• Journal of the Korea Institute of Building Construction
• /
• v.8 no.6
• /
• pp.91-98
• /
• 2008

It is time-consuming and difficulty to solve the time-cost trade-off problems, as there are trade-offs between time and cost to complete the activities in construction projects and this problems do not have unique solutions. Typically, heuristic methods, mathematical models and GA models has been used to solve this problems. As heuristic methods and mathematical models are have weakness in solving the time-cost trade-off problems, GA based model has been studied widely in recent. This paper suggests the time-cost trade-off optimization algorithm using particle swarm optimization. The traditional particle swarm optimization model is modified to generate optimal tradeoffs among construction time and cost efficiently. An application example is analyzed to illustrate the use of the suggested algorithm and demonstrate its capabilities in generating optimal tradeoffs among construction time and cost. Future applications of the model are suggested in the conclusion.

• Journal of the Korean Applied Science and Technology
• /
• v.21 no.1
• /
• pp.69-75
• /
• 2004

In this study, various model composite latexes were synthesized using n-butyl acrylate and methyl methacrylate as comonomers by seeded multi-staged emulsion polymerization. Monodispersed model composite latex particles with size of 190 nm and polydispersity index of 1.05, which have various morphology including random copolymer particle, soft-core/hard-shell particle, hard-core/soft shell particle, and gradient-type copolymer particle, homopolymers particles were prepared. The designed morphology of model composite particles were confirmed.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2012.11a
• /
• pp.552-555
• /
• 2012

The main goal of this paper is to develop a robust visual tracking algorithm with particle filtering. Visual Tracking with particle filter technique is not easy task due to cluttered environment, illumination changes. To deal with these problems, we develop an efficient observation model for target tracking with particle filter. We develop a robust phase correlation combined with motion information based observation model for particle filter framework. Phase correlation provides straight-forward estimation of rigid translational motion between two images, which is based on the well-known Fourier shift property. Phase correlation has the advantage that it is not affected by any intensity or contrast differences between two images. On the other hand, motion cue is also very well known technique and widely used due to its simplicity. Therefore, we apply the phase correlation integrated with motion information in particle filter framework for robust tracking. In experimental results, we show that tracking with multiple cues based model provides more reliable performance than single cue.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.18 no.3
• /
• pp.59-65
• /
• 2019

In many industries, particle packing is adopted quite frequently. In the particle packing process, the Discrete Element Method (DEM) can analyze the multi-collision of particles efficiently. Two types of contact models are frequently used for the DEM. One is the linear spring model, which has the fastest calculation time, and the other is the Hertz-Mindlin model, which is the most frequently used contact model employing the DEM. Meanwhile, very tiny particles in the micrometer order are used in modern industries. In the micro length order, surface force is important to decreased particle size. To consider the effect of surface force in this study, we performed a simulation with the Hertz-Mindlin model and added the Johnson-Kendall-Roberts (JKR) theory depicting surface force with surface energy. In addition, three contact models were compared with several parameters. As a result, it was found that the JKR model has larger residual stress than the general contact models because of the pull-off force. We also validated that surface force can influence particle behavior if the particles are small.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2007.04a
• /
• pp.441-444
• /
• 2007

This paper presents a part of micormechanics-based elastic modeling (Lee and Pyo, 2007) of particle-reinforced composites containing slightly weakened interfaces. The Eshelby's tensor for a damaged ellipsoidal inclusion to model particles with slightly weakened interfaces is incorporated into a micormechanical formulation by Ju and Chen (1994). A damage model in accordance with the Weibull's probabilistic function is also developed to simulate the progression of weakened interface in the composites.

• 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 Fisheries and Marine Sciences Education
• /
• v.28 no.4
• /
• pp.1143-1151
• /
• 2016

To study the dispersion process and residence time of anthropogenic pollutant in Masan bay, a three-dimensional hydrodynamic model coupled to a particle tracking model, EFDC, is applied. Particle tracking model simulated the instantaneous release of particles emulating discharge from river and wastewater treatment plant to show the behaviour of pollutant in terms of water circulation and water exchange. Modelled outcomes for water circulation were in good agreement with tidal elevation and current data. The results of particle tracking model show that over half of particles released from northern Masan bay transport to out of area while the particles from Dukdong wastewater treatment plant transport to northern area. This meant pollution source from inside and outside of the northern area can affect water quality of northern Masan bay.

• Proceedings of the IEEK Conference
• /
• 2009.05a
• /
• pp.384-386
• /
• 2009

This paper introduces an effectively optimized Fuzzy model identification by means of complex and nonlinear system applying PSO algorithm. In other words, we use PSO(Particle Swarm Optimization) for identification of Fuzzy model structure and parameter. PSO is an algorithm that follows a collaborative population-based search model. Each particle of swarm flies around in a multidimensional search space looking for the optimal solution. Then, Particles adjust their position according to their own and their neighboring-particles experience. This paper identifies the premise part parameters and the consequence structures that have many effects on Fuzzy system based on PSO. In the premise parts of the rules, we use triangular. Finally we evaluate the Fuzzy model that is widely used in the standard model of gas data and sew data.

• Journal of Korean Society for Atmospheric Environment
• /
• v.20 no.1
• /
• pp.47-58
• /
• 2004

The $textsc{k}$-$\varepsilon$ algebraic stress model (KEASM) was applied to atmospheric dispersion simulation using the Lagrangian particle dispersion model and was compared with the most popular turbulence closure model in the field of atmospheric simulation, the Mellor-Yamada (MY) model. KEASM has been rarely applied to atmospheric simulation, but it includes the pressure redistribution effect of buoyancy due to heat and momentum fluxes. On the other hand, such effect is excluded from MY model. In the simulation study, the difference in the two turbulence models was reflected to both the turbulent velocity and the Lagrangian time scale. There was little difference in the vertical diffusion coefficient $\sigma$$_{z}$. However, the horizontal diffusion coefficient or calculated by KEASM was larger than that by MY model, coincided with the Pasquill-Gifford (PG) chart. The applicability of KEASM to atmospheric simulations was demonstrated by the simulations.s.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.8
• /
• pp.3791-3805
• /
• 2016

The visual attention mechanism includes 2 attention models, the bottom-up (B-U) and the top-down (T-D), the physiology of which have not yet been accurately described. In this paper, the visual attention mechanism is regarded as a Bayesian fusion process, and a visual attention model based on particle filter is proposed. Under certain particular assumed conditions, a calculation formula of Bayesian posterior probability is deduced. The visual attention fusion process based on the particle filter is realized through importance sampling, particle weight updating, and resampling, and visual attention is finally determined by the particle distribution state. The test results of multigroup images show that the calculation result of this model has better subjective and objective effects than that of other models.