• Title/Summary/Keyword: drawing coefficient

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A Graphical Method for Evaluation of Stages in Shrinkage Cracking Using S-shape Curve Model (S형 곡선 모델을 적용한 수축 균열 단계 평가)

  • Min, Tuk-Ki;Vo, Dai Nhat
    • Journal of the Korean Geotechnical Society
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    • v.24 no.9
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    • pp.41-48
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    • 2008
  • The aim of this study is to present a graphical method in order to evaluate stages in shrinkage cracking. Firstly, the distribution of crack openings is established by sorting the openings of individual cracks in the soil cracking system. Secondly, it is normalized in a range of 0 to 1 to obtain the normalized crack opening distribution. Thirdly, three S-shape curve models introduced by Brooks and Corey(1964), Fredlund and Xing(1994) and van Genuchten(1980) are chosen to fit the normalized crack opening distribution using a curve fitting method. The accuracy of fitting which is described through fitting parameters by the van Genuchten equation is much higher than that by the Brooks and Corey equation and slightly higher than that by the Fredlund and Xing equation; thus the van Genuchten model is used. Finally, the stages of shrinkage cracking are graphically evaluated by drawing three separate straight lines corresponding to three linear parts of the fitted normalized crack opening distribution. The proposed method is tested with different sample thicknesses. The measured data are fitted by the selected model with the fairly high regression coefficient and small root mean square error. The results show graphically that shrinkage cracking comprises three stages; namely, primary, secondary and residual stages. Subsequently, the ranges of evaluated crack opening for each of these stages are presented.

A Development of Torsional Analysis Model and Parametric Study for PSC Box Girder Bridge with Corrugated Steel Web (복부 파형강판을 사용한 PSC 복합 교량의 비틀림 해석모델의 제안 및 변수해석)

  • Lee, Han-Koo;Kim, Kwang-Soo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.2A
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    • pp.281-288
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    • 2008
  • The Prestressed Concrete (hereinafter PSC) box girder bridges with corrugated steel webs have been drawing an attention as a new structure type of PSC bridge fully utilizing the feature of concrete and steel. However, the previous study focused on the shear buckling of the corrugated steel web and development of connection between concrete flange and steel web. Therefore, it needs to perform a study on the torsional behavior and develop the rational torsional analysis model for PSC box girder with corrugated steel web. In this study, torsional analysis model is developed using Rausch's equation based on space truss model, equilibrium equation considering softening effect of reinforced concrete element and compatibility equation. Validation studies are performed on developed model through the comparison with the experimental results of loading test for PSC box girder with corrugated steel webs. Parametric studies are also performed to investigate the effect of prestressing force and concrete strength in torsional behavior of PSC box girder with corrugated steel web. The modified correction factor is also derived for the torsional coefficient of PSC box girder with corrugated steel web through the parametric study using the proposed anlaytical model.

Automated Measurement of Native T1 and Extracellular Volume Fraction in Cardiac Magnetic Resonance Imaging Using a Commercially Available Deep Learning Algorithm

  • Suyon Chang;Kyunghwa Han;Suji Lee;Young Joong Yang;Pan Ki Kim;Byoung Wook Choi;Young Joo Suh
    • Korean Journal of Radiology
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    • v.23 no.12
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    • pp.1251-1259
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    • 2022
  • Objective: T1 mapping provides valuable information regarding cardiomyopathies. Manual drawing is time consuming and prone to subjective errors. Therefore, this study aimed to test a DL algorithm for the automated measurement of native T1 and extracellular volume (ECV) fractions in cardiac magnetic resonance (CMR) imaging with a temporally separated dataset. Materials and Methods: CMR images obtained for 95 participants (mean age ± standard deviation, 54.5 ± 15.2 years), including 36 left ventricular hypertrophy (12 hypertrophic cardiomyopathy, 12 Fabry disease, and 12 amyloidosis), 32 dilated cardiomyopathy, and 27 healthy volunteers, were included. A commercial deep learning (DL) algorithm based on 2D U-net (Myomics-T1 software, version 1.0.0) was used for the automated analysis of T1 maps. Four radiologists, as study readers, performed manual analysis. The reference standard was the consensus result of the manual analysis by two additional expert readers. The segmentation performance of the DL algorithm and the correlation and agreement between the automated measurement and the reference standard were assessed. Interobserver agreement among the four radiologists was analyzed. Results: DL successfully segmented the myocardium in 99.3% of slices in the native T1 map and 89.8% of slices in the post-T1 map with Dice similarity coefficients of 0.86 ± 0.05 and 0.74 ± 0.17, respectively. Native T1 and ECV showed strong correlation and agreement between DL and the reference: for T1, r = 0.967 (95% confidence interval [CI], 0.951-0.978) and bias of 9.5 msec (95% limits of agreement [LOA], -23.6-42.6 msec); for ECV, r = 0.987 (95% CI, 0.980-0.991) and bias of 0.7% (95% LOA, -2.8%-4.2%) on per-subject basis. Agreements between DL and each of the four radiologists were excellent (intraclass correlation coefficient [ICC] of 0.98-0.99 for both native T1 and ECV), comparable to the pairwise agreement between the radiologists (ICC of 0.97-1.00 and 0.99-1.00 for native T1 and ECV, respectively). Conclusion: The DL algorithm allowed automated T1 and ECV measurements comparable to those of radiologists.

Analysis of the Effect of the Revised Ground Amplification Factor on the Macro Liquefaction Assessment Method (개정된 지반증폭계수의 Macro적 액상화 평가에 미치는 영향 분석)

  • Baek, Woo-Hyun;Choi, Jae-Soon
    • Journal of the Korean Geotechnical Society
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    • v.36 no.2
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    • pp.5-15
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    • 2020
  • The liquefaction phenomenon that occurred during the Pohang earthquake (ML=5.4) brought new awareness to the people about the risk of liquefaction caused by the earthquake. Liquefaction hazard maps with 2 km grid made in 2014 used more than 100,000 borehole data for the whole country, and regions without soil investigation data were produced using interpolation. In the mapping of macro liquefaction hazard for the whole country, the site amplification effect and the ground water level 0 m were considered. Recently, the Ministry of Public Administration and Security (2018) published a new site classification method and amplification coefficient of the common standard for seismic design. Therefore, it is necessary to rewrite the liquefaction hazard map reflecting the revised amplification coefficient. In this study, the results of site classification according to the average shear wave velocity in soils before and after revision were compared in the whole country. Also, liquefaction assessment results were compared in Gangseo-gu, Busan. At this time, two ground accelerations corresponding to the 500 and 1,000 years of return period and two ground water table, 5 m for the average condition and 0 m the extreme condition were applied. In the drawing of liquefaction hazard map, a 500 m grid was applied to secure a resolution higher than the previous 2 km grid. As a result, the ground conditions that were classified as SC and SD grounds based on the existing site classification standard were reclassified as S2, S3, and S4 through the revised site classification standard. Also, the result of the Liquefaction assessments with a return period of 500 years and 1,000 years resulted in a relatively overestimation of the LPI applied with the ground amplification factor before revision. And the results of this study have a great influence on the liquefaction assessment, which is the basis of the creation of the regional liquefaction hazard map using the amplification factor.

A Study on Decreasing Effects of Ultra-fine Particles (PM2.5) by Structures in a Roadside Buffer Green - A Buffer Green in Songpa-gu, Seoul - (도로변 완충녹지의 식재구조에 따른 초미세먼지(PM2.5)농도 저감효과 연구 - 서울 송파구 완충녹지를 대상으로 -)

  • Hwang, Kwang-Il;Han, Bong-Ho;Kwark, Jeong-In;Park, Seok-Cheol
    • Journal of the Korean Institute of Landscape Architecture
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    • v.46 no.4
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    • pp.61-75
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    • 2018
  • This study aims to verify the effect of green buffers, built as urban planning facilities on the reduction of ultra-fine particulate($PM_{2.5}$) and analyze changes in ultra-fine particles by structure, green volume and planting types of wayside green buffers, thus drawing the factors that can be used when green buffers are built to reduce ultra-fine particulate based on the results. This study selected Songpa-gu, and investigated 16 sites on 5 green buffers adjacent to two of Songpa-gu's main roads, 'Yangjaedaero' and 'Songpadaero'. This study divided all the green spaces into three different types-slope type, plain type and mounding type, and analyzed the mean green volume. As a result of measuring the concentration of $PM_{2.5}$, this study found that it was $55.5{\mu}g/m^3$ on average in winter, which was a harmful level according to the integrated environmental index provided by Seoul City, saying that levels above $50{\mu}g/m^3$ may have a harmful effect on sensitive groups of people. Particularly, the concentration of $PM_{2.5}$ was $38.6{\mu}g/m^3$ on average in spring, which exceeded the mean concentration of $PM_{2.5}$ in Seoul City in 2015. The mean concentrations of $PM_{2.5}$ in every investigation spot were $46.6{\mu}g/m^3$ for sidewalks, $45.5{\mu}g/m^3$ for green spaces and $42.9{\mu}g/m^3$ for residential areas, all of which were lower than $53.2{\mu}g/m^3$ for roads, regardless of the season. The concentration of $PM_{2.5}$ for residential areas was the lowest. In the stage of confirming the effect of green buffers, this study analyzed the correlation between the green volume of vegetation and the fluctuated rate of ultra-fine particles. As a result, it was found that the green coverage rate of trees and shrubs was related to the crown volume in every investigation spot but were mutually and complexly affected by each other. Therefore, this study judged that the greater the number of layers of shrubs that are made, the more effective it is in reducing the concentration of $PM_{2.5}$. As for seasonal characteristics, this study analyzed the correlation between the concentration of $PM_{2.5}$ for residential areas in winter and the green coverage rate of each green space type. As a result, this study found that there was a negative correlation showing that the higher the shrub green coverage rate is, the lower the concentration value becomes in all the slope-type, plain-type and mounding-type green spaces. This study confirmed that the number of tree rows and the number of shrub layers have negative correlations with the fluctuated concentration rate of $PM_{2.5}$. Especially, it was judged that the shrub green volume has greater effect than any other factor, and each green space type shows a negative correlation with the shrub coverage rate in winter.

A Study on Differences of Contents and Tones of Arguments among Newspapers Using Text Mining Analysis (텍스트 마이닝을 활용한 신문사에 따른 내용 및 논조 차이점 분석)

  • Kam, Miah;Song, Min
    • Journal of Intelligence and Information Systems
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    • v.18 no.3
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    • pp.53-77
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    • 2012
  • This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.