• 한국정보시스템학회지:정보시스템연구
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• 제10권2호
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• pp.165-192
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• 2001

Knowledge Management (KM) is the systematic, explicit, and deliberate building, renewal, and application of knowledge to maximize an enterprise's knowledge-related effectiveness and performance from its knowledge assets. KM applies systematic approaches to find, understand, and use knowledge to create new capabilities, solve problems, enable superior performance, and encourage innovation. The purpose of this research is to identify the relationship of KM capabilities (KM infrastructures and KM processes) and organizational effectiveness and performance. An empirical research of the relationship of knowledge management capabilities and organizational effectiveness and performance is conducted from the information systems and knowledge management literature in order to access the following questions: (1) Does the knowledge management infrastructure contribute to the organizational effectiveness and peformance? (2) Does the knowledge management process contribute to the organizational effectiveness and peformance? The research design employs a mail survey questionnaire for gathering data from 500 firms in a number of industries. From a mail survey of 61 top managers of knowledge management, the results of empirical analyses provide the following major findings: (1) While the external effectiveness of organization is influenced by the cultural infrastructure of knowledge management, the overall performance of organization is influenced by the structural infrastructure of knowledge management. (2) While the external effectiveness of organization is influenced by the application and protection processes of knowledge management, the overall performance of organization is influenced by the knowledge acquisition process of knowledge management.

• 한국기계가공학회지
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• 제16권3호
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• pp.54-62
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• 2017

When gears mesh, shock and noise are produced as results of tooth error and tooth deformation under load. Transmission error (TE) is the most important cause of gear noise and vibration because TEs affect the changes of the force and the speed of gears. Gear tooth modification research plays a positive role in reducing TE and improving the design level and transmission performance of transmission systems. In high-precision manufacturing gear, gear tooth modification is also commonly used to reduce noise in practical applications. In order to study the accuracy of gear transmission, some empirical gear profile micro-modifications are introduced, and a helical gear pair is modeled and analyzed in RomaxDesigner software to investigate the utility of these modification methods. Some of these will be selected as experimental proposals for gear pairs, and these manufactured gears will be tested and compared in a semi-anechoic room later. The final purpose of this study is to find reasonable and convenient empirical formulae to facilitate improved gear production.

• Geomechanics and Engineering
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• 제28권3호
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• pp.313-324
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• 2022

Rock properties are important in the design of mines and civil engineering excavations to prevent the imminent failure of slopes and collapse of underground excavations. However, the time, cost, and expertise required to perform experiments to determine those properties are high. Therefore, empirical models have been developed for estimating the mechanical properties of rock that are difficult to determine experimentally from properties that are less difficult to measure. However, the inherent variability in rock properties makes the accurate performance of the empirical models unrealistic and therefore necessitate the use of soft computing models. In this study, Gaussian process regression (GPR), artificial neural network (ANN) and response surface method (RSM) have been proposed to predict the static and dynamic rock properties from the P-wave and rock density. The outcome of the study showed that GPR produced more accurate results than the ANN and RSM models. GPR gave the correlation coefficient of above 99% for all the three properties predicted and RMSE of less than 5. The detailed sensitivity analysis is also conducted using the RSM and the P-wave velocity is found to be the most influencing parameter in the rock mechanical properties predictions. The proposed models can give reasonable predictions of important mechanical properties of sedimentary rock.

• 터널과지하공간
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• 제13권4호
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• pp.260-269
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• 2003

In order to introduce to engineers the suitable calculation techniques of TBM advance rate (ad.) and ultimately promote to understand the designing process, this study was carried out. We analyzed the 17 bored data of TBM which applied to the roadway and water supply tunnels in Korea. From this analysis, it was able to how that the average utilization is 30.83% md the correlation equation of Ad and TBM´s diameter (D) is Ad(m/month) = 506.05ㆍ $e^{-0.1162}$$\times$D than the correlation coefficient ($R^2$) is 0.76. In the object of the W tunnel of Seoul-Busan highspeed railway, the Ad of TBM 5.0mø was analyzed by the variety of empirical models and upper correlation equation. Average Ad of the empirical models was calculated to be larger than one of the upper equations. But considering only the results of 3.0~5.0mø TBM in the 17 bored data, the average Ad by the models belongs to the similar range of bored data. Therefore, when the reliability and representative of parameters are decreased, a reliability test should be carried out through the comparison a variety of empirical models with the upper correlation equation.

• Corrosion Science and Technology
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• 제19권4호
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• pp.174-188
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• 2020

Atmospheric corrosion is a natural surface degradation process of metal due to changes in environmental parameters in the surrounding atmosphere. It is very sensitive to environmental parameters such as temperature, relative humidity, sulphur dioxide, and chloride, making it a major global economic challenge. Existing forecasting empirical corrosion models including the ISO standard are based on statistical analysis of experimental studies without considering the behavior of atmospheric parameters. The present study proposes a reliable global empirical model for estimating short and long-term atmospheric corrosion rates based on environmental parameters and corrosion mechanisms obtained from a parametric study. Repercussion of atmospheric corrosion rate due to individual and combined influences of environmental parameters specifies their importance in the estimation. New global empirical coefficients obtained for environmental parameters are statistically established (R² =0.998) with 95% confidence limit. They are validated using experimental datasets of existing studies observed at 88 different continental locations. The current proposed model can predict atmospheric corrosion by means of corrosion formation mechanisms influenced by combined effects of environmental parameters, further abating applicability limitations of location and time.

• 대한수학회지
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• 제32권3호
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• pp.427-446
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• 1995

Let S be a set and B be a $\sigma$-field on S. We consider $(\Omega = S^Z, T = B^z, P)$ as the basic probability space. We denote by T the left shift on $\Omega$. We assume that P is invariant under T, i.e., $PT^{-1} = P$, and that T is ergodic. We denote by $X = \cdots, X_-1, X_0, X_1, \cdots$ the coordinate maps on $\Omega$. From our assumptions it follows that ${X_i}_{i \in Z}$ is a stationary and ergodic process.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2005년도 춘계 학술발표회 논문집
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• pp.179-184
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• 2005

Empirical findings on interet rate dynamics imply that short rates show some long memories and non-Markovin. It is well-known that fractional Brownian motion(fBm) is a proper candidate for modelling this empirical phenomena. fBm, however, is not a semimartingale process. For this reason, it is very hard to apply such processes for asset price modelling. With some modifications, this paper investigate the fBm interest rate theory, and obtain a pure discount bond price and Greeks.

• Journal of the Korean Statistical Society
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• 제27권1호
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• pp.113-132
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• 1998

In this paper, we consider a minimum distance (M.D.) estimation based on kernels for U-statistics. We use Cramer-von Mises type distance function which measures the discrepancy between U-empirical distribution function(d.f.) and modeled d.f. of kernel. In the distance function, we allow various integrating measures, which can be finite, $\sigma$-finite or discrete. Then we derive the asymptotic normality and study the qualitative robustness of M. D. estimates.

• Journal of the Korean Data and Information Science Society
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• 제17권1호
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• pp.221-231
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• 2006

A chi-squared test of multivariate normality is suggested which is oriented for detecting deviations from elliptical symmetry. We derive the limiting distribution of the test statistic via a central limit theorem on empirical processes. A simulation study is conducted to study the accuracy of the limiting distribution in finite samples. Finally, we compare the power of our method with those of other popular tests of multivariate normality under a non-normal distribution.

• Journal of the Korean Data and Information Science Society
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• 제10권1호
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• pp.1-10
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• 1999

Table of the empirical quantiles for the well known Shapiro-Francia W' goodness of fit statistic is produced which is more accurate than the existing ones. Prediction equation for the quantiles of W' statistic for sample sizes 30 or more we developed. The process of computing the expected values for the standard normal variate is discussed. This work is intended to make the Shapiro-Francia W' statistic more accessible to the practitioner.