• Atmosphere
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• v.32 no.4
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• pp.341-351
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• 2022

Recently, interest in the possibility of a washout effect using artificial rain enhancement technology to reduce high-concentration fine dust is growing. Therefore, in this study, the reduction rate of PM₁₀ concentration according to the amount of artificial rain enhancement was calculated during Asian Dust event which occurred over the Korean Peninsula on March 29, 2021 using air quality model [i.e., Community Multiscale Air Quality (CMAQ)] combined with the mesoscale model for artificial rain enhancement (i.e., WRF-MMS). According to WRF-MMS, the washout effect lasted 5 hours, and the maximum precipitation rate was calculated to be 1.5 mm hr^-1. According the CMAQ results, the PM₁₀ reduction rate was up to 22%, and the affected area was calculated to be 6.4 times greater than that of the artificial rain enhancement area. Even if the maximum amount of precipitation per hour is lowered to 0.8 mm hr^-1 (about 50% level), the PM₁₀ reduction rate appears to be up to 16%. In other words, it is believed that this technique can be used as a direct method for reducing high-concentration fine dust even when the artificial rain enhancement effect is weak.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1759-1772
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• 2023

Chinese named entity recognition (NER) is a challenging work that seeks to find, recognize and classify various types of information elements in unstructured text. Due to the Chinese text has no natural boundary like the spaces in the English text, Chinese named entity identification is much more difficult. At present, most deep learning based NER models are developed using a bidirectional long short-term memory network (BiLSTM), yet the performance still has some space to improve. To further improve their performance in Chinese NER tasks, we propose a new NER model, IDCNN-BiLSTM-Highway, which is a combination of the BiLSTM, the iterated dilated convolutional neural network (IDCNN) and the highway network. In our model, IDCNN is used to achieve multiscale context aggregation from a long sequence of words. Highway network is used to effectively connect different layers of networks, allowing information to pass through network layers smoothly without attenuation. Finally, the global optimum tag result is obtained by introducing conditional random field (CRF). The experimental results show that compared with other popular deep learning-based NER models, our model shows superior performance on two Chinese NER data sets: Resume and Yidu-S4k, The F1-scores are 94.98 and 77.59, respectively.

• Interaction and multiscale mechanics
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• v.1 no.1
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• pp.143-156
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• 2008

Elliptical tubes may buckle in an elastic local buckling failure mode under uniform compression. Previous analyses of the local buckling of these members have assumed that the cross-section is hollow, but it is well-known that the local buckling capacity of thin-walled closed sections may be increased by filling them with a rigid medium such as concrete. In many applications, the medium many not necessarily be rigid, and the infill can be considered to be an elastic material which interacts with the buckling of the elliptical tube that surrounds it. This paper uses an energy-based technique to model the buckling of a thin-walled elliptical tube containing an elastic infill, which elucidates the physics of the buckling phenomenon from an engineering mechanics basis, in deference to a less generic finite element approach to the buckling problem. It makes use of the observation that the local buckling in an elliptical tube is localised with respect to the contour of the ellipse in its cross-section, with the localisation being at the region of lowest curvature. The formulation in the paper is algebraic and it leads to solutions that can be determined by implementing simple numerical solution techniques. A further extension of this formulation to a stiffness approach with multiple degrees of buckling freedom is described, and it is shown that using the simple one degree of freedom representation is sufficiently accurate for determining the elastic local buckling coefficient.

• Interaction and multiscale mechanics
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• v.2 no.3
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• pp.223-233
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• 2009

This paper presents a new nonlocal stress variational principle approach for the transverse free vibration of an Euler-Bernoulli cantilever nanobeam with an initial axial tension at its free end. The effects of a nanoscale at molecular level unavailable in classical mechanics are investigated and discussed. A sixth-order partial differential governing equation for transverse free vibration is derived via variational principle with nonlocal elastic stress field theory. Analytical solutions for natural frequencies and transverse vibration modes are determined by applying a numerical analysis. Examples conclude that nonlocal stress effect tends to significantly increase stiffness and natural frequencies of a nanobeam. The relationship between natural frequency and nanoscale is also presented and its significance on stiffness enhancement with respect to the classical elasticity theory is discussed in detail. The effect of an initial axial tension, which also tends to enhance the nanobeam stiffness, is also concluded. The model and approach show potential extension to studies in carbon nanotube and the new result is useful for future comparison.

• Smart Structures and Systems
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• v.13 no.4
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• pp.501-515
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• 2014

This paper presents a linear computational homogenization framework to evaluate the effective (or generalized) electromechanical coupling coefficient (EMCC) of adaptive structures with piezoelectric structural fiber (PSF) composite elements. The PSF consists of a silicon carbide (SiC) or carbon core fiber as reinforcement to a fragile piezo-ceramic shell. For the micro-scale analysis, a micromechanics model based on the variational asymptotic method for unit cell homogenization (VAMUCH) is used to evaluate the overall electromechanical properties of the PSF composites. At the macro-scale, a finite element (FE) analysis with the commercial FE code ABAQUS is performed to evaluate the effective EMCC for structures with the PSF composite patches. The EMCC is postprocessed from free-vibrations analysis under short-circuit (SC) and open-circuit (OC) electrodes of the patches. This linear two-scale computational framework may be useful for the optimal design of active structure multi-functional composites which can be used for multi-functional applications such as structural health monitoring, power harvest, vibration sensing and control, damping, and shape control through anisotropic actuation.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.1
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• pp.49-62
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• 2005

Lake Paldang is a main resource of drinking water for 20 million people in the greater Seoul area. Dry deposition amounts of nitrogen and sulfur were estimated for three typical days in each season over the watershed of Lake Paldang. Models- 3/CMAQ (Community Multiscale Air Quality) and MM5 (Mesoscale Model) were used to predict air quality and meteorology, respectively. Aerosols as well as gaseous pollutants were considered. Nitrogen was mainly deposited in the form of HNO, while most of sulfur was deposited in the form of SO$_2$. Contribution of secondary pollutants was the largest in fall since they were transported from the greater Seoul area. However, contribution of secondarily-formed particulate pollutants to the nitrogen deposition was the largest in winter because semi-volatile ammonium nitrate favors lower temperature. Annual deposition amounts of nitrogen and sulfur were 37% and 26% of their emission amounts, respectively, over the watershed of Lake Paldang. Higher value of the nitrogen deposition showed a more influence of pollutants emitted in the greater Seoul area.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.4
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• pp.413-419
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• 2011

The nano-size hoenycomb structures have the higher ratio of the surface to the volume than macro-size honeycomb structures, and they can maximize the functionality of the electrical and chemical catalyst. The mechanical behaviors of the nano-sized structures are different from ones of the macro-size structure, and it is caused by the surface effect. This surface effect can be investigated by the atomistic simulation; however, the prediction of mechanical behaviors of the nano-sized honeycombs are practically impossible due to excessive computational resources and computation time. In this paper, by combining the bridging method considering the surface stress elasticity model with homogenization method, the mechanical behaviors of the nano-sized honeycombs are predicted efficiently.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2004.04a
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• pp.67-70
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• 2004

An investigation was performed to study the impact damage of the laminated composite plates caused by a low- velocity foreign object with multi-scale modeling based on the concepts of Direct Numerical Simulation (DNS)[4]. In the micro-scale part, we discretize the composite plates through separate modeling of fiber and matrix for the local microscopic analysis. A micro-scalemodel was developed for predicting the initiation of the damage and the extent of the final damage as a function of material properties, laminate configuration and the impactor's mass, etc. Anda macro-scale model was developed for description of global dynamic behavior. The connection betweenmicroscopic and macroscopic is implemented by the tied interface constraints of LS-DYNA contact card. A transient dynamic finite element analysis was adopted for calculating the contact force history and the stresses and strains inside the composites during impact resulting from a point-nose impactor. The low-velocity impact events such as contact force, deformation, etc. are simulated in the macroscopic sense and the impact damages, fiber-breakage, matrix cracking and delamination etc. are examined in the microscopic sense.

• Interaction and multiscale mechanics
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• v.6 no.2
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• pp.157-172
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• 2013

This paper presented an investigation of macromolecular suspension in a grooved channel by using the dissipative particle dynamics (DPD) with finitely extensible non-linear elastic (FENE) bead spring chains model. Before studying the movement and evolution of macromolecules, the DPD method was first validated by modeling the simple fluid flow in the grooved channel. For both simple fluid flow and macromolecular suspension, the flow fields were analyzed in detail. It is found that the structure of the grooved channel with sudden contraction and expansion strongly affects the velocity distribution. As the width of the channel reduces, the horizontal velocity increases simultaneously. Vortices can also be found at the top and bottom corners behind the contraction section. For macromolecular suspension, the macromolecular chains influence velocity and density distribution rather than the temperature and pressure. Macromolecules tend to drag simple fluid particles, reducing the velocity with density and velocity fluctuations. Particle trajectories and evolution of macromolecular conformation were investigated. The structure of the grooved channel with sudden contraction and expansion significantly influence the evolution of macromolecular conformation, while macromolecules display adaptivity to adjust their own conformation and angle to suit the structure so as to pass the channel smoothly.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.43-54
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• 2005

This paper proposes a novel texture segmentation method using Bayesian image segmentation method and SOM(Self Organization feature Map). Multi-scale wavelet coefficients are used as the input of SOM, and likelihood and a posterior probability for observations are obtained from trained SOMs. Texture segmentation is performed by a posterior probability from trained SOMs and MAP(Maximum A Posterior) classification. And the result of texture segmentation is improved by context information. This proposed segmentation method shows better performance than segmentation method by HMT(Hidden Markov Tree) model. The texture segmentation results by SOM and multi-sclae Bayesian image segmentation technique called HMTseg also show better performance than by HMT and HMTseg.