• Environmental Engineering Research
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• v.11 no.4
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• pp.201-207
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• 2006

A simple empirical model with good quantitative prediction of inter-particle and intra-particle distance in a cake layer with respect to ionic strength was developed. The model is an inverse length scale with functions of interaction energy and hydrodynamic factor and it explains that the inter-particle and intra-particle distance in a cake is directly related to the effective size of particles. Particle compressibility with respect to ionic strength was also predicted by the model. The model corroborated very well with experimental results of polystyrene microsphere latex particles microfiltation in a dead end operation. From the results of the model, specific cake resistance could be controlled by the same variables affecting the height of particle energy barrier described by the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory.

• Journal of Biomedical Engineering Research
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• v.43 no.2
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• pp.71-80
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• 2022

The interaction between dual-ligand decorated particle-based delivery system and target cell under shear flow is predicted using probability model developed. We assumed the two kinds of ligand are decorated on the surface of the particle with 10% length difference. Fixed with other biophysical parameters, a study on the particle-cell interaction for the different non-specific interaction parameter is performed. To induce the firm adhesion, short ligand-receptor should be engaged. Also, it is shown that the rational design of ligand-receptor interaction, including receptor number, specific interaction parameter, kinds of ligand-receptor, etc., should be considered.

• The Journal of Korea Robotics Society
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• v.8 no.2
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• pp.104-115
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• 2013

For natural human-robot interaction, we need to know location and shape of facial feature in real environment. In order to track facial feature robustly, we can use the method combining particle filter and active appearance model. However, processing speed of this method is too slow. In this paper, we propose two ideas to improve efficiency of this method. The first idea is changing the number of particles situationally. And the second idea is switching the prediction model situationally. Experimental results is presented to show that the proposed method is about three times faster than the method combining particle filter and active appearance model, whereas the performance of the proposed method is maintained.

• Journal of Ocean Engineering and Technology
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• v.27 no.2
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• pp.53-58
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• 2013

Recently, some fluid-structure interaction (FSI) problems involving the fluid impact loads interacting with structures, such as sloshing, slamming, green-water, etc., have been considered, especially in the ocean engineering field. The governing equations for both an elastic solid model and flow model were originally derived from similar continuum mechanics principles. In this study, an elastic model based on a particle method, the MPS method, was developed for simulating the FSI problems. The developed model was first applied to a simple cantilever deflection problem for verification. Then, the model was coupled with the fluid flow model, the PNU (Pusan National University modified)-MPS method, and applied to the numerical investigation of the coupling effects between a cantilever and a mass of water, which has variable density, free-falling to the end of the cantilever.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.186-192
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• 2009

In this paper, we represent the recognition method for human frontal upper body pose. In HCI(Human Computer Interaction) and HRI(Human Robot Interaction) when a interaction is established the human has usually frontal direction to the robot or computer and use hand gestures then we decide to focus on human frontal upper-body pose, The two main difficulties are firstly human pose is consist of many parts which cause high DOF(Degree Of Freedom) then the modeling of human pose is difficult. Secondly the matching between image features and modeling information is difficult. Then using Pictorial Model we model the human main poses which are mainly took the space of frontal upper-body poses and we recognize the main poses by making main pose database. using determined main pose we used the model parameters for particle filter which predicts the posterior distribution for pose parameters and can determine more specific pose by updating model parameters from the particle having the maximum likelihood. Therefore based on recognizing main poses and tracking the specific pose we recognize the human frontal upper body poses.

• Journal of Biomedical Engineering Research
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• v.43 no.2
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• pp.94-101
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• 2022

Recent advancement of micro/nano technology enables the development of diverse micro/nano particle-based delivery systems. Due to the multi-functionality and engineerability, particle-based delivery system are expected to be a promising method for delivery to the target cell. Since the particle-based delivery system should be delivered to the various kinds of target cell, including the cardiovascular system, cancer cell etc., it is frequently decorated with multiple kinds of targeting molecule(s) to induce specific interaction to the target cell. The surface decorated molecules interact with the cell surface expressed molecule(s) to specifically form a firm adhesion. Thus, in this study, the probability of adhesion is estimated to predict the possibility to form a firm adhesion for the multi-ligand decorated particle-based delivery system.

• Journal of the Korean Society of Visualization
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• v.15 no.1
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• pp.32-40
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• 2017

Interaction between fluid and a rigid object is frequently observed in everyday life. However, it is difficult to simulate their interaction as the medium and the object have different representations. One of the challenging issues arises especially in handling deformation of the object visually as well as rendering haptic feedback. In this paper, we propose a real-time simulation technique for multimodal interaction between particle-based fluids and soluble solids. We have developed the dissolution behavior model of solids, which is discretized based on the idea of smoothed particle hydrodynamics, and the changes in physical properties accompanying dissolution is immediately reflected to the object. The user is allowed to intervene in the simulation environment anytime by manipulating the solid object, where both visual and haptic feedback are delivered to the user on the fly. For immersive visualization, we also adopt the screen space fluid rendering technique which can balance realism and performance.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.2
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• pp.639-647
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• 2019

A realistic numerical simulation technology using a Lagrangian Fluid-Structure Interaction (FSI) model was combined with a fracture algorithm to predict the fluid-ice-structure interaction. The failure of ice was modeled as the tensile fracture of elastic material by applying a novel FSI model based on the Moving Particle Semi-implicit (MPS) method. To verify the developed fracture algorithm, a series of numerical simulations for 3-point bending tests with an ice beam were performed and compared with the experiments carried out in an ice room. For application of the developed FSI model, a dropping water droplet hitting a cantilever ice beam was simulated with and without the fracture algorithm. The simulation showed that the effects of fracture which can occur in the process of a FSI simulation can be studied.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2160-2164
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• 2007

In this study, the mechanism of enhanced thermal conductivity is elucidated on the bases of both electric double layer (EDL) and kinetic theory. A novel expression for the thermal conductivity of nanofluids is proposed and verified by applying to $Al_2O_3$ nanofluids with regard to various temperatures, volume fractions and particle sizes. In dilute nanofluids, the effects of Brownian motion and particle interaction on enhancing the thermal conductivity of nanofluids are quite comparable while the effect of particle interaction due to EDL is more prominent in dense nanofluids. The model presented in this paper shows that particle interaction due to the electrical double layer is the most responsible for the enhancement of thermal conductivity of nanofluids.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.4
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• pp.653-662
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• 2010

This study investigates the effect of particle size on the detergency of particulate soil using an $\alpha-Fe_2O_3$ particle as the model. Monodispersed spherical $\alpha-Fe_2O_3$ particles were prepared by the hydrothermal aging of an acidic $FeCl_3$ and HCl solution. The $\xi$-potential of PET fiber was measured by the streaming potential method. The potential energy of interaction between the particle and fiber was calculated using the heterocoagulation theory for a sphere-plate model. The $\xi$-potential of PET fiber and potential energy of interaction between particles and fiber increased with a decreasing particle size in a DBS solution. However, in the nonionic surfactant solution, the $\xi$-potential signs of PET fiber and $\alpha-Fe_2O_3$ particles were (-) and (+), respectively; there was no repulsive power between the particles and substrate. The adhesion of particles to the fabric increased with increasing particle size in the anionic surfactant solution and their removal from the fabric increased with a decreasing particle size. The adhesion of particles to the fabric and their removal from the fabric was biphasic with a maximum and minimum at 0.1% concentration of the surfactant solution. In the nonionic surfactant solution the adhesion of particles to fabric and their removal from the fabric were greater than the ones in the anionic surfactant DBS solution.