• Journal of Animal Science and Technology
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• v.55 no.5
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• pp.381-388
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• 2013

This study examined the effects of sex in different group sizes of Hanwoo calves. The growth performance including the mean daily gain, feed conversion rate, behavioral characteristics, and blood parameters in Hanwoo calves were investigated. A total of 54 heads of Hanwoo calves were housed separately at 4 heads per group, 3 heads per group, and 2 heads per group per pen. In the heifer calves, except for those 10 months of age, the growth performance was improved by increasing the group size, which was similar to steer calves (p<0.05). The heifer calves housed in 3 heads group spent more time lying down (p<0.05). The steer calves spent more time standing in the 3 heads group, lying down (2 heads group), and walking (4 heads group). The heifer calves housed in 2 heads group had a lower frequency of drinking, self-grooming, pairwise grooming, and fighting (p<0.05). On the other hand, the steer calves in the 4 heads group had a higher frequency of drinking, rubbing, and fighting (p<0.05). The white blood cell and cortisol were highest in the heifer calves in the 2 heads group (p<0.05).

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.6
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• pp.694-707
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• 2016

This study investigated the community structure of macrobenthic assemblages in the Taehwa River Estuary, Ulsan, Korea. Macrobenthos were collected with a Van Veen Grab Sampler during February and November 2012. The total species number and mean density were $176species/9.6m^2$ and $1,992inds./m^2$, respectively. Polychaetes were the most dominant faunal group in terms of species (91 species) and abundance ($1,463inds./m^2$). The major dominant species were polychaetes Minuspio japonica ($609{\pm}1,221inds./m^2$), Hediste japonica ($174{\pm}318inds./m^2$), Tharyx sp.1 ($106{\pm}283inds/m^2$), Lumbrineris longifolia ($79{\pm}207inds./m^2$), bivalve Theora fragilis ($114{\pm}272inds./m^2$) and amphipod Grandidierella japonica ($88{\pm}223inds./m^2$). Based on community statistics (cluster analysis and non-metric multidimensional scaling (nMDS) ordination), the macrobenthic community was divided into three station groups. Group I(freshwater dominated stations 2-6 with coarse sediment) was characterized by a high abundance of polychaetes Minuspio japonica, Hediste japonica, Capitella capitata, Pseudopolydora kempi, amphipods Grandidierella japonica and Apocorophium acutum. Group II (ecotone, stations 7-9 with mixed sediment) was numerically dominated by bivalve Theora fragilis, polychaetes Cirriformia tentaculata, Tharyx sp.1, Lumbrineris longifolia and Chaetozone sp. Finally, Group III (seawater dominated stations 10-12 with fine sediment) was characterized by a high density of polychaete Magelona japonica. These results showed that changes in salinity gradient and sedimentary characteristics were the main factors behind spatial changes in the macrobenthic communities of the Taehwa River Estuary.

• Korean Journal of Microbiology
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• v.39 no.4
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• pp.260-266
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• 2003

In this study bacterial community was analyzed to evaluate the impacts of long-term use of agricultural chemicals on a soil ecosystem as well as to obtain fundamental data on the relationship. Sequences of 16S rRNA clones from a non-agricultural site and a tangerine orchard soil which has a history of long-term use of agricultural chemicals over 30 years were analyzed. This revealed that bacterial community containing 5 divisions and 18 genera was distributed in a tangerine orchard soil, while bacterial community containing 9 divisions and 44 genera was distributed. In a tangerine orchard soil site, the most abundant bacteria in subdivision level were placed into Proteobacteria γ group which occupied 56% of total clones. The other bacterial clones from the ocrhcard soil exposed to agricultural chemicals over 30 years were Acidobacteria group (25%), Fimicutes group (5%), Planctomycetes group (2%), Proteobacteria α (1%), δ group (1%), and Cyanobacteria group (1%). Whereas, the clones were from the non-agricultural site were distributed among the division or subdivision Acidobacteria group (14%), Planctomycetes group (13%), Proteobacteria α (10%), β (9%), δ (9%), Fimicutes group (8%), Verrucomicrobia group (8%), Actinobacteria group (6%), Proteobacteria γ group (3%), Bacteroidetes group (3%), Gemmatimonadetes group (3%), and Cyanobacteria group (1%). This finding suggests the possibility that long-term application of agricultural chemicals or fertilizers on a tangerine orchard might result in drastic reduction or alteration in the composition of the bacterial community in the contaminated soil site.

• Journal of Life Science
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• v.31 no.12
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• pp.1079-1087
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• 2021

To analyze gut microbiota of livestock in Korea and compare taxonomic differences, we conducted 16S rRNA metagenomic analysis through next-generation sequencing. Fecal samples from broiler chickens, pigs, and cattle were collected from domestic feedlots randomly. α-diversity results showed that significant differences in estimated species richness estimates (Chao1 and ACE, Abundance-based coverage estimators) and species richness index (OUTs, Operational taxonomic units) were identified among the three groups. However, NPShannon, Shannon, and Simpson indices revealed that abundance and evenness of the species were statistically significant only for poultry (broiler chickens) and mammals (pigs and cattle). Firmicutes was the most predominant phylum in the three groups of fecal samples. Linear discriminant (LDA) effect size (LEfSe) analysis was conducted to reveal the ranking order of abundant taxa in each of the fecal samples. A size-effect over 2.0 on the logarithmic LDA score was used as a discriminative functional biomarker. As shown by the fecal analysis at the genus level, broiler chickens were characterized by the presence of Weissella and Lactobacillus, as well as pigs were characterized by the presence of provetella and cattele were characterized by the presence of Acinetobacter. A permutational multivariate analysis of variance (PERMANOVA) showed that differences of microbial clusters among three groups were significant at the confidence level. (p=0.001). This study provides basic data that could be useful in future research on microorganisms associated with performance growth, as well as in studies on the livestock gut microbiome to increase productivity in the domestic livestock industry.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.237-258
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• 2022

As the global market environment changes, the domestic ICT industry has a growing influence on the world economy. This industry is regarded as an important driving force in the national economy from a technological and social point of view. In particular, small and medium-sized enterprises (SMEs) in the ICT industry are regarded as essential actors of domestic economic development in terms of company diversity, technology development and job creation. However, since it is small compared to large-sized enterprises, it is difficult for SMEs to survive with a differentiated strategy in an incomplete and rapidly changing environment. Therefore, SMEs must make a lot of efforts to improve their own capabilities, and the government needs to provide the desirable help suitable for corporate internal resources so that they can continue to be competitive. This study classifies the types of ICT SMEs participating in government support programs, and analyzes the relationship between resources and performance creation of each type. The data from the "ICT Small and Medium Enterprises Survey" conducted annually by the Ministry of Science and ICT was used. In the first stage, ICT SMEs were clustered based on common factors according to their experiences with government support programs. Three clusters were meaningfully classified, and each cluster was named "active participation type," "initial support type," and "soloist type." As a second step, this study compared the characteristics of each cluster through profiling analysis for each cluster. The third step carried out in this study was to find out the mechanism of R&D performance creation for each cluster through regression analysis. Different factors affected performance creation for each cluster, and the magnitude of the influence was also different. Specifically, for "active participation type", "current manpower", "technology competitiveness", and "R&D investment in the previous year" were found to be important factors in creating R&D performance. "Initial support type" was identified as "whether or not a dedicated R&D organization exists", "R&D investment amount in the previous year", "Ratio of sales to large companies", and "Ratio of vendors supplied to large companies" contributed to the performance. Lastly, in the case of "soloist type", "current workforce" and "future recruitment plan", "technological competitiveness", "R&D investment", "large company sales ratio", and "overseas sales ratio" showed a significant relationship with the performance. This study has practical implications of showing what strategy should be established when supporting SMEs in the future according to the government's participation in the startup program and providing a guide on what kind of support should be provided.

• Korean Journal of Ecology and Environment
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• v.55 no.1
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• pp.84-98
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• 2022

Estuary is important in terms of biodiversity because it has the characteristics of transition waters, created by the mixing of fresh- and seawater. The estuarine water circulation provides a variety of habitats with different environments by inducing gradients in the chemical and physical environment, such as water quality and river bed structure, which are ultimately the main factors influencing biological community composition. If the water circulation is interrupted, the loss of brackish areas and the interception of migration of biological communities will lead to changes in the spatial distribution of biodiversity. In this study, among the sites covered by the Estuary Aquatic Ecosystem Health Assessment, we selected study sites where changes in biodiversity can be assessed by spatial gradient from the upper reaches of the river to the lower estuarine area. The α-, γ- and β-diversity of diatom, benthic macroinvertebrates, and fish communities were calculated, and they were divided into open and closed estuary data and compared to determine the trends in biodiversity variation due to estuarine circulation. As results, all communities showed higher γ-diversity at open estuary sites. The benthic macroinvertebrate community showed a clear difference between open and closed estuaries in β-diversity, consequently the estuarine transects were considered as a factor that decreases spatial heterogeneity of their diversity among sites. The biodiversity trends analyzed in this study will be used to identify estuaries with low γ- and β-diversity by community, providing a useful resource for further mornitoring and management to maintain estuarine health.

• Spatial Information Research
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• v.8 no.1
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• pp.171-182
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• 2000

Random sampling or systematic sampling method is commonly used to assess the accuracy of classification results. In remote sensing, with these sampling method, much time and tedious works are required to acquire sufficient ground truth data. So , a more effective sampling method that can retain the characteristics of the population is required. In this study, fractal analysis is adopted as an index for reference sampling . The fractal dimensions of the whole study area and the sub-regions are calculated to choose sub-regions that have the most similar dimensionality to that of whole-area. Then the whole -area s classification accuracy is compared to those of sub-regions, respectively, and it is verified that the accuracies of selected sub regions are similar to that of full-area . Using the above procedure, a new kind of reference sampling method is proposed. The result shows that it is possible to reduced sampling area and sample size keeping up the same results as existing methods in accuracy tests. Thus, the proposed method is proved cost-effective for reference data sampling.

• The Korean Journal of Applied Statistics
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• v.32 no.6
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• pp.837-849
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• 2019

Latent class models (LCM) are useful tools to draw hidden information from categorical data. This model can also be interpreted as a mixture model with multinomial component distributions. In some cases, however, an available dataset may contain both categorical and count or continuous data. For such cases, we can extend the LCM to a mixture model with both multinomial and other component distributions such as normal and Poisson distributions. In this paper, we consider a LCM for the data containing categorical and count data to analyze the Drug Review dataset which contains categorical responses and text review. From this data analysis, we show that we can obtain more specific hidden inforamtion than those from the LCM only with categorical responses.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.1
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• pp.63-70
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• 2014

This study is to analyze impact of geography and timing on the real transactions prices of apartment complexes in Seoul using data provided by the Ministry of Land, Infrastructure and Transport. The average real transactions and location data of apartment complex was combined into the GIS data. First, the pattern of apartment real transaction price change by period and by area was analyzed by kriging, the one of the spatial interpolation technique. Second, to analyze the pattern of apartment market price change by administrative district(administrative 'Dong' unit), the average of market price per unit area was calculated and converted to Moran I value, which was used to analyze the clustering level of the real transaction price. Through the analysis, spatial-temporal distribution pattern can be found and the type of change can be forecasted. Therefore, this study can be referred as of the base data research for the housing or local policies. Also, the regional unbalanced apartment price can be presented by analyzing the vertical pattern of the change in the time series and the horizontal pattern of the change based on GIS.

• The Journal of Engineering Geology
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• v.23 no.4
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• pp.467-476
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• 2013

With increasing interest in environmental issues and the quality of surface water becoming inadequate for water supply, the Korean government has launched a groundwater development policy to satisfy the demand for clean water. To drive this policy effectively, it is essential to guarantee the accuracy of sustainable groundwater yield and groundwater use amount. In this study, groundwater use was monitored over several years at various locations in Korea (32 cities/counties in 5 provinces) to obtain accurate groundwater use data. Statistical analysis of the results was performed as a method for estimating rational groundwater use. For the case of groundwater use for living purposes, we classified the cities/counties into three regional types (urban, rural, and urban-rural complex) and divided the groundwater facilities into five types (domestic use, apartment housing, small-scale water supply, schools, and businesses) according to use. For the case of agricultural use, we defined three regional types based on rainfall intensity (average rainfall, below-average rainfall, and above-average rainfall) and the facilities into six types (rice farming, dry-field farming, floriculture, livestock-cows, livestock-pigs, and livestock-chickens). Finally, we developed groundwater-use estimation equations for each region and use type, using cluster analysis and regression model analysis of the monitoring data. The results will enhance the reliability of national groundwater statistics.