• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.10
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• pp.1826-1835
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• 2007

In this paper, we present a new approach for automatic detection and tracking for multiple targets. We combine a highest probability data association(HPDA) algorithm for target detection with a particle filter for multiple target tracking. The proposed approach evaluates the probabilities of one-to-one assignments of measurement-to-track and the measurement with the highest probability is selected to be target- originated, and the measurement is used for probabilistic weight update of particle filtering. The performance of the proposed algorithm for target tracking in clutter is compared with the existing clustering algorithm and the sequential monte carlo method for probability hypothesis density(SMC PHD) algorithm for multi-target detection and tracking. Computer simulation studies demonstrate that the HPDA algorithm is robust in performing automatic detection and tracking for multiple targets even though the environment is hostile in terms of high clutter density and low target detection probability.

• 한국전산유체공학회:학술대회논문집
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• 2007.04a
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• pp.53-57
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• 2007

The quality of chaotic mixing in square cavity flow was studied numerically by CFD simulation and particle tracking technique. The chaotic mixing was generated by using time-periodic electro-osmotic flow. Finite Volume Method (FVM) was employed to get the stretching and folding field in cavity domain. With adjusting the initial condition of concentration distribution, the best values of modulation period and Peclet number which gave us good mixing performance was determined precisely. From $Poicar{\acute{e}}section$and Lyapunov exponents for characteristic trajectories we find that mixing performance also depends on modulation period. The higher value of modulation period, the better mixing performance wag achieved in this case. Furthermore, the results for tracking particle trajectories were also compared between using of Bilinear Interpolation and Higher-order scheme. The values of modulation period for obtaining best mixing effect were matched between using FVM and particle tracking techniques.

• Journal of ILASS-Korea
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• v.12 no.4
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• pp.191-197
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• 2007

This study presents in-line digital particle holography and its application to spray droplets to measure the characteristics of spray droplets. Several important parameters at the time of hologram recording such as the object distance and the region of laser beam used were verified. The correlation coefficient method with important parameters such as the reconstruction interval and the correlation interval was used for determination of the focal planes of particles. The optimal values of all these parameters are obtained by either numerical simulation of holograms or experiments. Using these optimal parameters, double pulse digital spray holograms in a short time interval were recorded with the synchronization system for the time control. The spatial positions of droplets that are used for the evaluation of the three dimensional droplet velocities can be easily located, which proves the feasibility of the digital holographic technology for measurements of several important features of spray droplets.

• Earthquakes and Structures
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• v.5 no.3
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• pp.359-378
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• 2013

The problem of identification of multi-component and (or) spatially varying earthquake support motions based on measured responses in instrumented structures is considered. The governing equations of motion are cast in the state space form and a time domain solution to the input identification problem is developed based on the Kalman and particle filtering methods. The method allows for noise in measured responses, imperfections in mathematical model for the structure, and possible nonlinear behavior of the structure. The unknown support motions are treated as hypothetical additional system states and a prior model for these motions are taken to be given in terms of white noise processes. For linear systems, the solution is developed within the Kalman filtering framework while, for nonlinear systems, the Monte Carlo simulation based particle filtering tools are employed. In the latter case, the question of controlling sampling variance based on the idea of Rao-Blackwellization is also explored. Illustrative examples include identification of multi-component and spatially varying support motions in linear/nonlinear structures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2959-2973
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• 2021

In wireless sensor and actuator networks (WSANs), the network lifetime is an important criterion to measure the performance of the WSAN system. Generally, the network lifetime is mainly affected by the energy of sensors. However, the energy of sensors is limited, and the batteries of sensors cannot be replaced and charged. So, it is crucial to make energy consumption efficient. WSAN introduces multiple actuators that can be regarded as multiple collectors to gather data from their respective surrounding sensors. But how to deploy actuators to reduce the energy consumption of sensors and increase the manageability of the network is an important challenge. This research optimizes actuators deployment by a proposed probabilistic mutation multi-layer particle swarm optimization algorithm to maximize the coverage of actuators to sensors and reduce the energy consumption of sensors. Simulation results show that this method is effective for improving the coverage rate and reducing the energy consumption.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.131-138
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• 2022

A Mobile Ad-hoc Network (MANET) is a collection of moving nodes that communicate and collaborate without relying on a pre-existing infrastructure. In this type of network, nodes can freely move in any direction. Routing in this sort of network has always been problematic because of the mobility of nodes. Most existing protocols use simple routing algorithms and criteria, while another important criterion is path selection. The existing protocols should be optimized to resolve these deficiencies. 'Particle Swarm Optimization (PSO)' is an influenced method as it resembles the social behavior of a flock of birds. Genetic algorithms (GA) are search algorithms that use natural selection and genetic principles. This paper applies these optimization models to the OLSR routing protocol and compares their performances across different metrics and varying node sizes. The experimental analysis shows that the Genetic Algorithm is better compared to PSO. The comparison was carried out with the help of the simulation tool NS2, NAM (Network Animator), and xgraph, which was used to create the graphs from the trace files.

• Nuclear Engineering and Technology
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• v.47 no.5
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• pp.546-558
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• 2015

Chord length sampling method in Monte Carlo simulations is a method used to model spherical particles with random sampling technique in a stochastic media. It has received attention due to the high calculation efficiency as well as user convenience; however, a technical issue regarding boundary effect has been noted. In this study, after analyzing the distribution characteristics of spherical particles using an explicit method, an alternative chord length sampling method is proposed. In addition, for modeling in finite media, a correction method of the boundary effect is proposed. Using the proposed method, sample probability distributions and relative errors were estimated and compared with those calculated by the explicit method. The results show that the reconstruction ability and modeling accuracy of the particle probability distribution with the proposed method were considerably high. Also, from the local packing fraction results, the proposed method can successfully solve the boundary effect problem. It is expected that the proposed method can contribute to the increasing of the modeling accuracy in stochastic media.

• Geomechanics and Engineering
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• v.10 no.4
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• pp.455-470
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• 2016

In ballasted railway tracks, ballast fouling due to finer material intrusion has been identified as a challenging issue in track maintenance works. In this research, deformation characteristics of crushed stone-sand mixtures, simulating fresh and fouled ballasts were studied from laboratory and a 3-D discrete element method (DEM) triaxial compression tests. The DEM simulation was performed using a recently developed DEM approach, named, Yet Another Dynamic Engine (YADE). First, void ratio characteristics of crushed stone-sand mixtures were studied. Then, triaxial compression tests were conducted on specimens with 80 and 50% of relative densities simulating dense and loose states respectively. Initial DEM simulations were conducted using sphere particles. As stress-strain behaviour of crushed stone-sand mixtures evaluated by sphere particles were different from laboratory specimens, in next DEM simulations, the particles were modeled by a clump particle. The clump shape was selected using shape indexes of the actual particles evaluated by an image analysis. It was observed that the packing behaviour of laboratory crushed stone-sand mixtures were matched well with the DEM simulation with clump particles. The results also showed that the strength properties of crushed stone deteriorate when they are mixed by 30% or more of sand, specially under dense state. The results also showed that clump particles give closer stress-strain behaviour to laboratory specimens than sphere particles.

• Journal of the Korea Society for Simulation
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• v.27 no.2
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• pp.83-90
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• 2018

This paper describes the method of hull shape optimization to improve the resistance performance of planing hulls when a reference hull shape and its principal dimensions are given. First, the planing hull of precedent research is adopted as the reference hull and an optimization problem is formulated by defining hull shape parameters. The search space of this research is discretized for computing cost and DPSO(Discrete binary version of Particle Swarm Optimization) method is used to solve the optimization problem. As the result of optimization, the decrease of resistance is confirmed from the comparison between the reference hull's and the modified hull's planing performance from computational results.

• Progress in Superconductivity and Cryogenics
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• v.18 no.1
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• pp.19-22
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• 2016

A Superconducting High Gradient Magnetic Separation (HGMS) system is proposed for treatment of feed-water in thermal power plant [1]. This is a method to remove the iron scale from feed-water utilizing magnetic force. One of the issues for practical use of HGMS system is to extend continuous operation period. In this study, we designed the magnetic filters by particle trajectory simulation and HGMS experiments in order to solve this problem. As a result, the quantity of magnetite captured by each filter was equalized and filter blockage was prevented. A design method of the magnetic filter was proposed which is suitable for the long-term continuous scale removal in the feed-water system of the thermal power plant.