• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.91-94
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• 2005

A numerical formula that presents relationship between a point of a satellite image and its ground position is called a sensor model. For precise geolocation of satellite images, we need an error-free sensor model. However, the sensor model based on GOES ephemeris data has some error, in particular after Image Motion Compensation (IMC) mechanism has been turned off. To solve this problem, we investigate three sensor models: Collinearity model, Direct Linear Transform (DLT) model and Orbit-based model. We apply matching between GOES images and global coastline database and use successful results as control points. With control points we improve the initial image geolocation accuracy using the three models. We compare results from three sensor models that are applied to GOES-9 images. As a result, a suitable sensor model for precise geolocation of GOES-9 images is proposed.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2006년도 추계학술대회
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• pp.169-172
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• 2006

Most studies using state-space models have been conducted under the assumption of independently distributed noises in measurement and state equation without adequate verification of the assumption. To avoid the improper use of state-space model, testing the assumption prior to the parameter estimation of state-space model is very important. The purpose of this paper is to investigate the general relationship between parameters of state-space models and those of ARIMA processes. Under the assumption, we derive restricted parameter spaces of ARIMA(p,0,p-1) models with mutually different AR roots where $p\;{\le}\;5$. In addition, the results of ARIMA(p,0,p-1) case can be expanded to more general ARIMA models, such as ARIMA(p-1,0,p-1), ARIMA(p-1,1,p-1), ARIMA(p,0,p-2) and ARIMA(p-1,1,p-2).

• 대한교통학회지
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• 제8권1호
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• pp.55-71
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• 1990

The behavioral mechanism underlying the traffic assignment model is a choice, or decision-making process of traveling paths between origins and destinations. The deterministic approach to traffic assignment assumes that travelers choose shortest path from their origin-destination pair. Although this assumption seems reasonable, it presumes that all travelers have perfect information regarding travel time, that they make consistently correct decision, and that they all behave in identical fashion. Stochastic user equilibrium assignment relaxes these presumptions by including a random component in traveler's perception of travel time. The objective of this study is to compare "A Model of Deterministic User Equilibrium Assignment" with "Models of Stochastic User Equilibrium Assignment" in the theoretical and practical aspects. Specifically, SUE models are developed to logit and probit based models according to discrete choice functions. The models were applied to sioux Falls net ork consisting of 24 zones, 24 nodes and 76 links. The distribution of perceived travel time was obtained by using the relationship between speed and traffic flow.

• Journal of Information Processing Systems
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• 제18권2호
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• pp.268-281
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• 2022

The development of information technology is bringing many changes to everyday life, and machine learning can be used as a technique to solve a wide range of real-world problems. Analysis and utilization of data are essential processes in applying machine learning to real-world problems. As a method of processing data in machine learning, we propose an approach based on applying multiple linear regression models by interlacing data to the task of classifying similar software. Linear regression is widely used in estimation problems to model the relationship between input and output data. In our approach, multiple linear regression models are generated by training on interlaced feature data. A combination of these multiple models is then used as the prediction model for classifying similar software. Experiments are performed to evaluate the proposed approach as compared to conventional linear regression, and the experimental results show that the proposed method classifies similar software more accurately than the conventional model. We anticipate the proposed approach to be applied to various kinds of classification problems to improve the accuracy of conventional linear regression.

• 한국경영과학회지
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• 제23권2호
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• pp.103-129
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• 1998

Corporate level decision making with multiple decision makers in a consistent way is essential in Decision Support System. However, since the decision makers have different interests and knowledge, the models used by them are also different in their level of abstraction. This makes decision makers waste a lot of efforts for an integrated decision making. The purpose of this paper is to propose an integration mechanism so that collaborative decision making models may be used synthetically in multi-abstraction level. Models are classified as multimedia model, mathematical model, qualitative model, causal ＆ directional model, causal model, directional model and relationship model according to the level of abstraction. The proposed integration mechanism consists of model interpretation phase. model transformation phase, and model integration phase. Specifically, the model transformation Phase is divided into (1) model tightening mode which gather information to make a model transformed into upper level model, and (2) model relaxing mode which makes lower level model. In the model integration phase, models of same level are to be integrated schematically. An illustrative M＆A-decision example is given to show the possibility of the methodology.

• Communications for Statistical Applications and Methods
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• 제13권3호
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• pp.755-764
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• 2006

Most graphical methods for categorical data can describe the structure of data and represent a measure of association among categorical variables. Among them the polyhedron plot represents sequential relationships among hierarchical log-linear models for a multidimensional contingency table. This kind of plot could be explored to describe the differences among sequential models. In this paper we suggest graphical methods, containing all the information, that reflect the relationship among all log-linear models in a certain hierarchical structure. We use the ideas of a correlation diagram.

• 제어로봇시스템학회논문지
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• 제22권3호
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• pp.177-185
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• 2016

This paper presents a method to design a controller for active suspension with 1-DOF decoupled models. Three 1-DOF decoupled models describing vertical, roll and pitch motions are used to design a controller in order to generate a vertical force, roll and pitch moments, respectively. These control inputs are converted into active suspension forces with geometric relationship. To design a controller, a sliding mode control is adopted. Frequency domain analysis and simulation on vehicle simulation software, CarSim$^{(R)}$, show that the proposed method is effective for ride comfort.

• Communications for Statistical Applications and Methods
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• 제16권1호
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• pp.21-29
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• 2009

Engle과 Russell (1998)의 ACD 모형은 재무학에서 가격과 거래 시간의 밀접한 관계에 대한 관심을 불러 일으켰다. ACD 모형은 GARCH 모형과의 유사성을 바탕으로 Box-Cox 변환과 충격 함수 곡선(shocks impact curve)을 적용시켜 Log ACD, Power ACD, Box-Cox ACD 등과 같은 보다 유연한 모형으로 일반화될 수 있다. 본 연구에서는 이와 같이 일반화된 ACD 모형들을 국내 주식시장에서 거래되고 있는 주식의 price duration에 적용시켜 그 성능을 비교해보고자 한다.

• 기술혁신학회지
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• 제5권2호
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• pp.129-140
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• 2002

This study is try to do the empirical tests on the relationship among innovation cycle, investment cycle, and business cycle suggested in recent economic growth models. We apply co-spectra analysis to estimate dynamic correlations in the extraction HP filtered variables and first difference filtered variables in our data set. Our empirical results are; (i) an existing asynchronization between innovation cycle and investment cycle, (ii) in the long frequency, an existing positive correlation between innovation cycle and business cycle, (iii) in the short frequency, however, a finding the high negative correlation between the two cycle. Our empirical findings support the recent growth through cycle models and suggest some economic policy implementations for economic stabilization during a severe business cycle.

• 한국방재학회 논문집
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• 제8권2호
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• pp.97-103
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• 2008

Determination of stress-strain relationship in torsional tests is complicated due to nonuniform stress-strain variation occurring linearly with the radius in a soil specimen in torsion. The equivalent radius approach is adequate when calculating strain at low to intermediate strains, however, the approach is less accurate when performing the test at higher strain levels. The modified equivalent radius approach was developed to account for the problem more precisely. This approach was extended to generate the plots of equivalent radius ratio versus strain using modified hyperbolic and Ramberg-Osgood models. Results showed the effects of soil nonlinearity on the equivalent radius ratio curves were observed. Curve fitting was also performed to find the stress-strain relationship by fitting the theoretical torque-rotation relationship to measured torque-rotation relationship.