• 디지털콘텐츠학회 논문지
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• 제13권1호
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• pp.21-29
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• 2012

최근 인터넷의 급격한 발전과 유비쿼터스 컴퓨팅 환경 그리고 센서 네트워크와 같은 많은 정보들의 교환이 이루어지는 환경에서 연속적으로 전송되는 데이터에 대한 처리가 요구되고 있다. 이와 관련하여 XML 스트림 데이터에 대한 빈발구조 추출 및 효율적인 질의처리를 위한 마이닝 방법들이 연구되고 있다. 본 논문에서는 연속적으로 빠르게 발생하는 스트림 데이터로부터 유용한 정보를 발견하기 위한 기반 연구로써 트리거를 이용한 슬라이딩 윈도우 기반의 XML 빈발구조 탐색 방법을 제안한다. 제안된 방법은 스트림 데이터에 대한 마이닝과 연속질의 처리등을 위해 트리거를 이용하여 데이터의 흐름을 자동으로 제어할 수 있는 기반이 된다.

• Journal of Microbiology and Biotechnology
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• 제30권6호
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• pp.848-855
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• 2020

Land subsidence induced by underground coal mining leads to severe ecological and environmental problems. Arbuscular mycorrhizal fungi (AMF) have the potential to improve plant growth and soil properties. We aimed to assess the effects of AMF on the growth and soil properties of sea buckthorn under field conditions at different reclamation times. Inoculation with AMF significantly promoted the survival rate of sea buckthorn over a 50-month period, while also increasing plant height after 14, 26, and 50 months. Crown width after 14 months and ground diameter after 50 months of inoculation treatment were significantly higher than in the uninoculated treatment. AMF inoculation significantly improved plant mycorrhizal colonization rate and promoted an increase in mycelial density in the rhizosphere soil. The pH and electrical conductivity of rhizosphere soil also increased after inoculation. Moreover, after 26 and 50 months the soil organic matter in the inoculation treatment was significantly higher than in the control. The number of inoculated soil rhizosphere microorganisms, as well as acid phosphatase activity, also increased. AMF inoculation may play an active role in promoting plant growth and improving soil quality in the long term and is conducive to the rapid ecological restoration of damaged mining areas.

• 한국지구물리탐사학회:학술대회논문집
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• 한국지구물리탐사학회 1999년도 제2회 학술발표회
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• pp.21-36
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• 1999

전기비저항 탐사는 국내에서 가장 성공적으로 적용되고 있는 물리탐사 기술의 하나로서 최근에는 토목 건설분야의 지반조사 등에서의 역할이 증대되고 있다. 이와 같은 역할의 증대에 따라 더욱 정확한 해석기법의 등장이 요구되었으며, 특히 국내의 경우 매우 복잡한 지질구조와 험난한 지형여건을 고려할 수 있는 해석기술이 요구되고 있다 이러한 맥락에서 최근에 3차원 전기비저항 탐사자료의 역산기술이 개발되었다. 개발된 3차원 전기비저항 역산법은 유한요소법을 이용한 3차원 전기비저항 모델링 알고리듬을 근간으로 함으로써 국내와 같이 험난한 지형 및 복잡한 지질구조에 대하여 정확한 지하구조의 3차원 영상을 제공할 수 있으며, 특히 ACB법 (Active Constraint Balancing method)의 채용으로 지하구조에 대한 분해능의 향상을 기대할 수 있게 되었다. 개발된 3차원 영상화 기술을 토대로 토목${\cdot}$건설분야의 지반조사에 3차원 전기비저항 탐사가 동원되고 있으며, 지반조사 대상지역에 있어서 중요한 지하구조에 대한 정보인 기반암 심도, 연약대 및 파쇄대 발달상황, 지하공동의 분포 등을 제공할 수 있었다.

• International Journal of Advanced Culture Technology
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• 제12권2호
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• pp.221-226
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• 2024

This study used text mining, a big data analysis technique, to explore XR trends in South Korea. For this research, I utilized a big data platform called BigKinds. I collected data focusing on the keyword 'XR', spanning approximately 14 years from 2010 to 2024. The gathered data underwent a cleansing process and was analyzed in three ways: keyword trend analysis, relational analysis, and word cloud. The analysis identified the emergence and most active discussion periods of XR, with XR devices and manufacturers emerging as key keywords.

• Journal of Information Processing Systems
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• 제8권4호
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• pp.575-588
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• 2012

Exploiting unlabeled text data with a relatively small labeled corpus has been an active and challenging research topic in text mining, due to the recent growth of the amount of biomedical literature. Biomedical named-entity recognition is an essential prerequisite task before effective text mining of biomedical literature can begin. This paper proposes an Active Co-Training (ACT) algorithm for biomedical named-entity recognition. ACT is a semi-supervised learning method in which two classifiers based on two different feature sets iteratively learn from informative examples that have been queried from the unlabeled data. We design a new classification problem to measure the informativeness of an example in unlabeled data. In this classification problem, the examples are classified based on a joint view of a feature set to be informative/non-informative to both classifiers. To form the training data for the classification problem, we adopt a query-by-committee method. Therefore, in the ACT, both classifiers are considered to be one committee, which is used on the labeled data to give the informativeness label to each example. The ACT method outperforms the traditional co-training algorithm in terms of f-measure as well as the number of training iterations performed to build a good classification model. The proposed method tends to efficiently exploit a large amount of unlabeled data by selecting a small number of examples having not only useful information but also a comprehensive pattern.

• Toxicological Research
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• 제29권1호
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• pp.69-79
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• 2013

The purpose of this study was to investigate the current status of metal pollution in the sediment from rivers, lakes, and streams in active gold mining districts in Ghana. Two hundred and fifty surface sediment samples from 99 locations were collected and analyzed for concentrations of As, Hg, Cr, Co, Cu, Fe, Zn, Pb, Cd, Ni, and Mn using inductively coupled plasma-mass spectroscopy (ICP-MS). Metal concentrations were then used to assess the human health risks to resident children and adults in central tendency exposure (CTE) and reasonable maximum exposure (RME) scenarios. The concentrations of Pb, Cd, and As were almost twice the threshold values established by the Hong Kong Interim Sediment Quality Guidelines (ISQG). Hg, Cu, and Cr concentrations in sediment were 14, 20, and 26 times higher than the Canadian Freshwater Sediment Guidelines for these elements. Also, the concentrations of Pb, Cu, Cr, and Hg were 3, 11, 12, and 16 times more than the Australian and New Zealand Environment and Conservation Council (ANZECC) sediment guideline values. The results of the human health risk assessment indicate that for ingestion of sediment under the central tendency exposure (CTE) scenario, the cancer risks for child and adult residents from exposure to As were $4.18{\times}10^{-6}$ and $1.84{\times}10^{-7}$, respectively. This suggests that up to 4 children out of one million equally exposed children would contract cancer if exposed continuously to As over 70 years (the assumed lifetime). The hazard index for child residents following exposure to Cr(VI) in the RME scenario was 4.2. This is greater than the United States Environmental Protection Agency (USEPA) threshold of 1, indicating that adverse health effects to children from exposure to Cr(VI) are possible. This study demonstrates the urgent need to control industrial emissions and the severe heavy metal pollution in gold mining environments.

• 한국지구과학회지
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• 제30권7호
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• pp.921-925
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• 2009

아르헨티나의 전반적인 광물자원 현황의 개략적인 이해를 위해 30여개의 광상과 프로젝트를 간략히 소개하였다. 유망광상 대부분이 아르헨티나 북서 및 중서부에 분포하는데 이는 안데스 조산운동과 밀접한 관련이 있음을 시사한다. 아르헨티나는 동, 금, 은, 납, 아연, 리튬 및 붕소의 중요수출국이다. 연료에너지와 광물자원 수급의 장기적인 전략으로 양국간의 지질연구 및 광산사업의 공동협력이 활발히 요구된다.

• Journal of Power Electronics
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• 제17권5호
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• pp.1317-1326
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• 2017

The cascaded H-bridge (CHB) multilevel converter is a promising topology for large-scale photovoltaic (PV) systems. The output voltage over-modulation derived by the inter-module active power imbalance is one of the key issues for CHB PV systems. This paper proposed a dynamic power distribution strategy to eliminate the over-modulation in a CHB PV system by suitably redistributing the reactive power among the inverter modules of the CHB PV system. The proposed strategy can effectively extend the operating region of the CHB PV system with a simple control algorithm and easy implementation. Simulation and experimental results carried out on a seven-level CHB grid-connected PV system are shown to validate the proposed strategy.

• 한국정보과학회논문지:데이타베이스
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• 제29권1호
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• pp.1-14
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• 2002

연관규칙 탐사는 지지도와 신뢰도를 바탕으로 연관성 있는 강한 항목들을 탐사한다. 탐사된 연관규칙은 장바구니 분석 등과 같이 전자 상거래 및 대형 소매점 등의 판매 패턴에 대한 분석에 유용하게 적용될 수 있다. 이와 같은 연관규칙 탐사는 대규모로 축적되어 트랜잭션 데이터를 대상으로 하는 기법으로서 대규모 데이터에 대한 반복적 스캔연산을 수반한다. 그러므로 매우 높은 연산 부하를 안고 있으며 이로 인해 동적 환경에서 실시간 제한사항을 탐사에 대한 시도를 하지 못하고 있다. 따라서 이 논문에서는 연관규칙 탐사의 비 실시간적 제한사항을 위하여 트리거와 점진적 갱신 기법을 이용한 능동적 후보항목 관리 모델을 제안하였다. 아울러 제안 모델을 구현하기 위해 점진적 갱신 기법을 이용한 능동적 후보항목 관리 모델을 제한하였다. 아울러 제안 모델을 구현하기 위해 점진적 갱신 연산의 구현 모델을 제시하고 이의 구현 및 실험을 통해 성능 특성을 분석하였다.

• 한국축산식품학회지
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• 제33권4호
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• pp.463-473
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• 2013

Through the development of efficient data collecting technologies like RFID, and inter-enterprise collaboration platforms such as web services, companies which participate in supply chains can acquire visibility over the whole supply chain, and can make decisions to optimize the overall supply chain networks and processes, based on the extracted knowledge from historical data collected by the visibility system. Although not currently active, the MeatWatch system has been developed, and is used in part for this purpose, in the imported beef distribution network in Korea. However, the imported beef distribution network is too complicated to analyze its various aspects using ordinary process analysis approaches. In this paper, we suggest a novel approach, called RFID-based supply chain process mining, to automatically discover and analyze the overall supply chain processes from the distributed RFID event data, without any prior knowledge. The proposed approach was implemented and validated, by using a case study of the imported beef distribution network in Korea. Specifically we demonstrated that the proposed approach can be successfully applied to discover supply chain networks from the distributed event data, to simplify the supply chain networks, and to analyze anomaly of the distribution networks. Such novel process mining functionalities can reinforce the capability of traceability services like MeatWatch in the future.