• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.703-712
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• 2017

The composite blades of offshore wind turbines accumulate structural damage such as fatigue cracking due to harsh operation environments during their service time, leading to premature structural failures. This paper investigates various fatigue crack models for reproducing crack development in composite blades and proposes a stochastic approach to predict fatigue crack evolution and to analyse failure probability for the composite blades. Three typical fatigue models for the propagation of fatigue cracks, i.e., Miner model, Paris model and Reifsnider model, are discussed to reproduce the fatigue crack evolution in composite blades subjected to cyclical loadings. The lifetime probability of fatigue failure of the composite blades is estimated by stochastic deterioration modelling such as gamma process. Based on time-dependent reliability analysis and lifecycle cost analysis, an optimised maintenance policy is determined to make the optimal decision for the composite blades during the service time. A numerical example is employed to investigate the effectiveness of predicting fatigue crack growth, estimating the probability of fatigue failure and evaluating an optimal maintenance policy. The results from the numerical study show that the stochastic gamma process together with the proper fatigue models can provide a useful tool for remaining useful life predictions and optimum maintenance strategies of the composite blades of offshore wind turbines.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.849-861
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• 2021

This paper aims to introduce the basic concept of probabilistic record linkage and its statistical framework, and describe the specific process and principle of performing it using a real example from Statistics Korea. First, we briefly describe the deterministic record linkage and compare it with probabilistic record linkage. We introduce the Fellegi-Sunter model framework for record linkage and the related paprameters: m-probability, u-probability, matched weight and decision rule. Finally, we show the detailed process of record linkage under Fellegi-Sunter model framework and evaluate the record linkage results, using sample data from the registered-based census and Population and Housing Census survey in Statistics Korea.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.2
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• pp.63-72
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• 2016

An expected-discounted cost model based on RRP(Renewal Reward Process), referred to as a stochastic decision model, has been developed to estimate the optimal period of in-depth inspection which is one of critical issues in the life-cycle maintenance management of harbor structures such as rubble-mound breakwaters. A mathematical model, which is a function of the probability distribution of the service-life, has been formulated by simultaneously adopting PIM(Periodic Inspection and Maintenance) and CBIM(Condition-Based Inspection and Maintenance) policies so as to resolve limitations of other models, also all the costs in the model associated with monitoring and repair have been discounted with time. From both an analytical solution derived in this paper under the condition in which a failure rate function is a constant and the sensitivity analyses for the variety of different distribution functions and conditions, it has been confirmed that the present solution is more versatile than the existing solution suggested in a very simplified setting. Additionally, even in that case which the probability distribution of the service-life is estimated through the stochastic process, the present model is of course also well suited to interpret the nonlinearity of deterioration process. In particular, a MCS(Monte-Carlo Simulation)-based sample path method has been used to evaluate the parameters of a damage intensity function in stochastic process. Finally, the present stochastic decision model can satisfactorily be applied to armor units of rubble mound breakwaters. The optimal periods of in-depth inspection of rubble-mound breakwaters can be determined by minimizing the expected total cost rate with respect to the behavioral feature of damage process, the level of serviceability limit, and the consequence of that structure.

• Communications of Mathematical Education
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• v.26 no.2
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• pp.221-249
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• 2012

The purpose of this study is to investigate students decision-making progress through ill-structured problem solving process. For this study, 25 fifth graders in an elementary school were observed by applying ABCDE model (Analyze - Browse - Create - Decision making - Evaluate), and analyzed their decision-making progress analyzing framework which follows 3 steps - making their own decision, discussing/revising with peers, and lastly decision making/solving problem. Upper two groups with better performance in ill-structured problem solving model among 6 groups showed active discussion in group and decision making process with 3 steps (making their own decision, discussing/revising with peers). Even though their decisions are not good-fit to mathematical reasoning result, development and application of ill-structured problems would bring better ability of high level thinking and problem solving to students.

• The Journal of the Acoustical Society of Korea
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• v.24 no.7
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• pp.410-415
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• 2005

Recently, most of the speaker verification systems are based on the pattern recognition approach method. And performance of the pattern-classifier depends on how to classify a variety of speakers' feature parameters. In order to classify feature parameters efficiently and effectively, it is of great importance to enlarge variations between speakers and effectively measure distances between feature parameters. Therefore, this paper would suggest the positively mixed model scheme that can enlarge inter-speaker variation by searching the individual model with world model at the same time. During decision procedure, we can maximize inter-speaker variation by using the proposed mixed model scheme. We also make use of a symbol probability weighting function in this system so as to reduce vector quantization errors by measuring symbol probability derived from the distance rate of between the world codebook and individual codebook. As the result of our experiment using this method, we could halve the Detection Cost Function (DCF) of the system from $2.37\%\;to\;1.16\%$.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.367-372
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• 2013

In Speech recognition system, there is a problem with phoneme in the model training and it cause a stored mode regeneration process which come into being appear time and more costs. In this paper, we propose the methode of likely phoneme model schema using decision tree clustering. Proposed system has a robust and correct sound model which system apply the decision tree clustering methode form generate model, therefore this system reduce the regeneration process and provide a retrieve the phoneme unit in probability model. Also, this proposed system provide a additional likely phoneme model and configured robust correct sound model. System performance as a result of represent vocabulary dependence recognition rate of 98.3%, vocabulary independence recognition rate of 98.4%.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.483-490
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• 2021

In Indonesia, coffee shops, commonly called warung or kedai shops, have begun to appear amid society from remote villages to urban centers. Therefore, the purpose of this study is to examine the effect of cafe atmosphere (i.e., exterior, interior, interior point-of-purchase displays and store layout) on the purchase decision of Generation Z. This study is conducted because of cafe competition is currently overgrowing. This study model consisted of five variables: exterior, interior, interior point-of-purchase displays, store layout, and purchase decision. Sampling in this study used non-probability, with a purposive sampling technique. According to predetermined criteria, the data collection technique employed a questionnaire distributed online to consumers had visited a cafe at least once in the last three months. This study's sample was 137 cafe visitors in Yogyakarta, representing one of the big cities in Indonesia. Therefore, the data was analyzed by using multiple regression. The results of the study indicated that the exterior and interior had a positive and significant effect on purchasing decision. Likewise, interior point-of-purchase displays and store layout positively and significantly affected purchase decision. In addition, this study's findings generally concluded that the cafe atmosphere had a positive and significant effect on purchase decision.

• Journal of Hospice and Palliative Care
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• v.24 no.3
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• pp.184-193
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• 2021

Purpose: This study attempted to develop clinical guidelines to help patients use hospice and palliative care (HPC) at an appropriate time after writing physician orders for life-sustaining treatment (POLST) by identifying the characteristics of HPC use of patients with terminal cancer. Methods: This retrospective study was conducted to understand the characteristics of HPC use of patients with terminal cancer through decision tree analysis. The participants were 394 terminal cancer patients who were hospitalized at a cancer-specialized hospital in Seoul, South Korea and wrote POLST from January 1, 2019 to March 31, 2021. Results: The predictive model for the characteristics of HPC use showed three main nodes (living together, pain control, and period to death after writing POLST). The decision tree analysis of HPC use by terminal cancer patients showed that the most likely group to use HPC use was terminal cancer patients who had a cohabitant, received pain control, and died 2 months or more after writing a POLST. The probability of HPC usage rate in this group was 87.5%. The next most likely group to use HPC had a cohabitant and received pain control; 64.8% of this group used HPC. Finally, 55.1% of participants who had a cohabitant used HPC, which was a significantly higher proportion than that of participants who did not have a cohabitant (1.7%). Conclusion: This study provides meaningful clinical evidence to help make decisions on HPC use more easily at an appropriate time.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.433-444
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• 2021

The study seeks to identify the factors affecting the green marketing element of students' food purchasing decision at Co-opMart supermarket chain in Ho Chi Minh City through the application of a mix of qualitative and quantitative research methods that include probability sampling and convenient sampling of 400 students from Ho Chi Minh City University of Technology (HUTECH). The data are analyzed with SPSS software using Cronbach's Alpha, Exploratory Factor Analysis, Multiple Linear Regression and PATH model to test the model through the intermediate variable 'student's perception' and the hypotheses, identifying the green marketing effects on HUTECH students' food purchasing decisions at Ho Chi Minh City Co-opMart supermarket chain. The results of the study identify four factors of the green marketing mix (4Cs), namely, green commodity, green cost, green convenience, and green communication. All these factors have an influence on the student's food purchasing decision at Co-opMart supermarket. Cost is the strongest factor eliciting student's interest in purchasing green products, followed by convenience, then communication. Commodity has the least impact on green purchasing decision. This study proposes some feasible solutions for Co-opMart managers to attract more students using green food in the complex situation of contaminated food, which is extremely harmful to consumers' health.

• KDI Journal of Economic Policy
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• v.32 no.1
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• pp.131-169
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• 2010

I develop a matching model in which risk-averse workers face borrowing constraints and make a labor force participation decision as well as a job search decision. A sharp distinction between unemployment and out of the labor force is made: those who look for work for a certain period but find no job are classified as the unemployed and those who do not look for work are classified as those out of the labor force. In the model, the job search decision consists of two steps. First, each individual who is not working obtains information about employment opportunities. Second, each individual who decides to search has to take costly actions to find a job. Since individuals differ with respect to asset holdings, they have different reservation job-finding probabilities at which an individual is indifferent between searching and not searching. Individuals, who have large asset holdings and thereby are less likely to participate in the labor market, have high reservation job-finding probability, and they are less likely to search if they have less quality of information. In other words, if individuals with large asset holdings search for job, they must have very high quality of information and face very high actual job-finding probability. On the other hand, individuals with small asset holdings have low reservation job-finding probability and they are likely to search for less quality of information. They face very low actual job-finding probability and seem to remain unemployed for a long time. Therefore, differences in the quality of information explain heterogeneous job search decisions among individuals as well as higher job finding probability for those who reenter the labor market than for those who remain in the labor force. The effect of the extended maximum duration of unemployment insurance benefits on the aggregate labor market and the labor market flows is investigated. The benchmark benefit duration is set to three months. As maximum benefit duration is extended up to six months, the employment-population ratio decreases while the unemployment rate increases because individuals who are eligible for benefits have strong incentives to remain unemployed and decide to search even if they obtain less quality of information, which leads to low job-finding probability and then high unemployment rate. Then, the vacancy-unemployment ratio decreases and, in turn, the job-finding probability for both the unemployed and those out of the labor force decrease. Finally, the outflow from nonparticipation decreases with benefit duration because the equilibrium job-finding probability decreases. As the job-finding probability decreases, those who are out of the labor force are less likely to search for the same quality of information. I also consider the matching model with two states of employment and unemployment. Compared to the results of the two-state model, the simulated effects of changes in benefit duration on the aggregate labor market and the labor market flows are quite large and significant.