• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.11
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• pp.48-56
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• 2005

Predictive filter theory proposed recently can be characterized by inherent advantages of estimating modelling error and overcoming the disadvantage of the Kalman filter theory. A one-step ahead error is minimized to produce optimized filter performance in the form of the predictive filter. The main advantage of this filter lies in the ability to estimate both state vector and system model error. In this paper, attitude estimation results based upon the predictive filter theory is addressed. Mathematical formulation for estimating bias signal is peformed by using the predictive filter theory, and attitude estimation based upon vector observation is presented. From the results of this study, the potential applicability of the predictive filter is highlighted.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.275-286
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• 2000

After commencing the local self~governing system. it has been requested to make statistics about Si-Gun-Gu level. and the necessity of unemployment statistics in Si-GunGu area has also been proposed as the unemployment became a political issue and social problem due to an I:YIF situation Throughout this paper, therefore, we suggest two small area estimations that can produce the unemployment statistics of Si-Gun-Gu based on the Current Population Survey In addition, we estimate the unemployment number of Si-Gun-Gu in ChungBuk area from the real data of the Current Population Survey. Finally, It was also proved that the applicability of small area estimation was valid in comparison with efficiency of small area estimations.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.514-519
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• 1992

To make an accurate retrieval of the proportion of each category among mixed pixels (Mixel's) of a remotely sensed imagery, a maximum likelihood estimation method of category proportion is proposed. In this method, the observed multispectral vector is considered as probability variables along with the approximation that the supervised data of each category can be characterized by normal distribution. The results show that this method can retrieve accurate proportion of each category among Mixel's. And a index that can estimate the degree of error in each category is proposed. AS one of the application of the proportion estimation, a method for image classification based on category proportion estimation is proposed. In this method all pixel in a remotely sensed imagery are assumed to be Mixel's, and are classified to most dominant category. Among the Mixel's, there exists unconfidential pixels which should be categorized as unclassified pixels. In order to discriminate them, two types of criteria, Chi square and AIC, are proposed for fitness test on pure pixel hypothesis. Experimental result with a simulated dataset show an usefulness of proposed classification criterion compared to the conventional maximum likelihood criterion and applicability of the fitness tests based on Chi square and AIC,

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.641-655
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• 1998

The methods of development and application of an expert system are suggested to solve more efficiently the problems of water resources and quality induced by the rapid urbanization. Major parameters of the water quantity and quality of urban areas are selected their characteristics are presented by the sensitivity analysis. The rules to decide the parameters effectively are proposed based on these characteristics. the ESPE(Expert System for Parameter Estimation), an expert system based on the 'facts' and 'rules', is developed using the CLIPS 6.0 and applied to the basin of the An-Yang stream. The results of estimating t도 parameters of water quantity show a high applicability, but those of water quality imply the necessity of improving the present methods due to both the complexity of estimation processes and the lack of decision rules.

• Journal of Korean Society of Water and Wastewater
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• v.31 no.3
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• pp.237-248
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• 2017

The estimation method of economical leakage management target utilized upon planning business for improvement of revenue water ratio in South Korea is presented and applicability of methods developed in this study is assessed through application on site. With a consideration of revenue water ratio in application target area, estimation method of long-term economical leakage management target is applied. Three leakage reduction methods such as replacement of residual aged pipe, leakage investigation and restoration and water pressure management are applied with a consideration of characteristics of site. Due to difficulty of obtaining data, analysis of cost/benefit by leakage reduction methods is performed by applying method of leakages estimation equation among statistical methods. As a result of application, revenue water ratio corresponding to long-term economical leakage management target is 91.6 %.

• Architectural research
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• v.20 no.4
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• pp.137-145
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• 2018

The nondestructive test is widely used in the field of diagnosis and maintenance to evaluate the degree of damaging of structures caused by aging, and the demand for this test method is expected to continue increasing. However, there is a lack of standards related to the nondestructive test, and South Korea is relying heavily on developed nations for original technologies related to diagnosis. It is an urgent task to establish a nondestructive test method appropriate for the circumstance of South Korea. The purpose of this study is to compare and analyze estimated error of compressive strength in single-story structures comprised of vertical and horizontal reinforced concrete members using the impact testing method and rebound hardness method, which are nondestructive test methods, and to review on-site applicability of these methods. Based on compressive strength of the structures estimated, overall mean error was 21.2% for the impact testing method and 15.6% for the rebound hardness method. The necessity of a reliable diagnostic method based on compound nondestructive test methods to increase accuracy of estimation was confirmed.

• Smart Structures and Systems
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• v.23 no.1
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• pp.61-69
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• 2019

Offshore structures are generally exposed to harsh environments such as strong tidal currents and wind loadings. Monitoring the structural soundness and integrity of offshore structures is crucial to prevent catastrophic collapses and to prolong their lifetime; however, it is intrinsically challenging because of the difficulties in accessing the critical structural members that are located under water for installing and repairing sensors and data acquisition systems. Virtual sensing technologies have the potential to alleviate such difficulties by estimating the unmeasured structural responses at the desired locations using other measured responses. Despite the usefulness of virtual sensing, its performance and applicability to the structural health monitoring of offshore structures have not been fully studied to date. This study investigates the use of virtual sensing of offshore structures. A Kalman filter based virtual sensing algorithm is developed to estimate responses at the location of interest. Further, this algorithm performs a multi-sensor data fusion to improve the estimation accuracy under non-stationary tidal loading. Numerical analysis and laboratory experiments are conducted to verify the performance of the virtual sensing strategy using a bottom-fixed offshore structural model. Numerical and experimental results show that the unmeasured responses can be reasonably recovered from the measured responses.

• Ocean Systems Engineering
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• v.11 no.4
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• pp.331-351
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• 2021

Underwater images are very much different from images taken on land, due to the presence of a higher disturbance ratio caused by the presence of water medium between the camera and the target object. These distortions and noises result in unclear details and reduced quality of the output image. An underwater image restoration method is proposed in this paper, which uses blurriness information, background light neutralization information, and red-light intensity to estimate depth. The transmission map is then estimated using the derived depth map, by considering separate attenuation coefficients for direct and backscattered signals. The estimated transmission map and estimated background light are then used to recover the scene radiance. Qualitative and quantitative analysis have been used to compare the performance of the proposed method against other state-of-the-art restoration methods. It has been shown that the proposed method can yield good quality restored underwater images. The proposed method has also been evaluated using different qualitative metrics, and results have shown that method is highly capable of restoring underwater images with different conditions. The results are significant and show the applicability of the proposed method for underwater image restoration work.

• Smart Structures and Systems
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• v.32 no.2
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• pp.123-133
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• 2023

This paper proposes a thermography-based coating thickness estimation method for steel structures using model-agnostic meta-learning. In the proposed method, a halogen lamp generates heat energy on the coating surface of a steel structure, and the resulting heat responses are measured using an infrared (IR) camera. The measured heat responses are then analyzed using model-agnostic meta-learning to estimate the coating thickness, which is visualized throughout the inspection surface of the steel structure. Current coating thickness estimation methods rely on point measurement and their inspection area is limited to a single point, whereas the proposed method can inspect a larger area with higher accuracy. In contrast to previous ANN-based methods, which require a large amount of data for training and validation, the proposed method can estimate the coating thickness using only 10- pixel points for each material. In addition, the proposed model has broader applicability than previous methods, allowing it to be applied to various materials after meta-training. The performance of the proposed method was validated using laboratory-scale and field tests with different coating materials; the results demonstrated that the error of the proposed method was less than 5% when estimating coating thicknesses ranging from 40 to 500 ㎛.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.4
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• pp.9-19
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• 2016

The objective of this study was to evaluate the applicability of SWAT (Soil and Water Assessment Tool) model for runoff estimation in the Nam river dam watershed. Input data for the SWAT model were established using spatial data (land use, soil, digital elevation map) and weather data. The SWAT model was calibrated and validated using observed runoff data from 2003 to 2014 for three stations (Sancheong, Shinan, Changchon) within the study watershed. The $R^2$ (Determination Coefficient), RMSE (Root Mean Square Error), NSE (Nash-Sutcliffe efficiency coefficient), and RMAE (Relative Mean Absolute Error) were used to evaluate the model performance. Parameters for runoff calibration were selected based on user's manual and references and trial and error method was applied for parameter calibration. Calibration results showed that annual mean runoff were within ${\pm}5%$ error compared to observed. $R^2$ were ranged 0.64 ~ 0.75, RMSE were 2.51 ~ 4.97 mm/day, NSE were 0.48 ~ 0.65, and RMAE were 0.34 ~ 0.63 mm/day for daily runoff, respectively. The runoff comparison for three stations showed that annual runoff was higher in Changchon especially summer and winter seasons. The flow exceedance graph showed that Sancheong and Shinan stations were similar while Changchon was higher in entire fraction.