• Journal of the Korean Geotechnical Society
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• v.23 no.1
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• pp.23-37
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• 2007

Recently a concept of pile-tip enlarged PHC pile (Ext-PHC pile), for use in the auger-drilled construction method, has been developed and is being implemented in practice. A series of field axial load tests on both PHC and Ext-PHC piles were conducted at an experimental site. In addition, a parametric study on a number of influencing factors was made using a validated finite element model. The field axial load tests indicated an enhanced load-settlement characteristics for the Ext-PHC piles compared with the PHC piles, giving approximately 50% increase in the end bearing capacity. Also found in the results of the parametric study was that the increase in the end bearing capacity of Ext-PHC piles slightly varies with the mechanical properties of supporting ground as well as pile length, in the range of 1.25 to 1.4 time that of PHC. Overall, the results of the field tests as well as the numerical study confirmed that the end bearing capacity of PHC pile can be improved by the concept of.Ext-PHC pile.

• Journal of the Korean Geotechnical Society
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• v.38 no.3
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.157-168
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• 2023

Image segmentation and supervised classification techniques are widely used to monitor the ground surface using high-resolution remote sensing images. In order to classify various objects, a process of defining a class corresponding to each object and selecting samples belonging to each class is required. Existing methods for extracting class samples should select a sufficient number of samples having similar intensity characteristics for each class. This process depends on the user's visual identification and takes a lot of time. Representative samples of the class extracted are likely to vary depending on the user, and as a result, the classification performance is greatly affected by the class sample extraction result. In this study, we propose an image classification technique that minimizes user intervention when extracting class samples by applying the histogram back-projection technique and has consistent intensity characteristics of samples belonging to classes. The proposed classification technique using histogram back-projection showed improved classification accuracy in both the experiment using hue subchannels of the hue saturation value transformed image from Compact Advanced Satellite 500-1 imagery and the experiment using the original image compared to the technique that did not use histogram back-projection.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1497-1503
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• 2023

To address challenges in classifying clouds and snow cover when calculating ground reflectance in Near-UltraViolet (UV) wavelengths, this study introduces a methodology that combines cloud data from the Geostationary Environmental Monitoring Spectrometer (GEMS) and the Advanced Meteorological Imager (AMI)satellites for snow cover analysis. The proposed approach aims to enhance the quality of surface reflectance calculations, and combined cloud data were generated by integrating GEMS cloud data with AMI cloud detection data. When applied to compute GEMS surface reflectance, this fusion approach significantly mitigated underestimation issues compared to using only GEMS cloud data in snow-covered regions, resulting in an approximately 17% improvement across the entire observational area. The findings of this study highlight the potential to address persistent underestimation challenges in snow areas by employing fused cloud data, consequently enhancing the accuracy of other Level-2 products based on improved surface reflectivity.

• Korean Journal of Radiology
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• v.23 no.1
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• pp.112-123
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• 2022

Objective: To investigate the relationship between ¹⁸F-FDG PET/CT semi-quantitative parameters and the International Association for the Study of Lung Cancer, American Thoracic Society/European Respiratory Society (IASLC/ATS/ERS) histopathologic classification, including histological subtypes, proliferation activity, and somatic mutations. Materials and Methods: This retrospective study included 419 patients (150 males, 269 females; median age, 59.0 years; age range, 23.0-84.0 years) who had undergone surgical removal of stage IA-IIIA lung adenocarcinoma and had preoperative PET/CT data of lung tumors. The maximum standardized uptake values (SUVmax), background-subtracted volume (BSV), and background-subtracted lesion activity (BSL) derived from PET/CT were measured. The IASLC/ATS/ERS subtypes, Ki67 score, and epidermal growth factor/anaplastic lymphoma kinase (EGFR/ALK) mutation status were evaluated. The PET/CT semi-quantitative parameters were compared between the tumor subtypes using the Mann-Whitney U test or the Kruskal-Wallis test. The optimum cutoff values of the PET/CT semi-quantitative parameters for distinguishing the IASLC/ATS/ERS subtypes were calculated using receiver operating characteristic curve analysis. The correlation between the PET/CT semi-quantitative parameters and pathological parameters was analyzed using Spearman's correlation. Statistical significance was set at p < 0.05. Results: SUVmax, BSV, and BSL values were significantly higher in invasive adenocarcinoma (IA) than in minimally IA (MIA), and the values were higher in MIA than in adenocarcinoma in situ (AIS) (all p < 0.05). Remarkably, an SUVmax of 0.90 and a BSL of 3.62 were shown to be the optimal cutoff values for differentiating MIA from AIS, manifesting as pure ground-glass nodules with 100% sensitivity and specificity. Metabolic-volumetric parameters (BSV and BSL) were better potential independent factors than metabolic parameters (SUVmax) in differentiating growth patterns. SUVmax and BSL, rather than BSV, were strongly or moderately correlated with Ki67 in most subtypes, except for the micropapillary and solid predominant groups. PET/CT parameters were not correlated with EGFR/ALK mutation status. Conclusion: As noninvasive surrogates, preoperative PET/CT semi-quantitative parameters could imply IASLC/ATS/ERS subtypes and Ki67 index and thus may contribute to improved management of precise surgery and postoperative adjuvant therapy.

• Korean Journal of Poultry Science
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• v.51 no.2
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• pp.47-56
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• 2024

This study investigated the quality characteristics of low-fat chicken breast sausage with cauliflower powder to replace the fat. Cauliflower was freeze-dried and then ground into powder form. Sausagebatter was prepared separately according to the amount of fat and cauliflower powder added. 1) Control, sausage with 20% of pork fat, 2) LF, sausage with 3% of pork fat, 3) C0.5, sausage with 3% of pork fat and 0.5% of cauliflower powder, 4) C1.0, sausage with 3% of pork fat and 1.0% cauliflower powder. The prepared sausage batter was heated to a final internal temperature of 75℃. The pH of sausage batter increased with the addition of cauliflower powder (P<0.05). Storage loss and cooking loss increased in low-fat samples but decreased as the amount of cauliflower powder added increased (P<0.05). The hardness measured on the 30th day of storage decreased in LF but increased with the content of cauliflower powder (P<0.05). The redness and yellowness of the sausage increased with the addition of cauliflower powder. The malondialdehyde content of chicken breast sausages decreased at C0.5 and C1.0 on the 30th day of storage. The sausages with cauliflower powder received lower scores in sensory evaluation (P<0.05). Therefore, the addition of cauliflower powder to low-fat chicken breast sausage reduced overall sensory acceptability but improved water-holding capacity and oxidative stability.

• Journal of the Korea Organic Resources Recycling Association
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• v.17 no.3
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• pp.55-70
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• 2009

The long-term effects and the soil environmental changes were examined to ensure the safety of food waste compost in agricultural use. Based on conventional nitrogen application rate of chemical fertilizer, Pig manure compost with $24g\;N\;kg^{-1}$, $8g\;P_2O_5\;kg^{-1}$, and $10.4g\;K_2O\;kg^{-1}$ and food waste compost with $20g\;N\;kg^{-1}$, $20.1g\;P_2O_5\;kg^{-1}$, and $6.5g\;K_2O\;kg^{-1}$ were applied to the paddy soil in $2{\times}2{\times}2m$ lysimeter in which paddy rice (Oryza sativa L. var Chucheong) were grown. The rice grown where food waste compost applied showed better growth responses than control, whereas less yield rate than chemical fertilizer applied. The contents of organic matter, nitrogen, and phosphorus after experiment were increased with compost applied. In addition, it improved soil aeration by the application of food waste compost, while little difference was observed in the quality of surface, infiltrated, and ground water compared to chemical fertilizer applied or control.

• Geophysics and Geophysical Exploration
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• v.13 no.3
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• pp.268-276
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• 2010

Earthquake Hazard Mitigation Law was activated into force on March 2009. By the law, the obligation to monitor the effect of earthquake on the facilities was extended to many organizations such as gas company and local governments. Based on the estimation of National Emergency Management Agency (NEMA), the number of free-surface acceleration stations would be expanded to more than 400. The advent of internet protocol and the more simplified operation have allowed the quick and easy installation of seismic stations. In addition, the dynamic range of seismic instruments has been continuously improved enough to evaluate damage intensity and to alert alarm directly for earthquake hazard mitigation. For direct visualization of damage intensity and area, Real Time Intensity COlor Mapping (RTICOM) is explained in detail. RTICOM would be used to retrieve the essential information for damage evaluation, Peak Ground Acceleration (PGA). Destructive earthquake damage is usually due to surface waves which just follow S wave. The peak amplitude of surface wave would be pre-estimated from the amplitude and frequency content of first arrival P wave. Earthquake Early Warning (EEW) system is conventionally defined to estimate local magnitude from P wave. The status of EEW is reviewed and the application of EEW to Odesan earthquake is exampled with ShakeMap in order to make clear its appearance. In the sense of rapidity, the earthquake announcement of Korea Meteorological Agency (KMA) might be dramatically improved by the adaption of EEW. In order to realize hazard mitigation, EEW should be applied to the local crucial facilities such as nuclear power plants and fragile semi-conduct plant. The distributed EEW is introduced with the application example of Uljin earthquake. Not only Nation-wide but also locally distributed EEW applications, all relevant information is needed to be shared in real time. The plan of extension of Korea Integrated Seismic System (KISS) is briefly explained in order to future cooperation of data sharing and utilization.

• Journal of the Korean Society of Food Science and Nutrition
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• v.38 no.2
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• pp.146-153
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• 2009

This study was conducted to examine the effects of fruits and stems of Opuntia ficus-indica var. saboten Makino on water intake, feed intake, body weight, blood glucose level and glucose tolerance in streptozotocin (STZ)-induced diabetic rats. Forty Sprague-Dawley male rats were divided into non-diabetic control (NC), diabetic control (DC), 8% Opuntia fruit (DOF), 5% Opuntia stem (DO-5) and 10% Opuntia stem (DO-10) groups. Fruits and stems of Opuntia ficus-indica were freeze-dried and ground before use in the experiment. Animals were fed experimental diet for 3 weeks. DOF, DO-5 and DO-10 groups showed lower water and feed intake as well as less body weight loss than DC group. The fasting blood glucose levels were 100 mg/dL for NC and 379 mg/dL for DC. Fasting glucose level of DOF was a significantly low level of 28% (p<0.05), whereas DO-5 and DO-10 had a decrease of 5% and 9% compared to DC. As for the glucose tolerance test, the highest blood glucose levels for NC and DC-10 group were observed at 30 minutes after glucose injection while those of DOF and DO-5 groups were after 60 minutes. DOF and DO-5 plasma insulin level improved. Plasma total cholesterol, triglyceride, non-esterified fatty acid (NEFA) and LDL-cholesterol concentrations were also lower in DOF, DO-5 and DO-10 groups, although HDL-cholesterol level was only slightly affected by experimental diets compared to DC. These results suggest that the feeding of Opuntia ficus-indica fruits and stems improved blood glucose and lipid metabolism in STZ-induced diabetic rats.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.679-692
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• 2020

We coupled a CFD model to the WRF-Chem model (WRF-CFD model) and investigated the characteristics of flows and carbon monoxide (CO) distributions in a building-congested district. We validated the simulated results against the measured wind speeds, wind directions, and CO concentrations. The WRF-Chem model simulated the winds from southwesterly to southeasterly, overestimating the measured wind speeds. The statistical validation showed that the WRF-CFD model simulated the measured wind speeds more realistically than the WRF-Chem model. The WRF-Chem model significantly underestimated the measured CO concentrations, and the WRF-CFD model improved the CO concentration prediction. Based on the statistical validation results, the WRF-CFD model improved the performance in predicting the CO concentrations by taking complicatedly distributed buildings and mobiles sources of CO into account. At 04 KST on May 22, there was a downdraft around the AQMS, and airflow with a relatively low CO concentration was advected from the upper layer. Resultantly, the CO concentration was lower at the AQMS than the surrounding area. At 15 KST on May 22, there was an updraft around the AQMS. This resulted in a slightly higher CO concentration than the surroundings. The WRF-CFD model transported CO emitted from the mobile sources to the AQMS measurement altitude, well reproducing the measured CO concentration. At 18 KST on May 22, the WRF-CFD model simulated high CO concentrations because of high CO emission, broad updraft area, and an increase in turbulent diffusion cause by wind-shear increase near the ground.