• Childhood Kidney Diseases
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• v.7 no.2
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• pp.181-188
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• 2003

Purpose : Vesicoureteral reflux(VUR) is known to be the main cause of childhood hypertension and renal failure. Knowing its familial occurrence, we determined the incidence of VUR and renal scar in asymptomatic siblings of Korean patients with primary VUR Methods : A total of 50 siblings from 37 index patients were included. Voiding cystourethro-graphy(VCUG) and renal scintigraphy using $^{99m}Tc-DMSA$ were peformed in these siblings from June, 1994 to May, 2001, Index patients were classified into two groups according to the presence of VUR in their siblings, and the clinical factors of the index patients such as age, sex, grade of reflux and renal cortical defect were compared between the groups. Results : Among the 50 siblings, VUR were found in 8(16%) and renal cortical defects were detected in 8(16%) siblings respectively. The incidence of renal cortical defects was 87.5%(7 out of 8) in the VUR(+) siblings. There was a case of VUR(-) cortical defect in one sibling, presumed as a scar from an old VUR. There was no relationship among age, sex, grade of reflux and renal cortical defect of the index patient to the presence of VUR in siblings. Conclusion : This study confirmed a significant incidence of VUR(16%) and renal cortical defects(16%) in the asymptomatic siblings of patients with primary VUR in Korea. It Is resonable to recommend screening studies to the siblings of patients with VUR for the early detection and prevention of probable reflux nephropathy. (J K orean Soc Pediatr Nephrol 2003;7:181-188)

• The Korean Journal of Nuclear Medicine Technology
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• v.19 no.1
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• pp.30-36
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• 2015

Purpose Whole body bone scan, which makes up a largest percentage of nuclear medicine tests, has high sensitivity and resolution about bone lesion like osteomyelitis, fracture and the early detection of primary cancer. However, any standard for valuation has not yet been created except minimum factor. Therefore, in this study, we will analysis the method which show a quantitative evaluation index in whole body bone scan. Materials and Methods This study is conducted among 30 call patients, who visited the hospital from April to September 2014 with no special point of view about bone lesion, using GE INFINIA equipment. Enumerated data is measured mainly with patient's whole body count and lumbar vertabrae, and the things which include CNR (Contrast to Noise ratio), SNR (Signal to Noise ratio) are calculated according to the mean value signal and standard deviation of each lumbar vertabrae. In addition, the numerical value with the abdominal thickness is compared to each value by the change of scan speed and tissue equivalent material throughout the phantom examination, and compared with 1hours deleyed value. Completely, on the scale of ten, 2 reading doctors and 5 skilled radiologists with 5-years experience analysis the correlation between visual analysis with blind test and quantitative calculation. Results The whole body count and interest region count of patients have no significant correlation with visual analysis value throughout the blind test(P<0.05). There is definite correlation among CNR and SNR. In phantom examination, Value of the change was caused by the thickness of the abdomen and the scan speed. And The poor value of the image in the subject as a delay test patient could be confirmed that the increase tendency. Conclusion Now, a standard for valuation has not been created in whole body bone scan except minimum factor. In this study, we can verify the significant correlation with blind test using CNR and SNR and also assure that the scan speed is a important factor to influence the imagine quality from the value. It is possible to be some limit depending on the physiology function and fluid intake of patient even if we progress the evaluation in same condition include same injection amount, same scan speed and so on. However, that we prove the significant evaluation index by presenting quantitative calculation objectively could be considered academic value.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.317-324
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• 2015

GNSS was firstly proposed for application in weather forecasting in the mid-1980s. It has continued to demonstrate the practical uses in GNSS meteorology, and other relevant researches are currently being conducted. Precipitable Water Vapor (PWV), calculated based on the GNSS signal delays due to the troposphere of the Earth, represents the amount of the water vapor in the atmosphere, and it is therefore widely used in the analysis of various weather phenomena such as monitoring of weather conditions and climate change detection. In this study we calculated the PWV through the meteorological information from an Automatic Weather Station (AWS) as well as GNSS data processing of a Continuously Operating Reference Station (CORS) in order to analyze the heavy snowfall of the Ulsan area in early 2014. Song’s model was adopted for the weighted mean temperature model (T_m), which is the most important parameter in the calculation of PWV. The study period is a total of 56 days (February 2013 and 2014). The average PWV of February 2014 was determined to be 11.29 mm, which is 11.34% lower than that of the heavy snowfall period. The average PWV of February 2013 was determined to be 10.34 mm, which is 8.41% lower than that of not the heavy snowfall period. In addition, certain meteorological factors obtained from AWS were compared as well, resulting in a very low correlation of 0.29 with the saturated vapor pressure calculated using the empirical formula of Magnus. The behavioral pattern of PWV has a tendency to change depending on the precipitation type, specifically, snow or rain. It was identified that the PWV showed a sudden increase and a subsequent rapid drop about 6.5 hours before precipitation. It can be concluded that the pattern analysis of GNSS PWV is an effective method to analyze the precursor phenomenon of precipitation.

• Korean Journal of Remote Sensing
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• v.8 no.1
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• pp.27-43
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• 1992

The purpose of this study is to detect and evaluate the change of urban vegetation of Seoul during 1980s. Large areas covered with agricultural crops or forests were converted to residential and commercial areas, roads, schools, sports complexes, etc. There were also widespreas concerns on the deterioration of the quality of urban vegetation due to severe air pollution, overcrowding of nature parks, and idling of farm lands by land speculators. The image used for this study were MSS(Oct. 4, 1979) and TM(Apr. 26, 1990). The Green Vegetation Index of Kauth & Thomas(1976) was for the analysis. The GVI were resampled with 75$\times$75m grids and overlaid with the jurisdictional boundaries of 22 districts of Seoul. The results were reclassified to 6 classes, class 6 representing grids with the most vigorous vegetation or the best vegetation improvement in 1980s. The finding of this study can be summarized as follows : First, the most vigorous vigorous vegetation, in terms of GVI, of the 1979 image can be found at paddy fields located on alluvial near Han River. Broad-leaf forests located on hilly terrains have higher GVI than conifers located on the upper-parts of mountains. The average GVI of the northern part and southern part of Han River are 3.56 and 3.74, respectively. The main reason why the southern part has higher GVI is that there are more prime agricultural lands. Districts of Kangseo, Yangcheon, and Songpa have the highest percentage of grids of GVI class 6, and the percentages are 3.55 %, 3.47 %, and 2.69 %, respectively. Second, the most vigorous vegetation of the 1990 image can be found at the grass lands of the Yongsan golf club and the Sungsu horse racing track. The GVI of farm lands is lower than forest because most agricultural crops are at the early stage of growing season when the TM image was taken. The size of built-up area is much larger than of 1979. On the other hand, vegetation patches surrounded by developed area become smaller and have stronger contrast to surrounding area. The average GVI of the northern part and southern part of Han River are 3.57 and 3.51, respectively. The main reason why the southern part has lower GVI is the at more large-scale urban development projects were carried out in there during 1980s. Districts of Tobong, Nowon, and Seocho have the highest percentage of class 6, and the perecentages are 16.58 %, 10.14 %, and 8.50% respectively. Third, the change of urban vegetation in Seoul during 1980s are significant. Grids of GVI change classes 1 and 2, which represent severe vegetation loss, occupy 15.97% of Seoul. Three districts which lost the most vegetation are Yangcheon, Kangseo, and Songpa, where the percentages of GVI class 1 are 13.42%, 13.39% and 9.06%, respectively. The worst deterioration was mainly caused by residential developments. On the other hand, the vegetation of some part of Seoul improved in this period. Grids of GVI change classes 5 and 6 occupy 9.83 % of Seoul. Distircts of Jung, Yongsan, and Kangnam have the highest percentage of grids with GVI change classes 5 and 6, and their percentages are 22.31%, 19.17%, and 13.66%, respectively. The improvement of vegetation occurred in two areas. Forest vegetation is generally improving despite of concerns based on air pollution and heavy use by recreationists. Vegetation in open spaces established in riverside parks, large residential areas, and major public facilities are also improving.

• Journal of The Korean Astronomical Society
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• v.52 no.1
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• pp.11-21
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• 2019

Intensive Monitoring Survey of Nearby Galaxies (IMSNG) is a high cadence observation program monitoring nearby galaxies with high probabilities of hosting supernovae (SNe). IMSNG aims to constrain the SN explosion mechanism by inferring sizes of SN progenitor systems through the detection of the shock-heated emission that lasts less than a few days after the SN explosion. To catch the signal, IMSNG utilizes a network of 0.5-m to 1-m class telescopes around the world and monitors the images of 60 nearby galaxies at distances D < 50 Mpc to a cadence as short as a few hours. The target galaxies are bright in near-ultraviolet (NUV) with $M_{NUV}$ < -18.4 AB mag and have high probabilities of hosting SNe ($0.06SN\;yr^{-1}$ per galaxy). With this strategy, we expect to detect the early light curves of 3.4 SNe per year to a depth of R ~ 19.5 mag, enabling us to detect the shock-heated emission from a progenitor star with a radius as small as $0.1R_{\odot}$. The accumulated data will be also useful for studying faint features around the target galaxies and other science projects. So far, 18 SNe have occurred in our target fields (16 in IMSNG galaxies) over 5 years, confirming our SN rate estimate of $0.06SN\;yr^{-1}$ per galaxy.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.149-155
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• 2021

Early warning systems for weather risk management in the agricultural sector have been developed to predict potential wind damage to crops. These systems take into account the daily maximum wind speed to determine the critical wind speed that causes fruit drops and provide the weather risk information to farmers. In an effort to increase the accuracy of wind risk predictions, an artificial neural network for binary classification was implemented. In the present study, the daily wind speed and other weather data, which were measured at weather stations at sites of interest in Jeollabuk-do and Jeollanam-do as well as Gyeongsangbuk- do and part of Gyeongsangnam- do provinces in 2019, were used for training the neural network. These weather stations include 210 synoptic and automated weather stations operated by the Korean Meteorological Administration (KMA). The wind speed data collected at the same locations between January 1 and December 12, 2020 were used to validate the neural network model. The data collected from December 13, 2020 to February 18, 2021 were used to evaluate the wind risk prediction performance before and after the use of the artificial neural network. The critical wind speed of damage risk was determined to be 11 m/s, which is the wind speed reported to cause fruit drops and damages. Furthermore, the maximum wind speeds were expressed using Weibull distribution probability density function for warning of wind damage. It was found that the accuracy of wind damage risk prediction was improved from 65.36% to 93.62% after re-classification using the artificial neural network. Nevertheless, the error rate also increased from 13.46% to 37.64%, as well. It is likely that the machine learning approach used in the present study would benefit case studies where no prediction by risk warning systems becomes a relatively serious issue.

• Pediatric Infection and Vaccine
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• v.28 no.2
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• pp.101-109
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• 2021

Purpose: Common human coronaviruses (HCoVs) are relatively understudied due to the mild nature of HCoV infection. Given the lack of local epidemiology data on common HCoVs, we aimed to describe clinical and epidemiological characteristics of common HCoVs in children. Methods: Respiratory viral test results from 9,589 respiratory samples from Seoul National University Children's Hospital were analyzed from January 2015 to December 2019. Viral detection was done by the multiplex reverse transcription polymerase chain reaction. Demographics and clinical diagnosis were collected for previously healthy children tested positive for HCoVs. Results: Of the 9,589 samples tested, 1 or more respiratory viruses were detected from 5,017 (52.3%) samples and 463 (4.8%) samples were positive for HCoVs (OC43 2.8%, NL63 1.4%, 229E 0.7%). All 3 types co-circulated during winter months (November to February) with some variation by type. HCoV-OC43 was the most prevalent every winter season. HCoV-NL63 showed alternate peaks in late winter (January to March) and early winter (November to February). HCoV-229E had smaller peaks every other winter. Forty-one percent of HCoV-positive samples were co-detected with additional viruses; human rhinovirus 13.2%, respiratory syncytial virus 13.0%, influenza virus 4.3%. Common clinical diagnosis was upper respiratory tract infection (60.0%) followed by pneumonia (14.8%), croup (8.1%), and bronchiolitis (6.7%). Croup accounted for 17.0% of HCoV-NL63-positive children. Conclusions: This study described clinical and epidemiological characteristics of common HCoVs (OC43, NL63, 229E) in children. Continuing surveillance, perhaps by adding HKU1 in the diagnostic panel can further elucidate the spectrum of common HCoV infections in children.

• Korean Journal of School Psychology
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• v.17 no.1
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• pp.17-38
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• 2020

This study examined the factor structure of the Child Behavior Checklist Dysregulation Profile(CBCL-DP) for school-aged children in Korea identified differences in the level of maladjustment and problematic behaviors between the clinical group which had characteristics of CBCL-DP and the control group which did not. Confirmative factor analysis was performed on three alternative models from the literature to determine which was the most appropriate factor structure for the CBCL-DP. The result showed that the bi-factor model fit the sample data better than both the one and second-factor models. To confirm that the bi-factor model was the most appropriate factor structure, regression paths with relevant variables examined. The showed that CBCL-DP with the bi-factor model was associated with executive function difficulty as reported by parents and with school adjustment and all sub-factors of strength and difficulty as reported by teachers. The results also showed that this model had a different relationship with anxiety/depression, aggressive behavior, and attention problems than the other models. The clinical group was shown to have more executive function difficulty, worse adjustment of school life and to be less likely to engage in desired behaviors than the control group. These results indicate the CBCL-DP is more related to negative outcomes than any other factor, and that the bi-factor model was found to best fit the sample data, consistent with other studies. The early discovery of CBCL-DP can be used to provide interventions for high-risk children who exhibit emotional and behavioral problems, making its detection a significant diagnostic tool. The implications of these result, the limitations of this study, and areas for future research are discussed in this paper.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.17-27
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• 2023

Weeds are one of the factors that reduce crop yield through nutrient and photosynthetic competition. Quantification of weed density are an important part of making accurate decisions for precision weeding. In this study, we tried to quantify the density of weeds in images of maize fields taken by unmanned aerial vehicle (UAV). UAV image data collection took place in maize fields from May 17 to June 4, 2021, when maize was in its early growth stage. UAV images were labeled with pixels from maize and those without and the cropped to be used as the input data of the semantic segmentation network for the maize detection model. We trained a model to separate maize from background using the deep learning segmentation networks DeepLabV3+, U-Net, Linknet, and FPN. All four models showed pixel accuracy of 0.97, and the mIOU score was 0.76 and 0.74 in DeepLabV3+ and U-Net, higher than 0.69 for Linknet and FPN. Weed density was calculated as the difference between the green area classified as ExGR (Excess green-Excess red) and the maize area predicted by the model. Each image evaluated for weed density was recombined to quantify and visualize the distribution and density of weeds in a wide range of maize fields. We propose a method to quantify weed density for accurate weeding by effectively separating weeds, maize, and background from UAV images of maize fields.

• Journal of Chest Surgery
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• v.43 no.6
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• pp.588-595
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• 2010

Background: Base on types of tumor, the types of expressed tumor is diverse and the difference in its expression rate is even more various. Due to such reasons an animal model is absolutely needed for a clinical research of lung cancer. The author attempted oncogenesis by cultivating a cell line of non-small cell carcinoma and then injecting it inside thoracic cavities of nude mice. The author conducted quantitative analyses of HER2/neu tumor gene - an epidermal growth factor receptor (EGFR) related to lung cancer, and TGF-${\beta}_1$, which acts as a resistance to cell growth inhibition and malignant degeneration. In order to investigate achievability of the oncogenesis, histological changes and the expression of cancer gene in case of orthotopic lung cancer is necessary. Material and Method: Among 20 immunity-free male BALB/c, five nude mice were selected as the control group and rest as the experimental group. Their weights ranged from 20 to 25 gm (Orient, Japan). After injection of lung cancer line (SW900 G IV) into the pleural cavity of nude mice, They were raised at aseptic room for 8 weeks. HER2/neu was quantitatively analyzed by separating serum from gathered blood via chemiluminiscent immunoassay (CLIA), and immunosandwitch method was applied to quantitatively analyze TGF-${\beta}_1$. SPSS statistical program (SPSS Version 10.0, USA) was implemented for statistical analysis. Student T test was done, and cases in which p-value is less than 0.05 were considered significant. Result: Even after lung cancer was formed in the normal control group or after intentionally injected lung cancer cell line, no amplification of HER2/neu gene showed reaction. However, the exact quantity of TGF-${\beta}_1$ was $28,490{\pm}8,549pg/mL$, and the quantity in the group injected with lung cancer cell was $42,362{\pm}14,449pg/mL$, meaning 1.48 times highly Significant (p<0.483). It proved that HER2/neu gene TGF-${\beta}_1$ had no meaningful interconnection. Conclusion: TGF-${\beta}_1$ gene expressed approximately 1.48 times amplification in comparison to the control group. The amplification of TGF-${\beta}_1$ meant somatic recuperation inhibition mechanism due to carcinogenesis in nude mice was definitely working. It may be implemented as a quantitative analysis that allows early detection of lung cancer in human body.