• 한국해양공학회지
• /
• 제26권6호
• /
• pp.80-85
• /
• 2012

The methods of robust design optimization (RDO) and reliability-based robust design optimization (RBRDO) were implemented in the present study. RBRDO is an integrated method that accounts for the design robustness of an objective function and for the reliability of constraints. The objective function in RBRDO is expressed in terms of the mean and standard deviation of an original objective function. Thus, a multi-objective formulation is employed. The regressive approximate models are generated via the moving least squares method (MLSM) and constraint-feasible moving least squares method (CF-MLSM), which make it possible to realize the feasibility regardless of the multimodality/nonlinearity of the constraint function during the approximate optimization processes. The regression model based RBRDO is newly devised and its numerical characteristics are explored using the design of an actively controlled ten bar truss structure.

• 전기학회논문지
• /
• 제57권4호
• /
• pp.692-699
• /
• 2008

Semiconductor research and development(R&D) fabs are very different than production fabs in many ways such as the scales of production, job priority, production methods, and performance measures. Efficient operations of R&D fabs are very important to the development of new product, process stability, high yield, and ultimately company competitiveness. This paper proposes the fab-wide scheduling method for operational optimization of the R&D fabs. Most scheduling systems of semiconductor fabs have only focused on maximizing throughput of each separated areas without considering WIP(works in process) flows of entire fab. In this paper, we proposes the a fab-wide scheduling system which schedules all lots to entire fab equipment at once. We develop the MIP(mixed integer programing) model which allocates the lots to production equipment considering many constraints of all processes and the CP(constraint programming) model which determines the sequences of the lots in the production equipment. The proposed FAB-wide scheduling model is applied to the newly constructed R&D fab. As a result, we have accomplished the system based automated job reservation, decrease of the hot lot delay, increase of the queue time satisfaction, the high throughput by maximizing the batch sizes, decrease of the WIP TAT(Turn Around Time).

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2013년도 추계학술대회 논문집
• /
• pp.236-240
• /
• 2013

Due to difficulty of considering dynamic load in side of a computer resource and computing time, it is common that external load is assumed as ideal static load. However, structural analysis under static load cannot guarantee the safety of structural design. Recently, the systematic method to construct equivalent static load from the given dynamic load has been proposed. Previous study has calculated equivalent static load through the optimization procedure under displacement constraints. And previously reported works to distribute equivalent static load were based on ad hoc methods. However, it is appropriate to take into account the stress constraint for the safety design. Moreover, the improper selection of loading position may results in unreliable structural design. The present study proposes the methodology to optimize an equivalent static which distributed on the primary DOFs, DOFs of the constraint elements, DOF of an external load as positions. In conclusion, the reliability of proposed method is demonstrated through a global optimization.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권4호
• /
• pp.1263-1274
• /
• 2021

In online competitive social networks, each user can be influenced by different competing influencers and consequently chooses different products. But their interest may change over time and may have swings between different products. The existing influence spreading models seldom take into account the time-related shifts. This paper proposes a minimum cost influence maximization algorithm based on the competitive transition probability. In the model, we set a one-dimensional vector for each node to record the probability that the node chooses each different competing influencer. In the process of propagation, the influence maximization on Competitive Linear Threshold (IMCLT) spreading model is proposed. This model does not determine by which competing influencer the node is activated, but sets different weights for all competing influencers. In the process of spreading, we select the seed nodes according to the cost function of each node, and evaluate the final influence based on the competitive transition probability. Experiments on different datasets show that the proposed minimum cost competitive influence maximization algorithm based on IMCLT spreading model has excellent performance compared with other methods, and the computational performance of the method is also reasonable.

• 한국멀티미디어학회논문지
• /
• 제7권12호
• /
• pp.1737-1744
• /
• 2004

In the compression methods widely used today, the image compression by VQ is the most popular and shows a good data compression ratio. Almost all the methods by VQ use the LBG algorithm that reads the entire image several times and moves code vectors into optimal position in each step. This complexity of algorithm requires considerable amount of time to execute. To overcome this time consuming constraint, we propose an enhanced self-organizing neural network for color images. VQ is an image coding technique that shows high data compression ratio. In this study, we improved the competitive learning method by employing three methods for the generation of codebook. The results demonstrated that compression ratio by the proposed method was improved to a greater degree compared to the SOM in neural networks.

• 한국데이터정보과학회:학술대회논문집
• /
• 한국데이터정보과학회 2006년도 PROCEEDINGS OF JOINT CONFERENCEOF KDISS AND KDAS
• /
• pp.163-169
• /
• 2006

This paper deals with the comparison of parameter estimation methods in a 3-parameter Kappa distribution which is sometimes used in flood frequency analysis. The method of moment estimation(MME), L-moment estimation(L-ME), and maximum likelihood estimation(MLE) are applied to estimate three parameters. The performance of these methods are compared by Monte-carlo simulations. Especially for computing MME and L-ME, ike dimensional nonlinear equations are simplied to one dimensional equation which is calculated by the Newton-Raphson iteration under constraint. Based on the criterion of the mean squared error, the L-ME is recommended to use for small sample size $(n\leq100)$ while MLE is good for large sample size.

• 대한산업공학회지
• /
• 제25권2호
• /
• pp.240-253
• /
• 1999

In this paper we propose new approximate methods for the performance analysis of closed-loop production systems with unreliable machines and random processing times. Each approximate method decomposes the production system consisting of K machines into a set of K subsystems, each subsystem consisting of two machines separated by a finite buffer. Then, each subsystem is analyzed by three different analyzing methods in isolation. The population constraint of the closed-loop production system is taken into account by prescribing that the sum of average buffer levels in the subsystems is equal to the number of customers in the closed-loop production system. We establish a set of equations that characterize unknown parameters of the servers in the subsystems. An iterative procedure is then used to determine the unknown parameters. Experimental results show that these methods provide a good estimation of the throughput.

• Communications for Statistical Applications and Methods
• /
• 제12권2호
• /
• pp.443-451
• /
• 2005

The studied in this paper is a new algorithm for searching the maximum likelihood estimate(MLE) in which probability density function is not explicitly expressed. Newton-Raphson's root-finding routine and a nonlinear numerical optimization algorithm with constraint (so-called feasible sequential quadratic programming) are used. This algorithm is applied to the Wakeby distribution which is importantly used in hydrology and water resource research for analysis of extreme rainfall. The performance comparison between maximum likelihood estimates and method of L-moment estimates (L-ME) is studied by Monte-carlo simulation. The recommended methods are L-ME for up to 300 observations and MLE for over the sample size, respectively. Methods for speeding up the algorithm and for computing variances of estimates are discussed.

• 한국통신학회논문지
• /
• 제37권6A호
• /
• pp.458-463
• /
• 2012

본 논문에서는 평행형 카메라 배열 뿐 아니라 수렴형 카메라 배열에서도 깊이 지도를 직접적으로 구할 수 있는 방법을 제안한다. 기존의 스테레오 정합 방법들은 복잡도를 줄이고 정확도를 향상시키기 위해서 영상 정렬화를 수행한다. 하지만 수렴형 배열에서의 영상 정렬화는 원치 않는 결과를 발생시킨다. 따라서 제안하는 방법은 문제가 되는 영상 정렬화 과정을 생략하고, 영상 자체의 에피폴라 제약 사항을 이용하여 깊이 값을 직접적으로 추출한다. 깊이 지도의 정확도를 보다 향상시키기 위해서 폐색 영역을 탐지하고 처리하는 과정을 추가적으로 수행한다. 탐지한 폐색 영역은 보이는 주변 영역의 화소들과의 거리와 색상차를 고려하여 적절한 깊이 값으로 채워진다. 실험을 통해 제안한 방법이 기존의 방법에 비해 카메라 배열에 대한 제약이 적고, 안정적으로 깊이 지도를 생성할 수 있음을 확인했다.

• 한국멀티미디어학회논문지
• /
• 제11권4호
• /
• pp.471-480
• /
• 2008

농자들은 청각장애를 가지고 있기 때문에 알람, 도어 벨, 싸이렌, 경적, 전화 벨 등과 같은 유용한 소리정보를 인식할 수 없다. 이러한 문제를 해결하기 위해서는 주요한 환경소리 인식방법을 탑재한 휴대형 청각보조 장구가 요구되어진다. 본 논문에서는 환경소리 인식시스템에 적용할 수 있는 능동형 기울기 가중치제약 방식의 새로운 동적 시간정합 알고리듬을 제안하였다. 환경소리 인식방법은 크게 세 단계로 구성된다. 첫 번째 단계에서는 소리의 주파수 성분과 크기를 이용하여 시작점과 끝점을 추출한다. 두 번째 단계에서는 추출된 구간에 대하여 특징을 추출하며 세 번째 단계에서는 추출된 특징들을 분류한다. 실험 결과 제안한 방법의 인식률이 거의 90%가 되었다. 그리고 기존의 동적 시간정합 알고리듬과 비교하였을 때 인식율에 있어서 약 20%정도의 개선이 있었다. 따라서 제안된 방법을 사용하여 농자가 환경소리를 인식할 수 있는 휴대형 청각 보조 장구가 개발된다면 그들의 생활에 편리함을 줄 수 있을 것으로 판단된다.