• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.538-543
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• 2016

For a good product quality and plant safety, it is necessary to implement the on-line monitoring and diagnosis schemes of industrial processes. Combined with monitoring systems, reliable diagnosis schemes seek to find assignable causes of the process variables responsible for faults or special events in processes. This study deals with the real-time diagnosis of complicated industrial processes from the intelligent use of multivariate statistical techniques. The presented diagnosis scheme consists of a classification-based diagnosis using nonlinear representation and filtering of process data. A case study based on the simulation data was conducted, and the diagnosis results were obtained using different diagnosis schemes. In addition, the choice of future estimation methods was evaluated. The results showed that the performance of the presented scheme outperformed the other schemes.

• Journal of Korean Society for Quality Management
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• v.51 no.2
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• pp.223-245
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• 2023

Purpose: This study aim to identify the trends in AI-based PHM technology that can enhance reliability and minimize costs. Furthermore, this research provides valuable guidelines for future studies in various industries Methods: In this study, I collected and selected AI-based PHM studies, established classification criteria, and analyzed research trends based on classified fields and techniques. Results: Analysis of 125 domestic studies revealed a greater emphasis on machinery in both diagnosis and prognosis, with more papers dedicated to diagnosis. various algorithms were employed, including CNN for image diagnosis and frequency analysis for signal data. LSTM was commonly used in prognosis for predicting failures and remaining life. Different industries, data types, and objectives required diverse AI techniques, with GAN used for data augmentation and GA for feature extraction. Conclusion: As studies on AI-based PHM continue to grow, selecting appropriate algorithms for data types and analysis purposes is essential. Thus, analyzing research trends in AI-based PHM is crucial for its rapid development.

• Journal of Medicine and Life Science
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• v.20 no.4
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• pp.141-157
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• 2023

Stroke is a leading cause of disability and death. The condition requires prompt diagnosis and treatment. The quality of care provided to patients with stroke can vary depending on the availability of medical resources, which in turn, can affect prognosis. Recently, there has been growing interest in using machine learning (ML) to support stroke diagnosis and treatment decisions based on large medical data sets. Current ML applications in stroke care can be divided into two categories: analysis of neuroimaging data and clinical information-based predictive models. Using ML to analyze neuroimaging data can increase the efficiency and accuracy of diagnoses. Commercial software that uses ML algorithms is already being used in the medical field. Additionally, the accuracy of predictive ML models is improving with the integration of radiomics and clinical data. is expected to be important for improving the quality of care for patients with stroke.

• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.511-518
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• 2008

Medical diagnosis systems have been developed to make the knowledge and expertise of human experts more widely available, therefore achieving high-quality diagnosis. In this study, in order to support the diagnosis by the medical diagnosis system, we have preformed medical diagnosis inference three times: first by a neural network with the backpropagation algorithm, secondly by a discriminant analysis with all of the variables, and thirdly by a discriminant analysis with the selected variables. A discussion on comparison of these three methods has been provided.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.16-21
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• 2008

Aero-engine, as one kind of rotating machinery with complex structure and high rotating speed, has complicated vibration faults. Therefore, condition monitoring and fault diagnosis system is very important for airplane security. In this paper, a vibration data acquisition and intelligent fault diagnosis system is introduced. First, the vibration data acquisition part is described in detail. This part consists of hardware acquisition modules and software analysis modules which can realize real-time data acquisition and analysis, off-line data analysis, trend analysis, fault simulation and graphical result display. The acquisition vibration data are prepared for the following intelligent fault diagnosis. Secondly, two advanced artificial intelligent(AI) methods, mapping-based and rule-based, are discussed. One is artificial neural network(ANN) which is an ideal tool for aero-engine fault diagnosis and has strong ability to learn complex nonlinear functions. The other is data mining, another AI method, has advantages of discovering knowledge from massive data and automatically extracting diagnostic rules. Thirdly, lots of historical data are used for training the ANN and extracting rules by data mining. Then, real-time data are input into the trained ANN for mapping-based fault diagnosis. At the same time, extracted rules are revised by expert experience and used for rule-based fault diagnosis. From the results of the experiments, the conclusion is obvious that both the two AI methods are effective on aero-engine vibration fault diagnosis, while each of them has its individual quality. The whole system can be developed in local vibration monitoring and real-time fault diagnosis for aero-engine.

• The Korean Journal of Health Service Management
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• v.10 no.4
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• pp.13-23
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• 2016

Objectives : This research used an exploratory approach to identify factors affecting business strategies due to changes in the healthcare market and customer loyalty factors. Methods : The research model was formulated using antecedents divided into diagnosis quality, employee attitudes, and servicescape. Moreover, differences in the structured model were analyzed according to hospital size. The data were gathered through surveys on clients, who has received care at participating hospitals. From the 200 that were distributed, 150 questionnaires were analyzed, to facilitate analysis of the research model. Results : The effects of diagnosis quality, employee attitudes, and servicescape, on customer loyalty were mediated by trust. We also found the differences between small and large hospitals. Conclusions : Customer loyalty in small hospitals was affected by servicescape, whereas that in large hospitals was affected by diagnosis quality and employee attitudes. The research results could be used to develop strategies to improve customer loyalty.

• Korean Journal of Adult Nursing
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• v.27 no.2
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• pp.188-197
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• 2015

Purpose: The purpose of this study was to examine fatigue, sleep disturbances, and quality of life (QOL) among patients with breast cancer receiving radiotherapy. Methods: A cross-sectional, descriptive design was used. Data were collected through questionnaires distributed to 201 breast cancer patients in a hospital. The data were analyzed using SPSS 21.0. Results: The fatigue scores showed significant differences depending on exercise and duration since diagnosis. The sleep disturbance scores showed significant differences depending on duration since diagnosis. QOL scores showed significant differences depending on exercise, duration since diagnosis, and treatment site. Fatigue and sleep disturbances (r=.40, p<.001) showed statistically significant positive correlations, while fatigue and QOL (r=-.55, p<.001), and sleep disturbances and QOL (r=-.45, p<.001) showed statistically significant negative correlations. The multiple regression analysis, which was used to determine the variables influencing on QOL after radiotherapy, resulted in a significant regression model (F=23.88, p<.001), which accounted for approximately 45% of the explanatory power. Fatigue (${\beta}=-.39$, p<.001) and sleep disturbances (${\beta}=-.27$, p<.001) were revealed to adversely affect quality of life. Conclusion: The nursing intervention is necessary to reduce fatigue and sleep disturbance and to promote exercise in order to enhance QOL of patients with breast neoplasm while receiving radiotherapy.

• International Journal of Quality Innovation
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• v.4 no.1
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• pp.46-53
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• 2003

Under the strong leadership of Chinese Government to the anti-SARS struggle, the situation has been successfully controlled. Since May 1 of 2003, the Ministry of Health of China published daily the number of newly increased SARS patient of Beijing, the authors analyzed these data using $X_cs$$-R_scs$ cause-selecting control charts of Statistical Diagnosis(SPD) Theory. Data about number of newly increased SARS patient consists of two kinds of variation: random variation and tendency variation of SARS epidemic. It is concluded that SARS epidemic of Beijing was already controlled since May 9 of 2003.

• Journal of Korean Society for Quality Management
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• v.24 no.4
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• pp.29-43
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• 1996

This paper identifies these data by the data diagnosis in lognormal distribution and presents the method to obtain exact parameter estimates and confidence intervals of regression line. The life-stress relationship uses Arrhenius model and life data generate Class-H insulation complete data by simulation. Also, the method to estimate parameters uses least squares estimation and externally Studentized residuals can be used as test statistics for identifing outliers. And influential cases are identified by Cook's distance. This research is intended to obtain the useful information for the life of products and test method, to save time and costs, and to help optimum accelerated life test plans.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.3 no.1
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• pp.57-72
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• 2008

Serve and do so that graft together specialists' view application field of computer and developmental disability diagnosis estimation data to construct developmental disability diagnosis estimation system in this Paper and constructed developmental disability diagnosis estimation system. Developmental disability diagnosis estimation must supply information of specification area that specialists are having continuously. Developmental disability diagnosis estimation specialist system need multimedia data processing that is specialized little more for developmental disability classification diagnosis and decision-making and is atomized for this. Characteristic of developmental disability diagnosis estimation system that study in this paper can supply quick feedback about result, and can reduce mistake on recording and calculation as well as can shorten examination's enforcement time, and background of training is efficient system fairly in terms of nonprofessional who is not many can use easily. But, as well as when multimedia information that is essential data of system construction for developmental disability diagnosis estimation is having various kinds attribute and a person must achieve description about all developmental disability diagnosis estimation informations, great amount of work done is accompanied, technology about equal data can become different according to management. Because of these problems, applied search technology of contents base (Content-based) that search connection information by contents of edit target data for developmental disability diagnosis estimation data processing multimedia data processing technical development. In the meantime, typical access way for conversation style data processing to support fast image search, after draw special quality of data by N-dimension vector, store to database regarding this as value of N dimension and used data structure of Tree techniques to use index structure that search relevant data based on this costs. But, these are not coincided correctly in purpose of developmental disability diagnosis estimation because is developed focusing in application field that use data of low dimension such as original space DataBase or geography information system. Therefore, studied save structure and index mechanism of new way that support fast search to search bulky good physician data.