• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.1
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• pp.31-36
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• 2010

Collecting all failures during life cycle of vehicle is not easy way because its life cycle is normally over 10 years. Warranty period can help gathering failures data because most customers try to repair its failures during warranty period even though small failures. This warranty data, which means failures during warranty period, can be a good resource to predict initial reliability and permanence reliability. However uncertainty regarding reliability prediction remains because this data is censored. University of Wuppertal and major auto supplier developed the reliability prognosis model considering censored data and this model introduce to predict reliability estimate further "failure candidate". This paper predicts reliability of telecommunications system in vehicle using the model and describes data structure for reliability prediction.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.4
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• pp.134-140
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• 2016

Main Spindle System has effect on performance of machine tools and working quality as well as is required of high reliability. Especially, it takes great importance in producing automobiles which includes a large number of working processes. However, main spindle unit in Machine tools are often cases where damage occurs do not meet the design life due to driving in harsh environments. This is when excessive maintenance and repair of machine tools or for damage stability has resulted in huge economic losses. Therefore, this studying propose a method of accelerated life test for diagnosing and prognosis the state of life assessment main spindle system. Time status monitoring of diagnostic data - through the analysis of the frequency band signals were carried out inside the main spindle bearing condition monitoring and fault diagnosis.

• Journal of Gastric Cancer
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• v.20 no.4
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• pp.385-394
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• 2020

Purpose: Patients with gastric cancer who receive neoadjuvant therapy are staged before treatment (cStage) and after treatment (ypStage). We aimed to compare the prognostic reliability of cStage and ypStage, alone and in combination. Materials and Methods: Data for all patients who received neoadjuvant therapy followed by surgery for gastric adenocarcinoma from 2004 to 2015 were extracted from the National Cancer Database. Kaplan-Meier (KM)curves were used to model overall survival based on cStage alone, ypStage alone, cStage stratified by ypStage, and ypStage stratified by cStage. P-values were generated to summarize the differences in KM curves. The discriminatory power of survival prediction was examined using Harrell's C-statistics. Results: We included 8,977 patients in the analysis. As expected, increasing cStage and ypStage were associated with worse survival. The discriminatory prognostic power provided by cStage was poor (C-statistic 0.548), while that provided by ypStage was moderate (C-statistic 0.634). Within each cStage, the addition of ypStage information significantly altered the prognosis (P<0.0001 within cStages I-IV). However, for each ypStage, the addition of cStage information generally did not alter the prognosis (P=0.2874, 0.027, 0.061, 0.049, and 0.007 within ypStages 0-IV, respectively). The discriminatory prognostic power provided by the combination of cStage and ypStage was similar to that of ypStage alone (C-statistic 0.636 vs. 0.634). Conclusions: The cStage is unreliable for prognosis, and ypStage is moderately reliable. Combining cStage and ypStage does not improve the discriminatory prognostic power provided by ypStage alone. A ypStage-based prognosis is minimally affected by the initial cStage.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.2
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• pp.287-291
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• 2013

Fault Diagnosis is a process of detecting and isolating faults in a system. On demanding for safety and high reliability systems make it important for some reasons such as economical and environmental incentives. Especially embedded technology and IT technology combined with precise sensing techniques has been doing well developed and applied to fault diagnosis and prognosis in industrial systems like as automotive, ship, heavy industry and aerospace as well. This paper, as an empirical application of diesel engine, presents a method how to get raw data from physical systems, what to consider for successful implementation and which theoretic mathematical models should be applied. In a sense of system level Adaptive Filtering (we call Modified Kalman Filter) and a unit of part level Hidden Markov Process was developed and applied.

• Journal of Korean Academy of Nursing
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• v.17 no.2
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• pp.122-136
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• 1987

A group of studies revealed that family members of the seriously ill patient had some needs during the period of patient's hospitalization. Needs of the seriously-ill patient family could be classified into three aspect, i. e. needs on the prognosis of patient, needs on the well-being of family members themselves and needs on hospital environment. Several instrument were developed to measure the needs of the seriously ill patient, but their content tended to overemphasize the aspect of the prognosis of patient. The purpose of this study was to develop a new instrument to measure the needs in the aspect of the seriously ill patient's family themselves in details to increase the cummulative Percentage of the scale. Subjects were 134 family members of the seriously-ill patients, who were bung cared in ICU of seven university hospitals and data were collected from march 16, 1987 to April 11, 1987. The instrument used in this study was made by the author on the basis of results of literature review. Content valitity of the instrument was tested by a professor majoring in nursing and reliability by calculation of Cronbach's α with data of the respondents. Data was analyzed as follows, using SAS, computer system. Factor structures of the seriously ill patients' family needs were elicited by factor analysis. The programme was the Principal Component Factor Analysis Method of factoring employing Varimax Orthogonal Rotation. The influences of the demographic variables on the degree of the seriously-ill patients' family need were analyzed by t-test and P-test. Results were as follows. 1. Needs of the seriously-ill patients' family elicited and their cummulative percentage were: Needs to be supported emotionally, 29.2% Needs to be informed on facilities available, 9.6% Needs to be informed on the patient's prognosis, 7.7%. Needs to be supported spiritually, 5.1%. Needs to be informed on hospital environment, 4.2%. Needs to be helped to spare time, 3.9%. Needs to be informed on their role, 3.5%. Needs to be present near patient, 3.3%. 2. Educational background was found to influence on some factors. College-graduate group had higher Bevel of needs to be . informed on facilities available to be informed on the patient's prognosis, needs to be supported spiritually, needs to be helped to spare time, needs to be informed on their role than high school graduate group. 3. Among the parents, sons and daughters and the relative groups, the parents of the seriously ill patient had highest level of needs to be present near patient. Suggestions for further studies were as follows. 1. As the instruments used in the previous studies had high cummulative percentages in the aspect of the prognosis of patient and that in this study in the aspect of the prognosis of patient and that in this study in the aspect of the seriously ill patient's family themselves, development of a new instrument which combined the items of both of them is needed. 2. A study to clarify the influence of type and number of admission on need to be supported emotionally is needed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.6
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• pp.810-816
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• 2012

As wind power has increased steadily, the importance of a condition monitoring system is being emphasized to maximize the availability and reliability of a wind turbine. To develop the advanced algorithms for fault detection and lifespan estimation, a wind turbine simulator is essential for verification of the proposed algorithms before applying them to a condition diagnosis & integrity prognosis system. The developed new-type simulator in this paper includes blades and various sensors as well as a motor, a gearbox and a generator of which the existing simulators generally consist. It also has similarity with a 3MW class wind turbine and can be used to acquire operational data from various operation conditions. This paper presents a design method of control logic for the wind turbine simulator, which gives a wind generation method and similar dynamic characteristics with the 3MW wind turbine. Finally, the proposed control logic is verified through experiments.

• 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 the Society of Naval Architects of Korea
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• v.60 no.2
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• pp.95-109
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• 2023

In the 4th industrial revolution, changes in the technological paradigm have had a direct impact on the maintenance system of ships. The 2-stroke low speed engine system integrates with the core equipment required for propulsive power. The Condition Based Management (CBM) is defined as a technology that predictive maintenance methods in existing calender-based or running time based maintenance systems by monitoring the condition of machinery and diagnosis/prognosis failures. In this study, we have established a framework for CBM technology development on our own, and are engaged in engineering-based failure analysis, data development and management, data feature analysis and pre-processing, and verified the reliability of failure mode DB using LSTM algorithms. We developed various simulated failure mode scenarios for 2-stroke low speed engine and researched to produce data on onshore basis test_beds. The analysis and pre-processing of normal and abnormal status data acquired through failure mode simulation experiment used various Exploratory Data Analysis (EDA) techniques to feature extract not only data on the performance and efficiency of 2-stroke low speed engine but also key feature data using multivariate statistical analysis. In addition, by developing an LSTM classification algorithm, we tried to verify the reliability of various failure mode data with time-series characteristics.

• Restorative Dentistry and Endodontics
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• v.46 no.1
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• pp.8.1-8.7
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• 2021

Objectives: The reliability and educational quality of videos on YouTube for patients seeking information regarding instrument separation in root canal treatment were evaluated. Materials and Methods: YouTube was searched for videos on instrument separation in root canal treatment. Video content was scored based on reliability in terms of 3 categories (etiology, procedure, and prognosis) and based on video flow, quality, and educational usefulness using the Global Quality Score (GQS). Descriptive statistics were obtained and the data were analyzed using analysis of variance and the Kruskal-Wallis test. Results: The highest mean completeness scores were obtained for videos published by dentists or specialists (1.48 ± 1.06). There was no statistically significant difference among sources of upload in terms of content completeness. The highest mean GQS was found for videos published by dentists or specialists (1.82 ± 0.96), although there was no statistically significant correlation between GQS and the source of upload. Conclusions: Videos on YouTube have incomplete and low-quality content for patients who are concerned about instrument separation during endodontic treatment, or who experience this complication during endodontic treatment.

• The Journal of Internal Korean Medicine
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• v.38 no.2
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• pp.152-163
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• 2017

Objectives: The aim of this review was to compare the findings of 14 studies of tongue diagnosis in Korean stroke patients. Methods: The purpose, subjects, observation methods, statistical methods, classification of tongue diagnosis, significance, and limitations were analyzed and compared. Results: In Korean stroke patients, tongue diagnosis is significant in pattern identifications, prognosis evaluation, degree of neurological deficit, past history, blood tests, and pulse diagnosis. Interobserver reliability of tongue diagnosis is relatively high.