• 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 Microbiology and Biotechnology
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• v.26 no.7
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• pp.1320-1332
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• 2016

Light hydrocarbons accumulated in subsurface soil by long-term microseepage could favor the anomalous growth of indigenous hydrocarbon-oxidizing microorganisms, which could be crucial indicators of underlying petroleum reservoirs. Here, Illumina MiSeq sequencing of the 16S rRNA gene was conducted to determine the bacterial community structures in soil samples collected from three typical oil and gas fields at different locations in China. Incubation with n-butane at the laboratory scale was performed to confirm the presence of "universal microbes" in light-hydrocarbon microseepage ecosystems. The results indicated significantly higher bacterial diversity in next-to-well samples compared with background samples at two of the three sites, which were notably different to oil-contaminated environments. Variation partitioning analysis showed that the bacterial community structures above the oil and gas fields at the scale of the present study were shaped mainly by environmental parameters, and geographic location was able to explain only 7.05% of the variation independently. The linear discriminant analysis effect size method revealed that the oil and gas fields significantly favored the growth of Mycobacterium, Flavobacterium, and Pseudomonas, as well as other related bacteria. The relative abundance of Mycobacterium and Pseudomonas increased notably after n-butane cultivation, which highlighted their potential as biomarkers of underlying oil deposits. This work contributes to a broader perspective on the bacterial community structures shaped by long-term light-hydrocarbon microseepage and proposes relatively universal indicators, providing an additional resource for the improvement of microbial prospecting of oil and gas.

• 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.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.721-727
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• 2002

Precipitation evapotranspiration and runoff are three key parameters of regional water balance. Problems exist in the traditional methods for calculating such factors , such as explaining of the geographic rationality of spatial interpolating methods and lacking of enough observation stations in many important area for bad natural conditions. With the development of modern spatial info-techniques, new efficient shifts arose for traditional studies. Guided by theories on energy flow and materials exchange within Soil-Atmosphere-Plant Continuant (SPAC), retrieval models of key hydrological parameters were established in the Yellow River basin using CMS-5 and FengYun-2 meteorological satellite data. Precipitation and evapotranspiration were then estimated: (1) Estimating tile amount of solar energy that is absorbed by the ground with surface reflectivity, which is measured in the visible wavelength band (VIS): (2) Assessing the partitioning of the absorbed energy between sensible and latent heat with the surface temperature, which was measured in the thermal infrared band (TIR), the latent heat representing the evapotranspiration of water; (3) Clouds are identified and cloud top levels are classified using both VIS and TIR data. Hereafter precipitation will be calculated pixel by pixel with retrieval model. Daily results are first obtained, which are then processed to decade, monthly and yearly products. Precipitation model has been has been and tested with ground truth data; meanwhile, the evapotranspiration result has been verified with Large Aperture Scintillometry (LAS) presented by Wageningen University of the Netherlands. Further studies may concentrate on the application of models, i.e., establish a hydrological model of the Yellow river basin to make the accurate estimation of river volume and even monitor the whole hydrological progress.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3565-3583
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• 2022

The task scheduling problem has received a lot of attention in recent years as a crucial area for research in the cloud environment. However, due to the difference in objectives considered by service providers and users, it has become a major challenge to resolve the conflicting interests of service providers and users while both can still take into account their respective objectives. Therefore, the task scheduling problem as a bi-objective game problem is formulated first, and then a task scheduling model based on the bi-objective game (TSBOG) is constructed. In this model, energy consumption and resource utilization, which are of concern to the service provider, and cost and task completion rate, which are of concern to the user, are calculated simultaneously. Furthermore, a many-objective evolutionary algorithm based on a partitioned collaborative selection strategy (MaOEA-PCS) has been developed to solve the TSBOG. The MaOEA-PCS can find a balance between population convergence and diversity by partitioning the objective space and selecting the best converging individuals from each region into the next generation. To balance the players' multiple objectives, a crossover and mutation operator based on dynamic games is proposed and applied to MaPEA-PCS as a player's strategy update mechanism. Finally, through a series of experiments, not only the effectiveness of the model compared to a normal many-objective model is demonstrated, but also the performance of MaOEA-PCS and the validity of DGame.

• The Korean Journal of Pesticide Science
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• v.9 no.4
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• pp.303-310
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• 2005

This study was performed to examine analytical method of a quinolone compound, oxolinic acid in paddy soil by HPLC coupled with UV detector. Two types of soil texture in different regions were used for this experiment. Oxolinic acid was extracted by a 4 M-KOH : MeOH(1 : 3, v/v) mixtures and acidified followed by liquid-liquid partitioning in dichloromethane. Dichlormethane layer was dehydrated, evaporated and analyzed by HPLC (262 nm). Retention time was 10.2 min. The standard calibration curve of oxolinic acid showed linearity ($r^2>0.999^{**}$, y=378.99x+135.08) in the range of $1{\sim}40$ ng. The mean recoveries, evaluated from fortified soil samples at two concentration levels of 0.2 mg/kg and 1.0 mg/kg, were $90.9{\pm}4.52%$(C.V. 4.97%) and $95.0{\pm}0.23%$(C.V. 0.24%) for soil 1 and $92.2{\pm}1.15%$(C.V. 1.25%) and $93.1{\pm}0.31%$ (C.V. 0.33%) for soil 2, respectively The detection limits of two types of soils were same as 0.05 ppm. Overall, the present analytical method of oxolinic acid by HPLC coupled with UV detector seems to be used reasonably.