• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.457-468
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• 2007

This paper proposes an adaptive moving average (A-MA) control chart with variable sampling intervals (VSI) for detecting shifts in the process mean. The basic idea of the VSI A-MA chart is to adjust sampling intervals as well as to accumulate previous samples selectively in order to increase the sensitivity. The VSI A-MA chart employs a threshold limit to determine whether or not to increase sampling rate as well as to accumulate previous samples. If a standardized control statistic falls outside the threshold limit, the next sample is taken with higher sampling rate and is accumulated to calculate the next control statistic. If the control statistic falls within the threshold limit, the next sample is taken with lower sampling rate and only the sample is used to get the control statistic. The VSI A-MA chart produces an 'out-of-control' signal either when any control statistic falls outside the control limit or when L-consecutive control statistics fall outside the threshold limit. The control length L is introduced to prevent small mean shifts from being undetected for a long period. A Markov chain model is employed to investigate the VSI A-MA sampling process. Formulae related to the steady state average time-to signal (ATS) for an in-control state and out-of-control state are derived in closed forms. A statistical design procedure for the VSI A-MA chart is proposed. Comparative studies show that the proposed VSI A-MA chart is uniformly superior to the adaptive Cumulative sum (CUSUM) chart and to the Exponentially Weighted Moving Average (EWMA) chart, and is comparable to the variable sampling size (VSS) VSI EWMA chart with respect to the ATS performance.

• Korean Journal of Optics and Photonics
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• v.14 no.3
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• pp.272-278
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• 2003

We studied patterned ITO layers of PDP thin films on glass substrates using spectroscopic ellipsometry. The optical property of ITO is expressed with the optical model based on two Lorentz oscillators. The effect of patterned ITO is calculated by taking the weighted average of reflectance in proportion to ITO coverage. The relative coverage of ITO is determined by using the model analysis of spectroellipsometric data. The difference of ITO coverage obtained by the best-fit model analysis of ellipsometric spectra to the expected one is critically examined and suggestions are made to minimize the observed discrepancy.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.19 no.2
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• pp.93-101
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• 2023

In this study, a deep learning algorithm was used to diagnose electric potential signals obtained through CIPS and DCVG, used indirect inspection methods to confirm the soundness of buried pipes. The deep learning algorithm consisted of CNN(Convolutional Neural Network) model for diagnosing the electric potential signal and Grad CAM(Gradient-weighted Class Activation Mapping) for showing the flaw prediction point. The CNN model for diagnosing electric potential signals classifies input data as normal/abnormal according to the presence or absence of flaw in the buried pipe, and for abnormal data, Grad CAM generates a heat map that visualizes the flaw prediction part of the buried pipe. The CIPS/DCVG signal and piping layout obtained from the 3D finite element model were used as input data for learning the CNN. The trained CNN classified the normal/abnormal data with 93% accuracy, and the Grad-CAM predicted flaws point with an average error of 2m. As a result, it confirmed that the electric potential signal of buried pipe can be diagnosed using a CNN-based deep learning algorithm.

• Imaging Science in Dentistry
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• v.50 no.3
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• pp.183-192
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• 2020

Purpose: This study was performed to assess the accuracy of preoperative cone-beam computed tomography (CBCT), when justified for other reasons, in locating the apical foramen and establishing the working length. Materials and Methods: Six electronic databases were searched for studies on this subject. All studies, of any type, were included if they compared measurements of working length with preoperative CBCT to measurements using an electronic apex locator (EAL) or histological reference standard. Due to the high levels of heterogeneity, an inverse-variance random-effects model was chosen, and weighted mean differences were obtained with 95% confidence intervals and P values. Results: Nine studies were included. Compared to a histological reference standard, CBCT indicated that the apical foramen was on average 0.40 mm coronal of its histological position, with a mean absolute difference of 0.48 mm. Comparisons were also performed to an EAL reference standard, but the conclusions could not be considered robust due to high levels of heterogeneity in the results. Conclusion: A low level of evidence is produced suggesting that preoperative CBCT shows the apical foramen to be on average 0.40 mm coronal to its histological position, with a mean absolute difference of 0.48 mm.

• Nuclear Engineering and Technology
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• v.22 no.4
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• pp.410-415
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• 1990

Prompt fission neutron energy spectrum as a function of energies of neutron inducing fission has been calculated en the basis of the Madland-Nix(MN) model. The resultant spectra have been weighted to excitation functions of $^{27}$ Al(n, $\alpha$), $^{32}$ S(n, p) and $^{115}$ In(n, n') threshold reactions in order to get the average cross sections and then spectral indices which are defined as the average cross section ratio for two selective threshold reactions among the above three. It is appeared that spectral indices together with the neutron spectra are varying with energies of neutron inducing fission. This may indicate that the prompt fission neutron energy spectrum can be determined by measuring experimentally the spectral index.

• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.23-35
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• 2005

This paper aims to develop a practical finite capacity MRP (FCMRP) system based on the needs of an automotive parts manufacturing company in Thailand. The approach includes a linear goal programming model to determine the optimal start time of each operation to minimize the sum of penalty points incurred by exceeding the goals of total earliness, total tardiness, and average flow-time considering the finite capacity of all work centers and precedence of operations. Important factors of the proposed FCMRP system are penalty weights and dispatching rules. Effects of these factors on the performance measures are statistically analyzed based on a real situation of an auto-part factory. Statistical results show that the dispatching rules and penalty weights have significant effects on the performance measures. The proposed FCMRP system offers a good tradeoff between conflicting performance measures and results in the best weighted average performance measures when compared to conventional forward and forward-backward finite capacity scheduling systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.64-88
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• 2024

Security and reliability are the utmost importance facts in intelligent networked vehicles. Stochastic Petri Net and Z (SPZN) as an excellent formal verification tool for modeling concurrent systems, can effectively handles concurrent operations within a system, establishes relationships among components, and conducts verification and reasoning to ensure the system's safety and reliability in practical applications. However, the application of a system with numerous nodes to Petri Net often leads to the issue of state explosion. To tackle these challenges, a refinement and abstraction method based on SPZN is proposed in this paper. This approach can not only refine and abstract the Stochastic Petri Net but also establish a corresponding relationship with the Z language. In determining the implementation rate of transitions in Stochastic Petri Net, we employ the interval average and weighted average method, which significantly reduces the time and space complexity compared to alternative techniques and is suitable for expert systems at various levels. This reduction facilitates subsequent comprehensive system analysis and module analysis. Furthermore, by analyzing the properties of Markov Chain isomorphism in the case study, recommendations for minimizing system risks in the application of intelligent parking within the intelligent networked vehicle system can be put forward.

• Korean Journal of Optics and Photonics
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• v.11 no.6
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• pp.395-399
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• 2000

In white light interferometry, fast and accurate localization of the fringe visibility is the most essential part in application of the principle. So much attention has been concentrated on speeding up the process, we in this study decided to investigate the results of the various peak-finding algorithms. Of the many approaches, two most simplistic algorithms were selected for their straightforwardness and robustness. Both were equally accurate in measuring the step height of a sample, but the method based on the weighted average technique proved to be truer to the surface topography. A model explaining the shortcomings of the correlation technique is presented. ented.

• Water for future
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• v.28 no.1
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• pp.133-144
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• 1995

The subject of the paper is the selection of the number and location of rainguage stations among existing ones, which will be part of real-time data collection system, for the computation of mean areal precipitation and for use as input of real-time flow forecasting models. The weighted average method developed by National Weather Service was used to compute MAP. Two different searching methods were used to find local optimal solutions as a function of the number of rainguages. An operational rainfall-runoff model was used to determine the optimal location and number of stations for flow prediction.

• Journal of Internet Computing and Services
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• v.1 no.2
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• pp.89-96
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• 2000

Relevance feedback is a technique to learn the user's subjective perception of similarity between images, and has recently gained attention in Content Based Image Retrieval. Most relevance feedback methods assume that the individual features that are used in similarity judgments do not interact with each other. However, this assumption severely limits the types of similarity judgments that can be modeled In this paper, we explore a more sophisticated model for similarity judgments based on fuzzy measures and the Choquet Integral, and propose a suitable algorithm for relevance feedback, Experimental results show that the proposed method is preferable to traditional weighted- average techniques.