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유정래 ( Jung Re Yu ),진현정 ( Hyoun Jung Chin ),김미연 ( Mi Yeon Kim ),정우성 ( Woo Seong Jeong ),이상아 ( Sang Ah Lee ),이대호 ( Dae Ho Lee ),고관표 ( Gwan Pyo Koh ) 대한내과학회 2012 대한내과학회지 Vol.83 No.4
A 53-year-old woman had a 1.7 cm left adrenal mass on an abdominal computed tomography (CT) scan. She presented with paroxysmal headache, palpitation, sweating, and hypertension. The patient was highly suspected of having a pheochromocytoma, but measurements of 24-hour urinary metanephrine, catecholamines, and vanillylmandelic acid were normal. Plasma and urine catecholamine levels were within the normal range even during paroxysmal episodes. A scintigraphic study with 131I-metaiodobenzylguanidine (MIBG) revealed selective concentration of the radiotracer, corresponding to the CT mass. The patient underwent a left adrenalectomy and the pathological examination confirmed the diagnosis of pheochromocytoma. In this report, we describe a rare case of a symptomatic pheochromocytoma with normal catecholamine levels. Our case illustrates that routine nuclear scintigraphy, such as 131I-MIBG, should be performed even in cases with normal hormonal testing for all patients with high clinical suspicion of pheochromocytoma. (Korean J Med 2012;83:503-509)
정예민 ( Yemin Jeong ),윤유정 ( Youjeong Youn ),김서연 ( Seoyeon Kim ),강종구 ( Jonggu Kang ),최소연 ( Soyeon Choi ),임윤교 ( Yungyo Im ),서영민 ( Youngmin Seo ),유정아 ( Jeong-ah Yu ),성경희 ( Kyoung-hee Sung ),김상민 ( Sang-min 대한원격탐사학회 2023 大韓遠隔探査學會誌 Vol.39 No.5
산불은 오랜 기간동안 사회 및 경제적으로 지구에 많은 피해를 야기하며, 이러한 산불은 자연적 혹은 인위적으로 발생되어왔다. 이로 인해 여러 실험들에서 산불로 인한 악영향에 관한 연구들을 진행하였으며, 동시에 산불 발생 시 빠른 대처를 위한 산불탐지 및 오염배출 물질 탐지 등과 같은 연구들도 수행되었다. 그러나 현재까지 한국 및 동아시아 영역을 배경으로 한 연구는 부족한 실정이고 산불 탐지에 활용되는 자료들의 정확도에 한계가 있었다. 본 연구에서는 정지궤도 환경위성(Geostationary Environment Monitoring Spectrometer, GEMS) 영상에 위색합성기법을 활용해 새로운 산불연기 탐지 산출물을 생성하고 해당 영상을 U-Net 모델링에 활용해 기존의 연구들에서 산불 탐지시에 활용했던 가시광선 채널 영상의 한계를 보완하였다. 그리고 U-Net 모델링을 통해 산출된 산불연기 영역으로부터 황사 픽셀 필터링을 수행하는 분류모델을 구축하여 순수 산불연기 탐지 영상을 산출하였으며, 이는 GEMS 기반의 재난감시에 활용될 수 있을 것으로 기대한다. Wildfires cause a lot of environmental and economic damage to the Earth over time. Various experiments have examined the harmful effects of wildfires. Also, studies for detecting wildfires and pollutant emissions using satellite remote sensing have been conducted for many years. The wildfire product for the Geostationary Environmental Monitoring Spectrometer (GEMS), Korea’s first environmental satellite sensor, has not been provided yet. In this study, a false-color composite for better expression of wildfire smoke was created from GEMS and used in a U-Net model for wildfire detection. Then, a classification model was constructed to distinguish yellow dust from the wildfire smoke candidate pixels. The proposed method can contribute to disaster monitoring using GEMS images.
정예민 ( Yemin Jeong ),김서연 ( Seoyeon Kim ),김승연 ( Seung-yeon Kim ),유정아 ( Jeong-ah Yu ),이동원 ( Dong-won Lee ),이양원 ( Yangwon Lee ) 대한원격탐사학회 2022 大韓遠隔探査學會誌 Vol.38 No.5
산불의 발생과 강도는 기후 변화로 인하여 증가하고 있다. 산불 연기에 의한 배출가스 대기질과 온실 효과에 영향을 미치는 주요 원인 중 하나로 인식되고 있다. 산불 연기의 효과적인 탐지를 위해서는 위성 산출물과 기계학습의 활용이 필수적이다. 현재까지 산불 연기 탐지에 대한 연구는 구름 식별의 어려움 및 모호한 경계 기준 등으로 인한 어려움이 존재하였다. 본 연구는 우리나라 환경위성 센서인 Geostationary Environment Monitoring Spectrometer (GEMS)의 Level 1, Level 2 자료와 기계학습을 이용한 산불 연기 탐지를 목적으로 한다. 2022년 3월 강원도 산불을 사례로 선정하여 산불 연기 레이블 영상을 생성하고, 랜덤 포레스트 모델에 GEMS Level 1 및 Level 2 자료를 투입하여 연기 픽셀 분류 모델링을 수행하였다. 훈련된 모델에서 입력변수의 중요도는 Aerosol Optical Depth (AOD), 380 nm 및 340 nm의 복사휘도 차, Ultra-Violet Aerosol Index (UVAI), Visible Aerosol Index (VisAI), Single Scattering Albedo (SSA), 포름알데히드, 이산화질소, 380 nm 복사휘도, 340 nm 복사휘도의 순서로 나타났다. 또한 2,704개 픽셀에 대한 산불 연기 확률(0≤p≤1) 추정에서 Mean Bias Error (MBE)는 -0.002, Mean Absolute Error (MAE)는 0.026, Root Mean Square Error (RMSE)는 0.087, Correlation Coefficient (CC)는 0.981의 정확도를 보였다. The occurrence and intensity of wildfires are increasing with climate change. Emissions from forest fire smoke are recognized as one of the major causes affecting air quality and the greenhouse effect. The use of satellite product and machine learning is essential for detection of forest fire smoke. Until now, research on forest fire smoke detection has had difficulties due to difficulties in cloud identification and vague standards of boundaries. The purpose of this study is to detect forest fire smoke using Level 1 and Level 2 data of Geostationary Environment Monitoring Spectrometer (GEMS), a Korean environmental satellite sensor, and machine learning. In March 2022, the forest fire in Gangwon-do was selected as a case. Smoke pixel classification modeling was performed by producing wildfire smoke label images and inputting GEMS Level 1 and Level 2 data to the random forest model. In the trained model, the importance of input variables is Aerosol Optical Depth (AOD), 380 nm and 340 nm radiance difference, Ultra-Violet Aerosol Index (UVAI), Visible Aerosol Index (VisAI), Single Scattering Albedo (SSA), formaldehyde (HCHO), nitrogen dioxide (NO<sub>2</sub>), 380 nm radiance, and 340 nm radiance were shown in that order. In addition, in the estimation of the forest fire smoke probability (0 ≤ p ≤ 1) for 2,704 pixels, Mean Bias Error (MBE) is -0.002, Mean Absolute Error (MAE) is 0.026, Root Mean Square Error (RMSE) is 0.087, and Correlation Coefficient (CC) showed an accuracy of 0.981.
권명옥 ( Kwon Myoung-ok ),김혜원 ( Kim Hye-won ),유정아 ( Yu Jeong-a ),송수아 ( Song Su-ah ),전정희 ( Jeon Jeung-hee ),정유미 ( Jung Yoo-mi ) 국군간호사관학교 군건강정책연구소 2016 군진간호연구 Vol.34 No.2
Purpose : The purpose of this study is to analyze the healthcare system of North Korea and compare it with that of South Korea and ultimately provide suggestions in the preparation for unification. Methods : The study started from literature review and in-depth interview, followed by specialist consultation. Results : 1) Healthcare system of North Korea is organized, but the service is provided depending on the status and ranks of an individual. 2) North Korean military medical service emphasizes three following principles : providing primary care, ensuring the continuity, and offering rapidity of medical support. 3) Medical personnel are military physicians, military nurses, and medics. 4) Major health issues are infectious and chronic degenerative disease, to which people have become more susceptible due to poor infrastructure. 5) Periodic training for nuclear war is conducted. Conclusion : This study analyzed North Korea`s healthcare system and tried to find challenges in military medical nursing field in the preparation for unification. These findings will offer valuable information to military medical readiness.