• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.139-149
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• 2010

Internet was designed for network scalability and best-effort service which makes all hosts connected to Internet to be vulnerable against attack. Many papers have been proposed about attack detection algorithms against the attack using IP spoofing and DoS/DDoS attack. Purpose of DoS/DDoS attack is achieved in short period after the attack begins. Therefore, DoS/DDoS attack should be detected as soon as possible. Attack detection algorithms using false alarm rates consist of the false negative rate and the false positive rate. Moreover, they are important metrics to evaluate the attack detections. In this paper, we analyze the performance of the attack detection algorithms using the impact of false negative rate and false positive rate variation to the normal traffic and the attack traffic by simulations. As the result of this, we find that the number of passed attack packets is in the proportion to the false negative rate and the number of passed normal packets is in the inverse proportion to the false positive rate. We also analyze the limits of attack detection due to the relation between the false negative rate and the false positive rate. Finally, we propose a solution to minimize the limits of attack detection algorithms by defining the network state using the ratio between the number of packets classified as attack packets and the number of packets classified as normal packets. We find the performance of attack detection algorithm is improved by passing the packets classified as attacks.

• Communications for Statistical Applications and Methods
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• v.28 no.2
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• pp.161-169
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• 2021

The two-dimensional confusion matrix used in credit assessment, biostatistics, and many other fields consists of true positive, true negative, false positive, and false negative. Their rates, such as the true positive rate (TPR), true negative rate (TNR), false positive rate, and false negative rate, can be applied to measure its accuracy. In this study, we propose the TPR-TNR plot, a graphical method that can geometrically describe and explain these rates based on the confusion matrix. The proposed TPR-TNR plot consists of two right-angled triangles. We obtain that the TPR and TNR describe the acute angles of right-angled triangles in the plot. These acute angles can be used to determine optimal thresholds corresponding to lots of accuracy measures.

• Journal of radiological science and technology
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• v.44 no.6
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• pp.635-643
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• 2021

The results of empirical researches on the diagnosis of lung cancer are insufficient, so it is limited to objectively judge the clinical possibility and utilization according to the accuracy of diagnosis. Thus, this study retrospectively analyzed the lung cancer diagnostic performance of PET-MRI (Positron Emission Tomography-Magnetic Resonance Imaging) by using the decision matrix. This study selected and experimented total 165 patients who received both hematological CEA (Carcinoembryonic Antigen) test and hybrid PET-MRI (¹⁸F-FDG, 5.18 MBq/kg / Body TIM coil. VIVE-Dixon). After setting up the result of CEA (positive:>4 ㎍/ℓ. negative:<2.5㎍/ℓ) as golden data, the lung cancer was found in the image of PET-MRI, and then the SUV_max (positive:>4, negative:<1.5) was measured, and then evaluated the correlation and significance of results of relative diagnostic performance of PET-MRI compared to CEA through the statistical verification (t-test, P>0.05). Through this, the PET-MRI was analyzed as 96.29% of sensitivity, 95.23% of specificity, 3.70% of false negative rate, 4.76% of false positive rate, and 95.75% of accuracy. The false negative rate was 1.06% lower than the false positive rate. The PET-MRI that significant accuracy of diagnosis through high sensitivity and specificity, and low false negative rate and false positive rate of lung cancer, could acquire the fusion image of specialized soft tissue by combining the radio-pharmaceuticals with various sequences, so its clinical value and usefulness are regarded as latently sufficient.

• The Korean Journal of Cytopathology
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• v.7 no.2
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• pp.111-121
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• 1996

Fine needle aspiration cytology(FNAC) is preferred because of simplicity, safety, and reliability in the evaluation of patients with thyroid nodule or hyperplasia. However, there are a few limitations such as false-negative or false-positive cases and non-diagnostic material. To evaluate the usefulness of FNAC in thyroid lesions, we reviewed 704 FNAC cases of thyroid nodules from 1988 to 1994 at Soonchunhyang University Hospital. The results are as follows. 1. Among 704 FNAC cases of thyroid gland, 571(81.1%) cases were benign, 12(1.7%) were suspicious, 71(10.1%) were malignancy, and 50(7.1%) were material insufficiency. The cytologic diagnoses of the benign lesions included 168 cases of follicular neoplasm, 139 cases of adenomatous goiter, 162 cases of follicular lesion such as follicular neoplasm or adenomatous goiter, 61 cases of Hashimoto's thyroiditis, 13 cases of subacute thyroiditis, and 28 cases of colloidal nodule or benign nodule. The malignant lesions included 68 cases of papillary carcinona, two medullary carcinomas and a case of metastatic colon cancer. 2. The average number of cytologic smear slides was $4.12{\pm}1.81$ in material insufficiency and $5.63{\pm}1.79$ in diagnostic cases. This difference was statistically significant(p<0.00001). 3. Histological assessment of 150 cases revealed 2 false negative and 1 false positive cases. The false negative cases were a case of marked sclerosis in papillary carcinoma and an occult case of papillary carcinoma. The false positive case resulted from pseudo-ground glass nuclei due to marked dry artifact. 4. Comparison between the FNAC and the histologic diagnosis revealed that FNAC had a sensitivity of 93.5%, a specificity of 99.2%, a false negative rate of 6.6%, a false positive rate of 0.8%, and an overall diagnostic accuracy of 98.0%. Therefore, FNAC of thyroid gland is a very reliable diagnostic method with excellent accuracy rate.

• Journal of KIISE:Information Networking
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• v.31 no.2
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• pp.171-178
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• 2004

Port scanning detection systems should rather satisfy a certain level of the requirement for system performance like a low rate of “False Positive” and “False Negative”, and requirement for convenience for users to be easy to manage the system security with detection systems. However, public domain Real Time Scan Detection Systems have high rate of false detection and have difficulty in detecting various scanning techniques. In addition, as current real time scan detection systems are based on command interface, the systems are poor at user interface and thus it is difficult to apply them to the system security management. Hence, we propose TkRTSD(Tcl/Tk Real Time Scan Detection System) that is able to detect various scan attacks based on port scanning techniques by applying a set of new filter rules, and minimize the rate of False Positive by applying proposed ABP-Rules derived from attacker's behavioral patterns. Also a GUI environment for TkRTSD is implemented by using Tcl/Tk for user's convenience of managing network security.

• Korean Journal of Head & Neck Oncology
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• v.8 no.2
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• pp.97-105
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• 1992

One hundred and thirty-nine thyroid nodules were evaluated by aspiration biopsy cytology (ABC) and were compared with the postoperative histologic diagnosis during the period from May 1, 1986 through Aug. 31, 1992. The correlation betwen the two diagnoses proved to be comparable with a low incidence of false-negative diagnoses, but with a relatively high incidence of false-positive ones. The sensitivity was 93.5%, specificity 89.6%, false-negative rate 6.5%, false-positive rate 10.4%, positive predictability 87.9%, negative predictability 94.5%, and overall diagnostic accuracy 91.4%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2341-2348
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• 2009

An intrusion detection technique based on host consider system call sequence or system call arguments. These two ways are suitable when system call sequence or order and length of system call arguments are out of order. However, there are two disadvantages which a false positive rate and a false negative rate are high. In this paper we propose the T-N2SCD detection model based on Time Window in order to reduce false positive rate and false negative rate. Data for using this experiment is provided from DARPA. As experimental results, the proposed model showed that the false positive rate and the false negative rate are lowest at an interval of 1000ms than at different intervals.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.154-168
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• 2021

COVID-19 has been spreading all around the world, and threatening global health. In this situation, identifying and isolating infected individuals rapidly has been one of the most important measures to contain the epidemic. However, the standard diagnosis procedure with RT-PCR (Reverse Transcriptase Polymerase Chain Reaction) is costly and time-consuming. For this reason, pooled testing for COVID-19 has been proposed from the early stage of the COVID-19 pandemic to reduce the cost and time of identifying the COVID-19 infection. For pooled testing, how many samples are tested in group is the most significant factor to the performance of the test system. When the arrivals of test requirements and the test time are stochastic, batch-service queueing models have been utilized for the analysis of pooled-testing systems. However, most of them do not consider the false-negative test results of pooled testing in their performance analysis. For the COVID-19 RT-PCR test, there is a small but certain possibility of false-negative test results, and the group-test size affects not only the time and cost of pooled testing, but also the false-negative rate of pooled testing, which is a significant concern to public health authorities. In this study, we analyze the performance of COVID-19 pooled-testing systems with false-negative test results. To do this, we first formulate the COVID-19 pooled-testing systems with false negatives as a batch-service queuing model, and then obtain the performance measures such as the expected number of test requirements in the system, the expected number of RP-PCR tests for a test sample, the false-negative group-test rate, and the total cost per unit time, using the queueing analysis. We also present a numerical example to demonstrate the applicability of our analysis, and draw a couple of implications for COVID-19 pooled testing.

• Communications for Statistical Applications and Methods
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• v.19 no.4
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• pp.629-638
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• 2012

We propose some methods to obtain optimal thresholds and classification functions by using various cutoff criterion based on the bivariate ROC curve that represents bivariate cumulative distribution functions. The false positive rate and false negative rate are calculated with these classification functions for bivariate normal distributions.

• The Korean Journal of Nuclear Medicine
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• v.27 no.1
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• pp.81-87
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• 1993

Retrospective analysis of cholescintigraphy and ultrasonography was done in 76 patients with clinically suspected acute cholecystitis to assess the relative value of the two modalities. Excluding the Patients with obstructive jaundice, the overall results of cholescintigraphy(sensitivity 100%, specificity 95%, false positive rate 5%, false negative rate 0%, accuracy 97%) are nearly identical with or rather superior to those of the ultrasonography(sensitivity 94%, specificity 100%, false positive rate 0%, false negative rate 5%, accuracy 97%). We recommend the cholescintigraphy as the initial modality in patients with clinically suspected acute cholecystitis, and ultrasonography can be used in jaundiced patients to exclude the possibility of the false positive of cholescintigraphy.