• Bulletin of the Korean Mathematical Society
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• v.33 no.1
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• pp.97-106
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• 1996

The study of surface in a Euclidean space whose Gauss map G satisfies the condition : \DeltaG = AG(*)$ for some matrix A was studied by C. Baikoussis, D. E. Blair, B. Y. Chen, F. Dillen, L. Verstraelen ([1]1, [2], [7]) and so on.

• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.148-151
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• 2004

This study presents a new intelligent yield management methodology which can forecast the yield level of a production unit based on features' behaviors. In this proposed methodology, we identify the existing features using C5.0 that are combination of nodes (i.e., variables) in the decision tree generated by C5.0, use SOM(Self-Organizing Map) neural networks in oder to extract the feature's patterns and classify, and then make features' control rules using C5.0.

• Journal of Hydrogen and New Energy
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• v.23 no.6
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• pp.604-611
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• 2012

For the commercialization of fuel cell powered vehicle, it is highly important to improve the performance and efficiency of an automotive polymer electrolyte membrane fuel cell (PEMFC) system. The performance and efficiency of PEMFC systems are significantly influenced by their operating conditions. Among these conditions, the system operating pressure is considered as the one of the main factors. In this study, to investigate the effects of operating pressure on the performance and efficiency of automotive PEMFC systems, two types of high-pressure operating PEMFC systems adopting two different compressors (i. e. different performance maps) are modeled by using MATLAB/Simulink environment. The PEMFC system efficiency and parasitic compressor power are mainly analyzed and compared for the two types of high-pressure operating PEMFC systems under the same system net power conditions. It is expected that this kind of study can contribute to provide basic insight into the operating strategies of high-pressure operating PEMFC systems for automotive use.

• Journal of Information Technology Applications and Management
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• v.28 no.4
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• pp.59-78
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• 2021

Mobile Grocery Shopping (MGS) has become the New Normal as the COVID-19 pandemic has changed the way consumers shop. Drawing on the framework of Customer Journey Map (CJM), this study explores consumers' MGS by identifying specific stages of Customer Journey and comparing consumers' satisfaction between PC-based online and mobile shopping experiences at each stage throughout the journey. This study collected 562 responses from subjects who have mobile and PC-based grocery shopping experiences at the major domestic e-Commerce platforms. Independent t-test analysis showed that differences in satisfaction between mobile and online shopping experiences exist in 5 main stages and 16 sub-stages of CJM. The results of service and technological innovation mentioned in the actual industry report were seen as empirical results leading to continued use of MGS as well as customer satisfaction. The findings of this study contribute to the research stream on Customer Journey by adopting the structure of CJM and analyzing specific stages of the journey in the context of MGS. Managerial implications for mobile-based business practitioners are also discussed.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.53-57
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• 2005

The moors ecosystem is sensitive environment change and weak in artificial interference. These nature property are very important to people. It is necessary to preservation and protection the moors with a countermeasure. We really need to Environment-GIS(E-GIS) using Geographical Information System(GIS) and digital map including range, correct position and attribute data of moors. In this study, we take priority of making a database of moors management. Taking effect an environment assesment, we concentrate on a standard method of digital map production and a preservation of moors in our research using GIS. Especially, we have to preserve our important national heritage using GIS when Environment Assesment is conducting under construction. We suggest to pre-estimated model of hidden moors as analysing terrain, geological feature, a geographical distribution of plants and animals using GIS.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.83-98
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• 2021

Urban green space is an important component for enhancing urban ecosystem health. Thus, identifying the spatial structure of urban green space is required to manage a healthy urban ecosystem. The Ministry of Environment has provided the level 3 land cover map(the highest (1m) spatial resolution map) with a total of 41 classes since 2010. However, specific urban green information such as street trees was identified just as grassland or even not classified them as a vegetated area in the map. Therefore, this study classified detailed urban green information(i.e., tree, shrub, and grass), not included in the existing level 3 land cover map, using two types of high-resolution(<1m) remote sensing data(i.e., airborne LiDAR and RGB ortho imagery) in Suwon, South Korea. U-Net, one of image segmentation deep learning approaches, was adopted to classify detailed urban green space. A total of three classification models(i.e., LRGB10, LRGB5, and RGB5) were proposed depending on the target number of classes and the types of input data. The average overall accuracies for test sites were 83.40% (LRGB10), 89.44%(LRGB5), and 74.76%(RGB5). Among three models, LRGB5, which uses both airborne LiDAR and RGB ortho imagery with 5 target classes(i.e., tree, shrub, grass, building, and the others), resulted in the best performance. The area ratio of total urban green space(based on trees, shrub, and grass information) for the entire Suwon was 45.61%(LRGB10), 43.47%(LRGB5), and 44.22%(RGB5). All models were able to provide additional 13.40% of urban tree information on average when compared to the existing level 3 land cover map. Moreover, these urban green classification results are expected to be utilized in various urban green studies or decision making processes, as it provides detailed information on urban green space.

• Korean Journal of Pharmacognosy
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• v.44 no.2
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• pp.118-124
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• 2013

Mast cells is the key effector cells for IgE-mediated allergic responses. In this study, we investigated whether Rhus trichocarpa extract (RT) inhibited IgE-mediated allergic responses in mast cells and an allergic animal model. We further tried to find its mechanism of action in mast cells. We found that RT suppressed antigen-stimulated degranulation and production of TNF-${\alpha}$ and IL-4 in rat basophilic leukemia (RBL)-2H3 mast cells and bone marrow-derived mast cells (BMMC), as well as IgE-mediated passive cutaneous anaphylaxis (PCA) in mice. As the mechanism of action of RT, it inhibited the activation of spleen tyrosine kinase (Syk), a pivotal signaling molecule for activation of mast cells and that of LAT, a downstream adaptor molecule of Syk in $Fc{\varepsilon}RI$-mediated signal pathways. RT also suppressed the activation of mitogen-activated protein (MAP) kinases and Akt. The current results demonstrated for the first time that RT has the anti-allergic effect through inhibiting degranulation and secretion of cytokines by suppression of Syk in antigen-stimulated mast cells. Therefore, RT might be useful for allergic diseases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.7
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• pp.1305-1310
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• 2007

ePosition is a technology that can provide the spacial position of the earth to the information of ePosition ID through the Internet. It is serving the information of land location based on the Internet using the ePosition technology now, but it needs the service technique which can supply the marine data and the information of maritime position. Moreover, to support the information service of marine position, it needs the ENC linked technique based on S-57 that is an IHO transfer standard for digital hydrographic data. In this paper, therefore, it develops a linkage method for applying and utilizing the ePosition technology to ENC data, and supplements the base technology for applying it to marine related fields. As study method, firstly, this paper analyses ENC data model and structure, and converses for processing ENC file to ePosition data. Lastly, it derives the interconnection method with ePosition database and shows the ePosition service application based on the linked data and its validity.

• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1239-1247
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• 2009

Study the gene about economical characteristic of human disease or domestic animal is a matter of grave interest, preserve and elevation of gene of Korea cattle is key subject. Studies have been done on the gene of Korea cattle using EST based SNP map, but it is based on statistical model, therefore there are difference between real position and statistical position. These problems are solved using both EST_based SNP map and Gene on sequence by Lee et al. (2009b). We have used multifactor dimensionality reduction(MDR) method to study interaction effect of statistical model in general. But MDR method cannot be applied in all cases. It can be applied to the only case-control data. So, method is suggested E-MDR method using CART algorithm. Also we identified interaction effects of single nucleotide polymorphisms(SNPs) responsible for average daily gain(ADG) and marbling score(MS) using E-MDR method.

• Spatial Information Research
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• v.11 no.2
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• pp.101-117
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• 2003

High resolution satellite image analysis has been recognized as an effective technique for monitoring local land-cover and atmospheric changes. In this study, a new high resolution map for land-cover was generated using both high-resolution IKONOS image and conventional land-use mapping. Fuzzy classification method was applied to classify land-cover, with minimum operator used as a tool for joint membership functions. In separateness analysis, the values were not great for all bands due to discrepancies in spectral reflectance by seasonal variation. The land-cover map generated in this study revealed that conifer forests and farm land in the ground and tidal flat and beach in the ocean were highly changeable. The kappa coefficient was 0.94% and the overall accuracy of classification was 95.0%, thus suggesting a overall high classification accuracy. Accuracy of classification in each class was generally over 90%, whereas low classification accuracy was obtained for classes of mixed forest, river and reservoir. This may be a result of the changes in classification, e.g. reclassification of paddy field as water area after water storage or mixed use of several classification class due to similar spectral patterns. Seasonal factors should be considered to achieve higher accuracy in classification class. In conclusion, firstly, IKONOS image are used to generated a new improved high resolution land-cover map. Secondly, IKONOS image could serve as useful complementary data for decision making when combined with GIS spatial data to produce land-use map.