• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.245-247
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• 2022

Backscattered x-ray imaging is a technology capable of acquiring an image inside an irradiated object by measuring X-rays scattered from an object. For image acquisition, the system must include an X-ray generator and a detection system for measuring scattered x-rays. The imaging device must acquire a real-time signal at sampling intervals for x-rays generated by passing through a high-speed rotating collimator, and for this purpose, a high-speed signal acquisition device is required. We developed a high-speed multi-channel signal acquisition device for converting and transmitting signals generated by the sensor unit composed of a large-area plastic scintillator and a photomultiplier tube. The developed detector is a system capable of acquiring signals at intervals of at least 15u seconds and converting and transmitting signals of up to 6 channels. And a system includes remote control functions such as high voltage, signal gain, and low level discrimination for individual calibration of each sensor. Currently, we are conducting an application test for image acquisition under various conditions.

• Korean Journal of Radiology
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• v.22 no.8
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• pp.1240-1252
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• 2021

Objective: To compare the accuracy for detecting breast cancer in the diagnostic setting between the use of digital breast tomosynthesis (DBT), defined as DBT alone or combined DBT and digital mammography (DM), and the use of DM alone through a systematic review and meta-analysis. Materials and Methods: Ovid-MEDLINE, Ovid-Embase, Cochrane Library and five Korean local databases were searched for articles published until March 25, 2020. We selected studies that reported diagnostic accuracy in women who were recalled after screening or symptomatic. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. A bivariate random effects model was used to estimate pooled sensitivity and specificity. We compared the diagnostic accuracy between DBT and DM alone using meta-regression and subgroup analyses by modality of intervention, country, existence of calcifications, breast density, Breast Imaging Reporting and Data System category threshold, study design, protocol for participant sampling, sample size, reason for diagnostic examination, and number of readers who interpreted the studies. Results: Twenty studies (n = 44513) that compared DBT and DM alone were included. The pooled sensitivity and specificity were 0.90 (95% confidence interval [CI] 0.86-0.93) and 0.90 (95% CI 0.84-0.94), respectively, for DBT, which were higher than 0.76 (95% CI 0.68-0.83) and 0.83 (95% CI 0.73-0.89), respectively, for DM alone (p < 0.001). The area under the summary receiver operating characteristics curve was 0.95 (95% CI 0.93-0.97) for DBT and 0.86 (95% CI 0.82-0.88) for DM alone. The higher sensitivity and specificity of DBT than DM alone were consistently noted in most subgroup and meta-regression analyses. Conclusion: Use of DBT was more accurate than DM alone for the diagnosis of breast cancer. Women with clinical symptoms or abnormal screening findings could be more effectively evaluated for breast cancer using DBT, which has a superior diagnostic performance compared to DM alone.

• Journal of Chest Surgery
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• v.57 no.1
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• pp.44-52
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• 2024

Background: Visceral pleural invasion (VPI) is a poor prognostic factor that contributes to the upstaging of early lung cancers. However, the preoperative assessment of VPI presents challenges. This study was conducted to examine intraoperative pleural carcinoembryonic antigen (pCEA) level and maximum standardized uptake value (SUVmax) as predictive markers of VPI in patients with clinical T1N0M0 lung adenocarcinoma. Methods: A retrospective review was conducted of the medical records of 613 patients who underwent intraoperative pCEA sampling and lung resection for non-small cell lung cancer. Of these, 390 individuals with clinical stage I adenocarcinoma and tumors ≤30 mm were included. Based on computed tomography findings, these patients were divided into pleural contact (n=186) and non-pleural contact (n=204) groups. A receiver operating characteristic (ROC) curve was constructed to analyze the association between pCEA and SUVmax in relation to VPI. Additionally, logistic regression analysis was performed to evaluate risk factors for VPI in each group. Results: ROC curve analysis revealed that pCEA level greater than 2.565 ng/mL (area under the curve [AUC]=0.751) and SUVmax above 4.25 (AUC=0.801) were highly predictive of VPI in patients exhibiting pleural contact. Based on multivariable analysis, pCEA (odds ratio [OR], 3.00; 95% confidence interval [CI], 1.14-7.87; p=0.026) and SUVmax (OR, 5.25; 95% CI, 1.90-14.50; p=0.001) were significant risk factors for VPI in the pleural contact group. Conclusion: In patients with clinical stage I lung adenocarcinoma exhibiting pleural contact, pCEA and SUVmax are potential predictive indicators of VPI. These markers may be helpful in planning for lung cancer surgery.

• Korean Journal of Radiology
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• v.24 no.1
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• pp.51-61
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• 2023

Objective: To develop and test a machine learning model for classifying human papillomavirus (HPV) status of patients with oropharyngeal squamous cell carcinoma (OPSCC) using ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) PET-derived parameters in derived parameters and an appropriate combination of machine learning methods in patients with OPSCC. Materials and Methods: This retrospective study enrolled 126 patients (118 male; mean age, 60 years) with newly diagnosed, pathologically confirmed OPSCC, that underwent ¹⁸F-FDG PET-computed tomography (CT) between January 2012 and February 2020. Patients were randomly assigned to training and internal validation sets in a 7:3 ratio. An external test set of 19 patients (16 male; mean age, 65.3 years) was recruited sequentially from two other tertiary hospitals. Model 1 used only PET parameters, Model 2 used only clinical features, and Model 3 used both PET and clinical parameters. Multiple feature transforms, feature selection, oversampling, and training models are all investigated. The external test set was used to test the three models that performed best in the internal validation set. The values for area under the receiver operating characteristic curve (AUC) were compared between models. Results: In the external test set, ExtraTrees-based Model 3, which uses two PET-derived parameters and three clinical features, with a combination of MinMaxScaler, mutual information selection, and adaptive synthetic sampling approach, showed the best performance (AUC = 0.78; 95% confidence interval, 0.46-1). Model 3 outperformed Model 1 using PET parameters alone (AUC = 0.48, p = 0.047) and Model 2 using clinical parameters alone (AUC = 0.52, p = 0.142) in predicting HPV status. Conclusion: Using oversampling and mutual information selection, an ExtraTree-based HPV status classifier was developed by combining metabolic parameters derived from ¹⁸F-FDG PET/CT and clinical parameters in OPSCC, which exhibited higher performance than the models using either PET or clinical parameters alone.

• Economic and Environmental Geology
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• v.37 no.4
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• pp.413-424
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• 2004

A paleomagnetic investigation of the Mesozoic Daedong Supergroup and the Precambrian Seosan Group in the Kyeonggi massif is carried out to elucidate the tectonic evolution of Korea under the effect of the collision between Korea and the North/South China Blocks. For the Daedong Supergroup, the characteristic direction of D/I=74.5$^{\circ}$/36.7$^{\circ}$(k=60.7, $\alpha$=5.1$^{\circ}$) after tilt correction is better clustered than that before tilt correction (D/I=61.9$^{\circ}$/52.8$^{\circ}$, k=4.4,$$\alpha$_{95}$=21.5$^{\circ}$), indi-cating that it is a primary magnetization acquired during the formation of the rock. Paleomagnetic pole position of the formation locates at 208.0$^{\circ}$E, 24.5$^{\circ}$N (n=14, K=67.5, $A_{95}$=4.9$^{\circ}$), statistically similar to those of Middle Triassic period of the SCB, revealing that the two had occupied the same tectonic unit during this period. It is observed that only 6 out of 33 sites of the Seosan Group yield remagnetized paleomagnetic direction. The rest of the sampling sites reveals severe dispersion of magnetic directions presumably due to the consequences of the collision between Korea and the North/South China Blocks. The characteristic direction of the Seosan Group is D/I=45.7$^{\circ}$/60.1$^{\circ}$(k=41.2,$$\alpha$_{95}$=10.6$^{\circ}$) and the corresponding pole is at 195.0$^{\circ}$E, 51.6$^{\circ}$N (n=6, K=20.8, $A_{95}$=12.4$^{\circ}$). Although the pole position is close to those of Jurassic period of the Kyeonggi massif and Early Cretaceous of the Kyeongsang basin. it is interpreted that the Seosan Group was remagnetized by the influence of the emplacement of the Jurassic Daebo Granite after or at the closing stage of the orogenic episode rather than under the direct effect of deformation and/or metamorphism caused by the collision.

• Pediatric Infection and Vaccine
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• v.19 no.1
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• pp.19-27
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• 2012

Purpose : As the number of children who attend child care centers has increased, concerns has increased about the effect of child day care on childhood illness. This study was conducted to examine the relationship between experience in child care and common infectious diseases in children under 5 years of age. Methods : Data were collected by surveying 1,000 respondents with children under age 5 through online interviews using a structured questionnaire. The contents of the survey were composed of demographic characteristics, child care facilities usage, experience in infectious diseases, and immunization status Results : Among the 1,000 children <5 years of age, 78.5% attended a child care facility. Rates of common communicable illnesses were higher in children in child care than for children reared exclusively at home. The predominant communicable diseases which the respondents' children experienced, in order of decreasing frequency, were gastroenteritis (47.1%), otitis media (41.8%) and pneumonia (19.1%). The immunization rate of vaccines that are not included the national immunization program (NIP) (Haemophilus influenzae type b vaccine - 76.6%, hepatitis A vaccine - 63.3%, pneumococcal vaccine - 59.4%, rotavirus vaccine - 43.1%) was lower than that of the NIP vaccines (90.4%) Conclusion : Children in child care experience more bouts of common infectious disease, so nationwide policies to prevent or to control the spread of infectious agents in a child-care should be available and appropriate immunization should be emphasized as the most effective method for the control of infectious disease for children.

• The Korean Journal of Nuclear Medicine
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• v.33 no.3
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• pp.316-326
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• 1999

Purpose: We evaluated the feasibility of extracting pure left ventricular blood pool and myocardial time-activity curves (TACs) and of generating factor images from human dynamic N-13 ammonia PET using factor analysis. The myocardial blood flow (MBF) estimates obtained with factor analysis were compared with those obtained with the user drawn region-of-interest (ROI) method. Materials and Methods: Stress and rest N-13 ammonia cardiac PET imaging was acquired for 23 min in 5 patients with coronary artery disease using GE Advance tomograph. Factor analysis generated physiological TACs and factor images using the normalized TACs from each dixel. Four steps were involved in this algorithm: (a) data preprocessing; (b) principal component analysis; (c) oblique rotation with positivity constraints; (d) factor image computation. Area under curves and MBF estimated using the two compartment N-13 ammonia model were used to validate the accuracy of the factor analysis generated physiological TACs. The MBF estimated by factor analysis was compared to the values estimated by using the ROI method. Results: MBF values obtained by factor analysis were linearly correlated with MBF obtained by the ROI method (slope = 0.84, r = 0.91), Left ventricular blood pool TACs obtained by the two methods agreed well (Area under curve ratio: 1.02 ($0{\sim}1min$), 0.98 ($0{\sim}2min$), 0.86 ($1{\sim}2min$)). Conclusion: The results of this study demonstrates that MBF can be measured accurately and noninvasively with dynamic N-13 ammonia PET imaging and factor analysis. This method is simple and accurate, and can measure MBF without blood sampling, ROI definition or spillover correction.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.157-173
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• 2011

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.363-368
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• 2003

We have successfully developed a more effective algorithm to extract the lineament in the area covered by wide alluvial deposits characterized by a relatively narrow range of brightness in the Landsat TM image, while the currently used algorithm is limited to the mountainous areas. In the new algorithm, flat areas mainly consisting of alluvial deposits were selected using the Local Enhancement from the Digital Elevation Model (DEM). The aspect values were obtained by 3${\times}$3 moving windowing of Zevenbergen & Thorno's Method, and then the slopes of the study area were determined using the aspect values. After the lineament factors in the alluvial deposits were revealed by comparing the threshold values, the first rank lineament under the alluvial deposits were extracted using the Hough transform In order to extract the final lineament, the lowest points under the alluvial deposits in a given topographic section perpendicular to the first rank lineament were determined through the spline interpolation, and then the final lineament were chosen through Hough transform using the lowest points. The algorithm developed in this study enables us to observe a clearer lineament in the areas covered by much larger alluvial deposits compared with the results extracted using the conventional existing algorithm. There exists, however, some differences between the first rank lineament, obtained using the aspect and the slope, and the final lineament. This study shows that the new algorithm more effectively extracts the lineament in the area covered with wide alluvlal deposits than in the areas of converging slope, areas with narrow alluvial deposits or valleys.

• Tuberculosis and Respiratory Diseases
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• v.65 no.4
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• pp.269-276
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• 2008

Background: Although the prevalence of tuberculosis infections (PTBI) is one of the basic epidemiologic indices, no survey has been carried out since 1995 because the nation-wide tuberculosis prevalence survey was changed to a surveillance system. Subjects without a BCG scar are examined in a tuberculin survey. However, it is very difficult to select these subjects under high vaccination coverage. It is important to evaluate the impact of BCG vaccinations on the tuberculin response and estimate the PTBI regardless of the BCG vaccination status. Methods: A nation-wide, school-based cross-sectional tuberculin survey was carried out among first graders in elementary school in 2006. A total of 5,148 children in 40 schools were selected by quota sampling. Tuberculin testing with 0.1 ml of two tuberculin units of PPD RT23 was carried out on 4,018 children. The maximum transverse diameter of induration was measured 48 to 72 hours later. The presence of a BCG scar was checked separately. Results: There were no BCG scars in 6.3% of the subjects. The mean induration size of tuberculin testing was $3.7{\pm}4.4mm$, which included 1,882 (46.8%) subjects with an induration size of 0 mm. The PTBI was 10.9% (439 subjects) using a cut-off point of ${\geq}10mm$ (conventional method). The annual risk of tuberculosis infections (ARTI) was 1.9% when the mean age of the subjects was assumed to be 6 years. There was no difference in the PTBI according to the presence or absence of a BCG scar [11.2% vs 7.6% (OR: 1.54, 95% CI: 0.98~2.43)]. Using a mirror image technique with 16 mm as the cut-off point, the PTBI and ARTI had decreased to 2.4% and 0.4% respectively. Conclusion: PTBI and ARTI, as estimated by conventional methods, appear to be high among BCG vaccinated children. A mirror image technique is more suitable for estimating the indices in a country with an intermediate burden of tuberculosis than the conventional method.