• Nuclear Engineering and Technology
• /
• 제51권4호
• /
• pp.954-962
• /
• 2019

It is well known that the variance of tally is biased in a Monte Carlo calculation based on the power iteration method. Several studies have been conducted to estimate the real variance. Among them, the batch method, which was proposed by Gelbard and Prael, has been utilized actively in many Monte Carlo codes because the method is straightforward, and it is easy to implement the method in the codes. However, there is a problem when utilizing the batch method because the estimated variance varies depending on batch size. Often, the appropriate batch size is not realized before the completion of several Monte Carlo calculations. This study recognizes this shortcoming and addresses it by permitting selection of an appropriate batch size.

• 한국시뮬레이션학회논문지
• /
• 제5권2호
• /
• pp.59-72
• /
• 1996

The purpose of this study is to make an improvement to the batch-means method, which is a procedure to construct a confidence interval(c.i.) for the steady-state process mean of a stationary simulation output process. In the batch-means method, the data in the output process are grouped into batches. The sequence of means of the data included in individual batches is called a batch-menas process and can be treated as an independently and identically distributed set of variables if each batch includes sufficiently large number of observations. The traditional batch-means method, therefore, uses a batch size as large as possible in order to. destroy the autocovariance remaining in the batch-means process. The c.i. prodedure developed and empirically tested in this study uses a small batch size which can be well fitted by a simple ARMA model, and then utilizes the dependence structure in the fitted model to correct for bias in the variance estimator of the sample mean.

• 분석과학
• /
• 제12권3호
• /
• pp.196-202
• /
• 1999

갈조류인 Sargassum horneri를 중금속 흡착제로 사용하여 중금속 Cd(II) 및 Pb(II)이온을 제거하였다. Sargassum horneri는 동해안에서 채취하였고, 풍건 건조시켜 40~60 mesh의 입자 크기로 흡착제를 만들어 사용하였다. batch법은 진탕 시간에 따른 흡착량을 측정함으로써 흡착속도를 조사하였고, column법은 해조 분말을 충진 시킨후 일정농도의 중금속용액을 1 mL/min의 속도로 흘려보내면서 흡착시키고 흡착량을 알아 보았다. 중금석 흡착에 미치는 pH의 영향은 batch법과 column법 모두, pH 10.5>7.0>3.5순으로 나타났다. Pb(II)이온이 Cd(II)이온보다 높은 흡착량을 보였다. 특히 batch법에서는 모든 pH의 조건하에서 5분이내에 최대 흡착량에 도달하였다. 회수율은 batch법에 의해 흡착된 중금속의 회수율이 column법에 의해 흡착된 중금속의 회수율 보다 조금 높게 나타났다.

• 한국건축시공학회지
• /
• 제13권6호
• /
• pp.565-578
• /
• 2013

Batch production is common in repetitive construction projects, and it is not unusual for different batch sizes to be used by contractors in one project. While several scheduling methods, such as the Linear Scheduling Method (LSM) and the Repetitive Scheduling Method (RSM) have been proposed and used, no mathematical method for repetitive construction projects has been developed, and it is difficult to consider different batch sizes with the existing methods. An original mathematical algorithm for scheduling repetitive projects with different batch sizes is proposed in this study. This algorithm is illustrated with assumptions of resource continuity and single path in a project and introduces new terms, control batch and critical batch. The algorithm logics and mathematical equations are validated by comparison with the outcomes from a graphical scheduling approach through a simple and practical hypothetic project. As a result, it is expected that the proposed algorithm can be easily adapted and extended to computer software for scheduling, and can be a starting point for research on batch size management in repetitive construction projects.

• 한국컴퓨터정보학회논문지
• /
• 제25권12호
• /
• pp.187-194
• /
• 2020

오늘날 반도체나 석유 화학 공정과 같이 프로세스 중심의 산업에서는 관측된 자료들 사이에 자기 상관이 존재한다. 자기상관이 존재하는 공정에 대한 관리 방법으로는 관측치를 이용하여 뱃치 평균이 독립에 가까워지도록 뱃치를 구성하여 관리하거나, 관측치의 EWMA (지수 가중치 이동 평균) 통계량을 EWMA 관리도에 적용하는 방법등이 주로 사용되고 있다. 본 논문에서는 관찰치에 대한 관리 방법으로 일반적으로 사용되는 UBM 의 뱃치 크기를 결정하는 방법을 소개하고, ARL(평균 실행 길이)을 기반으로 최적 뱃치 크기를 정하는 방법과 그러한 뱃치 구성에서 공정의 표준 편차를 추정하는 방법을 제안 한다. 자기상관이 존재하는 공정에 대한 개선된 관리도를 제안하고자 한다.

• 한국초전도ㆍ저온공학회논문지
• /
• 제7권3호
• /
• pp.9-12
• /
• 2005

[ $Y_1Ba_2Cu_3O_{7-8}$ ] (YBCO) coated conductor has been fabricated by batch-type process using oxide-precursor-based metal-organic deposition (MOD) method. The batch-type process can be scaled up more simply to Produce long-length YBCO conductor than the reel-to-reel process. Also, it has less handling problems and is adequate to the ambient gas environment. In this work, YBCO oride powder was used as a starting precursor for MOD method. After reel-to-reel dip coating process, me ter-long-buffered metal tape was wound around a cylinder and underwent calcination and annealing processes. Annealed YBCO films showed good c-axis alignment and dense surface morphology with no cracks, but exhibited very low critical current density of $10^5\;A/cm^2$.

• 대한산업공학회지
• /
• 제33권2호
• /
• pp.246-253
• /
• 2007

All of the machines in a production line can be classified into bottleneck and non-bottleneck machines. A bottleneck is a resource whose capacity limits the throughput of the whole production facility. This paper addresses a batch sizing problem at the bottleneck machine. Traditionally, most batch sizing decisions have been made based on the EOQ (economic order quantity) model where setup and inventory costs are considered while throughput rate is assumed to be given. However, since batch size affects the capacity of the bottleneck machine, the throughput rate may not be constant. As the batch size increases, the frequency of the setup decreases. The saved setup time can be transferred to processing time, which results in higher throughput. But, the larger batch size may also result in longer lead time and larger WIP inventory level. This paper presents an alternative method to determine batch size at the bottleneck machine in a manufacturing line. A linear search algorithm is introduced to find optimal throughput rate and batch size at the same time. Numerical examples are provided to see how the proposed method works and to investigate the effects of some parameters.

• 제어로봇시스템학회논문지
• /
• 제18권3호
• /
• pp.285-294
• /
• 2012

Using bearing measurement only, target motion state is not directly obtained so that TMA (Target Motion Analysis) is needed for this situation. TMA is a nonlinear estimation technique used in passive SONAR systems. Also it is the one of important techniques for underwater combat management systems. TMA can be divided to two parts: batch estimation and sequential estimation. It is preferable to use sequential estimation for reducing computational load as well as adaptively to target maneuvers, batch estimation is still required to attain target initial state vector for convergence of sequential estimation. Selection of batch time interval which depends on observability is critical in TMA performance. Batch estimation in general utilizes predetermined batch time interval. In this paper, we propose a new method called the BTIS (Batch Time Interval and Initial State Estimation). The proposed BTIS estimates target initial status and determines the batch time interval sequentially by using a bank of GMM-TS (Gaussian Mixture Measurement-Track Splitting) filters. The performance of the proposal method is verified by a Monte Carlo simulation study.

• 제어로봇시스템학회논문지
• /
• 제8권10호
• /
• pp.833-841
• /
• 2002

We develope a model that can manipulate the reflux ratio of a batch distillation process in real time for optimal operations. Firstly, reflux ratio decision model for batch distillation unit was developed using the simple short-cut method. Secondly, more detailed rigorous method was applied to improve the accuracy of the model. Based on these models, operational strategies for the optimal reflux ratio was proposed. The results are illustrated with suitable examples and compared with the results using commercial simulator.

• 인터넷정보학회논문지
• /
• 제19권3호
• /
• pp.35-42
• /
• 2018

딥 러닝은 영상 분류를 위한 여러 방법 중 높은 정확도를 보이는 방법으로 알려져 있다. 본 논문에서는 딥 러닝 방법 가운데 합성곱 신경망 (CNN:Convolutional Neural Network)을 이용하여 영상을 분류함에 있어 배치 정규화 방법이 추가된 CNN을 이용하여 영상 분류의 정확도를 높이는 방법을 제시하였다. 본 논문에서는 영상 분류를 더 정확하게 수행하기 위해 기존의 뉴럴 네트워크에 배치 정규화 계층 (layer)를 추가하는 방법을 제안한다. 배치 정규화는 각 계층에 존재하는 편향을 줄이기 위해 고안된 방법으로, 각 배치의 평균과 분산을 계산하여 이동시키는 방법이다. 본 논문에서 제시된 방법의 우수성을 입증하기 위하여 SHREC13, MNIST, SVHN, CIFAR-10, CIFAR-100의 5개 영상 데이터 집합을 이용하여 영상분류 실험을 하여 정확도와 mAP를 측정한다. 실험 결과 일반적인 CNN 보다 배치 정규화가 추가된 CNN이 영상 분류 시 보다 높은 분류 정확도와 mAP를 보임을 확인 할 수 있었다.