• Journal of the Optical Society of Korea
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• v.18 no.3
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• pp.217-224
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• 2014

A major advantage of wavefront reconstruction based on a series of diffracted intensity images using only single-beam illumination is the simplicity of setup. Here we propose a fast-converging algorithm for wavefront calculation using single-beam illumination. The captured intensity images are resampled to a series of intensity images, ranging from highest to lowest resampling; each resampled image has half the number of pixels as the previous one. Phase calculation at a lower resolution is used as the initial solution phase at a higher resolution. This corresponds to separately calculating the phase for the lower- and higher-frequency components. Iterations on the low-frequency components do not need to be performed on the higher-frequency components, thus making the convergence of the phase retrieval faster than with the conventional method. The principle is verified by both simulation and optical experiments.

• Journal of Korean Academic Society of Home Health Care Nursing
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• v.28 no.3
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• pp.266-275
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• 2021

Purpose: This study was conducted to explore the mediating effect of menopausal symptoms in the relationship between occupational stress and quality of Life in middle-aged working women Method: Data collection was conducted from May 2019 to July 2019. A sample of 130 middle-aged working women was recruited from three cities in Korea. The collected data were analyzed using descriptive statistics, t-tset, ANOVA, Scheffé test, pearson correlation, and a three step regression analysis. The mediating effect was analyzed using PROCESS macro with a 95.0% bias corrected bootstrap confidence interval (5,000 bootstraps resampling). Results: Quality of life had a negative correlation with occupational stress and menopausal symptoms, while there was a positive correlation between occupational stress and menopausal symptoms. Menopausal symptoms showed a direct effect on quality of life through occupational stress as a mediating variable. Conclusion: These results suggest that menopausal symptoms should be considered when developing interventions to improve quality of life through occupational stress control of middle-aged working women

• Smart Structures and Systems
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• v.31 no.4
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• pp.383-392
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• 2023

Post-earthquake building condition assessment is crucial for subsequent rescue and remediation and can be automated by emerging computer vision and deep learning technologies. This study is based on an endeavour for the 2nd International Competition of Structural Health Monitoring (IC-SHM 2021). The task package includes five image segmentation objectives - defects (crack/spall/rebar exposure), structural component, and damage state. The structural component and damage state tasks are identified as the priority that can form actionable decisions. A multi-task Convolutional Neural Network (CNN) is proposed to conduct the two major tasks simultaneously. The rest 3 sub-tasks (spall/crack/rebar exposure) were incorporated as auxiliary tasks. By synchronously learning defect information (spall/crack/rebar exposure), the multi-task CNN model outperforms the counterpart single-task models in recognizing structural components and estimating damage states. Particularly, the pixel-level damage state estimation witnesses a mIoU (mean intersection over union) improvement from 0.5855 to 0.6374. For the defect detection tasks, rebar exposure is omitted due to the extremely biased sample distribution. The segmentations of crack and spall are automated by single-task U-Net but with extra efforts to resample the provided data. The segmentation of small objects (spall and crack) benefits from the resampling method, with a substantial IoU increment of nearly 10%.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.139-139
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• 2021

Flooding events often result from extreme precipitations driven by various climate mechanisms, which are often disregarded in flood risk assessments. To bridge this gap, we propose a climate-mechanism-based flood frequency analysis that accommodates the direct linkage between the dominant climate processes and risk management decisions. Several statistical methods have been utilized in this approach including the Markov Chain analysis, K-nearest neighbor (KNN) resampling approach, and Z-score-based jittering method. After that, the impacts of climate change are associated with the modification of the transition matrix (TM) and the application of the quantile mapping approach. For this study, we have selected the Nam River Basin, South Korea, to consider the heterogeneous impacts of the two climate mechanisms, including the Tropical Cyclone (TC) and non-TCs. Based on our results, while both climate mechanisms have significant impacts on future flood extremes, TCs have been observed to bring more significant and immediate impacts on the flood extremes. The results in this study have proven that the proposed approach can lead to a new insights into future flooding management.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.6
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• pp.143-151
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• 2009

Extreme hydrologic events cause serious disaster, such as flood and drought. Many researchers have an effort to estimate design rainfalls or discharges. This study evaluated parameter estimation methods to estimate probability rainfalls with low uncertainty which will be used in design rainfalls. This study collected rainfall data from Incheon, Gangnueng, Gwangju, Busan, and Chupungryong gage station, and generated synthetic rainfall data using ARMA model. This study employed the maximum likelihood method and the Bayesian inference method for estimating parameters of the Gumbel and GEV distribution. Using a bootstrap resampling method, this study estimated the confidence intervals of estimated probability rainfalls. Based on the comparison of the confidence intervals, this study recommended a proper parameter estimation method for estimating probability rainfalls which have a low uncertainty.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.3
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• pp.210-216
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• 2009

Several empty-space leaping methods have been proposed for CPU-based volume ray casting. When sample points are located in semi-transparent cells, however, previous leaping methods perform unnecessary resamplings even if the scalar values on those points are confined within transparent range. A semi-transparent cells leaping method for volume ray casting using the Marching Cubes algorithm is proposed to solve this problem in our previous work. When a ray reaches a semi-transparent cell, our method performs in-out test between current sample point and the bounding box enclosing the triangles generated by the Marching Cubes. If the sample point lies on outside of the bounding box, we estimate the point is regarded as transparent. In this case, the ray advances to the next sample point without performing a resampling operation. We can frequently refer the tables for neighboring voxels, however, when we exploit conventional data structures of the Marching Cubes. We propose modified Marching Cubes tables for solving this problem.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.25-32
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• 2016

In this paper, we propose a method that is tracking an object in real time using particle filter and the observation model with edge. First of all, the proposed method defines the object to be tracked in the initial frame. Then, it generates the edge observation model for the object to be tracked and a set of particles. It calculates the weight by comparing the average of the middle distance in eight-way of particle filter edge model with that in edge observation model, and then updates the weight with the calculated value. After resampling particles using the updated weights, it estimates the current location of the tracked object. Finally, this paper demonstrates the performance of the stable tracking through comparison with the existing method by using a number of experimental data.

• Journal of Korean Society for Geospatial Information Science
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• v.1 no.2 s.2
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• pp.83-96
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• 1993

The orthophto map is seen as the form of picture with the uniform reduced scale as the current terrain map. Thus it provides a reasonable feeling of scene and is easy to be interpreted. Furthermore, digital orthophoto is currently used as the basic terrain information data of the Geo-Spatial Information System(GSIS). Therefore, the orhtophoto map has high potential use as a future terrain map. This paper studies the method of producing orthophoto map by using the digital satellite imagery data taken from SPOT satellite of France. The production of orthophoto map requires the process of generating orthophoto imagery with digital elevation model, which process is called digital differential rectification. As the final accuracy of orthophoto map depends on that of digital elevation model, the precise and efficient production method of digital elevation model should be preceded. This study investigated the method of producing digital elevation model directly from SPOT satellite imagery and generated ortho-image by resampling the original SPOT imagery through digital differential rectification. Finally, Simple orthophoto map was made by overlaying the ortho-image and the contour map from digital elevation model.

• Journal of the Korea Society of Computer and Information
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• v.15 no.2
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• pp.109-117
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• 2010

Digital watermarking has drawn extensive attention for protecting digital contents from unauthorized copying. This paper proposes a new watermarking scheme in frequency domain for copyright protection of digital audio. In our proposed watermarking system, the original audio is segmented into non-overlapping frames. Watermarks are then embedded into the selected prominent peaks in the magnitude spectrum of each frame. Watermarks are extracted by performing the inverse operation of watermark embedding process. Simulation results indicate that the proposed scheme is robust against various kinds of attacks such as noise addition, cropping, resampling, re-quantization, MP3 compression, and low pass filtering. Our proposed watermarking system outperforms Cox's method in terms of imperceptibility, while keeping comparable robustness with the Cox's method. Our proposed system achieves SNR (signal-to-noise ratio) values ranging from 20 dB to 28 dB. This is in contrast to Cox's method which achieves SNR values ranging from only 14 dB to 23 dB.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2107-2119
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• 2022

Accurate remaining useful life (RUL) prediction for critical components of nuclear power equipment is an important way to realize aging management of nuclear power equipment. The electric gate valve is one of the most safety-critical and widely distributed mechanical equipment in nuclear power installations. However, the electric gate valve's extended service in nuclear installations causes aging and degradation induced by crack propagation and leakages. Hence, it is necessary to develop a robust RUL prediction method to evaluate its operating state. Although the particle filter(PF) algorithm and its variants can deal with this nonlinear problem effectively, they suffer from severe particle degeneracy and depletion, which leads to its sub-optimal performance. In this study, we combined the whale algorithm with regularized particle filtering(RPF) to rationalize the particle distribution before resampling, so as to solve the problem of particle degradation, and for valve RUL prediction. The valve's crack propagation is studied using the RPF approach, which takes the Paris Law as a condition function. The crack growth is observed and updated using the root-mean-square (RMS) signal collected from the acoustic emission sensor. At the same time, the proposed method is compared with other optimization algorithms, such as particle swarm optimization algorithm, and verified by the realistic valve aging experimental data. The conclusion shows that the proposed method can effectively predict and analyze the typical valve degradation patterns.