• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2014.10a
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• pp.114-116
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• 2014

The interpolation of the missing AIS dynamic data can be used for predicting the lost data of the ship's state which is able to product the valuable information for analyzing and investigating the maritime accidents. The previous research proposed some interpolating methods however there exists some problem, firstly, the interpolated parameters such as COG, SOG, HDG weren't described sufficiently and accurately as in AIS message, secondly, each method is only suitable to some kinds of given AIS data, finally at heavy wind and current area, the parameters of AIS dynamic change quickly in short time, therefore, the modelling of the variation of ship's dynamic based on the physical characteristic is very difficult, in these cases the time-series and numerical method are usually better. This research proposes the other method through numerical analysis which can be suitable for many different kinds of the lost data, parameters are interpolated sufficiently, beside that this model is appropriate to all variation in short time interval. All the given AIS dynamic are regarded as the functions to time, then curves are established for fitting all data. Experiments are carried out to evaluate the performance of this approach, the interpolation results show this approach can be applied well in practice.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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• pp.167-173
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• 2005

This paper presents an autocorrelation test that is applicable to dynamic panel data models with serially correlated errors. The residual-based GMM t-test is a significance test that is applied after estimating a dynamic model by using the instrumental variable(IV) method and is directly applicable to any other consistently estimated residuals. Monte Carlo simulations show that the t-test has considerably more power than the $m_2$ test or the Sargan test under both forms of serial correlation (i.e., AR(1) and MA(1)).

• Journal of the Korean Statistical Society
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• v.34 no.4
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• pp.367-375
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• 2005

This paper presents an autocorrelation test that is applicable to dynamic panel data models with serially correlated errors. The residual-based GMM t-test is a significance test that is applied after estimating a dynamic model by using the instrumental variable (IV) method and is directly applicable to any other consistently estimated residuals. Monte Carlo simulations show that the t-test has considerably more power than the $m_2$ test or the Sargan test under both forms of serial correlation (i.e., AR(1) and MA(1)).

• Journal of Electrical Engineering and Technology
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• v.6 no.4
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• pp.484-492
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• 2011

Power system analyses, which involve the handling of massive data volumes, necessitate the use of effective visualization methods to facilitate analysis and assist the user in obtaining a clear understanding of the present state of the system. This paper introduces an interface that compensates for the limitations of the visualization modules of dynamic security assessment tools, such as PSS/e and TSAT, for power system variables including generator rotor angle and frequency. The compensation is made possible through the automatic provision of dynamic simulation data in visualized and tabular form for better data intuition, thereby considerably reducing the redundant manual operation and time required for data analysis. The interface also determines whether the generators are stable through a generator instability algorithm that scans simulation data and checks for an increase in swing or divergence. The proposed visualization methods are applied to the dynamic simulation results for contingencies in the Korean Electric Power Corporation system, and have been tested by power system researchers to verify the effectiveness of the data visualization interface.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.40
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• pp.1-14
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• 1996

We develop a dynamic demand forecasting model compared to regression analysis model and AutoRegressive Integrated Moving Average(ARIMA) model. The dynamic model can apply to the current dynamic data to forecasts through introducing state equation. A multiple regression model and ARIMA model using given data are designed via the model analysis. The forecasting fitness evaluation between the designed models and the dynamic model is compared with the criterion of sum of squared error.

• Proceedings of the KSR Conference
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• 2003.10b
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• pp.563-568
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• 2003

High-speed railway bridges subject to effect of dynamic loads by interaction between vehicle load which run specially fast and behavior of bridges. Such dynamic load effects result in fluctuations and fatigues to each elements as well as whole conduct of bridges. and is influenced in life of bridges. For these reason. Analysis and estimation of data about dynamic behavior of bridges occupies important factor in that estimate the remaining life of bridges and select the maintenance. repair and retrofit. In this paper. Analysis for the dynamic behavior of bridges using displacement and acceleration data that is actuality measure data to the bridges of Seoul-Susan high speed railroad test section has been made.

• Earthquakes and Structures
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• v.11 no.6
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• pp.1043-1060
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• 2016

The engineering background of this article is an ancient wooden building with extremely high historic and cultural values in Tibet. A full understanding of the dynamic behaviour of this historic building under in-service environments is the basis to assess the condition of the structure, especially its responses to earthquake, environmental and operational loading. A dynamic monitoring system has been installed in the building for over one year and the large amounts of high quality data have been obtained. The paper aims at studying the dynamic behaviour of the wooden building in seismic and operational conditions using the field monitoring data. Specifically the effects of earthquake and crowd loading on the structure's dynamic response are investigated. The monitoring data are decomposed into principal components using the Singular Spectrum Analysis (SSA) technique. The relationship between the average acceleration amplitude and frequencies of the principle components and operational conditions has been discussed. One main contribution is to understand the health condition of complex ancient building based on large databases collected on the field.

• Architectural research
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• v.10 no.2
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• pp.21-26
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• 2008

The number of measured degrees of freedom for detecting the damage of any structures is usually less than the number of model degrees of freedom. It is necessary to expand the measured data to full set of model degrees of freedom for updating modal data. This study presents the expansion methods to estimate all static displacements and dynamic modal data of finite element model from the measured data. The static and dynamic methods are derived by minimizing the variation of the potential energy and the Gauss's function, respectively. The applications illustrate the validity of the proposed methods. It is observed that the numerical results obtained by the static approach correspond with the Guyan condensation method and the derived static and dynamic approaches provide the fundamental idea for damage detection.

• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.5
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• pp.56-61
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• 2010

This paper presents dynamic clearance verification considering engine movement for vehicle engine room package and validates through physical vehicle test. Traditionally, static clearance guide has been used for engine room package, but it's only 2-dimension criteria that results in requiring unnecessary space and it's not possible to conduct engine movement with real driving conditions. Thus, the dynamic DMU considers engine movement based on 28 load cases that are Roll Data analyzed by CAE for maximum engine movement and visualizes part-to-part dynamic clearance into virtual space. The dynamic DMU enables to develop compact engine room package without unnecessary space. The result of comparison between simulation and physical test has 0.892 correlation coefficient.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.237-253
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• 2018

In a rapidly changing environment, dynamic resources have become important factors for companies, the use of Big Data come into focus new core value of business but researches on the major resources and capabilities of companies are insufficient. In this study, the effect of dynamic capability and entrepreneurial orientation in the SMEs on the intention of Big Data utilization are explored. For the purpose of empirical analysis, the survey condusted of 364 domestic SMEs to analyze the effect of dynamic capability on the intention of Big Data utilization through entrepreneurial orientation, performed a parallel multi-parameter analysis of using SPSS Win Ver.22.0 and PROCESS macro v3.0. The results of hypothesis testing showing that dynamic resources and entrepreneurial orientation had positive influence intention of big data utilization. For the determinants of Big Data utilization related to AI it provide suggestions thereby improving the understanding of dynamic capabilities and entrepreneurial orientation and helping to improve the management of SMEs.