• The Korea Journal of Herbology
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• v.38 no.5
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• pp.9-19
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• 2023

Objectives : Osteoporosis is a systemic skeletal disorder characterized by reduced bone mineral density and increased risk of fractures. Bisphosphonates and selective estrogen receptors, which are bone resorption inhibitors that are currently widely used as osteoporosis treatments, show serious side effects when administered for a long time. Research on bone resorption inhibitors that complement the problems of existing treatments is needed. The purpose of this study was to investigate the effect of inhibiting osteoclast differentiation and activity on the tuberous root of Ampelopsis japonica (Thunb.) Makino (AM). Methods : After extracting AM using distilled water and ethanol, the inhibitory effects of the two solvents on osteoclast differentiation were compared using the RANKL-induced in vitro experimental model and the TRAP assay kit. The impact of AM on bone resorption was investigated through the pit formation assay, and its effect on F-actin formation was assessed through fluorescent staining. Additionally, protein and mRNA expression levels of osteoclast differentiation markers (NFATc1, c-Fos, TRAP and ATP6v0d2) and resorption markers (MMP-9, CTK, and CA2) were analyzed via western blot and RT-PCR. Results : AM treatment significantly decreased the number of TRAP-positive cells and pit formation area. Furthermore, AM suppressed both the protein and mRNA expression of NFATc1 and c-Fos, key transcription factors involved in osteoclast differentiation and it downregulated the expression of osteoclast-associated genes such as TRAP, CTK, MMP-9, CA2, and ATP6v0d2. Conclusions : These results suggest that AM can inhibit bone resorption and osteoclast differentiation, indicating its potential for use in the treatment and prevention of osteoporosis.

• Journal of Practical Agriculture & Fisheries Research
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• v.3 no.1
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• pp.70-78
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• 2001

The objective of this study was to determine effects of corn germ meal(CGM) and condensed molasses fermentation solubles(CMS) as the replacement of rice bran on mycelial growth and density in various mushrooms. The results of this study showed that CGM and CMS might be utilized more efficiently than rice bran in culturing mushrooms. The results are as follows; 1. Mycelial growth of Pleurotus ostreatus was remarkably higher than that of control when the concentration of CGM and CMS was 10%, respectively. However, the mycelial density was lower than that of control. Thus, Considering the mycelial growth as well as density, it was found that 20% supplements of CGM and CMS resulted in the best with 78mm/10d and 71mm/10d, respectively. 2. Mycelial growth of Pleurotus eryngii in the treatment group of 10% CMS and 20% CGM showed 74mm/10d and 67mm/10d, respectively. This result tended to be equal or somewhat lower compared with that of control(74mm/10d). 3. Mycelial growth of Flamulina velutipes was 87mm/10d in the treatment of 10% CMS, 79mm/10d in the treatment of 20% CGM, which showed significantly higher than that of control(56mm/10d). When the contents of CGM and CMS were mixed with the amount of 10-30%, Thus, it was assumed that the quantity of mushrooms may increase with the supplements of CEM and CMS. 4. Mycelial growth of Lentinus edodes in the treatment group of 10-40% CMS and 10-30% CGM showed 58-52mm/10d and 56-49mm/10d, respectively. This result was significantly higher that control(47mm/10d). 5. When CMS and CGM were supplememted with the level of 10-30%, mycelial growth rate of Ganoderma lucidum showed 76-72mm/10d and 74-69mm/10d, respectively, which are higher than those of control.

• Journal of Korean Neurosurgical Society
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• v.66 no.2
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• pp.144-154
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• 2023

Objective : Stroke caused from large vessel occlusion (LVO) has emerged as the most common stroke subtype worldwide. Intravenous tissue plasminogen activator administration (IV-tPA) and additional intraarterial thrombectomy (IA-Tx) is regarded as standard treatment. In this study, the authors try to find the early recanalization rate of IV-tPA in LVO stroke patients. Methods : Total 300 patients undertook IA-Tx with confirmed anterior circulation LVO, were analyzed retrospectively. Brain computed tomography angiography (CTA) was the initial imaging study and acute stroke magnetic resonance angiography (MRA) followed after finished IV-tPA. Early recanalization rate was evaluated by acute stroke MRA within 2 hours after the IV-tPA. In 167 patients undertook IV-tPA only and 133 non-recanalized patients by IV-tPA, additional IA-Tx tried (IV-tPA + IA-Tx group). And 131 patients, non-recanalized by IV-tPA (IV-tPA group) additional IA-Tx recommend and tried according to the patient condition and compliance. Results : Early recanalization rate of LVO after IV-tPA was 12.0% (36/300). In recanalized patients, favorable outcome (modified Rankin Scale, 0-2) was 69.4% (25/36) while it was 32.1% (42/131, p<0.001) in non-recanalized patients. Among 133 patients, non-recanalized after intravenous recombinant tissue plasminogen activator and undertook additional IA-Tx, the clinical outcome was better than not undertaken additional IA-Tx (favorable outcome was 42.9% vs. 32.1%, p=0.046). Analysis according to the perfusion/diffusion (P/D)-mismatching or not, in patient with IV-tPA with IA-Tx (133 patients), favorable outcome was higher in P/D-mismatching patient (52/104; 50.0%) than P/D-matching patients (5/29; 17.2%; p=0.001). Which treatment tired, P/D-mismatching was favored in clinical outcome (iv-tPA only, p=0.008 and IV-tPA with IA-Tx, p=0.001). Conclusion : The P/D-mismatching influences on the recanalization and clinical outcomes of IV-tPA and IA-Tx. The authors would like to propose that we had better prepare IA-Tx when LVO is diagnosed on initial diagnostic imaging. Furthermore, if the patient shows P/D-mismatching on MRA after IV-tPA, additional IA-Tx improves treatment results and lessen the futile recanalization.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.62.2-62.2
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• 2019

한국의 고천문 자료는 삼국시대 이후 근대 조선까지 다수가 존재하여 세계적으로 드문 기록 문화를 보유하고 있으나, 한문 번역이 많이 이루어지지 않아 학술적 활용이 활발하지 못한 상태이다. 고문헌의 한문 문장 번역은 전문인력의 수작업에 의존하는 만큼 소요 시간이 길기에 투자대비 효율성이 떨어지는 편이다. 이에 최근 여러 분야에서 응용되는 인공지능의 적용을 대안으로 삼을 수 있으며, 초벌 번역 수준일지라도 자동번역기의 개발은 유용한 학술도구가 될 수 있다. 한국천문연구원은 한국정보화진흥원이 주관하는 2019년도 Information and Communication Technology 기반 공공서비스 촉진사업에 한국고전번역원과 공동 참여하여 인공신경망 기계학습이 적용된 고문헌 자동번역모델을 개발하고자 한다. 이 연구는 고천문 도메인에 특화된 인공지능 기계학습 기법으로 자동번역모델을 개발하여 이를 서비스하는 것을 목적으로 한다. 연구 방법은 크게 4가지 개발을 진행하는 것으로 나누어 볼 수 있다. 첫째, 인공지능의 학습 데이터에 해당되는 '코퍼스'를 구축하는 것이다. 이는 고문헌의 한자 원문과 한글 번역문이 쌍을 이루도록 만들어 줌으로써 학습에 최적화한 데이터를 최소 6만 개 이상 추출하는 것이다. 둘째, 추출된 학습 데이터 코퍼스를 다양한 인공지능 기계학습 기법에 적용하여 천문 분야 특수고전 도메인에 특화된 자동번역 모델을 생성하는 것이다. 셋째, 클라우드 기반에서 참여 기관별로 소장한 고문헌을 자동 번역 모델에 기반하여 도메인 특화된 모델로 도출 및 활용할 수 있는 대기관 서비스 플랫폼 구축이다. 넷째, 개발된 자동 번역기의 대국민 개방을 위해 웹과 모바일 메신저를 통해 자동 번역 서비스를 클라우드 기반으로 구축하는 것이다. 이 연구는 시스템 요구사항 분석과 정의를 바탕으로 설계가 진행 또는 일부 완료되어 구현 중에 있다. 추후 이 연구의 성능 평가는 자동번역모델 평가와 응용시스템 시험으로 나누어 진행된다. 자동번역모델은 평가용 테스트셋에 의한 자동 평가와 전문가에 의한 휴먼 평가에 따라 모델의 품질을 수치로 측정할 수 있다. 또한 응용시스템 시험은 소프트웨어 방법론의 개발 단계별 테스트를 적용한다. 이 연구를 통해 고천문 분야가 인공지능 자동번역 확산 플랫폼 시범의 첫 케이스라는 점에서 의의가 있다. 즉, 클라우드 기반으로 시스템을 구축함으로써 상대적으로 적은 초기 비용을 투자하여 활용성이 높은 한문 문장 자동 번역기라는 연구 인프라를 확보하는 첫 적용 학문 분야이다. 향후 이를 활용한 고천문 분야 학술 활동이 더욱 활발해질 것을 기대해 볼 수 있다.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.56.1-56.1
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• 2020

한국의 고문헌 중에는 다양한 고천문 기록들이 한문 형태로 존재하며, 이를 학술적으로 활용하기 위해서는 전문 번역가 투입에 따른 많은 비용과 시간이 요구된다. 이에 인공신경망 기계학습에 의한 인공지능 번역기를 개발하여 비록 초벌 번역 수준일지라도 문장 형태의 한문을 한글로 자동번역해 주는 학술 도구를 소개하고자 한다. 이 자동번역기는 한국천문연구원이 한국정보화진흥원이 주관하는 2019년도 Information and Communication Technology 기반 공공서비스 촉진사업에 한국고전번역원과 공동 참여하여 개발 완료한 것이다. 이 연구는 고천문 도메인에 특화된 인공지능 기계학습용 데이터인 천문 고전 코퍼스를 구축하여 이를 기반으로 천문 고전 특화 자동번역 모델을 개발하고 번역 서비스하는 것을 목적으로 한다. 이를 위해 구축되는 시스템은 크게 세 가지이다. 첫째, 로그인이 필요 없이 누구나 웹 접속을 통해 사용이 가능한 클라우드 기반의 고문헌 자동번역 대국민서비스 시스템이다. 둘째, 참여 기관별로 구축된 코퍼스와 도메인 특화된 번역 모델의 생성 및 관리할 수 있는 클라우드 기반의 대기관 서비스 플랫폼 구축이다. 셋째, 개발된 자동번역 Applied Programmable Interface를 활용한 한국천문연구원 내 자체 서비스가 가능한 AITHA 시스템이다. 연구 결과로서 먼저 구축된 천문 고전 코퍼스 60,760건에 대한 샘플링 검수 결과는 품질 순도 99.9% 이상이다. 아울러 도출된 천문 고전 특화 번역 모델 총 20개 중 대표 모델에 대한 성능 평가 결과는 기계 번역 텍스트 품질 평가 알고리즘인 Bilingual Evaluation Understudy 평가에서 40.02점이며, 전문가에 의한 휴먼 평가에서 5.0 만점 중 4.05점이다. 이는 당초 연구 목표로 삼았던 초벌 번역 수준에 충분하며, 현재 개발된 시스템들은 자체 시험 운영 중이다. 이 연구는 특수 고문헌에 해당되는 고천문 기록들의 번역 장벽을 낮춰 관련 연구자들의 학술적 접근 및 다양한 연구에 도움을 줄 수 있다는 점에서 의의가 있다. 또한 고천문 분야가 인공지능 자동번역 확산 플랫폼 시범의 첫 케이스로써 추후 타 학문 분야 참여 시 시너지 효과도 기대해 볼 수 있다. 고문헌 자동번역기는 점차 더 많은 학습 데이터와 학습량이 쌓일수록 더 좋은 학술 도구로 진화할 것이다.

• Journal of Korean Tunnelling and Underground Space Association
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• v.11 no.2
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• pp.199-211
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• 2009

Development of underground space is actively performed globally for better life in the surface, and the scale of the space is increasing. Extreme care should be taken in the construction of the underground space in urban areas in order to avoid damage of adjacent structures and interference with existing underground space. In case of shallow tunnels, reinforcement of ground and structures is necessary to minimize the damage to structures due to excavation but any standard for optimum range of the reinforcement has not been established yet. In this paper, a series of numerical analyses have been performed for a 20 m diameter tunnel excavated underneath a structure to investigate the degree of damage of the structure according to vertical and horizontal spacing between the tunnel and structure. In addition to that, optimum range of reinforcement is presented for each case where reinforcement is required. It has been observed that the reinforcement is necessary for the ground condition adapted in the analyses as follows: (1) if horizontal spacing ($S_{H}$) approaches to 0D (D: equivalent diameter of tunnel) for vertical spacing (Sv) of 0.5D, and (2) if tunnel exists underneath the structure for vertical spacing (Sv) of 0.75D. The reinforcement is not necessary for Sv of 10 regardless of $S_{H}$. It also has been obtained that the optimum ranges of the reinforcement around structure foundation are 7 m in depth and whole width of the structure and 5 m beyond tunnel sidewall. These reinforcememt ranges have been confirmed to be enough for stability of the structure if types of reinforcement method is appropriately selected.

• Journal of the Korean Recycled Construction Resources Institute
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• v.11 no.4
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• pp.355-363
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• 2023

In safety assessment of a aged bridge, dynamic characteristics and displacement are directly related to the rigidity of the structural system, especially displacement is the most important factor as the physical quantity that the bridge user can directly detect. However, in order to measure the displacement of the bridge, it is difficult to install displacement sensors at the bottom of the bridge and conduct traffic blocking and loading tests, resulting in increased costs or impossible measurements depending on the bridge's environment. In this study, a method of measuring the displacement of a bridge using only accelerometers without installing displacement sensors and ambient vibration without a loading test was proposed. For the analysis of bridge dynamic characteristics and displacement using ambient vibration, the mode shape and natural frequency of the bridge were extracted using a TDD technique known to enable quick analysis with simple calculations, and the unit load displacement of the bridge was analyzed through flexibility analysis to calculate static displacement. To verify this proposed technology, an on-site test was conducted on C Bridge, and the results were compared with the measured values of the loading test and the structural analysis data. As a result, it was confirmed that the mode shape and natural frequency were 0.42 to 1.13 % error ratio, and the maximum displacement at the main span was 3.58 % error ratio. Therefore, the proposed technology can be used as a basis data for indirectly determine the safety of the bridge by comparing the amount of displacement compared to the design and analysis values by estimating the displacement of the bridge that could not be measured due to the difficulty of installing displacement sensors.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.795-799
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• 2023

The Canadian military participated in World War I and felt the limitations of the recruitment system through the continuous shortage of troops caused by the prolonged war, therefore expanded the role and scope of female manpower. The use of female manpower, which began with medical support for the first time, increased its necessity and importance as medical support personnel were dispatched overseas and women's manpower was expanded to combat support missions for the Army, Navy, and Air Force. Since then, the proportion of female manpower has been limited to 1.5% of the total number of employees at the end of the Second World War and the reduction of troops and the dismantling of the women's unit. In this situation, the Austrian Defence Force gradually accepts the recommendation of the Royal Canadian Women's Status Committee to improve the service conditions of women, marking a turning point in expanding the role of women in the Canadian military. The the Austrian Defence Force conducted long-term combat experiments to increase the proportion and role of female manpower, increasing reliability through observation and analysis to prove whether female manpower is suitable for combat troops. Korea also wants to draw implications for the future direction by comparing the history and current appearance of the Canadian military's use of female manpower with the Korean military at a time when the problem of a shortage of troops is emerging due to the recent decline in fertility and low birth rates.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.161-172
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• 2023

Autonomous driving vehicles recognize the surroundings through various sensors mounted on the vehicle and control the vehicle based on the collected information. The level of autonomous driving technology is improving due to the development of sensor technology and algorithms that process collected data, but the implementation of perfect autonomous driving technology has not been achieved. To overcome these limitations, through autonomous cooperative driving centered on infrastructure. In this study, developed a position correction sign that provides a reference for positioning of autonomous vehicles. First of all, an analysis was performed on the current status of positioning technology for autonomous driving. And measure the number of point clouds for the 1st sample consisting of two square reflective surfaces and 2nd sample that increased the vertical length of each reflective surface. Experimental results show that both primary and secondary products are installed at least 15 m apart It could be recognized as a sensor, and it was confirmed that the secondary production that increased the length of the top and bottom had a higher number of point clouds than the primary production and better expressed the shape of the facility.

• Korean Journal of Radiology
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• v.22 no.3
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• pp.476-488
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• 2021

Objective: We aimed to develop a deep neural network for segmenting lung parenchyma with extensive pathological conditions on non-contrast chest computed tomography (CT) images. Materials and Methods: Thin-section non-contrast chest CT images from 203 patients (115 males, 88 females; age range, 31-89 years) between January 2017 and May 2017 were included in the study, of which 150 cases had extensive lung parenchymal disease involving more than 40% of the parenchymal area. Parenchymal diseases included interstitial lung disease (ILD), emphysema, nontuberculous mycobacterial lung disease, tuberculous destroyed lung, pneumonia, lung cancer, and other diseases. Five experienced radiologists manually drew the margin of the lungs, slice by slice, on CT images. The dataset used to develop the network consisted of 157 cases for training, 20 cases for development, and 26 cases for internal validation. Two-dimensional (2D) U-Net and three-dimensional (3D) U-Net models were used for the task. The network was trained to segment the lung parenchyma as a whole and segment the right and left lung separately. The University Hospitals of Geneva ILD dataset, which contained high-resolution CT images of ILD, was used for external validation. Results: The Dice similarity coefficients for internal validation were 99.6 ± 0.3% (2D U-Net whole lung model), 99.5 ± 0.3% (2D U-Net separate lung model), 99.4 ± 0.5% (3D U-Net whole lung model), and 99.4 ± 0.5% (3D U-Net separate lung model). The Dice similarity coefficients for the external validation dataset were 98.4 ± 1.0% (2D U-Net whole lung model) and 98.4 ± 1.0% (2D U-Net separate lung model). In 31 cases, where the extent of ILD was larger than 75% of the lung parenchymal area, the Dice similarity coefficients were 97.9 ± 1.3% (2D U-Net whole lung model) and 98.0 ± 1.2% (2D U-Net separate lung model). Conclusion: The deep neural network achieved excellent performance in automatically delineating the boundaries of lung parenchyma with extensive pathological conditions on non-contrast chest CT images.