• Korean Journal of Food Science and Technology
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• v.34 no.6
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• pp.1073-1078
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• 2002

Antimicrobial activities in 70% ethanol extracts of Korean bamboo trees were investigated. Among the antimicrobial activities against ten major strains causing food poisening, Wangdae (Phyllostachys bambusoides S. et Z.) showed the strongest activity among five major bamboo trees cultivated in Korea. Although all extracts showed relatively strong antimicrobial activities against Staphylococcus aureus and Streptoccus mutans, the extracts of bamboo culms showed stronger activities than that of bamboo leaves. MICs (minimal inhibitory concentration) of the extracts of Wangdae culm against Staphylococcus aureus and Streptococcus mutans were over $10\;and\;20\;{\mu}L/disc$, respectively. The extract of Wangdae culm inhibited the growth of Staphylococcus aureus and Streptococcus mutans at over 0.5% concentration, and almost inhibited the growth of these strains at 1% level. The inhibitory effect of the extract of Wangdae culm was not destroyed by heating at 60, 80, and $100^{\circ}C$ for 60 min and at $121^{\circ}C$ for 15 min, suggesting that the component in the bamboo tree was very heat-stable. These results indicate that 70% ethanol extract of Wangdae culm could be useful as a natural antimicrobial agent.

• Journal of Korean Society of Forest Science
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• v.90 no.6
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• pp.692-698
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• 2001

This study has been carried out to estimate aboveground biomass and net primary production(NPP) in an average 41-years-old Quercus variabilis stand of Gongju area, 45-years-old Quercus variabilis stand of Pohang area, and 54-years-old Quercus variabilis stand of Yangyang area. Ten sample trees were cut in each forest and soil samples were collected in July to August, 2000. Estimation for aboveground biomass and net primary production were made by the equation model $Wt=aD^b$ where Wt is oven dry weight in kg and D is DBH in cm. Total aboveground biomass was 91.31ton/ha in Gongju area, 207.6ton/ha in Pohang area, and 71.39ton/ha in Yangyang area. The aboveground biomass 207.6ton/ha in Pohang area is the highest biomass production among the amount of biomass in Quercus variabils stands reported in Korea. The proportion of each tree component to total aboveground biomass was high in order of bolewood, bolebark, branches and leaves in the three forests. Aboveground total net primary production was estimated at 7.8ton/ha in Gongju area, 11.5ton/ha in Pohang area, and 6.40ton/ha in Yangyang area. There were at least 2 times higher total aboveground biomass in Pohang area than in the Gongju and Yangyang areas because of climate difference among the study areas.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.413-413
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• 2019

하천과 호수에서 남조류의 이상 과잉증식 문제(이하 녹조문제)는 담수생태계의 생물다양성을 감소시키며, 음용수의 이취미 원인물질을 발생시켜 물 이용에 장해가 된다. 또한 독소를 생산하는 유해남조류가 대량 증식할 경우에는 가축이나 인간의 건강에 치명적 해를 끼치기도 한다. 그 동안 국내에서 녹조문제는 댐 저수지와 하구호와 같은 정체수역에서 간헐적으로 문제를 일으켰으나, 4대강사업(2010-2011)으로 16개의 보가 설치된 이후 낙동강, 금강, 영산강 등 대하천에서도 광범위하게 발생되고 있어 중요한 사회적 환경적 이슈로 대두되었다. 한편, 대하천에 설치된 보 구간에서 빈번히 발생하는 녹조현상의 원인에 대해서는 전 지구적 기온상승에 따른 기후변화의 영향이라는 주장과 유역으로부터 영양염류의 과도한 유입, 가뭄에 따른 유량감소, 보 설치에 따른 체류시간 증가 등 다양한 의견이 제시되고 있으나, 대상 유역과 수체의 특성에 따라 녹조 발생의 원인이 상이하거나 또는 다양한 요인이 복합적으로 작용하기 때문에 보편적 해석(universal interpretation)이 어려운 것이 현실이다. 따라서 각 수계별, 보별 녹조현상에 대한 정확한 원인분석과 효과적인 대책 마련을 위해서는 집중된 실험자료와 데이터마이닝 기법에 근거로 한 보다 과학적이고 객관적인 접근이 이루어져야 한다. 본 연구에서는 2012년 보 설치 이후 남조류에 의한 녹조현상이 빈번히 발생하고 있는 낙동강 4개보(강정고령보, 달성보, 합천창녕보, 창녕함안보)를 대상으로 집중적인 현장조사와 실험분석을 수행하고, 수집된 기상, 수문, 수질, 조류 자료에 대해 통계분석과 다양한 데이터모델링 기법을 적용하여 보별 남조류 우점 환경조건과 이를 제어하기 위한 주요 조절변수를 규명하는데 있다. 연구대상 보 별 수질과 식물플랑크톤의 정성 및 정량 실험은 2017년 5월부터 2018년 11월까지 2년에 걸쳐 실시하였으며, 남조류 세포수 밀도와 환경요인과의 상관성 분석을 실시하고, 단계적 다중회귀모델(Step-wise Multiple Linear Regressions, SMLR), 랜덤포레스트(Random Forests, RF) 모델과 재귀적 변수 제거 기법(Recursive Feature Elimination using Random Forest, RFE-RF)을 이용한 변수중요도 평가, 의사결정나무(Decision Tree, DT), 주성분분석(Principal Component Analysis, PCA) 기법 등 다양한 모수적 및 비모수적 데이터마이닝 결과를 바탕으로 각 보별 남 조류 우점 환경요인을 종합적으로 해석하였다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.2
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• pp.123-131
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• 2021

The buffer is a key component of an engineered barrier system that safeguards the disposal of high-level radioactive waste. Buffers are located between disposal canisters and host rock, and they can restrain the release of radionuclides and protect canisters from the inflow of ground water. Since considerable heat is released from a disposal canister to the surrounding buffer, the thermal conductivity of the buffer is a very important parameter in the entire disposal safety. For this reason, a lot of research has been conducted on thermal conductivity prediction models that consider various factors. In this study, the thermal conductivity of a buffer is estimated using the machine learning methods of: linear regression, decision tree, support vector machine (SVM), ensemble, Gaussian process regression (GPR), neural network, deep belief network, and genetic programming. In the results, the machine learning methods such as ensemble, genetic programming, SVM with cubic parameter, and GPR showed better performance compared with the regression model, with the ensemble with XGBoost and Gaussian process regression models showing best performance.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.49-68
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• 2022

The operation system of a shipping company is still maintaining the mainframe based terminal access environment or the client/server based environment. Nowadays shipping companies that try to migrate it into a web-based environment are increasing. However, in the transition, if the design is processed by the old configuration and knowledge without considering the characteristics of the web-based environment and shipping business, various security vulnerabilities will be revealed at the actual system operation stage, and system maintenance costs to fix them will increase significantly. Therefore, in the transition to a web-based environment, a security design must be carried out from the design stage to ensure system safety and to reduce security-related maintenance costs in the future. This paper examines the characteristics of various threat modeling techniques, selects suitable modeling technique for the operation system of a shipping company, applies data flow diagram and STRIDE threat modeling technique to shipping business, derives possible security threats from each component of the data flow diagram in the attacker's point of view, validates the derived threats by mapping them with attack library items, represents the attack tree having various attack scenarios that attackers can attempt to achieve their final goals, organizes into the checklist that has security check items, associated threats and security requirements, and finally presents 23 security requirements that can respond to threats. Unlike the existing general security requirements, the security requirements presented in this paper reflect the characteristics of shipping business because they are derived by analyzing the actual business of a shipping company and applying threat modeling technique. Therefore, I think that the presented security requirements will be of great help in the security design of shipping companies that are trying to proceed with the transition to a web-based environment in the future.

• Animal Bioscience
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• v.35 no.9
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• pp.1340-1350
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• 2022

Objective: Luxi Black Head sheep (LBH) is the first crossbreed specialized for meat production and was developed by crossbreeding Black Head Dorper sheep (DP) and Small Tailed Han sheep (STH) in the farming areas of northern China. Research on the genomic variations and selection signatures of LBH caused by continuous artificial selection is of great significance for identifying the genetic mechanisms of important traits of sheep and for the continuous breeding of LBH. Methods: We explored the genetic relationships of LBH, DP, and several Mongolian sheep breeds by constructing phylogenetic tree, principal component analysis and linkage disequilibrium analysis. In addition, we analysed 29 whole genomes of sheep. The genome-wide selection signatures have been scanned with four methods: heterozygosity (H_P), fixation index (F_ST), cross-population extended haplotype homozygosity (XP-EHH) and the nucleotide diversity (𝜃_π) ratio. Results: The genetic relationships analysis showed that LBH appeared to be an independent cluster closer to DP. The candidate signatures of positive selection in sheep genome revealed candidate genes for developmental process (HoxA gene cluster, BCL2L11, TSHR), immunity (CXCL6, CXCL1, SKAP2, PTK6, MST1R), growth (PDGFD, FGF18, SRF, SOCS2), and reproduction (BCAS3, TRIM24, ASTL, FNDC3A). Moreover, two signalling pathways closely related to reproduction, the thyroid hormone signalling pathway and the oxytocin signalling pathway, were detected. Conclusion: The selective sweep analysis of LBH genome revealed candidate genes and signalling pathways associated with developmental process, immunity, growth, and reproduction. Our findings provide a valuable resource for sheep breeding and insight into the mechanisms of artificial selection.

• Animal Bioscience
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• v.37 no.7
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• pp.1168-1176
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• 2024

Objective: As a charismatic species, cashmere goats have rich genetic resources. In the Inner Mongolia Autonomous Region, there are three cashmere goat varieties named and approved by the state. These goats are renowned for their high cashmere production and superior cashmere quality. Therefore, it is vitally important to protect their genetic resources as they will serve as breeding material for developing new varieties in the future. Methods: Three breeds including Inner Mongolia cashmere goats (IMCG), Hanshan White cashmere goats (HS), and Ujimqin white cashmere goats (WZMQ) were studied. IMCG were of three types: Aerbas (AEBS), Erlangshan (ELS), and Alashan (ALS). Nine DNA samples were collected for each population, and they were genomically re-sequenced to obtain high-depth data. The genetic diversity parameters of each population were estimated to determine selection intensity. Principal component analysis, phylogenetic tree construction and genetic differentiation parameter estimation were performed to determine genetic relationships among populations. Results: Samples from the 45 individuals from the five goat populations were sequenced, and 30,601,671 raw single nucleotide polymorphisms (SNPs) obtained. Then, variant calling was conducted using the reference genome, and 17,214,526 SNPs were retained after quality control. Individual sequencing depth of individuals ranged from 21.13× to 46.18×, with an average of 28.5×. In the AEBS, locus polymorphism (79.28) and expected heterozygosity (0.2554) proportions were the lowest, and the homologous consistency ratio (0.1021) and average inbreeding coefficient (0.1348) were the highest, indicating that this population had strong selection intensity. Conversely, ALS and WZMQ selection intensity was relatively low. Genetic distance between HS and the other four populations was relatively high, and genetic exchange existed among the other four populations. Conclusion: The Inner Mongolia cashmere goat (AEBS type) population has a relatively high selection intensity and a low genetic diversity. The IMCG (ALS type) and WZMQ populations had relatively low selection intensity and high genetic diversity. The genetic distance between HS and the other four populations was relatively high, with a moderate degree of differentiation. Overall, these genetic variations provide a solid foundation for resource identification of Inner Mongolia Autonomous Region cashmere goats in the future.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.

• Korean Journal of Soil Science and Fertilizer
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• v.20 no.3
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• pp.251-259
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• 1987

Humic acids extracted from decomposing plant residues were characterized by infrared(IR) spectra. The IR spectra were further interpreted by chemical analyses for oxygen-containing functional groups such as carboxyl, phenolic, alcoholic, carbonyl, and quinionic groups. 1. The IR spectra obtained in this study were divied into three categories: spectra of humic acids from grain crop straws of rice, barley, wheat and rye produced Type I, while that from wild grass hay yielded Type II, and those from forest tree litter of the deciduous and conifers were led to give Type III. 2. There were no significant changes in the absorption bands observed among humic acids extracted at various stages of decomposition of a given Plant material. 3. The absorption band at about $3,430cm^{-1}$ represents the presence of hydrogen-bonded hydroxyl groups, phenolic-OH groups being the major component. 4. A close relationship was found between the total acidity and the content of phenolic-OH groups of humic acids. The content of carboxyl groups maintains a direct relationship with the content of total hydroxyl groups, and such a close relationship also exists between the content of alcoholic hydroxyls and that of total hydroxyl groups. 5. Overlapping of the absorption bands of carbonyl groups and quinones renders it difficult to make differentiation between the two. 6. A variety of non-armoatic cyclic hydrocarbons appears to be a structural component as evidenced by a sharp absorption peak near $995-1000cm^{-1}$.

• Korean journal of applied entomology
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• v.59 no.3
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• pp.217-231
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• 2020

In 2019, the sex pheromones of Spodoptera frugiperda were used to examine moth trapping in cornfields in Gochang, Korea. Four types of traps were prepared, two funnel-types and two delta-types, each baited with 300 or 1000 ㎍ of a two-component (2C) blend of synthetic sex pheromones [100% (Z)-9-tetradecenyl acetate (Z9-14Ac) and 2% (Z)-7-dodecenyl acetate (Z7-12Ac)]. The greatest number of S. frugiperda were captured in the 300 ㎍ funnel-type trap (first catch: August 6). Large numbers of Mythimna loreyi (a non-target) were also caught in the funnel-type traps. Two wing-type traps were baited with 1000 ㎍ of the 2C blend or a four-component (4C) blend [100% (Z)-9-tetradecenyl acetate, 8% (Z)-11-hexadecenyl acetate (Z11-16Ac), 2% (Z)-7-dodecenyl acetate, and 1% (Z)-9-dodecenyl acetate (Z9-12Ac)] and the capture efficiency was assessed. Low numbers of S. frugiperda were captured regardless of the blend, and more M. loreyi were captured using the 4C blend. The two intraspecies groups clustered separately in a phylogenetic tree constructed using partial sequences (1004 bp) of cytochrome c oxidase subunit 1 (CO1). Of the 70 S. frugiperda captured in the pheromone traps, 66 belonged to CO1-RS (CO1 rice-strain) and 4 to CO1-CS (CO1 corn-strain). Twelve consistent single nucleotide polymorphisms (SNPs) were identified in CO1 between the CO1-RS and CO1-CS groups of S. frugiperda. Of the 73 S. frugiperda, 4 had the same SNP pattern as the CO1-CS group (including the corn strain) and 69 had the same SNP pattern as the CO1-RS group (including the rice strain).