• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1960-1961
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• 2006

In this paper, The trajectory control of robot manipulator is proposed. It divides by trajectory planning and tracking control. A trajectory planning and tracking control of robot manipulator is used to the neural network and evolutionary algorithm. The trajectory planning provides not only the optimal trajectory for a given cost function through evolutionary algorithm but also the configurations of the robot manipulator along the trajectory by considering the robot dynamics. The computed torque method (C.T.M) using the model of the robot manipulators is an effective means for trajectory tracking control. However, the tracking performance of this method is severely affected by the uncertainties of robot manipulators. The Radial Basis Function Networks(RBFN) is used not to learn the inverse dynamic model but to compensate the uncertainties of robot manipulator. The computer simulations show the effectiveness of the proposed method.

• Journal of Technology Innovation
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• v.22 no.4
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• pp.117-143
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• 2014

Tracing an evolutionary technological trajectory in the macroscopic viewpoint is useful for technology policy, but not for corporate technology and intellectual property strategy. Tackling this issue, recent bibliometric studies using patents and papers have made efforts to identify more specific and detailed technological trajectory. However, these studies cannot go beyond simple description of the past trajectory. Also, identification of technology fusion and evolution relies on experts judgments. We suggest a way of identifying microscopic evolutionary technological trajectories by combining patent citation network analysis with dynamic technology tree. Also, using new indicators of generality, diversity and novelty, we can detect key technologies that can be a starting point of next generation technology and derivative technology. HVDC(High Voltage DC transmission) system technology is exemplified.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1181-1184
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• 1996

As usual systems, robot manipulators have also physical constraints for operating. It is a difficult problem that we operate manipulator in the minimal time under these constraints. In this paper, we solve this problem dividing it into two steps. In the first step, we find the minimal time trajectories by optimizing qubic polynomial joint trajectories using evolutionary algorithms. In the second step, we optimize controller for robot manipulator to track precisely trajectories optimized in the previous step.

• Journal of Space Technology and Applications
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• v.1 no.3
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• pp.302-318
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• 2021

A basic study was conducted on how to determine the launch timing of a space probe targeting an Earth-approaching asteroid. In the future, when a probe mission targeting an asteroid approaching Earth's orbit is conducted in Korea, in order to determine the launch time, an appropriate solution should be obtained by applying the Global Optimization technique. For this, accurate current orbit information of each asteroid must be obtained first, and prior scenarios such as Earth's orbit information, main engine performance information of the probe and launch vehicle, the number of gravity-assisted maneuvers, and maximum flight time limit should be discussed. Also, the criteria for optimization should be determined first. In this paper, based on these prerequisites and information, a method for finding the launch time of an asteroid probe was studied using the open source software such as PyKEP and Evolutionary Mission Trajectory Generator (EMTG) which are the programs for interplanetary trajectory generation purpose.

• Journal of the Economic Geographical Society of Korea
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• v.11 no.4
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• pp.509-526
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• 2008

This paper aims to examine the evolutionary dynamics of the Korea's footwear industry by adopting evolutionary perspectives. To explain the evolutionary dynamics of an industry, evolutionary perspectives have paid a particular attention to exploring a variety of factors for influencing the evolution of the industry, such as the selection and imitation of the firm, the mechanism of firm's entry and exit, technological characteristics and innovation processes. The majority of existing research tend to explain that the decline of the Korea's footwear industry since 1990 was mostly due to the rapid rising of wage and the structural changes in labor-intensive industries. On the contrary, this paper attempts to explain the decline of the Korea's footwear industry, in terms of the path of selection and imitation, the dominant technological paradigm, regulatory frameworks and the meso trajectory of industry evolution. This paper concludes that the decline of the Korea's footwear industry since 1990 was appeared as a result of the evolutionary selection processes of the firms in order to adapt to changes in the environment of competition and the regime of market selection in the global footwear industry.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2420-2426
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• 2015

This paper proposes an evolutionary optimization approach for optimal hopping of humanoid robots. In the proposed approach, the hopping trajectory is generated by a central pattern generator (CPG). The CPG is one of the biologically inspired approaches, and it generates rhythmic signals by using neural oscillators. During the hopping motion, the disturbance caused by the ground reaction forces is compensated for by utilizing the sensory feedback in the CPG. Posture control is essential for a stable hopping motion. A posture controller is utilized to maintain the balance of the humanoid robot while hopping. In addition, a compliance controller using a virtual spring-damper model is applied for stable landing. For optimal hopping, the optimization of the hopping motion is formulated as a minimization problem with equality constraints. To solve this problem, two-phase evolutionary programming is employed. The proposed approach is verified through computer simulations using a simulated model of the small-sized humanoid robot platform DARwIn-OP.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.189-191
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• 1995

This paper proposes a design of self-tuning fuzzy controller based on evolutionary computation. Optimal membership functions are found by using evolutionary computation. Genetic algorithms and evolution strategy are used for tuning of fuzzy membership function. An arbitrarily speed trajectory is selected to show the performance of the proposed methods. Experiment results show the good performance in the DC motor control system with the self-tuning fuzzy controller based on evolutionary computation.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.1
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• pp.95-104
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• 2016

To make a firing table of artillery with trajectory simulation, a precise trajectory model which corresponds with real firing test is required. Recent 4-DOF modified point mass trajectory model is considered accurate as a theoretical model, but fitting coefficients are used in calculation to match with real firing test results. In this paper, modified point mass trajectory model is presented and method of setting ballistic coefficient is introduced by applying optimization algorithms. After comparing two different algorithms, Particle Swarm Optimization and Covariance Matrix Adaptation - Evolutionary Strategy, we found that using CMA-ES algorithm gives fine optimization result. This fitting coefficient setting method can be used to make trajectory simulation which is required for development of new projectiles in the future.

• Molecules and Cells
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• v.43 no.8
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• pp.728-738
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• 2020

Time and cost-effective production of next-generation sequencing data has enabled the performance of population-scale comparative and evolutionary studies for various species, which are essential for obtaining the comprehensive insight into molecular mechanisms underlying species- or breed-specific traits. In this study, the evolutionary and functional analysis of Korean native pig (KNP) was performed using single nucleotide polymorphism (SNP) data by comparative and population genomic approaches with six different mammalian species and five pig breeds. We examined the evolutionary history of KNP SNPs, and the specific genes of KNP based on the uniqueness of non-synonymous SNPs among the used species and pig breeds. We discovered the evolutionary trajectory of KNP SNPs within the used mammalian species as well as pig breeds. We also found olfaction-associated functions that have been characterized and diversified during evolution, and quantitative trait loci associated with the unique traits of KNP. Our study provides new insight into the evolution of KNP and serves as a good example for a better understanding of domestic animals in terms of evolution and domestication using the combined approaches of comparative and population genomics.

• Proceedings of the Korean Society for Applied Microbiology Conference
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• 2005.06a
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• pp.137-138
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• 2005