• Korean Journal of Occupational Health Nursing
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• v.28 no.4
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• pp.262-270
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• 2019

Purpose: This study aims to provide preliminary data for weight management, and prevention and management of cardiovascular and cerebrovascular diseases. We examined the effect of changes in the weight of workers at a manufacturing company over three years on their metabolic syndrome and metabolic syndrome diagnosis components. Methods: Necessary data were collected from the questionnaire and the results of the Korean National Health Screening of 2015 and 2017, which included 228 workers at a manufacturing company in G region. The collected data were analyzed using the SPSS/WIN 23.0 program. ANCOVA was used to examine the differences in the metabolic syndrome diagnosis components according to weight change. In addition, multiple logistic regression analysis was used to obtain the odds ratios of metabolic syndrome and metabolic syndrome analysis component, based on the weight changes in the normal weight group and the obesity group. Results: Waist measure, systolic blood pressure, and blood pressure were found to have significant effects based on participants' weight change over three years. These factors increased with a larger increase in weight at a statistically significant level. This study analyzed the weight changes of the normal weight group and the obesity group considering the data from the National Health Screening of 2015, and found that the risk of metabolic syndrome increased at a statistically significant level as body weight increased; thus, the obesity group showed a higher risk in this regard. It was also found that waist measure, fasting blood sugar, and high-density low cholesterol increased at a statistically significant level as body weight increased. Conclusion: Health administrators need to recognize the importance of workers' weight management, select an intensive management group based on a time series analysis of weight changes, and develop and implement programs to manage the metabolic syndrome diagnosis components.

• Korean Journal of Adult Nursing
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• v.15 no.1
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• pp.22-32
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• 2003

Purpose: The purpose of this descriptive study was to identify the discharge nursing needs of patients who received gastrectomy. Method: The subjects of this study consisted of 100 patients who had gastric surgery in 4 university hospitals in chungnam province. The instrument for this study was developed by the researcher based on literature through in-depth interviews. Data was collected from October 4 to October 30, 2000. Result: The results were as follows: Discharge nursing needs were classified in 8 main categories. The 8 categories were 'emotional and spiritual support', 'nutrition and diet control', 'medication', 'treatment planning and follow up care', 'activity level', 'symptom management' 'health seeking behavior' and 'social support'. The total mean score for nursing needs was 3.89. 'Nutrition and diet control' was the highest degree of nursing needs and 'activity level' was the lowest degree of nursing needs. There were significant differences in degrees of nursing needs between different ages(F=2.74, p=.048), level of education(F=2.91, p=.038) and period since diagnosis(F=4.46, p=.037). Conclusion: This study looked at 8 categories of discharge nursing needs. Patients identified 'nutrition and diet control' as the highest need and 'activity level' as the lowest need. Further research needs to be done to identify discharge educational needs for various age groups, educational level and for patients with varing lengths of diagnosis time to surgery.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.2
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• pp.252-261
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• 2014

A Bayesian network (BN) based fault diagnosis framework for semiconductor etching equipment is presented. Suggested framework contains data preprocessing, data synchronization, time series modeling, and BN inference, and the established BNs show the cause and effect relationship in the equipment module level. Statistically significant state variable identification (SVID) data of etch equipment are preselected using principal component analysis (PCA) and derivative dynamic time warping (DDTW) is employed for data synchronization. Elman's recurrent neural networks (ERNNs) for individual SVID parameters are constructed, and the predicted errors of ERNNs are then used for assigning prior conditional probability in BN inference of the fault diagnosis. For the demonstration of the proposed methodology, 300 mm etch equipment model is reconstructed in subsystem levels, and several fault diagnosis scenarios are considered. BNs for the equipment fault diagnosis consists of three layers of nodes, such as root cause (RC), module (M), and data parameter (DP), and the constructed BN illustrates how the observed fault is related with possible root causes. Four out of five different types of fault scenarios are successfully diagnosed with the proposed inference methodology.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.10a
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• pp.236-241
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• 2010

This paper presents a wear diagnosis method for centrifugal impellers by using an accelerometer. The features are calculated from raw and wavelet transformed signals with several statistical methods applied in time or frequency domains. From the effectiveness coefficient test, it is shown that 7th level of wavelet transformed signal is suitable for wear classification problems. A neural network with 5 feature sets is applied to diagnose the wear magnitude of pump impellers. The verification result reveals that high accuracy for the wear diagnosis of impellers can be obtained by using wavelet features transformed from acceleration signals.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1428-1431
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• 1997

This paper presents an efficient fault diagnosis methodology for lare chemical processes. The methodology is based on a two-tier strategy, When a falt occurs in a process, a top tier identifies the sector (process part or unit) that may contain the fault(s). Afterwards, a bottom tier or lower level evaluates the suspicious sector. The process modeling methodology based on functionality-behavior relations of process units, is proposed and utilized in the top-tier. This methodology models a target process as sequences of functions and variables and their relations. In the bottom tier, each sector has a dedicated diagostic module, which is tailored to the available information or models of the sector. For the sectors selected in the top-tier diagnosis, each diagnostic module is executed to identify the actual faults within the sector. Teh utility of the methodology is illustrated in the diagnosis of the CSTR with heat exchanger.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.14 no.2
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• pp.122-129
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• 2011

The persistence of jaundice beyond the first 2 weeks of life require further investigation and this can be determined if the conjugated bilirubin levels are greater than 1.5 mg/dL or greater than 20% of the total bilirubin level. There is a diverse differential diagnosis for the cause of neonatal cholestasis due to hepatobiliary disease including biliary atresia, which eventually leads to liver cirrhosis if uncorrected before 60~80 days of life. Long-established initial studies include abdominal ultrasonography, hepatobiliary scintigraphy and liver biopsy, but better diagnostic methods are needed. Promising new options are described including MRCP (magnetic resonance cholangiography), ERCP (endoscopic retrograde cholangiography), and PCC (percutaneous cholecysto-cholangiography). Though no single test can differentiate biliary atresia from other neonatal cholestasis with confidence, a combination of diagnostic methods is usually consistently beneficial. By excluding biliary atresia as early as possible, the risk of unnecessary explolaparotomy with intraoperative cholangiography is decreased. Further evaluation would be required for the diagnosis of neonatal cholestasis after excluding biliary atresia.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.647-650
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• 2000

For the failure diagnosis of industrial system like various manufacturing systems, power plants and etc, many failure diagnosis approaches are considered. Here we are focus on the DES approach for failure diagnosis. We treats of failure recovery problem that is euly not mentioned in DES approach. The procedure to design a recoverable diagnoser is presented. And the recoverability, necessary and sufficient condition fur recoverability are defined. Then we make the high-level diagnoser to reduce the state size of recoverable diagnsoer. Finally, a pump-valve system example is presented.

• International Journal of Automotive Technology
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• v.7 no.2
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• pp.201-208
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• 2006

This paper describes the control philosophy of ESP(Electronic Stability Program) which consists of the stability control the fault diagnosis and the fault tolerant control. Besides the functional performance of the stability control, robustness of control and fault diagnosis is focused to avoid the unnecessary activation of the controller. The look-up tables are mentioned to have the accurate target yaw rate of the vehicle and obtained from vehicle tests for the whole operation range of the steering wheel angle and the vehicle speed. The wheel slip control with a design goal of wheel slip invariance is implemented for the yaw compensation and the target wheel slip is determined by difference between the target yaw rate and actual yaw rate. Since the ESP has a high severity level and the robust control is required, the robustness margin for the stability control is determined according to several uncertainties and the robust fault diagnosis is performed. Both computer simulation and test results are shown in this paper.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.05c
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• pp.33-37
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• 2001

Recently, the HFPD measurement testing is widely used in partial discharge measurement of HV machines because HFPD measurement testing receives less influence of external noise and has a merit of good sensitivity. Also HFPD testing is able to offer the judgement standard of degradation level of HV machine and can detect discharge signals in live-line. Therefore it is very useful method compare to previous conventional PD testing method and effective diagnosis method in power transformer that requires live-line diagnosis. But partial discharges have very complex characteristics of discharge pattern so it is required continuous research to development of precise analysis method. In recent, the study of partial discharge is carrying out discover of initial defect of power equipment through condition diagnosis and system development of degradation diagnosis using HFPD(High Frequency Partial Discharge) detection. In this study, simulated transformer is manufactured and HFPD occurred from transformer is measured with broad band antenna in real time, the degradation grade of transformer is analyzed through produced patterns in simulated transformer according to applied voltages.

• The Journal of the Korean dental association
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• v.55 no.11
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• pp.800-807
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• 2017

Ultrasonography is one of the most common diagnostic tools in medical imaging with non-invasive and non-radiation loaded characteristics. In the field of dentistry, especially for periodontology, high frequency ultrasonic device can be used for several purposes such as evaluating gingival thickness, identifying the level of alveolar bone, measuring the volume of mucosa of donor site for soft tissue graft and so on. According to recent studies, it was demonstrated that ultrasonic diagnosis had both accuracy and repeatability comparable to conventional diagnostic tools. However, improvement and development of intra-oral probe suitable for adpatation to gingiva and palatal mucosa, are considered as prerequisites for diffusion of ultrasonic diagnosis in periodontology.