• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.90-103
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• 2012

Mallipo is a representative beach contaminated by Hebei Spirit oil spill accident in December 2007. This study aims to compare the differences of two seasons (winter and summer) for the spatio-temporal variation patterns of oiling status in the whole area and divided five regions of Mallipo beach. In the whole area, the decreasing rate of average TPH (total petroleum hydrocarbon) in winter was twice greater than summer during four years. According to the spatial variation pattern analysis of oiling status using weighted mean center and weighted standard distance, the oil concentration was clustered on southwestern region in winter, however, the TPH was dispersed in the whole area in summer. Temporal variation pattern of TPH in each of Mallipo's five regions showed that TPH had been consistently decreased in winter, but oil concentration had not been changed in summer since 2009 except the southwestern region. Therefore, in order to evaluate and predict the progress of oiling status, it is needed to analyze the spatio-temporal variation pattern of TPH using spatial analysis after separating data into seasons (e.g., winter and summer). In addition, time series analysis is useful in the regional scales through spatial partitioning rather than the whole beach area for the understanding of temporal variation pattern.

• Economic and Environmental Geology
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• v.36 no.3
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• pp.243-255
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• 2003

The mathematical models for GIS-based spatial data integration have been developed for geological applications such as mineral potential mapping or landslide susceptibility analysis. Among various models, the effectiveness of fuzzy logic based integration of multiple sets of geological data is investigated and discussed. Unlike a traditional target-driven fuzzy integration approach, we propose a data-driven approach that is derived from statistical relationships between the integration target and related spatial geological data. The proposed approach consists of four analytical steps; data representation, fuzzy combination, defuzzification and validation. For data representation, the fuzzy membership functions based on the likelihood ratio functions are proposed. To integrate them, the fuzzy inference network is designed that can combine a variety of different fuzzy operators. Defuzzification is carried out to effectively visualize the relative possibility levels from the integrated results. Finally, a validation approach based on the spatial partitioning of integration targets is proposed to quantitatively compare various fuzzy integration maps and obtain a meaningful interpretation with respect to future events. The effectiveness and some suggestions of the schemes proposed here are illustrated by describing a case study for landslide susceptibility analysis. The case study demonstrates that the proposed schemes can effectively identify areas that are susceptible to landslides and ${\gamma}$ operator shows the better prediction power than the results using max and min operators from the validation procedure.

• Journal of KIISE:Software and Applications
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• v.27 no.1
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• pp.62-73
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• 2000

In this paper, we propose a criteria which can be applied to classify conventional color feature based Content Based Image Retrieval (CBIR) methods with its application areas, and a new image retrieval method which can represent sufficient spatial information in the image and is powerful in invariant searching to translation, rotation and enlargement transform. As the conventional color feature based CBIR methods can not sufficiently include the spatial information in the image, in general, they have drawbacks, which are weak to the translation or rotation, enlargement transform. To solve it, they have represented the spatial information by partitioning the image. Retrieval efficiency, however, is decreased rapidly as increasing the number of the feature vectors. We classify conventional methods to ones using 1st order relations and ones using 2nd order relations as their color object relation, and propose a new method using 3rd order relation of color objects which is good for the translation, rotation and enlargement transform. It makes quantized 24 buckets and selects 3 high scored histogram buckets and calculates 3 mean positions of pixels in 3 buckets and 3 angles. Then, it uses them as feature vectors of a given image. Experiments show that the proposed method is especially good at enlarged images and effective for its small calculation.

• Korean Journal of Agricultural Science
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• v.43 no.4
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• pp.537-546
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• 2016

The development of models for agriculture systems, especially for crop production, has supported the prediction of crop yields under various environmental change scenarios and the selection of better crop species or cultivar. Crop models could be used as tools for supporting reasonable nutrient management approaches for agricultural land. This paper outlines the simplified structure of main crop models (crop growth model, crop-soil model, and crop-soil-environment model) frequently used in agricultural systems and shows diverse application of their simulated results. Crop growth models such as LINTUL, SUCROS, could provide simulated data for daily growth, potential production, and photosynthesis assimilate partitioning to various organs with different physiological stages, and for evaluating crop nutrient demand. Crop-Soil models (DSSAT, APSIM, WOFOST, QUEFTS) simulate growth, development, and yields of crops; soil processes describing nutrient uptake from root zone; and soil nutrient supply capability, e.g., mineralization/decomposition of soil organic matter. The crop model built for the DSSAT family software has limitations in spatial variability due to its simulation mechanism based on a single homogeneous field unit. To introduce well-performing crop models, the potential applications for crop-soil-environment models such as DSSAT, APSIM, or even a newly designed model, should first be compared. The parameterization of various crops under different cultivation conditions like those of intensive farming systems common in Korea, shortened crop growth period, should be considered as well as various resource inputs.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.40 no.2
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• pp.84-94
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• 2007

The comparative feeding ecology of greenling Hexagrammos otakii and Schlegel's black rockfish Sebastes schlereli populations was investigated in the Jangbong tidal flat near Incheon, Korea. Monthly samples were taken using a modified otter trawl from November 1999 to January 2001. The stomach contents of 124 greenling and 115 Schlegel's black rockfish were analyzed. The diet of H. otakii was dominated by the amphipods Gammaropsis iaponicus, Caprella scaura, Isaeopsis sp. and Monocorophium acherusicum, the shrimps Latreutes mucronatus and Alpheus japonicus, the mysid Neomysis orientalis and the bivalve Mytilus edulis. In contrast, S. schlegeli mainly fed on the mysids N. orientalis, N japonica, and N. awatschensis, the shrimps Exopalaemon carinicauda, A. japonicus and L. mucronatus, and the fish Pholis fangi and unidentified gobiids. A comparison of the frequency and abundance of food items showed that crustaceans (e.g. amphipods, mysids and shrimps) were important foods for both species. Their main dietary components, however differed which is probably due to differences in the spatial distribution of the two species and their prey items. In conclusion, greenling and Schlegel's black rockfish, despite being sympatric on a tidal flat have distinct food habits and low dietary overlap (Schooner's index: 0.1). These results indicate, to some extent, resource partitioning for the maximum utilization of available foods in the tidal flat.

• Journal of Korea Multimedia Society
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• v.7 no.3
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• pp.388-398
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• 2004

This paper focuses on the reduction method of message traffic occurred when multiple participants collaborate in the distributed virtual environment. It is referred to as filtering method of update message to minimize data traffic exchanged in the virtual environment, and it is the essential process to improve the scalability of the virtual environment. Spatial partitioning method, a popular filtering technique, divides the whole environment into smaller sub-parts in order to make it small the regions to be maintained consistently. However, it is less flexible and adaptable because the information of area of interest must be configured before simulation. In this paper, the concept of dynamic area of interest is proposed, which is highly adaptable by applying dynamic environmental elements to AOI management. It uses multiple layering and multiple consistency algorithms for dynamic management, and makes it possible to consume system resource efficiently. For performance evaluation, experiments are performed with virtual avatars, measuring message traffic. Finally, the proposed model could be applied to the AOI management systems which accommodate massive users like MMORPG, or virtual communities.

• Journal of Korea Multimedia Society
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• v.7 no.4
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• pp.550-558
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• 2004

Previous researches on scalability problem of distributed virtual environment (DVE) have been mainly focused on spatial partitioning of area of interest (AOI). Congestion phenomena by avatar groups in AOI have been neglected relatively However, AOI congestion is highly related to scalability of DVE because it exhausts system resources such as network bandwidth and rendering time, and could be a bar to perform collaboration among participants. In this paper, this will be defined as the problem that must be solved for the realization of the scalable DVE, and a model will be proposed to measure and control congestion situation in AOI. The purposes of the proposed model are to prevent high density of participants in AOI, and to protect stable collaboration in DVE. For evaluation of the performance it is compared with a previous method by defining the resource cost model which is dynamically activated to AOI congestion.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.527-531
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• 2003

Previous researches on scalability problem of distributed virtual environment (DVE) have been mainly focused on spatial partitioning of area of interest (AOI). Congestion phenomena by avatar groups in AOI have been neglected relatively. However, AOI congestion is highly related to scalability of DVT because it exhausts system resources such as network bandwidth and rendering time, and could be a bar to perform collaboration among participants. In this paper, this will be defined as the problem that must be solved for the realization of the scalable DVE, and a model will be proposed to measure and control congestion situation in AOI. The purposes of the proposed model are to prevent high density of participants in AOI, and to protect stable collaboration in DVE. For evaluation of the performance it is compared with a previous method by defining the resource cost model which is dynamically activated to AOI congestion.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.39 no.spc1
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• pp.165-179
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• 2006

Food habits of the gavelin goby Acanthogobius hasta and the fine spot goby Chaeturichtys stigmatias populations were investigated in the Jangbong tidal flat near Incheon, Korea. Samples were taken monthly from November 1999 to January 2001. The gut contents of 248 gavelin gobies and 139 fine spot gobies were analyzed. The diet of the gavelin goby was dominated by the gammaridean amphipod Chitinomandibulum emargicoxa, the crabs Macrophthalmus japonicus and Ilyoplax pingi, the shrimp Exopalaemon carinicauda, the bivalve Raetellops pulchella and the macro-algae Porphyra tenera. On the other hand, the fine spot goby mainly feed on the shrimps Crangon affinis, Latreutes mucronatus, E. carinicauda and Alpheus japonicus, the gammaridean amphipods C. emargicoxa and Synchelidium miraculum, and the bivalve R. pulchella. A comparison between frequencies of occurrence and abundance of food items in the gut showed that crustaceans (gammaridean amphipods, crabs and shrimps) and bivalves were important foods for the two gobies. However, the main components of the gut contents were different between two species, though this was probably due to differences in spatial distribution patterns of gobies and their prey items. In conclusion, both the gavelin goby and the fine spot goby, despite being the related species and co-inhabiting the similar part of the tidal flat, had quite distinct food habits and low dietary overlap (Schoener's index: 0.4). These indicated that the two gobies are or were partitioning resources in space and time for maximum uitilization of available food.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.105-113
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• 2019

Physically-based fluid simulation takes a lot of time for high resolution. To solve this problem, there are studies that make up the limitation of low resolution fluid simulation by using deep running. Among them, Super-resolution, which converts low-resolution simulation data to high resolution is under way. However, traditional techniques require to the entire space where there are no density data, so there are problems that are inefficient in terms of the full simulation speed and that cannot be computed with the lack of GPU memory as input resolution increases. In this paper, we propose a new method that divides and classifies 2D smoke simulation data into the space using the quad tree, one of the spatial partitioning methods, and performs Super-resolution only required space. This technique accelerates the simulation speed by computing only necessary space. It also processes the divided input data, which can solve GPU memory problems.