• Journal of the Korean Geotechnical Society
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• v.15 no.3
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• pp.161-176
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• 1999

A powerful numerical method that can be used for modeling rock-structure interaction is the Discontinuous Deformation Analysis (D D A) method developed by Shi in 1988. In this method, rock masses are treated as systems of finite and deformable blocks. Large rock mass deformations and block movements are allowed. Although various extensions of the D D A method have been proposed in the literature, the method is not capable of modeling water-block interaction, sequential loading or unloading and rock reinforcement; three features that are needed when modeling surface or underground excavation in fractured rock. This paper presents three new extensions to the D D A method. The extensions consist of hydro-mechanical coupling between rock blocks and steady water flow in fractures, sequential loading or unloading, and rock reinforcement by rockbolts, shotcrete or concrete lining. Examples of application of the D D A method with the new extensions are presented. Simulations of the underground excavation of the \ulcornerUnju Tunnel\ulcorner in Korea were carried out to evaluate the influence of fracture flow, excavation sequence and reinforcement on the tunnel stability. The results of the present study indicate that fracture flow and improper selection of excavation sequence could have a destabilizing effect on the tunnel stability. On the other hand, reinforcement by rockbolts and shotcrete can stabilize the tunnel. It is found that, in general, the D D A program with the three new extensions can now be used as a practical tool in the design of underground structures. In particular, phases of construction (excavation, reinforcement) can now be simulated more realistically.

• Korean Journal of Construction Engineering and Management
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• v.17 no.3
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• pp.32-42
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• 2016

In Korea, the absence of BIM use in existing civil structures and buildings is driving a demand for as-built BIM. As-built BIMs are often created using laser scanners that provide dense 3D point cloud data. Conventional static laser scanning approaches often suffer from limitations in their operability due to the difficulties in moving the equipment, the selection of scanning location, and the requirement of placing targets or extracting tie points for registration of each scanned point cloud. This paper aims at reducing the manual effort using a kinematic 3D laser scanning system based on graph-based simultaneous localization and mapping (SLAM) for continuous indoor mapping. The robotic platform carries three 2D laser scanners: the front scanner is mounted horizontally to compute the robot's trajectory and to build the SLAM graph; the other two scanners are mounted vertically to scan the profiles of surrounding environments. To reduce the accumulated error in the trajectory of the platform through loop closures, the graph-based SLAM system incorporates AdaBoost loop closure approach, which is particularly suitable for the developed multi-scanner system providing more features than the single-scanner system for training. We implemented the proposed method and evaluated it in two indoor test sites. Our experimental results show that the false positive rate was reduced by 13.6% and 7.9% for the two dataset. Finally, the 2D and 3D mapping results of the two test sites confirmed the effectiveness of the proposed graph-based SLAM.

• Journal of Korean Society of Forest Science
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• v.109 no.2
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• pp.231-242
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• 2020

This study identified the types and features of forest leisure activities based on data from the Nationwide Survey on Forest Leisure Activities (N= 6,191). Further, the study analyzed the demographic impact factors of the categorized forest leisure activities according to four types of objectives reported by visitors: health promotion, education, relaxation, and leisure sports. The investigation revealed that people visit forests for relaxation regardless of the season; however, leisure-sports visitors engage in activities that occur in summer, are most expensive, and involve the shortest trip time. The study also found that age, gender, household incomes, and the presence of children were the most important factors influencing the selection of activities. Age was found the predominant consideration: the older the age was, the more likely people were to prefer the relaxation and health promotion type. Men were more likely to choose health promotion activities over relaxation and tended to prefer educational trips over relaxation when accompanied by children. Higher household incomes corresponded to an increased likelihood of visitor preferences for relaxation over education and for health promotion over relaxation. This study contributes to the extant literature by statistically determining the nationwide predominance of age as the principal factor driving visitor preferences for forest leisure activities. Future studies should establish policy directions for forest welfare from the perspective of users grouped into day visitors and overnight guests.

• Journal of the Korea Society of Computer and Information
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• v.14 no.9
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• pp.11-19
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• 2009

A RAM-based Neural Net(RBNN) which has multi-discriminators is more effective than RBNN with a discriminator. Experience Sensitive Cumulative Neural Network and 3-D Neuro System(3DNS) that accumulate the features point improved the performance of BNN, which were enabled to train additional and repeated patterns and extract a generalized pattern. In recognition process of Neural Net with multi-discriminator, the selection of class was decided by the value of MRD which calculates the accumulated sum of each class. But they had a saturation problem of its memory cells caused by learning volume increment. Therefore, the decision of MRD has a low performance because recognition rate is decreased by saturation. In this paper, we propose the method which improve the MRD ability. The method consists of the optimum MRD and the matching ratio prototype to generalized image, the cumulative filter ratio, the gap of prototype response MRD. We experimented the performance using NIST database of NIST without preprocessor, and compared this model with 3DNS. The proposed MRD method has more performance of recognition rate and more stable system for distortion of input pattern than 3DNS.

• Journal of Plant Biotechnology
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• v.42 no.4
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• pp.326-335
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• 2015

Citrus is an economically important fruit tree with the largest amount of fruit production in the world. It provides important nutrition such as vitamin C and other health-promoting compounds including its unique flavonoids for human health. However, it is classified into the most difficult crops to develop new cultivars through conventional breeding approaches due to its long juvenility and some unique reproductive biological features such as gamete sterility, nucellar embryony, and high level of heterozygosity. Due to global warming and changes in consumer trends, establishing a systematic and efficient breeding programs is highly required for sustainable production of high quality fruits and diversification of cultivars. Recently, reference genome sequences of sweet orange and clementine mandarin have been released. Based on the reference whole-genome sequences, comparative genomics, reference-guided resequencing, and genotyping-by-sequencing for various citrus cultivars and crosses could be performed for the advance of functional genomics and development of traits-related molecular markers. In addition, a full understanding of gene function and gene co-expression networks can be provided through combined analysis of various transcriptome data. Analytic information on whole-genome and transcriptome will provide massive data on polymorphic molecular markers such as SNP, INDEL, and SSR, suggesting that it is possible to construct integrated maps and high-density genetic maps as well as physical maps. In the near future, integrated maps will be useful for map-based precise cloning of genes that are specific to citrus with major agronomic traits to facilitate rapid and efficient marker-assisted selection.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.1-12
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• 2017

The Seoul metropolitan transportation card's high value lies in its recording of total population movements of the public transit system. In case of recorded information on transit by bus, even though route information utilized by each passenger is accurate, the lack of passenger transfer information of the urban railway makes it difficult to estimate correct routes taken by each passenger. Therefore, pinpointing passenger path selection patterns arising in the metropolitan railway network and using this as part of a path movement estimation model is essential. This research seeks to determine that features of passenger movement routes in the urban railway system is comprised of M-similar routes with increasing number of transfer reflected as additional costs. In order to construct the path finding conditions, an M-similar route searching method is proposed, embedded with non additive path cost which appears through inclusion of the stepwise transportation parameter. As well, sensitivity of the M-similar route method based on transportation card records is evaluated and a stochastic trip assignment model using M-similar path finding is constructed. From these, link trip and transfer trip results between lines of the Seoul metropolitan railway are presented.

• Journal of the Korean association of regional geographers
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• v.2 no.2
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• pp.183-196
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• 1996

The purpose of this paper is to explore the possibility of automatic extraction of line feature from Satellite image. The first part reviews the relationship between spatial filtering and cartographic interpretation. The second part describes the principal operations of high frequency filters and their properties, the third part presents the result of filtering application to the SPOT Panchromatic image of the Chinju city. Some experimental results are given here indicating the high feasibility of the filtering technique. The results of the paper is summarized as follows: Firstly the good all-purposes filter dose not exist. Certain laplacian filter and Frei-chen filter were very sensitive to the noise and could not detect line features in our case. Secondly, summary filters and some other filters do an excellent job of identifying edges around urban objects. With the filtered image added to the original image, the interpretation is more easy. Thirdly, Compass gradient masks may be used to perform two-dimensional, discrete differentiation directional edge enhancement, however, in our case, the line featuring was not satisfactory. In general, the wide masks detect the broad edges and narrow masks are used to detect the sharper discontinuities. But, in our case, the difference between the $3{\times}3$ and $7{\times}7$ kernel filters are not remarkable. It may be due to the good spatial resolution of Spot scene. The filtering effect depends on local circumstance. Band or kernel size selection must be also considered. For the skillful geographical interpretation, we need to take account the more subtle qualitative information.

• Economic and Environmental Geology
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• v.55 no.4
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• pp.353-366
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• 2022

Spatial estimation of geoscience data (geo-data) is challenging due to spatial heterogeneity, data scarcity, and high dimensionality. A novel spatial estimation method is needed to consider the characteristics of geo-data. In this study, we proposed the application of Gaussian Mixture Model (GMM) among machine learning algorithms with multivariate data for robust spatial predictions. The performance of the proposed approach was tested through soil chemical concentration data from a former smelting area. The concentrations of As and Pb determined by ex-situ ICP-AES were the primary variables to be interpolated, while the other metal concentrations by ICP-AES and all data determined by in-situ portable X-ray fluorescence (PXRF) were used as auxiliary variables in GMM and ordinary cokriging (OCK). Among the multidimensional auxiliary variables, important variables were selected using a variable selection method based on the random forest. The results of GMM with important multivariate auxiliary data decreased the root mean-squared error (RMSE) down to 0.11 for As and 0.33 for Pb and increased the correlations (r) up to 0.31 for As and 0.46 for Pb compared to those from ordinary kriging and OCK using univariate or bivariate data. The use of GMM improved the performance of spatial interpretation of anthropogenic metals in soil. The multivariate spatial approach can be applied to understand complex and heterogeneous geological and geochemical features.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.519-528
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• 2023

The visual characteristics of the World Cup emblem play an important role in conveying culture and identity, highlighting the key elements of the Games, and strengthening the brand image. This study first investigated the visual elements and theoretical background of the emblem through previous studies. Second, the selection of symbolism, shape, and color was the subject of the study. Third, based on the shape-related theory based on the '100 National Cultural Symbols', the analysis was performed using the 'IRI Color Matching Image Scale' as a tool, and a final conclusion was drawn. The World Cup emblem uses a lot of ethnic and living symbols, and the living and ethnic symbols are expressed in a combination. In the beginning, there were many symmetric shapes, but after that it changed to an asymmetric shape. The curved expression form is more used than the straight expression form. And most of the color arrangement image scale distribution shows light, dynamic and modern color arrangement characteristics. In the future, the World Cup emblem design will continue to use national and living symbols. The shape of the emblem should use curves and asymmetric designs, be intuitive, and directly reflect the theme of the competition. In addition, the national flag color should be used as the main color, and other colors should be used as secondary colors. The combination of colors must match the light, dynamic and modern color characteristics of the IRI color scheme image scale.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.3
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• pp.221-230
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• 2004

In general, remote monitoring systems monitor the status of distributed hosts and/or applications in real-time for diverse managerial purposes. However, most of the extant systems have a few undesirable problems. First of all, they are platform-dependent and are not resilient to network and/or host failures. Moreover, they normally focus on the resource usage trends in monitored hosts, rather than on the status change of the applications running on them. We strongly believe that the latter has more direct and profound effect on the resource usage patterns on each host. In this paper, we present the design and implementation of the Remote Applications Monitoring System (RAMS) that enables us to effectively manage distributed applications through a real-time monitoring of their respective resource usages. The RAMS is a centralized system that consists of many distributed agents and a single centralized manager. An agent on each host is in charge of collecting and reporting the status of local applications. The manager handles agent registration and provides a central access point to the selection and monitoring of distributed applications. The salient features of the system include robustness and portability The adoption of JINI greatly facilitates an automatic recovery from partial network failure and host failure.