• Korean journal of applied entomology
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• v.61 no.4
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• pp.563-575
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• 2022

Maruca vitrata is one of important pests in leguminous crops, especially red bean. We investigated the effects of temperature on development of each life stage, adult longevity and fecundity of M. vitrata for understanding the biological characteristics of the insect species at eight constant temperatures of 13, 16, 19, 22, 25, 28, 31, and 34℃. Eggs hatched successfully at all temperature subjected and larvae successfully developed to the adult stage from 16℃ to 31℃. The developmental period of egg decreased up to 31℃ and after then increased. The developmental period of larva and pupa, and adult longevity of M. vitrata decreased with increasing temperature. 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 M. vitrata were estimated by linear regression as 12.8℃ and 280.8DD, respectively. TL and TH from egg hatching to adult emergence using SSI model were 14.2℃ and 31.9℃. Thermal windows, i.e., the range in temperature between the minimum and maximum rate of development, of M. vitrata was 17.7℃. In addition, we constructed the oviposition models of adult, using the investigated adult traits including survival, longevity, oviposition period and fecundity. Temperature-dependent development models and adult oviposition models will be helpful to understand the population dynamics of M vitrata and to establish the strategy of integrated pest management in legume crops.

• Korean journal of applied entomology
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• v.61 no.3
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• pp.435-447
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• 2022

The soybean podborer, Matsumuraeses falcana (Lepidoptera: Tortricidae), is one of important pests in soybean crop. In the purpose of forecasting population dynamics of M. falcana, we investigated the effects of temperature on development of each life stage, adult longevity and fecundity of Matsumuraeses falcana at seven constant temperatures of 10, 13, 19, 22, 25, 28, and 31℃. Eggs hatched successfully at all temperature subjected. M. falcana developed from egg hatching to adult emergence at the tested temperatures except 10, 13, and 31℃. The developmental period of each life stage and adult longevity of M. falcana decreased as temperature increased. The lower developmental threshold (LDT) and thermal constant (K) from egg hatching to adult emergence of M. falcana were estimated by linear regression as 10.2℃ and 492.04DD, respectively. Lower and higher threshold temperature (TL and TH) were calculated by the Lobry-Rosso-Flandrois (LRF) and Sharpe-Schoolfield-Ikemoto (SSI) models. TL and TH from egg hatching to adult emergence using SSI model were 16.7℃ and 29.1℃. Thermal windows, i.e., the range in temperature between the minimum and maximum rate of development, of M. falcana was 12.4℃. We constructed the adult oviposition model of M. falcana using adult survivorship and fecundity. Temperature-dependent immature development and adult oviposition models will help constructing the population model of M. falcana and developing the strategies of integrated pest management in soybean fields.

• Korean journal of applied entomology
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• v.61 no.3
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• pp.461-473
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• 2022

Matsumuraeses phaseoli is one of important pests in soybean crops, especially adzuki beans. We investigated the effects of temperature on development of each life stage, adult longevity and fecundity of M. phaseoli for understanding the biological characteristics of M. phaseoli at ten constant temperatures of 7, 10, 13, 16, 19, 22, 25, 28, 31, and 34℃. Eggs hatched successfully at all temperature subjected except 7℃ and 34℃. The developmental period of each life stage and adult longevity of M. phaseoli 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 M. phaseoli were estimated by linear regression as 9.04℃ and 422.97DD, respectively. TL and TH from egg hatching to adult emergence using SSI model were 20.0℃ and 32.3℃. Thermal windows, i.e., the range in temperature between the minimum and maximum rate of development, of M. phaseoli was 12.3℃. We constructed the adult oviposition model of M. phaseoli using adult survivorship and fecundity. Temperature-dependent development models and adult oviposition models will be helpful to understand the population dynamics of M. falcana and to establish the strategy of integrated pest management in soybean fields.

• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.451-463
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• 2018

The empirical/statistical models to estimate the ground Particulate Matter ($PM_{2.5}$) concentration from Geostationary Ocean Color Imager (GOCI) Aerosol Optical Depth (AOD) product were developed and analyzed for the period of 2015 in Seoul, South Korea. In the model construction of AOD-$PM_{2.5}$, two vertical correction methods using the planetary boundary layer height and the vertical ratio of aerosol, and humidity correction method using the hygroscopic growth factor were applied to respective models. The vertical correction for AOD and humidity correction for $PM_{2.5}$ concentration played an important role in improving accuracy of overall estimation. The multiple linear regression (MLR) models with additional meteorological factors (wind speed, visibility, and air temperature) affecting AOD and $PM_{2.5}$ relationships were constructed for the whole year and each season. As a result, determination coefficients of MLR models were significantly increased, compared to those of empirical models. In this study, we analyzed the seasonal, monthly and diurnal characteristics of AOD-$PM_{2.5}$model. when the MLR model is seasonally constructed, underestimation tendency in high $PM_{2.5}$ cases for the whole year were improved. The monthly and diurnal patterns of observed $PM_{2.5}$ and estimated $PM_{2.5}$ were similar. The results of this study, which estimates surface $PM_{2.5}$ concentration using geostationary satellite AOD, are expected to be applicable to the future GK-2A and GK-2B.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.207-221
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• 2023

This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.

• The Korean Journal of Nuclear Medicine
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• v.31 no.1
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• pp.73-82
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• 1997

Regional myocardial blood flow (rMBF) can be noninvasively quantified using N-13 ammonia and dynamic positron emission tomography (PET). The quantitative accuracy of the rMBF values, however, is affected by the distortion of myocardial PET images caused by finite PET image resolution and cardiac motion. Although different methods have been developed to correct the distortion typically classified as partial volume effect and spillover, the methods are too complex to employ in a routine clinical environment. We have developed a refined method incorporating a geometric model of the volume representation of a region-of-interest (ROI) into the two-compartment N-13 ammonia model. In the refined model, partial volume effect and spillover are conveniently corrected by an additional parameter in the mathematical model. To examine the accuracy of this approach, studies were performed in 9 coronary artery disease patients. Dynamic transaxial images (16 frames) were acquired with a GE $Advance^{TM}$ PET scanner simultaneous with intravenous injection of 20 mCi N-13 ammonia. rMBF was examined at rest and during pharmacologically (dipyridamole) induced coronary hyperemia. Three sectorial myocardium (septum, anterior wall and lateral wall) and blood pool time-activity curves were generated using dynamic images from manually drawn ROIs. The accuracy of rMBF values estimated by the refined method was examined by comparing to the values estimated using the conventional two-compartment model without partial volume effect correction rMBF values obtained by the refined method linearly correlated with rMBF values obtained by the conventional method (108 myocardial segments, correlation coefficient (r)=0.88). Additionally, underestimated rMBF values by the conventional method due to partial volume effect were corrected by theoretically predicted amount in the refined method (slope(m)=1.57). Spillover fraction estimated by the two methods agreed well (r=1.00, m=0.98). In conclusion, accurate rMBF values can be efficiently quantified by the refined method incorporating myocardium geometric information into the two-compartment model using N-13 ammonia and PET.

• Journal of Nutrition and Health
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• v.56 no.3
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• pp.264-276
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• 2023

Purpose: Food environmental factors related to food insecurity affect household food intake in several socio-ecological aspects. This study explores the relationship between food environment factors and food insecurity in households with married immigrant women. Methods: From November 2018 to February 2020, a survey was conducted enrolling 249 married immigrant women residing in the metropolitan areas of South Korea. In the final analysis, 229 subjects were divided into 2 groups classified as food security (n = 154) and food insecurity (n = 75), as assessed by the score of food security. Three aspects of food environments were measured: built·natural, political·economic, and socio-cultural Results: Food environments were significantly different between food security and food insecurity groups, as follows: the number of foods market and their distance from the home and food status for the last week at home in the built·natural domain; monthly cost of food purchase and experience for food assistance in the political·economic domain; total score of social support, parenting, and cooking skills in the socio-cultural domain. A stepwise multivariate linear regression model showed a negative association between the food insecurity score with social support from family and food inventory status in the last week. After adjusting for confounders, a positive association was obtained between the experience of a food support program. The final regression model explains about 30% of the relationship obtained in the three food environment domains and food insecurity (p < 0.001). Conclusion: Not only economic factors, which are common determinants of household food insecurity, but socio-cultural factors such as social support also affect household food insecurity. Therefore, plans for implementing a food assistance program to improve food insecurity for households with immigrant women should consider financial support as well as other comprehensive aspects, including socio-cultural domain such as social support from family and community.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.327-336
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• 2019

Soybean is one of the most important crops of which the grains contain high protein content and has been consumed in various forms of food. Soybean plants are generally cultivated on the field and their yield and quality are strongly affected by climate change. Recently, the abnormal climate conditions, including heat wave and heavy rainfall, frequently occurs which would increase the risk of the farm management. The real-time assessment techniques for quality and growth of soybean would reduce the losses of the crop in terms of quantity and quality. The objective of this work was to develop a simple model to estimate the growth of soybean plant using a multispectral sensor mounted on a rotor-wing unmanned aerial vehicle(UAV). The soybean growth model was developed by using simple linear regression analysis with three phenotypic data (fresh weight, dry weight, leaf area index) and two types of vegetation indices (VIs). It was found that the accuracy and precision of LAI model using GNDVI (R²= 0.789, RMSE=0.73 ㎡/㎡, RE=34.91%) was greater than those of the model using NDVI (R²= 0.587, RMSE=1.01 ㎡/㎡, RE=48.98%). The accuracy and precision based on the simple ratio indices were better than those based on the normalized vegetation indices, such as RRVI (R²= 0.760, RMSE=0.78 ㎡/㎡, RE=37.26%) and GRVI (R²= 0.828, RMSE=0.66 ㎡/㎡, RE=31.59%). The outcome of this study could aid the production of soybeans with high and uniform quality when a variable rate fertilization system is introduced to cope with the adverse climate conditions.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.73-81
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• 2013

Ordinary least squares (OLS) regression is the primary statistical method in previous studies for vegetation distribution patterns in relation to landform. However, this global regression lacks the ability to uncover some local-specific relationships and spatial autocorrelation in model residuals. This study employed geographically weighted regression (GWR) to examine the spatially varying relationships between NDVI (Normalized Difference Vegetation Index) patterns and changing trends of landform (elevation, slope) and solar intensity (insolation and duration of sunshine) in Mt Geum-gang of North-Korea. Results denoted that GWR was more powerful than OLS in interpreting relationships between NDVI patterns and landform/solar intensity, since GWR was characterized by higher adjusted R2, and reduced spatial autocorrelations in model residuals. Unlike OLS regression, GWR allowed the coefficients of explanatory variables to differ by locality by giving relatively more weight to NDVI patterns which are affected by local landform and solar factors. The strength of the regression relationships in the GWR increased significantly, by showing regression coefficient of higher than 70% (0.744) in the southern ridge of the experimental area. It is anticipated that this research output will serve to increase the scientific and objective vegetation monitoring in relation to landform and solar intensity by overcoming serious constraints suffered from the past non-GWR-based approach.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.5A
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• pp.317-325
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• 2012

In this study, to evaluate the shrinkage behavior of ultra high performance fiber reinforced concrete (UHPFRC) under restrained condition, restrained shrinkage test was performed according to ring-test mostly used at home and abroad. Ring-test was performed with the various thicknesses and radii of inner steel ring to give different degree of restraint. Free shrinkage and tensile tests were carried out simultaneously to estimate the degree of restraint, stress relaxation, and shrinkage cracking potential. Test results indicated that the average steel strain and residual tensile stress were reduced as the thicker inner steel ring was used, whereas degree of restraint was increased. The steel strain, residual tensile stress and degree of restraint were hardly affected by the size of radius of inner ring. In the case of all ring specimens, shrinkage crack did not occur because the residual tensile stress was lower than the tensile strength. About 39~65% of the elastic shrinkage stress was relaxed by the sustained interface pressure, and the maximum relaxed stress was increased as the thicker inner ring was applied. Finally, the degree of restraint with age was predicted by performing non-linear regression analysis, and it was in good agreement with the test results.