• Journal of Korean Institute of Industrial Engineers
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• v.30 no.2
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• pp.84-92
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• 2004

A process control procedure is proposed when 100% inspection is performed in a process with excellent capability. Only the incomplete measurement data is assumed to be available, i.e. the specific measurement value of the quality characteristic is not available for each item but it can be determined to be smaller or larger than any prescribed value. In the suggested model, a signal limit is introduced to determine whether the process under study is in control or not. If the quality characteristic of an incoming item exceeds the upper signal or the lower signal limit, the process is determined to be stopped or not by comparing the number of consecutively accepted items with a predetermined threshold number. The procedure is designed based on the type I and II errors. The performance of the model is evaluated by the expected number of items produced under the in-control and out-of-control states until the process is stopped.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.471-483
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• 2012

In this paper, the structural health monitoring (SHM) benchmark problem of the Canton tower is studied. Based on the field monitoring data from the 20 accelerometers deployed on the tower, some modal frequencies and mode shapes at measured degrees of freedom of the tower are identified. Then, these identified incomplete modal data are used to update the reduced finite element (FE) model of the tower by a novel algorithm. The proposed algorithm avoids the problem of subjective selection of updated parameters and directly updates model stiffness matrix without model reduction or modal expansion approach. Only the eigenvalues and eigenvectors of the normal finite element models corresponding to the measured modes are needed in the computation procedures. The updated model not only possesses the measured modal frequencies and mode shapes but also preserves the modal frequencies and modes shapes in their normal values for the unobserved modes. Updating results including the natural frequencies and mode shapes are compared with the experimental ones to evaluate the proposed algorithm. Also, dynamic responses estimated from the updated FE model using remote senor locations are compared with the measurement ones to validate the convergence of the updated model.

• Journal of Information Technology Services
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• v.11 no.1
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• pp.239-246
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• 2012

The user increases around the WiBro and in which the mobile broad band service is the wireless internet base technology HSDPA, that is the cellular phone foundation technique, and moreover the issue about the user effective quality guarantee emerges but the quality control of the wireless network is the incomplete actual condition. Therefore, the reliability verification according to the development of the system for the performance measure for the continued wireless data service and it and evaluation are needed for the quality control. In this paper, the wireless data service quality measurement system was implemented with the design. The same test environment as the existing network performance measurement program was built for the reliability verification of the embodied device for measuring quality and evaluation and the cost performance was performed. It could confirm that design and embodied wireless data service quality measurement system operated accurately in this paper through the quality measure result value analysis.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.11
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• pp.2033-2048
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• 1992

This paper presents the theoretical development and qualitative evaluation of a new concept in the mathematical modeling of dynamic structures. We use both test data and analytical approximations to identify the parameters of an incomplete model. The model has the capability of predicting the response of the points of interest on the structure over the frequency range of interest and can be used to predict the changes in natural frequencies and normal modes due to structural changes. The theory was tested by running simulated tests on a relatively simple structure, identifying the parameters of the incomplete model, and using this model to predict the effects on frequency and mode shapes of several mass and stiffness changes. The conditions of the tests were varied by selecting different numbers of points of measurement, varying the frequency range, and by including assumed measurement error. It is recommended that the theoretical development be continued and that applications to more complex structures be carried out in order to develop a better understanding of the limitations and capabilities of the method. A successful, more definitive sevaluation could lead to immediate practical applications.

• Journal of The Geomorphological Association of Korea
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• v.27 no.2
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• pp.19-28
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• 2020

Grain size analysis is the most basic procedure for identifying the origin, transport and sedimentation processes of sediments, and is widely used in geomorphology and sedimentology. Traditionally, grain size was determined by a sieve-pippette method, but the use of automated analyzers is increasing in recent years. These analyzers have many advantages over traditional techniques, but the measurement results are not always the same. It is still difficult to solve the pretreatment problem such as incomplete diffusion and residual organic matter, and inappropriate results may be obtained. This study compared image-based grain size analysis and sieve analysis to verify its statistical reliability, and conducted experiments to enhance the measurement accuracy using shape parameters. The results showed that the image-based analysis overestimated the grain size of sand dunes by about 7% compared to the sieve analysis, but the two measurements were not statistically different. In addition, by using shape parameters, such as aspect ratio, sphericity, and convexity, improved statistics were obtained compared to the original data. Using the morphological properties of the individual grains is a complementary method to the incomplete pretreatment of the grain size analysis process, and at the same time, it will contribute to improving the accuracy and reliability of the results.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.244-249
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• 1998

The present paper improves the direct identification scheme based upon the equation error formulation with incomplete modal data. First, an indirect estimation technique is considered for estimating unmeasured elements of latent vectors by the combined use of a model and measured incomplete eigen vectors. It is used for estimating the other elements of eigen vectors, which are essential for identification but not available. Next an index is introduced here to indicate the quality of estimation with respect to the mode and the measured positions. A sensitivity formula for eigenvalues with respect to the unknown joint coefficient is also derived to select the modes appropriate for identification. An identification strategy is suggested to meet with practical problems with the help of the index and sensitivity formula. The index and the sensitivity are proved to be useful for selecting measurement positions and modes appropriate for identification A comprehensive simulation study is performed to test the proposed method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.04a
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• pp.279-284
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• 1992

This paper presents the theoretical development and qualitiative evaluation of a new concept in the mathematical modeling of dynamicstructures. We use both test data and analytical approximations to identify the parameters of an incomplete model. The model has the capability of prodicting the response of the points of interest on the structure over the frequency range of interest and can be used to predict the changes in natural frequencies and normal modes due to structural changes. The theory was tested by running simulated tests on a relatively simple structure, identifying the parameters of the incomplete model, and using this model to predict the effects on frequency and mode shapes of several mass and stiffness changes. The conditions of the test were varied by selecting different numbers of points of meansurement, varying the frequency range, and by including assumed measurement error. It is recommended that the theroetical development be continued and that applications to more complex structures be carried out in order todevelop a better understanding of the limitations and capabilites of the method. A successful, more definitive evaluation could lead to immediate practical applications.

• The Journal of Korean Institute for Practical Engineering Education
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• v.3 no.1
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• pp.45-50
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• 2011

Despite the highly sophisticated development of finite element analysis, a finite element model for structural dynamic analysis can be inaccurate or even incorrect due to the difficulties of correct modelling, uncertainties on the finite element input data and geometrical oversimplification, while the modal data extracted from measurement are supposed to be correct, even though incomplete. The assumption that the test results represent the true dynamic behaviour of the structure, however, may not be correct because of various measurement errors. The measurement errors are investigated and their effects on estimated frequency response functions(FRFs) are also investigated.

• Advances in nano research
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• v.14 no.3
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• pp.225-234
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• 2023

In this study, we aim to use big data resources and statistical analysis to obtain a reliable instruction to reach high-quality and high yield agricultural yields. In this regard, soil type data, raining and temperature data as well as wheat production in each year are collected for a specific region. Using statistical methodology, the acquired data was cleaned to remove incomplete and defective data. Afterwards, using several classification methods in machine learning we tried to distinguish between different factors and their influence on the final crop yields. Comparing the proposed models' prediction using statistical quantities correlation factor and mean squared error between predicted values of the crop yield and actual values the efficacy of machine learning methods is discussed. The results of the analysis show high accuracy of machine learning methods in the prediction of the crop yields. Moreover, it is indicated that the random forest (RF) classification approach provides best results among other classification methods utilized in this study.

• Structural Engineering and Mechanics
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• v.68 no.1
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• pp.39-51
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• 2018

In this study, a frequency domain model updating method is presented using power spectral density (PSD) data. It uses the sensitivity of PSD function with respect to the unknown structural parameters through a decomposed form of transfer function. The stiffness parameters are captured with high accuracy through solving the sensitivity equations utilizing the least square approach. Using numerically noise polluted data, the model updating results of a truss model prove robustness of the method against measurement and mass modelling errors. Results prove the capabilities of the method for parameter estimation using highly noise polluted data of low ranges of excitation frequency.