• 제목/요약/키워드: Split map

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한국 상록활엽수림의 군집분류 (Syntaxonomy of Evergreen Broad-leaved Forests in Korea)

  • Kil, Bong-Seop;Kim, Jeong-Un
    • 환경생물
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    • 제17권3호
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    • pp.233-247
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    • 1999
  • 우리나라 상록활엽수림의 식생인 동백나무군강(Camellietea japonicae)에 대한 군집분류 체계의 수립을 시도하였다. 여러 저자들에 의한 399 식생조사 자료로 2개의 식물사회학적인 표를 작성하고 군단을 정리한 바, 한국의 상록활엽수림 식생은 현재 15개의 군집을 포함하는 3개의 군단으로 구분되었다. 즉, (1) 신칭 가시나무-잣밤나무군단(Querco-Castanopsion all. nov.)은 구실잣밤나무군집 (Castano-psietum sieboldii), 붉가시나무군집 (Quercetum acutae), 가시나무군집 (Quercetum myrsinaefoliae)과 까마귀쪽나무군집(Litseetum japonicae)등 4개의 군집으로 나누어지고 (2) 신칭 후박나무-동백나무군단 (Machilo-Camellion all. nov.)은 10개의 군집 즉, 후박나무군집 (Machiletum thunbergii), 돈나무군집 (Pittosporetum tobirae), 식나무군집 (Aucubetum japonicae), 참식나무군집 (Neolitsetum sericeae), 우묵사 스레피군집 (Euryetum emarginatae), 보리밥나무군집 (Elaeagnetum macrophyllae), 동백나무군집 (Camellietum japonicae), 차나무-동백 나무군집 (Theo-Camellietum japonicae), 다정큼나무군집 (Raphiolepietum umbellatae)과 굴거리군집 (Daphniphylletum macropodae)이 그것이다. 또 (3) 황칠나무-구실잣밤나무군단(Dendropanaco-Castanopsion sieboldii)은 하나의 군집인 좀비비추-구실잣밤나무군집(Hosto minoris-Castanopsietum sieboldii)을 포함하고 있다. 이들 군단의 식물종조성, 생태학적 특성을 기술하고 그들의 분포를 나타내는 지도를 작성했다.

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DEVELOPMENT OF A WALL-TO-FLUID HEAT TRANSFER PACKAGE FOR THE SPACE CODE

  • Choi, Ki-Yong;Yun, Byong-Jo;Park, Hyun-Sik;Kim, Hee-Dong;Kim, Yeon-Sik;Lee, Kwon-Yeong;Kim, Kyung-Doo
    • Nuclear Engineering and Technology
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    • 제41권9호
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    • pp.1143-1156
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    • 2009
  • The SPACE code that is based on a multi-dimensional two-fluid, three-field model is under development for licensing purposes of pressurized water reactors in Korea. Among the participating research and industrial organizations, KAERI is in charge of developing the physical models and correlation packages for the constitutive equations. This paper introduces a developed wall-to-fluid heat transfer package for the SPACE code. The wall-to-fluid heat transfer package consists of twelve heat transfer subregions. For each sub-region, the models in the existing safety analysis codes and the leading models in literature have been peer reviewed in order to determine the best models which can easily be applicable to the SPACE code. Hence a wall-to-fluid heat transfer region selection map has been developed according to the non-condensable gas quality, void fraction, degree of subcooling, and wall temperature. Furthermore, a partitioning methodology which can take into account the split heat flux to the continuous liquid, entrained droplet, and vapor fields is proposed to comply fully with the three-field formulation of the SPACE code. The developed wall-to-fluid heat transfer package has been pre-tested by varying the independent parameters within the application range of the selected correlations. The smoothness between two adjacent heat transfer regimes has also been investigated. More detailed verification work on the developed wall-to-fluid heat transfer package will be carried out when the coupling of a hydraulic solver with the constitutive equations is brought to completion.

투자자별 거래정보와 머신러닝을 활용한 투자전략의 성과 (Performance of Investment Strategy using Investor-specific Transaction Information and Machine Learning)

  • 김경목;김선웅;최흥식
    • 지능정보연구
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    • 제27권1호
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    • pp.65-82
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    • 2021
  • 주식시장에 참여하는 투자자들은 크게 외국인투자자, 기관투자자, 그리고 개인투자자로 구분된다. 외국인투자자 같은 전문투자자 집단은 개인투자자 집단과 비교하여 정보력과 자금력에서 우위를 보이고 있으며, 그 결과 시장 참여자들 사이에는 외국인투자자들이 좋은 투자 성과를 보이는 것으로 알려져 있다. 외국인 투자자들은 근래에는 인공지능을 이용한 투자를 많이 하고 있다. 본 연구의 목적은 투자자별 거래량 정보와 머신러닝을 결합하는 투자전략을 제안하고, 실제 주가와 투자자별 거래량 데이터를 이용하여 제안 모형의 포트폴리오 투자 성과를 분석하는 것이다. 일별 투자자별 매수 수량과 매도 수량 정보는 한국거래소에서 공개하고 있는 자료를 활용하였으며, 여기에 인공신경망을 결합하여 최적의 포트폴리오 전략을 도출하고자 하였다. 본 연구에서는 자기 조직화 지도 모형 인공신경망을 이용하여 투자자별 거래량 데이터를 그룹화하고 그룹화한 데이터를 변환하여 오류역전파 모형을 학습하였다. 학습 후 검증 데이터 예측결과로 매월 포트폴리오 구성을 하도록 개발하였다. 성과 분석을 위해 포트폴리오의 벤치마크를 지정하였고 시장 수익률 비교를 위해 KOSPI200, KOSPI 지수 수익률도 구하였다. 포트폴리오의 동일배분 수익률, 복리 수익률, 연평균 수익률, MDD, 표준편차, 샤프지수, 벤치마크로 지정한 시가총액 상위 10종목의 Buy and Hold 수익률 등을 사용하여 성과 분석을 진행하였다. 분석 결과 포트폴리오가 벤치마크 대비 2배 수익률을 올렸으며 시장 수익률보다 좋은 성과를 보였다. MDD와 표준편차는 포트폴리오와 벤치마크가 비슷한 결과로 성과 대비 비교한다면 포트폴리오가 좋은 성과라고 할 수 있다. 샤프지수도 포트폴리오가 벤치마크와 시장 결과보다 좋은 성과를 내었다. 이를 통해 머신러닝과 투자자별 거래정보 분석을 활용한 포트폴리오 구성 프로그램 개발의 방향을 제시하였고 실제 주식 투자를 위한 프로그램 개발에 활용할 수 있음을 보였다.

Spatial and Temporal Analyses of Cervical Cancer Patients in Upper Northern Thailand

  • Thongsak, Natthapat;Chitapanarux, Imjai;Suprasert, Prapaporn;Prasitwattanaseree, Sukon;Bunyatisai, Walaithip;Sripan, Patumrat;Traisathit, Patrinee
    • Asian Pacific Journal of Cancer Prevention
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    • 제17권11호
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    • pp.5011-5017
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    • 2016
  • Background: Cervical cancer is a major public health problem worldwide. There have been several studies indicating that risk is associated with geographic location and that the incidence of cervical cancer has changed over time. In Thailand, incidence rates have also been found to be different in each region. Methods: Participants were women living or having lived in upper Northern Thailand and subjected to cervical screening at Maharaj Nakorn Chiang Mai Hospital between January 2010 and December 2014. Generalized additive models with Loess smooth curve fitting were applied to estimate the risk of cervical cancer. For the spatial analysis, Google Maps were employed to find the geographical locations of the participants' addresses. The Quantum Geographic Information System was used to make a map of cervical cancer risk. Two univariate smooths: x equal to the residency duration was used in the temporal analysis of residency duration, and x equal to the calendar year that participants moved to upper Northern Thailand or birth year for participants already living there, were used in the temporal analysis of the earliest year. The spatial-temporal analysis was conducted in the same way as the spatial analysis except that the data were split into overlapping calendar years. Results: In the spatial analysis, the risk of cervical cancer was shown to be highest in the Eastern sector of upper Northern Thailand (p-value <0.001). In the temporal analysis of residency duration, the risk was shown to be steadily increasing (p-value =0.008), and in the temporal analysis of the earliest year, the risk was observed to be steadily decreasing (p-value=0.016). In the spatial-temporal analysis, the risk was stably higher in Chiang Rai and Nan provinces compared to Chiang Mai province. According to the display movement over time, the odds of developing cervical cancer declined in all provinces. Conclusions: The risk of cervical cancer has decreased over time but, in some areas, there is a higher risk than in the major province of Chiang Mai. Therefore, we should promote cervical cancer screening coverage in all areas, especially where access is difficult and/or to women of lower socioeconomic status.

Frequency Ratio와 Evidential Belief Function을 활용한 산사태 유발에 대한 환경지리적 민감성 분석과 검증 - 2013년 춘천 산사태를 중심으로 - (Analysis and Validation of Geo-environmental Susceptibility for Landslide Occurrences Using Frequency Ratio and Evidential Belief Function - A Case for Landslides in Chuncheon in 2013 -)

  • 이원영;성효현;안세진;박선기
    • 한국지형학회지
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    • 제27권1호
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    • pp.61-89
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    • 2020
  • The objective of this study is to characterize landslide susceptibility depending on various geo-environmental variables as well as to compare the Frequency Ratio (FR) and Evidential Belief Function (EBF) methods for landslide susceptibility analysis of rainfall-induced landslides. In 2013, a total of 259 landslides occurred in Chuncheon, Gangwon Province, South Korea, due to heavy rainfall events with a total cumulative rainfall of 296~721mm in 106~231 hours duration. Landslides data were mapped with better accuracy using the geographic information system (ArcGIS 10.6 version) based on the historic landslide records in Chuncheon from the National Disaster Management System (NDMS), the 2013 landslide investigation report, orthographic images, and aerial photographs. Then the landslides were randomly split into a testing dataset (70%; 181 landslides) and validation dataset (30%; 78 landslides). First, geo-environmental variables were analyzed by using FR and EBF functions for the full data. The most significant factors related to landslides were altitude (100~200m), slope (15~25°), concave plan curvature, high SPI, young timber age, loose timber density, small timber diameter, artificial forests, coniferous forests, soil depth (50~100cm), very well-drained area, sandy loam soil and so on. Second, the landslide susceptibility index was calculated by using selected geo-environmental variables. The model fit and prediction performance were evaluated using the Receiver Operating Characteristic (ROC) curve and the Area Under Curve (AUC) methods. The AUC values of both model fit and prediction performance were 80.5% and 76.3% for FR and 76.6% and 74.9% for EBF respectively. However, the landslide susceptibility index, with classes of 'very high' and 'high', was detected by 73.1% of landslides in the EBF model rather than the FR model (66.7%). Therefore, the EBF can be a promising method for spatial prediction of landslide occurrence, while the FR is still a powerful method for the landslide susceptibility mapping.