• Structural Engineering and Mechanics
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• v.60 no.4
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• pp.655-665
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• 2016

This paper aims to develop models to accurately predict the behavior of fresh concrete exposed to vibration using artificial neural networks (ANNs) model and regression model (RM). For this purpose, behavior of a full scale precast concrete mold was investigated experimentally and numerically. Experiment was performed under vibration with the use of a computer-based data acquisition system. Transducers were used to measure time-dependent lateral displacements at some points on mold while both mold is empty and full of fresh concrete. Modeling of empty and full mold was made using both ANNs and RM. For the modeling of ANNs: Experimental data were divided randomly into two parts. One of them was used for training of the ANNs and the remaining part was used for testing the ANNs. For the modeling of RM: Sinusoidal regression model equation was determined and the predicted data was compared with measured data. Finally, both models were compared with each other. The comparisons of both models show that the measured and testing results are compatible. Regression analysis is a traditional method that can be used for modeling with simple methods. However, this study also showed that ANN modeling can be used as an alternative method for behavior of fresh concrete exposed to vibration in precast concrete structures.

• Korean Journal of Child Studies
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• v.11 no.1
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• pp.87-99
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• 1990

The present study was designed to investigate the effect of altruistic TV viewing and verbal training on the altruistic behavior of preschoolers. The subjects of this study were a total of 56 boys and 57 girls from a kindergarten in Kwachon, Kyung-gi do. The subjects were assigned to one of three conditions: in the first condition subjects were shown video tapes designed to portray prosocial themes (TV modeling group) ; in the second condition subjects saw the video tapes in addition to verbal training (TV modeling plus verbal training group); in the third condition subjects received neither TV modeling nor verbal training (control group). Statistical analysis was by ANOVA and $Scherr\acute{e}$ test. Significant differences were found in altruistic behavior between the TV modeling and the TV modeling with verbal training groups.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.179-184
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• 2005

Recently, studying on modeling the emotion of a robot has become issued among fields of a humanoid robot and an interaction of human and robot. Especially, modeling of the motivation, the emotion, the behavior, and so on, in the robot, is hard and need to make efforts to use our originality. In this paper, new modeling using mathematical formulations to represent the emotion and the behavior selection is proposed for the software robot with virtual sensor modules. Various Points which affect six emotional states such as happy or sad are formulated as simple exponential equations with various parameters. There are several experiments with seven external sensor inputs from virtual environment and human to evaluate this modeling.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.37-42
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• 2006

Recently, studying on modeling the emotion of a robot has become issued among fields of a humanoid robot and an interaction of human and robot. Especially, modeling of the motivation, the emotion, the behavior. and so on, in the robot, is hard and need to make efforts to use ow originality. In this paper, new modeling using mathematical formulations to represent the emotion and the behavior selection is proposed for the software robot with virtual sensor modules. Various points which affect six emotional states such as happy or sad are formulated as simple exponential equations with various parameters. There are several experiments with seven external sensor inputs from virtual environment and human to evaluate this modeling.

• Journal of the Korea Society for Simulation
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• v.6 no.1
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• pp.15-24
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• 1997

VRML (Virtual Reality Modeling Language) is an Web-based standard for modeling 3D spaces and provides applications with 3D interactive interfaces. With its recent upgrade, it supports events, routes, scripts, and other behavior modeling constructs. This paper approaches VRML as a simulation modeling language. This approach promotes the sharing and distribution of simulation results and demonstration among distributed users as well as efficient modeling of systems through the direct mapping of 3D objects and behaviors. This paper analyzes the behavior modeling constructs of VRML, presents effective modeling alternatives through the modeling of a simple material processing system, and discusses the upgrade direction of VRML as a foundation for distributed interactive simulation system.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.2
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• pp.354-362
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• 1995

The finite element modeling is used to study the buckling and postbuckling behavior of composite laminates with an embedded delamination. Degenerated shell element and rigid beam element are utilized for the finite element modeling. In the nonlinear finite element formulation, the updated Lagrangian description method based on the second Piola-Kirchhoff stress tensor and the Green strain tensor is used. The buckling and postbuckling behavior of composite laminates with a delamination are investigated for various delamination sizes, stacking sequences, and boundary conditions. It is shown that the buckling load and postbuckling behavior of composite laminates depend on the buckling model which is determined by the delamination size, stacking sequence and boundary condition. Also, results show that introduction of couplings can reduce greatly the buckling load.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.591-597
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• 2001

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). Immune system is living body's self-protection and self-maintenance system. These features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For applying immune system to DARS, a robot is regarded as a B-cell, each environmental condition as an antigen, a behavior strategy as an antibody and control parameter as a T-cell respectively. The executing process of proposed method is as follows. When the environmental condition changes, a robot selects an appropriate behavior strategy. And its behavior strategy is stimulated and suppressed by other robot using communication. Finally much stimulated strategy is adopted as a swarm behavior strategy. This control school is based on clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy. By T-cell modeling, adaptation ability of robot is enhanced in dynamic environments.

• Computers and Concrete
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• v.12 no.4
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• pp.443-498
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• 2013

A detailed finite element modeling is presented for the simulation of the nonlinear behavior of reinforced concrete structures which manages to predict the nonlinear behavior of four different experimental setups with computational efficiency, robustness and accuracy. The proposed modeling method uses 8-node hexahedral isoparametric elements for the discretization of concrete. Steel rebars may have any orientation inside the solid concrete elements allowing the simulation of longitudinal as well as transverse reinforcement. Concrete cracking is treated with the smeared crack approach, while steel reinforcement is modeled with the natural beam-column flexibility-based element that takes into consideration shear and bending stiffness. The performance of the proposed modeling is demonstrated by comparing the numerical predictions with existing experimental and numerical results in the literature as well as with those of a commercial code. The results show that the proposed refined simulation predicts accurately the nonlinear inelastic behavior of reinforced concrete structures achieving numerical robustness and computational efficiency.

• Computers and Concrete
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• v.30 no.3
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• pp.209-224
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• 2022

In this paper, the artificial neural network (ANN) is employed to predict the flexural behavior of reinforced concrete (RC) beams retrofitted with carbon fiber/epoxy composites modified by carbon nanotubes (CNTs). Multiple techniques are used to improve the accuracy of the ANN prediction, as the data represents a multivalued function. These techniques include static ANN modeling, ANN modeling with load history, and ANN modeling with double load history. The developed ANN models are used to predict the load-displacement profiles of beams retrofitted with either CFRP or CNTs modified CFRP, flexural capacity, and maximum displacement of the beams. The results demonstrate that the ANN is able to predict the flexural behavior of the retrofitted RC beams as well as the effect of each parameter including the type of the used epoxy and the presence of the CNTs.

• Journal of Information Processing Systems
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• v.8 no.1
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• pp.55-66
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• 2012

This paper presents a dual modeling method that simulates the graphic and haptic behavior of a volumetric deformable object and conveys the behavior to a human operator. Although conventional modeling methods (a mass-spring model and a finite element method) are suitable for the real-time computation of an object's deformation, it is not easy to compute the haptic behavior of a volumetric deformable object with the conventional modeling method in real-time (within a 1kHz) due to a computational burden. Previously, we proposed a fast volume haptic rendering method based on the S-chain model that can compute the deformation of a volumetric non-rigid object and its haptic feedback in real-time. When the S-chain model represents the object, the haptic feeling is realistic, whereas the graphical results of the deformed shape look linear. In order to improve the graphic and haptic behavior at the same time, we propose a dual modeling framework in which a volumetric haptic model and a surface graphical model coexist. In order to inspect the graphic and haptic behavior of objects represented by the proposed dual model, experiments are conducted with volumetric objects consisting of about 20,000 nodes at a haptic update rate of 1000Hz and a graphic update rate of 30Hz. We also conduct human factor studies to show that the haptic and graphic behavior from our model is realistic. Our experiments verify that our model provides a realistic haptic and graphic feeling to users in real-time.