• Structural Engineering and Mechanics
• /
• v.35 no.6
• /
• pp.773-789
• /
• 2010

It is well known that the analytical vibration characteristic of a cracked beam depends largely on the crack model. In the forward analysis, an improved and simplified approach in modeling discrete open cracks in beams is presented. The effective length of the crack zone on both sides of a crack with stiffness reduction is formulated in terms of the crack depth. Both free and forced vibrations of cracked beams are studied in this paper and the results from the proposed modified crack model and other existing models are compared. The modified crack model gives very accurate predictions in the modal frequencies and time responses of the beams particularly with overlaps in the effective lengths with reduced stiffness. In the inverse analysis, the response sensitivity with respect to damage parameters (the location and depth of crack, etc.) is derived. And the dynamic response sensitivity is used to update the damage parameters. The identified results from both numerical simulations and experiment work illustrate the effectiveness of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.10
• /
• pp.3482-3497
• /
• 2021

Artificial intelligence has emerged as the core of the 4th industrial revolution, and large amounts of data processing, such as big data technology and rapid data analysis, are inevitable. The most fundamental and universal data interpretation technique is an analysis of information through regression, which is also the basis of machine learning. Ridge regression is a technique of regression that decreases sensitivity to unique or outlier information. The time-consuming calculation portion of the matrix computation, however, basically includes the introduction of an inverse matrix. As the size of the matrix expands, the matrix solution method becomes a major challenge. In this paper, a new algorithm is introduced to enhance the speed of ridge regression estimator calculation through series expansion and computation recycle without adopting an inverse matrix in the calculation process or other factorization methods. In addition, the performances of the proposed algorithm and the existing algorithm were compared according to the matrix size. Overall, excellent speed-up of the proposed algorithm with good accuracy was demonstrated.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.7 no.4
• /
• pp.690-696
• /
• 2006

This study applies the methods proposed in this issue[1] to the 11 rainfall gauging stations of the Pyongchang area. Also, this study analyzes the error range of each interpolation method, and considers spatial distribution according to the number of gauging station. As the results, the linear programming methods shows the best minimum error. However, this method might be difficult to apply in the field because of need for programming. Comparatively, the inverse distance method shows more simple and accurate results than the linear programming one. The result of this study could contribute to the increase of accuracy for the filling of missing rainfall data.

• Wind and Structures
• /
• v.11 no.1
• /
• pp.19-33
• /
• 2008

This research investigates the adaptive input estimation method applied to the multilayer shearing stress structure. This method is to estimate the values of wind load inputs by analyzing the active reaction of the system. The Kalman filter without the input term and the adaptive weighted recursive least square estimator are two main portions of this method. The innovation vector can be produced by the Kalman filter, and be applied to the adaptive weighted recursive least square estimator to estimate the wind load input over time. This combined method can effectively estimate the wind loads to the structure system to enhance the reliability of the system active performance analysis. The forms of the simulated inputs (loads) in this paper include the periodic sinusoidal wave, the decaying exponent, the random combination of the sinusoidal wave and the decaying exponent, etc. The active reaction computed plus the simulation error is regard as the simulated measurement and is applied to the input estimation algorithm to implement the numerical simulation of the inverse input estimation process. The availability and the precision of the input estimation method proposed in this research can be verified by comparing the actual value and the one obtained by numerical simulation.

• Journal of Magnetics
• /
• v.21 no.4
• /
• pp.561-569
• /
• 2016

Although pretty methods have been proposed to reduce torque ripple, they generally suffer from the decreased torque density. This paper will investigate the spoke-type interior permanent magnet (IPM) machine with shaping methods, including the sinusoidal (SIN), the inverse cosine (ICS), the sinusoidal with third harmonic (SIN+3rd), and the inverse cosine with third harmonic (ICS+3rd). In order to obtain low torque ripple and high torque density, the shaping method applied in rotor and stator at the same time, termed as the dual-shaping method, is proposed. This method is analytically derived and further confirmed by finite element method (FEM). It turns out that the ICS and ICS+3rd shaping methods are more suitable for outer rotors, while the SIN and the SIN+3rd shaping method should be used in inner stators. The original machine, the singular shaped machines and the dual-shaped machines on electromagnetic performances are compared for evaluation. The results verify that the dual-shaping method can improve torque density, whilst reducing torque ripple.

• Journal of Korean Society of Forest Science
• /
• v.87 no.3
• /
• pp.334-340
• /
• 1998

This research was conducted to identify plant regulatory regions by gene tagging method. A promoterless GUS coding sequence was introduced to Populus nigra ${\times}$ P. maximowiczii via Agrobacterium strains(LBA4404/EHA101), and putative transgenic poplars were selected by culturing on medium containing G418($60mg/{\ell}$) and by GUS assay. Among them one positive plant was to amplify the native sequences flanking to the introduced GUS gene in plant genome by inverse PCR method and from this 730 by DNA product was obtained. After subcloning and sequencing, it has 88% homology to the Eucalyptus gunnii CAD(cinnamyl alcohol dehydrogenase) gene. The GUS gene fused with the putative promoter reinserted into poplar leaves by particle bombardment method to test the funtional promoter activity. Upon staining with X-gluc, many blue spots appeared on the leaf segments bombarded by the chimeric gene 2-3 days, thus the isolated DNA fragment contain some possible coding region as well as a putative regulatory sequences of poplar CAD gene.

• Communications for Statistical Applications and Methods
• /
• v.10 no.2
• /
• pp.423-432
• /
• 2003

The data observed at different positions are called the estimate of interested variable at new observation point on the Kriging utilize the space estimate technique, in which case there is correlation spatially. In this paper we provide the estimate for Variogram and Kriging methods as a field of kriging theory and dealt with actually measured data. And at the same time we forecast the amount of ozone that was not measured at this point by Kriging method and compared Ordinary Kriging method with Inverse Distance Kriging method.

• The Korean Journal of Applied Statistics
• /
• v.36 no.4
• /
• pp.323-335
• /
• 2023

In causal analysis of high dimensional data, it is important to reduce the dimension of covariates and transform them appropriately to control confounders that affect treatment and potential outcomes. The augmented inverse probability weighting (AIPW) method is mainly used for estimation of average treatment effect (ATE). AIPW estimator can be obtained by using estimated propensity score and outcome model. ATE estimator can be inconsistent or have large asymptotic variance when using estimated propensity score and outcome model obtained by parametric methods that includes all covariates, especially for high dimensional data. For this reason, an ATE estimation using an appropriate dimension reduction method and semiparametric model for high dimensional data is attracting attention. Semiparametric method or sparse sufficient dimensionality reduction method can be uesd for dimension reduction for the estimation of propensity score and outcome model. Recently, another method has been proposed that does not use propensity score and outcome regression. After reducing dimension of covariates, ATE estimation can be performed using matching. Among the studies on ATE estimation methods for high dimensional data, four recently proposed studies will be introduced, and how to interpret the estimated ATE will be discussed.

• Korean Journal of Remote Sensing
• /
• v.37 no.1
• /
• pp.97-110
• /
• 2021

Fog can cause large-scale human and economic damages, including traffic systems and agriculture. So, Korea Meteorological Administration is operating about 290 visibility meters to improve the observation level of fog. However, it is still insufficient to detect very localized fog. In this study, high-resolution grid-type visibility data were retrieved from irregularly distributed visibility data across the country. To this end, three objective analysis techniques (Inverse Distance Weighting (IDW), Ordinary Kriging (OK) and Universal Kriging (UK)) were used. To find the best method and parameters, sensitivity test was performed for the effective radius, power parameter and variogram model that affect the level of objective analysis. Also, the effect of data distribution characteristics (level of normality) on the performance level of objective analysis was evaluated. IDW showed a relatively high level of objective analysis in terms of bias, RMSE and correlation, and the performance is inversely proportional to the effective radius and power parameter. However, the two Krigings showed relatively low level of objective analysis, in particular, greatly weakened the variability of the variables, although the level of output was different depending on the variogram model used. As the level of objective analysis is greatly influenced by the distribution characteristics of data, power, and models used, care should be taken when selecting objective analysis techniques and parameters.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.3 no.2
• /
• pp.48-62
• /
• 1985

A method for the free network adjustment is proposed, based on the application of generalized inverse matrix (g-inverse). If the network adjustment is executed according to the solution with parameters, especially when all coordinates are considered as parameters to keep unity strength, the matrix of normal equation will be singular. This paper discusses the problem of singular matrix and the analysis of accuracy between conventional method and the free network adjustment of trilateration. In case of the adjustment, the RMS errors of adjusted X, Y coordinates are increased to 35.6% in a polygon, central-point figure, and 50.5% in a quadrilateral. In the elements of error ellipse, the RMS errors are decreased by $\pm$24.5% (a) and $\pm$5.0 % (b) in the polygon, $\pm$42.6% (a) and $\pm$49.2% (b) in the quadrilateral. Introduction of free network adjustment, therefore, could be applied to improvement of relative accuracy in the horizontal positioning.