• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.2
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• pp.137-144
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• 2001

In this paper, a state assignment algorithm was proposed to reduce power consumption in control-flow oriented finite state machines. The Markov chain model is used to reduce the switching activities, which closely relate with dynamic power dissipation in VLSI circuits. Based on the Markov probabilistic description model of finite state machines, the hamming distance between the codes of neighbor states was minimized. To express the switching activities, the cost function, which also accounts for the structure of a machine, is used. The proposed state assignment algorithm is tested with Logic Synthesis Benchmarks, and reduced the cost up to 57.42% compared to the Lakshmikant's algorithm.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.2
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• pp.267-276
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• 1993

This paper discusses the neural network application in the study on the obstacle avoidance of robot manipulator during the trajectory planning. The collision problem of two robot manipulators which are simultaneously moving in the same workspace is investigated. Instead of the traditional modeling method, this paper processing based on the calculation of joint angle in the cartesian coordinate with constrained condition shows the possibility of real time control. The problem of the falling into the local minima is cleared by the adaptive weight factor control using the temperature adding method. Computer simulations are shown for the verification.

• Microbiology and Biotechnology Letters
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• v.18 no.4
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• pp.394-400
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• 1990

Maximization of productivity of recombinant cell fermentations requires consideration of the inverse relationship between the host cell growth rate and product formation rate. The problem of maximizing a weighted performance index was solved by using optimal control theory for recombinant E. coli fermentation. Concentration of a growth inhibitor was used as a control variable to manipulate the specific growth rate, and consequently the cloned-gene expression rate. Using a simple unstructured model to describe the main characteristics of this system, theoretical analysis showed that the optimal control profile results in an initial high growth rate phase followed by a low growth rate and high product formation rate phase. Numerical calculations were done to determine optimal switching times from the growth to the production stage for two representative cases corresponding to different dependency of the product formation rate on the growth rate. For the case when product formation rate is sensitive to the specific growth rate, the optimized operation yields about 60% increase in the final product concentration compared with a simple batch fermentation.

• Journal of Labour Economics
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• v.36 no.1
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• pp.45-62
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• 2013

In this study, we revisit an empirical literature has found that neighborhood income inequality lowers people's likelihood of contributing public goods in terms of volunteering. We contribute to the literature by explicitly addressing the issues of larger and improper neighborhood choice with a census-type data and endogenous neighborhood location with some unique features of 2009 Social Survey Data by Statistics Korea. The results have confirmed that income heterogeneity lowers people's volunteering.

• Journal of Power System Engineering
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• v.14 no.3
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• pp.33-38
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• 2010

Technology of vehicle industry has been developing and it is required a better vehicle performance than before. Therefore, the consumers are asking not only an economic efficiency, functionality, polished design, ride comfort and silence but also a driving stability. The ride comfort, silence and driving stability are influenced by the size of vehicle and various facilities. But the principal factor is a room noise and vibration sensed by a driver and passenger. Thus, the NVH of vehicle has been raised and used as a principal factor for evaluation of vehicle performance. The primary objective of this study is an optimized design of powertrain mounting system. To optimized design was applied MSC.Nastran optimization modules. Results of dynamic analysis for powertrain mounting system was investigated. By theses results, design variables was applied 12 dynamic spring constant. And the weighting factor according to translational displacement and rotational displacement applied 3 cases. The objective function was applied to minimize displacement of powertrain. And the design variable constraint was imposed dynamic spring constant ratio. The constraint of design variable for objective function was imposed bounce displacement for powertrain.

• The Korean Journal of Applied Statistics
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• v.15 no.1
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• pp.57-71
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• 2002

We introduce three types of exponential survival models, such as simple model, change-point model and finite mixture model in this paper. Among these models, in order to choose the best model, the model choice method is proposed using Gelfand and Ghosh(1998)'s idea. Then to avoid the computational difficulties, data augmentation method (Tanner and Wong, 1987) and Gibbs sampler (Gelfand and Smith, 1990) are employed. Our methodology is applied to both simulated data and Stangl (1991)'s On-impramint Hydrochloride data.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1147-1154
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• 2010

One of the important goals in data mining is to discover and decide the relationships between different variables. Association rules are required for this technique and it find meaningful rules by quantifying the relationship between two items based on association measures such as support, confidence, and lift. In this paper, we presented the evaluation criteria of weighted association rule considering item RFM scores as importance of items. Original RFM technique has been used most widely applied method using customer information to find the most profitable customers. And then we compared general association rule technique with weighted association rule technique through the simulation data.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.9-16
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• 2008

Recently, there are a lot of multimedia products using image interpolation system. However, most interpolation systems in existence suffer visually to some extents from the effects of blurred edges and jagged artifacts in the image. In this paper, we propose a new adaptive linear interpolation system that uses the sub-pixel. The proposed system calculate the warped distance among the pixels of an image by optimizing length parameter. A new cost function is introduced to reflect frequency properties of the origin data in order to improve image quality. Experimental results show that our new algorithm significantly outperforms conventional interpolation methods in subjective quality, and in most cases, in terms of PSNR as well.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.12 no.4
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• pp.619-627
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• 1999

다분야 통합 시스템의 설계문제는 다량의 설계변수와 구속조건으로 구성되며 다수의 공학적 현상으로 연관되어 있다. 다분야 통합 최적설계 문제를 효과적으로 다루기 위해서는 다양한 해석분야의 공학적 설계원리를 동시에 고려하여 균형 있고 유기적인 방법으로 최적의 설계를 결정하는 체계적인 설계자동화기술이 요구된다. 다분야 통합 설계문제를 위한 효율적인 설계방법론으로 분리기반 최적화 기법이 적용되는데 이 방법은 한 단위의 대규모 설계문제를 여러 개의 하부시스템으로 분리하여 독립적으로 최적화를 수행하고 각 하부 시스템으로부터의 설계해 사이의 중재 및 통합화를 거쳐 최종적으로 수렴된 최적설계를 찾는 방법이다. 본 논문에서는 분리기반 최적화기법을 다분야 통합최적 설계문제에 적용하는데 필요한 시스템분리기법을 유전알고리즘 및 다층 역전 파 신경회로망을 이용하여 정립하였다. 시스템분리기법을 검증하기 위해 최근 미국 Boeing사에서 개발중인 고속 민간항공기인 HSCT의 시뮬레이션기반 설계문제를 이용하였다. 대규모 설계시스템의 분리결과는 전체 설계문제의 특성을 파악하기 위한 자료로 활용되며 향후, 분리기반 최적화과정에서 최종적으로 통합된 최적설계를 탐색하는데 필요한 기반구조를 제공한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.217-217
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• 2023

상수도관망은 사용자에게 고품질의 물을 안정적으로 공급하는 것을 목적으로 하며, 이를 평가하기 위한 지표 중 하나로 압력을 활용한다. 최근 스마트 센서의 설치가 확장됨에 따라 기계학습기법을 이용한 실시간 데이터 기반의 분석이 활발하다. 따라서 어디에서 데이터를 수집하느냐에 대한 센서 위치 결정이 중요하다. 본 연구는 eXtreme Gradient Boosting(XGBoost) 모델을 활용하여 대규모 상수도관망 내 센서 위치를 최적화하는 방법론을 제안한다. XGBoost 모델은 여러 의사결정 나무(decision tree)를 활용하는 앙상블(ensemble) 모델이며, 오차에 따른 가중치를 부여하여 성능을 향상시키는 부스팅(boosting) 방식을 이용한다. 이는 분산 및 병렬 처리가 가능해 메모리리소스를 최적으로 사용하고, 학습 속도가 빠르며 결측치에 대한 전처리 과정을 모델 내에 포함하고 있다는 장점이 있다. 모델 구현을 위한 독립 변수 결정을 위해 압력 데이터의 변동성 및 평균압력 값을 고려하여 상수도관망을 대표하는 중요 절점(critical node)를 선정한다. 중요 절점의 압력 값을 예측하는 XGBoost 모델을 구축하고 모델의 성능과 요인 중요도(feature importance) 값을 고려하여 센서의 최적 위치를 선정한다. 이러한 방법론을 기반으로 상수도관망의 특성에 따른 경향성을 파악하기 위해 다양한 형태(예를 들어, 망형, 가지형)와 구성 절점의 수를 변화시키며 결과를 분석한다. 본 연구에서 구축한 XGBoost 모델은 추가적인 전처리 과정을 최소화하며 대규모 관망에 간편하게 사용할 수 있어 추후 다양한 입출력 데이터의 조합을 통해 센서 위치 외에도 상수도관망에서의 성능 최적화에 활용할 수 있을 것으로 기대한다.