• Journal of Korean Medicine for Obesity Research
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• v.19 no.2
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• pp.119-136
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• 2019

Objectives: People often fail to maintain their weight even though they have succeeded in weight loss. The purpose of this study was to review previously published study results with regards to the predictive factors associated with weight loss maintenance after successful weight loss. Methods: The authors searched for the articles related to weight loss maintenance after successful weight loss, published up until June 2019 on PubMed, Cochrane Central Register of Controlled Trials (CENTRAL), Embase, Research Information Sharing Service (RISS), and Koreanstudies Information Service System (KISS). A total of 76 articles were finally selected. From the study results, changeable and unchangeable predictors were extracted, and these predictors were examined according to detailed categories. Results: The changeable predictors of weight loss maintenance included behavioral factors, psychological factors and treatment process-related factors, whereas the unchangeable predictors included genetic and physiological factors, demographic factors, history of treatment on obesity-related factors. The main factors of weight loss maintenance were changeable predictors such as healthy eating habits, dietary intake control, binge eating control, regular exercise and physical activity, depression and stress control, social supports, self-regulation, self-weighing and initial weight loss and unchangeable predictors such as low initial weight and maximum lifetime weight. Conclusions: The results of our review results suggest that changeable and unchangeable predictors of weight loss maintenance should be carefully examined during treatments of obesity.

• Korean Journal of Construction Engineering and Management
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• v.21 no.6
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• pp.46-55
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• 2020

The maintenance cost for highway pavement is gradually increasing due to the continuous increase in road extension as well as increase in the number of old routes that have passed the public period. As a result, there is a need for a method of minimizing costs through preventative grievance Preventive maintenance requires the establishment of a strategic plan through accurate prediction old Highway pavement. herefore, in this study, the XGBoost among machine learning classification-based models was used to develop a highway pavement damage prediction model. First, we solved the imbalanced data issue through data sampling, then developed a predictive model using the XGBoost. This predictive model was evaluated through performance indicators such as accuracy and F1 score. As a result, the over-sampling method showed the best performance result. On the other hand, the main variables affecting road damage were calculated in the order of the number of years of service, ESAL, and the number of days below the minimum temperature -2 degrees Celsius. If the performance of the prediction model is improved through more data accumulation and detailed data pre-processing in the future, it is expected that more accurate prediction of maintenance-required sections will be possible. In addition, it is expected to be used as important basic information for estimating the highway pavement maintenance budget in the future.

• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.644-647
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• 2003

The predictive maintenance can help to avoid the serious plant breakdowns and catastrophies. This paper deals with the fault diagnosis of the rotor of the induction motor which is widely used in the plants. In order to detect the broken bar, the Extended Kalman Filter is adopted to estimate the rotor resistance on the base of model-based method. The proposed estimation method is simulated with the aid of Matlab.

• Proceedings of the KIEE Conference
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• 1993.07b
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• pp.818-820
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• 1993

In the three phase full-wave thyristor rectifier, heat radiation concentrated at a few thyristor(s), while equipment's output is normal. That is very important on the predictive maintenance or checking including replacement of parts(or modules). Therefore, this report explains the method of effective diagnosis and the reason that firing control modules have to be adjusted accuratly on each phase.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.6 no.2
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• pp.267-276
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• 1999

The purpose of this study was to identify risk factors predictive of alterations in skin integrity during the intraoperative period. The predictive risk factors were studied for intraoperative pressure sores from December 1998 through January 1999. A sample of 220 patients was selected from the operating room schedule of a University Hospital in Pusan. There were two criteria in including patients : the operation lasted longer than 2 hours and the absence of skin break-down according to NPUAP criteria. The data were analized by SPSS/PC, Stepwise multiple logistic regression was used to identify the variables which were predictive of alterations in skin integrity. Of the 220 patients studied, 41 patients (18.6%) developed stage 1 pressure sores in the immediate postoperative period. In relation to skin changes, three independent variables emerged from the stepwise multiple logistic regression as being significant (p<0.05). Factors predictive of pressure sore formation included low serum albumin(p=0.000), prone position while undergoing surgery(p=0.0004), time on the operating table(p=0.0165). Among the intrinsic factors, serum albumin was the most significant causal factor in pressure sores development in the intra-operative period. Pressure and shearing force were the most significant extrinsic factors in pressure sores development. From the results of this study we concluded that the primary nursing goal is the maintenance of the proper patient' position during the intraoperative period. Also imperative for sore prevention is the reduction of surgery time and improving preoperative nutritional status.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.5
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• pp.393-402
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• 2013

The Mahalanobis-Taguchi System (MTS) is a diagnostic and predictive method for multivariate data. In the MTS, the Mahalanobis space (MS) of reference group is obtained using the standardized variables of normal data. The Mahalanobis space can be used for multi-class classification. Once this MS is established, the useful set of variables is identified to assist in the model analysis or diagnosis using orthogonal arrays and signal-to-noise ratios. And other several techniques have already been used for classification, such as linear discriminant analysis and logistic regression, decision trees, neural networks, etc. The goal of this case study is to compare the ability of the Mahalanobis-Taguchi System and logistic regression using a data set.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.10
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• pp.1882-1888
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• 2010

It is widely known that ESA(Electric Signature Analysis) method is very useful one for fault diagnosis of an induction motor. Online fault diagnosis system of induction motors using LabVIEW is proposed to detect the fault of broken rotor bars and shorted turns in stator. This system is not model-based system of induction motor but LabVIEW-based fault diagnosis system using FFT spectrum of stator current in faulty motor without estimating of motor parameters. FFT of stator current in faulty induction motor is measured and compared with various reference fault data in data base to diagnose the fault. This paper is focused on to predict and diagnose of the health state of induction motors in steady state. Also, it can be given to motor operator and maintenance team in order to enhance an availability and maintainability of induction motors. Experimental results are demonstrated that the proposed system is very useful to diagnose the fault and to implement the predictive maintenance of induction motors.

• Journal of the Korea Safety Management & Science
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• v.1 no.1
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• pp.7-17
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• 1999

As the loss from break-downs and errors, which became more frequent with the growth of elaborateness, complexity and in scale of the plant and equipments, are enormous, the improvement in the reliability, maintenance, safety, and qualify become to have interest. The fault diagnosis is a systematic and unified method to find errors, which is based on the interpretation that data, subconsciously, have noises. But, as most of the methods are inferences based on binomial logic, the uncertainty is not correctly reflected. In this study, we suggest, to manage the uncertainty in the system efficiently on the point of predictive maintenance, We should use fuzzy expert system, which make the decision considering uncertainty possible by taking linguistical variable and fixed quantity by using the fuzzy theory concepts on the basis of an expert's direct observation and experience.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.2
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• pp.189-194
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• 2015

In this paper, We study case for rotary machine with a breakdown analysis. Also We analyze the solution of the safety and the future breakdown of the each rotary machine through vibration analysis using measurement data. The implementation of the measurement and the test results are discussed. The result that is applied condition Monitoring & Diagnostics on this paper show the future breakdown of rotary machine.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.2
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• pp.195-202
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• 2015

Rotating equipment seldom fails without notice, so breakdowns can usually be predicted and avoided by watching for signs of failure. In this paper, We study case for rotary machine with a breakdown analysis. Also We analyze the solution of the safety and the future breakdown of the each rotary machine through vibration analysis using measurement data. The implementation of the measurement and the test results are discussed. The result with suggested method showed netter stable Condition Monitoring & Diagnostics.