• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.101.4-101
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• 2001

Evolutionary algorithm has been receiving a remarkable attention due to the model-free and population-based parallel search attributes and much successful results are coming out. However, there are some problems in most of the evolutionary algorithms. The critical one is that it takes much time or large generations to search the global optimum in case of the objective function with multimodality. Another problem is that it usually cannot search all the local optima because it pays great attention to the search of the global optimum. In addition, if the objective function has several global optima, it may be very difficult to search all the global optima due to the global characteristics of the selection methods. To cope with these problems, at first we propose a preprocessing process, grid-filtering algorithm(GFA), and propose a new distributed evolutionary ...

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.3
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• pp.203-209
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• 2010

This paper presents a hierarchical fuzzy motion planner for humanoid robots in 3D uneven environments. First, we define both motion primitives and locomotion primitives of humanoid robots. A high-level planner finds a global path from a global navigation map that is generated based on a combination of 2.5 dimensional maps of the workspace. We use a passage map, an obstacle map and a gradient map of obstacles to distinguish obstacles. A mid-level planner creates subgoals that help the robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. We use a local obstacle map to find the subgoals along the global path. A low-level planner searches for an optimal sequence of locomotion primitives between subgoals by using fuzzy motion planning. We verify our approach on a virtual humanoid robot in a simulated environment. Simulation results show a reduction in planning time and the feasibility of the proposed method.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.2
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• pp.111-117
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• 2020

The photovoltaic module has the characteristic that the output power varies according to the amount of insolation. If partial shading occurs in an environment composed of an array, a number of local maximum power points (LMPPs) may be generated according to the shading state. Photovoltaic arrays require global maximum power point tracking due to variations in output characteristics caused by solar radiation and temperature. Conventional algorithms, such as P&O and Incond, do not follow the global maximum power point in a partial shaded solar array. In this study, we propose a technique to follow the global maximum power point by using the correlation of voltage, current, and power in solar arrays. The proposed control technique 2qw validated through simulation and experiments by constructing a 2-kW solar system.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.4
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• pp.451-455
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• 2009

This paper provides a comparison of global path planning method in single string by using pulled and pushed SOFM (Self-Organizing Feature Map) which is a method among a number of neural network. The self-organizing feature map uses a randomized small valued initial-weight-vectors, selects the neuron whose weight vector best matches input as the winning neuron, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. On the other hand, the modified SOFM method in this research uses a predetermined initial weight vectors of the one dimensional string, gives the systematic input vector whose position best matches obstacles, and trains the weight vectors such that neurons within the activity bubble are move toward or reverse the input vector, by rising a pulled- or a pushed-SOFM. According to simulation results one can conclude that the modified neural networks in single string are useful tool for the global path planning problem of a mobile robot. In comparison of the number of iteration for converging to the solution the pushed-SOFM is more useful than the pulled-SOFM in global path planning for mobile robot.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.9
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• pp.868-874
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• 2007

This paper proposes an efficient partial matching system and representation by using a region-based method for 2D image, and we applied to an extraction of the ROI(Region of Interest) according to its matching score. The matching templates consist of the global pattern and the local one. The global pattern can make it by using region-based relation between center region and its rest regions in an object. And, the local pattern can be obtained appling to the same method as global, except relation between objects. As the templates can be normalized, we use this templates for extraction of ROI with invariant to size and position. And, our system operates only one try to match, due to normalizing of region size. To use our system for searching and examining if it's the ROI by evaluating the matching function, at first, we are searching to find candidate regions with the global template. Then, we try to find the ROI among the candidates, and it works this time by using the local template. We experimented to the binary and the color image respectively, they showed that the proposed system can be used efficiently for representing of the template and the useful applications, such as partially retrievals of 2D image.

• Journal of the Korean earth science society
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• v.33 no.6
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• pp.554-566
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• 2012

High-density temperature and salinity profiles from the successful international Argo project made it possible to reproduce the three-dimensional global ocean state in near-real time, which also increased much attention on the data analysis studies of global ocean. This paper reviewed several important issues on the recent data analysis studies such as systematic biases of XBT (eXpendable BathyThermograph) and Argo data, sea level budget discrepancy between steric height and satellite observed data, heat content change, and the current status of the development of objective analysis fields. This study also emphasized that it is required to carry out very cautious ocean data quality control and understand global-scale ocean variability prior to analyzing the regional-scale ocean climate change, particularly, in the East Asian marginal Seas.

• Journal of International Academy of Physical Therapy Research
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• v.10 no.3
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• pp.1849-1855
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• 2019

Background: Stroke patients require arm movement exercising for various stimulations in standing position for various stimulations rather than in a sitting position because they require integrated skillful movements, such as stretching, holding, and controlling. Objective: This study was conducted to provide foundational clinical data about lower limb global synkinesis in stroke patients using arm movements in a standing position. Design: Randomized controlled trial. Methods: The subjects were divided into a control group (n = 10) and an experimental group (n = 10), and a pre-test was conducted to evaluate leg global synkinesis (GS) and balance. Intervention method is stretching an arm to hold a ball, repeating supination and pronation of the hand only while maintaining the arm extended as much as possible, repeating shoulder abduction and adduction while holding the pegboard. This was followed by a three-week intervention during which re-measurement was conducted in the same way as was done for the pre-test. Results: The control group showed a significant difference in GS and balance during plantar flexion (p<.05), and the experimental group showed a significant difference in GS and balance during all movements (p<.05, p<.01, respectively). There was a significant difference in GS and balance between the two groups during dorsiflexion (p<.05, p<.01, respectively). Conclusion: The findings demonstrate that human arm movements in a standing position can reduce GS in the affected limb, and balance can be improved by stimulating the surrounding tissues of the affected limb and changing them positively.

• Journal of Korean Society of Water and Wastewater
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• v.27 no.6
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• pp.711-721
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• 2013

Optimal operation of a combined sewer network with distributed storage facilities aims to use the whole retention capacity of all reservoirs efficiently before overflows take place somewhere in the considered network system. An efficient real-time network control (RTNC) strategy has been emerging as an attractive approach for reducing substantially the overflows from a sewer network compared to the conventional fixed or manually adjusted gate setting method, but the related concrete framework for RTC development has not been throughly introduced so far. The main goal of this study is to give a detailed description of the RTNC systems via reviewing several guidelines published abroad, and finally to suggest methods for the proper application of RTNC on distributed storage facilities. Especially, this study is focused on emphasizing the importance of hierarchical structure of RTNC system that consists of three control layers (management, global control and local control). Further, with regard to the global control layer which is responsible for the central overall network control, the wide-ranging details of two components (adaption and optimization layers) are also presented. This study can provide the valuable basis for the RTNC implementation in the particular sewer network with distributed multiple storage facilities.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.2
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• pp.314-324
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• 2018

This paper proposes a linear distributed target tracking filter for multiple unmanned aerial vehicles(UAVs) sharing their passive sensor measurements through communication channels. Different from the conventional nonlinear filtering schemes, the distributed passive target tracking problem is newly formulated within the framework of a linear robust state estimation theory incorporated with a linear uncertain measurement equation including the coordinate transform uncertainty. To effectively cope with the performance degradation due to the coordinate transform uncertainty, a linear consistent robust Kalman filter(CRKF) theory is devised and applied for designing a distributed passive target tracking filter. Through the simulations for typical UAV surveillance mission, the superior performance of the proposed method over the existing schemes of distributed passive target tracking are demonstrated.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.405-413
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• 2006

A novel approach based on genetic algorithms (GA) is developed to find a global minimum-jerk trajectory of a space robotic manipulator in joint space. The jerk, the third derivative of position of desired joint trajectory, adversely affects the efficiency of the control algorithms and stabilization of whole space robot system and therefore should be minimized. On the other hand, the importance of minimizing the jerk is to reduce the vibrations of manipulator. In this formulation, a global genetic-approach determines the trajectory by minimizing the maximum jerk in joint space. The planning procedure is performed with respect to all constraints, such as joint angle constraints, joint velocity constraints, joint angular acceleration and torque constraints, and so on. We use an genetic algorithm to search the optimal joint inter-knot parameters in order to realize the minimum jerk. These joint inter-knot parameters mainly include joint angle and joint angular velocities. The simulation result shows that GA-based minimum-jerk trajectory planning method has satisfactory performance and real significance in engineering.