• 한국방재안전학회논문집
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• 제16권4호
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• pp.123-128
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• 2023

본 논문은 점검진단 보고서의 데이터에 기반한 교량의 내하율 추정 모델의 판별 정확도 분석 결과를 보여준다. 내하율 추정 모델은 2,161건의 점검진단 보고서 수집을 통해, 통계적 방법에 의해 도출하였다. 교량의 제원 및 유지관리 정보를 입력하면 해당 교량의 추정된 내하율을 확인할 수 있다. 추정 내하율 모델의 판별 정확도를 검증하기 위하여, 데이터 확보가 되어 있는 공용중 교량 164개소에 대해 추정 내하율과 점검진단 보고서 상의 내하율을 비교하였다. 교량 형식별로 차이가 있지만 추정 내하율 판별 정확도 80% 이상의 결과를 도출하였다.

• 대한한의학회지
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• 제44권4호
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• pp.136-149
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• 2023

Objectives: Facial diagnosis is an important part of clinical diagnosis in traditional East Asian Medicine. In this paper, we proposed a model to quantitatively classify cold sensitivity using a fully automated facial image analysis system. Methods: We investigated cold sensitivity in 452 subjects. Cold sensitivity was determined using a questionnaire and the Cold Pattern Score (CPS) was used for analysis. Subjects with a CPS score below the first quartile (low CPS group) belonged to the cold non-sensitivity group, and subjects with a CPS score above the third quartile (high CPS group) belonged to the cold sensitivity group. After splitting the facial images into train/validation/test sets, the train and validation set were input into a convolutional neural network to learn the model, and then the classification accuracy was calculated for the test set. Results: The classification accuracy of the low CPS group and high CPS group using facial images in all subjects was 76.17%. The classification accuracy by sex was 69.91% for female and 62.86% for male. It is presumed that the deep learning model used facial color or facial shape to classify the low CPS group and the high CPS group, but it is difficult to specifically determine which feature was more important. Conclusions: The experimental results of this study showed that the low CPS group and the high CPS group can be classified with a modest level of accuracy using only facial images. There was a need to develop more advanced models to increase classification accuracy.

• Korean Journal of Radiology
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• 제22권7호
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• pp.1203-1212
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• 2021

Objective: To investigate the diagnostic accuracy and complications of cone-beam CT-guided percutaneous transthoracic needle biopsy (PTNB) of juxtaphrenic lesions and identify the risk factors for diagnostic failure and complications. Materials and Methods: In total, 336 PTNB procedures for lung lesions (mean size ± standard deviation [SD], 4.3 ± 2.3 cm) abutting the diaphragm in 326 patients (189 male and 137 female; mean age ± SD, 65.2 ± 11.4 years) performed between January 2010 and December 2014 were included. The accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the PTNB procedures for the diagnosis of malignancy were measured based on the intention-to-diagnose principle. The risk factors for diagnostic failures and complications were evaluated using logistic regression analysis. Results: The accuracy, sensitivity, specificity, PPV, and NPV were 92.7% (293/316), 91.3% (219/240), 91.4% (74/81), 96.9% (219/226), and 77.9% (74/95), respectively. There were 23 diagnostic failures (7.3%), and lesion sizes ≤ 2 cm (p = 0.045) were the only significant risk factors for diagnostic failure. Complications occurred in 98 cases (29.2%), including 89 cases of pneumothorax (26.5%) and 7 cases of hemoptysis (2.1%). The multivariable analysis showed that old age (> 65 years) (p = 0.002), lesion size of ≤ 2 cm (p = 0.003), emphysema (p = 0.006), and distance from the pleura to the target lesion (> 2 cm) (p = 0.010) were significant risk factors for complications. Conclusion: The diagnostic accuracy of cone-beam CT-guided PTNB of juxtaphrenic lesions for malignancy was fairly high, and the target lesion size was the only significant predictor of diagnostic failure. Complications of cone-beam CT-guided PTNB of juxtaphrenic lesions occurred at a reasonable rate.

• 분석과학
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• 제29권6호
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• pp.261-268
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• 2016

TXRF는 시료전처리 없이 분말상 시료의 정량분석이 가능하여 토양시료를 효율적으로 분석할 수 있다. 기존의 내부표준법을 이용한 분석법은 매질 효과 및 형광신호의 겹침으로 인한 간섭 효과로 인해 정확도가 떨어진다. 이를 개선하기 위해 외부표준법을 적용하여 용액화한 토양시료와 분말상 토양시료를 분석하였다. 용액화한 토양시료의 경우 개별표준물질로 만든 표준용액으로 작성한 검량선으로 분석하였는데, 내부 및 외부표준법 간 유의미한 차이가 없었다. 반면 분말상 토양시료로 부유용액을 만들어 검량선을 작성한 후 이를 이용하여 분말상 토양시료를 분석한 결과, 전반적으로 외부표준법을 적용한 결과가 내부표준법의 그것에 비해 정확도가 높았다. 두 가지 표준토양시료로 교차검증한 결과, Al, Fe, K, Ca, Ti, Ba, Mn, Sr, Rb, Cu 등 10개의 원소들에 대해 ${\pm}20%$ 내외의 상대오차가 측정되었다.

• 한국멀티미디어학회논문지
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• 제18권4호
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• pp.524-532
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• 2015

All data created in BigData times is included potentially meaning and correlation in data. A variety of data during a day in all society sectors has become created and stored. Research areas in analysis and grasp meaning between data is proceeding briskly. Especially, accuracy of meaning prediction and data imbalance problem between data for analysis is part in course of something important in data analysis field. In this paper, we proposed data prediction model based on data weights and neural network using R for meaning analysis between data. Proposed data prediction model is composed of classification model and analysis model. Classification model is working as weights application of normal distribution and optimum independent variable selection of multiple regression analysis. Analysis model role is increased prediction accuracy of output variable through neural network. Performance evaluation result, we were confirmed superiority of prediction model so that performance of result prediction through primitive data was measured 87.475% by proposed data prediction model.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2007년도 추계학술대회 논문집
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• pp.271-274
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• 2007

Housing and insulation of electrical connectors are made of plastic resin by injection molding process. The metallic inner tube is easily deformed by high pressure during the injection process. In order to prevent deformation of the inner tube, it is desirable to simulate it by structural CAE analysis. However, it takes a long time to calculate the stress- of the part by commercially available injection molding CAE software with sufficient accuracy. In this study, structural analysis in conjunction with injection molding analysis is proposed to improve accuracy of the structural analysis. Pressure distribution on the inner tube is predicted by the injection molding CAE analysis, and then mapped onto the mesh of structural analysis by a mapping algorithm developed in this study. As a result reliable result is obtained in shorter time than the conventional method. The predicted deformation of the inner tube is compared with the actual part after experiment.

• Nuclear Engineering and Technology
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• 제54권3호
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• pp.1109-1114
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• 2022

The SMART (System-integrated Modular Advanced ReacTor) is an integral-type small modular reactor developed by KAERI (Korea Atomic Energy Research Institute). This paper discusses the feasibility and applicability of a 3D-based equivalent model using dynamic condensation method for seismic analysis of a SMART control rod drive mechanism. The equivalent model is utilized for complicated seismic analysis during the design of the SMART. While the 1D-based beam-mass equivalent model is widely used in the nuclear industry for its calculation efficiency, the 3D-based equivalent model is suggested for the seismic analysis of SMART to enhance the analysis accuracy of the 1D-based equivalent model while maintaining its analysis efficiency. To verify the suggested model, acceleration response spectra from seismic analysis based on the 3D-based equivalent model are compared to those from the 1D-based beam-mass equivalent model and experiments. The accuracy and efficiency of the dynamic condensation method are investigated by comparison to analysis results based on the conventional modeling methodology used for seismic analysis.

• 한국지리정보학회지
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• 제11권1호
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• pp.80-89
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• 2008

위성영상을 이용한 지도제작 분야는 입체영상 획득이 가능한 SPOT 위성이 발사되면서 이에 대한 정량적인 분석이 가능해졌다. 특히, 고해상도 위성영상은 항공사진촬영이 불가능하여 대축척 지도제작이 곤란한 지역 또는 지상기준점 측량이 불가능한 지역에 대한 수치지도 제작 분야에 있어서 효율적인 방법으로 주목을 받고 있다. 이에 본 연구에서는 미국 국가지형공간정보국(NGA;The National Geospatial-Intelligence Agency)에서 제공하는 정사영상 자료를 이용하여 지역적 특성을 고려한 지형정보를 추출하고 이에 대한 평면위치 정확도를 분석하였다. 이를 위해 일정한 크기로 타일링된 정사영상에 대해 국토지리정보원에서 제공하는 축척 1:5000 수치지도를 기준으로 지역적 특성에 따른 정확도를 평가하였고 이를 바탕으로 비접근 지역의 지형정보 획득을 위한 기 구축 정사영상의 활용 가능성을 제시하고자 하였으며 비접근 및 난접근 지역에서의 지상기준점 획득에 대한 제한을 극복하는 수단으로 본 연구의 결과를 활용하고자 하였다.

• 말소리와 음성과학
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• 제10권1호
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• pp.75-81
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• 2018

Diplophonia is generally defined as the perception of more than one fundamental frequency component in a voice. Its perceptual aspect has traditionally been used to evaluate diplophonia because the perceptions can be easily evaluated, but there are limitations in the validity of the reliability of the intra- and inter-raters, examination situation, and variation of voice sample. Therefore, the purpose of this study is to confirm the reliability and accuracy of auditory perceptual evaluation by comparing non-invasive indirect assessment methods (sound waveform and EGG analysis), and to identify their usefulness with diplophonia. A total of 28 diplophonic voices and 39 non-periodic voices were assessed. Three raters assessed the diplophonia by performing an auditory perception evaluation and identifying the quasi-periodic perturbations of the acoustic waveform and EGG. Among the three discrimination methods, intra- and inter-rater reliability, sensitivity, specificity, accuracy, positive likelihood ratio, and negative likelihood ratio were examined, and the McNemar test was performed to compare the discriminant agreement. The accuracy of the auditory perceptual evaluation (86.57%) was not significantly different from that of sound waveform acoustic (88.06%), but it was significantly different from that of EGG (83.33%). The reading time (6.02 s) for the auditory perceptual evaluation was significantly different from that for sound waveform analysis (30.15 s) and EGG analysis (16.41 s). In the discrimination of diplophonia, auditory perceptual evaluation has sufficient reliability and accuracy as compared to sound waveform and EGG. Since immediate feedback is possible, auditory perceptual evaluation is more convenient. Therefore, it can continue to be used as a tool to discriminate diplophonia in clinical practice.

• Structural Engineering and Mechanics
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• 제45권5호
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• pp.595-611
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• 2013

This paper aims to compare three collocation point methods associated with the odd order stochastic response surface method (SRSM) in a systematical and quantitative way. The SRSM with the Hermite polynomial chaos is briefly introduced first. Then, three collocation point methods, namely the point method, the root method and the without origin method underlying the odd order SRSMs are highlighted. Three examples are presented to demonstrate the accuracy and efficiency of the three methods. The results indicate that the condition that the Hermite polynomial information matrix evaluated at the collocation points has a full rank should be satisfied to yield reliability results with a sufficient accuracy. The point method and the without origin method are much more efficient than the root method, especially for the reliability problems involving a large number of random variables or requiring complex finite element analysis. The without origin method can also produce sufficiently accurate reliability results in comparison with the point and root methods. Therefore, the origin often used as a collocation point is not absolutely necessary. The odd order SRSMs with the point method and the without origin method are recommended for the reliability analysis due to their computational accuracy and efficiency. The order of SRSM has a significant influence on the results associated with the three collocation point methods. For normal random variables, the SRSM with an order equaling or exceeding the order of a performance function can produce reliability results with a sufficient accuracy. The order of SRSM should significantly exceed the order of the performance function involving strongly non-normal random variables.