• Journal of the Korea Safety Management & Science
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• v.16 no.4
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• pp.229-236
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• 2014

Failure modes and effects analysis (FMEA) is a widely used engineering tool in the fields of the design of a product or a process to improve its quality or performance by prioritizing potential failure modes in terms of three risk factors-severity, occurrence, and detection. In a classical FMEA, the risk priority number is obtained by multiplying the three values in 10 score scales which are evaluated for the three risk factors. However, the drawbacks of the classical FMEA have been mentioned by many previous researchers. As a way to overcome these difficulties, this paper suggests the ELECTRE III that is a representative technique among outranking models. Furthermore, fuzzy linguistic variables are included to deal with ambiguous and imperfect evaluation process. In addition, when the importances for the three risk factors are obtained, the entropy method is applied. The numerical example which was previously studied by Kutlu and Ekmekio$\breve{g}$lu(2012), who suggested the fuzzy TOPSIS method along with fuzzy AHP, is also adopted so as to be compared with the results of their research. Finally, after comparing the results of this study with that of Kutlu and Ekmekio$\breve{g}$lu(2012), further possible researches are mentioned.

• Journal of Biomedical Engineering Research
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• v.22 no.4
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• pp.369-375
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• 2001

The statistical regression model is one of the most frequently used clinical analysis methods. It has basic assumption of linearity, additivity and normal distribution of data. However, most of biological data in medical field are nonlinear and unevenly distributed. To overcome the discrepancy between the basic assumption of statistical model and actual biological data, we propose a new analytical method based on artificial neural network. The newly developed multilayer perceptron(MLP) is trained with 120 data set (60 normal, 60 patient). On applying test data, it shows the discrimination power of 0.76. The diabetic risk factors were also identified from the MLP neural network model and the logistic regression model. The signigicant risk factors identified by MLP model were post prandial glucose level(PP2), sex(male), fasting blood sugar(FBS) level, age, SBP, AC and WHR. Those from the regression model are sex(male), PP2, age and FBS. The combined risk factors can be identified using the MLP model. Those are total cholesterol and body weight, which is consistent with the result of other clinical studies. From this experiment we have learned that MLP can be applied to the combined risk factor analysis of biological data which can not be provided by the conventional statistical method.

• Journal of the Society of Naval Architects of Korea
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• v.41 no.2
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• pp.106-113
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• 2004

The block assembly of ship consists of a certain type of heat processes such as cutting, bending, welding, residual stress relaxation and fairing. The residual deformation due to welding is inevitable at each assembly stage. The geometric inaccuracy caused by the welding deformation tends to preclude the introduction of automation and mechanization and needs the additional man-hours for the adjusting work at the following assembly stage. To overcome this problem, a distortion control method should be applied. For this purpose, it is necessary to develop an accurate prediction method which can explicitly account for the influence of various factors on the welding deformation. Systematic and quantitative theoretical works to clarify the effects of various factors on the welding deformation have rarely been found. Therefore, in this paper, the effects of various factors, such as welding process and gravity on the butt welding deformation have been investigated through a number of numerical analyses. In addition, this paper proposes a simplified analysis method to predict the butt welding deformation in actual plate structure. For this purpose, a simple prediction model for butt welding deformations has been derived based on numerical and experimental results through the regression analysis. Based on these results, the simplified analysis method has been applied to some examples to show its validity.

• Journal of Korean Academy of Nursing
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• v.35 no.7
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• pp.1210-1220
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• 2005

Purpose: This study was aimed to examine how subjects' characteristics and nursing service quality influence hospital revisiting intent, to compare perceptions of patients with those of nurses, Method: The questionnaire was developed and distributed to 300 patients and nurses at six general hospitals in a provincial city, Korea, For data analysis, the SPSS/PC program was used. Result: The nursing service quality's scores of patients is 3.61, that of nurses is 3.77, and there is a significant difference. The hospital revisiting intent's score of patients is 4.84, that of nurses is 4.61, and there are no significant differences. In subjects' characteristics, patients perceive that the hospital is the only different factor, and place hospital revisiting intent at $3.6\%$. Nurses perceive that education level and position are different factors, and place hospital revisiting intent at $3.3\%$. In nursing service quality, patients perceive that 2 attributes explain hospital revisiting intent at $17.8\%$ and 2 factors explain it at $16.5\%$; whereas, nurses perceive that 2 attributes explain hospital revisiting intent at $15.3\%$ and 3 factors explain it at $12.2\%$. Conclusion: There are perception gaps between consumers and providers. So nursing and hospital managers must recognize these facts and provide various marketing strategies to overcome them.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.1
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• pp.36-43
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• 1999

This paper proposes a new hybrid genetic algorithm for auto-tuning fuzzy controllers improving the performance. In general, fuzzy controllers use pre-determined moderate membership functions, fuzzy rules, and scaling factors, by trial and error. The presented algorithm estimates automatically the optimal values of membership functions, fuzzy rules, and scaling factors for fuzzy controllers, using a hybrid genetic algorithm. The object of the proposed algorithm is to promote search efficiency by the hybrid optimization technique. The proposed hybrid genetic algorithm is based on both the standard genetic algorithm and a modified gradient method. If a maximum point is not be changed around an optimal value at the end of performance during given generation, the hybrid genetic algorithm searches for an optimal value using the the initial value which has maximum point by converting the genetic algorithms into the MGM(Modified Gradient Method) algorithms that reduced the number of variables. Using this algorithm is not only that the computing time is faster than genetic algorithm as reducing the number of variables, but also that can overcome the disadvantage of genetic algoritms. Simulation results verify the validity of the presented method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.49-61
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• 2019

As the technological gap amongst manufacturers decreases, the life cycle of products has shortened, and competition accelerates due to the development of technology, incumbent manufacturing companies face growth limitations. In order to overcome such business issues, manufacturing companies are increasingly interested in changes in business models and innovations, especially in the direction of providing services where they can maintain the competitive advantage of their products. In such context, this empirical study examines managerial leadership, differentiation strategies, and products and services pricing as 'servitization factors', which can be driving forces for moving into a new era of growth for Korean SMEs, focusing on the mediating effects of servitization competency. The results are as follows : First, it was confirmed that executive leadership, differentiation strategy, and information & communication technology capability have a direct effect on service sales. Second, the process competency, partnership competency, and ICT competency, which are presented as the service competence of SMEs, were found to play an important role in inducing service sales in managerial leadership, differentiation strategy, product and services pricing. It also emphasized the role of the public policy such as helping to foster SMEs as key partners in the expansion of social facilities and establishing platforms through ICT and data utilization for the convergence of manufacturing services.

• Yonsei Medical Journal
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• v.59 no.9
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• pp.1015-1025
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• 2018

Kidney diseases including acute kidney injury and chronic kidney disease are among the largest health issues worldwide. Dialysis and kidney transplantation can replace a significant portion of renal function, however these treatments still have limitations. To overcome these shortcomings, a variety of innovative efforts have been introduced, including cell-based therapies. During the past decades, advances have been made in the stem cell and developmental biology, and tissue engineering. As part of such efforts, studies on renal cell therapy and artificial kidney developments have been conducted, and multiple therapeutic interventions have shown promise in the pre-clinical and clinical settings. More recently, therapeutic cell-secreting secretomes have emerged as a potential alternative to cell-based approaches. This approach involves the use of renotropic factors, such as growth factors and cytokines, that are produced by cells and these factors have shown effectiveness in facilitating kidney function recovery. This review focuses on the renotropic functions of bioactive compounds that provide protective and regenerative effects for kidney tissue repair, based on the available data in the literature.

• The Korean Journal of Food & Health Convergence
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• v.5 no.1
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• pp.21-31
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• 2019

Exposure to a traumatic events gives people many post traumatic conditions resulting Post Traumatic Stress Disorder (PTSD) or Post Traumatic Growth (PTG). Some of them may come up with acute Stress Disorder and some may having with grievances. But most of people overcome their traumatic condition with using their Emotional Intelligence and Resilience capacities. This article is focused on indicating basic mechanisms and resources in which can be lead to have better social rehabilitation along with the matters that can be important in trauma coping. The later part of the article appeals the concept of social work theory highlighting the psych dynamic approach which can be impact positively on psycho social rehabilitation. Traumatic experiences are really unpredictable and it can be resulted Post Traumatic Stress Disorders, Post traumatic growth in the end. But developing skills that required to overcoming trauma is facilitated by the Emotional Intelligence, Resilience, and Coping capacities that people having with. Exposure to a traumatic experience and not having a PTSD is determined by the many other factors such as social support system and government facilitation of the wellbeing afterwards the trauma. Here in this article the basic components of Emotional Intelligence, Resilience, and coping mechanisms have been considered as the major factors.

• Journal of Information Technology Applications and Management
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• v.28 no.3
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• pp.109-125
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• 2021

For the government of president Moon's AI SW HRD policy, he proclaimed AI democracy that anyone can utilize artificial intelligence technology to spread AI education for the people of the country. Through cognitive map analysis, this study presents expected policy outcomes due to the input of policy factors to overcome crisis factors and utilize opportunity factors. According to the cognitive guidance analysis, first, the opportunity factor is recognized as accelerating the digital transformation to Covid 19 if AI SW HRD is well nurtured. Second, the crisis factor refers to the rapid paradigm shift caused by the intelligence information society, resulting in job losses in the manufacturing sector and deepening imbalance in manpower supply and demand, especially in the artificial intelligence sector. Third, the comprehensive cognitive map shows a circular process for creating an AI SW ecosystem in response to threats caused by untact caused by Corona and a circular process for securing AI talent in response to threats caused by deepening imbalance in manpower supply and demand in the AI sector. Fourth, in order to accelerate the digital circulation that has been accelerated by Corona, we found a circular process to succeed in the Korean version of digital new deal by strengthening national and corporate competitiveness through AI-utilized capacity and industrial and regional AI education. Finally, the AI utilization empowerment strengthening rotation process is the most dominant of the four mechanisms, and we also found a relatively controllable feedback loop to obtain policy outputs.

• Communications for Statistical Applications and Methods
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• v.29 no.5
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• pp.547-559
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• 2022

For a chi-squared test, which is a statistical method used to test the independence of a contingency table of two factors, the expected frequency of each cell must be greater than 5. The percentage of cells with an expected frequency below 5 must be less than 20% of all cells. However, there are many cases in which the regional expected frequency is below 5 in general small area studies. Even in large-scale surveys, it is difficult to forecast the expected frequency to be greater than 5 when there is small area estimation with subgroup analysis. Another statistical method to test independence is to use the Bayes factor, but since there is a high ratio of data dependency due to the nature of the Bayesian approach, the low expected frequency tends to decrease the precision of the test results. To overcome these limitations, we will borrow information from areas with similar characteristics and pool the data statistically to propose a pooled Bayes test of independence in target areas. Jo et al. (2021) suggested hierarchical Bayesian pooling models for small area estimation of categorical data, and we will introduce the pooled Bayes factors calculated by expanding their restricted pooling model. We applied the pooled Bayes factors using bone mineral density and body mass index data from the Third National Health and Nutrition Examination Survey conducted in the United States and compared them with chi-squared tests often used in tests of independence.