• Interaction and multiscale mechanics
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• v.3 no.3
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• pp.235-255
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• 2010

This paper investigates the heat equation for domains subjected to an internal source with a sharp spatial gradient. The solution is first approximated using linear finite elements, and sufficiently small time-step sizes to yield stable simulations. The main area of interest is then in the ability to approximate the solution using Generalized Finite Elements, and again explore the time-step limitations required for stable simulations. Both high order elements, as well as elements with special enrichments are used to generate solutions. When compared to linear finite elements, the high order elements deliver better accuracy at a given level of mesh refinement, but do not offer an increase in critical time-step size. When special enrichment functions are used, the solution can be approximated accurately on very coarse meshes, while yielding solutions which are both accurate and computationally efficient. The major conclusion of interest is that the significantly larger element size yields larger allowable time-step sizes while still maintaining stability of the time-stepping algorithm.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.87-93
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• 2017

A maximum likelihood (ML) approach is presented for estimating the mean of radar cross section (RCS) of a Swerling III target and its numerical solution methods are discussed. The solution methods are based on an approximate expression for implementing the expectation maximization (EM) algorithm. The methods are evaluated and compared through Monte Carlo simulations in terms of estimation accuracy and computational efficiency to obtain a most efficient method for both Swerling I and Swerling III targets. The methods are also compared with a previously reported method based on heuristics.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.990-995
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• 1990

A minimum-time trajectory planning for two robot arms with designated paths and coordination is proposed. The problem considered in this paper is a subproblem of hierarchically decomposed trajectory planning approach for multiple robots : i) path planning, ii) coordination planning, iii) velocity planning. In coordination planning stage, coordination space, a specific form of configuration space, is constructed to determine collision region and collision-free region, and a collision-free coordination curve (CFCC) passing collision-free region is selected. In velocity planning stage, normal dynamic equations of the robots, described by joint angles, velocities and accelerations, are converted into simpler forms which are described by traveling distance along collision-free coordination curve. By utilizing maximum allowable torques and joint velocity limits, admissible range of velocity and acceleration along CFCC is derived, and a minimum-time velocity planning is calculated in phase plane. Also the planning algorithm itself is converted to simple numerical iterative calculation form based on the concept of neural optimization network, which gives a feasible approximate solution to this planning problem. To show the usefulness of proposed method, an example of trajectory planning for 2 SCARA type robots in common workspace is illustrated.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.11
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• pp.1179-1185
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• 2013

In this study, the design optimization of the automotive side member is performed to maximize the crash energy absorption efficiency per unit weight. Design parameters which seriously influence on the frontal crash performance are selected through the sensitivity analysis using the Plackett-Burman design method. And also the design variables, which are determined from the sensitivity analysis, are optimized by two methods. One is conventional approximate optimization method which uses the statistical design of experiments (DOE) and response surface method (RSM). The other is a methodology derived from previous work by the authors, which is called sequential design of experiments (SDOE), to reduce a trial and error procedure and to find an appropriate condition for using micro-genetic algorithm. The proposed optimization technique shows that the automotive side member structure can be designed considering the frontal crash performance.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.1
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• pp.147-162
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• 1997

When designing workplaces or arranging controls on panel, devices and controls should be placed within the reach of operator's arm or foot to guarantee effective performances. Most of the existing research on the reach volume were based on measurements of a few subject's arm reach, and limited to Caucasian and Chinese populations. Furthermore, reach volume considering foot or trunk motion have not been investigated. Range of human joint motion and that of two degrees of freedom motion are needed to generate reach volume analytically using the sweeping algorithm. However, range of two degrees of freedom motion has not been measured up to now. Therefore, range of two degrees of freedom motion was measured in this research, where 47 college students were participated voluntarily as subjects. The results showed that the motion of one joint can be limited by the motion of another motion, that is to say, the shoulder flexion was decreased significantly when the shoulder was adducted or abducted. Second, new approximate algorithms generating reach volumes were suggested, in which range of two degrees of freedom motion was used as input data. Depending upon the body segment included such as trunk, arm and leg, three types of reach volume were provided, in which the human body was modeled as a multilink system based on the robot kinematics and the sweeping method was employed. Reach volume generated analytically in this study showed statistically reasonable results when compared with that obtained from direct measurement.

• Journal of the Korean Institute of Navigation
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• v.21 no.3
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• pp.55-66
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• 1997

In this paper, applications of neural networks to vibration control of flexible single link robot manipulator are ocnsidered. The architecture of neural networks is a hidden layer, which is comprised of self-recurrent one. Tow neural networks are utilized in a control system ; one as an identifier is called neuro identifier and the othe ra s a controller is called neuro controller. The neural networks can be used to approximate any continuous function to any desired degree of accuracy and the weights are updated by dynamic error-backpropagation algorithm(DEA). To guarantee concegence and to get faster learning, an approach that uses adaptive learning rates is developed by introducing a Lyapunov function. When a flexible manipulator is ratated by a motor through the fixed end, transverse vibration may occur. The motor torque should be controlle dinsuch as way, that the motor is rotated by a specified angle. while simulataneously stabilizing vibration of the flexible manipulators so that it is arrested as soon as possible at the end of rotation. Accurate vibration control of lightweight manipulator during the large body motions, as well as the flexural vibrations. Therefore, dynamic models for a flexible single link manipulator is derived, and LQR controller and nerual networks controller are composed. The effectiveness of the proposed nerual networks control system is confirmed by experiments.

• Transactions of the Korean Society of Mechanical Engineers
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• v.9 no.5
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• pp.647-654
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• 1985

A computer aided design package is developed that can perform such functions as computer aided inputing/drafting/modifying/outputing, automatic determination of volumetric properties, finite element analysis and post processing for the design of axisymmetric shell with slight asymmetry. In order to make the design modification easy and to accelerate the computation time for analysis, developed is a new finite element analysis which utilizes an approximate solution method and a conical ring eleement with slight asymmetry. Also proposed is a computer aided process planning algorithm which is based on the axiomatic approach.

• The KIPS Transactions:PartD
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• v.18D no.6
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• pp.415-422
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• 2011

Finding similar strings is an important operation because textual data can have errors, duplications, and inconsistencies by nature. Many algorithms have been developed for string approximate searches and most of them make use of inverted lists to find similar strings. These algorithms basically perform merge operations on inverted lists. In this paper, we develop a bitmap representation of an inverted list and propose an efficient search algorithm that can skip unnecessary inverted lists without searching using bitmap filters. Experimental results show that the proposed technique consistently improve the performance of the search.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.2
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• pp.101-106
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• 2010

We propose an approach to estimate the real-time moving trajectory of an object in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the inputoutput relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

• Water for future
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• v.25 no.4
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• pp.109-119
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• 1992

The purpose of this study is to develop real-time streamflow forecasting models in order to manage effectively the flood warning system and water resources during the storm. The stochastic system models of the rainfall-runoff process using in this study are constituted and applied the Recursive Least Square and the Instrumental Variable-Approximate Maximum Likelihood algorithm which can estimate recursively the optimal parameters of the model. Also, in order to improve the performance of streamflow forecasting, initial values of the model parameter and covariance matrix of parameter estimate errors were evaluated by using the observed historical data of the hourly rainfall-runoff, and the accuracy and applicability of the models developed in this study were examined by the analysis of the I-step ahead streamflow forecasts.