• Advances in environmental research
• /
• v.3 no.2
• /
• pp.131-149
• /
• 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.

• Journal of the Korean Burn Society
• /
• v.24 no.1
• /
• pp.1-6
• /
• 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.

• Korean Journal of Agricultural Science
• /
• v.43 no.4
• /
• pp.581-588
• /
• 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.

• Journal of The Korean Society of Grassland and Forage Science
• /
• v.40 no.4
• /
• pp.259-264
• /
• 2020

The aim of this study was to investigate the feasibility of discrimination 12 different cultivar of sorghum × sudangrass hybrid (Sorghum genus) seed through near infrared spectroscopy (NIRS). The amount of samples for develop to the best discriminant equation was 360. Whole samples were applied different three spectra range (visible, NIR and full range) within 680-2500 nm wavelength and the spectrastar 2500 Near near infrared was used to measure spectra. The calibration equation for discriminant analysis was developed partial least square (PLS) regression and discrimination equation (DE) analysis. The PLS discriminant analysis model for three spectra range developed with mathematic pretreatment 1,8,8,1 successfully discriminated 12 different sorghum genus. External validation indicated that all samples were discriminated correctly. The whole discriminant accuracy shown 82 ~ 100 % in NIR full range spectra. The results demonstrated the usefulness of NIRS combined with chemometrics as a rapid method for discrimination of sorghum × sudangrass hybrid cultivar through seed.

• Proceedings of the Korean Information Science Society Conference
• /
• 1999.10b
• /
• pp.551-553
• /
• 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.

• Proceedings of the IEEK Conference
• /
• 2003.11a
• /
• pp.61-64
• /
• 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.

• Proceedings of the Earthquake Engineering Society of Korea Conference
• /
• 2005.03a
• /
• pp.62-67
• /
• 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.

• Communications for Statistical Applications and Methods
• /
• v.18 no.3
• /
• pp.343-355
• /
• 2011

For a data with the assumption of the mixture distribution, it is important to find an appropriate threshold and evaluate its performance. The relationship is found of well-known nine classification accuracy measures such as MVD, Youden's index, the closest-to-(0, 1) criterion, the amended closest-to-(0, 1) criterion, SSS, symmetry point, accuracy area, TA, TR. Then some conditions of these measures are categorized into seven groups. Under the normal mixture assumption, we calculate thresholds based on these measures and obtain the corresponding type I and II errors. We could explore that which classification measure has minimum type I and II errors for estimated mixture distribution to understand the strength and weakness of these classification measures.

• Journal of Korea Multimedia Society
• /
• v.11 no.6
• /
• pp.764-776
• /
• 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.

• Journal of Sasang Constitutional Medicine
• /
• v.31 no.3
• /
• pp.48-65
• /
• 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.