• Structural Engineering and Mechanics
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• v.54 no.3
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• pp.419-432
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• 2015

The free vibration of rotating Euler-Bernoulli beams with the thickness and/or width of the cross-section vary linearly along the length is investigated by using the Adomian modified decomposition method (AMDM). Based on the AMDM, the governing differential equation for the rotating tapered beam becomes a recursive algebraic equation. By using the boundary condition equations, the dimensionless natural frequencies and the closed form series solution of the corresponding mode shapes can be easily obtained simultaneously. The computed results for different taper ratios as well as different offset length and rotational speeds are presented in several tables and figures. The accuracy is assured from the convergence and comparison with the previous published results. It is shown that the AMDM provides an accurate and straightforward method of free vibration analysis of rotating tapered beams.

• Journal of Korea Trade
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• v.24 no.7
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• pp.93-106
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• 2020

Purpose - This paper aims to examine the environmental effects of South Korean foreign trade, and the changing relationship between industrial "three wastes" emissions and foreign trade. Design/methodology - Based on time series data of South Korean foreign trade and industrial "three wastes" from 2009 to 2019, a VAR model was used to analyze the long-term internal links and dynamic changes between foreign trade and environmental pollution. Findings - Variance decomposition analysis shows that for the three types of pollutants, self-impact contributes the most to the variance decomposition. It follows that South Korean foreign trade has a certain negative impact on the environment, and this impact has a certain sustainability. Originality/value - This paper contributes to the study on the relationship between foreign trade and environmental pollution. It theoretically proposes a coordinated development path for foreign trade development and green development based on the environmental impact of foreign trade, to provide a reference for the development of collaborative promotion.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.1
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• pp.48-55
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• 2022

This paper proposes a battery remaining useful life (RUL) prediction method using a deep learning-based EMD-CNN-LSTM hybrid method. The proposed method pre-processes capacity data by applying empirical mode decomposition (EMD) and predicts the remaining useful life using CNN-LSTM. CNN-LSTM is a hybrid method that combines convolution neural network (CNN), which analyzes spatial features, and long short term memory (LSTM), which is a deep learning technique that processes time series data analysis. The performance of the proposed remaining useful life prediction method is verified using the battery aging experiment data provided by the NASA Ames Prognostics Center of Excellence and shows higher accuracy than does the conventional method.

• Transactions on Electrical and Electronic Materials
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• v.18 no.4
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• pp.221-224
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• 2017

This paper dealt with the extraction of series arc signals based on wavelet transform in order to improve the accuracy of arc detection in indoor wiring systems. Three types of arc sources including a cord-cord, a terminal-cord, and an outlet-plug were fabricated to simulate typical arc defects. An arc generator fabricated according to UL 1699 was used to generate arcs. The optimal mother wavelet was selected as bior1.5 by calculating the correlation coefficients between the detected single current pulse and the wavelet. The detected arc current signals were then decomposed into eight levels using the discrete wavelet transform that implements the multi-resolution analysis method. By analyzing the decomposed components, the detail components D6, D7, and D8 were associated with arc signals, which were used for signal reconstruction. From the result, it was verified that the proposed method can be used for the extraction of the series arc signal from the AC mains, which is expected to be applied to further analysis of arc signals in indoor wiring systems.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.165-177
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• 2008

Small baseline subset (SBAS) algorithm has been recently developed using an appropriate combination of differential interferograms, which are characterized by a small baseline in order to minimize the spatial decorrelation. This algorithm uses the singular value decomposition (SVD) to measure the time-series surface deformation from the differential interferograms which are not temporally connected. And it mitigates the atmospheric effect in the time-series surface deformation by using spatially low-pass and temporally high-pass filter. Nevertheless, it is not easy to correct the phase unwrapping error of each interferogram and to mitigate the time-varying noise component of the surface deformation from this algorithm due to the assumption of the linear surface deformation in the beginning of the observation. In this paper, we present an improved SBAS technique to complement these problems. Our improved SBAS algorithm uses an iterative approach to minimize the phase unwrapping error of each differential interferogram. This algorithm also uses finite difference method to suppress the time-varying noise component of the surface deformation. We tested our improved SBAS algorithm and evaluated its performance using 26 images of ERS-1/2 data and 21 images of RADARSAT-1 fine beam (F5) data at each different locations. Maximum deformation amount of 40cm in the radar line of sight (LOS) was estimated from ERS-l/2 datasets during about 13 years, whereas 3 cm deformation was estimated from RADARSAT-1 ones during about two years.

• Journal of the Chungcheong Mathematical Society
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• v.26 no.2
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• pp.421-426
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• 2013

We give a series of discrete random variables which converges to a random variable whose distribution function is the Riesz-N$\acute{a}$gy-Tak$\acute{a}$cs (RNT) distribution. We show this using the correspondence theorem that if the moments coincide then their corresponding distribution functions also coincide.

• Management Science and Financial Engineering
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• v.1 no.1
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• pp.21-37
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• 1995

This paper suggests a procedure of decomposing a multi-stage dynamic location problem into stages with respect stage. The problem can be formulated as a mixed integer programming problem, which is difficult to be solved directly. We perform a series of transformations in order to divide the problem into stages. In the process, the assumption of PSO (production-system-only) plays a critical role. The resulting subproblem becomes a typical single-stage dynamic location problem, whose efficient algorithms have been developed efficiently. An extension of this study is to find a method to integrate the solutions of subproblems for a final solution of the problem.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.03a
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• pp.245-250
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• 1998

This thesis is concerned with the development of useful engineering techniques to detect and analyze nonlinearities in mechanical systems. The methods developed are based on the concepts of higher order spectra, in particular the bispectrum and trispectrum, and the Volterra series. The study of higher order statistics has been dominated by work on the bispectrum. The bispectrum can be viewed as a decomposition of the third moment(skewness) of a signal over frequency and as such is blind to symmetric nonlinearities.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.406-410
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• 1990

This paper presents an approximate analysis of the serial production lines using decomposition technique. A serial production line consists of a series of unreliable machines separated by finite buffers. The serial production line is evaluated by approximation method, the results of which are compared with those examined by the discrete time event simulation, based on this approximation method, a gradient technique is proposed, which improves the efficiency of an operation of production line through the re-allocation of buffers.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.91-91
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• 2011

In the present study, the proposed EMD and NSOR models has been applied in hydrology and climate sciences. Here, we present those applications as the following: (1) to extend future scenarios of Global Surface Temperature Anomaly including long-term oscillation component; (2) to extend the future evolution of the Eastern Canada winter precipitation; (3) to apply EMD in detecting climate change.