• Journal of Korea Society of Industrial Information Systems
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• v.9 no.2
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• pp.1-8
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• 2004

In this paper, we propose three estimators of Kullback-Leibler Information functions using the data from accelerated life tests. This acceleration model is assumed to be a cumulative exposure model. Some asymptotic properties of proposed estimators are proved. Simulations are performed for comparing the small sample properties of the proposed estimators under use condition of accelerated life test.

• Korean Journal of Construction Engineering and Management
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• v.24 no.6
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• pp.81-90
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• 2023

Climate change has resulted in increased frequency and intensity of heat waves, which poses a significant threat to the health and safety of construction workers, particularly those engaged in labor-intensive and heat-stress vulnerable working environments. To address this challenge, this study aimed to propose an interpretable machine learning approach for forecasting personal heat strain by considering the cumulative effect of heat exposure as a situational variable, which has not been taken into account in the existing approach. As a result, the proposed model, which incorporated the cumulative working time along with environmental and personal variables, was found to have superior forecast performance and explanatory power. Specifically, the proposed Multi-Layer Perceptron (MLP) model achieved a Mean Absolute Error (MAE) of 0.034 (℃) and an R-squared of 99.3% (0.933). Feature importance analysis revealed that the cumulative working time, as a situational variable, had the most significant impact on personal heat strain. These findings highlight the importance of systematic management of personal heat strain at construction sites by comprehensively considering the cumulative working time as a situational variable as well as environmental and personal variables. This study provided a valuable contribution to the construction industry by offering a reliable and accurate heat strain forecasting model, enhancing the health and safety of construction workers.

• 대한예방의학회:학술대회논문집
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• 1994.02a
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• pp.651-657
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• 1994

To assess quantitatively the association between benzene exposure and leukemia, we examined the mortality rate of a cohort with occupational exposure to benzene. Cumulative exposure for each cohort member was estimated from historical air-sampling data and, when no sampling data existed, from interpolation on the basis of existing data. The overall standardized mortality ratio (a measure of relative risk multiplied by 100) for leukemia was 337 (95 percent confidence interval, 154 to 641), and that for multiple myeloma was 409 (95 percent confidence interval, 110 to 1047). With stratification according to levels of cumulative exposure, the standardized mortality ratios for leukemia increased from 109 to 322, 1186, and 6637 with increases in cumulative benzene exposure from less than 40 parts per million-years (ppm-years), to 40 to 199, 200 to 399, and 400 or more. respectively. A cumulative benzene exposure of 400 ppm years is equivalent to a mean annual exposure of 10 ppm over a 40-year working lifetime; 10 ppm is the currently enforceable standard in the United States for occupational exposure to benzene. To examine the shape of the exposure-response relation, we performed a conditional logistic-regression analysis, in which 10 controls were matched to each cohort member with leukemia. From this model, it can be calculated that protection from benzene induced leukemia would increase exponentially with any reduction in the permissible exposure limit.

• Communications for Statistical Applications and Methods
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• v.23 no.4
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• pp.269-285
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• 2016

In this paper, a simple step-stress accelerated life test (ALT) under progressive type-II censoring is considered. Progressive type-II censoring and accelerated life testing are provided to decrease the lifetime of testing and lower test expenses. The cumulative exposure model is assumed when the lifetime of test units follows an extension of the exponential distribution. Maximum likelihood estimates (MLEs) and Bayes estimates (BEs) of the model parameters are also obtained. In addition, a real dataset is analyzed to illustrate the proposed procedures. Approximate, bootstrap and credible confidence intervals (CIs) of the estimators are then derived. Finally, the accuracy of the MLEs and BEs for the model parameters is investigated through simulation studies.

• Safety and Health at Work
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• v.8 no.2
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• pp.130-142
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• 2017

Background: Osteoarthritis of the knee is considered to be related to knee straining activities at work. The objective of this review is to assess the exposure dose-response relation between kneeling or squatting, lifting, and climbing stairs at work, and knee osteoarthritis. Methods: We included cohort and case-control studies. For each study that reported enough data, we calculated the odds ratio (OR) per 5,000 hours of cumulative kneeling and per 100,000 kg of cumulative lifting. We pooled these incremental ORs in a random effects meta-analysis. Results: We included 15 studies (2 cohort and 13 case-control studies) of which nine assessed risks in more than two exposure categories. We considered all but one study at high risk of bias. The incremental OR per 5,000 hours of kneeling was 1.26 (95% confidence interval 1.17-1.35, 5 studies, moderate quality evidence) for a log-linear exposure dose-response model. For lifting, there was no exposure dose-response per 100,000 kg of lifetime lifting (OR 1.00, 95% confidence interval 1.00-1.01). For climbing, an exposure dose-response could not be calculated. Conclusion: There is moderate quality evidence that longer cumulative exposure to kneeling or squatting at work leads to a higher risk of osteoarthritis of the knee. For other exposure, there was no exposure dose-response or there were insufficient data to establish this. More reliable exposure measurements would increase the quality of the evidence.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.136-141
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• 2004

The gear in various mechanical components easily occurs at damages by the external torque. The main failure modes of the gear are surface pitting with the tooth surface and breakage with tooth root by caused fatigue. Therefore, the gear is very important role in the reliability research since it may cause fatal damage of entire system such as the gear box in automobile transmission. In this study, the failure mode of the gear was analyzed and accelerated durability analysis was employed for the life estimation of spur gears. In the case of assumed load spectrums, the reliability of spur gears was evaluated by inverse power law-Weibull accelerated life test model with cumulative damage exposure.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.271-280
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• 2015

In this paper, the maximum likelihood estimators for parameters are derived under three step-stress accelerated life tests for Type-I hybrid censored data. The exponential distribution and the cumulative exposure model are considered based on the assumption that a log quadratic relationship exits between stress and the mean lifetime ${\theta}$. The test plan to search optimal stress change times minimizing the asymptotic variance of maximum likelihood estimators are presented. A numerical example to illustrate the proposed inferential procedures and some simulation results to investigate the sensitivity of the optimal stress change times by the guessed parameters are given.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.2
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• pp.15-21
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• 1993

This paper considers the optimal design of accelerated life test in which the stress is linearly increased. It discusses the special case when the life distribution under constant stress follows an exponential distribution and the accelerated equation satisfies the inverse power law. It is assumed that cumulative damage is linear, that is, the remaining life of test units depends only on the current cumulative fraction failed and current stress(cumulative exposure model). The optimization criterion is the asymptotic variance of the maximum likelihood estimator of the log mean life at a design stress. The optimal increasing rate is obtained to minimize the asymptotic variance. Table of sensitivity analysis is given for the prior estimators of model parameters.

• International Journal of Reliability and Applications
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• v.15 no.2
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• pp.85-98
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• 2014

Accelerated life testing (ALT) is a well famous technique in life testing and reliability studies, this is particularly used to induce so high stress leading to failure of the highly reliable units quickly under stipulated duration of time. The step-stress ALT is one of the systematic experimental strategy of ALT applied to fail the units in steps. In this article we focus on two important issues (i) necessity of life tests at higher steps with relevant causes (ii) to develop a new optimum test plan for 3-step SSALT under the modified cumulative exposure model proposed by Khamis and Higgins (1998). It is assumed that the lifetime of test units follows Rayleigh distribution and its scale parameter at constant stress level is assumed to be a log-linear function of the stress. The maximum likelihood estimates of the parameters involved in the step-stress ALT model are obtained. A simulation study is performed for numerical investigation of the proposed new optimum plan 3-step, step-stress ALT. The necessity of the life test units at 3-step step-stress is also numerically examined in comparison to simple step-stress setup.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.04b
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• pp.132-135
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• 2002

In this paper, a new method to implement the photopolymer-based VHOE using the optimized exposure time schedule is proposed. The cumulative grating strength dependence on the exposure energy is mathematically modeled by using the fourth-order polynomial function and then using this model, the optimized exposure-time schedule of the photopolymer for recording the given multiple gratings is calculated.