• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1119-1131
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• 2016

The Neyman-Scott Rectangular Pulses Model (NSRPM) is mainly used to construct hourly rainfall series. This model uses a modest number of parameters to represent the rainfall processes and underlying physical phenomena, such as the arrival of storms or rain cells. In NSRPM, the method of moments has often been used because it is difficult to know the distribution of rainfall intensity. Recently, approximated likelihood function for NSRPM has been introduced. In this paper, we propose a hierarchical model for applying a spatial structure to the NSRPM parameters using the approximated likelihood function. The proposed method is applied to summer hourly precipitation data observed at 59 weather stations (Korea Meteorological Administration) from 1973 to 2011.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.2
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• pp.163-168
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• 2011

Robust optimization or reliability-based design optimization are some of the methodologies that are employed to take into account the uncertainties of a system at the design stage. For applying such methodologies to solve industrial problems, accurate and efficient methods for estimating statistical moments and failure probability are required, and further, the results of sensitivity analysis, which is needed for searching direction during the optimization process, should also be accurate. The aim of this study is to employ the function approximation moment method into the sensitivity analysis formulation, which is expressed as an integral form, to verify the accuracy of the sensitivity results, and to solve a typical problem of reliability-based design optimization. These results are compared with those of other moment methods, and the feasibility of the function approximation moment method is verified. The sensitivity analysis formula with integral form is the efficient formulation for evaluating sensitivity because any additional function calculation is not needed provided the failure probability or statistical moments are calculated.

• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.149-157
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• 2012

In this thesis, the problem of computing approximate answers to continuous sliding-window joins over data streams when the available memory may be insufficient to keep the entire join state. One approximation scenario is to provide a maximum subset of the result, with the objective of losing as few result tuples as possible. An alternative scenario is to provide a random sample of the join result, e.g., if the output of the join is being aggregated. It is shown formally that neither approximation can be addressed effectively for a sliding-window join of arbitrary input streams. Previous work has addressed only the maximum-subset problem, and has implicitly used a frequency based model of stream arrival. There exists a sampling problem for this model. More importantly, it is shown that a broad class of applications for which an age-based model of stream arrival is more appropriate, and both approximation scenarios under this new model are addressed. Finally, for the case of multiple joins being executed with an overall memory constraint, an algorithm for memory allocation across the join that optimizes a combined measure of approximation in all scenarios considered is provided.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.1-8
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• 2007

In this paper, research on joint optimization of the image spatial registration and the exposure compensation is conducted. The exposure compensation is performed in a frame work of the intensity compensation based on the polynomial approximation of the relationship between images. This compensation is jointly combined with the registration problem employing the Gauss-Newton nonlinear optimization method. In this paper, to perform for a simple and stable optimization, the block-coordinate method is combined with the Gauss-Newton optimization and extensively compared with the traditional approaches. Furthermore, regression analysis is considered in the compensation part for a better stable performance. By combining the block-coordinate method with the Gauss-Newton optimization, we can obtain a compatible performance reducing the computational complexity and stabilizing the performance. In the numerical result for a particular image, we obtain a satisfactory result for 10 repeats of the iteration, which implies a 50% reduction of the computational complexity. The error is also further reduced by 1.5dB compared to the ordinary method.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.2
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• pp.87-95
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• 1997

This paper presents an optimal design procedure to realize an BSB neural networks by means of the parametrization of solution space and optimization of parameters using evaluation program. In particular, the performance index based on DOA analysis may make an associative memory implementation reach on the level of practical success.

• The Journal of the Acoustical Society of Korea
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• v.2 no.1
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• pp.41-47
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• 1983

고속 Walsh-hadamard 변환방식을 사용하여 근사적으로 조기적인 신호의 μPCM 데이터를 압축 할 수 있음을 확인하였으며 최대 압축율은 기준 SQNR을 30dB로 할 경우 6 이상임을 보였다. 또한 decion level을 변화시킬 때 SQNR 변화를 조사하였으며 시스템 특성에 다라 decion level의 최적화를 얻을 수 있었다. 또한 양자화 레벨을 조정하여 SQNR을 검토한 바 대체로 선형적임을 나타내었다.

• Proceedings of the Optical Society of Korea Conference
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• 2001.02a
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• pp.30-31
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• 2001

다중모드간섭을 이용한 소자는 집적광학에서 광신호의 분리와 결합에 있어서 널리 사용되고 있다. 이러한 소자는 편광상태와 파장에 덜 민감하며, 광 대역폭과 제작 허용오차가 크다는 장점을 가진다. 이러한 다중모드간섭기의 설계에 있어서 간섭기의 폭은 주로 출력단에서의 도파로 폭과 도파로간 간격으로부터 정해져왔다. 본 연구에서는 특별히 광신호의 효율적인 분배를 위해 간섭기의 폭과 관련하여 광 분배기의 손실 및 균일도를 최적화하기 위한 방안을 강구하였으며, 근사적인 이론식에 의한 결과와 비교하였다. (중략)

• Proceedings of the KAIS Fall Conference
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• 2003.06a
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• pp.211-214
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• 2003

본 연구에서는 실리콘 웨이퍼 제조 현장에서 사용 중인 단결정 실리콘 성장기의 자동 직경 제어기를 2계 근사 모델을 이용하여 설계하고 시간지연 보상기를 적용함으로써 결정봉의 직경과 인상 속도를 최적화하여 결정봉의 제품에 직접적인 영향을 주는 결정 결함 및 언더나 오버의 직경 이상을 줄이고 제품의 질과 수율을 향상시킬 수 있다. 또한 기존의 자동직경제어시스템의 고전적인 제어기를 보완함으로써 결과적으로 생산량 증가 및 제품의 질 향상에 이바지를 하고 새로이 요구되는 고객의 신기술 요구에 대한 현 장비의 제한성을 극복하는데 큰 기여를 할 것으로 기대 된다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.2
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• pp.176-181
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• 2002

In this paper, we consider the optimal control of detection threshold to minimize the conditional expectation of mean-square state estimation error for a probabilistic data association (PDA) filter. Earlier works on this problem involved the cumbersome graphical optimization algorithm or time-consuming numerical optimization algorithm. Using the numerical approximation of information reduction factor, we obtained the suboptimal detection threshold in a closed-form. This results are very useful for real- time implementation.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.6
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• pp.55-60
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• 2020

The injection molding technique is a processing method widely used for the production of plastic parts. In this study, the gate position, gate size, packing time, and melt temperature were optimized to minimize both the stress and deformation that occur during the injection molding process of medical suction device components. We used a central composite design and Latin hypercube sampling to acquire the data and adopted the response surface method as an approximation method. The efficiency of the optimization of the injection molding problem was determined by comparing the results of a genetic algorithm, sequential quadratic programming, and a non-dominant classification genetic algorithm.