• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.594-609
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• 1998

In this dissertation, a new process capability index $C_{psk}$ is introduced for non-normal process. The Pearson curve and the Johnson curve are selected for capability index calculation and data modeling the normal-based index $C_{psk}$ is used as the model for non-normal process. A significant result of this research find that the ranking of the seven indices, $C_p,\;C_{pk},\;C_{pm},\;C^{\ast}_{pm},\;C_{pmk},\;C_s,\;C_{psk}$ in terms of sensitivity to departure of the process median from the target value T=M from the most sensitive one up to the least sensitive are $C_{psk},\;C_{s},\;C_{pmk},\;C^{\ast}_{pm},\;C_{pm},\;C_{pk},\;C_p$. i.e, By the criteria adopted for evaluation of PCI's $C_{psk}$ is the most sensitive to the departure of the process median from target and $C_p$ is least

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.52
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• pp.347-354
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• 1999

Statistical Process Control(SPC) which uses control charts is widely used to inspect and improve manufacturing process as a effective method. A parametric method is the most common in statistical process control. Shewhart chart was made under the assumption that measurements are independent and normal distribution. In practice, this assumption is often excluded, for example, in case of (equation omitted) chart, when the subgroup sample is small or correlation, it happens that measured data have bias or rejection of the normality test. A bootstrap method can be used in such a situation, which is calculated by resampling procedure without pre-distribution assumption. In this study, applying bootstrap percentile method to (equation omitted) chart, it is compared and evaluated standard process control limit with bootstrap percentile control limit. Also, under the normal and non-normal distributions, where parameter is 0.5, using computer simulation, it is compared standard parametric with bootstrap method which is used to decide process control limits in process quality.

• Journal of Korean Academy of Nursing
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• v.37 no.1
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• pp.91-104
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• 2007

Purpose: The purpose of this study was to explore the experiences of parenting from the parents of children with ADHD and to develop a grounded theory about their experiences. Method: This study was a qualitative research study that used a grounded theory to understand and discuss the parenting experiences of parents of children with ADHD in a greater depth. Grounded data was collected through an in-depth interview from twelve participants with ADHD children. The data was analyzed using the grounded theory method. Results: 'Approaching the normal' emerged as the core phenomenone. Parenting experiences for parents of children with ADHD referred to a process of bringing the children, back on track of normal growth development, and their functioning in the family at a normal level and establishing a new normalcy. The process of approaching the normal involved a basic social-psychological process, such as 'living a day in hell', 'accepting', 'confronting the conflicts', 'lowering expectations', and 'making a new normalcy'. Conclusion: The outcomes of this study, which observed the parenting process of parents of children with ADHD, could enhance nurses' understanding of ADHD and help nurses become major mental health service providers for the mental health of children with ADHD and their families.

• Journal of Biomedical Engineering Research
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• v.15 no.4
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• pp.407-412
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• 1994

This paper describes the construction of an anisotropic three dimensional ventricular model based on the bidomain model. The cardiac activation process in the normal cardiac cell and the myocardial ischemic cell are simulated by the Huygen's principle. The depolarization process in the myocardial ischemia displays the delayed activation compared to the normal state. The repolarization process is simulated by the myocardial potential at the arbitrary ellapsed time after activation process. Using the potential data, the equivalent cardiac source at the arbitrary time can be computed. In conclusion, this simulation suggests the possibilities of the depolarization and the repolarization process in the normal and abnormal myocardiac cells.

• Nuclear Engineering and Technology
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• v.54 no.2
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• pp.644-652
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• 2022

During the pyroprocessing operation, various signals can be collected by process monitoring (PM). These signals are utilized to diagnose process states. In this study, feasibility of using PM for nuclear safeguards of electrorefining operation was examined based on the use of machine learning for detecting off-normal operations. The off-normal operation, in this study, is defined as co-deposition of key elements through reduction on cathode. The monitored process signal selected for PM was cathode potential. The necessary data were produced through electrodeposition experiments in a laboratory molten salt system. Model-based cathodic surface area data were also generated and used to support model development. Computer models for classification were developed using a series of recurrent neural network architectures. The concept of transfer learning was also employed by combining pre-training and fine-tuning to minimize data requirement for training. The resulting models were found to classify the normal and the off-normal operation states with a 95% accuracy. With the availability of more process data, the approach is expected to have higher reliability.

• Industry Promotion Research
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• v.1 no.2
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• pp.1-6
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• 2016

By using the high tensile steel plate (SPFH590) 1 Primary normal shear process clearance was studied through an experiment for the effect of the second shaving process in this study. Experiment result, Shaving process in the case of processed 15% of the Primary normal shear process clearance was some residual surface does not remove it completely. and Shaving process of shearing products by the general shearing process clearance of 10% it was found that the wider the size of shear surface. The shear surface of 93% occurred in case of the clearance of general shearing process is 10% and the Shaving clearance is 2%, The shear surface of 87% were to occur in case of the Shaving clearance is 3%.

• Neonatal Medicine
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• v.18 no.2
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• pp.165-176
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• 2011

The pathologic hallmark of new bronchopulmonary dysplasia (BPD) is an arrest in alveolarization and vascular development. Alveoli are the fully mature gas-exchange units and alveolarization denotes the process through which the developing lung attains its fully mature structure. In human, alveolarization is mainly a postnatal event and begins in utero around 35 postmenstrual weeks and continues to 2 postnatal years. Beginning of respiration with very immature lungs as a result of preterm delivery renders the immature lung to be exposed to various injuries such as mechanical stretch, hyperoxia, infection/inflammation and leads to a disruption of normal alveolarization process, which is a main pathologic finding of BPD. Better understanding of the control mechanisms of normal alveolarization process should help us to figure out the pathophysiology of BPD and discover effective preventive or therapeutic measures for BPD. In this review, the pathologic evolution of BPD from 'old' to 'new' BPD, the detailed mechanisms of normal alveolarization, and the factors that disrupt normal alveolarization will be discussed.

• Nonlinear Functional Analysis and Applications
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• v.26 no.5
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• pp.995-1009
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• 2021

Many iterative algorithms like that Picard, Mann, Ishikawa and S-iteration are very useful to elucidate the fixed point problems of a nonlinear operators in various topological spaces. The recent trend for elucidate the fixed point via inertial iterative algorithm, in which next iterative depends on more than one previous terms. The purpose of the paper is to establish convergence theorems of new inertial Picard normal S-iteration algorithm for nonexpansive mapping in Hilbert spaces. The comparison of convergence of InerNSP and InerPNSP is done with InerSP (introduced by Phon-on et al. [25]) and MSP (introduced by Suparatulatorn et al. [27]) via numerical example.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.37-45
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• 2016

Control chart is representative tools of statistical process control (SPC). It is a graph that plotting the characteristic values from the process. It has two steps (or Phase). First step is a procedure for finding a process parameters. It is called Phase I. This step is to find the process parameters by using data obtained from in-controlled process. It is a step that the standard value was not determined. Another step is monitoring process by already known process parameters from Phase I. It is called Phase II. These control chart is the process quality characteristic value for management, which is plotted dot whether the existence within the control limit or not. But, this is not given information about the economic loss that occurs when a product characteristic value does not match the target value. In order to meet the customer needs, company not only consider stability of the process variation but also produce the product that is meet the target value. Taguchi's quadratic loss function is include information about economic loss that occurred by the mismatch the target value. However, Taguchi's quadratic loss function is very simple quadratic curve. It is difficult to realistically reflect the increased amount of loss that due to a deviation from the target value. Also, it can be well explained by only on condition that the normal process. Spiring proposed an alternative loss function that called reflected normal loss function (RNLF). In this paper, we design a new control chart for overcome these disadvantage by using the Spiring's RNLF. And we demonstrate effectiveness of new control chart by comparing its average run length (ARL) with ${\bar{x}}-R$ control chart and expected loss control chart (ELCC).

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.116-122
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• 2016

Recently, the production cycle in manufacturing process has been getting shorter and different types of product have been produced in the same process line. In this case, the control chart using coefficient of variation would be applicable to the process. The theory that random variables are located in the three times distance of the deviation from mean value is applicable to the control chart that monitor the process in the manufacturing line, when the data of process are changed by the type of normal distribution. It is possible to apply to the control chart of coefficient of variation too. ${\bar{x}}$, s estimates that taken in the coefficient of variation have just used all of the data, but the upper control limit, center line and lower control limit have been settled by the effect of abnormal values, so this control chart could be in trouble of detection ability of the assignable value. The purpose of this study was to present the robust control chart than coefficient of variation control chart in the normal process. To perform this research, the location parameter, ${\bar{x_{\alpha}}}$, $s_{\alpha}$ were used. The robust control chart was named Tim-CV control chart. The result of simulation were summarized as follows; First, P values, the probability to get away from control limit, in Trim-CV control chart were larger than CV control chart in the normal process. Second, ARL values, average run length, in Trim-CV control chart were smaller than CV control chart in the normal process. Particularly, the difference of performance of two control charts was so sure when the change of the process was getting to bigger. Therefore, the Trim-CV control chart proposed in this paper would be more efficient tool than CV control chart in small quantity batch production.