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강종구,Kang, Jong-Gu 한국시뮬레이션학회 2017 한국시뮬레이션학회 논문지 Vol.26 No.1
은밀하게 침투하여 아군의 핵심자산으로 접근하는 표적 잠수함을 상시 감시하기 위하여 수중 해저면 위치에 최적의 고정형 수동탐지소나를 배치하는 것을 고려 할 수 있다. 수동탐지소나 배치 최적화를 위한 효과도 지수는 넓은 탐지영역과 위치추정가능성의 함수로 적용할 수 있는데 계절적인 요인, 해상상태, 표적 잠수함의 침투심도 등의 다양한 확률적 변이를 포함하고 있어서 효과도지수가 배치의 입력에 대하여 확률적으로 나타나는 특성을 갖는다. 본 논문에서는 다양한 파라메타의 입력조건에 대하여 확률적인 출력을 갖는 수동탐지소나의 배치에 대한 최적화 문제를 정의하였으며, DPSO(Discrete binary version of PSO) 방법을 사용하여 최적 배치 안을 도출하기 위한 모의기반의 절차를 제시하고 고찰하였다. An arrangement of passive sonars is considered to be a fixed underwater surveillance system for detecting an anti-submarine consistently. An effectiveness score for optimizing the arrangement of passive sonars is defined in a function of the probability of detection and localization. These two features contain various probabilistic variations including seasons, sea states, depths of water, etc. Due to this reason, the effectiveness scores show probabilistic characteristics from the input of the arrangement of passive sonars. This paper defines the optimization problem having the results of probabilistic characteristics from various parameters of input conditions. Also, we suggest a simulation-based process of deciding the optimized arrangement of passive sonars using DPSO(Discrete binary version of PSO) method.
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강종구,이민규,김선범,황근철,이동훈,Kang, Jong-Gu,Lee, Minkyu,Kim, Sunbum,Hwang, Kun-Chul,Lee, Donghoon 한국시뮬레이션학회 2015 한국시뮬레이션학회 논문지 Vol.24 No.2
다양한 변수들이 존재하는 현대의 전투전장에서는 운용전술에 따라 전투의 양상이 결정되기 때문에 최적화된 운용전술을 도출하는 연구가 필요하다. 기존의 M&S(Modeling & Simulation) 연구에서는 몬테 칼로 실험을 통해 변수들을 분석하는 것이 일반적이다. 그러나 이 방법은 상호 복합적으로 작용하는 다수의 변수들의 모든 조합에 대해 시뮬레이션을 수행하기 때문에, 많은 수행시간이 소요되고 최적의 운용전술 도출을 위한 별도의 분석이 필요하다. 본 논문에서는 최적화 요소를 찾는 전산탐색 기법 중 하나인 DPSO(Discrete binary version of PSO) 알고리즘을 기반으로 하는 최적화 시뮬레이션 프레임워크를 제안하였다. 최적화 시뮬레이션 프레임워크는 짧은 시간 내에 최적화된 운용전술을 도출하기 위하여 설계되었다. 본 연구에서는 아군 수상함이 적 어뢰로부터 회피하는 사례를 적용하여 최적화 시뮬레이션 프레임워크의 탐색 성능을 확인하였다. 이를 통해 최적화 시뮬레이션 프레임워크의 효율성을 제시하였다. The tactical employment is a critical factor to win the war in the modern battlefield. To apply optimized tactics, it needs analyses related to a battle system. Normally, M&S (Modeling & Simulation) has been studied to analyze data in general problems. However, this method is not suitable for military simulations because there are many variables which make complex interaction in the system. For this reason, we suggested the optimized simulation framework based on the M&S by using DPSO (Discrete binary version of PSO) algorithm. This optimized simulation framework makes the best tactical employment to reduce the searching time compared with the normal M&S used by Monte Carlo search method. This paper shows an example to find the best combination of anti-torpedo scenario in a short searching time. From the simulation example, the optimized simulation framework presents the effectiveness.
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강종구,김창기,권영방,Kang, Jong-koo,Kim, Chang-ki,Kwon, Young-bang 대한수의학회 1996 大韓獸醫學會誌 Vol.36 No.1
1. The sixty raised shepherd and sixty-five inhoused pet dogs in the regions of Daejon and Cheongju were subjected to investigate the TB infection by means of BCG and X-ray diagnosis. The 5 out of 65 inhoused pet and 7 out of 60 shepherd dogs were observed to be infected with TB, respectively. However, none of Mycobacterium species were detected from lung tissues of 4-slaughtered dogs showing BCG positive reaction. 2. The rats were first inoculated with 0.1ml BCG, and then 0.1ml M bovis suspended solution($1{\times}10^5$ organisms/0.2ml) 3weeks later. After 5 months, the animals were killed. The pathohistological results from both groups, TB inoculated and BCG treated groups, were observed on the surface of lung. Furthermore, the severe pathological lesion in the Iung was observed in M bovis inoculated group compared to BCG treated group. 3. The slight macrophage invasion and granuloma formation in the lung from BCG treated group were observe individually. However, it was confirmed that the lung from M bovis treated group was invaded by the macrophages and neutrophils combined with the granuloma formation. 4. When the numbers of the total cells taken from broncho-alvealar fluid in each of mouse from both groups were differentially counted, the number of total cell, neutrophils, and lymphocytes from M bovis treated group were significantly increase compared with those of BCG treated group. 5. Although there were nearly no response of the alveolar macrophages to CSF in serum obtained from control group, those from M boris treated group were significantly proliferated.
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DeepLabV3+와 Swin Transformer 모델을 이용한 Sentinel-2 영상의 구름탐지
강종구,박강현,김근아,윤유정,최소연,이양원,Kang, Jonggu,Park, Ganghyun,Kim, Geunah,Youn, Youjeong,Choi, Soyeon,Lee, Yangwon 대한원격탐사학회 2022 大韓遠隔探査學會誌 Vol.38 No.6
Sentinel-2 can be used as proxy data for the Korean Compact Advanced Satellite 500-4 (CAS500-4), also known as Agriculture and Forestry Satellite, in terms of spectral wavelengths and spatial resolution. This letter examined cloud detection for later use in the CAS500-4 based on deep learning technologies. DeepLabV3+, a traditional Convolutional Neural Network (CNN) model, and Shifted Windows (Swin) Transformer, a state-of-the-art (SOTA) Transformer model, were compared using 22,728 images provided by Radiant Earth Foundation (REF). Swin Transformer showed a better performance with a precision of 0.886 and a recall of 0.875, which is a balanced result, unbiased between over- and under-estimation. Deep learning-based cloud detection is expected to be a future operational module for CAS500-4 through optimization for the Korean Peninsula.
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강종구,김창기,Kang, Jong-koo,Kim, Chang-ki The Korean Society of Veterinary Science 1992 大韓獸醫學會誌 Vol.32 No.1
Mycobacterium (M) bovis 를 인공감염시킨 개에 있어서 BCG의 전처치효과를 in vivo 및 in vitro에서 검토하였다. 개들은 BCG 전처치군, M bovis 단독처치군, 비감염대조군의 세군으로 나누었다. BCG는 M bovis 복강접종 3주일전에 0.2ml를 피내접종하였다. 결핵균 투여 4개월후에 전군을 도살하여 실험에 사용하였다. 도살시 모든 처치군에서 감염이 확인되었다. 병리조직학적으로 BCG전처치군의 폐장내에서는 경도의 macrophage의 침윤과 소상의 육아종 형성이 관찰되였으나 M bovis 단독처치군에 있어서는 보다 고도의 macrophage의 침윤, 중등도의 호중구의 침윤 및 중등도의 육아종의 형성이 확인되었다. 각 동물의 기관지폐포세정액을 분리하여 그 속의 총세포수와 각 세포의 분획을 검토하였다. 비감염 대조군의 기관지폐포세정액내의 총세포수는 두 처치군보다 훨씬 낮았으며 M bovis 단독처치군의 총세포수는 BCG 전처치군보다 1.8배 높았다. 이 세정액으로부터 폐포 macrophage를 분리배양하여 macrophage의 활성능과 결핵균의 증식능을 관찰하였다. BCG처치군은 M bovis 단독처치군에 비하여 높은 Fc receptor 활성(rosette 형성능, 탐식능)과 낮은 결핵균의 증식이 관찰되었다. 그러나 BCG의 전처치는 결핵균을 killing하지는 못하였다. 개에게 BCG를 전처치하면 폐내에 극소수의 결핵균이 지속적으로 잔존하지만 폐포 macrophage는 이미 항결핵성면역능을 지닌채로 계속 활성화된 상태로 존재하기 때문에 결핵에 대하여 예방효과를 갖는다고 사료된다. Dogs were divided into 3 groups of two each; Bacillie Calmette-Guerin(BCG) pretreatment, M bovis only treatment and uninfected control group. BCG were vaccinated intradermally with 0.2ml before 3weeks of M bovis intraperitoneal infection. Infection at necropsy 4months later was readily in the both treated dogs. Histopathologically, the BCG pretreated dogs produce the moderate accumulation of macrophages and focal granuloma formation in the lung, whereas the M bovis only treared dogs produce the accumulation of predominantly macrophages, occasionaly polymorphonuclear cells and the more larger granuloma Bronchoalveolar lavage(BAL) was obtained and total and differential cell counts were examined. Total number of BAL cells harvested from uninfected dogs is lower compared with those of the both treated groups. The total cell number of M bovis only treated dogs were singificantly higher 1.8 times than that of the BCG pretreated dogs. The Fe receptor activity and the growth of organism in alveolar macrophages obtained from BCG pretreated dogs were compared with that in macrophages from M bovis only treated dogs. BCG vaccination resulted in substantial macrophage activation, measured as increased Fc receptor mediated phagocytosis and rosette formation, as wells as the inhibition of intracellular mycobacteria multiplication. However, actibated macrophages taken from BCG pretreated dogs are incapable of killing the M bovis. Thus, these results suggest that BCG pretrearment in the dog may produce a protective effect against tuberculosis because active alveolar macrophages have acquired antituberculous immunity, although few mycobacteria within the lung remain in a metabolically active state.
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DeepLabV3+ 모델을 이용한 PlanetScope 영상의 해상 유출유 탐지
강종구,윤유정,김근아,박강현,최소연,양찬수,이종혁,이양원,Kang, Jonggu,Youn, Youjeong,Kim, Geunah,Park, Ganghyun,Choi, Soyeon,Yang, Chan-Su,Yi, Jonghyuk,Lee, Yangwon 대한원격탐사학회 2022 大韓遠隔探査學會誌 Vol.38 No.6
Since oil spills can be a significant threat to the marine ecosystem, it is necessary to obtain information on the current contamination status quickly to minimize the damage. Satellite-based detection of marine oil spills has the advantage of spatiotemporal coverage because it can monitor a wide area compared to aircraft. Due to the recent development of computer vision and deep learning, marine oil spill detection can also be facilitated by deep learning. Unlike the existing studies based on Synthetic Aperture Radar (SAR) images, we conducted a deep learning modeling using PlanetScope optical satellite images. The blind test of the DeepLabV3+ model for oil spill detection showed the performance statistics with an accuracy of 0.885, a precision of 0.888, a recall of 0.886, an F1-score of 0.883, and a Mean Intersection over Union (mIOU) of 0.793.
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