• Journal of Korean Society of Forest Science
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• v.100 no.4
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• pp.565-576
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• 2011

This study was conducted to describe forest stand characteristics of the habitats of Allium victorialis var. platyphyllum population from the ecological analysis of classification of vegetation types, importance values, species diversity, interspecific association and community similarity in Ulleung Island and Mt. Hambaek, in which investigated by 48 plots ($10m{\times}10m$). The vegetation studied was classified into 1 community group, 2 communities, 2 groups and 3 subgroups for a species unit and divided by 5 units for a vegetation unit. In the Fagus engleriana group (vegetation unit 1, 2 and 3), importance value of A. victorialis var. platyphyllum in herb layer showed relatively higher value than other units. Importance value of A. victorialis var. platyphyllum in herb layer had higher value. In the analysis of interspecific association, most of the species associated positively to A. victorialis var. platyphyllum belonged to habitat features of valley area and sub-alpine zone. Therefore, it was considered that the growing environment of A. victorialis var. platyphyllum population was closely correlated to soil moisture and air humidity.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.193-198
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• 2021

Recently, interests in the 4th industry have increased the level of demand for pest control by farmers in the field of rice farming, and the interests and use of agricultural pest control drones. Therefore, the diversification of agricultural control drones that spray high-concentration pesticides and the increase of agricultural exterminators due to the acquisition of national drone certifications are rapidly developing the agricultural sector in the drone industry. In addition, as detailed projects, an effective platform is required to construct large-scale big data due to pesticide management, exterminator management, precise spraying, pest control work volume classification, settlement, soil management, prediction and monitoring of damages by pests, etc. and to process the data. However, studies in South Korea and other countries on development of models and programs to integrate and process the big data such as data analysis algorithms, image analysis algorithms, growth management algorithms, AI algorithms, etc. are insufficient. This paper proposed an online drone pest control management information platform to meet the needs of managers and farmers in the agricultural field and to realize precise AI pest control based on the agricultural drone pest control processor using drones and presented foundation for development of a comprehensive management system through empirical experiments.

• Journal of the Korean Geotechnical Society
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• v.37 no.12
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• pp.47-56
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• 2021

The cryosuction (negative pore pressure) in freezing soils causes groundwater migration from the frozen fringe to freezing front for ice lens formation. Frost heave and heaving pressure by ice lens cause damage to ground infrastructure. In order to prevent damage by the frost heave, various frost susceptibility criteria have been proposed. The SP (Segregation Potential) is the most widely used classification criterion for frost susceptibility in cold regions. The expansion of the ice lens by the migration of the groundwater is a key role in frost heave mechanism, and thus it is necessary to evaluate the hydraulic conductivity. In this paper, soil mixtures of coarse-fines (sand-silt) were prepared in various weight fractions and used for frost heave and column permeability test. For each case, the SP and the hydraulic conductivity were derived and correlations were analyzed. As a results, the transition threshold of the SP and the hydraulic conductivity were shown at 20% and 50% of the silt weight fraction, respectively. Although there are difference between these transition thresholds, these two coefficients show a specific correlation. In the future, additional study should be conducted for detailed analysis of the threshold transition values between SP and hydraulic conductivity.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.1C
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• pp.65-76
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• 2010

Recent earthquake events revealed that severe seismic damages were concentrated mostly at sites composed of soil sediments rather than firm rock. This indicates that the site effects inducing the amplification of earthquake ground motion are associated mainly with the spatial distribution and dynamic properties of the soils overlying bedrock. In this study, an integrated GIS-based information system for geotechnical data was constructed to establish a regional counterplan against ground motions at a representative metropolitan area, Seoul, in Korea. To implement the GIS-based geotechnical information system for the Seoul area, existing geotechnical investigation data were collected in and around the study area and additionally a walkover site survey was carried out to acquire surface geo-knowledge data. For practical application of the geotechnical information system used to estimate the site effects at the area of interest, seismic zoning maps of geotechnical earthquake engineering parameters, such as the depth to bedrock and the site period, were created and presented as regional synthetic strategy for earthquake-induced hazards prediction. In addition, seismic zonation of site classification was also performed to determine the site amplification coefficients for seismic design at any site and administrative sub-unit in the Seoul area. Based on the case study on seismic zonations for Seoul, it was verified that the GIS-based geotechnical information system was very useful for the regional prediction of seismic hazards and also the decision support for seismic hazard mitigation particularly at the metropolitan area.

• The Journal of Engineering Geology
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• v.33 no.4
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• pp.599-609
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• 2023

In the seismic retrofitting of harbor breakwaters in Korea, the recovery rate is often uncertain due to site conditions and site conditions, and problems continue to arise. Therefore, in this study, we analyzed the recovery rate and compressive strength of the improved material through drilling survey by grouting confirmation method after applying low-fluidity mortar injection method, and furthermore, we checked the elastic modulus by downhole test and tomography to confirm the reinforcement effect of soft ground after ground improvement. The experimental results showed that the average shear wave velocity of the ground increased from 229 m/s to 288 m/s in BH-1 and BH-3 boreholes to a depth of 28.0 m, and the average shear wave velocity of the ground to a depth of 30.0 m tended to increase from 224 m/s to 282 m/s in the downhole test. This is believed to be a result of the increased stiffness of the ground after reinforcement. The results of the tomographic survey showed that the Vs of the soft ground of the sample at Site 1 increased from 113 m/s to 214 m/s, and the Vs of the sample at Site 2 increased from 120 m/s to 224 m/s. This shows that the stiffness of the ground after seismic reinforcement is reinforced with hard soil, as the Vs value satisfies 180 m/s to 360 m/s in the classification of rock quality according to shear wave velocity.

• Journal of Applied Biological Chemistry
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• v.66
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• pp.394-403
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• 2023

In the pursuit of sustainable and environmentally-friendly agricultural practices, we conducted an extensive study on the rhizosphere bacteria inhabiting soils that have been devoid of chemical fertilizers for an extended period exceeding 40 years. Through this investigation, we isolated a total of 80 species of plant growth-promoting rhizosphere bacteria and assessed their potential to enhance plant growth. Among these isolates, Burkholderia cepacia CD2 displayed remarkable plant growth-promoting activity, making it an optimal candidate for further analysis. Burkholderia cepacia CD2 exhibited a range of beneficial characteristics conducive to plant growth, including phosphate solubilization, siderophore production, denitrification, nitrate utilization, and urease activity. These attributes are well-known to positively influence the growth and development of plants. To validate the taxonomic classification of the strain, 16S rRNA gene sequencing confirmed its placement within the Burkholderia genus, providing further insights into its phylogenetic relationship. To delve deeper into the potential mechanisms underlying its plant growth-promoting properties, we sought to confirm the presence of specific genes associated with plant growth promotion in CD2. To achieve this, whole genome sequencing (WGS) was performed by Plasmidsaurus Inc. (USA) utilizing Oxford Nanopore technology (Abingdon, UK). The WGS analysis of the genome of CD2 revealed the existence of a subsystem function, which is thought to be a pivotal factor contributing to improved plant growth. Based on these findings, it can be concluded that Burkholderia cepacia CD2 has the potential to serve as a microbial fertilizer, offering a sustainable alternative to chemical fertilizers.

• Journal of Korea Water Resources Association
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• v.51 no.10
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• pp.863-874
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• 2018

The purpose of this study is to evaluate the future climate change impact on stream aquatic ecology health of Han River watershed ($34,148km^2$) using SWAT (Soil and Water Assessment Tool) and random forest. The 8 years (2008~2015) spring (April to June) Aquatic ecology Health Indices (AHI) such as Trophic Diatom Index (TDI), Benthic Macroinvertebrate Index (BMI) and Fish Assessment Index (FAI) scored (0~100) and graded (A~E) by NIER (National Institute of Environmental Research) were used. The 8 years NIER indices with the water quality (T-N, $NH_4$, $NO_3$, T-P, $PO_4$) showed that the deviation of AHI score is large when the concentration of water quality is low, and AHI score had negative correlation when the concentration is high. By using random forest, one of the Machine Learning techniques for classification analysis, the classification results for the 3 indices grade showed that all of precision, recall, and f1-score were above 0.81. The future SWAT hydrology and water quality results under HadGEM3-RA RCP 4.5 and 8.5 scenarios of Korea Meteorological Administration (KMA) showed that the future nitrogen-related water quality in watershed average increased up to 43.2% by the baseflow increase effect and the phosphorus-related water quality decreased up to 18.9% by the surface runoff decrease effect. The future FAI and BMI showed a little better Index grade while the future TDI showed a little worse index grade. We can infer that the future TDI is more sensitive to nitrogen-related water quality and the future FAI and BMI are responded to phosphorus-related water quality.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.306-314
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• 2023

Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and　industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.

• Journal of Korean Society of Forest Science
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• v.81 no.3
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• pp.247-254
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• 1992

Vegetational data obtained from 50 quadrats of Mt. Jungwangsan area were analysed by applying two multivariate methods : two-way indicator species analysis(TWINSPAN) for classification and detrended canonical correspondence analysis(DCCA) for ordination. DCCA technique allowed to extract the ordination axes that could be related to 15 environmental factors. The forest vegetation in Mt. Jungwangsan was classified into Quercus mongolica-Tilia amurensis, Quercus mongolica-Rhododendron schlippenbachii, Quencus mongolica-Kalopanax pictus, Quercus mongolica-Carpinus cordata, Quercus mongolica-Cornus controversa, Betula costata, Fraxinus mandshurica, and Ulmus laciniata communities according to the TWINSPAN. The relationships between the distribution of dominant species of forest vegetation and soil condition in Mt. Jungwangsan were investigated by analyzing elevation and soil nutrition gradient. Ulmus laciniata, Betula costata, and Fraxinus mandshurica forest were distributed in a ravine of the low elevation and in the good nutrition area of $Mg^{{+}{+}}$, total nitrogen, and $Ca^{{+}{+}}$, Quercus mongolica groups in the high elevation and in the poor nutrition area. Quercus mongolica-Kalopanax pictus forest of Quercus mongolica groups was distributed in the high elevation and in the good nutrition area of $Ca^{{+}{+}}$, C.E.C., $Mg^{{+}{+}}$, and total nitrogen, Quercus mongolica-Rhododendron schlippenbachii forest in the low elevation and poor nutrition area. Quercus mongolica-Carpinus cordata forest and Quercus mongolica-Cornus controversa forest were distributed in the medium elevation and medium nutrition area. The two dominant factors influencing community distribution were elevation and topography.

• Weed & Turfgrass Science
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• v.7 no.3
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• pp.191-199
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• 2018

This study was to investigate the occurrence patterns of paddy weeds, their resistance levels to an ALS inhibiting herbicide, and to estimate the areas of resistance in these paddy fields. We used soil collected from 358 paddy fields of Jeonnam province in 2017. Based on their life cycles, weeds were 96% annuals and 4% perennial. Additionally, according to morphological classification, 59% were broad leaves, 28% were sedges and 13% were grasses. Different areas within Jeonnam province contained different numbers and occurrence rates of weed species. However, generally, we observed Lindernia dubia var. dubia, Monochoria vaginalis var. plantaginea, Ludwigia prostrata, L. procumbens, Cyperus difformis, Scirpus juncoides, Eleocharis Kuroguwai, Echinochloa oryzoides, and E. crus-galli var. echinata. We also observed seven weeds resistant to an ALS inhibiting herbicide. They were M. vaginalis, S. juncoides, C. difformis, L. dubia, Ludwigia prostrata, E. oryzoides, and E. crus-galli var. echinata. Although there were differences in the number and occurrence rate of resistant weed species to an ALS inhibiting herbicide among areas in Jeonnam province, the M. vaginalis, C. difformis, and S. juncoides occurred in 23 cities and counties in Jeonnam including Gwangju metropolitan city. Based on the rates (52%) of resistant occurrence to an ALS inhibiting herbicide in Jeonnam province, the area of weed resistant paddy fields was estimated to be 91,543 ha.