• Journal of the Korean Society of Radiology
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• v.11 no.3
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• pp.171-175
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• 2017

In the non-destructive inspection field, we invest a lot of time and resources in developing the radiation source system to ensure the safety of the workers. However, the probability of accidents is still high. In order to prevent potential radiation accidents in advance, it is necessary to directly verify the position of the radiation source, but the research is still insufficient. In this study, we developed a monitoring system that can detect the position of the radiation source in the source guide tube in the gamma-ray irradiator. The characteristics of the radiation detector are estimated by monte carlo simulation. As a result, the radiation detector for Ir-192 gamma-ray energy was analyzed to have secondary electron equilibrium at $150{\mu}m$ regardless of the semiconductor material. Also, it is expected that the gamma ray response characteristic is the best in $HgI_2$. These results are expected to be used as a basis for determining the optimal thickness of the radiation detector located in the detection part of the future monitoring system. In addition, when developing a monitoring system based on this, radiation workers can easily recognize the danger and secure safety, as well as prevent and preemptively respond to potential radiation accidents.

• Journal of Advanced Navigation Technology
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• v.20 no.4
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• pp.367-373
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• 2016

We propose an improved direction of arrival (DoA) estimation algorithm based on co-prime array and propagator method. The propagator method with co-prime array does not require singular value decomposition (SVD) requiring much less computational complexity but exhibiting somewhat worse performance in comparison with MUSIC based on co-prime array. We notice that one cause of the performance degradation was in the avoidance of the usage of the diagonal elements of the signal autocorrelation matrix that contains the noise power spectral density. So we propose an algorithm with the diagonal elements of the signal autocorrelation matrix based on the fact that the noise power spectral density can be estimated using noise observation over a long period of time. We observe, through simulations, that the proposed scheme in this paper improves the performance, with 4 times more computational requirement, by signal-to-noise ratio of 1.5dB and by DoA resolution of $0.7^{\circ}$ at the detection probability of 95% compared with the previously introduced co-prime array propagator scheme, resulting in performance much closer to that of co-prime array-based MUSIC scheme.

• Journal of Veterinary Clinics
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• v.26 no.2
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• pp.130-133
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• 2009

The use of screening tests as part of a diagnostic work-up is common in domestic canine practice, but understanding of the diagnostic test characteristics and factors affecting diagnostic accuracy is not clear among clinicians. This article was aimed to provide clinicians with a better understanding on the selection of test kits and with a proper interpretation of test results using an example from heartworm(Dirofilaria immitis) studies. From the literatures, diagnostic accuracy varied depending on the kits: percent average sensitivity and specificity of ELISA antigen-detecting kits were DiroChek(Synbiotics, USA) 78.1 and 95.2, SNAP(IDEXX, USA) 66.3 and 98.1, and Solo Step(Heska, Switzerland) 69.5 and 97.5, respectively, while the values for three hematological methods(Modified Knott's, direct smear and capillary tube) ranged from 38.4 to 81.8% and from 96.9 to 100%, respectively. Furthermore, it was also reported that the prevalence of heartworm disease in domestic dog populations varied depending on the regions studied: 2.5-22.8% for microfilarial test and 2.2-66.3% by ELISA. The values of predictive values for positive(PPV) and negative(NPV) provide useful information to clinicians on the probability of heartworm infection, but the PPV and NPV are greatly dependent on the heartworm prevalence. This suggests that PPV or NPV values of a test should be interpreted carefully in different clinical settings. Practical methods on the interpretation taking into account heartworm prevalence were discussed.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.287-299
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• 2017

The Southern Volcanic Zone (SVZ) of Chile consists of many volcanoes, including the Mt.Villarrica and Mt.Llaima, and the two volcanoes are covered with snow at the top of Mountain. The purpose of this study is to analyze the relationship between the ice caps and the volcanic activity of the two volcanoes for 25 years by using the satellite image data are available in a time series. A total of 60 Landsat-5 TM and Landsat-7 ETM + data were used for the study from September 1986 to February 2011. Using NDSI (Normalized Difference Snow Index) algorithm and SRTM DEM, snow cover and snowline were extracted. Finally, the snow cover area, lower-snowline, and upper-snowline, which are quantitative indicators of snow cover change, were directly or indirectly affected by volcanic activity, were extracted from the satellite images. The results show that the volcanic activity of Villarrica volcano is more than 55% when the snow cover is less than 20 and the lower-snowline is 1,880 m in Llaima volcano. In addition, when the upper-snowline of the two volcanoes is below -170m, it can be confirmed that the volcano is differentiated with a probability of about 90%. Therefore, the changes in volcanic snowfall are closely correlated with volcanic activity, and it is possible to indirectly deduce volcanic activity by monitoring the snow.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.1
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• pp.61-67
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• 2015

Recently, the initiation of outside diameter stress corrosion cracking (ODSCC) at the tube support plate region of domestic steam generators (SG) with Alloy600 HTMA tubes has been increasing. As a result, SGs with Alloy600 HTMA tubes must be replaced early or are scheduled to be replaced prior to their designed lifetime. ODSCC is one of the biggest threats to the integrity of SG tubes. Therefore, the accurate evaluation of tube integrity to determine ODSCC is needed. Eddy current testing (ECT) is conducted periodically, and its results could be input as parameters for evaluating the integrity of SG tubes. The reliability of an ECT inspection system depends on the performance of the inspection technique and abilty of the analyst. The detection probability and ECT sizing error of degradation are considered to be the performance indices of a nondestructive evaluation (NDE) system. This paper introduces an optimized evaluation method for ECT, as well as the sizing error, including the analyst performance. This study was based on the results of a round robin program in which 10 inspection analysts from 5 different companies participated. The analysis of ECT sizing results was performed using a linear regression model relating the true defect size data to the measured ECT size data.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.91-98
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• 2023

Recently, according to development of artificial intelligence, a wide range of industry being automatic and optimized. Also we can find out some research of using supervised learning for deteceting defect of railway in domestic rail industry. However, there are structures other than rails on the track, and the fastener is a device that binds the rail to other structures, and periodic inspections are required to prevent safety accidents. In this paper, we present a method of reducing cost for labeling using semi-supervised and transfer model trained on rail fastener data. We use Resnet50 as the backbone network pretrained on ImageNet. At first we randomly take training data from unlabeled data and then labeled that data to train model. After predict unlabeled data by trained model, we adopted a method of adding the data with the highest probability for each class to the training data by a predetermined size. Futhermore, we also conducted some experiments to investigate the influence of the number of initially labeled data. As a result of the experiment, model reaches 92% accuracy which has a performance difference of around 5% compared to supervised learning. This is expected to improve the performance of the classifier by using relatively few labels without additional labeling processes through the proposed method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.579-585
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• 2019

Increasing the detection probability of underwater targets necessitates securing the towing stability of the active towed SONAR. In this paper, to confirm the effects of tail wing fin on towing attitude and towing stability, two scale model experiments and one sea trials were conducted and the results were analyzed. The scale model tests measured the towing behavior of each of the tail fin shapes according to towing speed in a towing tank. The shape of the tail fin used in the scale model test was tested with an I-type tail fine and four Y-type tail fins, totaling five tail fins of the two kinds. The first scale model test confirmed that the Y-type tail fin was superior to the I-type tail fin in towing attitude and towing stability. The second scale model test confirmed the characteristics of the vertical tail fin height increase and the lower horizontal tail fin inclination angle application shape based on the Y-type tail fin. The shape of the application of the lower horizontal tail fin inclination angle showed the best performance. In order to verify the results of the scale model test, a full size model was constructed, sea trials were performed, and the towing attitude was measured. The results were similar to those of the scale model test.

• Journal of the Korean Society of Radiology
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• v.81 no.3
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• pp.610-619
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• 2020

Purpose The study aimed to investigate the role of Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) in predicting incidental prostate cancer (PCa) or urothelial carcinoma (UCa) extension in urinary bladder (UB) cancer patients. Materials and Methods A total of 72 UB cancer patients who underwent radical cystoprostatectomy and 3 Tesla multiparametric MRI before surgery were enrolled. PI-RADS v2 ratings were assigned by two independent radiologists. All prostate specimens were examined by a single pathologist. We compared the multiparametric MRI findings rated using PI-RADS v2 with the pathologic data. Results Of the 72 UB cancer patients, 29 had incidental PCa (40.3%) and 20 showed UCa extension (27.8%), with an overlap for 3 patients. With a score of 4 as the cut-off value for predicting incidental PCa, the diagnostic accuracy was 65.3%, specificity was 90.7%, and positive predictive value (PPV) was 66.7%. The diagnostic accuracy for incidental UCa extension was 47.2%, specificity was 92.3%, and PPV was 83.3%. Conclusion Despite the low diagnostic accuracy, the PPV and specificity were relatively high. Therefore, PI-RADS v2 scores of 1, 2, or 3 may help exclude the probability of incidental PCa or UCa extension.

• Korean Journal of Culture and Social Issue
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• v.14 no.4
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• pp.1-18
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• 2008

The present study examined the accuracy of polygraph tests through two types of statistical methods with unknown ground truth. One method evaluated the accuracy based on the rates of agreements between polygraph test results of crime suspects and prosecutors' indictment decisions for them. Those crime suspects were tested with polygraph by the Prosecutors' Office of the Republic of Korea between 2000 and 2004. The other method estimated the accuracy by using the latent class analysis based on the frequency distributions of the polygraph results and indictments during 2006. Excluding cases that were 'inconclusive' on the polygraph test, the study showed that the accuracy of the polygraph tests is .914 (SE=.004) for the 2000-2004 data, and .885 (SE=.021) for the 2006 data. With the inclusion of 'inconclusive' cases in the 2006 data, the results from the latent class analysis showed the accuracy in the range between .707 and .734 (SE=.027~.031), with false positives between .078 and .087 (SE=.019~.023), and false negatives between .029 and .078 (SE=.010~.023). The probability that the polygraph test correctly classifies subjects appeared to be in the range between .912 and .925 (SE=.013-.016) for those who lie, and in the range between .867 to .955 (SE=.011-.040) for those who tell the truth.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.201-208
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• 2014

In this paper, we propose the classifier structure design algorithm using DTW. Proposed algorithm uses DTW result to design the binary tree architecture based on the SVM which classify the multi-class data. Design the binary tree architecture for Support Vector Machine(SVM-BTA) using the threshold criterion calculated by the sum columns in square matrix which components are the reference data from each class. For comparison the performance of the proposed algorithm, compare the results of classifiers which binary tree structure are designed based on database and k-means algorithm. The data used for classification is 333 signals from 18 classes of underwater transient noise. The proposed classifier has been improved classification performance compared with classifier designed by database system, and probability of detection for non-biological transient signal has improved compare with classifiers using k-means algorithm. The proposed SVM-BTA classified 68.77% of biological sound(BO), 92.86% chain(CHAN) the mechanical sound, and 100% of the 6 kinds of the other classes.