• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.101-107
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• 2010

The aim of this paper is to come up with a methodology of constructing an efficient model for multiple representations which can manage and reconcile real-time data about large-scale roads in Vector Domain. In other words, we suggested framework based on a bottom-up approach, which is allowed to integrate data from the network of the lowest level sequentially and perform automated matching in order to produce variable-scale map. Finally, we applied designed multi-LoD model to in-vehicle application.

• Korean Journal of Remote Sensing
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• v.38 no.2
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• pp.199-213
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• 2022

The unsupervised domain adaptation can solve the impractical issue of repeatedly collecting high-quality training data every year for annual crop classification. This study evaluates the applicability of deep learning-based unsupervised domain adaptation models for crop classification. Three unsupervised domain adaptation models including a deep adaptation network (DAN), a deep reconstruction-classification network, and a domain adversarial neural network (DANN) are quantitatively compared via a crop classification experiment using unmanned aerial vehicle images in Hapcheon-gun and Changnyeong-gun, the major garlic and onion cultivation areas in Korea. As source baseline and target baseline models, convolutional neural networks (CNNs) are additionally applied to evaluate the classification performance of the unsupervised domain adaptation models. The three unsupervised domain adaptation models outperformed the source baseline CNN, but the different classification performances were observed depending on the degree of inconsistency between data distributions in source and target images. The classification accuracy of DAN was higher than that of the other two models when the inconsistency between source and target images was low, whereas DANN has the best classification performance when the inconsistency between source and target images was high. Therefore, the extent to which data distributions of the source and target images match should be considered to select the best unsupervised domain adaptation model to generate reliable classification results.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2006.06a
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• pp.159-163
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• 2006

최근 도메인에 기반한 개념과 이들 개념간의 관계를 설정할 수 있는 온톨로지 기반 컨텍스트 모델들이 유비쿼터스 컴퓨팅 환경에서 연구되고 있다. 그러나 새로운 개념의 추가에 따른 온톨로지 재구성은 시간이나 비용적으로 많은 오버헤드를 초래한다. 즉 하위 레벨에 있는 임의의 데이터 구조가 수정될 때마다 계속 적으로 기존 온톨로지를 변경해야만 한다. 따라서 센서 노드의 동적인 컨텍스트 표현보다 미들웨어와 같은 최상위의 추상적이고 정적인 컨텍스트 표현에 적합하다. 한편 센서 네트워크에서의 베이스 스테이션 기반 상황인지 기법은 상황 조건을 만족시키지 못하는 저수준 센싱 정보를 베이스 스테이션으로 전송하는데 많은 에너지를 소모한다. 본 논문에서는 센서 노드에서의 동적인 컨텍스트의 표현과 저수준 센싱 정보의 전송량을 줄이기 위해 메타데이터와 RDF 기반 구조의 변형인 Triple 구조를 결합한 컨텍스트 모델은 제안한다.

• Convergence Security Journal
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• v.3 no.2
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• pp.85-97
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• 2003

At the end of last January, 2003, a domestic top-level domain name server (DNS) shut down the server and it caused the wired and wireless internet services to be completely paralyzed in the aftermath of a virus attack incurring a various range of losses nationwide. The main reason of this event is the lack of our awareness of cyber security. In particular, in the small-scale network, there are few security administrators and no operating devices to protect information as well. Under this circumstance, using ESM center to service real-time security supervision and correspondence for network, it can be one option. However, due to the economic efficiency, most of security systems have been being developed focusing on the large-scale network first. Therefore, ESM centers which inspect security state of network concentrate on IDC or large-scale network services. This dissertation studies economical ESM service by designing exclusive SnSA for small-scale network for widespread use. Firstly, network invasion feeler function N_SnSA and host invasion feeler function H_SnSA are embodied to collect more informations in the small-scale network. Secondarily, the existing vulnerability is studied to find the solutions linked with a low cost to a Public center such as Kyonggi Univ ESM center.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.209-210
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• 2022

사회적 문제로 떠오르고 있는 건설산업에서 늘 만연한 산업재해 발생을 막기 위해서는 다양한 이해관계자들의 노력을 투자해야 한다. 특히, 이해 관계자들 사이에서 주문자는 프로젝트의 의사 결정 구조의 최상위에 있다. 따라서 주문자의 안전과 건강에 대한 인식은 전체 건설 현장의 안전을 확보하는 과정에 직접적인 영향을 미친다. 이러한 관점에서 본 연구는 최근에 도입된 고객에 대한 의무적인 안전 및 건강 조치에 관한 각 이해 관계자의 인식 차이를 확인하는 것을 목표로 한다. 또한 한국적 맥락에서 구체적인 이행 계획을 제시한다. 분석에 사용된 데이터는 주문자, 안전 관리자, 현장 관리자와 같은 이해 관계자를 대상으로 한 설문 조사를 통해 수집되었으며, 수집된 데이터는 분산 분석과 같은 다변량 분석 방법을 사용하여 정량적으로 검토되었다. 분석 결과, 소유자에 대한 안전 및 건강 의무의 도입이 필요한 것으로 판명되었으며, 안전 및 건강 전문가를 행동 계획으로 지정하고 운영하는 것이 합리적이라고 간주되었다. 저자들은 이번 연구 결과가 한국의 관련 규제 개정을 위한 기본 자료로 활용될 수 있을 것으로 기대하고 있다. 또한, 추가 연구로서, 규제 개선 후 효과에 대한 검토는 도메인에 크게 기여할 것이다.

• Journal of Life Science
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• v.31 no.9
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• pp.856-861
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• 2021

CD82/KAI1, identified as a metastasis suppressor, was initially known only as a molecular facilitator, but its various functions have recently been revealed. CD82 plays an important role in the stem-progenitor cell, angiogenesis, and muscle. We would like to introduce the recently reported functions and roles of CD82 in this review. CD82 is a member of the tetraspanin family, which consists of four transmembrane domains. The interaction between CD82 and cell adhesion molecules suppresses the metastasis of cancer. CD82 regulates the cell cycle of stem-progenitor cells in the stem cell niche. In the bone marrow, CD82 is expressed on long-term repopulating hematopoietic stem cells (LT-HSCs), which show multipotent differentiation potential. The interaction between CD82 and Duffy antigen receptor for chemokines (DARC) induces quiescence in LT-HSCs. CD82 also regulates Rac1 activity, resulting in the homing and engraftment of HSCs into the bone marrow niche. Besides, CD82 maintains the differentiation potential of muscle stem cells and prevents angiogenesis by inhibiting the expression of cytokines, such as IL-6 and VEGF and adhesion molecules in endothelial cells. CD82 is a key membrane protein that distinguishes the hierarchy of stem-progenitor cells, and is also important for amplification and verification of cellular resources. Further studies on the function of CD82 in various organs and cells are expected to advance cell biology and cell therapy.