• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.2
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• pp.185-194
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• 2008

In this paper, an efficient technique is proposed to integrate the 3D user interface with the tiled display system in PC cluster environment. In the developed 3D user interface software, various menus are provided to increase the user friendliness of the interface, including the several model-control-commands. To eliminate the noise produced from the 3D user interface devices, the box filtering algorithm is employed. Further, a communication splitting algorithm, which is a kind of asynchronous communication method, is proposed to reduce the motion delay between the 3D interface and the tiled display system, and its efficiency is validated through the benchmarking tests.

• Journal of Internet Computing and Services
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• v.12 no.3
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• pp.37-47
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• 2011

Current researches in the Cloud focus on the appropriate interactions of cloud components in a large-scale system implementation. However, the current designs do not include intelligent methods like grouping the similar service providers based on their properties and integrating adaptive schemes for load distribution which can promote effective sharing of resource. This paper proposes an efficient virtualization of services by grouping the cloud providers to improve the service provisioning. The grouping of cloud service providers based on a cluster analysis collects the similar and related services in one group. The adaptive load balancing supports the service provisioning of the cloud system where it manages the load distribution within the group using an adaptive scheme. The proposed virtualization mechanism (GRALB) showed good results in minimizing message overhead and throughput performance compared to other methods.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.16 no.4
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• pp.368-378
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• 1983

The community structure of intertidal benthic marine algae were studied seasonally at Odongdo, southern coast of Korea, from June 1982 to May 1983. Algal coverage in $50{\times}50\;cm$ quadrat were recorded for each species by line transect method. The vertical zonation investigated by line transects is recognized into three groups : Upper, middle, and lower zones. The representative species are Gelidium divaricatum, Enteromorpha linza, Porphyra yezoensis, Scytosiphon lomentaria, Blidingia nana, Ectocarpus confervoides in the upper, Ulva pertusa, Chondria crassicaulis in the middle, and Sargassum sagamianum, S. thunbergii, Undaria pinnatifida, Gelidium amansii and various other red algae in the lower zone. The number of algal species and coverage were generally highest in April and lowest in August. Species which appear dominant at least once a year were all of the spring type and the others were autumn type. According to the cluster analysis by similarity index community coefficient(SICC) among 5 transects, the algal communities are divided into two groups, i. e. open-sea group and inland-sea group.

• KIISE Transactions on Computing Practices
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• v.21 no.12
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• pp.745-750
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• 2015

LiDAR(Light Detection and Ranging) technology provides realistic 3-dimension image information, and it has been widely utilized in various fields. However, the utilization of this technology in the military domain requires prompt responses to dynamically changing tactical environment and is therefore limited since LiDAR technology requires complex processing in order for extensive amounts of LiDAR data to be utilized. In this paper, we introduce an Unmanned Aircraft Platform Based Real-time LiDAR Data Processing Architecture that can provide real-time detection information by parallel processing and off-loading between the UAV processing and high-performance data processing areas. We also conducted experiments to verify the feasibility of our proposed architecture. Processing with ARM cluster similar to the UAV platform processing area results in similar or better performance when compared to the current method. We determined that our proposed architecture can be utilized in the military domain for tactical and combat purposes such as unmanned monitoring system.

• Journal of KIISE:Information Networking
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• v.37 no.1
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• pp.50-56
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• 2010

This paper proposes a data gathering method by adapting the mobile sink to prolong the whole operation time of large WSNs. After partitioning a network into several clusters, a mobile sink visits each cluster and collects data from it. An efficient protocol improves the energy efficiency by delivering messages from the mobile sink to the cluster head as well as reduces the data gathering delay, which is the disadvantage of the mobile sink. For the scalability of sensor network, the network architecture should support the multihop transmission in the duster rather than the single hop transmission. The process for the data aggregation linked to the travelling path is proposed to improve the energy consumption of intermediate nodes. The experiment results show that the proposed model is more efficient than legacy methods in the energy consumption and the data gathering time.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.649-658
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• 2003

We propose a hierarchical architecture of ART2 Network for performance improvement and fast pattern classification model using fitness selection. This hierarchical network creates coarse clusters as first ART2 network layer by unsupervised learning, then creates fine clusters of the each first layer as second network layer by supervised learning. First, it compares input pattern with each clusters of first layer and select candidate clusters by fitness measure. We design a optimized fitness function for pruning clusters by measuring relative distance ratio between a input pattern and clusters. This makes it possible to improve speed and accuracy. Next, it compares input pattern with each clusters connected with selected clusters and finds winner cluster. Finally it classifies the pattern by a label of the winner cluster. Results of our experiments show that the proposed method is more accurate and fast than other approaches.

• Journal of the Korean Society for information Management
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• v.18 no.3
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• pp.159-178
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• 2001

This paper presents an automatic text summarization model which selects representative sentences from sentence clusters to create a summary. Summary generation experiments were performed on two sets of test documents after learning the optimum environment from a training set. Centroid clustering method turned out to be the most effective in clustering sentences, and sentence weight was found more effective than the similarity value between sentence and cluster centroid vectors in selecting a representative sentence from each cluster. The result of experiments also proves that inverse sentence weight as well as title word weight for terms and location weight for sentences are effective in improving the performance of summarization.

• Journal of environmental and Sanitary engineering
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• v.14 no.2
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• pp.56-67
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• 1999

This study was performed to suggest the basic data and plans for the establishment of safe water supply plans in simple water supply piped system in the rural areas. In 4 different places, 24 points of water sources 36 points of taps from water sources were sampled. Of the whole 60 points, 55 points were ground water and 5 points were surface water. 14 items were measured for the analysis of water quality on each samples. The measured items were analyzed again by statistical method ; cluster analysis and principle components analysis. The results of this study are as followed. 1) In water quality analysis on water sources, 4 items, bacteria, E.coli, NH3-N and Fe exceed the standard. Of 24 points, 20 points(83%) on bacteria, 1 point(4%) on NH3-N and Fe exceed the standard. 2) In water quality analysis on near and remote taps, 4 items, bacteria, E.coli, NH3-N and Fe , exceed the standard. Of 36 points, 20 points (81%) on bactria, 1 pint(3%) on NH3-N and Fe exceed the standard. 3)Cluster analysis on water quality shows the differences by the kinds of water sources, geographical characteristics and distance from water sources. 4) Principle components analysis on ground water shows that Factor 1 and Factor 3 are natural fluctuation by the content of soil. Also, Factor 2 and Factor 4 are penetration of pollutants to underground. Therefore, it is needed to take deeper ground water in order to prevent from pollution in the areas which have ground water as water source . 5) Principle components analysis on surface water shows that Factor 1 is penetration of vacteria from surface to water source when rainfalls. Also, Factor 2 is fluctuation of water quality by the geographical characteristics. Therefore, the counterplans against non-point pollution source must be taken. Filtration and disinfection facilities are needed in the areas which have surface water as water source.

• The Korean Journal of Mycology
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• v.25 no.4 s.83
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• pp.362-368
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• 1997

Five formae speciales of Fusarium oxysporum in Korea were examined using RFLP analysis to find the possibility for classification and analyze genetic variations. DNAs from F. oxysporum f. sp. lycopersici, cucumerinum, fragariae, garlic and sesami were used with three recombinant probes such as pFC46, pFC52 and pFC57. Distinct differences among five formae speciales of this fungus were detected in RFLP band patterns based on southern hybridization of genomic DNA using each recombinant clone, which was a repetitive copy probe. Strains belong to four formae speciales could be very stable in genetic variation except f. sp. sesami which has more variation than the others based on the RFLP analysis. They formed their own cluster which has high similarity within the same formae specialis resulted from the UPGMA analysis for genetic relationship analysis and each cluster represented its own formae specialis. The method using three recombinant DNA probes could be a good tool for classification of formae speciales in F. oxysporum.

• Journal of Korean Society on Water Environment
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• v.25 no.5
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• pp.735-741
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• 2009

In order to support the basic information for planning and performing the environment management such as Total Maximum Daily Loads (TMDLs), it is highly recommended to understand the spatial distribution of water quality and runoff data in the unit watersheds. Therefore, in the present study, we applied Self-Organizing Map (SOM) to detect the characteristics of spatial distribution of Biological Oxygen Demand (BOD) concentration and runoff data which have been measured in the Yeongsan, Seomjin, and Tamjin River basins. For the purpose, the input dataset for SOM was constructed with the mean, standard deviation, skewness, and kurtosis values of the respective data measured from the stations of 22-subbasins in the rivers. The results showed that the $4{\times}4$ array structure of SOM was selected by the trial and error method and the best performance was revealed when it classified the stations into three clusters according to the basic statistics. The cluster-1 and 2 were classified primarily by the skewness and kurtosis of runoff data and the cluster-3 including the basic statistics of YB_B, YB_C, and YB_D stations was clearly decomposed by the mean value of BOD concentration showing the worst condition of water quality among the three clusters. Consequently, the methodology based on the SOM proposed in the present study can be considered that it is highly applicable to detect the spatial distribution of BOD concentration and runoff data and it can be used effectively for the further utilization using different water quality items as a data analysis tool.