• Journal of the Korean earth science society
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• v.31 no.5
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• pp.437-447
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• 2010

Spatial estimation of environmental variables has been regarded as an important preliminary procedure for decision-making. A minimum variance criterion, which has often been adopted in traditional kriging algorithms, does not always guarantee the optimal estimates for subsequent decision-making processes. In this paper, a geostatistical framework is illustrated that consists of uncertainty modeling via stochastic simulation and risk modeling based on loss functions for the selection of optimal estimates. Loss functions that quantify the impact of choosing any estimate different from the unknown true value are linked to geostatistical simulation. A hybrid loss function is especially presented to account for the different impact of over- and underestimation of different land-use types. The loss function-specific estimates that minimize the expected loss are chosen as optimal estimates. The applicability of the geostatistical framework is demonstrated and discussed through a case study of copper mapping.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.5
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• pp.1-7
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• 2011

The objective of this study is to decide a spatial interpolation method on temperature data for the suitability analysis of garlic cultivation. In Korea, garlic is the second most cultivated condiment vegetable after red pepper. Nowadays warm-temperate garlic faces potential shift of its arable area according to warmer temperature in the Korean Peninsula, and the change can be drawn with the precise temperature map derived from interpolation on point-measured data. To find the preferable interpolation method in cases of germination and vegetative period of the garlic, different approaches were tested as follows: Inverse Distance Weighted (IDW), Spline, Ordinary Kriging (OK), and Universal Kriging (UK). As a result, IDW and UK show the lowest root mean square errors as for the germination and vegetative seasons, respectively. However, statistically significant difference was not revealed among the applied methods regarding the germinating period. Eventually this will contribute to mapping the suitable lands for the cultivation of warm-temperate garlic reasonably.

• Journal of information and communication convergence engineering
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• v.18 no.2
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• pp.69-74
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• 2020

Myanmar, also known as Burma, has a rich cultural heritage, and its historical tourist attractions well known around the world. Therefore, we designed and developed an interactive spatial augmented reality (iSAR) book on the cultural heritage of Myanmar. This iSAR book has total of 18 pages with rich media content including videos, animations, audio, and images featuring the cultural heritage of Myanmar in a digital format. In addition to virtual content, navigational features such as virtual buttons and touch-based hand gestures were implemented using Leap Motion and VVVV. Therefore, the developed iSAR book allows virtual content and navigational features to merge seamlessly into a physical book. Five participants were recruited to evaluate the prototype iSAR book, and interviews were conducted to gather their feedback based on its immersive qualities. Thus, the developed iSAR book on Myanmar effectively shares the cultural heritage of Myanmar, and ultimately allows users to explore and gain more insight into the country.

• Journal of the Korea Society of Computer and Information
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• v.21 no.3
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• pp.97-104
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• 2016

In this paper, we propose spatial information based simulator for user experience optimization and minimize real space complexity. We focus on developing simulator how to design virtual space model and to implement virtual character using real space data. Especially, we use expanded events-driven inference model for SVM based on machine learning. Our simulator is capable of feature selection by k-fold cross validation method for optimization of data learning. This strategy efficiently throughput of executing inference of user behavior feature by virtual space model. Thus, we aim to develop the user experience optimization system for people to facilitate mapping as the first step toward to daily life data inference. Methodologically, we focus on user behavior and space modeling for implement virtual space.

• Journal of the Korea Computer Industry Society
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• v.8 no.2
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• pp.113-122
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• 2007

Recently, there are many research interests in providing efficient, temporal and spatial distribution multimedia streaming service. This paper proposed a temporal and spatial object grouping method for distribution multimedia streaming service. The proposed method performs the grouping structure by filtering and mapping with the collected frame object in application domains and it's peformed by JM relationship with the mapped frame objects. The results show that the performance provides the better than the other methods.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.117-122
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• 2002

In this paper, we propose Media GIS web service architecture using 3D geographical database and GPS-related data resulted from 4S-Van. We introduce a novel interoperable geographical data service concept; so-called, Virtual World Mapping (VWM) that can map 3D graphic world with real-world video. Our proposed method can easily retrieve geographical in-formation and attributes to reconstruct 3D virtual space according to certain frame in video sequences. Our proposed system architecture also has an advantage that can provide geographical information service with video stream without any image processing procedures. In addition to, describing the details of our components, we present a Media GIS web service system by using GeoVideo Server, which performs VWM technique.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.3
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• pp.73-82
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• 2012

In order to carry out efficient investment and successful business in national geo-spatial industry, economic assessment on the field of 3D geo-information has recently emerged as a serious issue. Therefore, this study is intended to offer cost-effective evaluation scheme which are proper for 3D geo-spatial information, especially focusing on development of orthophoto and DEM. The study is organized as follows. The first section clarifies preliminary rules for feasibility by defining target work and category in order to estimate benefit. Then, this paper will be limited to consideration of production of digital mapping for target business which is expected to create high value and its benefit from cost reduction is suggested. Drawing from the AHP(Analytic Hierarchy Process) methods, this study comprehensively described final result and implication to examine business value. Consequently, this study can suggest economical evaluation methods on 3D geo-spatial information industry, which takes up a considerable part of immaterial benefit and has difficulties in economic assessment and estimation. preventing a variety of errors in system operation in advance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2737-2753
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• 2013

In this study, we propose a novel salient object detection strategy based on regional contrast and relative spatial compactness. Our algorithm consists of four basic steps. First, we learn color names offline using the probabilistic latent semantic analysis (PLSA) model to find the mapping between basic color names and pixel values. The color names can be used for image segmentation and region description. Second, image pixels are assigned to special color names according to their values, forming different color clusters. The saliency measure for every cluster is evaluated by its spatial compactness relative to other clusters rather than by the intra variance of the cluster alone. Third, every cluster is divided into local regions that are described with color name descriptors. The regional contrast is evaluated by computing the color distance between different regions in the entire image. Last, the final saliency map is constructed by incorporating the color cluster's spatial compactness measure and the corresponding regional contrast. Experiments show that our algorithm outperforms several existing salient object detection methods with higher precision and better recall rates when evaluated using public datasets.

• Korean Journal of Cognitive Science
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• v.10 no.1
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• pp.45-55
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• 1999

This paper argues that the basic modes of spatial cognition can be best identified in terms of argument/participant location, and shows that natural language uses‘simple’types of semantic denotations to encode spatial cognition, and further notes that spatial expressions should be interpreted not as locating an event/state as a whole but as locating arguments/participants of the event. The ways of locating events/states are identified in terms of argument orientation(AO), Which indicates semantic patterns of linkiarticipant location. and shows that natural langrage uses ng locatives to specific arguments. Four patterns of argument orientation described here reveal substantial modes of spatial cognition. and the AO patterns are mostly determined by the semantic classes of English verbs combining with locative expressions, i.e., by the event type of the predicate. As for the denotational constraint of locatives, the paper concludes that semantic denotations of locative PPs are restricted to the intersecting functions mapping relations to relations.

• Journal of The Geomorphological Association of Korea
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• v.23 no.3
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• pp.67-78
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• 2016

Soil carbon(C) is an essential property for characterizing soil quality. Understanding spatial patterns of soil C is particularly limited for mountain areas. This study aims to predict the spatial pattern of soil C using terrain analysis in a steep mountainous area. Specifically, model performances and prediction uncertainties were investigated based on the number of resampling repetitions. Further, important predictors for soil C were also identified. Finally, the spatial distribution of uncertainty was analyzed. A total of 91 soil samples were collected via conditioned latin hypercube sampling and a digital soil C map was developed using support vector regression which is one of the powerful machine learning methods. Results showed that there were no distinct differences of model performances depending on the number of repetitions except for 10-fold cross validation. For soil C, elevation and surface curvature were selected as important predictors by recursive feature elimination. Soil C showed higher values in higher elevation and concave slopes. The spatial pattern of soil C might possibly reflect lateral movement of water and materials along the surface configuration of the study area. The higher values of uncertainty in higher elevation and concave slopes might be related to geomorphological characteristics of the research area and the sampling design. This study is believed to provide a better understanding of the relationship between geomorphology and soil C in the mountainous ecosystem.