• Journal of Korea Water Resources Association
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• v.35 no.1
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• pp.1-12
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• 2002

This study was intended to investigate the rainfall-runoff relationship with spatially distributed rainfall data, and then, to analyze and quantify the uncertainty induced by spatially averaging rainfall data. For constructing spatially distributed rainfall data, several historical rainfall events were extended spatially by simple kriging method based on the semivariogram as a function of the relative distance. Runoff was computed by two models; one was the modified Clark model with spatially distributed rainfall data and the other was the conventional Clark model with spatially averaged rainfall data. Rainfall errors and discharge errors occurred through this process were defined and analyzed with respect to various rain-gage network densities. The following conclusions were derived as the results of this work; 1) The conventional Clark parameters could be appropriate for translating spatially distributed rainfall data. 2) The parameters estimated by the modified Clark model are more stable than those of the conventional Clark model. 3) Rainfall and discharge errors are shown to be reduced exponentially as the density of rain-gage network is increased. 4) It was found that discharge errors were affected largely by rainfall errors as the rain-gage network density was small.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.2
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• pp.179-187
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• 2023

APT cyber attacks have been a problem for over a past decade, but still remain a challenge today as attackers use more sophisticated techniques and the number of objects to be protected increases. 'Cyberattack Tracing System' allows analysts to find undetected attack codes that penetrated and hid in enterprises, and to investigate their lateral movement propagation activities. The enterprise is characterized by multiple networks and mass hosts (PCs/servers). This paper presents a data processing procedure that collects event data, generates a temporally and spatially extended provenance graph and cyberattack tracing paths. In each data process procedure phases, system design considerations are suggested. With reflecting the data processing procedure and the characteristics of enterprise environment, an operational architecture for CyberAttack Tracing System is presented. The operational architecture will be lead to the detailed design of the system.

• Journal of KIBIM
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• v.10 no.3
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• pp.54-62
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• 2020

There is growing consensus among planners and policymakers that brownfield remediation has positive impacts on neighborhoods in terms of housing prices, public health, and environmental quality. However, there is a limited understanding of how brownfield redevelopments spatially affect neighborhood housing turnover and stability. This paper addresses the spatial impacts of brownfield redevelopments on neighboring housing turnover in Cuyahoga County, Ohio. This study examines housing turnover before and after the remediation of brownfield sites countywide and in housing submarkets stratified by household income. Based on housing sales data between 1996 and 2007, the extended Cox Hazard model with the difference-in-difference approach is employed to clarify the causal relationships between brownfield redevelopments and neighboring housing turnover. Additionally, along with the results of the previous study examining impacts of brownfield remediation on nearby housing prices, this paper estimates the change of neighborhood stability due to brownfield redevelopments based on both attributes of housing prices and turnovers.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.113-115
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• 2000

A GIS software GEO Millennium SystemTM has been developed to integrated with spatial database that combines conventional and spatially related data. As we known well the standard query language lacks the support of spatial data type and predicate, and can not serve as the query language in the spatial database directly; some extended strategies have been proposed, but some of them need their own storage manager, some introfuce new clause into the SELECT-FROM-WHERE structure, and some is very complex and available to us. So we designed our own query language on the conventional storage manager system. It supports the Spatial Data Type and predicate, and provides the full query capabilities of SQL on the non-spatial part of the database while being tightly integrated with the spatial part, without changing the standard SQL structure.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.353-360
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• 2015

Various statistical models have been proposed over the last decade for spatially correlated Gaussian outcomes. The spatial linear mixed model (SLMM), which incorporates a spatial effect as a random component to the linear model, is the one of the most widely used approaches in various application contexts. Employing link functions, SLMM can be naturally extended to spatial generalized linear mixed model for non-Gaussian outcomes (SGLMM). We review popular SGLMMs on non-Gaussian spatial outcomes and demonstrate their applications with available public data.

• Earthquakes and Structures
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• v.3 no.3_4
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• pp.341-363
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• 2012

The spectral representation method is a quick and versatile tool for the generation of spatially variable, response-spectrum-compatible simulations to be used in the nonlinear seismic response evaluation of extended structures, such as bridges. However, just as recorded data, these simulated accelerations require processing, but, unlike recorded data, the reasons for their processing are purely numerical. Hence, the criteria for the processing of acceleration simulations need to be tied to the effect of processing on the structural response. This paper presents a framework for processing acceleration simulations that is based on seismological approaches for processing recorded data, but establishes the corner frequency of the high-pass filter by minimizing the effect of processing on the response of the structural system, for the response evaluation of which the ground motions were generated. The proposed two-step criterion selects the filter corner frequency by considering both the dynamic and the pseudo-static response of the systems. First, it ensures that the linear/nonlinear dynamic structural response induced by the processed simulations captures the characteristics of the system's dynamic response caused by the unprocessed simulations, the frequency content of which is fully compatible with the target response spectrum. Second, it examines the adequacy of the selected estimate for the filter corner frequency by evaluating the pseudo-static response of the system subjected to spatially variable excitations. It is noted that the first step of this two-fold criterion suffices for the establishment of the corner frequency for the processing of acceleration time series generated at a single ground-surface location to be used in the seismic response evaluation of, e.g. a building structure. Furthermore, the concept also applies for the processing of acceleration time series generated by means of any approach that does not provide physical considerations for the selection of the corner frequency of the high-pass filter.

• Smart Structures and Systems
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• v.5 no.4
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• pp.469-482
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• 2009

The emerging sensor-based structural health monitoring (SHM) technology has a potential for cost-effective maintenance of aging civil infrastructure systems. The author proposes to integrate continuous and global monitoring using on-structure sensors with targeted local non-destructive evaluation (NDE). Significant technical challenges arise, however, from the lack of cost-effective sensors for monitoring spatially large structures, as well as reliable methods for interpreting sensor data into structural health conditions. This paper reviews recent efforts and advances made in addressing these challenges, with example sensor hardware and health monitoring software developed in the author's research center. The hardware includes a novel fiber optic accelerometer, a vision-based displacement sensor, a distributed strain sensor, and a microwave imaging NDE device. The health monitoring software includes a number of system identification methods such as the neural networks, extended Kalman filter, and nonlinear damping identificaiton based on structural dynamic response measurement. These methods have been experimentally validated through seismic shaking table tests of a realistic bridge model and tested in a number of instrumented bridges and buildings.

• Journal of the Korean Geotechnical Society
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• v.22 no.2
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• pp.55-68
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• 2006

For the reliable prediction of spatial geotechnical data, a procedure to build the Geotechnical Information System (GTIS) based on geo-knowledge within the frame of GIS technology was developed by introducing a couple of new concepts of the extended area containing the study area and the additional site visit for acquiring surface geological data. To build the GTIS for Gyeongju as the case study of regional model application, intensive site investigations and pre-existing geotechnical data collections were performed and additional site visit was also carried out for acquiring surface geo-layer data in accordance with the developed procedure. Within the GTIS based on geo-knowledge for Gyeongiu area, the spatially distributed geo-layers across the extended area were predicted using the geostatistical kriging method and those for the study area were extracted. Furthermore, the spatial distribution maps for the thickess of geo-layers and the depth to bedrock were constructed for the practical use in geotechnical field. It was evaluated that the GTIS based on geo-knowledge developed in this study is superior to the conventional geotechnical GIS in terms of both the standard deviation and the geological expert judgment.

• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.119-124
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• 2009

In this paper, we propose a novel approach to estimating the real-time moving trajectory of an object is proposed in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the input-output relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.2
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• pp.101-106
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• 2010

We propose an approach to estimate the real-time moving trajectory of an object in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the inputoutput relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.