• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.1
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• pp.117-124
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• 2009

The p-convergent boundary element method has been proposed to analyze two-dimensional potential problem on the basis of high order Legendre shape functions that have different property comparing with the shape functions in conventional boundary element method. The location of nodes corresponding to high order shape function are not defined along the boundary, called by nodeless node, similar to the p-convergent finite element method. As the order of shape function increases, the collocation point method is used to solve linear simultaneous equations. The collocation patterns of p-convergent boundary element method consist of non-symmetric hierarchial or symmetric non-hierarchical. As the order of shape function increases, the number of collocation point increases. The singular integral that appears in p-convergent boundary element has been calculated by special numeric quadrature technique and semi-analytical integration technique. The L-shape domain problem including singularity in the vicinity of reentrant comer is analyzed and the numerical results show that the relative error is smaller than $10^{-2}%$ range as compared with other results in literatures. In case of same condition, the symmetric p-collocation point pattern shows high accuracy of solution.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.2
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• pp.79-86
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• 2019

For decades, in-memory data structures have been designed for DRAM-based main memory that provides symmetric read/write performances and has no limited write endurance. However, such data structures provide sub-optimal performance for NVM as it has different characteristics to DRAM. With this motivation, we rethink a conventional red-black tree in terms of its efficacy under NVM settings. The original red-black tree constantly rebalances sub-trees so as to export fast access time over dataset, but it inevitably increases the write traffic, adversely affecting the performance for NVM with a long write latency and limited endurance. To resolve this problem, we present a variant of the red-black tree called a hierarchical balanced binary search tree. The proposed structure maintains multiple keys in a single node so as to amortize the rebalancing cost. The performance study reveals that the proposed hierarchical binary search tree effectively reduces the write traffic by effectively reaping the high capacity of NVM.

• Steel and Composite Structures
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• v.49 no.4
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• pp.431-440
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• 2023

The functionally graded (FG) porous plates are usually characterized by the non-symmetric elastic modulus distribution through the thickness so that the plate neutral surface does not coincide with the mid-surface. Nevertheless, the conventional analysis models were mostly based on the plate mid-surface so that the accuracy of resulting numerical results is questionable. In this context, this paper presents the neutral surface-based static and free vibration analysis of FG porous plates and investigates the differences between the mid- and neutral surface-based analysis models. The neutral surface-based numerical method is formulated using the (3,3,2) hierarchical model and approximated by the last introduced natural element method (NEM). The volume fractions of metal and ceramic are expressed by the power-law function and the cosine-type porosity distributions are considered. The proposed numerical method is demonstrated through the benchmark experiment, and the differences between two analysis models are parametrically investigated with respect to the thickness-wise material and porosity distributions. It is found from the numerical results that the difference cannot be negligible when the material and porosity distributions are remarkably biased in the thickness direction.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.11
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• pp.1575-1589
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• 2017

Objective: This study was conducted to determine molecular structures related to carbohydrates and lipid in alfalfa hay cut at early bud, late bud and early flower and in the afternoon and next morning using Fourier transform infrared spectroscopy (FT/IR) and to determine their relationship with alfalfa hay nutrient profile and availability in ruminants. Methods: Chemical composition analysis, carbohydrate fractionation, in situ ruminal degradability, and DVE/OEB model were used to measure nutrient profile and availability of alfalfa hay. Univariate analysis, hierarchical cluster analysis (CLA) and principal components analysis (PCA) were conducted to identify FT/IR spectra differences. Results: The FT/IR non-structural carbohydrate (NSCHO) to total carbohydrates and NSCHO to structural carbohydrate ratios decreased (p<0.05), while lignin to NSCHO and lipid CH3 symmetric to CH2 symmetric ratios increased with advancing maturity (p<0.05). The FT/IR spectra related to structural carbohydrates, lignin and lipids were distinguished for alfalfa hay at three maturities by PCA and CLA, while FT/IR molecular structures related to carbohydrates and lipids were similar between alfalfa hay cut in the morning and afternoon when analyzed by PCA and CLA analysis. Positive correlations were found for FT/IR NSCHO to total carbohydrate and NSCHO to structural carbohydrate ratios with non-fiber carbohydrate (by wet chemistry), ruminal fast and intermediately degradable carbohydrate fractions and total ruminal degradability of carbohydrates and predicted intestinal nutrient availability in dairy cows ($r{\geq}0.60$; p<0.05) whereas FT/IR lignin to NSCHO and CH3 to CH2 symmetric stretching ratio had negative correlation with predicted ruminal and intestinal nutrient availability of alfalfa hay in dairy cows ($r{\geq}-0.60$; p<0.05). Conclusion: FT/IR carbohydrate and lipid molecular structures in alfalfa hay changed with advancing maturity from early bud to early flower, but not during the day, and these molecular structures correlated with predicted nutrient supply of alfalfa hay in ruminants.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.729-734
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• 2012

Clustering analysis has been widely used in numerous applications like pattern recognition, data analysis, intrusion detection, image processing, bioinformatics and so on. Much of previous work has been based on the numeric data only. However, symbolic data analysis has emerged to deal with variables that can have intervals, histograms, and even functions as values. In this paper, we propose a non symmetric proximity based clustering approach for symbolic objects. A method for clustering symbolic patterns based on the average similarity value(ASV) is explored. The results of the proposed clustering method differ from those of the existing methods and the results are very encouraging.