• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.1869-1880
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• 2009

Distribution line fault has been reduced gradually by the efforts on improving the quality of electrical materials and distribution system maintenance. However faults caused by medium voltage customers have been increased gradually even though we have done many efforts. The problem is that we don't know which customer will cause the fault. This paper presents the concept to find these customers using data mining techniques, which is based on accumulated fault records of medium voltage customers in the past. It also suggests the prediction model construction of medium voltage customers causing distribution line fault and methods to enhance the reliability of distribution system. We expect that we can effectively reduce faults resulted from medium voltage customers, which is 30% of total faults.

• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.909-916
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• 2010

A trend in software reliability engineering is to take into account the coverage growth behavior during testing. A coverage growth function that represents the coverage growth behavior is an essential factor in software reliability models. When multiple competitive coverage growth functions are available, there is a need for a criterion to select the best coverage growth functions. This paper proposes a selection criterion based on the prediction error. The conditional coverage growth function is introduced for predicting future coverage growth. Then the sum of the squares of the prediction error is defined and used for selecting the best coverage growth function.

• Journal of Applied Reliability
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• v.5 no.4
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• pp.427-438
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• 2005

This paper is concerned with the problem in predicting the reliability of an LCD product, Product reliability calculation methods classify accelerated life test (ALT) and using the reliability standard as MIL-HDBK-217F and Telcordia SR-332. The reliability standard can calculate estimating value more quickly than accelerated life test. The system MTBF was calculated in accordance of Telcordia SR-332 standard which includes directions of part electronic measurement, temperature rise and environmental test data. This research is intended to obtain the useful information for each electric design step to save time and cost.

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.04a
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• pp.69-75
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• 2006

As the level of technology and the standard of living improve, product reliability plays an Increasingly significant role. This study has been performed to build a reliability model of electronic ballasts for the low wattage fluorescent lamp. Telcordia SR-332, one of the most widely used reliability specifications, was selected for the model development. We briefly reviewed the basic concepts of the electronic ballast. We then developed a reliability model for the ballast using SR-332 concepts and the reliability has been examined.

• Journal of the Korean Geosynthetics Society
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• v.20 no.4
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• pp.141-149
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• 2021

In this study, an laboratory experiment was performed for prediction technology of water content in the ground using hyperspectral information. And the spectral reflectance with a specific wavelength band was obtained according to the fine and water content. Through it, the spectral information was normalized with the spectral index of the existing literature, and the relationship with the fine and water contents and the reliability of the prediction technology were analyzed. As a result of analysis, the spectral reflectance is decreased when the water and fine contents are increased under the high water contents. In addition, the reliability of prediction technology of water content was evaluated by examining 7 different spectral index calculation methods. Among them, DVI showed relatively high prediction reliability and was superior to other calculation methods in terms of sensitivity.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.2
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• pp.172-180
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• 2016

A cubesat classified as a pico-satellite typically uses commercial-grade components that satisfy the vibration and thermal environmental specifications and goes into mission orbit even after undergoing minimum environment tests due to their lower cost and short development period. However, its reliability exposed to the physical environment such as on-orbit thermal vacuum for long periods cannot be assured under minimum tests criterion. In this paper, we have analysed the reliability and life prediction of the failure mechanisms of the cubesat mission board during its service life under the launch and on-orbit environment by using the sherlock software which has been widely used in automobile fields to predict the reliability of electronic devices.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.12
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• pp.1379-1385
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• 2014

Even the rough prediction of the product test time before the lifetime test of mechanical component begins would be of use in estimating cost and deciding how to keep up with the test. The reliability predictions of mechanical components are difficult because failure or degradation mechanisms are complicated, and few plausible databases are available for lifetime prediction. Therefore, this study conducted lifetime predictions of elastomeric U seals that were respectively installed in a hydraulic actuator and a pneumatic actuator using lifetime models and a field database based on failure physics and an actual test database obtained from the NSWC handbook. To validate the results, the predicted failure rates were compared with the actual lifetime test results acquired in the lab durability tests. Finally, this study discussed an engineering procedure to determine the coefficients in the failure rate models and analyzed the sensitivity of each influential parameter on the seal lifetime.

• Geotechnical Engineering
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• v.13 no.6
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• pp.5-12
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• 1997

Predictions of settlements under preloading for the improvement of soft soil is a very important element of construction management. Due to the non uniformity, difficulty of estimating resonable soil properties, predictions of settlements and settlement velocities at the design stage seldom agree with the actual future settlements. To overcome this problem, the prediction methods based on the settlement observation of initial preloading stage such as hyperbolic method and Asaoka method have been employed frequently. However the estimating method for the reliability of these predictions at the time of prediction has not been suggested. In this study, comparisons of predicted settlements by hyperbolic met hed and observed settlements are explored through case studies. And a stratagem of estimating reliability of settlement predictions by hyperbolic method is suggested as the result of investigation on the relationship between the initial observed time and error of settlement prediction by hyperbolic method.

• The Journal of the Korea Contents Association
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• v.13 no.7
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• pp.379-385
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• 2013

On the internet, the rating scores assigned by customers are considered as the preference information of themselves and thus, these can be used efficiently in the customer profile generation process of recommender system. However, since anyone is free to assign a score that has a biased rating, using this without any filtering can exhibit a reliability problem. In this study, we suggest the methodology that measures the reliability of rating scores and then applies them to the customer profile creation process. Unlikely to some related studies which measure the reliability on the user level, we measure the reliability on the individual rating score level. Experimental results show that prediction accuracy of recommender system can be enhanced when ratings with higher reliability are selectively used for the customer profile configuration.

• Geomechanics and Engineering
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• v.30 no.2
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• pp.187-199
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• 2022

Kriging metamodel, as a flexible machine learning method for approximating deterministic analysis models of an engineering system, has been widely used for efficiently estimating slope reliability in recent years. However, the autocorrelation function (ACF), a key input to Kriging that affects the accuracy of reliability estimation, is usually selected based on empiricism. This paper proposes an adaption of the Kriging method, named as Genetic Algorithm optimized Whittle-Matérn Kriging (GAWMK), for addressing this issue. The non-classical two-parameter Whittle-Matérn (WM) function, which can represent different ACFs in the Matérn family by controlling a smoothness parameter, is adopted in GAWMK to avoid subjectively selecting ACFs. The genetic algorithm is used to optimize the WM model to adaptively select the optimal autocorrelation structure of the GAWMK model. Monte Carlo simulation is then performed based on GAWMK for a subsequent slope reliability analysis. Applications to one explicit analytical example and two slope examples are presented to illustrate and validate the proposed method. It is found that reliability results estimated by the Kriging models using randomly chosen ACFs might be biased. The proposed method performs reasonably well in slope reliability estimation.