• Journal of Korean Society of Steel Construction
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• v.14 no.5 s.60
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• pp.641-646
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• 2002

A new damage detection technique using static displacement data was developed, in order to assess the structural integrity of bridge structures. In conventional damage assessment techniques using dynamic response, the variation of natural frequencies is intrinsically insensitive to the damage of the bridge: thus, it is usually difficult to obtain them from the measured data. The proposed detection method enables the estimation of the stiffness reduction of bridges using the static displacement data that are measured periodically, without requiring a specific loading test. Devices such as a laser displacement sensor can be used to measure static displacement data due to the dead load of the bridge structure. In this study, structural damage was represented by the reduction in the elastic modulus of the element. The damage factor of the element was introduced to estimate the stiffness reduction of the bridge under consideration. Likewise, the proposed algorithm was verified using various numerical simulations and compared with other damage detection methods. The effects of noise and number of damaged elements on damage detection were also investigated. Results showed that the proposed algorithm efficiently detects damage on the bridge.

• Journal of Korea Water Resources Association
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• v.33 no.4
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• pp.505-515
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• 2000

THe purpose of this study is to forecast of runoff hydrographs according to rainfall event in a stream. The neural network theory as a hydrologic blackbox model is used to solve hydrological problems. The Back-Propagation(BP) algorithm by the Levenberg-Marquardt(LM) techniques and Radial Basis Function(RBF) network in Neural Network(NN) models are used. Runoff hydrograph is forecasted in Bocheongstream basin which is a IHP the representative basin. The possibility of a simulation for runoff hydrographs about unlearned stations is considered. The results show that NN models are performed to effective learning for rainfall-runoff process of hydrologic system which involves a complexity and nonliner relationships. The RBF networks consist of 2 learning steps. The first step is an unsupervised learning in hidden layer and the next step is a supervised learning in output layer. Therefore, the RBF networks could provide rather time saved in the learning step than the BP algorithm. The peak discharge both BP algorithm and RBF network model in the estimation of an unlearned are a is trended to observed values.

• Journal of the Korean Geotechnical Society
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• v.27 no.8
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• pp.51-61
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• 2011

Spatial estimation of the thickness and depth of the geological profile has been regarded as an important procedure for the design of soft ground. A minimum variance criterion, which has often been used in traditional kriging techniques, does not always guarantee the optima1 estimates for the decision-making process in geotechnical engineering. In this study, a geostatistica; framework is used to determine the optimal thickness of the consolidation layer and the optimal area that needs the adoption of prefabricated vertical drains via indicator kriging and loss function. From the exemplary problem, different optimal estimates can be obtained depending on the loss function chosen. The design procedure and method considering the minimum expected loss presented in this paper can be used in the decision-making process for geotechnical engineering design.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.4
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• pp.118-125
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• 2014

As the earth's current global warming has caused elevation of sea water temperature, size of storms is foreseen to increase and consequently large damages on port facilities are to be expected. In addition, due to the improved processing efficiency of port cargo volume and increasing necessity for construction of eco-friendly port, demands for various forms of port facilities are anticipated. In this study, two kinds of nondestructive evaluation (NDE) techniques (rebound hardness and ultrasonic pulse velocity methods) are investigated for the effective maintenance of smart green harbor system. A new methodology to estimate the underwater concrete strengths is proposed and its feasibility is verified throughout a series of experimental works.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.265-276
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• 2018

Observation and data analysis techniques have been developed for observational blind areas in the lower atmosphere that are difficult to be monitored with fixed equipment on the ground. The vertical data of temperature and relative humidity are remotely collected by the UHF radiosonde installed on UAV and compared with the data measured in the 10 m weather tower. From the validated vertical profile, extrapolated surface temperature and the bulk transfer method were used to estimate the sensible heat flux depending on the atmospheric stability. Compared with the sensible heat flux measured by the 3-dimensional ultrasonic anemometer on the ground, the error of the sensible heat flux estimated was 23% that is less than the range of 30% allowed in the remote sensing. Estimated atmospheric boundary layer height from UAV sensible heat fluxes can provide useful data for air pollution diffusion models in real time and economically.

• Journal of Korea Water Resources Association
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• v.50 no.12
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• pp.849-862
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• 2017

The increased frequency of meteorological disasters has been observed due to increased extreme events such as heavy rainfalls and flash floods. Numerous studies using high-resolution weather radar rainfall data have been carried out on the hydrological effects. In this study, a conditional merging technique is employed, which makes use of geostatistical methods to extract the optimal information from the observed data. In this context, three different techniques such as kriging, inverse distance weighting and spline interpolation methods are applied to conditionally merge radar and ground rainfall data. The results show that the estimated rainfall not only reproduce the spatial pattern of sub-hourly rainfall with a relatively small error, but also provide reliable temporal estimates of radar rainfall. The proposed modeling framework provides feasibility of using conditionally merged rainfall estimation at high spatio-temporal resolution in ungauged areas.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.6
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• pp.101-112
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• 2013

Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM) offers opportunities to make advances in many research areas including hydrology by providing near-global scale elevation measurements at a uniform resolution. Its wide coverage and complimentary online access especially benefits researchers requiring topographic information of hard-to-access areas. However, SRTM DEM also contains inherent errors, which are subject to propagation with its manipulation into analysis outputs. Sensitivity of hydrologic analysis to the errors has not been fully understood yet. This study investigated their impact on estimation of hydrologic derivatives such as slope, stream network, and watershed boundary using Monte Carlo simulation and spatial moving average techniques. Different amount of the errors and their spatial auto-correlation structure were considered in the study. Two sub-watersheds of Geum and Deadong River areas located in South and North Korea, respectively, were selected as the study areas. The results demonstrated that the spatial presentations of stream networks and watershed boundaries and their length and area estimations could be greatly affected by the SRTM DEM errors, in particular relatively flat areas. In the Deadong River area, artifacts of the SRTM DEM created sinks even after the filling process and then closed drainage basin and short stream lines, which are not the case in the reality. These findings provided an evidence that SRTM DEM alone may not enough to accurately figure out the hydrologic feature of a watershed, suggesting need of local knowledge and complementary data.

• Journal of Astronomy and Space Sciences
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• v.34 no.4
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• pp.315-330
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• 2017

Halo coronal mass ejections (CMEs) originating from solar activities give rise to geomagnetic storms when they reach the Earth. Variations in the geomagnetic field during a geomagnetic storm can damage satellites, communication systems, electrical power grids, and power systems, and induce currents. Therefore, automated techniques for detecting and analyzing halo CMEs have been eliciting increasing attention for the monitoring and prediction of the space weather environment. In this study, we developed an algorithm to sense and detect halo CMEs using large angle and spectrometric coronagraph (LASCO) C3 coronagraph images from the solar and heliospheric observatory (SOHO) satellite. In addition, we developed an image processing technique to derive the morphological and dynamical characteristics of halo CMEs, namely, the source location, width, actual CME speed, and arrival time at a 21.5 solar radius. The proposed halo CME automatic analysis model was validated using a model of the past three halo CME events. As a result, a solar event that occurred at 03:38 UT on Mar. 23, 2014 was predicted to arrive at Earth at 23:00 UT on Mar. 25, whereas the actual arrival time was at 04:30 UT on Mar. 26, which is a difference of 5 hr and 30 min. In addition, a solar event that occurred at 12:55 UT on Apr. 18, 2014 was estimated to arrive at Earth at 16:00 UT on Apr. 20, which is 4 hr ahead of the actual arrival time of 20:00 UT on the same day. However, the estimation error was reduced significantly compared to the ENLIL model. As a further study, the model will be applied to many more events for validation and testing, and after such tests are completed, on-line service will be provided at the Korean Space Weather Center to detect halo CMEs and derive the model parameters.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.2
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• pp.10-23
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• 2009

The fundamental matrix and key frame selection are one of the most important techniques to recover full 3D reconstruction of objects from turntable sequences. This paper proposes a new algorithm that estimates a robust fundamental matrix for camera calibration from uncalibrated images taken under turn-table motion. Single axis turntable motion can be described in terms of its fixed entities. This provides new algorithms for computing the fundamental matrix. From the projective properties of the conics and fundamental matrix the Euclidean 3D coordinates of a point are obtained from geometric locus of the image points trajectories. Experimental results on real and virtual image sequences demonstrate good object reconstructions.

• Korean Journal of Social Welfare
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• v.69 no.3
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• pp.9-33
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• 2017

This study estimated the socioeconomic costs of child poverty. Based on previous studies, the present study organized component categories for direct and indirect costs of child poverty, and estimated the cost of each category in 2015 through the collection of existing data and Delphi survey techniques among experts. The total socioeconomic costs of child poverty were compared to Korea's GDP. The results of this study were as follows. First, the socioeconomic costs of child poverty in Korea in 2015 ranged from 55 trillion KW(3.5% of GDP) to 99 trillion KW(6.5% of GDP). Second, the indirect socioeconomic costs of child poverty are much higher than the direct costs. Third, among the total cost categories, costs related to productivity loss and unemployment accounted for the largest portion of both the socioeconomic costs based upon absolute poverty and relative poverty. Crime costs are the second largest. Based on these results, we discussed the importance of early intervention for children in poverty; implementation of two-generation program that intervenes simultaneously with parents and children; and long-term, continuous and integrated intervention for high-risk groups such as poor children.