• 제목/요약/키워드: discrimination accuracy

검색결과 253건 처리시간 0.042초

Discrimination of rival isotherm equations for aqueous contaminant removal systems

  • Chu, Khim Hoong
    • Advances in environmental research
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    • 제3권2호
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    • pp.131-149
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    • 2014
  • Two different model selection indices, the Akaike information criterion (AIC) and the coefficient of determination ($R^2$), are used to discriminate competing isotherm equations for aqueous pollutant removal systems. The former takes into account model accuracy and complexity while the latter considers model accuracy only. The five types of isotherm shape in the Brunauer-Deming-Deming-Teller (BDDT) classification are considered. Sorption equilibrium data taken from the literature were correlated using isotherm equations with fitting parameters ranging from two to five. For the isotherm shapes of types I (favorable) and III (unfavorable), the AIC favors two-parameter equations which can easily track these simple isotherm shapes with high accuracy. The $R^2$ indicator by contrast recommends isotherm equations with more than two parameters which can provide marginally better fits than two-parameter equations. To correlate the more intricate shapes of types II (multilayer), IV (two-plateau) and V (S-shaped) isotherms, both indices favor isotherm equations with more than two parameters.

화상환자에서 사망예측모델의 성능 평가에 관한 연구 (The Accuracy of Prediction Models in Burn Patients)

  • 우재연;김도헌
    • 대한화상학회지
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    • 제24권1호
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    • pp.1-6
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    • 2021
  • Purpose: The purpose of this study was to evaluate the accuracy of four prediction models in adult burn patients. Methods: This retrospective study was conducted on 696 adult burn patients who were treated at burn intensive care unit (BICU) of Hallym University Hangang Sacred Heart Hospital from January 2017 to December 2019. The models are ABSI, APACHE IV, rBaux and Hangang score. Results: The discrimination of each prediction model was analyzed as AUC of ROC curve. AUC value was the highest with Hangang score of 0.931 (0.908~0.954), followed by rBaux 0.896 (0.867~0.924), ABSI 0.883 (0.853~0.913) and APACHE IV 0.851 (0.818~0.884). Conclusion: The results of evaluating the accuracy of the four models, Hangang score showed the highest prediction. But it is necessary to apply the appropriate prediction model according to characteristics of the burn center.

Characteristic of back fat and quality of longissimus dorsi muscle from soft fat pork carcasses

  • Lim, Daewoon;Song, Minho;Lee, Juri;Lee, Chulwoo;Lee, Jaechung;Lee, Wangyeol;Seo, Jihee;Jung, Samooel
    • 농업과학연구
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    • 제43권4호
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    • pp.581-588
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    • 2016
  • The objective of this study was to investigate the accuracy of visual discrimination of soft fat pork carcasses when subjecting carcasses to quality grade evaluations. In addition, the quality of the longissimus dorsi muscle from soft fat carcasses was investigated. Iodine values of back fat from soft fat carcasses evaluated by visual discrimination were significantly higher than those from firm fat carcass (p < 0.05). However, those values were lower than the standard for soft fat (iodine value = 70). There were no significant differences in linoleic acid content, b-values, and L-values (p < 0.05) of back fat between firm and soft fat carcasses evaluated by visual discrimination. Color of longissimus dorsi muscle from soft fat carcasses (iodine value higher than 70) was not different from that of firm fat carcass (iodine value lower than 70). Except for linoleic acid, there were no significant differences in any fatty acid contents between longissimus dorsi muscles from firm fat and soft fat carcasses. Monounsaturated fatty acid content of longissimus dorsi muscles from soft fat carcasses was significantly lower than those of firm fat carcass (p < 0.05). However polyunsaturated fatty acid content was significantly higher (p < 0.05) in longissimus dorsi muscles from soft fat carcasses. In conclusion, visual discrimination results for soft fat pork carcass were inaccurate. Therefore, other indicators should be required to evaluate soft fat pork carcasses. In contrast, the quality of longissimus dorsi muscle from soft fat carcasses was superior in terms of fatty acid composition compared with that of firm fat carcasses.

근적외선분광법을 이용한 수수×수단그라스 교잡종 종자의 품종 판별 (Variey Discrimination of Sorghum-Sudangrass Hybrids Seed Using near Infrared Spectroscopy)

  • 이기원;송요욱;김지혜;라하만 아티쿨;오미래;박형수
    • 한국초지조사료학회지
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    • 제40권4호
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    • pp.259-264
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    • 2020
  • 본 연구는 근적외선분광법을 이용하여 국내에서 재배중인 수수×수단그라스 교잡종 품 판별 가능성을 검토하고자 수행되었다. 근적외선분광기를 이용하여 수수×수단그라스 교잡종 종자를 가시파장 대역대 (680 - 1,099 nm), NIRS 파장 대역대 (1,100 - 2,500 nm) 및 NIRS 전체 파장 대역대 (680 - 2,500 nm)로 구분하여 스펙트라를 얻은 후 1차 미분과 8 nm gap으로 수 처리를 수행하였으며 부분최소자승 (PLS) 회귀분석법을 통해 품종판별 검량식을 개발하고 판별 정확성을 검증하였다. 수수×수단그라스 교잡종품종 판별의 정확성은 NIR파장대역에서 SECV 8.44 그리고 R2CV 0.89로 가장 판별 정확성이 낮았으며 NIRS 전체 파장대역에서 SECV 7.88 그리고 R2CV 0.90로 가장 높은 판별 정확성을 나타내었다. 파장대역별 예측 정확성은 NIR 파장대역 (1,100 - 2,500 nm)이 가장 우수하였으며, 교차검증오차 (SECV) 8.44에서 예측오차 (SEP) 12.03로 높아졌으며 가시영역대 (680 - 1,099)는 SECV 8.23에서 SEP 12.51로 높아졌다. Discrimination equation 분석법에 의한 NIRS 전체 파장대역별 수수×수단그라스 교잡종 종자의 판별 결과는 품종간에 판별 정확성의 차이가 크게 나타났으며 1, 2, 4 그리고 8번 품종 (G-7, BMR Gold II, Honey chew and SX-17)에서는 100 %의 정확성으로 가장 높게 나타났다. 따라서 NIRS를 이용한 수수×수단그라스 교잡종 종자의 판별분석이 가능할 것으로 판단되었다.

다수 분류기를 이용한 메타레벨 데이터마이닝 (Metalevel Data Mining through Multiple Classifier Fusion)

  • 김형관;신성우
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 1999년도 가을 학술발표논문집 Vol.26 No.2 (2)
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    • pp.551-553
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    • 1999
  • This paper explores the utility of a new classifier fusion approach to discrimination. Multiple classifier fusion, a popular approach in the field of pattern recognition, uses estimates of each individual classifier's local accuracy on training data sets. In this paper we investigate the effectiveness of fusion methods compared to individual algorithms, including the artificial neural network and k-nearest neighbor techniques. Moreover, we propose an efficient meta-classifier architecture based on an approximation of the posterior Bayes probabilities for learning the oracle.

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수화자(受話者) 구별을 위한 PAMD 구현 (Implement PAMD for discriminate human and ARS)

  • 서봉수
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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    • pp.61-64
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    • 2003
  • In this paper, we implement PAMD(Positive Answering Machine Detection) for discrimination human and ARS. We are used Grunt detection, Glitch Noise detection and Tone detection for PAMD. It distinguishes voice signals from ring-back tone and glitch noise respectively. And as a second step, it judges whether human responses or ARS responses after integrating pattern changes like initial response period, the number of voice data, each time of voice data period and glitch noise. The accuracy is about 9375 in ASR and about 98% in Mobile phone.

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실시간 지진 P파 검출 알고리즘 (Autopicking algorithm of P wave by real-time)

  • 류용규;김명수
    • 한국지진공학회:학술대회논문집
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    • 한국지진공학회 2005년도 학술발표회 논문집
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    • pp.62-67
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    • 2005
  • A new picking algorithm has been developed on real-time basis for finding the onset of P wave as well as discriminating the micro seismic signal from artificial noise. Unlike the previous methods which have used the STA/LTA ratio for discriminating the P arrivals, we have adopted the slope discrimination methods for identifying the P onset. As result, this algorithm has been turned out to be efficient in both accuracy and computation in on-line system.

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정규혼합에서 분류정확도 측도들의 최적기준 (Optimal Criterion of Classification Accuracy Measures for Normal Mixture)

  • 유현상;홍종선
    • Communications for Statistical Applications and Methods
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    • 제18권3호
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    • pp.343-355
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    • 2011
  • 두 분포함수의 혼합모형을 가정한 자료에서 적절한 분류점을 찾고 평가하는 것은 중요한 문제이다. 분류정확도 측도로 많이 사용하는 아홉 종류의 MVD, Youden지수, (0,1)까지 최단기준, 수정된(0,1)까지 최단 기준, SSS, 대칭점, 정확도면적, TA, TR에 대하여 설명하고, 이 측도들의 관계를 발견하면서 정확도 측도들의 조건을 몇 개의 범주로 군집화한다. 정규혼합분포를 가정하여 군집된 측도들에 기반하는 분류점들을 구하고, 그 분류점에 대응하는 제I종 오류율과 제II종 오류율 그리고 두 종류의 오류율합을 구하여 크기를 비교하고 토론하다. 추정된 혼합분포에 대하여 어떤 분류 정확도 측도의 제I종과 II종 오류율 또는 오류율합이 최소인지를 탐색할 수 있으며 자주 인용하는 정확도 측도의 장점과 단점을 파악할 수 있다.

Identification of Transformed Image Using the Composition of Features

  • Yang, Won-Keun;Cho, A-Young;Cho, Ik-Hwan;Oh, Weon-Geun;Jeong, Dong-Seok
    • 한국멀티미디어학회논문지
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    • 제11권6호
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    • pp.764-776
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    • 2008
  • Image identification is the process of checking whether the query image is the transformed version of the specific original image or not. In this paper, image identification method based on feature composition is proposed. Used features include color distance, texture information and average pixel intensity. We extract color characteristics using color distance and texture information by Modified Generalized Symmetry Transform as well as average intensity of each pixel as features. Individual feature is quantized adaptively to be used as bins of histogram. The histogram is normalized according to data type and it is used as the signature in comparing the query image with database images. In matching part, Manhattan distance is used for measuring distance between two signatures. To evaluate the performance of the proposed method, independent test and accuracy test are achieved. In independent test, 60,433 images are used to evaluate the ability of discrimination between different images. And 4,002 original images and its 29 transformed versions are used in accuracy test, which evaluate the ability that the proposed algorithm can find the original image correctly when some transforms was applied in original image. Experiment results show that the proposed identification method has good performance in accuracy test. And the proposed method is very useful in real environment because of its high accuracy and fast matching capacity.

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QSCC II+의 진단정확률 향상을 위한 환자군 연구 (Patient Group Study to Improve the Accuracy of QSCC II+)

  • 강민수;오지원;이혜리;이준희
    • 사상체질의학회지
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    • 제31권3호
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    • pp.48-65
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    • 2019
  • Background Several attempts have been made to accurately diagnose the Sasnag Constitution. One of these attempts is to use a questionnaire. Questionnaire for the Sasang Constitution Classification(QSCC) has been revised several times and now used as QSCC II+. This study was designed to improve the accuracy of the revised Questionnaire for the Sasang Constitution Classification(QSCC II+). Method 1,054 people were gathered for this study and analyzed to check discrimination ability of current discriminant function of QSCC II+. They were outpatients who visited the hospital and the constitution was confirmed by the specialist of Sasang Constitutional Medicine. Results Accuracy of QSCC II+ at Soeumin was improved from 74.9% to 79.3%, and there were no significant difference at Soyangin and Taeumin. Conclusion New discriminant function was constructed through discriminant analysis. And the accuracy of QSCC II+ was generally improved, especially in Soeumin.