• Electrical & Electronic Materials
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• v.8 no.6
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• pp.806-810
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• 1995

Electron swarm studies to derive electron collision cross sections of atoms and molecules from measurements of electron swarm data are reviewed. Stress is placed on those using molecular gas-rare gas mixtures.

• Journal of Electrical Engineering and Technology
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• v.11 no.5
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• pp.1404-1411
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• 2016

• Aerospace Engineering and Technology
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• v.13 no.1
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• pp.166-173
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• 2014

Recently, small quadcopters have been widely used in various areas ranging from military to entertainment applications because interest in the quadcopter increases. Especially, the research on swarm flight which control quadcopters simultaneously without any collision can increase success probability of a important mission. In addition the swarm flight can be applied for demonstrating choreographed aerial maneuvers such as dancing and playing musical instruments. In this paper, we introduce multiple AR.Drone control system based on motion capture for indoor environment in which quadcopters can recognize current position each other and perform scenario based mission.

• Aerospace Engineering and Technology
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• v.13 no.1
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• pp.153-165
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• 2014

Multi-rotor UAVs are utilized in various fields because of the advantages such that a hovering capability such as helicopters, a simple structure and a relatively high thrust. Recently, AR.Drone manufactured by Parrot is easily operated by beginner due to its internal stabilization loop in the on-board computer and it can be easily applied on various researches for the multi-rotor UAVs by providing an SDK(Software Development Kit). Further this platform can be suitably used for application to swarm flight since it is low cost and relatively small. Therefore, in this paper, we introduce the development process of the controller for indoor swarm flight by using the AR.Drone.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.450-456
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• 2014

Humanoid robot is the most suitable robot platform for effective human and robot interaction. However, the robot's complicated body structure containing more than twenty joint actuators makes it difficult to generate stable and elaborate postures using the conventional inverse kinematic method. This paper proposes an alternative approach to generate difficult postures of touching an object placed in front of the foot by the left or right hand with its torso bent forward in single support phase using the fast computational optimization method, particle swarm optimization. The simulated postures are also applied to a commercial humanoid robot platform, which validates the feasibility of the proposed approach.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1079-1085
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• 2000

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). An immune system is the living bodys self-protection and self-maintenance system. these features can be applied to decision making of the optimal swarm behavior in a dynamically changing environment. For applying immune system to DARS, a robot is regarded as a B-cell, each environmental condition as an antigen, a behavior strategy as an antibody, and control parameter as a T-cell, respectively. When the environmental condition (antigen) changes, a robot selects an appropriate behavior strategy (antibody). And its behavior strategy is stimulated and suppressed by other robots using communication (immune network). Finally, much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and immune network hypothesis, and it is used for decision making of the optimal swarm strategy. Adaptation ability of the robot is enhanced by adding T-cell model as a control parameter in dynamic environments.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.185-193
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• 2009

This paper presents a methodology for photovoltaic (PV) system allocation in distribution systems using a discrete particle swarm optimization (DPSO). The PV allocation problem is in the category of mixed integer nonlinear programming and its formulation may include multi-valued dis-crete variables. Thus, the PSO requires a scheme to deal with multi-valued discrete variables. This paper introduces a novel multi-level quantization scheme using a sigmoid function for discrete particle swarm optimization. The technique is employed to a standard PSO architecture; the same velocity update equation as in continuous versions of PSO is used but the particle's positions are updated in an alternative manner. The set of multi-level quantization is defined as integer multiples of powers-of-two terms to efficiently approximate the sigmoid function in transforming a particle's position into discrete values. A comparison with a genetic algorithm (GA) is performed to verify the quality of the solutions obtained.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.549-557
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• 2014

Recently, analysis of bargaining game using evolutionary computation is essential issues in field of game theory. In this paper, we observe a bargaining game using co-evolution between two heterogenous artificial agents. In oder to model two artificial agents, we use a particle swarm optimization and a differential evolution. We investigate algorithm parameters for the best performance and observe that which strategy is better in the bargaining game under the co-evolution between two heterogenous artificial agents. Experimental simulation results show that particle swarm optimization outperforms differential evolution in the bargaining game.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.2019-2024
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• 2014

This paper presents a method to optimize the design of a planar-type antenna and reduce the number of design parameters for rapid computation. The electromagnetic characteristics of the structure are analyzed, and Taguchi method is used to identify critical design parameters. Adaptive particle swarm optimization, which has a faster convergence rate than particle swarm optimization, is used to achieve the design goal effectively. A compact dual-band USB dongle antenna is tested to verify the advantage of the proposed method. In this case, we can use only five selected geometrical parameters instead of eighteen to accelerate the optimization of the antenna design. The 10 dB bandwidth for return loss ranges from 2.3 GHz to 2.7 GHz and from 5.1 GHz to 5.9 GHz, covering all the WiBro, Bluetooth, WiMAX, and 802.11 b/g/n WLAN bands in both simulation and measurement. The optimization process enables the antenna design to achieve the required performance with fewer design parameters.

• Journal of Astronomy and Space Sciences
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• v.37 no.1
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• pp.29-34
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• 2020

On 21 August 2017, during 16:49 UT and 20:02 UT period, a total solar eclipse started. The totality shadow occurred over the United States in time between ~17:15 UT and ~18:47 UT. When the solar radiation is blocked by the moon, observations of the ionospheric parameters will be important in the space weather community. Fortunately, during this eclipse, two Swarm satellites (A and C) flied at about 445 km through lunar penumbra at local noon of United States in the upper ionosphere. In this work, we investigate the effect of the solar eclipse on electron density, slant total electron content (STEC) and electron temperature using data from Swarm mission over United States. We use calibrated measurements of plasma density and electron temperature. Our results indicate that: (1) the electron density and STEC have a significant depletion associated with the eclipse; which could be due to dominance of dissociative recombination over photoionization caused by the reduction of ionizing extreme ultraviolet (EUV) radiation during the eclipse time (2) the electron temperature decreases, compared with a reference day, by up to ~150 K; which could be due to the decrease in photoelectron heating from reduced photoionization.