• Journal of the Korea Institute of Building Construction
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• v.22 no.6
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• pp.689-700
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• 2022

Layout work for building structures requires high precision to construct structural elements in the correct location. However, the accuracy and precision of the layout position are affected by the worker's skill, and productivity can be reduced when there is information loss and error. To solve this problem, it is necessary to automate the overall layout operation and introduce information technology, and layout process automation using construction robots can be an effective means of doing this. This study develops a prototype of an automated layout robot for building structures and evaluates its basic performance. The developed robot is largely composed of driving, marking, sensing, and control units, and is designed to enable various driving methods, and movement and rotation of the marking unit in consideration of the environment on structural work. The driving and marking performance experiments showed satisfactory performance in terms of driving distance error and marking quality, while the need for improvement in terms of some driving methods and marking precision was confirmed. Based on the results of this study, we intend to continuously improve the robot's performance and establish an automation system for overall layout work process.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.903-911
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• 2022

Groundwater, one of the resources for supplying water, fluctuates in water level due to various natural factors. Recently, research has been conducted to predict fluctuations in groundwater levels using Artificial Neural Network (ANN). Previously, among operators in ANN, Gradient Descent (GD)-based Optimizers were used as Optimizer that affect learning. GD-based Optimizers have disadvantages of initial correlation dependence and absence of solution comparison and storage structure. This study developed Gradient Descent combined with Harmony Search (GDHS), a new Optimizer that combined GD and Harmony Search (HS) to improve the shortcomings of GD-based Optimizers. To evaluate the performance of GDHS, groundwater level at Icheon Yullhyeon observation station were learned and predicted using Multi Layer Perceptron (MLP). Mean Squared Error (MSE) and Mean Absolute Error (MAE) were used to compare the performance of MLP using GD and GDHS. Comparing the learning results, GDHS had lower maximum, minimum, average and Standard Deviation (SD) of MSE than GD. Comparing the prediction results, GDHS was evaluated to have a lower error in all of the evaluation index than GD.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.274-284
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• 2022

To use kenaf (Hibiscus cannabinus L.) as a fiber and livestock feed, a high-yielding variety needs to be identified. For this, accurate phenotyping of plant height is required for this breeding purpose due to the strong relationship between plant height and yield. Plant height can be estimated using RGB images from unmanned aerial vehicles (UAV-RGB) and photogrammetry based on Structure from Motion (SfM) algorithms. In kenaf, accurate measurement of height is limited because kenaf stems have high flexibility and its height is easily affected by wind, growing up to 3 ~ 4 m. Therefore, we aimed to identify a method suitable for the accurate estimation of plant height of kenaf and investigate the feasibility of using the UAV-RGB-derived plant height map. Height estimation derived from UAV-RGB was improved using multi-point calibration against the five different wooden structures with known heights (30, 60, 90, 120, and 150 cm). Using the proposed method, we analyzed the variation in temporal height of 23 kenaf cultivars. Our results demontrated that the actual and estimated heights were reliably comparable with the coefficient of determination (R²) of 0.80 and a slope of 0.94. This method enabled the effective identification of cultivars with significantly different heights at each growth stages.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.87-96
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• 2022

The traffic vulnerable, including elderly pedestrians, have a relatively low walking speed and slow cognitive response time due to reduced physical ability. Although a smart crossing system has been developed and operated to improve problem, it is difficult to operate a signal that reflects the appropriate walking speed for each pedestrian. In this study, a neural network model and a multiple regression model-based traversing speed estimation model were developed using image information collected in an area with a high percentage of traffic vulnerability. to support the provision of optimal walking signals according to real-time traffic weakness. actual traffic data collected from the urban traffic network of Paju-si, Gyeonggi-do were used. The performance of the model was evaluated through seven selected indicators, including correlation coefficient and mean absolute error. The multiple linear regression model had a correlation coefficient of 0.652 and 0.182; the neural network model had a correlation coefficient of 0.823 and 0.105. The neural network model showed higher predictive power.

• Journal of the Korean Society of Radiology
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• v.17 no.2
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• pp.191-199
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• 2023

This study aimed to propose minimized radiation doses with an optimized abdomen x-ray image, which realizes a Deep Blind Image Super-Resolution Generative adversarial network (BSRGAN) technique. Entrance surface doses (ESD) measured were collected by changing exposure conditions. In the identical exposures, abdominal images were acquired and were processed with the BSRGAN. The images reconstructed by the BSRGAN were compared to a reference image with 80 kVp and 320 mA, which was evaluated by mean squared error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM). In addition, signal profile analysis was employed to validate the effect of the images reconstructed by the BSRGAN. The exposure conditions with the lowest MSE (about 0.285) were shown in 90 kVp, 125 mA and 100 kVp, 100 mA, which decreased the ESD in about 52 to 53% reduction), exhibiting PSNR = 37.694 and SSIM = 0.999. The signal intensity variations in the optimized conditions rather decreased than that of the reference image. This means that the optimized exposure conditions would obtain reasonable image quality with a substantial decrease of the radiation dose, indicating it could sufficiently reflect the concept of As Low As Reasonably Achievable (ALARA) as the principle of radiation protection.

• Journal of the Korean Geotechnical Society
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• v.25 no.10
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• pp.31-40
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• 2009

As the measurement of strain-gage type cone penetrometer is influenced by the temperature change during penetration, the temperature is a factor producing an error of the cone tip resistance. In this study, the 0.5 mm diameter temperature transducer and 7 mm diameter micro cone penetrometer are manufactured by using FBG sensors to evaluate the effect of temperature on the cone tip resistance. Design concepts include the cone configuration, sensor installation and the temperature compensation process. The test shows that the tip resistance measured by strain gauge is affected by the temperature change. The error of the tip resistance increases with an increase in temperature change, while the temperature effect on the tip resistance of FBG cone is effectively compensated by using FBG temperature transducer. Temperature compensated tip resistance of the strain gauge cone shows the good matched profile with FBG cone which performs real-time temperature compensation during penetration. This study demonstrates that the temperature compensation by using FBG sensor is an effective method to produce the more reliable cone tip resistance.

• Journal of Internet of Things and Convergence
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• v.9 no.3
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• pp.93-98
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• 2023

In this paper, an artificial neural network based on simulated annealing was constructed. The mapping relationship between the parameters of micro-scaled flow channels electrochemical machining and the channel shape was established by training the samples. The depth and width of micro-scaled flow channels electrochemical machining on stainless steel surface were predicted, and the flow channels experiment was carried out with pulse power supply in NaNO3 solution to verify the established network model. The results show that the depth and width of the channel predicted by the simulated annealing artificial neural network with "4-7-2" structure are very close to the experimental values, and the error is less than 5.3%. The predicted and experimental data show that the etching degree in the process of channels electrochemical machining is closely related to voltage and current density. When the voltage is less than 5V, a "small island" is formed in the channel; When the voltage is greater than 40V, the lateral etching of the channel is relatively large, and the "dam" between the channels disappears. When the voltage is 25V, the machining morphology of the channel is the best.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3C
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• pp.201-207
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• 2006

Soil tests are generally conducted using a membrane to measure a pore water pressure. However, it has also been recognized that the membrane penetrates into the specimen by the change of the confining pressure, and it results in the erroneous measurement in the pore water pressure and the volumetric strain. This study examined the effectiveness of the correction equation of the membrane penetration on the basis of the experimental data acquired during the isotropic unloading and the cyclic shear process using the hollow cylindrical shear test equipment. The results showed that the membrane penetration by the correction equation could be overestimated when the mean effective stress was lower than 20kPa in this study. The limitations originated from the sudden increase near the zero effective stress, and in order to prevent the overestimation in low effective stress condition, the use of the constant a was proposed in this study. Furthermore, the correction equation for the membrane penetration had to be applied carefully when the initial relative density was high and the density changes were occurred by the relocation of the soil particle by the liquefaction.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1A
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• pp.1-8
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• 2009

Stay cable is easily exposed to vibration induced rainy wind effects. There are some problems for not only unexpected vibration but also well-known vibration. An outbreak of displacement by the said effects brings damages such as over-tension of cables and barriers, fatigue of anchorages and dampers, and additional shear force variation of stiffening girders. This study suggests analytic methodology for dynamic tension variation of cables and shear force variation of stiffening girders. Additionally this study announces with dynamic problems for cable stayed bridge briefly. To realize this subject, we divide restoring force into chord component and normal component and then make up the differential equations which can satisfy physical phenomenon for each component. Finally we apply adequate functions such as sinusoidal and parabola in order to reduce these differential equations. Therefore we can meet with good results through a series of above process. As a remarkable result, CIP recommendations (2002) give inadequate solution with over 10% error. However it gives very good solution if parts of our study are reflected at the said recommendations. The fact means that CIP recommendations (2002) well-known as international standard of stay cables are not even concern about this subject yet. For verification of this study, F.E. analysis using E.C.C. with external forces was fulfilled, and the accuracy and conciseness of this study were shown.

• Journal of the Korean Society of Radiology
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• v.17 no.7
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• pp.1091-1097
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• 2023

Bolus is used in radiation therapy to prescribe an even dose to the tumor when the skin surface is inclined or has irregularities. At this time, the dose to the skin surface increases. Due to the patient's unique body structure and irregular skin, voids may occur between the bolus and the skin, which may reduce the accuracy of treatment. Therefore, in this study, the existing bolus and the self-produced bolus through 3D printing were applied to the nasal area, and the difference between the surface dose after treatment plan and the dose directly measured with an Optically Stimulated luminescence(OSL) dosimeter was compared to the existing bolus. The bolus rate was 97%, PLA 100.33%, ePETELA 75A 100.53%, and ePETELA 85A 100.36%. It was confirmed that there was little error in the measurement values and treatment plan values for each material. In addition, compared to when applying a conventional bolus, a difference of -3% to +0.5% for a 3D printed bolus can be confirmed, so a customized bolus produced through 3D printing can complement the shortcomings of the existing bolus. It is believed that there will be.