• Earthquakes and Structures
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• v.15 no.6
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• pp.595-603
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• 2018

Shake table testing has been regarded as one of the most effective experimental approaches to evaluate seismic response of structural systems subjected to earthquakes. However, reproducing a prescribed acceleration time history precisely over the frequency of interest is challenging because shake table test systems are eventually nonlinear by nature. In addition, interaction between the table and specimen could affect the control accuracy of shake table testing significantly. Various novel control algorithms have been proposed to improve the control accuracy of shake table testing; however, reference values for control performance assessment remain rare. In this study, reference values for control performance assessment of shake table testing are specified based on the statistical analyses of 1,209 experimental data provided by the Seismic Simulator Laboratory of National Center for Research on Earthquake Engineering in Taiwan. Three individual reference values are considered for the assessment including the root-mean-square error of the achieved acceleration time history; the percentage of the spectral acceleration that exceeds the determined tolerance range over the frequency of interest; and the error-ratio of the achieved peak ground acceleration. Quartiles of the real experimental data in terms of the three objective variables are obtained, providing users with solid and simple references to evaluate the control performance of shake table testing. Finally, a set of experimental data of a newly developed control framework implementation for uni-axial shake tables are used as an application example to demonstrate the significant improvement of control accuracy according to the reference values provided in this study.

• Journal of Environmental Impact Assessment
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• v.14 no.3
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• pp.127-134
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• 2005

Recently, aquaculture farm sites have been increased with demand of the expensive fish species and sea food like as seaweed, laver and oyster. Therefore coastal water quality have been deteriorated by organic contamination from marine aquaculture farm sites. For protecting of coastal environment, we need to control the location of aquaculture sites. The purpose of this study is to detect the laver aquaculture sites using multispectral remotely sensed data with autodetection algorithm. In order to detect the aquaculture sites, density slice and contour and vegetation index methods were applied with SPOT and IKONOS data of Shinan area. The marine aquaculture farm sites were extracted by density slice and contour methods with one band digital number(DN) carrying 65% accuracy. However, vegetation index algorithm carried out 75% accuracy using near-infra red and red bands. Extraction of the laver aquaculture site using remotely sensed data will provide the efficient digital map for coastal water management strategies and red tide GIS management system.

• Journal of Ocean Engineering and Technology
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• v.35 no.4
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• pp.273-286
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• 2021

In recent years, as human casualties and property damage caused by hazardous waves have increased in the East Sea, precise wave prediction skills have become necessary. In this study, the Simulating WAves Nearshore (SWAN) third-generation numerical wave model was calibrated and optimized to enhance the accuracy of winter storm wave prediction in the East Sea. We used Source Term 6 (ST6) and physical observations from a large-scale experiment conducted in Australia and compared its results to Komen's formula, a default in SWAN. As input wind data, we used Korean Meteorological Agency's (KMA's) operational meteorological model called Regional Data Assimilation and Prediction System (RDAPS), the European Centre for Medium Range Weather Forecasts' newest 5th generation re-analysis data (ERA5), and Japanese Meteorological Agency's (JMA's) meso-scale forecasting data. We analyzed the accuracy of each model's results by comparing them to observation data. For quantitative analysis and assessment, the observed wave data for 6 locations from KMA and Korea Hydrographic and Oceanographic Agency (KHOA) were used, and statistical analysis was conducted to assess model accuracy. As a result, ST6 models had a smaller root mean square error and higher correlation coefficient than the default model in significant wave height prediction. However, for peak wave period simulation, the results were incoherent among each model and location. In simulations with different wind data, the simulation using ERA5 for input wind datashowed the most accurate results overall but underestimated the wave height in predicting high wave events compared to the simulation using RDAPS and JMA meso-scale model. In addition, it showed that the spatial resolution of wind plays a more significant role in predicting high wave events. Nevertheless, the numerical model optimized in this study highlighted some limitations in predicting high waves that rise rapidly in time caused by meteorological events. This suggests that further research is necessary to enhance the accuracy of wave prediction in various climate conditions, such as extreme weather.

• Journal of Environmental Science International
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• v.29 no.10
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• pp.981-988
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• 2020

This study presents meteorological data integrity to improve environmental quality assessment in Yongdam catchment. The study examines both extreme ranges of meteorological data measurements and data reliability which include maximum and minimum temperature, relative humidity, dew point temperature, radiation, heat flux. There were some outliers and missing data from the measurements. In addition, the latent heat flux and sensible heat flux data were not reasonable and evapotranspiration data did not match at some points. The accuracy and consistency of data stored in a database for the study were secured from the data integrity. Users need to take caution when using meteorological data from the Yongdam catchment in the preparation of water resources planning, environmental impact assessment, and natural hazards analysis.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.126-129
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• 2020

We introduce a lifetime assessment technique using deep learning algorithm with complex electrical parameters such as resistivity, permittivity, impedance parameters as integrated indicators for predicting the degradation of the organic molecules. The evaluation system consists of fully automated in-situ measurement system and multiple layer perceptron learning system with five hidden layers and 1011 perceptra in each layer. Prediction accuracies are calculated and compared depending on the physical feature, learning hyperparameters. 62.5% of full time-series data are used for training and its prediction accuracy is estimated as r-square value of 0.99. Remaining 37.5% of the data are used for testing with prediction accuracy of 0.95. With k-fold cross-validation, the stability to the instantaneous changes in the measured data is also improved.

• Proceedings of the Korea Concrete Institute Conference
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• 2001.11a
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• pp.803-808
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• 2001

Mathematical basis of interpretation of data from nondestructive evaluation (NDE) methods in bridge inspection is presented. In bridge inspection with NDE methods, NDE data are not assessments. NDE data must be interpreted as condition of element. Interpretation is then assessment. Correct assessments of conditions of bridge elements depend on the accuracy and variability in test data as well as on the uncertainty of correlations between attributes (what is measured) and conditions (what is sought in the inspection). Inaccuracy and variability in test data defines the qualify or NDE test. The qualify or test itself is important, but in view of condition assessment, the significance of uncertainty in correlations of attributes and conditions must be combined. NDE methods that are accurate in their measurements may still be found to be poor methods if attributes are uncertain indicators of condition of bridge elements. This paper reports mathematical presentation of inaccuracy and variability in test data and of uncertainty in correlation of attributes to element conditions with three examples of NDE methods.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1152-1154
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• 2003

The needs of 3-D data have been increasing for various applications like visualization, 3-D modeling, planning and management as well as entertainment. Mobile mapping has become a quick and practical means for acquiring necessary 3-D data for above-mentioned applications. A mobile mapping system mainly consists of two main components, viz. data acquisition devices and positioning devices. The data acquisition devices consist of CCD cameras or/and laser scanners. The positioning devices consist of GPS, INS, Odometer (shaft encoder) and some other referencing devices. The overall accuracy of mobile mapping system depends on the accuracy of positioning devices and their integrated output. Though, GPS is the main input device for the position information, the signal is not available for the computation of position all the times in urban area. The GPS satellites are normally obstructed by high-rise buildings. Thus it is very important to understand the accuracy of such a system in different environments and means to solve such problems. We have developed a mobile mapping system called VLMS (Vehicle-borne Laser Mapping System), which consists of CCD Cameras, Laser scanners, GPS, INS and Odometer. In this paper, we will present and discuss the accuracy of this system with data acquired in different environments (open area, urban area, tunnel, express way etc) by analyzing the data with respect to other existing digital data.

• Atmosphere
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• v.33 no.5
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• pp.549-560
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• 2023

This study evaluates three distinct observation methods, CRDS, OA-ICOS, and OF-CEAS, in greenhouse gas monitoring equipment for atmospheric CO₂ and CH₄ concentrations. The assessment encompasses fundamental performance, high-concentration measurement accuracy, calibration methods, and the impact of atmospheric humidity on measurement accuracy. Results indicate that within a range of approximately 500 ppm, all three devices demonstrate high accuracy and linearity. However, beyond 1000 ppm, CO₂ accuracy sharply declines (84%), emphasizing the need for caution when interpreting high-concentration CO₂ data. An analysis of calibration methods reveals that both CO₂ and CH₄ measurements achieve high accuracy and linearity through 1-point calibration, suggesting that multi-point calibration is not imperative for precision. In dynamic atmospheric conditions with significant CO₂ and CH₄ concentration variations, a 1-point calibration suffices for reliable data (99% accuracy). The evaluation of humidity impact demonstrates that humidity removal devices significantly reduce air moisture levels, yet this has a negligible effect on dry CO₂ concentrations (less than 0.5% relative error). All three observation method instruments, which have integrated humidity correction to calculate dry CO₂ concentrations, exhibit minor sensitivity to humidity removal devices, implying that additional removal devices may not be essential. Consequently, this study offers valuable insights for comparing data from different measurement devices and provides crucial information to consider in the operation of monitoring sites.

• Korean Journal of Remote Sensing
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• v.17 no.2
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• pp.121-129
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• 2001

A DEM(digital elevation model) is generated from a SPOT panchromatic stereo-pair using automated algorithms over a 8 km$\times$10 km region around Mokpo city. The aims are to continue the accuracy assessment over diverse conditions and to examine the applicability of a SPOT DEM for coastal disaster monitoring. The accuracy is assessed with respect to three reference data sets: 10 global positioning system records, 19 leveling data, and 1:50,000 topography map. The planimetric error is 10.6m r.m.s. and the elevation erroer ranges from 12.4m to 14.4m r.m.s.. The DEM accuracy of the flat Mokpo region is consistent with that over a mountainous area, which supports the robustness of the algorithms. It was found that coordinate transformation errors are significant at a few meters when using the data from leveling and topographic maps. The error budget is greater than the requirements for coastal disaster monitoring. Exploiting that a sub-scene is used, the affine transformation improves the accuracy by 50% during the camera modeling.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.363-366
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• 2007

Road Design is being reached to the working design to produce drawings, calculate construction quantity and cost, through the basic design that contained feasibility study and all impact assessment. In general, to plan the route we use topographic map. The vertical positional accuracy is 30cm and horizontal positional accuracy is 35cm in 1:1,000 scale topographic map. In LiDAR, vertical positional accuracy is 15cm and horizontal positional accuracy is 30cm. So if we use LiDAR on road design, more accurate earth-volumn will be calculated when we plan the route. In this paper we try to find the method to use the LiDAR data on road design by drawing the profile and cross sectional view and comparing the earth-volumn to the road that working design is in process adopting the topographic map and LiDAR data.