• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1334-1337
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• 2004

This paper presents a novel method to speed up neural network (NN) based face detection systems. NN-based face detection can be viewed as a classification and search problem. The proposed method formulates the search problem as an integer nonlinear optimization problem (INLP) and expands the basic particle swarm optimization (PSO) to solve it. PSO works with a population of particles, each representing a subwindow in an input image. The subwindows are evaluated by how well they match a NN-based face filter. A face is indicated when the filter response of the best particle is above a given threshold. To achieve better performance, the influence of PSO parameter settings on the search performance was investigated. Experiments show that with fine-adjusted parameters, the proposed method leads to a speedup of 94 on 320${\times}$240 images compared to the traditional exhaustive search method.

• Elastomers and Composites
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• v.53 no.4
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• pp.207-212
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• 2018

Taylor rod impact tests have been the subject of many theoretical and experimental investigations. This paper discusses the numerical methods for simulating the Taylor impact test, which is widely used to obtain constitutive equations and failure conditions under high-velocity collisions of materials. With this in mind, a particle-based MPM (material point method) for linear viscoelastic solid materials was implemented, and MPM simulations for viscoelastic deformation behavior were numerically verified and confirmed by comparing the MPM and FEM results. In addition, this modeling and numerical approach could be extended to more complex viscoelastic models for basic understanding and to analyze the deformation and fracture behavior of more complicated viscoelastic material systems.

• Journal of Ocean Engineering and Technology
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• v.31 no.6
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• pp.388-396
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• 2017

A Lagrangian approach based computational fluid dynamics (CFD) was used to simulate large and/or sharp deformations and fragmentations of interfaces, including free surfaces, through tracing each particle with physical quantities. According to the concept of the particle-based CFD method, it is possible to apply it to both fluid particles and solid particles such as sand, gravel, and rock. However, the presence of more than two different phases in the same domain can make it complicated to calculate the interaction between different phases. In order to solve multiphase problems, particle interaction models for multiphase problems, including surface tension, buoyancy-correction, and interface boundary condition models, were newly adopted into the moving particle semi-implicit (MPS) method. The newly developed MPS method was used to simulate a typical validation problem involving dam breaking. Because the soil and other particles, excluding the water, may have different viscosities, various viscosity coefficients were applied in the simulations for validation. The newly developed and validated MPS method was used to simulate the mobile beds induced by broken dam flows. The effects of the viscosity on soil particles were also investigated.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.267-275
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• 2013

EKF has been widely used for GPS/INS integration as standard method but EKF has one well-known drawback. if the errors are not within the bounded region, the filter may be divergent. The particle filter has the advantage of the nonlinear and non-gaussian system. This paper proposes a method for compensating the GPS position errors based on the particle filter and presents loosely-coupled GPS/INS integration using proposed algorithm. We used GPS position pattern with particle filter and added attitude kalman filter for improving attitude accuracy. To verify the performance, the proposed method is compared with high cost GPS as reference. In the experimental result, we verified that the accuracy and robust were well improved by the proposed method filter effectively and robustness than by original loosely-coupled integration when vehicle turns at corner.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4987-5005
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• 2017

This paper introduces a new method to solve Similarity Recognition for Cloth Products, which is based on Fuzzy logic and Particle swarm optimization algorithm. For convenience, it is called the SRCPFP method hereafter. In this paper, the SRCPFP method combines Fuzzy Logic (FL) and Particle Swarm Optimization (PSO) algorithm to solve similarity recognition for cloth products. First, it establishes three features, length, thickness, and temperature resistance, respectively, for each cloth product. Subsequently, these three features are engaged to construct a Fuzzy Inference System (FIS) which can find out the similarity between a query cloth and each sampling cloth in the cloth database D. At the same time, the FIS integrated with the PSO algorithm can effectively search for near optimal parameters of membership functions in eight fuzzy rules of the FIS for the above similarities. Finally, experimental results represent that the SRCPFP method can realize a satisfying recognition performance and outperform other well-known methods for similarity recognition under considerations here.

• Proceedings of KOSOMES biannual meeting
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• 2017.11a
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• pp.14-14
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• 2017

• Journal of the Korean Society of Safety
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• v.13 no.4
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• pp.3-8
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• 1998

The vortex particle method, which includes viscous effects, consists of diffusion of boundary vorticity and creation of the vortex particles, convection, particle strength exchange, and particle redistribution. Accuracy of the boundary element method is very important since it creates the particles around the body at every time step. A boundary element method based on source panel was investigated as part of computation of unsteady separated flows by rising the vortex particle method. The potential flows were computed around a circular cylinder and a square cylinder. The results around the circular cylinder were compared with the exact solution, and the distribution of vorticity, in particular near the sharp comers of the square cylinder, is scrutinized for different number of panels.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.09a
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• pp.1090-1094
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• 2009

Many problems in geotechnical engineering such as slop failure, debris flow, ground heaving due to embankment, and lateral flow caused by liquefaction are related to large deformation rather than small deformation. Traditional numerical methods such as finite element and finite difference methods have a difficulty to solve such large deformations because they use grids. A particle method was developed for fluid dynamics. The particle method can solve large deformation problems because it uses particles to discretize differential equations. It can also include soil constitutive model and thus solve soil behavior on various boundary conditions. In this study, a particle method, which is based on particles rather than grids, is introduced and used to simulate large deformation including soil failure. The developed method can be applied for various large deformation problems in geotechnical engineering because it incorporates soil constitutive models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.710-726
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• 2018

This paper presents an extended particle filter to increase the accuracy and decrease the computation load of vehicle tracking. Particle filter has been the subject of extensive interest in video-based tracking which is capable of solving nonlinear and non-Gaussian problems. However, there still exist problems such as preventing unnecessary particle consumption, reducing the computational burden, and increasing the accuracy. We aim to increase the accuracy without an increase in computation load. In proposed method, we calculate the direction angle of the target vehicle. The angular difference between the direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted, based on their angular difference. Particles with angular difference greater than a threshold is eliminated and the remaining are stored with greater weights in order to increase their probability for state estimation. Threshold value is very critical for performance. Thus, instead of having a constant threshold value, proposed algorithm updates it online. The first advantage of our algorithm is that it prevents the system from failures caused by insufficient amount of particles. Second advantage is to reduce the risk of using unnecessary number of particles in tracking which causes computation load. Proposed algorithm is compared against camshift, direction-based particle filter and condensation algorithms. Results show that the proposed algorithm outperforms the other methods in terms of accuracy, tracking duration and particle consumption.

• Particle and aerosol research
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• v.5 no.1
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• pp.17-27
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• 2009

Particle deposition on a semiconductor wafer larger than 100 mm was studied experimentally and numerically. Particularly the electrostatic effect on particle deposition velocity was investigated. The experimental apparatus consisted of a particle generation system, a particle deposition chamber and a wafer surface scanner. Experimental data of particle deposition velocity were obtained for a semiconductor wafer of 200 mm diameter with the applied voltage of 5,000 V and PSL particles of the sizes between 83 and 495 nm. The experimental data of particle deposition velocity were compared with the present numerical results and the existing experimental data for a 100 mm wafer by Ye et al. (1991) and Opiolka et al. (1994). The present numerical method took into consideration the particle transport mechanisms of convection, Brownian diffusion, gravitational settling and electrostatic attraction in an Eulerian frame of reference. Based on the comparison of the present experimental and numerical results with the existing experimental results the present experimental method for a 200 mm semiconductor wafer was found to be able to present reasonable data.