ from 1994 to 2003 depended on annual mean air temperature and total radiation but not on precipitation. Other deficiencies of CLM3.5-DGVM have been discussed.

• Korean Journal of Environment and Ecology
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• v.33 no.4
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• pp.472-480
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• 2019

Selection of the plant material for planting to reduce fine dust should comprehensively consider the visual characteristics, such as the shape and texture of the plant leaves and form of bark, which affect the adsorption function of the plant. However, previous studies on reduction of fine dust through plants have focused on the absorption function rather than the adsorption function of plants and on foliage plants, which are indoor plants, rather than the outdoor plants. In particular, the criterion for selection of fine dust reduction species is not specific, so research on the selection criteria for plant materials for fine dust reduction in urban areas is needed. The purpose of this study is to identify the priorities of eight indicators that affect the fine dust reduction by using the fuzzy multi-criteria decision-making model (MCDM) and establish the tree selection criteria for the urban planting to reduce fine dust. For the purpose, we conducted a questionnaire survey of those who majored in fine dust-related academic fields and those with experience of researching fine dust. A result of the survey showed that the area of leaf and the tree species received the highest score as the factors that affect the fine dust reduction. They were followed by the surface roughness of leaves, tree height, growth rate, complexity of leaves, edge shape of leaves, and bark feature in that order. When selecting the species that have leaves with the coarse surface, it is better to select the trees with wooly, glossy, and waxy layers on the leaves. When considering the shape of the leaves, it is better to select the two-type or three-type leaves and palm-shaped leaves than the single-type leaves and to select the serrated leaves than the smooth edged leaves to increase the surface area for adsorbing fine dust in the air on the surface of the leaves. When considering the characteristics of the bark, it is better to select trees that have cork layers or show or are likely to show the bark loosening or cracks than to select those with lenticel or patterned barks. This study is significant in that it presents the priorities of the selection criteria of plant material based on the visual characteristics that affect the adsorption of fine dust for the planning of planting to reduce fine dust in the urban area. The results of this study can be used as basic data for the selection of trees for plantation planning in the urban area.