• 제목/요약/키워드: Kappa index

검색결과 157건 처리시간 0.03초

Old Corrugated Containers (OCC)로부터 인쇄·필기용지 제조 (Manufacture of Printing and Writing Papers from Old Corrugated Containers (OCC))

  • 이구;안병준;백기현
    • 공업화학
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    • 제10권3호
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    • pp.367-373
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    • 1999
  • OCC의 구성 특성을 조사하고 OCC로부터 elemental chlorine free (ECF)나 totally chlorine free (TCF) 표백을 통한 백색도 85% (ISO) 이상의 인쇄 및 필기용지를 제조하기 위한 연구가 수행되었다. American old corrugated containers (AOCC)는 Korean old corrugated containers (KOCC)보다 섬유길이가 길며, 주로 장섬유로 구성되어 있고 전자의 경우 약 80%가 unbleached kraft pulp (UKP)로 구성되어 있으나 후자는 20% 정도였다. 또한 KOCC의 경우 회분함량 (9.7%)과 NaOH 추출물 (19.3%)이 AOCC보다 현저히 높았다. AOCC로부터 ECF 표백이 가능한 펄프 (kappa no. 25이하, 수율 70%)를 생산하기 위한 증해조건은 활성알칼리 20%, 황화도 25%, Anthraquinone (AQ) 0.1%, 펄핑온도 $170^{\circ}C$, 증해시간 90분이다 (kappa no. 22.6, 수율 68%). KOCC의 경우는 증해시간을 60분으로 단축시킬 수 있었다. (kappa no. 16.4, 수율 66%) 증해된 AOCC 펄프를 TCF나 ECF 표백단계를 거치면 백색도 85% (ISO) 이상의 펄프를 생산할 수 있었다. 그러나 KOCC 펄프는 TCF 표백으로서 목표 백색도를 달성할 수 없었다. 표백 KOCC 펄프는 표백 AOCC 펄프에 비하여 연장지수가 낮으나 파열지수와 인열지수는 오히려 높은 경향을 나타내었다.

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Dextran Sodium Sulfate 유발 장염 모델에서 루테올린의 치료효과 (Effect of the Flavonoid Luteolin for Dextran Sodium Sulfate-induced Colitis in NF-${\kappa}B^{EGFP}$ Transgenic Mice)

  • 장병익
    • Journal of Yeungnam Medical Science
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    • 제23권1호
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    • pp.26-35
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    • 2006
  • 전염증성 사이토카인의 분비를 조절하는 전사인자인 NF-${\kappa}B$는 염증성 장질환 환자의 대장 점막에서 발현이 증가되어 있다고 보고하고 있으며 이를 억제하여 대장의 염증을 억제하려는 연구가 진행 중이다. 루테올린은 다양한 한약제에 포함되어 있는 플라보노이드 중 하나로 항염증 및 항산화작용이 있다고 알려져 있으며 LPS 자극된 대식세포에서 TNF-${\alpha}$ 분비의 억제 뿐만 아니라 전사인자인 NF-kB의 발현을 억제하여 항염증작용을 하는 것으로 알려져 있다. 본 연구에서는 DSS을 이용한 염증성 장질환 모델에서 루테올린의 장염의 치료효과를 보고자 하였다. C57BL/6 NF-${\kappa}B^{EGFP}$ 쥐에게 2.5% DSS를 투여하여 장염을 유발하였으며 치료군(n=6)에서는 매일 루테올린(1 mg/kg, vol 0.1 ml)을 비위관을 통해 경구투여 하였으며, 비치료군(n=6)에서는 매일 같은 양의 vehicle(vol 0.1 ml)를 투여하여 정상대조군(n=6)과 비교하였다. 실험 기간 동안 질병활성도를 기록하였으며, 투약 6일 후 모든 쥐를 희생하여 대장을 분리하여 길이를 측정하고, 조직검사를 시행하였다. 또한 대장점막조직을 배양하여 m IL-12 p40의 분비를 측정하였고, 공초점 형광현미경하에서 EGFP 발현의 정도를 관찰하였다. 질병의 활성도의 관찰에서 치료군에서 2.7점, 비치료군에서 2.5점으로 양군 사이에 유의한 차이가 없어 루테올린에 대한 장염예방효과는 없었다. 또한 치료군과 비치료군에서 대장점막의 m IL-12 p40의 분비 각각 $535.2{\pm}198.2pg/ml$, $412.5{\pm}48.2pg/ml$ 로 양군 사이의 차이는 없었다. 흥미롭게도 EGFP 발현은 치료군에서 오히려 높게 나타났으며, 공초점 형광현미경관찰에서 대부분의 고유근층하 대식세포에서 증가되어 있음을 알 수 있었다. 이상의 결과로 루테올린의 경구 투여는 DSS 유발 염증성 장질환 모델에서 대장 점막 염증을 억제하는 대체 요법으로써의 치료효과는 관찰할 수 없었으며, 향후 항염증작용이 있다고 알려져있는 플라보노이드 물질의 개발에 신중함이 있어야 할 것으로 사료된다.

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Unveiling the mysteries of flood risk: A machine learning approach to understanding flood-influencing factors for accurate mapping

  • Roya Narimani;Shabbir Ahmed Osmani;Seunghyun Hwang;Changhyun Jun
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2023년도 학술발표회
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    • pp.164-164
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    • 2023
  • This study investigates the importance of flood-influencing factors on the accuracy of flood risk mapping using the integration of remote sensing-based and machine learning techniques. Here, the Extreme Gradient Boosting (XGBoost) and Random Forest (RF) algorithms integrated with GIS-based techniques were considered to develop and generate flood risk maps. For the study area of NAPA County in the United States, rainfall data from the 12 stations, Sentinel-1 SAR, and Sentinel-2 optical images were applied to extract 13 flood-influencing factors including altitude, aspect, slope, topographic wetness index, normalized difference vegetation index, stream power index, sediment transport index, land use/land cover, terrain roughness index, distance from the river, soil, rainfall, and geology. These 13 raster maps were used as input data for the XGBoost and RF algorithms for modeling flood-prone areas using ArcGIS, Python, and R. As results, it indicates that XGBoost showed better performance than RF in modeling flood-prone areas with an ROC of 97.45%, Kappa of 93.65%, and accuracy score of 96.83% compared to RF's 82.21%, 70.54%, and 88%, respectively. In conclusion, XGBoost is more efficient than RF for flood risk mapping and can be potentially utilized for flood mitigation strategies. It should be noted that all flood influencing factors had a positive effect, but altitude, slope, and rainfall were the most influential features in modeling flood risk maps using XGBoost.

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Classification of tree species using high-resolution QuickBird-2 satellite images in the valley of Ui-dong in Bukhansan National Park

  • Choi, Hye-Mi;Yang, Keum-Chul
    • Journal of Ecology and Environment
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    • 제35권2호
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    • pp.91-98
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    • 2012
  • This study was performed in order to suggest the possibility of tree species classification using high-resolution QuickBird-2 images spectral characteristics comparison(digital numbers [DNs]) of tree species, tree species classification, and accuracy verification. In October 2010, the tree species of three conifers and eight broad-leaved trees were examined in the areas studied. The spectral characteristics of each species were observed, and the study area was classified by image classification. The results were as follows: Panchromatic and multi-spectral band 4 was found to be useful for tree species classification. DNs values of conifers were lower than broad-leaved trees. Vegetation indices such as normalized difference vegetation index (NDVI), soil brightness index (SBI), green vegetation index (GVI) and Biband showed similar patterns to band 4 and panchromatic (PAN); Tukey's multiple comparison test was significant among tree species. However, tree species within the same genus, such as $Pinus$ $densiflora-P.$ $rigida$ and $Quercus$ $mongolica-Q.$ $serrata$, showed similar DNs patterns and, therefore, supervised classification results were difficult to distinguish within the same genus; Random selection of validation pixels showed an overall classification accuracy of 74.1% and Kappa coefficient was 70.6%. The classification accuracy of $Pterocarya$ $stenoptera$, 89.5%, was found to be the highest. The classification accuracy of broad-leaved trees was lower than expected, ranging from 47.9% to 88.9%. $P.$ $densiflora-P.$ $rigida$ and $Q.$ $mongolica-Q.$ $serrata$ were classified as the same species because they did not show significant differences in terms of spectral patterns.

Charlson Comorbidity Index를 활용한 폐암수술환자의 건강결과 예측에 관한 연구 (Health Outcome Prediction Using the Charlson Comorbidity Index In Lung Cancer Patients)

  • 김세원;윤석준;경민호;윤영호;김영애;김은정;김경운
    • 보건행정학회지
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    • 제19권4호
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    • pp.18-32
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    • 2009
  • The goal of this study was to predict the health outcomes of lung cancer surgery based on the Charlson comorbidity index (CCI). An attempt was likewise made to assess the prognostic value of such data for predicting mortality, survival rate, and length of hospital stay. A medical-record review of 389 patients with non-small-cell lung cancer was performed. To evaluate the agreement, the kappa coefficient was tested. Logistic-regression analysis was also conducted within two years after the surgery to determine the association of CCI with death. Survival and multiple-regression analyses were used to evaluate the relationship between CCI and the hospital care outcomes within two-year survival after lung cancer surgery and the length of hospital stay. The results of the study showed that CCI is a valid prognostic indicator of two-year mortality and length of hospital stay, and that it shows the health outcomes, such as death, survival rate, and length of hospital stay, after the surgery, thus enabling the development and application of the methodology using a systematic and objective scale for the results.

여대생의 신체만족도와 체중조절 (Body Satisfaction and Weight Loss in Women College Students)

  • 정승교;민소영
    • 기본간호학회지
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    • 제13권3호
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    • pp.485-492
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    • 2006
  • Purpose: The purpose of this study was to identify body satisfaction and weight loss experience according to individual's discrepancy between obesity by BMI (body mass index) and self-assessment. Method: The data were obtained by measuring height, weight and using a questionnaire to obtain data on self-assessment of obesity, body satisfaction and weight loss experience. The participants were 286 women college students in J city, Chungbuk. Results: The mean BMI of the women college student was $21.4{\pm}2.93kg/m^2$ which is within the normal range. The concordance rates between obesity by BMI and self-assessment were 54.1%, 39.9%, 61.5%, 78.6% (Kappa=.29) in underweight, normal, overweight, obese students respectively. Forty seven percent of students who were not obese (BMI $<23kg/m^2$) assessed themselves as obese. The mean body satisfaction of college students was very low and 64.3% of the students had a weight loss experience. The students who perceived themselves to be 'obese' even when their BMI was under $23kg/m^2$ reported lower body satisfaction and higher weight loss experience than other students. Conclusion: There were significant discrepancies between obesity by BMI and self-assessment in women college students. The self-assessment of obesity had a greater effect on body satisfaction and weight loss experience than actual BMI in women college students.

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개미산-과산화수소 펄핑에 의하여 생산된 백합나무 펄프의 화학적 및 역학적 특성 분석 (Chemical and Mechanical Properties of Yellow Poplar Pulp Produced by Formic Acid- Hydrogen Peroxide Pulping)

  • 심재훈;김정호;박종문;신수정
    • 펄프종이기술
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    • 제45권1호
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    • pp.6-12
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    • 2013
  • TFormic acid-hydrogen peroxide (or performic acid) pulping process needs milder reaction condition than other chemical pulping process. Two-step formic acid-hydrogen peroxide pulping process can produce the chemical pulp with similar pulp yield and lignin content compared with soda-anthraquinone process. Formic acid-hydrogen peroxide pulp can be produced less xylan content than other alkaline pulps, which favor for dissolving pulp production. Formic acid-hydrogen peroxide pulp showed better response beating than soda-anthraquinone(AQ) pulps with reaching target freeness with less beating. Also, formic acid-hydrogen peroxide pulp had better tensile index at similar freeness level compared with soda-AQ pulps.

FUZZY ERROR MATRIX IN CLSSIFICATION PROBLEMS

  • Kannan, S.R.;Ramathilagam, S.R.
    • Journal of applied mathematics & informatics
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    • 제26권5_6호
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    • pp.861-876
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    • 2008
  • This paper concerns a new method called Fuzzy Supervised Method for error matrix, the method has developed based on Adoptive Neuro- Fuzzy Inference Systems(ANFIS). For the performance point of view initially the new method tested with trial data and then this paper applies the proposed method with real world problems. So that this paper generated 1000 random error matrices in programming language [R] and then it tests the new proposed method for the error matrices. The results of Fuzzy Supervised Method given in terms of Kappa Index and Congalton Accuracy Indexes, and performance of Fuzzy Supervised Method has evaluated by using Pearson's test.

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A comparison of RPLA and PCR for detection of enterotoxins in methicillin-resistant Staphylococcus aureus(MRSA) strains isolated in dogs

  • Park, Son-il;Han, Hong-ryul
    • 대한수의학회지
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    • 제39권4호
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    • pp.806-810
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    • 1999
  • A multiplex-polymerase chain reaction (PCR) assay was used to detect staphylococcal enterotoxin production by 12 strains of Staphylococcus aureus isolated from clinical specimens. To evaluate the efficacy and/or sensitivity of this method, the results were compared to those obtained with the reversed passive latex agglutination kit (SET-RPLA, Denka Seiken, Japan). Of 10 strains positive by PCR were positive by RPLA but two strains, representing high sensitivity of the former method. Enterotoxin B was the most prevalent by the two methods. The kappa index between the two methods was 0.826, indicating a higher agreement and fully reliable for use. These results would suggest that sensitive, inexpensive, and relatively rapid multiplex-PCR technique may be an effective means for the detection of staphylococcal enterotoxin genes as an alternative to traditional methods such as kits or immunological methods, which depend upon the amount of enterotoxin produced.

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Image classification methods applicable multiple satellite imagery

  • Jeong, Jae-Jun;Kim, Kyung-Ok;Lee, Jong-Hun
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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    • pp.81-81
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    • 2002
  • Classification is considered as one of the processes of extracting attributes from satellite imagery and is one of the usual functions in the commercial satellite image processing software. Accuracy of classification plays a key role in deciding the usage of its results. Many tremendous efforts far the higher accuracy have been done in such fields; training area selection, classification algorithm. Our research is one of these effort in different manners. In this research, we conduct classification using multiple satellite image data and evidential approach. We statistically consider the posterior probabilities and certainty in maximum likelihood classification and methodologically Dempster's orthogonal sums. Unfortunately, accuracy for the whole data sets has not assessed yet, but accuracy assessments in training fields and check fields shows accuracy improvement over 10% in overall accuracy and over 0.1 in kappa index.

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