• Journal of Biomedical Engineering Research
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• v.17 no.3
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• pp.365-372
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• 1996

The researches to acquire diagnostic parameters from ultrasonic images are advanced with the progress of the digital image processing technique. Especially, the detection of endocardial boundary is very important in ultrasonic images, because endocardial boundary is used as a clinical parameter to estimate both the cardiac area and the variation of cardiac volume. Various methods to detect cardiac boundary are proposed, but these are insufficient to detect boundary. In this paper, an algorithm that detects the endocardial boundary, expanding the cavity region from the center using statistical information, is proposed The value of mean and sty:nd, wd deviation in cavity region is lower than those in muscle re- gion. Therefore, if we define the multiplication of mean and standard deviation as homogeneous coefficient, it can lead to conclusion that the pixels with small variation of these coefficleno are cavity region, and extraction of endocardial boundary from cavity region is possible. The proposed method detected endocardial boundary more effectively than edge based or threshold based method and is robuster to noise than radial searching method that has high dependency for center position.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.30 no.6
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• pp.546-553
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• 2008

Purpose: The purpose of this study was to estimate validity of posterior anterior cephalometric and 3D-CT for orbital canting analysis. Materials and methods: Three trained observers classified two patients group using standardized frontal photographs of facial asymmetry patients. Group A consisted of patients with facial asymmetry and orbital canting(n=19), and group B consisted of patients with only facial asymmetry(n=43). Orbital canting was measured with line of bilateral inferior orbitale. Orbital canting measurement was done with posterior anterior cephalometric and 3D-CT. Each horizontal reference line was established by bilateral GWSO(cephalometric), FZS(3D-CT). Maxillary canting and mandibular deviation angle were also measured and analyzed with orbital canting. Results: The mean orbital canting was $3.03{\pm}1.00^{\circ}$ in Group A and $1.11{\pm}0.76^{\circ}$ in Group B in frontal photograph. The mean orbital canting was $1.20{\pm}0.74^{\circ}$ in group A and $1.22{\pm}0.65^{\circ}$ in group B by cephalometric analysis(p>0.05). In 3D-CT, orbital canting was almost paralleled with horizontal reference line. The orbital canting, maxillay canting and mandibular deviation between two groups showed no significant differences except madibular deviation in 3D-CT. Conclusion: Common analysis of posterior anterior cephalometric and 3D-CT is not valide method to evaluate orbital canting for facial asymmetry patients with orbital canting.

• Knowledge Management Research
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• v.19 no.2
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• pp.151-162
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• 2018

Response surface methodology (RSM) is one of popular tools to support a systematic improvement of quality of design in the product and process development stages. It consists of statistical modeling and optimization tools. RSM can be viewed as a knowledge management tool in that it systemizes knowledge about a manufacturing process through a big data analysis on products and processes. The conventional RSM aims to optimize the mean of a response, whereas dual-response surface optimization (DRSO), a special case of RSM, considers not only the mean of a response but also its variability or standard deviation for optimization. Recently, a posterior preference articulation approach receives attention in the DRSO literature. The posterior approach first seeks all (or most) of the nondominated solutions with no articulation of a decision maker (DM)'s preference. The DM then selects the best one from the set of nondominated solutions a posteriori. This method has a strength that the DM can understand the trade-off between the mean and standard deviation well by looking around the nondominated solutions. A posterior method has been proposed for DRSO. It employs an interval selection strategy for the selection step. This strategy has a limitation increasing inefficiency and complexity due to too many iterations when handling a great number (e.g., thousands ~ tens of thousands) of nondominated solutions. In this paper, a TOPSIS-based method is proposed to support a simple and efficient selection of the most preferred solution. The proposed method is illustrated through a typical DRSO problem and compared with the existing posterior method.

• Journal of Food Hygiene and Safety
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• v.14 no.1
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• pp.76-83
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• 1999

Solid phase microextraction (SPME) was used for the determination of 6 standard solvents (methanol, isopropanol, methyl ethyl ketone, ethyl acetate, cyclohexane, toluene) in food packaging materials. SPME method is a solvent-free sample preparation technique in which a fused silica fiber coated with polymeric organic liquid is introduced into the headspace above the sample. SPME method using fiber coated polydimethylisiloxane (PDMS) was compared with static headspace (SHS) method used as a reference. It was found that the optimal adsorption condition using PDMS-SPME method was 2$0^{\circ}C$ for 15 minutes for the standard solvents. Detection limits, linearity, reproducibility and recovery of both SHS and PDMS-SPME methods have been determined using 6 standard solvents. Both methods were characterized by high reproducibility and good linearity. Using SHS methods, the mean recovery of the 6 standard solvents was ranged from 75.5% to 105.8% with a mean relative standard deviation (RSD) of 0.3% to 4.8%. With PDMS-SPME method, the mean recovery of the 6 standard solvents was ranged from 86.7% to 108.3% with a mean RSD of 0.4% to 2.5%. The detection limits of both methods were the same for toluene, cyclohexane and methyl ethyl ketone; those of PDMS-SPME method were higher than those of SHS method for methanol, isopropanol and ethyl acetate. PDMS-SPME fiber shoed excellent adsorption for non-polar solvents such as toluene, while it showed relatively low adsorption for polar solvents such as methanol.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.187-194
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• 2020

In today's process-oriented industries, such as semiconductor and petrochemical processes, autocorrelation exists between observed data. As a management method for the process where autocorrelation exists, a method of using the observations is to construct a batch so that the batch mean approaches to independence, or to apply the EWMA (Exponentially Weighted Moving Average) statistic of the observed value to the EWMA control chart. In this paper, we propose a method to determine the batch size of UBM (Unweighted Batch Mean), which is commonly used as a management method for observations, and a method to determine the optimal batch size based on ARL (Average Run Length) We propose a method to estimate the standard deviation of the process. We propose an improved control chart for processes in which autocorrelation exists.

• Analytical Science and Technology
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• v.8 no.4
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• pp.771-778
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• 1995

The authors have developed an analytical method for determining trace amounts of 285 kinds of chemicals in natural waters by GC-ion trap MS. The results of overall recovery tests at $0.1{\mu}g/l$ showed that the mean recovery was 92.1% and the mean relative standard deviation was 10.8%. The mean of the method detection limits was $0.036{\mu}g/l$. From the results of analysis of real samples, it was confirmed that this method is useful to elucidate the concentration levels and the fate of chemicals in the aquatic environment.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.2
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• pp.63-69
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• 2012

Noise is regarded as an unwanted component of the image because it significantly reduces image quality. And image is often corrupted by mixed noise. In this paper an efficient modified weighted filter algorithm which combines spatial weight and intensity weight is proposed for removing mixed noise. In the proposed method, the filtering mask is separated into the four sub-windows and the parameters of the weights are confirmed by calculating local standard deviation and the mean of four sub-windows' standard deviations. Considering the spatial information and intensity information, the proposed method has good performance on not only noise elimination but also preservation of details. Simulation results demonstrate that the proposed method performs better than conventional algorithms.

• Journal of ILASS-Korea
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• v.27 no.1
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• pp.26-35
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• 2022

Electrospray is a method of atomizing fluid using high voltage supply and capable of generating continuous flow and coherent size of droplets. Electrical system and properties of fluids has enabled electrospray to have various spray modes. However, its studies have been confined only in Cone jet, which is more stable and easier to manipulate droplets' size than other spraying modes. Therefore, it is necessary to investigate and compare other spraying modes based on experimental parameters and physical properties of fluids. This research paper identified nine different spray modes. It was found out that Sauter Mean Diameter (SMD) is proportional to flow rate of fluids and maximum difference among spray modes was 1.7 times. On the other hand, SMD standard deviation had low variations on specific flow rates of fluids. Pulsed jet mode recorded the largest SMD standard deviation, while Spindle recorded the lowest.

• Journal of the Korean Professional Engineers Association
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• v.29 no.2
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• pp.71-79
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• 1996

This paper evaluates the clustering performance of a neural network and a statistical method. Algorithms which are used in this paper are the GLVQ(Generalized Loaming vector Quantization) for a neural method and the k -means algorithm for a statistical clustering method. For comparison of two methods, we calculate the Rand's c statistics. As a result, the mean of c value obtained with the GLVQ is higher than that obtained with the k -means algorithm, while standard deviation of c value is lower. Experimental data sets were the Fisher's IRIS data and patterns extracted from handwritten numerals.

• Toxicological Research
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• v.30 no.3
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• pp.185-191
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• 2014

Statistical methods are frequently used in toxicology, yet it is not clear whether the methods employed by the studies are used consistently and conducted based on sound statistical grounds. The purpose of this paper is to describe statistical methods used in top toxicology journals. More specifically, we sampled 30 papers published in 2014 from Toxicology and Applied Pharmacology, Archives of Toxicology, and Toxicological Science and described methodologies used to provide descriptive and inferential statistics. One hundred thirteen endpoints were observed in those 30 papers, and most studies had sample size less than 10, with the median and the mode being 6 and 3 & 6, respectively. Mean (105/113, 93%) was dominantly used to measure central tendency, and standard error of the mean (64/113, 57%) and standard deviation (39/113, 34%) were used to measure dispersion, while few studies provide justifications regarding why the methods being selected. Inferential statistics were frequently conducted (93/113, 82%), with one-way ANOVA being most popular (52/93, 56%), yet few studies conducted either normality or equal variance test. These results suggest that more consistent and appropriate use of statistical method is necessary which may enhance the role of toxicology in public health.