• Journal of Korean Society for Geospatial Information Science
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• v.1 no.2 s.2
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• pp.167-175
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• 1993

This article contains three objectives. First it is to revise unnecessary procedures of a transportation models and transform results of a model into an image. Second objectives is to develop an operational structures which automatically input all data needed from arc-node topology to link-node topology of transportation network. By solving the network discrepancy, time and money for constructing to transportation can be saved. In addition, the rate of errors that my caused during data input process can be reduced. Conclusively, it is found that the integration package may provide user friendliness and reduce the rate of errors. The package can extract informations such as distance between zones and nodes, lane numbers, and hierarchy from arc-node topology for executing SDI. Another advantage of integration is the ability of spatial analysis. The integrated package may provide adequate arrangements of traffic facilities and checking systems of the shortest path. Finally, the database function of GIS package provides various information about study area for transportation analysis.

• Spatial Information Research
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• v.14 no.1 s.36
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• pp.57-65
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• 2006

In general, the investigation for reservoir dredging are conducting a observation on the horizontal position and the depth of water by assembling GPS/Echo Sounder and Total Station/Echo Sounder, and it is computed at a section computation of riverbed, reservoir volume and dredging plan etc. at that times, the detail plane is determinated about soil volume, height for dredging. Planning has a fault that the method of sound detection using the Echo Sounder doesn't check up distribution of reservoir deposit. In this study, the author emphasizes that implementation of dredging with combined Global Positioning System(GPS) and Ground Penetration Radar(GPR) is well-done more than existed GPS/Echo Sounder. the combined equipment can be adapted to computation and dredging reffering to distribution of deposition. First of all, it is executed water tank modelling test through sampling for apply to test area and is estimated the possibility after passed far accuracy verification of equipment.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.11-20
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• 2010

In situation that carbon dioxide emissions are being increased as urbanization, urban green space is being promoted as an alternative to find solution for these problems. In urban areas, trees have the ability to reduce carbon dioxide as well as to be aesthetic effect. In this study, we proposed the methodology which uses only LIDAR data in order to extract these trees information effectively. To improve the operational efficiency according to the extraction of trees, the proposed methodology was carried out using multiple data processing such as point, polygon and raster. Because the existing NDSM(Normalized Digital Surface Model) contains both the building and tree information, it has the problems of high complexity of data processing for extracting trees. Therefore, in order to improve these problems, this study used modified NDSM which was removed estimate regions of building. To evaluate the performance of the proposed methodology, three different zones which coexist buildings and trees within urban areas were selected and the accuracy of extracted trees was compared with the image taken by digital camera.

• Journal of Distribution Science
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• v.16 no.9
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• pp.59-63
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• 2018

Purpose - It has already been proved that 'mood' as the physical environment of shopping affects consumers' main sensory channels such as sight, hearing, smell, touch. However, there is no consensus on how the olfactory cue influences the customers in the shopping environment. In this study, we examine the previous studies on how the olfactory cue affects the customers in the shopping environment and present a clear direction as a suggestion for progressive research. Research design, data, and methodology - It is not important to use a lot of unconditional fragrance, but it should be exposed to the environment that suits the proper fragrance. In recent years, meaningful research on store fragrance has been slowly increasing. As a result, studies on the fragrance effects of retail stores have been conducted to verify the relevance of fragrance suitability in stores and consumer spending scale. Results - The fragrance appropriate for each store can not be uniformly specified as any fragrance. This is because external variables such as time, season, temperature, lighting, density of shoppers, and music in the store also affect customer evaluation. For example, using an unsuitable fragrance may encourage customers to leave the store quickly by restraining impulsive purchases or by disturbing concentration. The store manager should also be interested in using fragrances that are proven and effective in the store environment, but they should also have the ability to easily manipulate and manage the fragrances very appropriately according to changes in the store environment. Store managers should observe consumer preferences and responses according to their goals and strategies, and then systematically manage and store information about the fragrance appropriate to the store. Conclusions - In the future, the fragrance marketing researcher needs to consider the spatial form and density of the customer. In practice, managers operating a retail store should check the most appropriate store density(congestion) according to the size and spatial characteristics of the store and maintain the ideal conditions. To do this, it is necessary to pay attention to how to select and control sensory elements such as fragrance(olfactory), music(auditory), and lighting(visual).

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.172-183
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• 2012

In 2011, floods were at the worst stage of devastation in Chao Phraya river basin of Thailand. The purpose of this study is to trace the flood inundation area around Chao Phraya river basin by using Terra MODIS image because it has the ability of spatiotemporal dynamics. The MODIS indices, which included the enhanced vegetation index(EVI), land surface water index(LSWI), and the difference in the values of EVI and LSWI(DVEL), were extracted from MODIS product MOD09 8-day composite datasets with a spatial resolution of 500m from Jul. 29, 2011 to Jan. 09, 2012. We found that combined application of EVI, LSWI, and DVEL was suitable for monitoring flood inundation. For the extracted flood inundation area and water-related area. The result can be used to acquire the flood inundation data scattered and demonstrate the potential for the use of MODIS data for temporal and spatial detection of flood effects.

• Journal of the Korean Geographical Society
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• v.39 no.6 s.105
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• pp.971-983
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• 2004

It is increasingly clear that student mastery of concepts and skills in geographic education is based on a complex set of variables. Sex and gender are the key variables. Much has been written about biological sex differences in learning, but less attention has been paid to the impacts of socio-cultural gender on learning geography. As such, the aims of this paper are two-fold. First, to examine theories which seek to explain why males and females might differ in their geographic and spatial knowledge or skill. Second, to examine the extent of sex differences and gender traits in the geographic learning. The results of study illustrate clearly that there are more similarities than differences between the sexes. Therefore, there are significant gender differences between the preferences of regions, contents, activities in the secondary geographic learning. The results also provide insights into improving contents and method of geographic education.

• Animal cells and systems
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• v.16 no.4
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• pp.302-312
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• 2012

The purpose of this study was to examine whether Phellodendri Cortex extract (PCE) could improve learning and memory impairments caused by lipopolysaccharide (LPS)-induced inflammation in the rat brain. The effect of PCE on modulating pro-inflammatory mediators in the hippocampus and its underlying mechanism were investigated. Injection of LPS into the lateral ventricle caused acute regional inflammation and subsequent deficits in spatial learning ability in the rats. Daily administration of PCE (50, 100, and 200 mg/kg, i.p.) for 21 days markedly improved the LPS-induced learning and memory disabilities in the Morris water maze and passive avoidance test. PCE administration significantly decreased the expression of pro-inflammatory mediators such as tumor necrosis factor-${\alpha}$, interleukin-$1{\beta}$, and cyclooxygenase-2 mRNA in the hippocampus, as assessed by RT-PCR analysis and immunohistochemistry. Together, these findings suggest that PCE significantly attenuated LPS-induced spatial cognitive impairment through inhibiting the expression of pro-inflammatory mediators in the rat brain. These results suggested that PCE may be effective in preventing or slowing the development of neurological disorders, including Alzheimer's disease, by improving cognitive and memory function because of its anti-inflammation activity in the brain.

• School Mathematics
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• v.18 no.2
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• pp.323-348
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• 2016

The 2009 revised national mathematics curriculum have inserted mathematical 'linking cube' activities in the 6th grade math classes to improve students' spatial problem solving abilities and communication skills. However, we found that it was hard for teachers to teach problem solving and communication skills due to the absence of mathematical way of representing linking cubes in the classroom. In this paper, we propose 3D 'turtle representation system' as teaching and learning tools for linking cube activities. After using turtle representation system for linking cube activities, teachers responded that turtle representation system is a valuable problem solving and communication tools for the linking cube mathematics classes. We conclude that turtle representation system is a well designed teaching and learning tools for linking cube activities, and there are lots of educational meanings in the 3D turtle representation system.

• YAKHAK HOEJI
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• v.58 no.5
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• pp.287-293
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• 2014

Alzheimer's disease (AD), most common form of dementia is characterized that memory deficit and loss of cognitive function. This study was evaluated cognitive enhancing effect of water and ethanol extracts of Codonopsis lanceolata and compared using Morris water maze and passive avoidance test. The water and 70% ethanol extracts (100, 300 and 500 mg/kg) were administered to mice. The neuroprotective effect on glutamate-induced cell death in HT22 cells was additionally investigated using MTT assay. Results showed 70% ethanol extract of Codonopsis lanceolata enhanced cognitive function than water extract, as shown by decrease in escape latency time in Morris water maze test. In passive avoidance test, 70% ethanol extract also increased the latency time compared to the water extract. Furthermore, 70% ethanol extract significantly protected neuronal cell against glutamate cytotoxicity and showed higher than neuroprotective effect of water extract. These results indicate that 70% ethanol extract more improve spatial cognitive ability and protected neuronal cells than water extract.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.1
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• pp.183-201
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• 2022

Estimating the implicit value of housing assets is a very important task for participants in the housing market. Until now, such estimations were usually carried out using multiple regression analysis based on the inherent characteristics of the estate. However, in this paper, we examine the estimation capabilities of the Artificial Neural Network(ANN) and its 'Deep Learning' faculty. To make use of the strength of the neural network model, which allows the recognition of patterns in data by modeling non-linear and complex relationships between variables, this study utilizes geographic coordinates (i.e. longitudinal/latitudinal points) as the locational factor of housing prices. Specifically, we built a dataset including structural and spatiotemporal factors based on the hedonic price model and compared the estimation performance of the models with and without geographic coordinate variables. The results show that high estimation performance can be achieved in ANN by explaining the spatial effect on housing prices through the geographic location.