• Journal of Korean Society of Coastal and Ocean Engineers
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• v.26 no.4
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• pp.207-216
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• 2014

Total organic carbon (TOC) is an important indicator used as an direct biological index in the research field of the marine carbon cycle. It is possible to produce the sufficient TOC estimation data by using the Chemical Oxygen Demand(COD) data because the available TOC data is relatively poor than the COD data. The outlier detection and treatment (removal) should be carried out reasonably and objectively because the equation for a COD-TOC conversion is directly affected the TOC estimation. In this study, it aims to suggest the optimal regression model using the available salinity, COD, and TOC data observed in the Korean coastal zone. The optimal regression model is selected by the comparison and analysis on the changes of data numbers before and after removal, variation coefficients and root mean square (RMS) error of the diverse detection methods of the outlier and influential observations. According to research result, it is shown that a diagnostic case combining SIQR (Semi - Inter-Quartile Range) boxplot and Cook's distance method is most suitable for the outlier detection. The optimal regression function is estimated as the TOC(mg/L) = $0.44{\cdot}COD(mg/L)+1.53$, then determination coefficient is showed a value of 0.47 and RMS error is 0.85 mg/L. The RMS error and the variation coefficients of the leverage values are greatly reduced to the 31% and 80% of the value before the outlier removal condition. The method suggested in this study can provide more appropriate regression curve because the excessive impacts of the outlier frequently included in the COD and TOC monitoring data is removed.

• Korean Journal of Organic Agriculture
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• v.28 no.2
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• pp.251-261
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• 2020

The developmental ecology and temperature-dependent growth model were calculated to develop the Scotinophara lurida control technology, which is mainly affected by environmentally friendly rice cultivation. The survival rate of S. lurida after overwintering in 2019 showed that 167 of 224 survived and the survival rate was 72.8%. Overwintering adult of S. lurida occur in rice fields in mid-June, spawn in early July, and first-generation adults develop in mid-August. In order to determine the temperature-dependent growth model, the growth periods by temperature and development stage were investigated in a incubator at 18, 21, 24, 27, 30℃ and 14L: 10D. The period from egg to adult at the temperature of 18, 21, 24, 27, 30℃ was 119.8, 73.1, 53.5, 39.4, and 82.0 days, respectively. The best development temperature was at 27℃. The regression curve was obtained by analyzing the relationship between temperature and growth rate using the Excell program, and the base temperature threshold and effective cumulative temperature for each development stage were calculated. From eggs to 5 nymphs of S. lurida the base temperature threshold was 17.9℃ and the effective cumulative temperature was 380.2 DD.

• Korean journal of applied entomology
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• v.61 no.4
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• pp.577-590
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• 2022

Ostrinia scapulalis is one of important pests in leguminous crops, especially red bean. In order to understand the biological characteristics of the insect, we investigated the effects of temperature on development of each life stage, adult longevity and fecundity of O. scapulalis at eleven constant temperatures of 7, 10, 13, 16, 19, 22, 25, 28, 31, 34, and 36℃. Eggs and larvae successfully developed next life stage at most temperature subjected except 7, 10 and 13℃. The developmental period of egg, larva and pupa decreased as temperature increased. Lower and higher threshold temperature (TL and TH) were calculated by the Lobry-Rosso-Flandrois (LRF) and Sharpe-Schoolfield-Ikemoto (SSI) models. The lower developmental threshold (LDT) and thermal constant (K) from egg hatching to adult emergence of O. scapulalis were estimated by linear regression as 13.5℃ and 384.5DD, respectively. TL and TH from egg hatching to adult emergence using SSI model were 19.4℃ and 39.8℃. Thermal windows, i.e., the range in temperature between the minimum and maximum rate of development, of O. scapulalis was 20.4℃. Adults produced viable eggs at the temperature range between 16℃ and 34℃, and showed a maximum number, ca. 416 offsprings, at 25℃. Adult models including aging rate, age-specific survival rate, age-specific cumulative oviposition, and temperature-dependent fecundity were constructed, using the temperature-dependent adult traits. Temperature-dependent development models and adult oviposition models will be useful components to understand the population dynamics of O. scapulalis and will be expected using a basic data for establishing the strategy of integrated pest management in leguminous crops.

• Korean Journal of Environmental Biology
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• v.38 no.2
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• pp.222-230
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• 2020

Temperature-dependent development models for Hydrochara affinis were built to estimate the ecological parameters as fundamental research for monitoring the impact of climate change on rice paddy ecosystems in South Korea. The models predicted the number of lifecycles of H. affinis using the daily mean temperature data collected from four regions (Cheorwon, Dangjin, Buan, Haenam) in different latitudes. The developmental rate of each life stage linearly increased as the temperature rose from 18℃ to 30℃. The goodness-of-fit did not significantly differ between the models of each life stage. Unlike the optimal temperature, the estimated thermal limits of development were considerably different among the models. The number of generations of H. affinis was predicted to be 3.6 in a high-latitude region (Cheorwon), while the models predicted this species to have 4.3 generations in other regions. The results of this study can be useful to provide essential information for estimating climate change effects on lifecycle variations of H. affinis and studies on biodiversity conservation in rice fields.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.42 no.6
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• pp.729-738
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• 1997

To estimate the change in rice productivity around lake Juam due to construction of artificial lake, growth, yield components and yield of rice were measured at different locations around lake Juam for three years from 1994 to 1996. Automated weather stations(AWS) were installed nearby the experimental paddy fields, and daily maximum, average and minimum temperature, solar radiation, relative humidity, and precipitation were measured for the whole growing period of rice. Plant height, number of tillers, leaf area and shoot dry weight per hill were observed from 8 to 10 times in the interval of 7 days after transplanting. Yield and yield components of rice were observed at the harvest time. Simulation model of rice productivity used in the study was SIMRIW developed by Horie. The observed data of rice at 5 locations in 1994, 3 locations in 1995 and 4 locations in 1996 were inputted in the model to estimate the unknown parameters. Comparisons between observed and predicted values of shoot dry weights, leaf area indices, and rough rice yield were fairly well, so that SIMRIW appeared to predict relatively well the variations in productivity due to variations of climatic factors in the habitat. Climatic elements prior to as well as posterior to dam construction were generated at six locatons around lake Juam for thirty years by the method of Pickering et al. Climatic elements simulated in the study were daily maximum and minimum temperature, and amount of daily solar radiation. The change in rice productivity around lake Juam due to dam construction were estimated by inputting the generated climatic elements into SIMRIW. Average daily maximum temperature after dam construction appeared to be more or less lower than that before dam construction, while average daily minimum temperature became higher after dam construction. Average amount of daily solar radiation became lower with 0.9 MJ $d^{-1}$ after dam construction. As a result of simulation, the average productivity of habitats around lake Juam decreased about 5.6% by the construction of dam.

• Korean Journal Plant Pathology
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• v.12 no.3
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• pp.307-315
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• 1996

토마토 잎에 집적된 triflumizole 잔류량 동태에 미치는 온도 영향과 Cladosporium fulvum에 대한 triflumizole의 살균효과를 구명하였다. 8주간 키운 토마토 식물체에 triflumizole을 분무 살포한 후 식물생장용 항온실에서 키우면서 4가지 온도 조건을 처리하였다. 주기적으로 토마토 잎을 채취하여 HPLC 방법을 이용하여 triflumizole의 잔류량을 조사하였다. Triflumizole 잔류량의 경시적 동태는 약제살포후 적산온도를 독립변수로 사용하는 지수적 감소 몸형으로 나타낼수 있었으며, 이는 triflumizole의 잔류성이 온도 영향을 크게 받는다는 것을 뜻한다. 경기도 농촌진흥원에 위치한 토마토 비닐하우스에서 수행한 실험에서 얻은 자료를 이용하여 평가한 결과 이 모형의 타당성이 인정되었다. Triflumizole의 약효에 대한 in vitro 실험 결과, 이 살균제는 C. fulvum의 균사 생장과 포자형성을 뚜렷이 억제하였으며, 잎곰팡이병 방제를 위해서는 토마토 잎에 집적된 triflumizole 잔류량이 최소한 10 ppm 이상이 되어야 할 것으로 추측된다. 본 연구에서 연구된 지수적 감소 모형은 토마토 잎에 집적된 triflumizole 잔류량을 추정하는데 활용될 수 있으며, 실용적인 측면에서 볼 때, 토마토 잎곰팡이병을 효과적으로 방제하는데 필요한 triflumizole의 최소 잔류량을 식물체에 유지하기 위하여 triflumizole을 살포해야 할 시기를 결정하는데 활용될 수 있다.

• Korean journal of applied entomology
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• v.51 no.4
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• pp.431-438
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• 2012

The developmental time of the nymphs of Myzus persicae was studied in the laboratory (six constant temperatures from 15 to $30^{\circ}C$ with 50~60% RH, and a photoperiod of 14L:10D) and in a green-pepper plastic house. Mortality of M. persicae in laboratory was high in the first(6.7~13.3%) and second instar nymphs(6.7%) at low temperatures and high in the third (17.8%) and fourth instar nymphs(17.8%) at high temperatures. Mortality was 66.7% at $33^{\circ}C$ in laboratory and $26.7^{\circ}C$ in plastic house. The total developmental time was the longest at $14.6^{\circ}C$ (14.4 days) and shortest at $26.7^{\circ}C$ (6.0 days) in plastic house. The lower threshold temperature of the total nymphal stage was $3.0^{\circ}C$ in laboratory. The thermal constant required for nymphal stage was 111.1DD. The relationship between developmental rate and temperature was fitted nonlinear model by Logan-6 which has the lowest value on Akaike information criterion (AIC) and Bayesian information criterion (BIC). The distribution of completion of each developmental stage was well described by the 3-parameter Weibull function ($r^2=0.95{\sim}0.97$). This model accurately described the predicted and observed occurrences. Thus the model is considered to be good for use in predicting the optimal spray time for Myzus persicae.

• Journal of The Korean Society of Grassland and Forage Science
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• v.37 no.1
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• pp.80-91
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• 2017

The objective of this study was to select a model showing high-levels of interpretability which is high in R-squared value in terms of predicting the yield in the mixed pasture using the factors of fertilization, seeding rate and years after pasture establishment in steps, as well as the climate as a basic factor. The processes of constructing the yield prediction model for the mixed pasture were performed in the sequence of data collection (forage and climatic data), preparation, analysis, and model construction. Through this process, six models were constructed after considering climatic variables, fertilization management, seeding rates, and periods after pasture establishment years in steps, thereafter the optimum model was selected through considering the coincidence of the models to the forage production theories. As a result, Model VI (R squared = 53.8%) including climatic variables, fertilization amount, seeding rates, and periods after pasture establishment was considered as the optimum yield prediction model for mixed pastures in South Korea. The interpretability of independent variables in the model were decreased in the sequence of climatic variables(24.5%), fertilization amount(17.8%), seeding rates(10.7%), and periods after pasture establishment(0.8%). However, it is necessary to investigate the reasons of positive correlation between dry matter yield and days of summer depression (DSD) by considering cultivated locations and using other cumulative temperature related variables instead of DSD. Meanwhile the another research about the optimum levels of fertilization amounts and seeding rates is required using the quadratic term due to the certain value-centered distribution of these two variables.

• Korean journal of applied entomology
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• v.51 no.4
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• pp.421-429
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• 2012

The developmental time period of Aphis gossypii was studied in laboratory (six constant temperatures from 15 to $30^{\circ}C$ with 50~60% RH, and a photoperiod of 14L:10D) and in a cucumber plastic house. The mortality of A. gossypii in the laboratory was high in the 2nd (20.0%) and 3rd stage(13.3%) at low temperature but high in the 3rd (26.7%) and 4th stage (33.3%) at high temperatures. Mortality in the plastic house was high in the 1st and 2nd stage but there was no mortality in the 4th stage at low temperature. The total developmental period was longest at $15^{\circ}C$ (12.2 days) in the laboratory and shortest at $28.5^{\circ}C$ (4.09 days) in the plastic house. The lower threshold temperature at the total nymphal stage was $6.8^{\circ}C$ in laboratory. The thermal constant required to reach the total nymphal stage was 111.1DD. The relationship between the developmental rate and temperature fit the nonlinear model of Logan-6 which has the lowest value for the Akaike information criterion(AIC) and Bayesian information criterion(BIC). The distribution of completion of each development stage was well described by the 3-parameter Weibull function ($r^2=0.89{\sim}0.96$). This model accurately described the predicted and observed outcomes. Thus it is considered that the model can be used for predicting the optimal spray time for Aphis gossypii.

• Korean Journal of Construction Engineering and Management
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• v.2 no.2 s.6
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• pp.90-97
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• 2001

The paper considers non-deterministic methods of analysing the risk exposure in a cost estimate. The method(referred to as the 'Monte Carlo simulation' method) interprets cost data indirectly, to generate a probability distribution for total costs from the deficient elemental experience cost distribution. The Monte Carlo method is popular method for incorporating uncertainty relative to parameter values in risk assessment modelling. Non-deterministic methods, they are here presented as possibly effective foundation on which to risk management in cost estimating. The objectives of this research is to develop a computerized algorithms to forecast the probabilistic total construction cost and the elemental work cost at the planning stage.