• Journal of Biomedical Engineering Research
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• v.31 no.3
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• pp.177-186
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• 2010

In 3D ultrasound color Doppler imaging (CDI), 8-16 pulse transmissions (ensembles) per each scanline are used for effective clutter rejection and flow estimation, but it yields a low volume acquisition rate. In this paper, we have evaluated three flow estimation methods: autoregression (AR), eigendecomposition (ED), and autocorrelation combined with adaptive clutter rejection (AC-ACR) for a small ensemble size (E=4). The performance of AR, ED and AC-ACR methods was compared using 2D and 3D in vivo data acquired under different clutter conditions (common carotid artery, kidney and liver). To evaluate the effectiveness of three methods, receiver operating characteristic (ROC) curves were generated. For 2D kidney in vivo data, the AC-ACR method outperforms the AR and ED methods in terms of the area under the ROC curve (AUC) (0.852 vs. 0.793 and 0.813, respectively). Similarly, the AC-ACR method shows higher AUC values for 2D liver in vivo data compared to the AR and ED methods (0.855 vs. 0.807 and 0.823, respectively). For the common carotid artery data, the AR provides higher AUC values, but it suffers from biased estimates. For 3D in vivo data acquired from a kidney transplant patient, the AC-ACR with E=4 provides an AUC value of 0.799. These in vivo experiment results indicate that the AC-ACR method can provide more robust flow estimates compared to the AR and ED methods with a small ensemble size.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.495-509
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• 2015

We study a classification problem of significant differences in the proportion of two groups known as the unbalanced classification problem. It is usually more difficult to classify classes accurately in unbalanced data than balanced data. Most observations are likely to be classified to the bigger group if we apply classification methods to the unbalanced data because it can minimize the misclassification loss. However, this smaller group is misclassified as the larger group problem that can cause a bigger loss in most real applications. We compare several classification methods for the unbalanced data using sampling techniques (up and down sampling). We also check the total loss of different classification methods when the asymmetric loss is applied to simulated and real data. We use the misclassification rate, G-mean, ROC and AUC (area under the curve) for the performance comparison.

• Journal of Korean Society of Water and Wastewater
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• v.34 no.4
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• pp.277-288
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• 2020

In this study, we performed algorithms to predict algae of Chlorophyll-a (Chl-a). Water quality and quantity data of the middle Nakdong River area were used. At first, the correlation analysis between Chl-a and water quality and quantity data was studied. We extracted ten factors of high importance for water quality and quantity data about the two weirs. Algorithms predicted how ten factors affected Chl-a occurrence. We performed algorithms about decision tree, random forest, elastic net, gradient boosting with Python. The root mean square error (RMSE) value was used to evaluate excellent algorithms. The gradient boosting showed 10.55 of RMSE value for the Gangjeonggoryeong (GG) site and 11.43 of RMSE value for the Dalsung (DS) site. The gradient boosting algorithm showed excellent results for GG and DS sites. Prediction value for the four algorithms was also evaluated through the Receiver operating characteristic (ROC) curve and Area under curve (AUC). As a result of the evaluation, the AUC value was 0.877 at GG site and the AUC value was 0.951 at DS site. So the algorithm's ability to interpret seemed to be excellent.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.1
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• pp.49-55
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• 2013

In this paper, we proposed a good classifier to match different spatial data sets by applying evaluation of classifiers performance in data mining and biometrics. For this, we calculated distances between a pair of candidate features for matching criteria, and normalized the distances by Min-Max method and Tanh (TH) method. We defined classifiers that shape similarity is derived from fusion of these similarities by CRiteria Importance Through Intercriteria correlation (CRITIC) method, Matcher Weighting method and Simple Sum (SS) method. As results of evaluation of classifiers performance by Precision-Recall (PR) curve and area under the PR curve (AUC-PR), we confirmed that value of AUC-PR in a classifier of TH normalization and SS method is 0.893 and the value is the highest. Therefore, to match different spatial data sets, we thought that it is appropriate to a classifier that distances of matching criteria are normalized by TH method and shape similarity is calculated by SS method.

• Journal of the Korean Society of Radiology
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• v.83 no.6
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• pp.1312-1326
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• 2022

Purpose To investigate the added value of right down decubitus (RDD) CT when determining adjacent organ invasion in cases of advanced gastric cancer (AGC). Materials and Methods A total of 728 patients with pathologically confirmed T4a (pT4a), surgically confirmed T4b (sT4b), or pathologically confirmed T4b (pT4b) AGCs who underwent dedicated stomach-protocol CT, including imaging of the left posterior oblique (LPO) and RDD positions, were included in this study. Two radiologists scored the T stage of AGCs using a 5-point scale on LPO CT with and without RDD CT at 2-week intervals and recorded the presence of "sliding sign" in the tumors and adjacent organs and compared its incidence of appearance. Results A total of 564 patients (77.4%) were diagnosed with pT4a, whereas 65 (8.9%) and 99 (13.6%) patients were diagnosed with pT4b and sT4b, respectively. When RDD CT was performed additionally, both reviewers deemed that the area under the curve (AUC) for differentiating T4b from T4a increased (p < 0.001). According to both reviewers, the AUC for differentiating T4b with pancreatic invasion from T4a increased in the subgroup analysis (p < 0.050). Interobserver agreement improved from fair to moderate (weighted kappa value, 0.296-0.444). Conclusion RDD CT provides additional value compared to LPO CT images alone for determining adjacent organ invasion in patients with AGC due to their increased AUC values and improved interobserver agreement.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.29-35
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• 2019

As the fourth industrial revolution is emerging, many companies are increasingly interested in smart factories and the importance of sensors is being emphasized. In the case that sensors for collecting sensing data fail, the plant could not be optimized and further it could not be operated properly, which may incur a financial loss. For this purpose, it is necessary to diagnose the status of sensors to prevent sensor' fault. In the paper, we propose a scheme to diagnose digital-sensor' fault by analyzing the rising time and falling time of digital sensors through the LSTM(Long Short Term Memory) of Deep Learning RNN algorithm. Experimental results of the proposed scheme are compared with those of rule-based fault diagnosis algorithm in terms of AUC(Area Under the Curve) of accuracy and ROC(Receiver Operating Characteristic) curve. Experimental results show that the proposed system has better and more stable performance than the rule-based fault diagnosis algorithm.

• Archives of Pharmacal Research
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• v.13 no.2
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• pp.180-186
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• 1990

A bioequivalence study of ranitidine tablets was conducted according to the Korean Guidine for the Bioequivalence Test using twelve healthy male subjects. The plasma concentration-timecurves of ranitidine from the test and reference tablets showed profound multiple peak phenomenon in each subject as reported earlier. However, the area under the plasma concentration-time curve (AUC) and the maximum ploasma concentration at the first peak ($C_{max1}$) of the two preparations was proven to be equal when analyzed satistically according to the criteria of the guidline;i. e., statistical power (1-$\beta$)was calculated to be over 0.8 under the condition of $\alpha$ = 5% and $\Delta$(minimum detectable difference) = 20%, and the confidence interval of the difference in AUC at 95% confidence level was in the range of $\pm$ 20%, which statisfied the criteria of bioequivalence. Equivalence of the peak concentration of ranitidine at the second peak ($C_{max2}$), and the time to reach the first ($T_{max1}$) and second verify the bioequivalence of $c_{max2}$ , $T_{max1}$ and $T_{max2}$ between the two tablets. However, we conclude that the test and reference tablets are bioequivalent taking the therapeutic characteristics of the ranitidine preparations into consideration.

• Biomolecules & Therapeutics
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• v.8 no.3
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• pp.262-268
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• 2000

The bioequivalence of two tiropramide products was evaluated in 18 health male volunteers following oral administration. Test product was Tira $m^{R}$ tablet (Shin Poong SP-102) (Shin Poong Pharm. Co., Ltd.) and reference product was Tirop $a^{R}$ tablet (Dae Woong Pharm. Co., Ltd.) One capsule of the test and reference product containing 100 mg of tropramide.hydrochloride was administered to the volunteers by randomized two period cross-over study (2 $\times$ 2 Latin square method). The drug concentration in plasma was determined by GC/MS for over a period of 12hours after administration. Analysis of variance reveal that there are no differences in AUC (area under the plasma concentration-time curve from time zero to infinity), Cmax (maximum plasma concentration) and Tmax (time to reach Cmax). The differences of mean AUC, Cmax and Tmax between two products were 3.85, 1.47 and -3.6%, respectively. Minimum detectable differences (%) at $\alpha$=0.1 were all less than 20% given as a guideline (18.07, 17.00 and 20.69% for AUC, Cmax and Tmax, respectively). From these results, the two products are bioequivalent.ent.

• YAKHAK HOEJI
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• v.27 no.2
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• pp.133-138
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• 1983

The interaction between nalidixic acid and probenecid was studied pharmacokinetically in rabbits. The blood level and the area under the concentration curve(AUC) of nalidixic acid administered orally in dose of 100mg/kg was elevated by the coadministration of probenecid. Probenecid inhibited both the urinary excretion and the biliary excretion of nalidixic acid. Therefore, biological half-life of nalidixic acid was prolonged by the coadministrarion of probenecid. It was considered that the coadmini-stration of probenecid is more desirable than the single administration of nalidixic acid for the therapeutic effect.

• Journal of Korean Academy of Nursing
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• v.33 no.2
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• pp.162-169
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• 2003

Purpose: This study was to compare the predictive validity of Norton Scale(1962), Cubbin & Jackson Scale(1991), and Song & Choi Scale(1991). Method: Data were collected three times per week from 48~72hours after admission based on the four pressure sore risk assessment scales and a skin assessment tool for pressure sore on 112 intensive care unit(ICU) patients in a educational hospital Ulsan during Dec, 11, 2000 to Feb, 10, 2001. Four indices of validity and area under the curve(AUC) of receiver operating characteristic(ROC) were calculated. Result: Based on the cut off point presented by the developer, sensitivity, specificity, positive predictive value, negative predictive value were as follows : Norton Scale : 97%, 18%, 35%, 93% respectively; Cubbin & Jackson Scale : 89%, 61%, 51%, 92%, respectively; and Song & Choi Scale : 100%, 18%, 36%, 100% respectively. Area under the curves(AUC) of receiver operating characteristic(ROC) were Norton Scale .737, Cubbin & Jackson Scale .826, Song & Choi Scale .683. Conclusion: The Cubbin & Jackson Scale was found to be the most valid pressure sore risk assessment tool. Further studies on patients with chronic conditions may be helpful to validate this finding.