• Proceedings of the Korea Society for Simulation Conference
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• 2002.05a
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• pp.211-216
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• 2002

This paper focuses on the measurement of increased work efficiency expected from the information system through random interactions of the organizational behavioral factors whose attributes can be changed with the implementation of the information systems. Specifically the work reported here is concerned with modeling and analyzing the random interrelationships among the organizational behavioral factors which an information system will have impact on throughout the time horizon of its implementation in terms of office productivity. In addition, it is also concerned with developing a multi-factor analysis model based on random interactions to be used to assess the impact of information systems.

• Journal of the Korea Society for Simulation
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• v.9 no.4
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• pp.1-10
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• 2000

One of the primary goals of the simulation experiments is to understand the overall system behavior and to analyze the system, ultimately to optimize the system. Optimizing the system includes determining the optimum condition of the system parameters of interest. This paper is concerned with the simulation methodology for estimating the unknown objective function for the system of interest and optimizing the system with respect to the controllable factors. In the process of estimating the unknown objective function, which is assumed to be a second order spline function, we use common random numbers for different set of the controllable factors resulting in more accurate parameter estimation for the objective function. We will show some mathematical result for the benefit of using common random numbers.

• Structural Engineering and Mechanics
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• v.36 no.1
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• pp.19-36
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• 2010

The load and resistance factors are generally obtained using the First Order Reliability Method (FORM), in which the design point should be determined and derivative-based iterations have to be used. In this paper, a simple method for estimating the load and resistance factors using the first four moments of the basic random variables is proposed and a simple formula for the target mean resistance is also proposed to avoid iteration computation. Unlike the currently used method, the load and resistance factors can be determined using the proposed method even when the probability density functions (PDFs) of the basic random variables are not available. Moreover, the proposed method does not need either the iterative computation of derivatives or any design points. Thus, the present method provides a more convenient and effective way to estimate the load and resistance factors in practical engineering. Numerical examples are presented to demonstrate the advantages of the proposed fourth moment method for determining the load and resistance factors.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.3
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• pp.1147-1152
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• 2012

In this paper, it is key issue about analysis of characteristics processing of digital random output stream of hardware random number generator, which is applied in medical area. The output stream of random number generator based on hardware binary random number is effected from factors such as delay, jitter, temperature, and so on. In this paper, it presents about major factor, which effects hardware output random number stream, and the randomness of output stream data, which are combined output stream and postprocessing data such as encryption algorithm, encoding algorithm, is analyzed. the analyzed results are evaluated by major test items of randomness.

• The Journal of Fisheries Business Administration
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• v.51 no.1
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• pp.81-96
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• 2020

The purpose of this paper is to analyze factors affecting the net income of regional and industrial fisheries cooperatives in South Korea using panel data. This paper utilizes linear or GLS regression models such as pooled OLS model, fixed effects model, and random effects model to estimate affecting factors of the net income of regional and industrial fisheries cooperatives. After reviewing various tests, we eventually select random effects model. The results, based on panel data between 2013 and 2018 year and 64 fisheries cooperatives, indicate that capital and area dummy variables have positive effects and employment has negative effect on the net income of regional and industrial fisheries cooperatives as predicted. However, debt are opposite with our predictions. Specifically, it turns out that debt has positive effect on the net income of regional and industrial fisheries cooperatives although it has been increased. Additionally, this paper shows that the member of confreres does not show any significant effect on the net income of regional and industrial fisheries cooperatives in South Korea. This study is significant in that it analyzes the major factors influencing changes in the net income that have not been conducted recently for the fisheries cooperatives by region and industry.

• Journal of Korea Planning Association
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• v.54 no.5
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• pp.129-138
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• 2019

This study aims to empirically examine the relationship between building energy consumption and building and local factors in Seoul. Building energy issue is an important topic for low carbon and eco-friendly city development. Building physical, socio-economic and environmental factors effect to increasing or decreasing energy consumption. However, there are different characteristic in each area, and this kind of variable has a hierarchical structure. The multi-level model was used to consider the hierarchical structure of the variables. In this study, a multi-level model was applied to confirm the difference between areas. Spatial area is Seoul, Korea and the temporal scope is August, summer season. As the result, in Model 1 (Null Model), ICC is 0.817. This shows that the energy consumption differs by 8.174% due to factors at the Dong level. Model 2 (Random Intercept Model) suggests that building's physical factors and Average age, Household size and Land price in Dong level have significant effects on Building energy consumption. In Model 3 (Random Coefficient Model), random effect variables have intercepts and slopes to vary across groups. This study provides a perspective for policy makers that the building energy reduction policies to be applied for buildings should be differently applied on area. Furthermore, not only physical factors but also socio-economic and environmental factors are important when making energy reduction policy.

• 한국데이터정보과학회:학술대회논문집
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• 2004.04a
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• pp.121-126
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• 2004

This paper discusses about how to build up a mixed-effects model using cumulative logits when there are some factors are fixed and others are random. Random factors are assumed to be coming from a two-way nested design for choosing individuals or experimental units to apply treatments. Estimation procedure for the unknown parameters in a suggested model is also discussed by an illustrated example.

• Proceedings of the Safety Management and Science Conference
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• 2011.04a
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• pp.95-99
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• 2011

The research analyzes structure models of Repeated Measurement Design (RMD) and Hierarchical Design (HD). The experimental unit of RMD model is living organisms, such as human. In contrast, HD is used when all the factors are random. The HD models are derived from R:B:A, R:C:B:A and R:C:($A{\times}B$).

• The Transactions of the Korean Institute of Power Electronics
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• v.22 no.1
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• pp.67-74
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• 2017

This study proposes a novel random pulse-width modulation (PWM) technique with a constant switching frequency utilizing a random offset voltage. The proposed PWM technique spreads switching harmonics by varying the position of an active voltage vector without a switching frequency variation. The implementation of the proposed PWM technique is simple because it does not require additional hardware and complex algorithm. The proposed random PWM technique is compared with the conventional PWM technique on the factors of harmonic spectrum, total harmonic distortion, and harmonic spread factor to confirm the harmonic spread effect. The validity of the proposed method is verified by simulations and experiments on a three-phase inverter drive system.

• Communications for Statistical Applications and Methods
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• v.25 no.3
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• pp.275-282
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• 2018

This paper discusses the use of projections for the sums of squares in the analyses of variance for two-way nested design data. The model for this data is assumed to only have random effects. Two different sizes of experimental units are required for a given experimental situation, since nesting is assumed to occur both in the treatment structure and in the design structure. So, variance components are coming from the sources of random effects of treatment factors and error terms in different sizes of experimental units. The model for this type of experimental situation is a random effects model with more than one error terms and therefore estimation of variance components are concerned. A projection method is used for the calculation of sums of squares due to random components. Squared distances of projections instead of using the usual reductions in sums of squares that show how to use projections to estimate the variance components associated with the random components in the assumed model. Expectations of quadratic forms are obtained by the Hartley's synthesis as a means of calculation.