• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.713-718
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• 2012

Lumber spine range of motion has been used to measure of physical and functional impairment by various tools from a ruler to 3D kinematic devices. However, pre-existing tools have problems in either movement or accuracy and reliability limitations. Accurate devices are limited by fixed space whereas simple devices are limited in measuring complex movements with less accuracy. In order to solve the location, movement and accuracy limitations at once, we have developed a novice measurement device equipped with accelerometer sensor and gyroscope sensor for getting three-dimensional information of motion. Furthermore, Kalman filter was applied to the algorithm to improve accuracy. In addition, RF wireless communication was added for the user to conveniently check measured data in real time. Finally, the measurement method was improved by considering the movement by a reference point. An experiment was conducted to test the accuracy and reliability of the device by conducting a test-retest reliability test. Further modification will be conducted to used the device in various joints range of motion in clinical settings in the future.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.7-11
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• 2011

Quantity take-off (QT) is one of the most important tasks for determining the total cost of a construction project, and it requires accuracy and reliability for the result. Accuracy and reliability in BIM-based QT are also required to assure the completeness of the result. However, there has been no basis to measure the completeness of the BIM-based QT result. As BIM is increasingly being adopted in the construction industry with a wide variety of purposes, it becomes more important to have a method to improve the completeness of BIM-based QT and criteria to measure it. This research focuses on the hypothesis that the completeness of BIM-based QT relies on the accuracy and reliability of BIM and the BIM-based QT process. As a basic research to determine the completeness of BIM-based QT, this research analyzes and derives factors that affect the completeness of BIM-based QT.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.780-786
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• 2013

In the reliability-based design optimization of electromagnetic devices, the accurate and efficient reliability assessment method is very essential. The first-order sensitivity-assisted Monte Carlo Simulation is proposed in the former research. In order to improve its accuracy for wide application, in this paper, the second-order sensitivity analysis is presented by using the hybrid direct differentiation-adjoint variable method incorporated with the finite element method. By combining the second-order sensitivity with the Monte Carlo Simulation method, the second-order sensitivity-assisted Monte Carlo Simulation algorithm is proposed to implement reliability calculation. Through application to one superconductor magnetic energy storage system, its accuracy is validated by comparing calculation results with other methods.

• Geomechanics and Engineering
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• v.17 no.6
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• pp.597-606
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• 2019

Ultrasonic Time-of-Flight Diffraction (TOFD) techniques are useful methods for non-destructive evaluation of fracture characteristics. This study focuses on the reliability and accuracy of ultrasonic diffraction methods to estimate the depth of rock fractures. The study material includes three different rock types; andesite, basalt and ignimbrite. Four different ultrasonic techniques were performed on these intact rocks. Artificial near-surface fracture depths were created in the laboratory by sawing. The reliability and accuracy of each technique was assessed by comparison of the repeated measurements at different path lengths along the rock surface. The standard error associated with the predictive equations is very small and their reliability and accuracy seem to be high enough to be utilized in estimating the depth of rock fractures. The performances of these techniques were re-evaluated after filling the artificial fractures with another material to simulate natural infills.

• International Journal of Reliability and Applications
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• v.3 no.1
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• pp.37-50
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• 2002

Simultaneous estimation of accuracy and probability corresponding to a prediction interval is considered in this study. Traditional application of confidence interval forecasting consists in evaluation of interval limits for a given significance level. The wider is this interval, the higher is probability and the lower is the forecast precision. In this paper a measure of stochastic forecast accuracy is introduced, and a procedure for balanced estimation of both the predicting accuracy and confidence probability is elaborated. Solution can be obtained in an optimizing approach. Suggested method is applied to constructing confidence intervals for parameters estimated by normal and t distributions

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.6
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• pp.982-989
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• 2010

This paper shows accuracy comparison results of reliability estimation methods for one-shot systems such as ammunitions. Quantal-response data, following a binomial distribution at each sampling time, characterizes lifetimes of one-shot systems. Various quantal-response data of different sample sizes are simulated using lifetime data randomly sampled from assumed weibull distributions with different shape parameters but the identical scale parameter in this paper. Then, reliability estimation methods in open literature are applied to the simulated quantal-response data to estimate true reliability over time. Rankings in estimation accuracy for different sample sizes are determined using t-test of SSE. Furthermore, MSE at each time, including both bias and variance of estimated reliability metrics for each method are analyzed to investigate how much both bias and variance contribute the SSE. From the MSE analysis, MSE provides reliability estimation trend for each method. Parametric estimation method provides more accurate reliability estimation results than the other methods for most of sample sizes.

• Structural Engineering and Mechanics
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• v.49 no.1
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• pp.111-128
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• 2014

The stochastic response surface method (SRSM) and the response surface method (RSM) are often used for structural reliability analysis, especially for reliability problems with implicit performance functions. This paper aims to compare these two methods in terms of fitting the performance function, accuracy and efficiency in estimating probability of failure as well as statistical moments of system output response. The computational procedures of two response surface methods are briefly introduced first. Then their capabilities are demonstrated and compared in detail through two examples. The results indicate that the probability of failure mainly reflects the accuracy of the response surface function (RSF) fitting the performance function in the vicinity of the design point, while the statistical moments of system output response reflect the accuracy of the RSF fitting the performance function in the entire space. In addition, the performance function can be well fitted by the SRSM with an optimal order polynomial chaos expansion both in the entire physical and in the independent standard normal spaces. However, it can be only well fitted by the RSM in the vicinity of the design point. For reliability problems involving random variables with approximate normal distributions, such as normal, lognormal, and Gumbel Max distributions, both the probability of failure and statistical moments of system output response can be accurately estimated by the SRSM, whereas the RSM can only produce the probability of failure with a reasonable accuracy.

• Structural Engineering and Mechanics
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• v.83 no.2
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• pp.167-178
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• 2022

Surrogate models aim to approximate the performance function with an active-learning design of experiments (DoE) to obtain a sufficiently accurate prediction of the performance function's sign for an inexpensive computational demand in reliability analysis. Nevertheless, many existing active-learning methods are limited to the Kriging model, while the uncertainties of the Kriging itself affect the reliability analysis results. Moreover, the existing general active-learning methods may not achieve a fully satisfactory balance between accuracy and efficiency. Therefore, a novel active-learning method GLM-CM is constructed to yield the issues, which conciliates several merits of existing methods. To demonstrate the performance of the proposed method, four examples, concerning both mathematical and engineering problems, were selected. By benchmarking obtained results with literature findings, various surrogate models combined with the proposed method not only provide an accurate reliability evaluation while highly alleviating the computational burden, but also provides a satisfactory balance between accuracy and efficiency compared to the other reliability methods.

• Journal of the Korean Society of Safety
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• v.35 no.5
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• pp.39-48
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• 2020

This study proposes a fast estimation method of dynamic reliability indices or failure probability for SDOF structure subjected to earthquake excitations. The proposed estimation method attempts to derive coefficient function for correcting dynamic effects from static reliability analysis in order to estimate the dynamic reliability analysis results. For this purpose, a total of 60 cases of structures with various characteristics of natural frequency and damping ratio under various allowable limits were taken into account, and various types of approximation coefficient functions were considered as potential candidate models for dynamic effect correction. Each reliability index was computed by directly performing static and dynamic reliability analyses for the given 60 cases, and nonlinear curve fittings for potential candidate models were performed from the computed reliability index data. Then, the optimal estimation model was determined by evaluating the accuracy of the dynamic reliability analysis results estimated from each candidate model. Additional static and dynamic reliability analyses were performed for new models with different characteristics of natural frequency, damping ratio and allowable limit. From these results, the accuracy and numerical efficiency of the optimal estimation model were compared with the dynamic reliability analysis results. As a result, it was confirmed that the proposed model can be a very efficient tool of the dynamic reliability estimation for seismically excited SDOF structure since it can provide very fast and accurate reliability analysis results.

• Journal of dental hygiene science
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• v.15 no.5
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• pp.673-678
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• 2015

The purpose of this study was to evaluate the reliability and accuracy of linear measurements in digital models compared to master model. A master model (ANKA-4; Frasaco GmbH, Tettnang, Germany) with the prepared upper full arch tooth was used. Four linear measurements were recorded between landmarks, directly on the master model and the digital models by a single examiner. Measurements were made with a digital caliper from manual model and with the software from the virtual models. The t-test for paired samples and intraclass correlation coefficient (ICC) were used for statistical analysis. The measurement of two methods showed good reliability. The mean differences between master and digital model were 0.06~0.12 mm. These in vitro studies show that accuracy and reliability of the digital impression is similar to that of the gold standard. Therefore digital impression was also considered to be a acceptable for placement clinically.