• Journal of Intelligence and Information Systems
• /
• v.9 no.3
• /
• pp.99-115
• /
• 2003

In this paper, we present a knowledge-based object-oriented spatial database system called KOBOS. A knowledge-based approach is introduced to the object-oriented spatial database system for data modeling and approximate query answering. For handling the structure of spatial objects and the approximate spatial operators, we propose three levels of object-oriented data model: (1) a spatial shape model; (2) a spatial object model; (3) an internal description model. We use spatial type abstraction hierarchies(STAHs) to provide the range of the approximate spatial operators. We then propose SOQL, a spatial object-oriented query language. SOQL provides an integrated mechanism for the graphical display of spatial objects and the retrieval of spatial and aspatial objects. To support an efficient hybrid query evaluation, we use the top-down spatial query processing method.

• Journal of the Korea Convergence Society
• /
• v.12 no.3
• /
• pp.187-196
• /
• 2021

The paper deals with comparative study for characteristics of approximation of design space according to various approximate models and sensitivity analysis using orthogonal array experiments in structure design of active type DSF which was developed for float-over installation of offshore plant. This study aims to propose the orthogonal array experiments based design methodology which is able to efficiently explore an optimum design case and to generate the accurate approximate model. Thickness sizes of main structure member were applied to the design factors, and output responses were considered structure weight and strength performances. Quantitative effects on the output responses for each design factor were evaluated using the orthogonal array experiment. Best design case was also identified to improve the structure design with weight minimization. From the orthogonal array experiment results, various approximate models such as response surface model, Kriging model, Chebyshev orthogonal polynomial model, and radial basis function based neural network model were generated. The experiment results from orthogonal array method were validated by the approximate modeling results. It was found that the radial basis function based neural network model among the approximate models was able to approximate the design space of the active type DSF with the highest accuracy.

• The Korean Journal of Applied Statistics
• /
• v.22 no.1
• /
• pp.205-220
• /
• 2009

For modeling skewed semicircular data, we derive new family of the exponential distributions. We extend it to the l-axial exponential distribution by a transformation for modeling any arc of arbitrary length. It is straightforward to generate samples from the f-axial exponential distribution. Asymptotic result reveals two things. The first is that linear exponential distribution can be used to approximate the l-axial exponential distribution. The second is that the l-axial exponential distribution has the asymptotic memoryless property though it doesn't have strict memoryless property. Some trigonometric moments are also derived in closed forms. Maximum likelihood estimation is adopted to estimate model parameters. Some hypotheses tests and confidence intervals are also developed. The Kolmogorov-Smirnov test is adopted for goodness of fit test of the l-axial exponential distribution. We finally obtain a bivariate version of two kinds of the l-axial exponential distributions.

• The Korean Journal of Applied Statistics
• /
• v.23 no.6
• /
• pp.1125-1145
• /
• 2010

For modeling(skewed) semicircular data, we derive a new exponential family of distributions. We extend it to the l-axial exponential family of distributions by a projection for modeling any arc of arbitrary length. It is straightforward to generate samples from the l-axial exponential family of distributions. Asymptotic result reveals that the linear exponential family of distributions can be used to approximate the l-axial exponential family of distributions. Some trigonometric moments are also derived in closed forms. The maximum likelihood estimation is adopted to estimate model parameters. Some hypotheses tests and confidence intervals are also developed. The Kolmogorov-Smirnov test is adopted for a goodness of t test of the l-axial exponential family of distributions. Samples of orientations are used to demonstrate the proposed model.

• Journal of the korean Society of Automotive Engineers
• /
• v.14 no.2
• /
• pp.88-98
• /
• 1992

Real automobiles have been utilized to study the occupant behaviors and the response of the structures in the crash environment. Since various parameters are involved in the automobile crashworthiness, a number of experiments must be conducted. The experiments have been contributed to increasing the cost due to the fact that the test is quite expensive. Therefore, computer simulation is adopted to reduce the number of experiments. A few computer programs have been developed specifically to solve the occupant responses in the crash environment. In this research, a software is used to study the occupant dynamic analysis. A modeling of occupant analysis is established for a passenger car and the results are verified through comparisons with real experiments. In the modeling, data are tuned very carefully so that simulated results such as HIC(Head Injury Criterion) and acceleration of each body may approximate to the experimental results. The compared experiment is a barrier test which is carried out by frontal impact. A feedback to the design process is suggested from the result of this research.

• Proceedings of the KIEE Conference
• /
• 2001.07b
• /
• pp.647-649
• /
• 2001

It is a indispensible condition that the simulation and the experiment to improve a efficiency of maglev system. We usually carry out the simulation using the approximate equation, because it is impossible to use a exact modeling such as a practice modeling. This paper proposed a ideal simulation ap to the maglev system modeling by Finite Ele Method. To save the electrical energy, zero p control method is used, and verifying the feasibi FEM dynamic simulation, we make an exper with a TI DSP TMS320F240-based hardware.

• The Journal of Information Systems
• /
• v.29 no.3
• /
• pp.103-117
• /
• 2020

Purpose Recently, various issues related to toxic comments on web portal sites and SNS are becoming a major social problem. Toxic comments can threaten Internet users in the type of defamation, personal attacks, and invasion of privacy. Over past few years, academia and industry have been conducting research in various ways to solve this problem. The purpose of this study is to develop the deep learning modeling for toxic comments classification. Design/methodology/approach This study analyzed 7,878 internet news comments through CNN classification modeling based on Highway Network and OOV process. Findings The bias and hate expressions of toxic comments were classified into three classes, and achieved 67.49% of the weighted f1 score. In terms of weighted f1 score performance level, this was superior to approximate 50~60% of the previous studies.

• Journal of the Korean Society for Precision Engineering
• /
• v.22 no.8 s.173
• /
• pp.34-41
• /
• 2005

Generally, it is not easy to get a suitable controller for multi variable systems. If the modeling equation of the system can be found, it is possible to get LQR control as an optimal solution. This paper suggests an LQR learning method to design LQR controller without the modeling equation. The proposed algorithm uses the same cost function with error and input energy as LQR is used, and the LQR controller is trained to reduce the function. In this training process, the Jacobian matrix that informs the converging direction of the controller Is used. Jacobian means the relationship of output variations for input variations and can be approximately found by the simple experiments. In the simulations of a hydrofoil catamaran with multi variables, it can be confirmed that the training of LQR controller is possible by using the approximate Jacobian matrix instead of the modeling equation and this controller is not worse than the traditional LQR controller.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 1995.10a
• /
• pp.227-232
• /
• 1995

This paper presents a digital modeling technique for the distributed parameter system. The basic idea of the proposed technique is to discretize a continuous system with respect to the spatial coordinate using the approximate methods such as bilinear method and backward difference method. The response of the discretized system is analyzed by Laplace transform and Z transform. The computational result of the proposed technique in a torsional shaft is compared with the exact solution and the result of the finite element method.

• International Journal of CAD/CAM
• /
• v.9 no.1
• /
• pp.85-91
• /
• 2010

In this paper, we demonstrate an autonomous design of motion control of virtual creatures (called animated robots in this paper) and develop modeling software for animated robots. An animated robot can behave autonomously by using its own sensors and controllers on three-dimensional physically modeled environment. The developed software can enable us to execute the simulation of animated robots on physical environment at any time during the modeling process. In order to simulate more realistic world, an approximate fluid environment model with low computational costs is presented. It is shown that a combinatorial use of neural network implementation for controllers and the genetic algorithm (GA) or the particle swarm optimization (PSO) is effective for emerging more realistic autonomous behaviours of animated robots.