• Computers and Concrete
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• 제15권5호
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• pp.771-794
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• 2015

This paper proposes an innovative method for selection of measurement sets in static parameter identification of concrete or steel bridges. This method is proved as a systematic tool to address the first steps of Structural System Identification procedures by observability techniques: the selection of adequate measurement sets. The observability trees show graphically how the unknown estimates are successively calculated throughout the recursive process of the observability analysis. The observability trees can be proved as an intuitive and powerful tool for measurement selection in beam bridges that can also be applied in complex structures, such as cable-stayed bridges. Nevertheless, in these structures, the strong link among structural parameters advises to assume a set of simplifications to increase the tree intuitiveness. In addition, a set of guidelines are provided to facilitate the representation of the observability trees in this kind of structures. These guidelines are applied in bridges of growing complexity to explain how the characteristics of the geometry of the structure (e.g. deck inclination, type of pylon-deck connection, or the existence of stay cables) affect the observability trees. The importance of the observability trees is justified by a statistical analysis of measurement sets randomly selected. This study shows that, in the analyzed structure, the probability of selecting an adequate measurement set with a minimum number of measurements at random is practically negligible. Furthermore, even bigger measurement sets might not provide adequate SSI of the unknown parameters. Finally, to show the potential of the observability trees, a large-scale concrete cable-stayed bridge is also analyzed. The comparison with the number of measurements required in the literature shows again the advantages of using the proposed method.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.247-249
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• 2007

Crown parameters are important roles in tree species identification, because the canopy is the aggregate of all the crowns. However, crown measurements with spaceborne image data have remained more difficult than on aerial photographs since trees show more structural detail at higher resolutions. This recognized problem led to the initiation of the research to determine if high resolution satellite image data could be used to identify and classify single tree species. In this paper, shape parameters derived from pixel-based crown area measurements and texture features derived from GLCM parameters in QuickBird image were tested and compared for individual tree species identification. As expected, initial studies have shown that the crown parameters and the canopy texture parameters provided a differentiating method between coniferous trees and broad-leaved trees within the compartment(less than forest stand) for single extraction from spaceborne high resolution image.

• Nuclear Engineering and Technology
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• 제53권9호
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• pp.2888-2898
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• 2021

Vital area identification (VAI) is an essential procedure for the design of physical protection systems (PPSs) for nuclear power plants (NPPs). The purpose of PPS design is to protect vital areas. VAI has been improved continuously to overcome the shortcomings of previous VAI generations. In first-generation VAI, a sabotage fault tree was developed directly without reusing probabilistic safety assessment (PSA) results or information. In second-generation VAI, VAI model was constructed from all PSA event trees and fault trees. While in third-generation VAI, it was developed from the simplified PSA event trees and fault trees. While VAIs have been performed for NPPs in full-power operations, VAI for NPPs in low-power and shutdown (LPSD) operations has not been studied and performed, even though NPPs in LPSD operations are very vulnerable to sabotage due to the very crowded nature of NPP maintenance. This study is the first to research and apply VAI to LPSD operation of NPP. Here, the third-generation VAI method for full-power operation of NPP was adapted to the VAI of LPSD operation. In this study, LPSD VAI for a few plant operational states (POSs) was performed. Furthermore, the operation strategy of vital areas for both full-power and LPSD operations was discussed. The LPSD VAI method discussed in this paper can be easily applied to all POSs. The method and insights in this study can be important for future LPSD VAI that reflects various LPSD operational states. Regulatory bodies and electric utilities can take advantage of this LPSD VAI method.

• 한국통신학회논문지
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• 제35권9B호
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• pp.1360-1368
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• 2010

최근 RFID 기술이 발전함에 따라 그 부가가치가 부각되고 있는 문화재 복원용 임목(금강송) 또는 보호수 등의 주요 임목에 대한 이력 및 위치 정보를 전자적으로 관리할 수 있는 서비스에 대한 요구가 증가하고 있다. 하지만 기존의 주요 임목 정보 관리 체계는 대상 임목의 이력 정보를 도면과 문서대장을 이원화하여 수기 중심으로 관리하거나, 또는 임목 정보를 한정된 PDA의 저장소에 데이터 파일 형태로 보관하여 내부업무로 컴퓨터에 입력 및 계산을 통하여 자료화하는 구조로 관리되어 왔다. 이러한 관리 구조는 대상 임목의 이력 및 위치 정보를 파악하는데 확장성과 범위성 측면에서 많은 어려움을 내포하고 있다. 본 논문에서는 RFID 기반의 문화재 복원용 임목 이력 정보 시스템을 설계 및 구현하였다. 제안 시스템의 특징으로는 문화재 복원용 임목 위치 및 이력 정보를 기존의 수기 중심의 시스템보다 체계적이고 효과적으로 관리할 수 있게 지원해주는 것이며, 또한 서비스 대상의 임목정보를 제공 및 관리할 수 있도록 무선인터넷 또는 무선 랜을 이용한 모바일 RFID 서비스를 구현하여 업무 프로세스를 개선하는 것이다. 제안한 시스템의 특징을 구현을 통하여 확인하였다.

• The Plant Pathology Journal
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• 제34권3호
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• pp.157-162
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• 2018

The objective of this work was to accomplish the isolation, molecular identification and characterizing the physiology of the causal agent of the algal spot in mango trees. For this purpose, the pathogen growth was assessed in different culture media, with subsequent observation and measurements of the filamentous cells. The molecular identification was made using mycelium obtained from leaf lesions and pure algae colonies grown in culture medium. Descriptions based on DNA sequencing indicated that the algae is Cephaleuros virescens. The algae must be isolated primarily in liquid medium for further pricking into agar medium. The highest mycelial growth average in Petri dishes occurred when the algae were grown in Trebouxia and BBM. Trebouxia enabled larger cells in the filamentous cells when compared to other culture media.

• 한국균학회지
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• 제46권3호
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• pp.205-211
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• 2018

Fungal endophytes are defined as fungi inhabiting plant tissues, causing no apparent disease. As the agricultural and ecological importance of endophytes has increased, many studies have been performed on various aspects, ranging from basic identification, taxonomy, and evolution to secondary metabolites with potential for human use. In the Korean Peninsula, conifers are the most commonly found evergreen trees, with approximately 30 to 60 reported taxa. Studies on the effect of conifer-associated endophytes on the host plants are required for the preservation and conservation of coniferous forests which decline by climate change and deforestation. This review summarizes the diversity of endophytic fungi in coniferous trees of Korea and their relationship with host plants.

• Journal of the Korean Wood Science and Technology
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• 제33권2호통권130호
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• pp.56-64
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• 2005

This study was performed to investigate the frequency of blue staining fungal species collected from pine trees, Experimental Forests of Kangwon National University in Korea based on their morphological characteristics. In addition the tolerance to fungicide, Woodguard, was assessed to get basic knowledges for preventing blue stain of wood. Totally Leptographium-type fungi were dominated by 79.3% among Ophiostomatoid fungi associated with scolityd bark beetles in pine trees. Leptographium-type Ds-isolates which have unusual morphology were collected as frequency of 17.0%. The most distinct differeneces of these Ds-isolates from L. procerum were the presence of roughened hyphae and flask-shaped conidiophores that have never been mentioned formerly for L. procerum, but since these Ds-isolates formed black concentric rings being a property of L. procerum, the Df-isolates were characterized as Leptographium-type fungi, which are the most common species with the highest frequency by 33.2% in this particular area. According to our experimental results, Leptographium-type Ds- and Df-isolates were very resistant to fungicide, Woodguard, therefore it was suggested that a new method for wood protection from the blue staining fungi should be developed. Exact identification of blue staining isolates collected from pine trees is keep going.

• 식물분류학회지
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• 제44권1호
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• pp.39-50
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• 2014

엽록체 matK 유전자와 핵 ITS 염기서열을 이용하여 나도풍란속 및 풍란속의 계통학적 위치를 정립하였다. 또한, 이들 마커를 이용하여 종 및 원산지 추적에 활용가능성을 평가하였다. 풍란속과 나도풍란속은 두 마커 모두에서 뚜렷한 단계통군을 형성하였다. 풍란속의 자매군은 Vanda임이 두 마커 모두에서 입증되었으나,본 연구 결과는 풍란속을 Vanda에 포함시키는 처리에는 동의하지 않았다. 나도풍란속은 (Dimorphorchis (Pteroceras (Saccolabiun+Phalaeonopsis))) 계통군과 자매군을 형성하였고, 이중 Dimorphorchis와 자매속일 가능성이 가장 높았다. 형태적 유사성으로 나도풍란속이 Aerides와 자매속이라는 주장의 가능성은 희박하였다. 두 마커를 분석한 결과 풍란속의 경우 종 및 종 내의 산지별 구별이 가능한 것으로 평가되었다. 따라서 풍란의 재배 개체들의 기원을 규명하는데도 유용한 것으로 평가되었다. 그러나, 공공 염기서열 DB에 있는 서열들은 의유전자로 추정되는 서열들을 다수 포함하고 있었다. 또한, 재배 난과식물에는 속간 및 종간 잡종이 많으며 잡종에 의한 수평적 유전자 이동문제 등이 결부되어 있으므로, 계통학적으로 염기서열 자료를 이용하는데 주의하여야 한다. 계통분석을 위하여는 한 종 내의 여러 개체로부터 염기서열을 확보하는 것이 이러한 위험성을 줄이는 방법 중에 하나이다.

• International journal of advanced smart convergence
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• 제13권2호
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• pp.48-60
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• 2024

With the exponential growth of satellite data utilization, machine learning has become pivotal in enhancing innovation and cybersecurity in satellite systems. This paper investigates the role of machine learning techniques in identifying and mitigating vulnerabilities and code smells within satellite software. We explore satellite system architecture and survey applications like vulnerability analysis, source code refactoring, and security flaw detection, emphasizing feature extraction methodologies such as Abstract Syntax Trees (AST) and Control Flow Graphs (CFG). We present practical examples of feature extraction and training models using machine learning techniques like Random Forests, Support Vector Machines, and Gradient Boosting. Additionally, we review open-access satellite datasets and address prevalent code smells through systematic refactoring solutions. By integrating continuous code review and refactoring into satellite software development, this research aims to improve maintainability, scalability, and cybersecurity, providing novel insights for the advancement of satellite software development and security. The value of this paper lies in its focus on addressing the identification of vulnerabilities and resolution of code smells in satellite software. In terms of the authors' contributions, we detail methods for applying machine learning to identify potential vulnerabilities and code smells in satellite software. Furthermore, the study presents techniques for feature extraction and model training, utilizing Abstract Syntax Trees (AST) and Control Flow Graphs (CFG) to extract relevant features for machine learning training. Regarding the results, we discuss the analysis of vulnerabilities, the identification of code smells, maintenance, and security enhancement through practical examples. This underscores the significant improvement in the maintainability and scalability of satellite software through continuous code review and refactoring.

• 한국약용작물학회지
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• 제10권2호
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• pp.126-131
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• 2002

황칠수액 분비량을 개체 및 서식지별 차이가 있는지를 검토하고, 차이가 있다면 이를 토대로 서식환경 및 우수개체선발을 위한 기초자료를 수집하고자 하였다. 황칠수액 분비량을 기준으로 우수개체를 선발하고 선발 개체군을 중심으로 주요 방향성 정유성분의 동정 및 분포 양상을 조사하였다. 황칠나무 수액은 서식지별, 수령 및 개체별 차이가 확인되었으며, 분비량을 기준으로 우수개체를 선발하였다. 선발된 개체에서의 주요 정유성분에서${\beta}-elemene,\;germacrene-D,\;{\beta}-selinene,\;{\alpha}-selinene,\;{\gamma}-cardinene,\;{\delta}-cadinene$ 등이 었으며, 그 중에서도 germacrene D가 주요 구성성분임이 확인되었다. 선발개체의 주요 정유성분의 구성비율은 서식지별 및 각 개체별 차이가 존재하였다.