• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.2
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• pp.130-134
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• 2019

In this paper, a laser-based non-contact load cell is newly developed for measuring forces in prestressed concrete tendons. First, alumina particles have been sprayed onto an empty load cell which has no strain gauges on it, and the layer has been used as a passive stress sensor. Then, the spectral shifts in fluorescence spectroscopy have been measured using a laser-based spectroscopic system under various force levels, and it has been found that the relation of applied force and spectral shift is linear in a lab-scale test. To validate the field applicability of the customized load cell, a full-scale prestressed concrete specimen has been constructed in a yard. During the field test, it was, however, found that the coating surface has irregular stress distribution. Therefore, the location of a probe has to be fixed onto the customized load cell for using the coating layer as a passive stress sensor. So, a prototype customized load cell has been manufactured, which consists of a probe mount on its casing. Then, by performing lab-scale uniaxial compression tests with the prototype load cell, a linear relation between compression stress and spectrum shift at a specific point where laser light had been illuminated has been detected. Thus, it has a high possibility to use the prototype load cell as a force sensor of prestressed concrete tendons.

• Journal of the Korean Society of Radiology
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• v.13 no.4
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• pp.661-666
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• 2019

Diverging collimators is used to obtain reduced images of an object, or to detect a wide filed-of-view (FOV) using a small gamma camera. In the gamma camera using the diverging collimators, the block scintillator, and the pixel scintillator array, gamma rays are obliquely incident on the scintillator surface when the source is located the periphery of the FOV. Therefore, the spatial resolution is reduced because it is obliquely detected in depth direction. In this study, we designed a novel system to improve the spatial resolution in the periphery of the FOV. Using a tapered crystal array to configure the scintillation pixels to coincide with the angle of the collimator's hole allows imaging to one scintillation pixel location, even if events occur to different depths. That is, even if is detected at various points in the diagonal direction, the gamma rays interact with one crystal pixel, so resolution does not degrade. The resolution of the block scintillator and the tapered crystal array was compared and evaluated through Geant4 Application for Tomographic Emission (GATE) simulation. The spatial resolution of the obtained image was 4.05 mm in the block scintillator and 2.97 mm in the tapered crystal array. There was a 26.67% spatial resolution improvement in the tapered crystal array compared to the block scintillation.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.4
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• pp.425-433
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• 2019

In this paper, the RCS analysis of the 10m unmanned surface vehicles was performed, and the factors of RCS increase were analyzed. Modeling techniques by transforming a geometric shape can reduce the RCS area, which can be used to develop stealth unmanned surface vehicles. In order to reduce the RCS, the existing Top Mast part was moved 1m to the tail part, the 5 degree tilt angle was moved below 0.5 m, and additional guided walls were installed to minimize the influence on the center and surrounding corner reflecting structures. As a result of comparing and analyzing the RCS analysis value with the existing model, it can be seen that the reduced countermeasure model is -3.79 dB lower than the existing model for all elevations. In particular, it can be seen that the strong scattering phenomenon is substantially removed in the region except the sacrificial angle region. In addition, it can be seen that in the case of -5m to 2m where the guide wall is added, the reflected signal is improved up to 20 to 40 dB or more, so that it does not appear on the 2D ISAR image. RCS analysis of unmanned surface vehicles explained the process of analyzing and identifying problem location through distance profile analysis and ISAR image analysis.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.30 no.6
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• pp.286-297
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• 2018

In the present study, wave measurements at KOGA-W01 were analyzed and then the numerical wind waves simulations have been conducted to investigate the characteristics of wind waves in the Yellow sea. According to the present analysis, even though the location of the wave stations are close to the coastal region, the deep water waves are prevailed due to the short fetch length. Chun and Ahn's (2017a, b) numerical model has been extended to the Yellow Sea in this study. The effects of tide and tidal currents should be included in the model to accommodate the distinctive effect of large tidal range and tidal current in the Yellow Sea. The wave hindcasting results were compared with the wave measurements collected KOGA-W01 and Kyeockpo. The comparison shows the reasonable agreements between wave hindcastings and measured data, however the model significantly underestimate the wave period of swell waves from the south due to the narrow computational domain. Despite the poorly prediction in the significant wave period of swell waves which usually have small wave heights, the estimation of the extreme wave height and corresponding wave period shows good agreement with the measurement data.

• Journal of the Society of Disaster Information
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• v.14 no.4
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• pp.501-509
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• 2018

Purpose: UAV-based photo measurements are being researched using UAVs in the space information field as they are not only cost-effective compared to conventional aerial imaging but also easy to obtain high-resolution data on desired time and location. In this study, the UAV-based high-resolution images were used to perform the land cover classification. Method: RGB cameras were used to obtain high-resolution images, and in addition, multi-distribution cameras were used to photograph the same regions in order to accurately classify the feeding areas. Finally, Land cover classification was carried out for a total of seven classes using created ortho image by RGB and multispectral camera, DSM(Digital Surface Model), NDVI(Normalized Difference Vegetation Index), GLCM(Gray-Level Co-occurrence Matrix) using RF (Random Forest), a representative supervisory classification system. Results: To assess the accuracy of the classification, an accuracy assessment based on the error matrix was conducted, and the accuracy assessment results were verified that the proposed method could effectively classify classes in the region by comparing with the supervisory results using RGB images only. Conclusion: In case of adding orthoimage, multispectral image, NDVI and GLCM proposed in this study, accuracy was higher than that of conventional orthoimage. Future research will attempt to improve classification accuracy through the development of additional input data.

• Journal of The Korean Association For Science Education
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• v.39 no.2
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• pp.233-248
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• 2019

This study shows that the Argovian Cantonal School in Aarau, Switzerland, which Albert Einstein attended from 1895 to 1896, had been closely related to the ideological education controversy in German Gymnasium throughout the 19th century. Due to this controversy, Einstein hardly received a formal science education in Bavaria. Despite the lack of formal education in Germany, he had a habit of self-studying from an early age and continued with this practice all through his life. He had a hard time at the authoritarian school in Munich, but at the democratic school in Aarau, where freedom and autonomy were secured, he was able to achieve emotional stability. For a long time, the city Aarau prevailed as a location of tolerance and multi-culturalism, without religious, regional, and national discrimination. This was possible due to the influence of external and unrestricted social mobility, as well as the Enlightenment from France. As a result, this small public school was able to acquire a mass of qualified human resources from outside of Switzerland. As a consequence of the controversy regarding the educational ideology, the Cantonal School adopted practical thoughts and the Enlightenment that fit the spirit of the times. The school consisted of two independent educational organizations: the Gymnasium, where the 'neuhumanistsch' education for the elite training was conducted, and the 'Gewerbeschule', where a more realistic education system was set up to suit the citizen life. In particular, after 1835, the Gymnasium changed gradually from the pure humanistic education to the 'utraquistisch' ways by introducing practical subjects such as natural history. Thereafter, the Cantonal School became an institution that was able to achieve a genuine humanity, academic, and civic life education. Einstein, who attended the 'technische Abteilung' of the 'Gewerbeschule,' considered this school as a role model of an institution that realized true democracy, and that left an unforgettable impression on him.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.37 no.1
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• pp.12-22
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• 2019

This study derived the design aspects by carrying out the case study of Neunggok prehistoric remains park, Ansansingil historic park and Yongjuk historic park to which are taken measures to preserve undesignated cultural heritages after studying the related laws & regulations and the systems as the design conditions of historic park preserving buried cultural heritages. The results of the study are as follows. First, according to the laws & regulations related to the historical parks, the historic sites should be preserved and utilized at the same time and can have history-related facility spaces, squares, rest spaces, exercise spaces, education & culture space, and convenience spaces. Second, by the space organization and the circulation system emphasizing only the preservation of buried cultural heritages, the feature-preservation space and the functional space are separated and due to not accepting the usage behavior considering peripheral land use, the effectiveness of the historical park was low. Third, the passive feature-preservation methods such as the preservation of the exposed site in architectural methods, the reproduction of the dugout hut, and the planting Royal azaleas or displaying stone after covering up the location of the pit dwellings with soil and the usage mainly for viewing have weakened the identity of the historical park. Fourth, the fence preventing users' access interferes experiencing the features, and the vertical structure protecting the upper part of the exposed features has overwhelmed the landscape of the historical parks. Fifth, it was difficult to figure out the feature space only by the texts mainly on terminologies and the excavation photographs presented on the information signs which introduce the buried cultural heritages.

• Journal of Korea Water Resources Association
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• v.54 no.5
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• pp.301-309
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• 2021

In this study, we tried to improve the performance of the existing U-net-based deep learning rainfall prediction model, which can weaken the meaning of time series order. For this, ConvLSTM2D U-Net structure model considering temporal consistency of data was applied, and we evaluated accuracy of the ConvLSTM2D U-Net model using a RainNet model and an extrapolation-based advection model. In addition, we tried to improve the uncertainty in the model training process by performing learning not only with a single model but also with 10 ensemble models. The trained neural network rainfall prediction model was optimized to generate 10-minute advance prediction data using four consecutive data of the past 30 minutes from the present. The results of deep learning rainfall prediction models are difficult to identify schematically distinct differences, but with ConvLSTM2D U-Net, the magnitude of the prediction error is the smallest and the location of rainfall is relatively accurate. In particular, the ensemble ConvLSTM2D U-Net showed high CSI, low MAE, and a narrow error range, and predicted rainfall more accurately and stable prediction performance than other models. However, the prediction performance for a specific point was very low compared to the prediction performance for the entire area, and the deep learning rainfall prediction model also had limitations. Through this study, it was confirmed that the ConvLSTM2D U-Net neural network structure to account for the change of time could increase the prediction accuracy, but there is still a limitation of the convolution deep neural network model due to spatial smoothing in the strong rainfall region or detailed rainfall prediction.

• Journal of the Society of Disaster Information
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• v.17 no.1
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• pp.120-127
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• 2021

Purpose: In this study, the effect of changes in the variables related to water droplets on the spray density on the floor in the analysis of the water mist fire protection system using FDS was analyzed. Method: When the spray of the water mist nozzle was analyzed in FDS, Particles Per Seconds, Particle Velocity, Size Distribution, and Spray Pattern Shape that can be set in relation to droplets were input to review the analyzed results. Result: In the analysis results, when the number of particles per second was set above a certain value, the spray density of the floor was similar. In the case of Particle Velocity, as the velocity decreases, the spray density of the central portion increases but decreases at a distance of 0.15m or more. From the analysis of the change in the size distribution function, it was found that an increase in the 𝛾 value increases the spray density of the central part, but the value at a remote location decreases. Compared to the result of applying the Gaussian distribution, the median value decreases dramatically when the uniform distribution is applied, but the value at the adjacent position increases. Conclusion: Variables related to the droplet properties of the FDS affect the spray density of the floor. Therefore, in order to increase the reliability of results before performing analyses such as fire suppression or cooling, a sufficient review of input variables is required.

• Korean Chemical Engineering Research
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• v.59 no.2
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• pp.209-218
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• 2021

First principle-based modeling studies have been performed to improve the heat exchange efficiency of ORV and optimize operation, but the heat transfer coefficient of ORV is an irregular system according to time and location, and it undergoes a complex modeling process. In this study, FNN, LSTM, and AutoML-based modeling were performed to confirm the effectiveness of data-based modeling for complex systems. The prediction accuracy indicated high performance in the order of LSTM > AutoML > FNN in MSE. The performance of AutoML, an automatic design method for machine learning models, was superior to developed FNN, and the total time required for model development was 1/15 compared to LSTM, showing the possibility of using AutoML. The prediction of NG and seawater discharged temperatures using LSTM and AutoML showed an error of less than 0.5K. Using the predictive model, real-time optimization of the amount of LNG vaporized that can be processed using ORV in winter is performed, confirming that up to 23.5% of LNG can be additionally processed, and an ORV optimal operation guideline based on the developed dynamic prediction model was presented.