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( Honggeun Kim ),( Kwanho Park ),( Seokhyun Lee ),( Kyuwon Kwak ),( Munsuk Choi ),( Jiyoung Choi ) 한국잠사학회 2015 International Journal of Industrial Entomology Vol.31 No.1
The white-spotted chafer, Protaetia brevitarsis (Coleoptera: Scarabaeidae), has been traditionally used in Korea as a medicine for preventing liver-related diseases and suppressing liver cancer. Therefore, this insect is economically important and is commercially reared and sold in Korea. Recently, P. brevitarsis was listed as a temporal food ingredient by the Korean Ministry of Food and Drug Safety. Given the increasing economic importance of this beetle, we have sought to improve rearing conditions for its commercial production. In this study, we compared the effects of two food supplements, clay and charcoal, on the growth of second instar larvae of P. brevitarsis . Clay and charcoal are generally known as good adsorbent for removal of contaminating substances in insect feed. We fed second instar P. brevitarsis larvae a commercial diet consisting of fermented sawdust with seven different combinations of clay and/or activated charcoal, and measured their effects on weight gain for approximately 17 wk until larvae pupated. We found that addition of clay at 2.5% w/w of the fermented sawdust diet had no negative effect on weight gain of second instar P. brevitarsis larvae and thus may improve the quality of P. brevitarsis as a commercial food.
동북아 전력계통 연계를 통한 융통전력 도입 시 가격상한 수준에 대한 분석
金洪槿(Kim Honggeun),鄭求亨(Chung Koohyung),金發鎬(Kim Balho) 대한전기학회 2006 전기학회논문지A Vol.55 No.3
Interstate electric power system, as an alternative for energy cooperation under regional economic bloc, has been hotly debated before progressing the restructure in electric power industry and rapidly expanded in many regions after 1990s. Especially, since northeast asia has strong supplementation in resource, load shape, fuel mix etc., electric power system interconnection in this region may bring considerable economic benefits. Moreover, since Korean electric power system has a great difficulty in a geographical condition to interrupt electricity transaction with other countries, it has been expanded as an independent system to supply all demand domestically. As a result, Korean electric power system makes considerable payment for maintaining system security and reliability and expands costly facilities to supply a temporary summer peak demand. Under this inefficiency, if there are electricity transactions with Russia via the North Korea route then economic electric power system operation may be achieved using seasonal and hourly differences in electricity price and/or load pattern among these countries. In this paper, we estimate price cap of transacted electricity via interstate electric power system in northeast asia. For this study, we perform quantitative economic analysis on various system interconnection scenarios.
아파트 하자 보수 시설공사 세부공종 머신러닝 분류 시스템에 관한 연구
김은혜 ( Eunhye Kim ),지홍근 ( HongGeun Ji ),김지나 ( Jina Kim ),박은일 ( Eunil Park ),엄재용 ( Jay Y. Ohm ) 한국정보처리학회 2021 정보처리학회논문지. 소프트웨어 및 데이터 공학 Vol.10 No.9
대한민국 건설사들은 아파트 하자 정보를 축적하고 보수작업을 관리하기 위한 시스템을 운영하는데 상당한 인력과 비용을 투자하고 있다. 본 연구에서는 하자 접수 상세내용 텍스트 데이터를 이용하여 하자 보수 시설공사에 따른 세부공종을 분류하는 머신러닝 모델을 제안한다. 두 가지 단어 임베딩(Bag-of-words, Term Frequency-Inverse Document Frequency (TF-IDF))과 두 가지 분류기(Support Vector Machine, Random Forest)를 통해 한국어로 작성된 65만건 이상의 하자 접수데이터로부터 하자보수 시설공사 세부공종을 분류했다. 특히, 이번 연구에서는 특정 시설공사(마감공사)의 9개 세부공종(가전제품, 도배공사, 도장공사, 미장공사, 석공사, 수장공사, 옥내가구공사, 주방기구공사, 타일공사)을 분류하는 이진 분류 모델과 다중 분류 모델을 연구했다. 그 결과, TF-IDF와 Random Forest를 사용한 두가지 분류 모델에서 90%이상의 정확도, 정밀도, 재현율 및 F1점수를 확인했다. A number of construction companies in Korea invest considerable human and financial resources to construct a system for managing apartment defect data and for categorizing repair tasks. Thus, this study proposes machine learning models to automatically classify defect complaint text-data into one of the sub categories of ‘finishing work’ (i.e., one of the defect repair tasks). In the proposed models, we employed two word representation methods (Bag-of-words, Term Frequency-Inverse Document Frequency (TF-IDF)) and two machine learning classifiers (Support Vector Machine, Random Forest). In particular, we conducted both binary- and multi- classification tasks to classify 9 sub categories of finishing work: home appliance installation work, paperwork, painting work, plastering work, interior masonry work, plaster finishing work, indoor furniture installation work, kitchen facility installation work, and tiling work. The machine learning classifiers using the TF-IDF representation method and Random Forest classification achieved more than 90% accuracy, precision, recall, and F1 score. We shed light on the possibility of constructing automated defect classification systems based on the proposed machine learning models.
점액성 위선암과 비점액성 위선암 및 위반지세포암종의 임상적 비교
안홍근 ( Honggeun Ahn ),정우철 ( Woo Chul Chung ),김연지 ( Yeon-ji Kim ),유성열 ( Seongyul Ryu ),임은선 ( Eunsun Lim ) 대한소화기학회 2020 대한소화기학회지 Vol.76 No.6
Background/Aims: This study examined the clinical features and prognosis of patients with mucinous gastric carcinoma (MGC), non-mucinous gastric carcinoma (NMGC), and signet ring cell gastric carcinoma (SRC). Methods: A retrospective cohort study was performed, enrolling 65 patients with MGC from January 2007 to December 2016. During the same period, 1,814 patients with histologically proven gastric cancers underwent curative or palliative operations. One hundred and ninety-five NMGC patients were selected as the 1:3 age- and sex-matched control groups. In addition, 200 SRC patients were identified. This study evaluated the demographic features of the patients, pathologic features of the tumor, and the predictive factors, such as the recurrence-free survival and overall survival. Results: The recurrence rates were significantly high in MGC than in NMGC or SRC (both p<0.01). The proportion of early gastric cancer was lower in the MGC group than in the other groups (p<0.01). In addition, metastatic lymph nodes were found more frequently in the MGC group (p<0.01), and the proportion of initial pT4, M1 stage, was highest in the MGC group. The recurrence- free survival and overall survival in the MGC group were significantly lower than those in the NMGC or SRC. Subgroup analysis showed that patients with the same American Joint Committee on Cancer (AJCC) stage of each cancer group showed a similar prognosis. Conclusions: MGC frequently presents an advanced stage with an unfavorable prognosis compared to NMGC or SRC. On the other hand, MGC of the same AJCC stage had a similar prognosis to NMGC and SRC. (Korean J Gastroenterol 2020;76:297-303)
Jung, Hyungsik,Jo, Honggeun,Kim, Sungil,Lee, Kyungbook,Choe, Jonggeun Elsevier 2017 Journal of petroleum science & engineering Vol.154 No.-
<P><B>Abstract</B></P> <P>Ensemble Kalman filter (EnKF) is one of the promising reservoir characterization schemes for history matching. It has been widely researched due to its excellence in recursive data processing and dependable uncertainty quantification. However, EnKF has critical limitations for applying to non-Gaussian distribution fields such as channel reservoirs.</P> <P>In this study, we propose a novel scheme to characterize channel reservoirs reliably. The scheme, recursive update of channel information (RUCI), updates key channel information such as facies ratio and permeabilities of each rock facies as components of the state vector. Since permeabilities assimilated by EnKF follow a Gaussian distribution, EnKF itself is not adequate to preserve channel structure. To overcome this limitation, we use cumulative distribution function mapping to maintain its bimodal distribution. In addition to RUCI, discrete cosine transform (DCT) is utilized to preserve clear channel continuities by figuring out essential channel trend.</P> <P>The proposed method, RUCI in EnKF with DCT, is applied to three different channel reservoir cases and is compared with typical three methods: EnKF, EnKF with DCT, and EnKF with normal score transform (NST). Both of conventional EnKF and EnKF with DCT show overshooting and fail to present channel details. Furthermore, their permeability distributions have a tendency to follow a Gaussian, not a typical bimodal distribution of sand and shale. Even if EnKF with NST maintains a bimodal distribution after updates, it cannot figure out overall channel trend. The proposed method not only prevents overshooting but also preserves a bimodal distribution of permeability. It can clearly characterize true channel trend even though initial reservoir models are poorly made. In addition, it gives better estimation of future oil and water productions than the other 3 methods by reducing uncertainties and matching true performances.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A novel scheme that updates channel information is suggested. </LI> <LI> The proposed method integrates the scheme and DCT to characterize channel reservoirs. </LI> <LI> It provides reliable characterization results by capturing true channel information and trends. </LI> </UL> </P>