• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2141-2155
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• 2020

In order to meet the requirements of background change, illumination variation, moving shadow interference and high accuracy in object detection of moving camera, and strive for real-time and high efficiency, this paper presents an object detection algorithm based on sparse approximation recursion and sparse coding migration in subspace. First, low-rank sparse decomposition is used to reduce the dimension of the data. Combining with dictionary sparse representation, the computational model is established by the recursive formula of sparse approximation with the video sequences taken as subspace sets. And the moving object is calculated by the background difference method, which effectively reduces the computational complexity and running time. According to the idea of sparse coding migration, the above operations are carried out in the down-sampling space to further reduce the requirements of computational complexity and memory storage, and this will be adapt to multi-scale target objects and overcome the impact of large anomaly areas. Finally, experiments are carried out on VDAO datasets containing 59 sets of videos. The experimental results show that the algorithm can detect moving object effectively in the moving camera with uniform speed, not only in terms of low computational complexity but also in terms of low storage requirements, so that our proposed algorithm is suitable for detection systems with high real-time requirements.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.12
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• pp.89-99
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• 2008

In this paper, the position tracking control problem of the servo system with nonlinear dynamic friction is issued. The nonlinear dynamic friction contains a directly immeasurable friction state variable and the uncertainty caused by incomplete parameter modeling and its variations. In order to provide the efficient solution to these control problems, we propose the composite control scheme, which consists of the robust friction state observer, the FNN approximator and the approximation error estimator with sliding mode control. In first, the sliding mode controller and the robust friction state observer is designed to estimate the unknown internal state of the LuGre friction model. Next, the FNN estimator is adopted to approximate the unknown lumped friction uncertainty. Finally, the adaptive approximation error estimator is designed to compensate the approximation error of the FNN estimator. Some simulations and experiments on the servo system assembled with ball-screw and DC servo motor are presented. Results show the remarkable performance of the proposed control scheme. The robust friction state observer can successfully identify immeasurable friction state and the FNN estimator and adaptive approximation error estimator give the robustness to the proposed control scheme against the uncertainty of the friction parameters.

• Journal of the Korea Safety Management & Science
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• v.8 no.3
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• pp.1-9
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• 2006

Recently data mining techniques have been used for analysis and classification of data related to industrial accidents. The main objective of this study is to compare algorithms for data analysis of industrial accidents and this paper provides an optimal predicting model of 5 kinds of algorithms including CHAID, CART, C4.5, LR (Logistic Regression) and NN (Neural Network) with ROC chart, lift chart and response threshold. Also, this paper provides an approximation model for an optimal predicting model based on NN. The approximation model provided in this study can be utilized for easy interpretation of data analysis using NN. This study uses selected ten independent variables to group injured people according to a dependent variable in a way that reduces variation. In order to find an optimal predicting model among 5 algorithms, a retrospective analysis was performed in 67,278 subjects. The sample for this work chosen from data related to industrial accidents during three years ($2002\;{\sim}\;2004$) in korea. According to the result analysis, NN has excellent performance for data analysis and classification of industrial accidents.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.513-520
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• 2010

The degradation phenomenon caused by noises significantly corrupts digitalized data. Therefore, a variety of methods to preserve the edge component of signals and remove noise simultaneously have been used in time domain and frequency domain. In this paper, we have proposed a new noise reduction algorithm using wavelet approximation coefficients to reduce the mixed noise overlapping the signal. The proposed algorithm adopts the distribution characteristics of the error function which is obtained by accumulating the wavelet approximation coefficients, in order to improve the capability to separate edges of the signal and noises.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.90-97
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• 2019

The charge redistribution digital-to-analog converter(CR-DAC) is often used for successive approximation register analog-to-digital converter(SAR ADC) that requiring low power consumption and small circuit area. However, CR-DAC is required 2 to the power of N unit capacitors to generate reference voltage for successive approximation of the N-bit SAR ADC, and many unit capacitors occupy large circuit area and consume more power. In order to improve this problem, this paper proposes SAR ADC using series capacitor DAC. The series capacitor DAC is required 2(1+N) unit capacitors to generate reference voltage for successive approximation and charges only two capacitors of the reference generation block. Because of these structural characteristics, the SAR ADC using series capacitor DAC can reduce the power consumption and circuit area. Proposed SAR ADC was designed in CMOS 180nm process, and at 1.8V supply voltage and 500kS/s sampling rate, proposed 6-bit SAR ADC have signal-to-noise and distortion ratio(SNDR) of 36.49dB, effective number of bits(ENOB) of 5.77-bit, power consumption of 294uW.

• Education of Primary School Mathematics
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• v.27 no.3
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• pp.247-260
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• 2024

In real life, the concepts of number range and approximation are frequently used. These concepts are closely related to various mathematical concepts, and the need for research on the defining and learning of these related terms is emphasized. The learning contents of seven mathematical terms related to the range of numbers and approximation were analyzed, focusing on the definition of terms and the context of real life. As a result of analyzing the contents of 10 currently used elementary school mathematics textbooks, the lessons were organized according to the achievement standards presented in the curriculum, but the composition and order, real-life context, examples used in definitions, and the highlighted parts and directions of the activities varied depending on the author's intent. Based on the analysis results, implications for textbook writing and classroom instruction were presented.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.10 no.3
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• pp.7-17
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• 1990

The objective of this paper is to provide a method of optimizing are as of the members as well as shape of both truss and arch structures. The design process includes satisfaction of stress and Euler buckling stress constraints for truss and combined stress constraints for arch structures. In order to reduce the number of detailed finite element analysis, the Force Approximation Method is used. A finite element analysis of the initial structure is performed and the gradients of the member end forces are calculated with respect to the areas and nodal coordinates. The gradients are used to form an approximate structural analysis based on first order Taylor series expansions of the member end forces. Using move limits, a numerical optimizer minimizes the volume of the structure with information from the approximate structural analysis. Numerical examples are performed and compared with other methods to demonstrate the efficiency and reliability of the Force Approximation Method for shape optimization. It is shown that the number of finite element analysis is greatly reduced and that it leads to a highly efficient method of shape optimization of structures.

• Journal of Broadcast Engineering
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• v.23 no.2
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• pp.302-315
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• 2018

Highly non-linear electro-optical transfer function of the Perceptual Quantizer was approximated by a truncated Taylor series, resulting in a closed form solution for luma adjustment. This previous solution is fast and quite suitable for the hardware implementation of luma adjustment, but the approximation error becomes relatively large in the range of 600~3,900 cd/m2 linear light. In order to reduce such approximation error, we propose a new linear model, for which a correction is performed on the position and the slope of line based on the scope of approximation. In order to verify the approximation capability of the proposed linear model, a comparative study on the luma adjustment schemes was conducted using various high dynamic range test video sequences. Via the comparative study, we identified a significant performance enhancement over the previous fast luma adjustment scheme, where a 4.65dB of adjusted luma t-PSNR gain was obtained for a test sequence having a large portion of saturated color pixels.

• Journal of Ocean Engineering and Technology
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• v.15 no.1
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• pp.12-18
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• 2001

This study concentrates on the second-order diffraction problem around circular cylinders in multi-frequency waves. The method of solution is a time-domain Rankine panel method which adopts a higher-order approximation for the velocity potential and wave elevation. In the present study, the multiple second-order quadratic transfer functions are extracted from the second-order time signal generated in random waves, and the comparison with other bench-mark test results shows a good agreement. This approach is directly applicable to prediction of nonlinear forces on offshore structures in random ocean.

• Journal of the Korean Mathematical Society
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• v.49 no.5
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• pp.927-945
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• 2012

An approximation of singular source terms in elliptic problems is developed and analyzed. Under certain assumptions on the curve where the singular source is defined, the second order convergence in the maximum norm can be proved. Numerical results present its better performance compared to previously developed regularization techniques.