• Title/Summary/Keyword: 인자추출

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Study of machine learning model for predicting non-small cell lung cancer metastasis using image texture feature (Image texture feature를 이용하여 비소세포폐암 전이 예측 머신러닝 모델 연구)

  • Hye Min Ju;Sang-Keun Woo
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.07a
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    • pp.313-315
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    • 2023
  • 본 논문에서는 18F-FDG PET과 CT에서 추출한 영상인자를 이용하여 비소세포폐암의 전이를 예측하는 머신러닝 모델을 생성하였다. 18F-FDG는 종양의 포도당 대사 시 사용되며 이를 추적하여 환자의 암 세포를 진단하는데 사용되는 의료영상 기법 중 하나이다. PET과 CT 영상에서 추출한 이미지 특징은 종양의 생물학적 특성을 반영하며 해당 ROI로부터 계산되어 정량화된 값이다. 본 연구에서는 환자의 의료영상으로부터 image texture 프절 전이 예측에 있어 유의한 인자인지를 확인하기 위하여 AUC를 계산하고 단변량 분석을 진행하였다. PET과 CT에서 각각 4개(GLRLM_GLNU, SHAPE_Compacity only for 3D ROI, SHAPE_Volume_vx, SHAPE_Volume_mL)와 2개(NGLDM_Busyness, TLG_ml)의 image texture feature를 모델의 생성에 사용하였다. 생성된 각 모델의 성능을 평가하기 위해 accuracy와 AUC를 계산하였으며 그 결과 random forest(RF) 모델의 예측 정확도가 가장 높았다. 추출된 PET과 CT image texture feature를 함께 사용하여 모델을 훈련하였을 때가 각각 따로 사용하였을 때 보다 예측 성능이 개선됨을 확인하였다. 추출된 영상인자가 림프절 전이를 나타내는 바이오마커로서의 가능성을 확인할 수 있었으며 이러한 연구 결과를 바탕으로 개인별 의료 영상을 기반으로 한 비소세포폐암의 치료 전략을 수립할 수 있을 것이라 기대된다.

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Landslide Susceptibility Analysis : SVM Application of Spatial Databases Considering Clay Mineral Index Values Extracted from an ASTER Satellite Image (산사태 취약성 분석: ASTER 위성영상을 이용한 점토광물인자 추출 및 공간데이터베이스의 SVM 통계기법 적용)

  • Nam, Koung-Hoon;Lee, Moung-Jin;Jeong, Gyo-Cheol
    • The Journal of Engineering Geology
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    • v.26 no.1
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    • pp.23-32
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    • 2016
  • This study evaluates landslide susceptibility using statistical analysis by SVM (support vector machine) and the illite index of clay minerals extracted from ASTER(advanced spaceborne thermal emission and reflection radiometer) imagery which can be use to create mineralogical mapping. Landslide locations in the study area were identified from aerial photographs and field surveys. A GIS spatial database was compiled containing topographic maps (slope, aspect, curvature, distance to stream, and distance to road), maps of soil properties (thickness, material, topography, and drainage), maps of timber properties (diameter, age, and density), and an ASTER satellite imagery (illite index). The landslide susceptibility map was constructed through factor correlation using SVM to analyze the spatial database. Comparison of area under the curve values showed that using the illite index model provided landslide susceptibility maps that were 76.46% accurate, which compared favorably with 74.09% accuracy achieved without them.

Identification of the Negative Regulatory Element on the Caprine $\beta$ Lactoglobulin Promoter (염소의 베타-락토글로불린 유전자 프로모터의 음성 조절 인자 규명)

  • 김재만;유명희
    • The Korean Journal of Zoology
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    • v.38 no.3
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    • pp.433-441
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    • 1995
  • Mammary tissue-specificity of the caprine $\beta$-lactoglobulin promoter appears to be secured by repression in non-expressing cells. In order to identify the mechanism of the negative regulation, the upstream promoter sequence of the caprine $\beta$-lactoglobulin gene was analyzed in detail. The repression was mediated by the upstream flanking sequence from -47O to -205. The sequence could repress the promoter activity of $\beta$-lactoglobulin in either orientation. The effect of the putative negative regulation element of caprine $\beta$-lactoglobulin on heterlogous promoters, however, varied: the promoter activity of herpes simplex virus thimidine kinase was either repressed or activated by the sequence depending on its orientation, while the SV4O early promoter was activated rather than repressed. The regulatory sequence involving the putative negative regulatory element was strongly shifted with the nuclear extract from non-mammary HeLa and CV-1 cells, while only weak shift was observed with that of mammary HC11 cells. Such correlation between repression and factor binding suggests that the protected regions in foot-printing assay may be the negative regulatory elements of $\beta$-lactoalobulin that serve tissue-specific repression.

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Model development for the estimation of specific degradation using classification and prediction of data mining (데이터 마이닝의 분류 및 예측 기법을 적용한 비유사량 추정 모델 개발)

  • Jang, Eun-kyung;Kang, Woochul
    • Journal of Korea Water Resources Association
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    • v.53 no.3
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    • pp.215-223
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    • 2020
  • The objective of this study is to develop a prediction model of specific degradation using data mining classification especially for the rivers in South Korea river. A number of critical predictors such as erosion and sediment transport were extracted for the prediction model considering watershed morphometric characteristics, rainfall, land cover, land use, and bed material. The suggested model includes the elevations at the mid relative area of the hypsometric curve of watershed morphomeric characteristics, the urbanization ratio, and the wetland and water ratio of land cover factors as the condition factors. The proposed model describes well the measured specific degradation of the rivers in South Korea. In addition, the development model was compared with the existing models, since the existing models based on different conditions and purposes show low predictability, they have a limit about the application of Korean River. Therefore, this study is focusing on improving the applicability of the existing model

Regulatory Effects of Chrysanthemi Zawadskii Herba on NO Production and Vascular Adhesion Molecule Expression (구절초(Chrysanthemi Zawadskii Herba)의 항염증 인자 생성 및 혈관부착인자 발현 억제 효과)

  • Sohn, E.S.;Kim, S.H.;Ha, C.W.;Jang, S.;Sohn, E.H.;Chae, C.J.;Koo, H.J.
    • Journal of Practical Agriculture & Fisheries Research
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    • v.24 no.1
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    • pp.14-22
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    • 2022
  • The purpose of this study is to provide evidence for discovering functional materials through the anti-inflammatory efficacy screening of randomly selected medicinal herbs. We prepared 70% ethanol extracts from 10 herbs and evaluated for the inhibitory effect of NO production on LPS-stimulated mouse macrophage cell line Raw 264.7. As a result, it was confirmed that the Chrysanthemi Zawadskii Herba (CZ) extract had the highest effect of inhibiting NO production induced by LPS. We therefore measured and compared NO inhibitory effects at different concentrations (10, 50, 250 ㎍/mL) of 70% ethanol and water extract of CZ. It was observed that both ethanol and water treatment groups inhibited NO production in a concentration-dependent manner in both ethanol and water treatment groups. In particular, it was confirmed that the CZ 70% ethanol extract (99.97%) had a higher NO inhibitory effect than the water extract (93.32%) in the high concentration (250 ㎍/mL) treatment group. There was no effect of CZ extract on cell viability at all concentrations used in the experiment. Moreover, it was shown that CZ ethanol extract remarkably inhibited the expression of VCAM-1 induced by TNF-𝛼, and it was slightly decreased even by treatment with water extract. This study suggests that Chrysanthemi Zawadskii Herba has potential as a functional substance that regulates vascular inflammation.

Shadow Extraction of Urban Area using Building Edge Buffer in Quickbird Image (건물 에지 버퍼를 이용한 Quickbird 영상의 도심지 그림자 추출)

  • Yeom, Jun-Ho;Chang, An-Jin;Kim, Yong-Il
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.2
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    • pp.163-171
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    • 2012
  • High resolution satellite images have been used for building and road system analysis, landscape analysis, and ecological assessment for several years. However, in high resolution satellite images, shadows are necessarily cast by manmade objects such as buildings and over-pass bridges. This paper develops the shadow extraction procedures in urban area including various land-use classes, and the extracted shadow areas are evaluated by a manually digitized shadow map. For the shadow extraction, the Canny edge operator and the dilation filter are applied to make building edge buffer area. Also, the object-based segmentation was performed using Gram-Schmitt fusion image, and spectral and spatial parameters are calculated from the segmentation results. Finally, we proposed appropriate parameters and extraction rules for the shadow extraction. The accuracy of the shadow extraction results from the various assessment indices is 80% to 90%.

세포능식촉진인자(MPF)의 특이적 억제제 생산 토양균주의 검색 및 억제제의 분리와 특성 규명에 관한 연구

  • 박희동;박상곤;이승기
    • Proceedings of the Korean Society of Applied Pharmacology
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    • 1994.04a
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    • pp.258-258
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    • 1994
  • 본 연구에서는 토양균이 생성하는 2차 대사산물로부터 세포증식 촉진인자 (Maturation Promoting Factor. MPF)인 cdc2/cdk2-cyclin의 복합체를 특이적으로 억제하는 물질을 분리하고 그 물질의 생리활성을 조사하였다. 토양으로부터 순수분리된 300여개의 토양균에서 생성된 배양액을 취하여 MPF의 특이적인 기질인 합성 peptide (CSH103 :HATPPKKKRK)를 사용하여 인산화 활성을 측정하였다. 그중 MPF 활성 억제능이 90% 이상인 19개의 균주를 1차적으로 선정한 후 각각에 대하여 열/pH에 대한 안정성, 각종 용매에 대한 추출성 등 이화학적 성질을 규명하였으며 이중 균주 LPL 931로부터 MPF 활성 억제제를 분리하고자 하였다. 예비실험의 결과로부터 토양균 LPL 931을 대량배양하여 열처리하고, 비이온성 수지인Amberlite XAD-2에 결합시키고 70% acetone으로 용출시켰다. 이 추출물로부터 ethylacetate와 n-butanol을 사용하여 MPF 억제 활성물질을 추출하였다. 이 추출액을 실리카겔 관 크로마토그래피, 분취 TLC, 분취 HPL를 하여 MPF 활성 억제 분획을 분리하였다.

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An Empirical Validation of Complexity Metrics for Java Programs (Java 프로그램에 대한 복잡도 척도들의 실험적 검증)

  • Kim, Jae-Woong;Yu, Cheol-Jung;Jang, Ok-Bae
    • Journal of KIISE:Software and Applications
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    • v.27 no.12
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    • pp.1141-1154
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    • 2000
  • 본 논문에서는 Java 프로그램의 복잡도를 측정하기 위해 필요한 인자들을 제안하였다. 이러한 인자들을 추출하기 위해 Java 프로그램을 분석하여 객체지향 설계 척도 값들을 계산하고 통계적 분석을 수행하였다. 그 결과 기존의 연구에서 발견되었던 클래스의 크기 인자 외에도 메소드 호출 빈도, 응집도, 자식 클래스의 수, 내부 클래스 및 상속 계층의 깊이가 주요 인자임이 파악되었다. 클래스의 크기 척도로 분류되었던 자식 클래스의 수는 다른 크기 척도들과 다른 성질을 가진다는 것을 발견하였다. 또한 프로그램의 크기가 커지고 결합도가 높아질수록 응집도가 떨어진다는 것을 입증하였다. 그리고 인자 분석을 바탕으로 인간의 인지 능력과 인자의 상관관계를 고려한 가중치를 적용하기 위해 인자별로 회귀분석을 수행하였다. 보다 적은 척도를 가지고 인자를 설명할 수 있는 회귀식을 도출하였다. 두 그룹에 대한 교차 검증 결과 회귀식이 높은 신뢰도를 가지는 것으로 나타났다. 따라서 본 논문에서 제안한 인자들을 이용하는 경우 Java 프로그램의 복잡도를 측정할 수 있는 새로운 척도로 사용할 수 있다.

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Identifying Compound Risk Factors of Disease by Evolutionary Learning of SNP Combinatorial Features (SNP 조합 인자들의 진화적 학습 방법 기반 질병 관련 복합적 위험 요인 추출)

  • Rhee, Je-Keun;Ha, Jung-Woo;Bae, Seol-Hui;Kim, Soo-Jin;Lee, Min-Su;Park, Keun-Joon;Zhang, Byoung-Tak
    • Journal of KIISE:Computing Practices and Letters
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    • v.15 no.12
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    • pp.928-932
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    • 2009
  • Most diseases are caused by complex processes of various factors. Although previous researches have tried to identify the causes of the disease, there are still lots of limitations to clarify the complex factors. Here, we present a disease classification model based on an evolutionary learning approach of combinatorial features using the data sets from the genetics and cohort studies. We implemented a system for finding the combinatorial risk factors and visualizing the results. Our results show that the proposed method not only improves classification accuracy but also identifies biologically meaningful sets of risk factors.

A Study on Evaluation Structure of luminous Environment in o residential space and office work space (주거.사무공간의 조명환경 평가구조에 관한 연구)

  • 이선영
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.17 no.2
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    • pp.1-9
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    • 2003
  • This paper is to find the difference of evaluation structure between a residential space and of ace work space and to examine a relation between mood item and behavior items on evaluation of the luminous environment. First 20 mood items md 15 behavior items were selected for evaluation item on the luminous environment. And then, subjective evaluation was experimented by the semantic differential method. The results are as follows: (1) In respect of evaluation un the mood both luminous environments that have each different character of space at evaluated by the three factors; activity, comfort and quality. (2) In respect of evaluation on the behavior, three factors, work, relaxation and entertainment are selected in the residential space and two factors, work and non-work are selected in the office work space. (3) In the residential space, activity is very important factor that affects on three behaviors, work, relaxation and entertainment. In the office work space, activity affects on work and quality affects on non-work.