• Proceedings of the Korea Society for Simulation Conference
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• 2001.05a
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• pp.31-35
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• 2001

Simulation --- The ideal tool for BPR. Work now and CASE tools are static modeling tools. Based on our own customers surveys, we have discovered that the use of process modeling tools thus far has focused on modeling the current(What-Is) state of a business. We have found that 90 percent of reengineering projects, the modeling tools of choice have been flowcharting tools. Static models offer help in understanding the overall nature of an existing process. However, static models can not really help you see the step by step motions towards completion of your goals. In static modeling, you see two pictures in time, usually taken at the current state and final state models of your reengineering project. Static models are usually not object oriented, therefore can not show facility or office layout and movement of entities and objects throughout the facility. However, this does not mean that static modeling does not have its application nor add value to the user as in a few success stories. Simulation helps the team analyze the complex aspects of the project. Many times a plan that looks good on paper might turn out entirely different when put into action. Therefore, simulation helps you look at how situations might work before actual implementation. In particular, computer simulation models help you view a reengineered condition before they are rolled-out. Items such as a lead time and resource allocation.

• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.825-835
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• 2008

Multivariate GARCH(MGARCH) has been useful in financial studies and econometrics for modeling volatilities and correlations between components of multivariate time series. An obvious drawback lies in that the number of parameters increases rapidly with the number of variables involved. This thesis tries to resolve the problem by using dimension reduction technique. We briefly review both factor models for dimension reduction and the MGARCH models including EWMA (Exponentially weighted moving-average model), DVEC(Diagonal VEC model), BEKK and CCC(Constant conditional correlation model). We create meaningful portfolios obtained after reducing dimension through statistical factor models and fundamental factor models and in turn these portfolios are applied to MGARCH. In addition, we compare portfolios by assessing MSE, MAD(Mean absolute deviation) and VaR(Value at Risk). Various financial time series are analyzed for illustration.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.1
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• pp.105-120
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• 1992

An expert system was developed as a framework of integrating diverse and multifactored ergonomic knowledge to investigate its effectiveness in ergonomic workplace design and evolution. Although numerous computer-assisted approaches have been made to overcome the lack of integrated design principles, those models being used require very specific information of various design activities that may not be available in the design stage. On the other hand, an expert system would be an effective design aid that is capable of guiding the designer to solve a problem. However, most expert systems lack detailed evaluation capabilities due to a qualitative nature of inference mechanisms. Furthermore, those approaches were independently developed, focusing mostly on a single aspect such as biomechanics, physiology, etc. In this paper, a design framework was developed which takes advantage of expert system metholologies, a relational data base and existing ergonomic models. The pattern-directed, rule-based expert system allows the designer to gradually formulate and subsequently evaluate workplace design. A comprehensive and modularized knowledge base was built incorporating biomechanics, physiology and psychophysics, which is, in turn, capable of accessing not only qualitative knowledge but complex analytic evaluation models and massive information in the data base through an interface. A conflict resolution strategy using multiple criteria decision-making schemes was also employed to reconcile multiple design alternatives.

• Journal of Family Relations
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• v.22 no.3
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• pp.29-46
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• 2017

Objectives: The purpose of this study was to investigate a role of self-compassion in conflict resolution strategies among dating couples. Further, we examined conflict resolution strategies as mechanisms to explain in the relationship between self-compassion and relationship satisfaction. Method: Two hundred forty two dating couples were recruited. Actor and Partner Independence Model(APIM) was used to examine actor and partner effects of self-compassion on relationship satisfaction as well as conflict resolution strategies. The total of 4 APIMs, two positive conflict resolution strategies(i.e., positive emotional reactions, active coping) and two negative conflict resolution strategies(i.e., negative emotional reactions and hostility, avoidance) were analyzed. Positive conflict resolution strategies had only actor effect in the link between self-compassion and relationship satisfaction. That is, self-compassionate men and women were more likely to use positive conflict resolution strategies and, in turn, led to their higher relationship satisfaction. Both actor and partner effects were found in the negative conflict resolution strategy models. In terms of actor effect self-compassionate men and women were less likely to use negative conflict resolution strategies and that, in turn, led to their higher relationship satisfaction. In terms of partner effects we found that women's negative emotional reactions and hostility mediated the link between women's self-compassion and their male partners' relationship satisfaction. Men's avoidance mediated the link between men's self-compassion and their female partners' relationship satisfaction.

• Journal of Korean Society of Transportation
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• v.11 no.1
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• pp.67-86
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• 1993

A formulation of dynamic traffic assignment between multiple origins and single destination was first introduced in 1987 by Merchant and Nemhauser, and then expanded for multiple destination in the late 1980's (Carey, 1987). Based on behavioral choice theory which provides proper demand elasticities with respect to changes in policy variables, traffic phenomena can be analysed more realistically, especially in peak periods. However, algorithms for these models are not well developed so far(working with only small toy network) and solutions of these models are not unique. In this paper, a new model is developed which keeps the simplicity of static models, but provides the sensitivity of dynamic models with changes of O-D flows over time. It can be viewed as a joint departure time and route choice model, in the given time periods(6-7, 7-8, 8-9 and 9-10 am). Standard multinomial logit model has been used for simulating the choice behavior of destination, mode, route and departure time within a framework of the incremental network assignment model. The model developed is workable in a PC 386 with 175 traffic zones and 3581 links of Seoul and tested for evaluating the exclusive use of Namsan tunnel for HOV and the left-turn prohibition. Model's performance results and their statistical significance are also presented.

• Journal of Korean Society of Transportation
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• v.7 no.1
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• pp.35-42
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• 1989

The multinomial logit model has been applied for various choice problems. Among others, the joint destination mode choice, the mode choice and the route choice are the three major modeling topics for korean transportation planners. This paper examines with real world data (the Olympic road and its competing two major arterials) the usefulness of a Logit route choice model. Quites surpisingly, it is found that the multinomial route choice behavioral model calibrated for this study based on (0,1) individula data base can not provide a good estimate for O-D trips less than 6㎞. 400data points and 3case studies might not be sufficient for a sound conclusion. It is, however, believed from a series of similar studies conducted by the authors that the route choice behavior is more sensitive (more demand elastic with respect to travel time changes) than the mode choice and the shorter trip, the more sensitive. The travel time parameters for destination choice models are usually smalle than the travel time parameters for mode choice models and these parameters (for mode choice models) turn our smaller than the travel time parameters for route choice models from this study. Table 2 in this paper shows parameter changes for three different markets and Table 3 shows the modeling errors when the estimated individual probabilities are aggregated into a route level.

• Computers and Concrete
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• v.11 no.1
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• pp.1-20
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• 2013

There is an abundance of research on the strengthening of reinforced concrete (RC) structural elements such as beams, columns and slabs with fibre reinforced polymer (FRP) composites. Less research by comparison has been conducted on the strengthening of RC beam-column connections and the majority of such research has been predominantly experimental to date. Few existing experimental studies have reported extensive instrumentation of test specimens which in turn makes understanding the behavior of the connections and especially the contributions made by the FRP difficult to ascertain. In addition, there has been even more limited research on the analytical and numerical modelling of FRP-strengthened connections. In this paper, detailed descriptions of key strategies to model FRP-strengthened RC connections with finite elements are provided. An extensively instrumented and comprehensively documented set of experiments on FRP-strengthened connections is firstly presented and finite element models are then constructed using ANSYS. The study shows that the finite element approach is able to capture the overall behavior of the test specimens including the failure mode as well as the behavior of the FRP which will most importantly lead to a detailed understanding of the FRP and the future development of rational analytical models. The finite element models are, however, unable to model the stiffness of the connections with accuracy in the ultimate load range of response.

• The Korean Journal of Applied Statistics
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• v.34 no.4
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• pp.611-622
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• 2021

With a wide recognition that financial time series typically exhibits asymmetry patterns in volatility so called leverage effects, various asymmetric GARCH(1, 1) processes have been introduced to investigate asymmetric volatilities. A lot of researches have also been directed to non-stationary volatilities to deal with frequent high ups and downs in financial time series. This article is concerned with both asymmetric and non-stationary GARCH-type models. As a subsequent paper of Choi et al. (2020), we review various asymmetric and non-stationary GARCH(1, 1) processes, and in turn propose how to compare competing models using a parametric bootstrap methodology. As an illustration, Dow Jones Industrial Average (DJIA) is analyzed.

• Electronics and Telecommunications Trends
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• v.36 no.3
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• pp.106-118
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• 2021

The field of brain science (or neuroscience in a broader sense) has inspired researchers in artificial intelligence (AI) for a long time. The outcomes of neuroscience such as Hebb's rule had profound effects on the early AI models, and the models have developed to become the current state-of-the-art artificial neural networks. However, the recent progress in AI led by deep learning architectures is mainly due to elaborate mathematical methods and the rapid growth of computing power rather than neuroscientific inspiration. Meanwhile, major limitations such as opacity, lack of common sense, narrowness, and brittleness have not been thoroughly resolved. To address those problems, many AI researchers turn their attention to neuroscience to get insights and inspirations again. Biologically plausible neural networks, spiking neural networks, and connectome-based networks exemplify such neuroscience-inspired approaches. In addition, the more recent field of brain network analysis is unveiling complex brain mechanisms by handling the brain as dynamic graph models. We argue that the progress toward the human-level AI, which is the goal of AI, can be accelerated by leveraging the novel findings of the human brain network.

• Journal of Astronomy and Space Sciences
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• v.18 no.3
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• pp.175-190
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• 2001

We investigated population of the elliptical galaxy NGC 4649 using the spectral synthesis technique based on the linear program in the spectral regions between $3160\AA$to $10800\AA$. We used the spectral data of stars obtained by Gunn & Striker (1983), and the integrated spectrum of NGC 4649 observed by Bertola et al. (1982). Among four models with different main sequence turn-off points, G8-K0V main sequence turn-off model is best fitted to the integrated spectrum of NGC 4649. We also found that super metal rich K giants are needed to describe the absorption lines in the long wavelength regions of integrated spectrum of NGC 4649. The mass to absolute light ratio obtained from the spectral synthesis is ~ 20 similar to those calculated dynamically.