• Food Science of Animal Resources
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• v.40 no.6
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• pp.938-945
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• 2020

A dynamic model was developed to predict the Escherichia coli cell counts in pig trotters at changing temperatures. Five-strain mixture of pathogenic E. coli at 4 Log CFU/g were inoculated to cooked pig trotter samples. The samples were stored at 10℃, 20℃, and 25℃. The cell count data was analyzed with the Baranyi model to compute the maximum specific growth rate (μ_max) (Log CFU/g/h) and lag phase duration (LPD) (h). The kinetic parameters were analyzed using a polynomial equation, and a dynamic model was developed using the kinetic models. The model performance was evaluated using the accuracy factor (A_f), bias factor (B_f), and root mean square error (RMSE). E. coli cell counts increased (p<0.05) in pig trotter samples at all storage temperatures (10℃-25℃). LPD decreased (p<0.05) and μ_max increased (p<0.05) as storage temperature increased. In addition, the value of h₀ was similar at 10℃ and 20℃, implying that the physiological state was similar between 10℃ and 20℃. The secondary models used were appropriate to evaluate the effect of storage temperature on LPD and μ_max. The developed kinetic models showed good performance with RMSE of 0.618, B_f of 1.02, and A_f of 1.08. Also, performance of the dynamic model was appropriate. Thus, the developed dynamic model in this study can be applied to describe the kinetic behavior of E. coli in cooked pig trotters during storage.

• Geophysics and Geophysical Exploration
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• v.21 no.2
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• pp.67-81
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• 2018

We acquired the magnetic and bathymetry data around the TA (Tofua Arc) 22 seamount in the Lau Basin for finding submarine hydrothermal deposits. From the data, we estimated the magnetic characteristics in the study area. The bathymetry shows that TA 22 seamount consists of the western and eastern summits. Each summit exhibits a caldera. The western caldera is smaller, but deeper than the eastern caldera. The slope gradients of the TA 22 are steeper around ~1000 m depth range and relatively gentle at the summit areas with the small difference of two calderas. The magnetic properties of TA 22 seamount present high anomalies at the summit and the vicinity of the caldera. Low magnetization zones appear over the outer flanks and center of the calderas. These magnetic patterns are similar to the previous studies which had represented high anomalies and low magnetization zones inside of the summit area or on the flank of the outside of the summit area. The results of the 2D magnetic forward modeling with seismic profiles show about 20 nT of RMSEs (root mean square error) between the modeled and observed values. The low RMSEs proposes a good correlation between the modeled 2D structure and the geophysical observation in this study area. Based on the modeling and magnetization distribution, hydrothermal deposits are predicted to be located at the inner area of the calderas or at small mounds around caldera rims.

• Journal of the Korea Concrete Institute
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• v.23 no.1
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• pp.77-86
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• 2011

The concrete creep deformation of a hybrid composite section can cause additional deformation of the composite section and the stress relaxation of pre-compressive stress on the concrete section due to partial restraint of the deformation. In this study, the stress relaxation coefficient method (SRCM) is derived for simple analysis of complicate hybrid or composite sections for engineering purpose. Also, an equation of the stress relaxation coefficient (SRC) required for the SRCM is proposed. The SRCM is derived with the parameters of a creep coefficient, section and loading properties using the same method as the constant-creep step-by-step method (CC-SSM). The errors of the SRCM is improved by using the proposed SRC equation than the average SRC's which were estimated from the CC-SSM. The root mean square error (RMSE) of the SRCM with the proposed SRC equation for concrete with creep coefficient less than 3 was less than 1.2% to the creep deformation at the free condition and was 3.3% for the 99% reliability. The proposed SRC equation reflects the internal restraint of composite sections, and the effective modulus of elasticity computed with the proposed SRC can be used effectively to estimate the rigidity of a composite section in a numerical analysis which can be applied in analysis of the external restrain effect of boundary conditions.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.404-414
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• 2023

In this study, digital climate maps with high-resolution (1km, daily) for the period of 1981 to 2020 were produced for the use as reference data within the procedures for statistical downscaling of climate change scenarios. Grid data for the six climate variables including maximum temperature, minimum temperature, precipitation, wind speed, relative humidity, solar radiation was created over Korean Peninsula using statistical downscaling model, so-called IGISRM (Improved GIS-based Regression Model), using global reanalysis data and in-situ observation. The digital climate data reflects topographical effects well in terms of representing general behaviors of observation. In terms of Correlation Coefficient, Slope of scatter plot, and Normalized Root Mean Square Error, temperature-related variables showed satisfactory performance while the other variables showed relatively lower reproducibility performance. These digital climate maps based on observation will be used to downscale future climate change scenario data as well as to get the information of gridded agricultural weather data over the whole Korean Peninsula including North Korea.

• Animal Bioscience
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• v.37 no.8
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• pp.1387-1397
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• 2024

Objective: The objective of the current study was to find out the independent and interactive effects of prilled fat supplementation with protein on the production performance of early lactating Nili Ravi buffaloes. Methods: Sixteen early lactating buffaloes (36.75±5.79 d in milk; mean±standard error) received 4 treatments in 4×4 Latin-square design according to 2×2 factorial arrangements. The dietary treatments were: i) low protein low fat, ii) low protein high fat, iii) high protein low fat, and iv) high protein high fat. The dietary treatments contained 2 protein (8.7% and 11.7% crude protein) and fat levels (2.6% and 4.6% ether extract) on a dry matter basis. Results: The yields of milk and fat increased with increasing protein and fat independently (p≤0.05). Energy-, protein-, and fat-corrected milk yields also increased with increasing protein and fat independently (p≤0.05). Increasing dietary protein increased the protein yield by 3.75% and lactose yield by 3.15% and increasing dietary fat supplies increased the fat contents by 3.93% (p≤0.05). Milk yield and fat-corrected milk to dry matter intake ratios were increased at high protein and high fat levels (p≤0.05). Milk nitrogen efficiency was unaffected by dietary fat (p>0.10), whereas it decreased with increasing protein supplies (p≤0.05). Plasma urea nitrogen and cholesterol were increased by increasing protein and fat levels, respectively (p≤0.05). The values of predicted methane production reduced with increasing dietary protein and fat. Conclusion: It is concluded that prilled fat and protein supplies increased milk and fat yield along with increased ratios of milk yield and fat-corrected milk yields to dry matter intake. However, no interaction was observed between prilled fat and protein supplementation for production parameters, body weight, body condition score and blood metabolites. Predicted methane production decreased with increasing protein and fat levels.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.397-418
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• 2024

The Land Surface Temperature (LST) is a crucial parameter in identifying drought. It is essential to identify how LST can increase its accuracy, particularly in mountainous and hill areas. Increasing the LST accuracy can be achieved by applying early data processing in the correction phase, specifically in the context of topographic correction on the Lambertian model. Empirical evidence has demonstrated that this particular stage effectively enhances the process of identifying objects, especially within areas that lack direct illumination. Therefore, this research aims to examine the application of the Lambertian model in estimating LST using the Multi-Channel Method (MCM) across various physiographic regions. Lambertian model is a method that utilizes Lambertian reflectance and specifically addresses the radiance value obtained from Sun-Canopy-Sensor(SCS) and Cosine Correction measurements. Applying topographical adjustment to the LST outcome results in a notable augmentation in the dispersion of LST values. Nevertheless, the area physiography is also significant as the plains terrain tends to have an extreme LST value of ≥ 350 K. In mountainous and hilly terrains, the LST value often falls within the range of 310-325 K. The absence of topographic correction in LST results in varying values: 22 K for the plains area, 12-21 K for hilly and mountainous terrain, and 7-9 K for both plains and mountainous terrains. Furthermore, validation results indicate that employing the Lambertian model with SCS and Cosine Correction methods yields superior outcomes compared to processing without the Lambertian model, particularly in hilly and mountainous terrain. Conversely, in plain areas, the Lambertian model's application proves suboptimal. Additionally, the relationship between physiography and LST derived using the Lambertian model shows a high average R² value of 0.99. The lowest errors(K) and root mean square error values, approximately ±2 K and 0.54, respectively, were achieved using the Lambertian model with the SCS method. Based on the findings, this research concluded that the Lambertian model could increase LST values. These corrected values are often higher than the LST values obtained without the Lambertian model.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.631-640
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• 2017

The estimation of rice yield affects the income of farmers as well as the fields related to agriculture. Moreover, it has an important effect on the government's policy making including the control of supply demand and the price estimation. Thus, it is necessary to build the crop yield estimation model and from the past, many studies utilizing empirical statistical models or artificial neural network algorithms have been conducted through climatic and satellite data. Presently, scientists have achieved successful results with deep learning algorithms in the field of pattern recognition, computer vision, speech recognition, etc. Among deep learning algorithms, the SSAE (Stacked Sparse AutoEncoder) algorithm has been confirmed to be applicable in the field of forecasting through time series data and in this study, SSAE was utilized to estimate the rice yield in South Korea. The climatic and satellite data were used as the input variables and different types of input data were constructed according to the period of rice growth in South Korea. As a result, the combination of the satellite data from May to September and the climatic data using the 16 day average value showed the best performance with showing average annual %RMSE (percent Root Mean Square Error) and region %RMSE of 7.43% and 7.16% that the applicability of the SSAE algorithm could be proved in the field of rice yield estimation.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.67-74
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• 2016

Drone images with high spatial resolution are emerging as an alternative to previous studies with extraction limits in high density forests. Individual tree in the dense forests were extracted from drone images. To detect the individual tree extracted through the image segmentation process, the image segmentation results were compared between the combination of DSM and all R,G,B band and the combination of DSM and R,G,B band separately. The changes in the tree density of a deciduous forest was experimented by time and image. Especially the image of May when the forests are dense, among the images of March, April, May, the individual tree extraction rate based on the trees surveyed on the site was 50%. The analysis results of the width of crown showed that the RMSE was less than 1.5m, which was the best result. For extraction of the experimental area, the two sizes of medium and small trees were extracted, and the extraction accuracy of the small trees was higher. The forest tree volume and forest biomass could be estimated if the tree height is extracted based on the above data and the DBH(diameter at breast height) is estimated using the relational expression between crown width and DBH.

• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.975-984
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• 2019

As an essential prerequisite for systematic and integrated management of river water, it is necessary to secure the basic data such as discharge supplied to the river and released from the river. Under the current permit system for river water use, 59.1% of licensed facilities were found to have no discharge meters in 2017, especially for agricultural water, which makes it difficult to secure reliable data as a large portion of the reports are voluntarily reported by users. In this study, the indirect discharge measurement method of calculating the discharge through the power usage of the pumping station was applied to secure reliable discharge data. In particular, focusing on the fact that the discharge calculated by the power usage method differed with the actual discharge according to the level of the river, the study was conducted on improving the power usage method reflecting the river water level and improving the accuracy of discharge data. Analysis of the discharge calculated using the power usage method considering river water level using the correlation analysis method such as regression analysis, percent difference, root mean square error etc. confirmed that the results are not high compared to the conventional power usage method, but are slightly more approximated to the actual discharge. Therefore, although reliable discharge data can be obtained from the existing power usage method, it is expected that more accurate data on intaking water of river water can be obtained if the improved power usage method is used at points where the variation in the water level of the river is large.

• Journal of Korean Society of Forest Science
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• v.101 no.3
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• pp.395-404
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• 2012

This study was conducted to develop site index equations and to estimate productive areas for major coniferous species in Korea such as Pinus densiflora Sieb. et. Zucc, Pinus densiflora for. erect, Larix leptolepis and Pinus koraiensis using environmental factors. Using the large data set from both a digital forest site map and a climatic map, a total of 43 environmental factors including 15 climatic variables were regressed on site index by tree species to develop site index equations. Six environmental factors by species were selected as independent variables in the final site index equations. The result showed that the coefficients of determination for site index equations by species were ranged from 0.36 to 0.56, which seem to be relatively low but good enough for the estimation of forest stand productivity. The site index equations developed in this study were also verified by three evaluation statistics such as the estimation bias of model, precision of model, and mean square error of measurement. According to the evaluation statistics, it was found that the site index equations by species fitted well to the test data sets with relatively low bias and variation. As a result, it was concluded that the site index equations by species were well capable of estimating site quality. Based on the site index equations, the productive areas by species for all forest areas were estimated by applying GIS technique to the digital forest site map and climate map. In addition, the distribution of productive areas by species was illustrated by using GIS technique.