• Title/Summary/Keyword: Error level

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Closing Analysis of Symmetric Steel Cable-stayed Bridges and Estimation of Construction Error (대칭형 강 사장교의 폐합해석과 시공오차의 예측)

  • Lee, Min Kwon;Lee, Hae Sung
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.1A
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    • pp.55-65
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    • 2006
  • This paper presents the closing analysis of a symmetric steel cable-stayed bridge erected by a free cantilever method. Two independent structural systems are formed before the closing procedure of a bridge is performed, and thus the compatibility conditions for vertical displacement and rotational angle are not satisfied at the closing section without the application of proper sectional forces. Since, however, it is usually impossible to apply sectional forces at the closing section, the compatibility conditions should be satisfied by proper external forces that can be actually applicable to a bridge. Unstrained lengths of selected cables and the pull-up force of a derrick crane are adjusted to satisfy nonlinear compatibility conditions, which are solved iteratively by the Newton-Raphson method. Cable members are modeled by the elastic catenary cable elements, and towers and main girders are discretized by linear 3-D frame elements. The sensitivities of displacement with respect to the unstrained lengths of selected cables and the pull-up force of the derrick crane are evaluated by the direct differentiation of the equilibrium equation. A Monte-Carlo simulation approach is proposed to estimate expected construction errors for a given confidence level. The proposed method is applied to the second Jindo Grand Bridge to demonstrate its validity and effectiveness.

Automated Satellite Image Co-Registration using Pre-Qualified Area Matching and Studentized Outlier Detection (사전검수영역기반정합법과 't-분포 과대오차검출법'을 이용한 위성영상의 '자동 영상좌표 상호등록')

  • Kim, Jong Hong;Heo, Joon;Sohn, Hong Gyoo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.4D
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    • pp.687-693
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    • 2006
  • Image co-registration is the process of overlaying two images of the same scene, one of which represents a reference image, while the other is geometrically transformed to the one. In order to improve efficiency and effectiveness of the co-registration approach, the author proposed a pre-qualified area matching algorithm which is composed of feature extraction with canny operator and area matching algorithm with cross correlation coefficient. For refining matching points, outlier detection using studentized residual was used and iteratively removes outliers at the level of three standard deviation. Throughout the pre-qualification and the refining processes, the computation time was significantly improved and the registration accuracy is enhanced. A prototype of the proposed algorithm was implemented and the performance test of 3 Landsat images of Korea. showed: (1) average RMSE error of the approach was 0.435 pixel; (2) the average number of matching points was over 25,573; (3) the average processing time was 4.2 min per image with a regular workstation equipped with a 3 GHz Intel Pentium 4 CPU and 1 Gbytes Ram. The proposed approach achieved robustness, full automation, and time efficiency.

Prediction of Ultimate Load of Drilled Shafts Embedded in Weathered Rock by Extrapolation Method (외삽법을 이용한 풍화암에 근입된 현장타설말뚝의 극한하중 예측)

  • Jung, Sung Jun;Lee, Sang In;Jeon, Jong Woo;Kim, Myoung Mo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.4C
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    • pp.145-151
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    • 2009
  • In general, a drilled shaft embedded in weathered rock has a large load bearing capacity. Therefore, most of the load tests are performed only up to the load level that confirms the pile design load capacity, and stopped much before the ultimate load of the pile is attained. If a reliable ultimate load value can be extracted from the premature load test data, it will be possible to greatly improve economic efficiency as well as pile design quality. The main purpose of this study is to propose a method for judging the reliability of the ultimate load of piles that is obtained from extrapolated load test data. To this aim, ten static load test data of load-displacement curves were obtained from testing of piles to their failures from 3 different field sites. For each load-displacement curve, loading was assumed as 25%, 50%, 60%, 70%, 80%, and 90% of the actual pile bearing capacity. The limited known data were then extrapolated using the hyperbolic function, and the ultimate capacity was re-determined for each extrapolated data by the Davisson method (1972). Statistical analysis was performed on the reliability of the re-evaluated ultimate loads. The results showed that if the ratio of the maximum-available displacement to the predicted displacement exceeds 0.6, the extrapolated ultimate load may be regarded as reliable, having less than a conservative 20% error on average. The applicability of the proposed method of judgment was also verified with static load test data of driven piles.

Modeling for Egg Price Prediction by Using Machine Learning (기계학습을 활용한 계란가격 예측 모델링)

  • Cho, Hohyun;Lee, Daekyeom;Chae, Yeonghun;Chang, Dongil
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.15-17
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    • 2022
  • In the aftermath of the avian influenza that occurred from the second half of 2020 to the beginning of 2021, 17.8 million laying hens were slaughtered. Although the government invested more than 100 billion won for egg imports as a measure to stabilize prices, the effort was not that easy. The sharp volatility of egg prices negatively affected both consumers and poultry farmers, so measures were needed to stabilize egg prices. To this end, the egg prices were successfully predicted in this study by using the analysis algorithm of a machine learning regression. For price prediction, a total of 8 independent variables, including monthly broiler chicken production statistics for 2012-2021 of the Korean Poultry Association and the slaughter performance of the national statistics portal (kosis), have been selected to be used. The Root Mean Square Error (RMSE), which indicates the difference between the predicted price and the actual price, is at the level of 103 (won), which can be interpreted as explaining the egg prices relatively well predicted. Accurate prediction of egg prices lead to flexible adjustment of egg production weeks for laying hens, which can help decision-making about stocking of laying hens. This result is expected to help secure egg price stability.

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Effects of Occupational Trauma Exposure on Brain Functional Connectivity in Firefighters With Subclinical Post-Traumatic Stress Symptoms: A Resting-State Functional Magnetic Resonance Imaging Study (직업적 외상 노출이 역치 하 외상 후 스트레스 증상을 보이는 소방공무원의 뇌 기능적 연결성에 미치는 영향: 휴지기 기능적 자기공명영상 연구)

  • Heo, Yul;Bang, Minji;Lee, Sang-Hyuk;Lee, Kang Soo
    • Anxiety and mood
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    • v.18 no.2
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    • pp.39-47
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    • 2022
  • Objective : This study investigated brain functional connectivity in male firefighters who showed subclinical post-traumatic stress disorder (PTSD) symptoms. Methods : We compared the data of 17 firefighters who were not diagnosed with PTSD and 18 healthy controls who had no trauma exposure. The following instruments were applied to assess psychiatric symptoms: Korean version of the Post-traumatic stress disorder Checklist for DSM-5 (PCL-5-K), Beck Depression Inventory-II (BDI-II), Beck Anxiety Inventory (BAI). For all subjects, functional magnetic resonance imaging was performed, and functional connectivity was compared between the two groups (family-wise error-corrected p<0.05). Additionally, correlations between psychiatric symptoms and functional connectivity were explored. Results : The following connectivity was higher than that of healthy controls: 1) the central opercular cortex-superior temporal gyrus, 2) planum polare-parahippocampal gyrus, 3) angular gyrus-amygdala, and 4) temporal fusiform cortex-parahippocampal gyrus. The functional connectivity of 1) the lateral occipital cortex-inferior temporal gyrus, 2) superior parietal lobule-caudate, and 3) middle temporal gyrus-thalamus were lower in firefighters. In firefighters, the connectivity of the planum polare-parahippocampal gyrus showed a negative correlation with the severity of arousal symptoms (rho=-0.586, p=0.013). The connectivity of the middle temporal gyrus-thalamus showed a positive correlation with the severity of intrusion (rho=0.552, p=0.022) and arousal symptoms (rho=0.619, p=0.008). The connectivity of the temporal fusiform cortex-parahippocampal gyrus was negatively correlated with intrusion (rho=-0.491, p=0.045) and arousal (rho=-0.579, p=0.015). Conclusion : Our results indicate that the brain functional connectivity is associated with occupational trauma exposure in firefighters without PTSD. Therefore, this study provides evidence that close monitoring and early intervention are important for firefighters with traumatic experience even at a subthreshold level.

Development and Validation of a Deep Learning System for Segmentation of Abdominal Muscle and Fat on Computed Tomography

  • Hyo Jung Park;Yongbin Shin;Jisuk Park;Hyosang Kim;In Seob Lee;Dong-Woo Seo;Jimi Huh;Tae Young Lee;TaeYong Park;Jeongjin Lee;Kyung Won Kim
    • Korean Journal of Radiology
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    • v.21 no.1
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    • pp.88-100
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    • 2020
  • Objective: We aimed to develop and validate a deep learning system for fully automated segmentation of abdominal muscle and fat areas on computed tomography (CT) images. Materials and Methods: A fully convolutional network-based segmentation system was developed using a training dataset of 883 CT scans from 467 subjects. Axial CT images obtained at the inferior endplate level of the 3rd lumbar vertebra were used for the analysis. Manually drawn segmentation maps of the skeletal muscle, visceral fat, and subcutaneous fat were created to serve as ground truth data. The performance of the fully convolutional network-based segmentation system was evaluated using the Dice similarity coefficient and cross-sectional area error, for both a separate internal validation dataset (426 CT scans from 308 subjects) and an external validation dataset (171 CT scans from 171 subjects from two outside hospitals). Results: The mean Dice similarity coefficients for muscle, subcutaneous fat, and visceral fat were high for both the internal (0.96, 0.97, and 0.97, respectively) and external (0.97, 0.97, and 0.97, respectively) validation datasets, while the mean cross-sectional area errors for muscle, subcutaneous fat, and visceral fat were low for both internal (2.1%, 3.8%, and 1.8%, respectively) and external (2.7%, 4.6%, and 2.3%, respectively) validation datasets. Conclusion: The fully convolutional network-based segmentation system exhibited high performance and accuracy in the automatic segmentation of abdominal muscle and fat on CT images.

A Study on Back Analysis Settlement Prediction of Soft Ground Using Numerical Analysis and Measurement Data (수치해석과 계측데이터를 이용한 연약지반의 역해석 침하 예측에 관한 연구)

  • Sangju Jeon;Hyeok Seo;Daehyeon Kim
    • Journal of the Korean Geosynthetics Society
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    • v.23 no.2
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    • pp.9-17
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    • 2024
  • When constructing on soft ground, managing ground settlement and safety is crucial. However, there often exists a significant disparity between the actual behavior of the ground and the design plans. In this study, we aimed to compare and analyze the difference between the predicted settlement based on theoretical formulas and the measured settlement during construction, in order to predict settlement. For this purpose, we analyzed settlement data from 18 construction sites. The results indicated that the back analysis settlement values were similar to the measured settlement values, whereas the design settlement values were significantly higher compared to the measured settlement values. Specifically, the design settlement values were 1.2 to 1.4 times higher than those derived from back analysis using measured values. The RMSE analysis revealed a value of 0.6212m for the design settlement and 0.1697m for the back analysis settlement. The difference between the back analysis settlement and the measured settlement was more than 70% lower than the difference between the design settlement and the measured settlement. This indicates that the back analysis settlement values exhibit lower error rates compared to the design settlement values.

Analysis of Hazard Factors for Domestic General Purpose Ventilator using Usability Assessment (사용적합성 평가를 적용한 국산 범용인공호흡기의 위험요인 분석)

  • Gyeongmin Kwon;Seung hee Kim;You Rim Kim;Won Seuk Jang
    • Journal of Biomedical Engineering Research
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    • v.45 no.1
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    • pp.10-19
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    • 2024
  • The purpose of this study is to conduct a summative evaluation of the usability of a general-purpose ventilator to determine whether it can be used for its intended purpose in the intended environment by the intended user and to find possible errors in use. The importance of ventilators has increased due to the accelerated aging of the population and the impact of the pandemic. In addition, patients who require ventilators are often in critical condition, so even a small error in use can be fatal. Therefore, it is important to ensure that the ventilator has sufficient stability and can be used satisfactorily without inconvenience to the user. In this study, we conducted a usability test with 17 respiratory nurses with more than 3 years of experience using the ventilator. We analyzed the task success rate, satisfaction, and opinions of the intended users while going through a total of 17 scenarios. Satisfaction was captured through an ASQ questionnaire and subjective opinions were captured through a detailed opinion questionnaire. The results showed a high level of satisfaction with an average score of 6.3 for the use scenarios. Evaluators expressed satisfaction with the overall visibility and versatility of the features, but noted that improvements were needed for calibration tasks with low task success rates. As the calibration method is different from other equipment, it was suggested that specific explanations of the calibration method and the picture that appears when calibrating are needed, and that if relevant training is provided, the equipment can be used without problems. If the usability evaluation is not limited to securing efficiency and satisfaction from the intended users, but also continuously receives feedback from users to prepare for use in emergency environments such as pandemic situations, it will be very helpful to seize opportunities such as emergency authorization in future situations, and ultimately contribute to patient safety by reducing use errors.

Analysis of Optimal Index for Heat Morbidity (온열질환자 예측을 위한 최적의 지표 분석)

  • Sanghyuck Kim;Minju Song;Seokhwan Yun;Dongkun Lee
    • Journal of Environmental Impact Assessment
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    • v.33 no.1
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    • pp.9-17
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    • 2024
  • The purpose of this study is to select and predict optimal heatwave indices for describing and predicting heat-related illnesses. Regression analysis was conducted using Heat-related illness surveillance system data for a number of heat-related illnesses and meteorological data from the Korea Meteorological Administration's Automatic Weather Station (AWS) for the period from 2021 to 2023. Daily average temperature, daily maximum temperature, daily average Wet Bulb Globe Temperature (WBGT), and daily maximum WBGT values were calculated and analyzed. The results indicated that among the four indicators, the daily maximum WBGT showed the highest suitability with an R2 value of 0.81 and RMSE of 0.98, with a threshold of 29.94 Celsius. During the entire analysis period, there were a total of 91 days exceeding this threshold, resulting in 339 cases of heat-related illnesses. Predictions of heat-related illness cases from 2021 to 2023 using the regression equation for daily maximum WBGT showed an accuracy with less than 10 cases of error annually, demonstrating a high level of precision. Through continuous research and refinement of data and analysis methods, it is anticipated that this approach could contribute to predicting and mitigating the impact of heatwaves.

The Measurement Algorithm for Microphone's Frequency Character Response Using OATSP (OATSP를 이용한 마이크로폰의 주파수 특성 응답 측정 알고리즘)

  • Park, Byoung-Uk;Kim, Hack-Yoon
    • The Journal of the Acoustical Society of Korea
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    • v.26 no.2
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    • pp.61-68
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    • 2007
  • The frequency response of a microphone, which indicates the frequency range that a microphone can output within the approved level, is one of the most significant standards used to measure the characteristics of a microphone. At present, conventional methods of measuring the frequency response are complicated and involve the use of expensive equipment. To complement the disadvantages, this paper suggests a new algorithm that can measure the frequency response of a microphone in a simple manner. The algorithm suggested in this paper generates the Optimized Aoshima's Time Stretched Pulse(OATSP) signal from a computer via a standard speaker and measures the impulse response of a microphone by convolution the inverse OATSP signal and the received by the microphone to be measured. Then, the frequency response of the microphone to be measured is calculated using the signals. The performance test for the algorithm suggested in the study was conducted through a comparative analysis of the frequency response data and the measures of frequency response of the microphone measured by the algorithm. It proved that the algorithm is suitable for measuring the frequency response of a microphone, and that despite a few errors they are all within the error tolerance.