• The Korean Journal of Soil Zoology
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• v.6 no.1_2
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• pp.25-31
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• 2001

Oribatid mite communities in the process of litter decomposition were analyzed In Korean pine (Pinus koraiensis) forests of Namsan and Kwangreung, which were supposed to be under different environmental selective pressures. Oribatid mites were collected bimonthly from the litter bags (mesh size 0.4 mm, 1.7 mm) which was set up in the forest floor of study sites. This study had been carried out from Jan., 1997 to Sept., 1998. Species abundance of Kwangreung (mesh size 1.7 mm) was significantly higher than that of Namsan (mesh size 1.7 mm), but total no. of species did not exceed 30 species in all study sites. Concerning body length, medium sized oribatid mites (0.3-0.7mm) were more abundant than small ( < 0.3 mm) and large ( > 0.7 mm) sized mites. In Kwangreung, species whose body lengths were 0.2 mm to 0.5 mm were major group. However, a little larger species than Kwangreung's major group were dominant in Namsan. Sorenson similarity index and cluster analysis suggested that there were qualitative and quantitative differences in species composition in Namsan and Kwangreung. More species were collected in May through September than the other sampling times, but the pattern was rather different between first year and second year. Newly immigrant species were high in May in the first year and many of them regained on next year. Diversity indices suggested that species diversity of Kwangreung was higher than that of Namsan. Nearly 70% of total individual abundance was occupied by several dominant species in Namsan and Kwangreung . In the litter bags of mesh size 1.7 mm, the most dominant species was Trichogalumna nipponica in Namsan and Kwangreung, but in the litter bags of mesh size 0.4 mm in Kwangreung it was Ramusella sengbuschi which is smaller than T. nipponica. And important species related to litter decomposition were selected as follows; T. nipponica, Epidamaeus coreanus, Scheloribates latipes, Ceratozetes japonicus, Ramusella sengbuschi, Eohypochthonius crassisetiger, and Cultroribula lata.

• Economic and Environmental Geology
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• v.8 no.3
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• pp.147-164
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• 1975

19 amphibolite samples from the Precambrian Sobaegsan metamorphic belt including the Ogbang mine amphibolites were analyzed for 24 elements each, by wet chemical and emission spectroscopic methods. All the chemical data were evaluated by the methods outlined by Evans and Leake(1960) and Leake(1964) and by Shaw and Kudo(1965). The chemical similarity of all the studied rocks analyzed to basic igneous rocks is consistently indicated particularly by trace element abundance and variation trends. Petrography and oxidation ratios were also considered in attempting to determine the nature of the parent rocks. 3 analyses of W-bearing mafic metamorphic rocks from Sangdong area of the Ogcheon geosynclinal zone are also presented and discussed. Geochemical data for these latter rocks have been possibly derived from mafic tuffs deposited in an area of carbonate deposition.

• Korean Journal of Microbiology
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• v.53 no.2
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• pp.83-96
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• 2017

A constructed sea stream in Yeongdo, Busan, Republic of Korea is mostly static due to the lifted stream bed and tidal characters, and receives domestic wastewater nearby, causing a consistent odor production and water quality degradation. Bioaugmentation of a microbial consortium was proposed as an effective and economical restoration technology to restore the polluted stream. The microbial consortium activated on site was augmented on a periodic basis (7~10 days) into the most polluted site (Site 2) which was chosen considering the pollution level and tidal movement. Physicochemical parameters of water qualities were monitored including pH, temperature, DO, ORP, SS, COD, T-N, and T-P. COD and microbial community analyses of the sediments were also performed. A significant reduction in SS, COD, T-N, and COD (sediment) at Site 2 occurred showing their removal rates 51%, 58% and 27% and 35%, respectively, in 13 months while T-P increased by 47%. In most of the test sites, population densities of sulfate reducing bacterial (SRB) groups (Desulfobacteraceae_uc_s, Desulfobacterales_uc_s, Desulfuromonadaceae_uc_s, Desulfuromonas_g1_uc, and Desulfobacter postgatei) and Anaerolinaeles was observed to generally decrease after the bioaugmentation while those of Gamma-proteobacteria (NOR5-6B_s and NOR5-6A_s), Bacteroidales_uc_s, and Flavobacteriales_uc_s appeared to generally increase. Aerobic microbial communities (Flavobacteriaceae_uc_s) were dominant in St. 4 that showed the highest level of DO and least level of COD. These microbial communities could be used as an indicator organism to monitor the restoration process. The alpha diversity indices (OTUs, Chao1, and Shannon) of microbial communities generally decreased after the augmentation. Fast uniFrac analysis of all the samples of different sites and dates showed that there was a similarity in the microbial community structures regardless of samples as the augmentation advanced in comparison with before- and early bioaugmentation event, indicating occurrence of changing of the indigenous microbial community structures. It was concluded that the bioaugmentation could improve the polluted water quality and simultaneously change the microbial community structures via their niche changes. This in situ remediation technology will contribute to an eco-friendly and economically cleaning up of polluted streams of brine water and freshwater.

• Geophysics and Geophysical Exploration
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• v.26 no.2
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• pp.52-61
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• 2023

The use of ultra-high-resolution (UHR) seismic surveys to preceisly characterize coastal and shallow structures have increased recently. UHR surveys derive a spatial resolution of 3.125 m using a high-frequency source (80 Hz to 1 kHz). A digital streamer system is an essential module for acquiring high-quality UHR seismic data. Localization studies have focused on reducing purchase costs and decreasing maintenance periods. Basic performance verification and application tests of the developed streamer have been successfully carried out; however, a comparative analysis with the existing benchmark model was not conducted. In this study, we characterized data obtained by using a developed streamer and a benchmark model simultaneously. Tamhae 2 and auxiliary equipment of the Korea Institute of Geoscience and Mineral Resources were used to acquire 2D seismic data, which were analyzed from different perspectives. The data obtained using the developed streamer differed in sensitivity from that obtained using benchmark model by frequency band.However, both type of data had a very high level of similarity in the range corresponding to the central frequency band of the seismic source. However, in the low frequency band below 60 Hz, data obtained using the developed streamer showed a lower signal-to-noise ratio than that obtained using the benchmark model.This lower ratio can hinder the quality in data acquisition using low-frequency sound sources such as cluster air guns. Three causes for this difference were, and streamers developed in future will attempt to reflect on these improvements.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.25-44
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• 2013

Accessing movie contents has become easier and increased with the advent of smart TV, IPTV and web services that are able to be used to search and watch movies. In this situation, there are increasing search for preference movie contents of users. However, since the amount of provided movie contents is too large, the user needs more effort and time for searching the movie contents. Hence, there are a lot of researches for recommendations of personalized item through analysis and clustering of the user preferences and user profiles. In this study, we propose recommendation system which uses ontology based knowledge base. Our ontology can represent not only relations between metadata of movies but also relations between metadata and profile of user. The relation of each metadata can show similarity between movies. In order to build, the knowledge base our ontology model is considered two aspects which are the movie metadata model and the user model. On the part of build the movie metadata model based on ontology, we decide main metadata that are genre, actor/actress, keywords and synopsis. Those affect that users choose the interested movie. And there are demographic information of user and relation between user and movie metadata in user model. In our model, movie ontology model consists of seven concepts (Movie, Genre, Keywords, Synopsis Keywords, Character, and Person), eight attributes (title, rating, limit, description, character name, character description, person job, person name) and ten relations between concepts. For our knowledge base, we input individual data of 14,374 movies for each concept in contents ontology model. This movie metadata knowledge base is used to search the movie that is related to interesting metadata of user. And it can search the similar movie through relations between concepts. We also propose the architecture for movie recommendation. The proposed architecture consists of four components. The first component search candidate movies based the demographic information of the user. In this component, we decide the group of users according to demographic information to recommend the movie for each group and define the rule to decide the group of users. We generate the query that be used to search the candidate movie for recommendation in this component. The second component search candidate movies based user preference. When users choose the movie, users consider metadata such as genre, actor/actress, synopsis, keywords. Users input their preference and then in this component, system search the movie based on users preferences. The proposed system can search the similar movie through relation between concepts, unlike existing movie recommendation systems. Each metadata of recommended candidate movies have weight that will be used for deciding recommendation order. The third component the merges results of first component and second component. In this step, we calculate the weight of movies using the weight value of metadata for each movie. Then we sort movies order by the weight value. The fourth component analyzes result of third component, and then it decides level of the contribution of metadata. And we apply contribution weight to metadata. Finally, we use the result of this step as recommendation for users. We test the usability of the proposed scheme by using web application. We implement that web application for experimental process by using JSP, Java Script and prot$\acute{e}$g$\acute{e}$ API. In our experiment, we collect results of 20 men and woman, ranging in age from 20 to 29. And we use 7,418 movies with rating that is not fewer than 7.0. In order to experiment, we provide Top-5, Top-10 and Top-20 recommended movies to user, and then users choose interested movies. The result of experiment is that average number of to choose interested movie are 2.1 in Top-5, 3.35 in Top-10, 6.35 in Top-20. It is better than results that are yielded by for each metadata.