• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.5
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• pp.910-924
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• 2010

As Internet usage has increased, the risk of adolescents being exposed to adult content and harmful information on the Internet has also risen. To help prevent adolescents accessing this content, a novel detection method for adult images is proposed. The proposed method involves three steps. First, the Image Of Interest (IOI) is extracted from the image background. Second, the IOI is distinguished from the segmented image using a novel weighting mask, and it is determined to be acceptable or unacceptable. Finally, the features (color and texture) of the IOI or original image are compared to a critical value; if they exceed that value then the image is deemed to be an adult image. A Receiver Operating Characteristic (ROC) curve analysis was performed to define this optimal critical value. And, the textural features are identified using a gray level co-occurrence matrix. The proposed method increased the precision level of detection by applying a novel weighting mask and a receiver operating characteristic curve. To demonstrate the effectiveness of the proposed method, 2850 adult and non-adult images were used for experimentation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.263-267
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• 2005

Building classifiers for financial real-world classification problems is often plagued by severely overlapping and highly skewed class distribution. New performance measures such as receiver operating characteristic (ROC) curve and area under ROC curve (AUC) have been recently introduced in evaluating and building classifiers for those kind of problems. They are, however, in-effective to evaluation of classifier's discrimination performance in a particular class of the classification problems that interests lie in only a local operating range of the classifier, In this paper, a new method is proposed that enables us to directly improve classifier's discrimination performance at a desired local operating range by defining and optimizing a partial area under ROC curve or domain-specific curve, which is difficult to achieve with conventional classification accuracy based learning methods. The effectiveness of the proposed approach is demonstrated in terms of fraud detection capability in a real-world fraud detection problem compared with the MSE-based approach.

• Analytical Science and Technology
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• v.34 no.2
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• pp.78-86
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• 2021

The objective of this study was to investigate urinary cut-off concentrations of quetiapine and risperidone for distinction between normal and abnormal/non-takers who were being placed on probation. Liquid chromatography-tandem mass spectrometric (LC-MS/MS) method was employed for determination of antipsychotic drugs in urine from mentally disordered probationers. The optimal cut-off values of antipsychotic drugs were calculated using receiver operating characteristic (ROC) curve analysis. The sensitivity and specificity of the method for the detection of antipsychotic drugs in urine were subsequently evaluated. The area under the ROC curve (AUC) was 0.927 for norquetiapine and 0.791 for 9-hydroxyrisperidone, respectively. These antipsychotic drugs are classified readily in the ROC curve analysis. The cut-off values for distinguishing regular and irregular/non-takers were 39.1 ng/mL for norquetiapine and 67.9 ng/mL for 9-hydroxyrisperidone, respectively. The results of this study suggest the cut-off values of quetiapine and risperidone were highly useful to distinguish regular takers from irregular/non-takers.

• The Journal of Korean Obstetrics and Gynecology
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• v.26 no.3
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• pp.85-92
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• 2013

Objectives: The purpose of this study is to find diagnostic points and define the cut off values of hot flashes by using digital infrared thermographic imaging. Methods: Thermographic images of 75 patients with hot flashes (HF, n=35) and non-hot flashes (NHF, n=40) were retrospectively reviewed. We used the temperature difference between Ex-HN3 and CV17, LU4, CV12, CV4 for diagnosing hot flashes. The temperature differences of between two groups were analysed using independent samples t-tests. The cut off values were calculated by received operating characteristic curve analysis. Analyses were undertaken using SPSS version 17.0. and p-value of <0.05 was considered significant. Results: The temperature difference Ex-HN3 and LU4 were the most significantly different between groups (p<0.001). Using receiver operating characteristic curve analysis, the sensitivity, specificity, and area under the curve were 65.7%, 72.5%, 0.729, respectively. The optimum cut off value was defined as $1.00^{\circ}C$. Conclusions: These results suggest that the digital infrared thermographic imaging is a reliable instrument for estimating hot flashes.

• Journal of Veterinary Clinics
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• v.19 no.3
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• pp.312-315
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• 2002

Diagnostic tests often require the determination of cut-off values that discriminate uninfected from infected individuals. The receiver operating characteristic (ROC) curve has been frequently used to attain this purpose and gives a representation of diagnostic accuracy (sensitivity and specificity) of a prediction model when varying the cut-point of a decision rule on a whole spectrum. We have written and tested a visual basic application program in EXCEL for maximum likelihood estimation of a binormal ROC curve, which also computes univariate statistics of a diagnostic test employed. Examples applying for computed tomographic images in radiology and methicillin-resistant Staphylococcus aureus research are given to illustrate this approach. This stand-alone module is available from the first author on request.

• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.11-18
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• 2005

Assume that the life times of the units under test follow the Rayleigh distribution and the test is terminated at a pre assigned time. Acceptance sampling plans are developed for this situation. The minimum sample size necessary to ensure the specified average life are obtained and the operating characteristic values of the sampling plans and producer's risk are given. An example is given to illustrate the methodology.

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

• Journal of Information Processing Systems
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• v.12 no.1
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• pp.109-128
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• 2016

This paper presents a new combined forecasting method that is guided by the soft set theory (CFBSS) to predict business failures with different sample sizes. The proposed method combines both qualitative analysis and quantitative analysis to improve forecasting performance. We considered an expert system (ES), logistic regression (LR), and support vector machine (SVM) as forecasting components whose weights are determined by the receiver operating characteristic (ROC) curve. The proposed procedure was applied to real data sets from Chinese listed firms. For performance comparison, single ES, LR, and SVM methods, the combined forecasting method based on equal weights (CFBEWs), the combined forecasting method based on neural networks (CFBNNs), and the combined forecasting method based on rough sets and the D-S theory (CFBRSDS) were also included in the empirical experiment. CFBSS obtains the highest forecasting accuracy and the second-best forecasting stability. The empirical results demonstrate the superior forecasting performance of our method in terms of accuracy and stability.

• The Journal of the Acoustical Society of Korea
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• v.7 no.2
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• pp.65-73
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• 1988

In this paper, V(z) curve has been analyzed theoretically and compared with the experimental result, and the relation between the V(z) curve and the material characteristic has been studied. Angular spectrum and ray optics theory have been used for theoretical analysis and the acoustic microscope operating at a center frequency of 3 MHz has been used for experiment. In experiment, it has been shown that each material has a V(z) curve of a unique form and the interval of dips appearing in the V(z) curves have been used to determine the Rayleigh wave velocity.

• 대한예방의학회:학술대회논문집
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• 1994.02b
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• pp.150-153
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• 1994

Receiver operating characteristic (ROC) curves have been frequently used to compare probability models applied to medical problems. Though the curves are a measure of the discriminatory power of a model. they do not reflect the model's accuracy. A supplementary accuracy curve is derived which will be coincident with the ROC curve if the model is reliable. will be above the ROC curve if the model's probabilities are too high or below if they are too low. A clinical example of this new graphical presentation is given.