• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.213-215
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• 2007

This paper introduces an emotional behavior decision model for intelligent service robots. An emotional model should make different behavior decisions according to the purpose of the robots. We propose an emotional behavior decision model which can change the character of emotional model and make different behavior decisions although the situation and environment remain the same. We defined each emotional element such as reactive dynamics, internal dynamics, emotional dynamics, and behavior dynamics by state dynamic equations. The proposed system model is a linear system. If you want to add one external stimulus or behavior, you need to add just one dimensional vector to the matrix of external stimulus or behavior dynamics. The case of removing is same. The change of reactive dynamics, internal dynamics, emotional dynamics, and behavior dynamics also follows the same procedure. We implemented the proposed emotional behavior decision model and verified its performance.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.5
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• pp.450-457
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• 2004

In this research, the automatic synthesis of knowledge models is proposed. which are the basis of the methods using qualitative models adapted widely in fault diagnosis and hazard evaluation of chemical processes. To provide an easy and fast way to construct accurate causal model of the target process, the Role-Behavior modeling method is developed to represent the knowledge of modularized process units. In this modeling method, Fault-Behavior model and Structure-Role model present the relationship of the internal behaviors and faults in the process units and the relationship between process units respectively. Through the multiple modeling techniques, the knowledge is separated into what is independent of process and dependent on process to provide the extensibility and portability in model building, and possibility in the automatic synthesis. By taking advantage of the Role-Behavior Model, an algorithm is proposed to synthesize the plant-wide causal model, Fault-Causality Graph (FCG) from specific Fault-Behavior models of the each unit process, which are derived from generic Fault-Behavior models and Structure-Role model. To validate the proposed modeling method and algorithm, a system for building FCG model is developed on G2, an expert system development tool. Case study such as CSTR with recycle using the developed system showed that the proposed method and algorithm were remarkably effective in synthesizing the causal knowledge models for diagnosis of chemical processes.

• Journal of Korean Academy of Nursing
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• v.41 no.2
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• pp.204-213
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• 2011

Purpose: This study was done to identify fundamental data on competency reinforcement programs to prevent adolescent risk behavior by developing and examining a competency model. Methods: In this study, competences on prevention of adolescent risk behavior were identified through competency modeling, and a competency model was developed and tested for validity. Results: Competences for prevention of adolescent risk behavior defined by the competency model included the following: self-control, positive mutual understanding between parents and adolescents, and positive connectedness with peer group. Validation of the competency model showed the model to be appropriate. Conclusion: The competency model for prevention of adolescent risk behavior through competency modeling is expected to be the foundation of an integral approach to enhance competency in adolescents and prevent adolescent risk behavior. This kind of approach can be a school-centered, cost-efficient strategy, which not only reduces adolescent risk behavior but also improves quality of adolescent resources.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.8
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• pp.760-768
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• 2007

This paper introduces an emotional behavior decision model based on linear system for intelligent service robots. An emotional model should make different behavior decisions according to the purpose of the robots. We propose an emotional behavior decision model which can change the character of intelligent service robots and make different behavior decisions although the situation and environment remain the same. We defined each emotional element such as reactive dynamics, internal dynamics, emotional dynamics, and behavior dynamics by state dynamic equations. The proposed system model is a linear dynamic system. If you want to add one external stimulus or behavior, you need to add just one dimensional vector to the matrix of external stimulus or behavior dynamics. The case of removing is same. The change of reactive dynamics, internal dynamics, emotional dynamics, and behavior dynamics also follows the same procedure. We implemented a cyber robot and an emotional head robot using 3D character for verifying the performance of the proposed emotional behavior decision model.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.570-592
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• 2019

The Event-B design pattern is an excellent way to quickly develop a formal model of the system. Researchers have proposed a number of Event-B design patterns, but they all lack formal behavior semantics. This makes the analysis, verification, and simulation of the behavior of the Event-B model very difficult, especially for the control-intensive systems. In this paper, we propose a novel method to transform the Event-B synchronous control flow design pattern into the labeled transition system (LTS) behavior model. Then we map the design pattern instantiation process of Event-B to the instantiation process of LTS model and get the LTS behavior semantic model of Event-B model of a multi-level complex control system. Finally, we verify the linear temporal logic behavior properties of the LTS model. The experimental results show that the analysis and simulation of system behavior become easier and the verification of the behavior properties of the system become convenient after the Event-B model is converted to the LTS model.

• Korea Journal of Hospital Management
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• v.11 no.4
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• pp.37-62
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• 2006

This study investigates the antecedents of knowledge sharing behavior focusing on the individual level factors in an assumption that the behavior is initiated from the individual level decisions. A hypothesis that the relation between personality trait and behavior is mediated by the social-cognitive constructs contained in the Theory of Planned Behavior(TPB) is tested. For the study, we suggest a TPB extended model that extends original TPB model by including conscientiousness facet of FFM(Five Factor Model). This study uses a cross-sectional design. Data were collected from a self-reported survey on 197 nurses in a tertiary hospital. The results showes a significant positive relationship between the conscientiousness facet of FFM and knowledge sharing behavior. In the TPB extended model, the conscientiousness facet has significant direct effects on all the constructs of original TPB model. Of the TPB exogenous constructs, the social norm construct alone has a significant effect on intention and the perceived behavioral has a direct significant effect on the knowledge sharing behavior. These results confirm the importance of conscientiousness in predicting knowledge sharing behavior and clarify the characteristics of knowledge sharing behavior as a contextual, job oriented behavior in a workplace. We conclude that personality trait as conceptualized in the FFM needs to be integrated into TPB model in explaining the knowledge sharing behavior. Based on these results theoretical and practical implications are discussed.

• Culinary science and hospitality research
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• v.14 no.2
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• pp.205-214
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• 2008

The purpose of this study was to measure the moderating effect of belief homogeneity on the relation-ships among attitudinal ambivalence, behavior intention and consumption behavior. The questionnaire, which consisted of items to measure the constructs of belief homogeneity, attitudinal ambivalence, behavior intention and consumption behavior, were completed by 338 subjects in Jeonnam area. Moderated regression analysis was used to measure the moderating effect of belief homogeneity. To test validity and reliability of constructs, factor analysis and Cronbach's $\alpha$ were used in this study. Results of the study demonstrated that the moderated regression analysis result for the data also indicated a better model fit in Model 2 than Model 1. In the Model 1, the main effects of behavior intention and attitudinal ambivalence on consumption behavior were statistically significant. In the Model 2, the main effects of behavior intention, belief homogeneity and attitudinal ambivalence on consumption behavior were statistically significant. The interactional effects of belief homogeneity$\times$attitudinal ambivalence on consumption behavior were statistically significant. Moreover, the effects of attitudinal ambivalence on consumption behavior were statistically significant at all levels of belief homogeneity, except for when homogeneity was high.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.9_10 s.146
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• pp.1285-1294
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• 2005

This study was fulfilled in the purpose of proposing construction strategies of Internet shopping-mall through the analysis of consumer moving line in Internet shopping-mall. This study was executed in two stages: theoretical study, qualitative study. In the theoretical study, hypothetical Internet shopping behavior model were constructed. Five internet shopping behavior types of apparel : purchase, searching purchase, prepurchase deliberation, information accumulation, opinion leadership and recreation were constructed. Next, consumer decision process were extracted from previous studies and a hypothetical internet shopping behavior model was constructed on the base of consumer decision process and Internet shopping behavior types. And then, through the qualitative study, Internet shopping behavior types were identified and hypothetical model was confirmed after adjustment. For qualitative study, 30 subjects were sampled by focus sampling and investigated by in-depth interview and observation. Seven internet shopping behavior types of apparel were found by the qualitative study: cautious purchase by price comparison, searching purchase, special low price purchase, impulse purchase, prepurchase deliberation, information accumulation and recreation-oriented. On the base of these behavior types, Internet shopping behavior model was adjusted and completed. Finally, according to the results of this study, Internet shopping construction methods that made customer's loyalty high and marketing strategy of Internet shopping-mall were proposed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.1
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• pp.64-71
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• 2016

This paper proposes nonlinear behavior in a love model for Romeo and Juliet with an external force of discontinuous time. We investigated the periodic motion and chaotic behavior in the love model by using time series and phase portraits with respect to some variable and fixed parameters. The computer simulation results confirmed that the proposed love model with an external force of discontinuous time shows periodic motion and chaotic behavior with respect to parameter variation.

• Journal of information and communication convergence engineering
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• v.11 no.2
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• pp.95-102
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• 2013

This paper presents a stochastic driver behavior modeling framework which takes into account both individual and general driving characteristics as one aggregate model. Patterns of individual driving styles are modeled using a Dirichlet process mixture model, as a non-parametric Bayesian approach which automatically selects the optimal number of model components to fit sparse observations of each particular driver's behavior. In addition, general or background driving patterns are also captured with a Gaussian mixture model using a reasonably large amount of development data from several drivers. By combining both probability distributions, the aggregate driver-dependent model can better emphasize driving characteristics of each particular driver, while also backing off to exploit general driving behavior in cases of unseen/unmatched parameter spaces from individual training observations. The proposed driver behavior model was employed to anticipate pedal operation behavior during car-following maneuvers involving several drivers on the road. The experimental results showed advantages of the combined model over the model adaptation approach.