• Korean Management Science Review
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• v.29 no.1
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• pp.1-14
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• 2012

The goal of the multi-reservoir operation planning is to provide an optimal release plan that maximize the reservoir storage and hydropower generation while minimizing the spillages. However, the reservoir operation is difficult due to the uncertainty associated with inflows. In order to consider the uncertain inflows in the reservoir operating problem, we present a Stochastic Dynamic Programming (SDP) model based on the markov decision process (MDP). The objective of the model is to maximize the expected value of the system performance that is the weighted sum of all expected objective values. With the SDP model, multi-reservoir operating rule can be derived, and it also generates the steady state probabilities of reservoir storage and inflow as output. We applied the model to the Geum-river basin in Korea and could generate a multi-reservoir monthly operating plan that can consider the uncertainty of inflow.

• 한국연소학회:학술대회논문집
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• 1999.10a
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• pp.155-163
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• 1999

A numerical study for simulating a swirling pulverized coal combustion in axisymmetric geometry is done here by applying the weighted sum of gray gases model (WSGGM) approach with the discrete ordinate method (DOM) to model the radiative heat transfer equation. In the radiative transfer equation, the same polynomial equation and coefficients for weighting factors as those for gas are adopted for the coal/char particles as a function of partial pressure and particle temperature. The Eulerian balance equations for mass, momentum, energy, and species mass fractions are adopted with the standard ${\kappa}-{\varepsilon}$ turbulence model, whereas the Lagrangian approach is used for the particulate phase for soot. The eddydissipation model is employed for the reaction rate for gaseous mixture, and the single-step first-order reaction model for the devolatilization process for coal. By comparing the numerical results with experimental ones, the models used here are confirmed and found to be one of good alternatives for simulating the combustion as well as radiative characteristics.

• Journal of the Korean Mathematical Society
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• v.55 no.3
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• pp.719-734
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• 2018

An image restoration problem with Poisson noise arises in many applications of medical imaging, astronomy, and microscopy. To overcome ill-posedness, Total Variation (TV) model is commonly used owing to edge preserving property. Since staircase artifacts are observed in restored smooth regions, higher-order TV regularization is introduced. However, sharpness of edges in the image is also attenuated. To compromise benefits of TV and higher-order TV, the weighted sum of the non-convex TV and non-convex higher order TV is used as a regularizer in the proposed variational model. The proposed model is non-convex and non-smooth, and so it is very challenging to solve the model. We propose an iterative reweighted algorithm with the proximal linearized alternating direction method of multipliers to solve the proposed model and study convergence properties of the algorithm.

• Bulletin of the Korean Mathematical Society
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• v.54 no.4
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• pp.1443-1455
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• 2017

Let $M_{z^N}(N{\in}{\mathbb{Z}}^d_+)$ be a bounded multiplication operator on a class of Hilbert spaces with orthogonal basis $\{z^n:n{\in}{\mathbb{Z}}^d_+\}$. In this paper, we prove that each reducing subspace of $M_{z^N}$ is the direct sum of some minimal reducing subspaces. For the case that d = 2, we find all the minimal reducing subspaces of $M_{z^N}$ ($N=(N_1,N_2)$, $N_1{\neq}N_2$) on weighted Bergman space $A^2_{\alpha}({\mathbb{B}}_2)$(${\alpha}$ > -1) and Hardy space $H^2({\mathbb{B}}_2)$, and characterize the structure of ${\mathcal{V}}^{\ast}(z^N)$, the commutant algebra of the von Neumann algebra generated by $M_{z^N}$.

• Journal of information and communication convergence engineering
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• v.15 no.1
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• pp.7-13
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• 2017

We consider a distributed estimation where many nodes remotely placed at known locations collect the measurements of the parameter of interest, quantize these measurements, and transmit the quantized data to a fusion node; this fusion node performs the parameter estimation. Noting that quantizers at nodes should operate in a non-regular framework where multiple codewords or quantization partitions can be mapped from a single measurement to improve the system performance, we propose a low-weight estimation algorithm that finds the most feasible combination of codewords. This combination is found by computing the weighted sum of the possible combinations whose weights are obtained by counting their occurrence in a learning process. Otherwise, tremendous complexity will be inevitable due to multiple codewords or partitions interpreted from non-regular quantized data. We conduct extensive experiments to demonstrate that the proposed algorithm provides a statistically significant performance gain with low complexity as compared to typical estimation techniques.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1560-1563
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• 1987

This paper is concerned with time delay modeling of ED MOS gates which takes into account the slope of input waveform as well as the load condition. Defining the delay time as the time required to charge/discharge the load to the physical reference level, the rise/fall delay times arc derived in an explicit formula in terms of the sum of optimally weighted current unbalances at two end points of voltage transition. The proposed model is computationally effective and the error is typically within 10% of the SPICE results.

• The Korean Journal of Applied Statistics
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• v.6 no.1
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• pp.67-78
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• 1993

A new diagnostic statistic for detecting outliers and influential observations in linear models is suggested and studied in this paper. The proposed statistic is a weighted sum of two measures; one is for detecting outliers and the other is for detecting influential observations. The merit of this statistic is that it is possible to distinguish outliers from influential observations. We have done some Monte-Carlo Simulation to find the probability distribution of this statistic.

• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.465-470
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• 2012

EWMA(exponentially weighted moving average) charts and CUSUM(cumulative sum) charts are very effective to detect small shifts in the process mean. These charts have some control-chart parameters that allow the charts and be tuned and be more sensitive to certain shifts. The EWMA chart requires users to specify the value of a smoothing parameter, which can also be designed for the size of the mean shift. However, the size of the mean shift that occurs in applications is usually unknown and EWMA charts can perform poorly when the actual size of the mean shift is significantly different from the assumed size. In this paper, we propose the design procedure to find the optimal smoothing parameter of the EWMA chart when the size of the mean shift is unknown.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2001.09a
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• pp.88-91
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• 2001

The purpose of this study is to localize the recharge rate into the national scale, calculated by use of the groundwater level from the 123 monitoring stations. The soil type, land use type, and bedrocks are selected for the influential factors over recharge rate. The main hypothesis is that the recharge rate can be expressed by the sum of the weighted averages of recharge rates of each factors. The optimized weights of soil type, land-use time and bedrocks from 119 stations are 0.80, 0.18 and 0.02 respectively. So this study offers that localization is available from the recharge rates calculated by groundwater level monitoring results.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.239-242
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• 2018

문맥 표현은 Recurrent neural network (RNN)에 기반한 언어 모델을 학습하여 얻은 여러 층의 히든 스테이트(hidden state)를 가중치 합(weighted sum)을 하여 얻어낸 벡터이다. Convolution neural network (CNN)를 이용하여 음절 표현을 학습하는 경우, 데이터 내에서 발생하는 미등록어를 처리할 수 있다. 본 논문에서는 음절 표현 CNN 기반의 포인터 네트워크와 문맥 표현을 함께 이용하는 방법을 제안하고, 이를 상호참조해결에 적용한다. 실험 결과, 질의응답 데이터셋에서 CoNLL F1 57.88%로 규칙기반에 비하여 11.09% 더 좋은 성능을 보였다.