• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2008.11a
• /
• pp.13-16
• /
• 2008

This paper is to present the performance data for improved direct setting method using tile bond for application of porcelain tile under 1 percent absorptance. For this purpose, improved direct setting method type 1 & 2(tile bond curing time 0, 24H) were compared with the conventional setting methods(including direct setting method and improved pressure setting method) in the sight of the adhesive stability of porcelain tile. It tested for tiles after 14, 28days under standard condition and severe conditions. The severe conditions were water immersion, heat ageing(70℃) and freeze-thaw cycle. On the basis of test results, the adhesive strength of direct setting method was lowest for the conventional setting methods. But improved direct setting method using tile bonds(A, B) came close to the result of improved pressure setting method using tile bonds.

• Structural Engineering and Mechanics
• /
• v.66 no.5
• /
• pp.649-663
• /
• 2018

The scaled boundary finite element method is extended to evaluate the dynamic stress intensity factors and T-stress with a numerical procedure based on the improved continued-fraction. The improved continued-fraction approach for the dynamic stiffness matrix is introduced to represent the inertial effect at high frequencies, which leads to numerically better conditioned matrices. After separating the singular stress term from other high order terms, the internal displacements can be obtained by numerical integration and no mesh refinement is needed around the crack tip. The condition numbers of coefficient matrix of the improved method are much smaller than that of the original method, which shows that the improved algorithm can obtain well-conditioned coefficient matrices, and the efficiency of the solution process and its stability can be significantly improved. Several numerical examples are presented to demonstrate the increased robustness and efficiency of the proposed method in both homogeneous and bimaterial crack problems.

• Structural Monitoring and Maintenance
• /
• v.5 no.2
• /
• pp.261-272
• /
• 2018

The commonly used TMD design method in the project assumes the TMD has pure linearity. However, in real engineering TMD will exhibit nonlinear behaviors. Without considering the nonlinearity of TMD, the control effect of the TMD that is designed by the linear design method, may be worse and even enlarge the structural response. In this paper, based on the previous study results of nonlinear TMD, the improved design method for engineering application is proposed. The linear design method and the improved design method are compared. Taking the best parameter obtained by the improved design method is less than or equal to 90% of that obtained by the original design method as the dividing line. The critical nonlinear coefficient, reaching which value the improved design method needs to be used, is given. Finally, numerical simulations on two engineering examples are conducted to proof the results.

• Interaction and multiscale mechanics
• /
• v.3 no.2
• /
• pp.123-143
• /
• 2010

The essential idea of the element-free Galerkin method (EFG) is that moving least-squares (MLS) approximation are used for the trial and test functions with the variational principle (weak form). By using the weighted orthogonal basis function to construct the MLS interpolants, we derive the formulae for an improved element-free Galerkin (IEFG) method for solving three-dimensional problems in linear elasticity. There are fewer coefficients in improved moving least-squares (IMLS) approximation than in MLS approximation. Also fewer nodes are selected in the entire domain with the IEFG method than is the case with the conventional EFG method. In this paper, we selected a few example problems to demonstrate the applicability of the method.

• ETRI Journal
• /
• v.45 no.3
• /
• pp.394-403
• /
• 2023

Direct tracking problem of moving noncircular sources for multiple arrays is investigated in this study. Here, we propose an improved unscented particle filter (I-UPF) direct tracking method, which combines system proportional symmetry unscented particle filter and Markov Chain Monte Carlo (MCMC) algorithm. Noncircular sources can extend the dimension of sources matrix, and the direct tracking accuracy is improved. This method uses multiple arrays to receive sources. Firstly, set up a direct tracking model through consecutive time and Doppler information. Subsequently, based on the improved unscented particle filter algorithm, the proposed tracking model is to improve the direct tracking accuracy and reduce computational complexity. Simulation results show that the proposed improved unscented particle filter algorithm for noncircular sources has enhanced tracking accuracy than Markov Chain Monte Carlo unscented particle filter algorithm, Markov Chain Monte Carlo extended Kalman particle filter, and two-step tracking method.

• Journal of information and communication convergence engineering
• /
• v.17 no.1
• /
• pp.41-48
• /
• 2019

In recent years, sentiment analysis research has become popular. The research results of sentiment analysis have achieved remarkable results in practical applications, such as in Amazon's book recommendation system and the North American movie box office evaluation system. Analyzing big data based on user preferences and evaluations and recommending hot-selling books and hot-rated movies to users in a targeted manner greatly improve book sales and attendance rate in movies [1, 2]. However, traditional machine learning-based sentiment analysis methods such as the Classification and Regression Tree (CART), Support Vector Machine (SVM), and k-nearest neighbor classification (kNN) had performed poorly in accuracy. In this paper, an improved kNN classification method is proposed. Through the improved method and normalizing of data, the purpose of improving accuracy is achieved. Subsequently, the three classification algorithms and the improved algorithm were compared based on experimental data. Experiments show that the improved method performs best in the kNN classification method, with an accuracy rate of 11.5% and a precision rate of 20.3%.

• Wind and Structures
• /
• v.39 no.2
• /
• pp.85-100
• /
• 2024

In light of extreme value distribution probability, an improved prediction method of the Recurrence Period Wind Speed (RPWS) is constructed considering wind direction, with the Equivalent Independent Wind Direction Number (EIWDN) introduced as a parameter variable. Firstly, taking the RPWS prediction of Beijing city as an example, the traditional Cook method is used to predict the RPWS of each wind direction based on the measured wind speed data in Beijing area. On basis of the results, the empirical formulae to determine the parameter variables are fitted to construct an improved expression of the non-exceedance probability of the RPWS. In this process, the statistical model of the optimal threshold is established, and thus the independent wind speed samples exceeding the threshold are extracted and fitted to follow the Generalized Pareto Distribution (GPD) model for analysis. In addition, the Extreme Value Type I (EVT I) distribution model is used to predict and analyze the RPWS. To verify its wide applicability, the improved method is further used in cities like Jinan, Nanjing, Wuxi, Shanghai and Shenzhen to predict and analyze the RPWS of each wind direction, and the prediction results are compared against those gained via the traditional Cook method and the whole direction. Results show that the 50-year RPWS results predicted by the improved method are basically consistent with those predicted by the traditional method, and the RPWS prediction values of most wind directions are within the envelope range of the whole wind direction prediction value. Compared with the traditional method, the improved method can readily predict the RPWS under different return periods through empirical formulae, and avoid the repeated operation process and some assumptions in the traditional Cook method, and then improve the efficiency of prediction. In addition, the improved RPWS prediction results corresponding to the GPD model are slightly larger than those of the EVT I distribution model.

• Journal of The Korean Astronomical Society
• /
• v.32 no.1
• /
• pp.65-73
• /
• 1999

In this study we present a new improved nonlinear calibration method for vector magnetograms made by the Solar Flare Telescope of BOAO. To identify Fe I 6302.5 line, we have scanned monochromatic images of the line integrated over filter passband, changing the location of the central transmission wavelength of a Lyot filter. Then we obtained a filter-convolved line profile, which is in good agreement with spectral atlas data provided by the Sacramento Peak Solar Observatory. The line profile has been used to derive calibration coefficients of longitudinal and transverse fields, employing the conventional line slope method under the weak field approximation. Our improved nonlinear calibration method has also been used to calculate theoretical Stokes polarization signals with various angles of inclination of magnetic fields. For its numerical test, we have compared input magnetic fields with the calibrated ones, which have been derived from the new improved non-linear method and the conventional method respectively. The numerical test shows that the calibrated fields obtained from the improved method are consistent with the input fields, but not with those from the conventional method. Finally, we applied our new improved method to a dipole model which characterizes a typical field configuration of a single, round sunspot. It is noted that the conventional method remarkably underestimates the transverse field component near the inner penumbra.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.12
• /
• pp.6028-6042
• /
• 2019

Since Sparse Nonnegative Matrix Factorization (SNMF) method can control the sparsity of the decomposed matrix, and then it can be adopted to control the sparsity of facial feature extraction and recognition. In order to improve the accuracy of SNMF method for facial feature recognition, new additive iterative rules based on the improved iterative step sizes are proposed to improve the SNMF method, and then the traditional multiplicative iterative rules of SNMF are transformed to additive iterative rules. Meanwhile, to further increase the sparsity of the basis matrix decomposed by the improved SNMF method, a threshold-sparse constraint is adopted to make the basis matrix to a zero-one matrix, which can further improve the accuracy of facial feature recognition. The improved SNMF method based on the additive iterative rules and threshold-sparse constraint is abbreviated as ASNMF, which is adopted to recognize the ORL and CK+ facial datasets, and achieved recognition rate of 96% and 100%, respectively. Meanwhile, from the results of the contrast experiments, it can be found that the recognition rate achieved by the ASNMF method is obviously higher than the basic NMF, traditional SNMF, convex nonnegative matrix factorization (CNMF) and Deep NMF.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2019.01a
• /
• pp.125-126
• /
• 2019

In this paper, we propose an improved kNN classification method. Through improved the mothed and normalizing the data, the purpose of improving the accuracy is achieved. Then we compared the three classification algorithms and the improved algorithm by experimental data.