• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.12-22
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• 2021

This article suggests the machine learning model, i.e., classifier, for predicting the production quality of free-machining 303-series stainless steel(STS303) small rolling wire rods according to the operating condition of the manufacturing process. For the development of the classifier, manufacturing data for 37 operating variables were collected from the manufacturing execution system(MES) of Company S, and the 12 types of derived variables were generated based on literature review and interviews with field experts. This research was performed with data preprocessing, exploratory data analysis, feature selection, machine learning modeling, and the evaluation of alternative models. In the preprocessing stage, missing values and outliers are removed, and oversampling using SMOTE(Synthetic oversampling technique) to resolve data imbalance. Features are selected by variable importance of LASSO(Least absolute shrinkage and selection operator) regression, extreme gradient boosting(XGBoost), and random forest models. Finally, logistic regression, support vector machine(SVM), random forest, and XGBoost are developed as a classifier to predict the adequate or defective products with new operating conditions. The optimal hyper-parameters for each model are investigated by the grid search and random search methods based on k-fold cross-validation. As a result of the experiment, XGBoost showed relatively high predictive performance compared to other models with an accuracy of 0.9929, specificity of 0.9372, F₁-score of 0.9963, and logarithmic loss of 0.0209. The classifier developed in this study is expected to improve productivity by enabling effective management of the manufacturing process for the STS303 small rolling wire rods.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.156-162
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• 2021

The number of smart farms has increased to save labor in agricultural production as the subsidy become available from central and local governments. The number of illegal greenhouses has also increased, which causes serious issues for the local governments. In the present study, we developed Mask-RCNN model to detect greenhouses based on satellite images. Greenhouses in the satellite images were labeled for training and validation of the model. The Mask-RC NN model had the average precision (AP) of 75.6%. The average precision values for 50% and 75% of overlapping area were 91.1% and 81.8%, respectively. This results indicated that the Mask-RC NN model would be useful to detect the greenhouses recently built without proper permission using a periodical screening procedure based on satellite images. Furthermore, the model can be connected with GIS to establish unified management system for greenhouses. It can also be applied to the statistical analysis of the number and total area of greenhouses.

• Journal of Korea Water Resources Association
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• v.54 no.8
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• pp.617-628
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• 2021

Drought is a major natural disaster that causes serious social and economic losses. Local drought forecasts can provide important information for drought preparedness. In this study, we propose a new machine learning model that predicts drought by using historical drought indices and meteorological data from 10 sites from 1981 to 2020 in the southeastern part of the Korean Peninsula, Busan-Ulsan-Gyeongnam. Using Bayesian optimization techniques, a hyper-parameter-tuned Random Forest, XGBoost, and Light GBM model were constructed to predict the evaporative demand drought index on a 6-month time scale after 1-month. The model performance was compared by constructing a single site model and a regional model, respectively. In addition, the possibility of improving the model performance was examined by constructing a fine-tuned model using data from a individual site based on the regional model.

• Journal of Ginseng Research
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• v.35 no.4
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• pp.504-513
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• 2011

In order to develop a novel system for the discrimination of five ginseng cultivars (Panax ginseng Meyer), single nucleotide polymorphism (SNP) genotyping assays with real-time polymerase chain reaction were conducted. Nucleotide substitution in gDNA library clones of P. ginseng cv. Yunpoong was targeted for the SNP genotyping assay. From these SNP sites, a set of modified SNP specific fluorescence probes (PGP74, PGP110, and PGP130) and novel primer sets have been developed to distinguish among five ginseng cultivars. The combination of the SNP type of the five cultivars, Chungpoong, Yunpoong, Gopoong, Kumpoong, and Sunpoong, was identified as 'ATA', 'GCC', 'GTA', 'GCA', and 'ACC', respectively. This study represents the first report of the identification of ginseng cultivars by fluorescence probes. An SNP genotyping assay using fluorescence probes could prove useful for the identification of ginseng cultivars and ginseng seed management systems and guarantee the purity of ginseng seed.

• Journal of Korean Society of Forest Science
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• v.84 no.2
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• pp.145-150
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• 1995

A plant regeneration system using shoot basal callus of in vitro cultured black locust(Robinia pseudoacacia L.) was established. Shoot basal callus was induced on MS medium supplemented with BA, or NAA, and mere more proliferated on BA containing medium than NAA containing medium at both light and dark conditions. Shoot basal callus was induced during shoot multiplication procedure. Two types of callus, green colored callus and whitish-yellow colored callus, were cultured on mMS medium containing 2.0 mg/l BA and 0.5 mg/l NAA. Green colored callus showed the shoot regeneration ability while whitish-yellow callus failed to regenerate shoot and died. Regenerated shoot were rooted on hormone-free ${\frac{1}{2}}MS$ medium within 2 weeks.

• Korean Journal of Environment and Ecology
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• v.32 no.2
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• pp.165-175
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• 2018

The purpose of this study is to provide the basic data such as distribution status, growth characteristics, and the structural characteristics of forest stands for the systematic conservation and management of relict forest trees (stem girth of 300cm or larger) established naturally in Gangwon Province, Korea. The survey showed that 434 individuals of 19 species (conifers: 228 individuals of 4 species, broad-leaved trees: 206 individuals of 15 species) were distributed in Gangwon Province, and Taxus cuspidata was the most abundant among them with 203 individuals or about 46.7 % of the total. The stem girth was average of 404cm (conifers: 373cm, broad-leaves: 421cm), and Tilia amurensis with multi-stemmed growing on Sorak mountain range had the largest stem girth at 1,113cm. The average height and the crown width of relict forest trees were 15.4m and 10.0m, respectively. Although the environments of relict forest trees showed a slight difference by species, the relative appearance frequencies of most trees were high in the environments where the altitude was higher than 1,000 m, slope degree was greater than $25^{\circ}$, the slope faced north, and microtopography was at the upper of slopes. Regarding the stand characteristics of relict forest trees per unit area ($/100m^2$), the average total coverage was 294% (max. 475%), the total average number of species was 36 species (max. 60 species), the average species diversity index (H') was 2.560 (max. 3.593), the average canopy closure was 84.8% (max. 94.6%), and the average basal area (/ha) was $52.7m^2$ (max. $116.4m^2$, relict trees $30.0m^2$, and other trees $22.7m^2$). The analysis of the dynamics of the forest stands where relict forest trees were growing showed four types of the maintenance mechanisms of relict forest trees depending on the supply pattern of succeeding trees: "Low-density but persistent type (Quercus mongolica, Abies holophylla, Tilia amurensis, and Pyrus ussuriensis)," "Long ago stopped type (Pinus densiflora)," "Recently stopped type (Abies nephrolepis, Quercus variabilis, and Betula schmidtii)," and "Periodically repeated types of supply and stop (Salix caprea and Quercus serrata).".

• Journal of Forest and Environmental Science
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• v.37 no.1
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• pp.62-68
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• 2021

Despite numerous efforts on reducing road-kill worldwide, the collisions have been occurring continuously. Many factors are affecting road-kill occurrences and the effect is various by species. We investigated Hydropotes inermis argyropus road-kill characteristics on the national highway. We examined 9,099 H. i. argyropus road-kill points with distance to the gaps on road (interchange and intersection) and distance to six natural land-cover types as explanatory variables. We also examined the number of road-kill occurrences according to temporal variation using chi-square test with 9,658 events. In general, H. i. argyropus road-kill location tended to occur close to the gaps on road, agricultural lands and forests. The average distance from road-kill to the gap was 694.7 m and 78.6% of the collisions were occurred within 1 km from the gaps. In addition, Kruskal-Wallis test showed the distance between road-kill points and each land cover and the gaps was significantly different. The temporal analyses showed that the differences of the H. i. argyropus road-kill frequency are significant in both month and season. Our results implies H. i. argyropus road-kill location tended to occur close to the gaps on road, agricultural lands and forests in general, especially during May and June, according to their seasonal behavior. Thus, we suggest there is a need of concentrated management on the roads with specific characteristics for both wildlife and human safety.

• Animal cells and systems
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• v.16 no.1
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• pp.11-19
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• 2012

A major concern regarding the collection and storage of biodiversity information is the inefficiency of conventional taxonomic approaches in dealing with a large number of species. This inefficiency has increased the demand for automated, rapid, and reliable molecular identification systems and large-scale biological databases. DNA-based taxonomic approaches are now arguably a necessity in biodiversity studies. In particular, DNA barcoding using short DNA sequences provides an effective molecular tool for species identification. We constructed a large-scale database system that holds a collection of 5531 barcode sequences from 2429 Korean species. The Korea Barcode of Life database (KBOL, http://koreabarcode.org) is a web-based database system that is used for compiling a high volume of DNA barcode data and identifying unknown biological specimens. With the KBOL system, users can not only link DNA barcodes and biological information but can also undertake conservation activities, including environmental management, monitoring, and detecting significant organisms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.127-130
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• 2005

Internal cities such as gray level been enclosed to building forest are paying a lot of efforts and expenses to change to green city that park and street tree get put together. By the example, 'GREEN CITY of PUSAN 21' progress to decorate army facilities like the park, and to plant street trees in several places of city plan in Pusan. And urban environment that big cities of advanced nation are agreeable is making in the large park and road street trees at several places in downtown. Because price of tree for the park is very expensive, tree management system was all-important. In this paper, Motes deliver the sensor information in each tree through radio sensor network by server side. This information can use in state grasping of tree, harmful insects courtesy call etc and this system design was suggested to inform to mode of life administration scholars.

• Journal of Korean Society of Forest Science
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• v.109 no.2
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• pp.124-135
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• 2020

Alder (Alnus japonica) forests are representative of the wetland in East Asia, including Korea. In the past, alder forests were relatively common in various habitats such as mountains, riversides, back marshes, and alluvial plains. However, this plant community has recently become rare due to increasingly arid habitats and the influence of various land uses. In this study, we identify the synecological characteristics of alder (A. japonica) forests distributed naturally in the mountainous wetlands of Korea and provide basic data for their systematic conservation and management in the future. Based on vegetation survey data collected from 66 alder forests, community types were classified using the methods of the Zürich-Montpellier School of Phytosociology and two-way indicator species analysis. There were eight community types: Styrax obassia, Weigela subsessilis-Fraxinus mandschurica, Spiraea fritschiana, Viola verecunda, Impatiens textori-Spiraea salicifolia, Glyceria leptolepis, Molinia japonica, and Lindera obtusiloba-Quercus acutissima. These community types constituted a vegetation unit hierarchy of two communities, four subcommunities, and eight variants. In addition, the ecological characteristics of each community type were compared (including total coverage per 100 square meter, importance value index, constancy class, life-form composition, diversity indices, community similarity coefficient, and indicator species).