• Proceedings of the Korea Society for Simulation Conference
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• 1993.10a
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• pp.2-2
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• 1993

Inference for discrete event simulations usually relies on either independent replications or, if each simulation run is expensive, the method of batch means applied to a single replications. We present a new method, threshold bootstrap, which equals or exceeds the performance of independent replications or batch means. The method works by resampling runs of data created when a stationary time series crosses a threshold level, such as the sample mean of series. Computational results show that the threshold bootstrap matches or exceeds the performance of these alternative methods in estimating the standard deviation of the sample mean and producing valid confidence intervals.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.277-284
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• 2022

In this paper, we proposes a method of optimizing the processing order of skids to minimize the span time in a conveyor environment of the shipbuilding subassembly process. The subassembly process consists of a series of fixed tasks where the required work time is varied according to the skid type. The loading order of skids on a conveyor which determines the span time should be properly optimized and the problem size exponentially increases with the number of skids. In this regard, we propose a novel method called UniDev by defining a measure of the mean-absolute-deviation about the time difference among simultaneously processed tasks and iteratively improving it. Through simulations with various numbers of skids and processes, it was observed that our proposed method can efficiently reduce the overall work time compared with the multi-start and the 2-OPT methods.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1288-1296
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• 2016

The reliable detection of the limited defect in TFT-LCD images is difficult due to the small intensity difference with the background. However, the proposed detection method reliably detects the limited defect by enhancing the TFT-LCD image based on the cumulative histogram and then detecting the defect through the mean and standard deviation of the enhanced image. Notably, an image enhancement using a cumulative histogram increases the intensity contrast between the background and the limited defect, which then allows defects to be detected by using the mean and standard deviation of the enhanced image. Furthermore, through the comparison with the histogram equalization, we confirm that the proposed algorithm suppresses the emphasis of the noise. Experimental comparative results using real TFT-LCD images and pseudo images show that the proposed method detects the limited defect more reliably than conventional methods.

• Phonetics and Speech Sciences
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• v.9 no.4
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• pp.107-114
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• 2017

The purpose of the current study was to compare selected acoustic and electroglottographic measures (closed quotient, pitch, and loudness) among vowel phonation, traditional voiced lip trill ($VLT_T$), modified voiced lip trill methods ($VLT_M$). A total of 21 participants without voice complaints produced 4-second long samples using each phonation method. Results indicated that mean closed quotient of $VLT_M$ was higher than that of vowel phonation and $VLT_T$, while its range and standard deviation measures were higher than those of vowel phonation. Mean, range, standard deviation, maximum of pitch measures of $VLT_M$ were higher than those of vowel phonation. Lastly, mean and maximum loudness of the $VLT_M$ were higher than $VLT_T$. In conclusion, the current data indicate the possibility to use the $VLT_M$ as a training method for singing or a strategy to facilitate generalization effect of voice therapy. Current results also reflect the necessity for further study pertaining to the long-term effect of the $VLT_M$ training method. Clinical implications are discussed.

• Journal of information and communication convergence engineering
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• v.9 no.6
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• pp.758-762
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• 2011

In this paper an efficient algorithm is proposed to remove additive white Gaussian noise(AWGN) with edge preservation. A function is used to separate the filtering mask to two sets according to the direction information. Then, we calculate the mean and standard deviation of the pixels in each set. In order to preserve the details, we also compare standard deviations between the two sets to find out smaller one. Corrupted pixel is replaced by the mean of the filtering window's median value and the smaller set's mean value that the rate of change is faster than the other one. Experiment results show that the proposed algorithm outperforms with significant improvement in image quality than the conventional algorithms. The proposed method removes the Gaussian noise very effectively.

• Journal of Korean Society for Quality Management
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• v.28 no.2
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• pp.70-88
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• 2000

Short runs where it is neither possible nor practical to obtain sufficient subgroups to estimate accurately the control limit are common in modem business environments. In this study, the standardized control chart, Hillier's exact method, Q chart, EWMA(Exponentially Weighted Moving Average) chart for Q statistics and EWMA chart for mean and absolute deviation among many SPC(Statistical Process Control) techniques for short runs have been reviewed and advantages and disadvantages of these techniques are discussed. The simulation experiments to compare performances of these variable charts for process mean and variations are conducted for combination of subgroup size, scale and timing of shifts of process mean an/or standard deviation. Based upon simulation results, some guidelines for practitioners to choose short run SPC techniques are recommended.

• Journal of Sensor Science and Technology
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• v.17 no.2
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• pp.87-94
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• 2008

Blood pressure (BP), one of the most important vital signs, is used to identify an emergency state and reflects the blood flow characteristics of the cardiovascular system. The conventional noninvasive method of measuring BP is inconvenient because patients must wear a cuff on their arm and the measurement process takes time. This paper proposes an algorithm for estimating the BP using the pulse transit time (PTT) of the photoplethysmography (PPG) and pressure pulse from finger at the same time as a more convenient way to measure the BP. After recording the electrocardiogram (ECG), measuring the pressure pulse, and performing PPG, we calculated the PTT from the acquired signals. Then, we used a multiple regression analysis to measure the systolic and diastolic BP indirectly. Comparing the BP measured indirectly using the proposed algorithm and the real BP measured with a sphygmomanometer, the systolic pressure had a mean error of ${\pm}3.240$ mmHg and a standard deviation of 2.530 mmHg, while the diastolic pressure had a satisfactory result, i.e., a mean error of ${\pm}1.807$ mmHg and a standard deviation of 1.396 mmHg. These results are more superior than existing method estimating blood pressure using the one PTT and satisfy the ANSI/AAMI regulations for certifying a sphygmomanometer i.e., the measurement error should be within a mean error of ${\pm}5$ mmHg and a standard deviation of 8 mmHg. These results suggest the possibility of applying our method to a portable, long-term BP monitoring system.

• Journal of the Ergonomics Society of Korea
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• v.32 no.3
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• pp.237-243
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• 2013

Objective: The present study developed an estimation method of boundary zone representative humanoids(hereafter, EBZ method) using descriptive statistics on the design target population. Background: The boundary zone method(hereafter, BZ method) generates representative humanoids at a boundary zone that statistically accommodates a designated percent of the design target population; however, the BZ method has a practical limitation because it requires a large scale anthropometric database on the design target population. Method: The EBZ method developed in the present study consisted of 3 steps. In the first step, the boundary zone of accommodating a designated percent(e.g., 90%) is formed under the assumption of normal distributions for anthropometric sizes. In the second step, cases that fall within the boundary zone are estimated using descriptive statistics(mean, standard deviation, and covariance) on the design target population. In the last step, K-mean cluster analysis is conducted for the cases, and representative humanoids are selected from each of clusters. Results: Evaluation results showed that mean accommodation percent of the EBZ method was 90.9%(range: 90.8~91.1%) which is similar to the target percent(90%). In addition, standard deviation of accommodation percent for 100 repetitions was 0.1%. Lastly, the number of representative humanoids generated by the EBZ method(n = 20) was similar to the BZ method(n = 16). Conclusion: The EBZ method can generate representative humanoids which accommodate a designated percent of the design target population using descriptive statistics. Application: The EBZ method can be utilized in the generation of humanoids for ergonomic design and evaluation of products when the large scale anthropometric database on the design target population is not existed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.1
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• pp.185-192
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• 1997

We propose a method of paramete estimation using order-of-magnitude analysis for optimal boundary smoothing in Mean Field Annealing(MFA) technique in this paper. We previously proposed two boundary smoothing methods for consistent object representation in the previous paper, one is using a constratined regulaization(CR) method and the other is using a MFA method. The CR method causes unnecessary smoothing effects at corners. On the other hand, the MFA method method smooths our the noise without losing sharpness of corners. The MFA algorithm is influenced by several parameters such as standard deviation of the noise, the relativemagnitude of prior ter, initial temperature and final temperature. We propose a general parameter esimation method for optimal boundary smoothing using order-of-magnitude analysis to be used for consistent object representation in this paper. In addition, we prove the effectiveness of our parameter estimation and also show the temperature parameter sensitivities of the algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.1
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• pp.46-51
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• 2007

In this paper, we propose a new data clustering method using local probability and hypothesis theory. To cluster the test data set we analyze the local area of the test data set using local probability distribution and decide the candidate class of the data set using mean standard deviation and variance etc. To decide each class of the test data, statistical hypothesis theory is applied to the decided candidate class of the test data set. For evaluating, the proposed classification method is compared to the conventional fuzzy c-mean method, k-means algorithm and Discriminator analysis algorithm. The simulation results show more accuracy than results of fuzzy c-mean method, k-means algorithm and Discriminator analysis algorithm.