• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.104-108
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• 2003

Finite element (FE) model updating is a procedure to minimize the differences between analytical and experimental results, which can be usually posed as an optimization problem. This paper aims to introduce a hybrid optimization algorithm (GA-SA), which consists of a Genetic algorithm (GA) stage and an Adaptive Simulated Annealing (ASA) stage, to FE model updating for a shrunk shaft. A good agreement of the first four natural frequencies has been achieved obtained from GASA based updated model (FEgasa) and experiment. In order to prove the validity of GA-SA, comparisons of natural frequencies obtained from the initial FE model (FEinit), GA based updated model (FEga) and ASA based updated model (FEasa) are carried out. Simultaneously, the FRF comparisons obtained from different FE models and experiment are also shown. It is concluded that the GA, ASA, GA-SA are powerful optimization techniques which can be successfully applied to FE model updating, the natural frequencies and FRF obtained from all the updated models show much better agreement with experiment than that obtained from FEinit model. However, FEgasa is proved to be the most reasonable FE model, and also FEasa model is better than FEga model.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.176-176
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• 2018

This study presents a regional, probabilistic framework for estimating streamflow via spatial scaling in the Great Lakes basin, which is the largest lake system in the world. The framework follows a two-fold strategy including (1) a quadratic-programming based optimization model a priori to explore the model structure, and (2) a time-varying hierarchical Bayesian model based on insights found in the optimization model. The proposed model is developed to explore three innovations in hierarchical modeling for reconstructing historical streamflow at ungaged sites: (1) information of physical characteristics is utilized in spatial scaling, (2) a time-varying approach is introduced based on climate information, and (3) heteroscedasticity in residual errors is considered to improve streamflow predictive distributions. The proposed model is developed and calibrated in a hierarchical Bayesian framework to pool regional information across sites and enhance regionalization skill. The model is validated in a cross-validation framework along with four simpler nested formulations and the optimization model to confirm specific hypotheses embedded in the full model structure. The nested models assume a similar hierarchical Bayesian structure to our proposed model with their own set of simplifications and omissions. Results suggest that each of three innovations improve historical out-of-sample streamflow reconstructions although these improvements vary corrsponding to each innovation. Finally, we conclude with a discussion of possible model improvements considered by additional model structure and covariates.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.99-106
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• 2014

Generation and analysis methods have been proposed in recent years, such as using a natural language and formal language processing, artificial intelligence algorithms based knowledge model is effective meaning. its semantic based knowledge model has been used effective decision making tree and problem solving about specific context. and it was based on static generation and regression analysis, trend analysis with behavioral model, simulation support for macroeconomic forecasting mode on especially in a variety of complex systems and social network analysis. In this study, in this sense, integrating knowledge-based models, This paper propose a text mining derived from the inter-Topic model Integrated formal methods and Algorithms. First, a method for converting automatically knowledge map is derived from text mining keyword map and integrate it into the semantic knowledge model for this purpose. This paper propose an algorithm to derive a method of projecting a significant topic map from the map and the keyword semantically equivalent model. Integrated semantic-based knowledge model is available.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.5
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• pp.24-32
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• 2011

According to accelerate the convergence of defense and information technology, there is a need for innovative change in Military e-Learning service system. In other words, It has increased the need for system integration based on standards and interoperability to develop into a network-centric information and knowledge. In this study, It would like to introduce an integrated direction Military e-Learning service system on the SOA-based video content services in the operating system for the operating model. SOA is taking advantage in integration and expansion of the unit with a process. Using it, define of video services platform architecture and define of business model based on the Imprimatur model. Based on this, it define the role of actors for video content service in each step of the operating model, that is Production model, Brokerage model and consumption model. In the operating system, it define the functions and data to control and handle the needed functionality for video content services based on the operational model.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.133-142
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• 2019

In physics-based character animation, trajectory optimization has been widely adopted for automatic motion synthesis, through the prediction of an optimal sequence of future states of the character based on its system dynamics model. In general, the system dynamics model is neither in a closed form nor differentiable when it handles the contact dynamics between a character and the environment with rigid body collisions. Employing smoothed contact dynamics, researchers have suggested efficient trajectory optimization techniques based on numerical differentiation of the resulting system dynamics. However, the numerical derivative of the system dynamics model could be inaccurate unlike its analytical counterpart, which may affect the stability of trajectory optimization. In this paper, we propose a novel method to derive the closed-form derivative for the system dynamics by properly approximating the contact model. Based on the resulting derivatives of the system dynamics model, we also present a model predictive control (MPC)-based motion synthesis framework to robustly control the motion of a biped character according to on-line user input without any example motion data.

• Journal of the Korean Statistical Society
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• v.30 no.4
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• pp.645-660
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• 2001

In this paper we propose a goodness-of-fit test statistic for testing the (null) parametric model versus the (alternative) nonparametric model. Most of existing nonparametric test statistics are based on the residuals which are obtained by regressing the data to a parametric model. Our test is based on the bootstrap estimator of the probability that the smoothing parameter estimator is infinite when fitting residuals to cubic smoothing spline. Power performance of this test is investigated and is compared with many other tests. Illustrative examples based on real data sets are given.

• Journal of information and communication convergence engineering
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• v.3 no.4
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• pp.209-212
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• 2005

This study proposes hybrid case-based reasoning and genetic algorithms model for customer classification. In this study, vertical and horizontal dimensions of the research data are reduced through integrated feature and instance selection process using genetic algorithms. We applied the proposed model to customer classification model which utilizes customers' demographic characteristics as inputs to predict their buying behavior for the specific product. Experimental results show that the proposed model may improve the classification accuracy and outperform various optimization models of typical CBR system.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.634-637
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• 2005

We propose a charge/discharge model for network based vehicle. These model include motor, alternator, lamp, brake, window brush, air conditioner, etc.. Also, we simulate these models in Matlab. The simulation results show that error range is less than 3%. So, we can adopt these model to charge/discharge simulator for network based vehicle. If this error range can be shrunk within 2%, we can use this simulator for comertial use.

• Journal of KIISE:Information Networking
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• v.29 no.1
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• pp.97-107
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• 2002

In general, under interactive broadcasting environment, user finds additional service using top-down menu. However, user can't know that additional service provides information until retrieval has finished and top-down menu requires multi-level retrieval. This paper proposes the new method for additional service providing not using top-down menu but using object selection. For the purpose of this method, the movie of a MPEG should be synchronized with the object information(position, size, shape) and object tracking technique is required. Synchronization technique uses the Directshow provided by the Microsoft. Object tracking techniques use a motion-based tracking and a model-based tracking together. We divide object into two parts. One is face and the other is substance. Face tracking uses model-based tracking and Substance uses motion-based tracking base on the block matching algorithm. To improve precise tracking, motion-based tracking apply the temporal prediction search algorithm and model-based tracking apply the face model which merge ellipse model and color model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.410-417
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• 2018

System design errors are more likely to occur in modern systems because of their steadily increasing size and complexity. Failures due to system design errors can cause safety-related accidents in the system, resulting in extensive damage to people and property. Therefore, international standards organizations, such as the U.S. Department of Defense and the International Electrotechnical Commission, have established international safety standards to ensure system safety, and recommend that system design and safety activities should be integrated. Recently, the safety of a system has been verified by modeling through a model-based system design. On the other hand, system design and safety activities have not been integrated because the model for system design and the failure model for safety analysis and verification were developed using different modeling language platforms. Furthermore, studies using UML or SysML-based failure models for deriving safety requirements have shown that these models have limited applicability to safety analysis and verification. To solve this problem, it is essential to extend the existing methods for failure model implementation. First, an improved SysML-based failure model capable of integrating system design and safety verification activities should be produced. Next, this model should help verify whether the safety requirements derived via the failure model are reflected properly in the system design. Therefore, this paper presents the concept and method of developing a SysML-based failure model for an automotive system. In addition, the failure model was simulated to verify the safety of the automotive system. The results show that the improved SysML-based failure model can support the integration of system design and safety verification activities.