• The Korean Journal of Applied Statistics
• /
• v.33 no.5
• /
• pp.541-553
• /
• 2020

The receiver operating characteristic (ROC) curve is expressed as both sensitivity and specificity; in addition, some optimal thresholds using the ROC curve are also represented with both sensitivity and specificity. In addition to the sensitivity and specificity, the expected usefulness function is considered as disease prevalence and usefulness. In particular, partial the area under the ROC curve (AUC) on a certain range should be compared when the AUCs of the crossing ROC curves have similar values. In this study, partial AUCs representing high sensitivity and specificity are proposed by using sensitivity and specificity lines, respectively. Assume various distribution functions with ROC curves that are crossing and AUCs that have the same value. We propose a method to improve the discriminant power of the classification models while comparing the partial AUCs obtained using sensitivity and specificity lines.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.61 no.12
• /
• pp.1782-1790
• /
• 2012

In this paper, a methodology to use load duration curve and the reactive power factor sensitivity of generation cost is proposed for analyzing the effects of load power factor effectively. A great deal of cases of power systems are classified into several patterns according to the characteristics using load duration curve, and the overall effects of load power factor are assessed by integrating the analysis results of load power factor in all the patterns. The reactive power sensitivity of generation cost and the integrated costs such as generation cost, investment cost, voltage variation penalty cost and CO2 emission cost are used for determining an appropriate load power factor. A systematic procedure for effective analysis of load power factor is presented. It is shown through the application to the practical power system of KEPCO(Korea Electric Power Corporation)that the effects of load power factor can be analyzed effectively using load duration curve and reactive power factor sensitivity.

• Communications for Statistical Applications and Methods
• /
• v.27 no.2
• /
• pp.211-224
• /
• 2020

Sensitivity and specificity are popular measures described by the receiver operating characteristic (ROC) curve. There are also two other measures such as the positive predictive value (PPV) and negative predictive value (NPV); however, the PPV and NPV cannot be represented by the ROC curve. Based on the total operating characteristic (TOC) curve suggested by Pontius and Si (International Journal of Geographical Information Science, 97, 570-583, 2014), explanatory methods are proposed to geometrically describe the PPV and NPV by the TOC curve. It is found that the PPV can be regarded as the slope of the right-angled triangle connecting the origin to a certain point on the TOC curve, while 1 - NPV can be represented as the slope of the right-angled triangle connecting a certain point to the top right corner of the TOC curve. When the neutral zone exists, the PPV and 1-NPV can be described as the slopes of two other right-angled triangles of the TOC curve. Therefore, both the PPV and NPV can be estimated using the TOC curve, whether or not the neutral zone is present.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
• /
• 2004.09a
• /
• pp.312-316
• /
• 2004

Single-well tracer tests, especially push pull tracer tests, are more effective to estimate hydraulic parameters and microbial metabolic activities in terms of duration and cost compared to multi-well tracer tests. However, there are some drawbacks in accuracy, complicated data analysis and uniqueness. These shortages are thought to be derived from the applied conditions which affect mass recovery curve and breakthrough curve. Factors such as extraction rate, resting period, hydraulic conductivity and hydraulic gradient are considered as the major factors determining the mass recovery rate and shape of the breakthrough curve. The results of the sensitivity analysis are summarized as follows: 1) the significant change in concentration of breakthrough curve is obtained when the extraction rate increases. This effect would also be much higher if the hydraulic conductivity is lower; 2) the mass recovery rate decreases with the increase of resting time, and the difference of mass recovery rates for different resting times is inversely proportional to the hydraulic conductivity; 3) the sensitivity values decrease with time. The hydraulic conductivity affects not only the early period, but the later period of the breakthrough curves; 4) The influence of the hydraulic gradient on the breakthrough curves is greater at earlier stage than at later stage. The mass recovery rate is inversely proportional to the hydraulic gradient.

• Korean Journal of Oriental Medicine
• /
• v.17 no.2
• /
• pp.107-113
• /
• 2011

Objectives : Sasang typology is extensively studied for the Sasang constitution diagnosis objectification with various data, for example, questionaires, reference materials, etc and analyzed with the several statistical methods. In this study, we used ROC-curve (Receiver Operating Characteristic curve) analysis to diagnose Sasang constitution, which is a kind of epidemiologic research methods and is away from traditional statistical methods. Methods : We collected personality questionnaire which consists of 15 items, from 24 oriental medical clinics. We analyzed the sensitivity and specificity using ROC curve method based on the score of personality questionnaire and also investigated classification accuracy and cut-off value of Sasang constitution. Results : The AUC (area under the ROC curve) value was 0.508 (p=.5511) for Taeeumin, 0.629 (p<.0001) for Soeumin and 0.604(p<.0001) for Soyangin, respectively. so the classification accuracy for Soeumin was highest Soeumin for over 30 points and Soyangin for below 28 points respectively. Conclusions : We suggest that Taeeumin is not classified easily in the ROC-curve analysis. We may classify Soeumin and Soyangin but the accuracy of Sasang constitutional diagnosis is still low.

• Journal of Chest Surgery
• /
• v.24 no.3
• /
• pp.253-260
• /
• 1991

The adequacy of anticoagulation with heparin during cardiopulmonary bypass, and precise neutralization with protamine at the conclusion of cardiopulmonary bypass, were important. In sixty children undergoing cardiopulmonary bypass, ACT and heparin dose-response curve were studied. Total dose of heparin before bypass were 2.80$\pm$0.74 mg/kg and the amount of protamine administered after bypass were 3.0$\pm$1.23 mg/kg. So protamine: heparin ratio was 1.07: l.c After administration of protamine which dose is calculated with heparin dose-response curve, ACTs were returned to normal range[mean 114.8 $\pm$13 second]. The heparin sensitivity and its half-life do not have relationship with age, weight, height, surface area and urine amount during operation. And there are too much individual variations in heparin sensitivity and its half-life. So conventional heparin protocols can overestimate or underestimate the amount of heparin and protamine. Heparin dose-response curve makes it possible to maintain anticoagulation in a safe range during bypass with adequate amount of heparin individually. At the conclusion of bypass, this curve can be used to predict the precise amount of protamine amount of protamine needed for neutralization of the heparin. But heparin dose-response curve to be used clinically, further studies will be needed about relationship between ACT and heparin level in the high range, influence of hemodilution and hypothermia to ACT and discrepancy between true adequate amount of protamine and calculated amount by heparin dose-response curve.

• Dementia and Neurocognitive Disorders
• /
• v.23 no.1
• /
• pp.11-21
• /
• 2024

Background and Purpose: Although dementia with Lewy bodies (DLB) is the second most common cause of neurodegenerative dementia, its clinical prevalence is low. We developed a short and easy-to-complete DLB screening questionnaire (DLBSQ) to raise diagnostic sensitivity in routine clinical settings. Methods: A total of 501 participants were retrospectively enrolled, including 71 controls, 184 patients without DLB, and 246 patients with probable DLB. All patients underwent clinical evaluation, including core features of DLB, the DLBSQ, brain magnetic resonance imaging, and detailed neuropsychological assessments. The diagnostic performance of the DLBSQ for probable DLB was investigated using a receiver operating characteristic curve analysis. Results: Total DLBSQ score was associated with visuospatial and frontal/executive dysfunction and the diagnosis of probable DLB. The area under the receiver operating characteristic curve for total DLBSQ score was 0.727. Youden's method revealed an optimal cutoff value of 3. The sensitivity and specificity of the DLBSQ were 68.7% and 62.4%, respectively. Its discriminating performance improved when cognitive test profiles were additionally considered (area under the curve: 0.822, sensitivity: 80.6%, and specificity: 70.4%). Conclusions: The DLBSQ might be a useful screening tool for DLB in routine clinical practice with good sensitivity and specificity.

• Journal of Veterinary Clinics
• /
• v.33 no.2
• /
• pp.97-101
• /
• 2016

In the field of clinical medicine, diagnostic accuracy studies refer to the degree of agreement between the index test and the reference standard for the discriminatory ability to identify a target disorder of interest in a patient. The receiver operating characteristic (ROC) curve offers a graphical display the trade-off between sensitivity and specificity at each cutoff for a diagnostic test and is useful in assigning the best cutoff for clinical use. In this end, the ROC curve analysis is a useful tool for estimating and comparing the accuracy of competing diagnostic tests. This paper reviews briefly the measures of diagnostic accuracy such as sensitivity, specificity, and area under the ROC curve (AUC) that is a summary measure for diagnostic accuracy across the spectrum of test results. In addition, the methods of creating an ROC curve in single diagnostic test with five-category discrete scale for disease classification from healthy individuals, meaningful interpretation of the AUC, and the applications of ROC methodology in clinical medicine to determine the optimal cutoff values have been discussed using a hypothetical example as an illustration.

• Korean Journal of Soil Science and Fertilizer
• /
• v.48 no.6
• /
• pp.712-723
• /
• 2015

This study was conducted to develop the SWCC estimation equation using scaling technique, and to investigate relative sensitivity of the SWCC according to the soil water tension, for the four kinds of soil texture such as Sand [S], Sandy Loam [SL], Loam [L] and Clay Loam [CL]. The SWCC estimation equation of scale factor [${\Theta}sc$] (Eq. 1) was developed based on the log function (Eq. 2) and exponential function (Eq. 3). ${\Theta}sc=[({\Theta}-{\Theta}r)/({\Theta}s-{\Theta}r)]$ (Eq. 1) ${\Theta}sc=-0.196ln(H)+0.4888$ (Eq. 2) ${\Theta}sc=0.3804(H)^{(-0.448)}$ (Eq. 3) where, ${\Theta}$: water content (g/g %), ${\Theta}s$: water content at 0.1bar, ${\Theta}r$: water content at 15bar, H: soil water tension (matric potential) (bar) Relative sensitivity of soil water content was decreased as increase soil water tension, those according to soil water tension were 0.952~0.620 compared to 0.1bar case. Relative sensitivity of scale factor was also decreased as increase soil water tension, those according to soil water tension were 0.890~0.577 compared to 0.2bar case.

• Current Optics and Photonics
• /
• v.7 no.5
• /
• pp.504-510
• /
• 2023

An optical fiber dislocation fusion humidity sensor coated with graphene quantum dots is investigated. A Mach-Zehnder interferometer is fabricated with three dislocated single-mode fibers with graphene quantum dots coating humidity-sensitive materials. Humidity response experiments showed a good linear response and high sensitivity with easy fabrication and low-cost materials. From 22% to 98% RH, the humidity response sensitivity of the sensor is 0.24 dB/% RH, with 0.9825 linearity. To investigate the cross-response of humidity and temperature, temperature response experiments are conducted. From 30 ℃ to 70 ℃, the results showed 0.02 dB/℃ sensitivity and 0.9824 linearity. The humidity response experimental curve is compared with the temperature experimental curve. The big difference between humidity sensitivity and temperature sensitivity is very helpful to solve the cross-response of humidity and temperature. The influence of temperature fluctuations in humidity measurements is not obvious.