• Korean Journal of Cognitive Science
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• v.10 no.4
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• pp.71-83
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• 1999

Conventional symbolic inference systems lack flexibility because they do not well reflect flexible semantic structure of knowledge and use symbolic logic for their basic inference mechanism. For solving this problem. we have recently proposed the 'Connectionist Semantic Network(CSN)' as a model for flexible knowledge representation and inference based on neural networks. The CSN is capable of carrying out both approximate reasoning and commonsense reasoning based on similarity and association. However. we have difficulties in representing general and structured high-level knowledge and variable binding using the connectionist framework of the CSN. In this paper. we propose a hybrid system called SymCSN(Symbolic CSN) that combines a symbolic module for representing general and structured high-level knowledge and a connectionist module for representing and learning low-level semantic structure Simulation results show that the SymCSN is a plausible model for human-like flexible knowledge representation and inference.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.12
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• pp.1433-1441
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• 2009

In multibody dynamic analysis, one of the most important problems is to reduce computation times for real-time simulation. This paper presents the derivation procedure of equations of motion of a 6${\times}$6 autonomous vehicle in terms of chassis local coordinates which do not require coordinates transformation matrix to enhance efficiency for real-time dynamic analysis. Also, equations of motion are derived using the VT(velocity transformation) technique and symbolic computation method coded by MATLAB. The Jacobian matrix of the equations of motion of a system is derived from symbolic operations to apply the implicit integration method. The analysis results were compared with ADAMS results to verify the accuracy and approve the feasibility of real time analysis.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.19 no.12
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• pp.1099-1105
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• 2006

In this paper, the equivalent circuit model of a Rosen-type multilayer piezoelectric transformer(MPT) has been proposed based on the Mason's equivalent circuit model and the principle of single layer piezoelectric plate. From the piezoelectric direct and converse effects, the symbolic expressions between the electric inputs and outputs of the MPT have been derived from the equivalent circuit model. A simplified equivalent circuit model of the MPT whose driving part has a single input form has been proposed. The symbolic expressions of the driving part have been derived from the simplified equivalent circuit model and the model was compared with the multi-input equivalent circuit model through the simulation. In the comparisons between the simulation results and the experimental data, output voltage is 630 Vp-p in case of 11-layered MPT and 670 Vp-p for 13-layered MPT over the experiment range. As the load resistance increases, output voltage increases and saturates over $300k{\Omega}$ and the resonant frequency changes from 102 kHz to 103 kHz. The simulation and the experimental results agree well over different load resistances and frequencies.

• Proceedings of the Korea Society for Simulation Conference
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• 1994.10a
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• pp.12-12
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• 1994

Simulation output knowledge analysis is one of problem-solving and/or knowledge adquistion process by investgating the system behavior under study through simulation . This paper describes an approach to simulation outputknowldege analysis using fuzzy neural network model. A fuzzy neral network model is designed with fuzzy setsand membership functions for variables of simulation model. The relationship between input parameters and output performances of simulation model is captured as system behavior knowlege in a fuzzy neural networkmodel by training examples form simulation exepreiments. Backpropagation learning algorithms is used to encode the knowledge. The knowledge is utilized to solve problem through simulation such as system performance prodiction and goal-directed analysis. For explicit knowledge acquisition, production rules are extracted from the implicit neural network knowledge. These rules may assit in explaining the simulation results and providing knowledge base for an expert system. This approach thus enablesboth symbolic and numeric reasoning to solve problem througth simulation . We applied this approach to the design problem of broadband communication network.

• Journal of applied mathematics & informatics
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• v.3 no.2
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• pp.129-148
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• 1996

This paper propose the inference mechanism for handling linear polynomial constraints called consistency checking algorithm based on the feasibility checking algorithm borrowed from linear pro-gramming. in contrast with other approaches proposed algorithm can efficiently and coherented by linear polynomial forms. The developed algorithm is successfully applied to the symbolic simulation that offers a convenient means to conduct multiple simultaneous exploration of model behaviors.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1764-1769
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• 1991

Recently, dexterous mechanical hands have become of interest in the field of robotics. In this paper, a new symbolic C-Y notation is proposed for the kinematic modeling, and we solve the kinematics of a simplified model of POSTECH Hand 1, which is a 5 fingered, 20 degrees of freedom anthropomorphic hand. POSTECH Hand I is designed to have distinctive kinematic structure and the kinematic analysis of the hand is carried out using C-Y notation. To prove the feasibility of C-Y notation, D-H notation is also applied to the POSTECH Hand 1. In the inverse kinematic analysis, we neglect the fingertip geometry and assume the point contact with 3 degrees of freedom constraints. The configurations which optimize manipulability index[2] was obtained based on the simulation experiments on the SUN-4 graphic workstation using SUNPhigs graphic software.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.272-277
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• 2005

We introduce a new approach to optimize the parameters in biological kinetic models by quantifier elimination (QE), in combination with numerical simulation methods. The optimization method was applied to a model for the inhibition kinetics of HIV proteinase with ten parameters and nine variables, and attained the goodness of fit to 300 points of observed data with the same magnitude as that obtained by the previous optimization methods, remarkably by using only one or two points of data. Furthermore, the utilization of QE demonstrated the feasibility of the present method for elucidating the behavior of the parameters in the analyzed model. The present symbolic-numeric method is therefore a powerful approach to reveal the fundamental mechanisms of kinetic models, in addition to being a computational engine.

• Communications for Statistical Applications and Methods
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• v.22 no.3
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• pp.265-276
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• 2015

In this paper, we propose hierarchical cluster analysis and multidimensional scaling for joint distribution valued data. Information technology is increasing the necessity of statistical methods for large and complex data. Symbolic Data Analysis (SDA) is an attractive framework for the data. In SDA, target objects are typically represented by aggregated data. Most methods on SDA deal with objects represented as intervals and histograms. However, those methods cannot consider information among variables including correlation. In addition, objects represented as a joint distribution can contain information among variables. Therefore, we focus on methods for joint distribution valued data. We expanded the two well-known exploratory methods using the dissimilarities adopted Hall Type relative projection index among joint distribution valued data. We show a simulation study and an actual example of proposed methods.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.375-376
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• 2023

정보기술의 발전으로 인해 코딩 교육의 중요성이 부각되고 있다. 코딩 교육과 다양한 분야와 융합된 교육 모델이 제시되고 있으며 그 중 드론을 활용한 코딩 교육 방법이 일부 존재하지만 오락성이 강조되거나 드론 조종에 초점을 두고 있어 코딩 역량 향상에는 한계가 있다. 본 논문에서는 학습자의 안전성을 보장하고 코딩 역량 향상을 위해 드론 교육에 적용 가능한 교육용 심볼릭 코딩 어플리케이션을 제시한다. 제시하는 어플리케이션은 사용자가 SW 설계 수준의 순서도 기반 심볼릭 코딩을 학습하고 코딩 결과를 드론 시뮬레이션 또는 실제 드론에 적용하여 확인할 수 있는 기능을 제공한다. 이를 통해 학습자들에게 실제적인 코딩 경험을 제공하고 창의적인 문제 해결 능력과 창의성 향상을 기대할 수 있다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.3
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• pp.389-394
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• 2014

Two evolutionary gait generation methods for Cartesian and Joint coordinates space are compared to develop a fast locomotion for quadruped robots. GA(Genetic Algorithm) based approaches seek to optimize a pre-selected set of parameters for the locus of paw and initial position in cartesian coordinates space. GP(Genetic Programming) based technique generate few joint trajectories using symbolic regression in joint coordinates space as a form of polynomials. Optimization for two proposed methods are executed using Webots simulation for the quadruped robot which is built by Bioloid. Furthermore, simulation results for two proposed methods are analysed in terms of different coordinate spaces.