• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.773-780
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• 1999

In this paper, we explore a behavioral animation of artificial birds that have lived by doing an aggregate motion. We first model individual birds and then propose a behavioral model for an aggregate motion of a flock of birds. In order to represent realistically collision avoidance and flock centering among birds, which are necessary properties in a flock of birds, we consider motive of a flock of birds, and role, velocity, momentum, banking and internal characteristics of each bird. The paper presents the simulation result of the proposed model for a flock of 100 birds.

• Journal of the Korea Society of Computer and Information
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• v.21 no.10
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• pp.21-28
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• 2016

The aim of this research is to analyze Perceived Usefulness(PU) and Perceived Ease of Use(PEOU) based on Technology Acceptance Model in , and how viewing experiences and knowledge of motion graphics have an impact on attitude toward using and behavioral intention to use. Both usability for learning and usability for appreciation in terms of PU have significant correlations with the degree of satisfaction and immersion, and behavioral intention to use. On the other hand, PEOU has an influence on degree of exhibition satisfaction and immersion, and onto behavioral intention to use with the exception of intention to revisiting . Unlike PU or PEOU, previous viewing experiences do not have correlation with attitude toward using and behavioral intention to use. Only previous knowledge of motion graphics has a correlation with degree of satisfaction and immersion, and behavioral intention to use. As the influence on PU and PEOU's attitude toward using and and behavioral intention to use has been verified, our findings show that two variables of TAM enable the prediction of user's technology acceptance on digital exhibitions and as a result prove the suitability for TAM as an evaluation model for digital exhibition of remediating the originals. This study offers a fresh understanding of the importance of motion graphic effects which influence attitude toward using and behavioral intention to use from the perspective of curating methodology.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.477-481
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• 2010

In this paper, we try to classify behavior patterns of a person around a bed based on a wireless sensor network system. We define five behavioral patterns and three states of a person around a bed which is described by a state machine. We collected data sensed by motion detection and vibration sensors installed around a bed from which a feature vector was extracted. Based on feature vector corresponding to behavioral patterns and the state machine, we established a model for behavioral patterns. To validate the model, experiments on subjects were performed and the model was fixed. These experimental results revealed that behavior patterns of a person around a bed can be classified well.

• Journal of Integrative Natural Science
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• v.9 no.4
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• pp.281-291
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• 2016

This study examines the causal relationship between adolescent impulsivity, academic procrastination and school adaptability. The main purpose of this study is to confirm the degree of influence among these variables and analyze the causes of school adaptability. In this model, impulsivity and academic procrastination were set as independent variables and school adaptability was set as a dependent variable. Impulsivity of adolescents affects academic procrastination and school adaptability, and academic procrastination will affect school adaptability. As a result of the research, first, it can be seen that adolescents 'cognition impulsivity, motion impulsivity, and unplanned impulsivity have a significant influence on behavioral in adolescents'. Second, adolescents' cognition impulsivity, motion impulsivity, and unplanned impulsivity a significant influence on the cognitive in the adolescents'. Third, adolescents' behavioral, cognitive, and emotional have a significant influence on school adaptability in adolescents' school adaptability. In conclusion, we proposed a policy proposal on school adaptability by deriving meaning to improve adolescents' school adaptability.

• The Journal of Korea Robotics Society
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• v.18 no.2
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• pp.143-154
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• 2023

In this study, a fast motion planning method for the swing motion of a 6x6 wheel-legged robot to traverse large obstacles and gaps is proposed. The motion planning method presented in the previous paper, which was based on trajectory optimization, took up to tens of seconds and was limited to two-dimensional, structured vertical obstacles and trenches. A deep neural network based on one-dimensional Convolutional Neural Network (CNN) is introduced to generate keyframes, which are then used to represent smooth reference commands for the six leg angles along the robot's path. The network is initially trained using the behavioral cloning method with a dataset gathered from previous simulation results of the trajectory optimization. Its performance is then improved through reinforcement learning, using a one-step REINFORCE algorithm. The trained model has increased the speed of motion planning by up to 820 times and improved the success rates of obstacle crossing under harsh conditions, such as low friction and high roughness.

• Journal of Ubiquitous Convergence Technology
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• v.1 no.1
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• pp.53-59
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• 2007

This paper proposes a new group mobility model for wireless communication. The mobility model considers the psychological and sociological behavior of each node and the perception of other nodes for describing interactions among a set of nodes. The model assumes no permanent membership of a group, capable of capturing natural behaviors as fork and join. It emulates a cooperative movement pattern observed in mobile ad hoc networks of military operation and campus, in which a set of mobile stations accomplish a cooperative motion affected by the individual behavior as well as a group behavior. The model also employs a physic model to avoid a sudden stopping and a sharping turning.

• Journal of Biomedical Engineering Research
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• v.20 no.4
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• pp.485-493
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• 1999

Human can generate various posture and motion with nearly 350 muscle pairs. From the viewpoint of mechanisms, the human skeleton mechanism represents great kinematic and dynamical complexity. Physical and behavioral fidelity of human motion requires dynamically accurate modeling and controling. This paper describes a mathematical modeling, and dynamic simulation of human body. The human dynamic model is simplified as a rigid body consisting of 18 actuated degrees of freedom for the real time computation. Complex kinematic chain of human body is partitioned as 6 serial kinematic chains that is, left arm, right arm, support leg, free leg, body, and head. Modeling is developed based on Newton-Euler formulation. The validity of proposed dynamic model, which represents mathematically high order differential equation, is verified through the dynamic simulation.

• Journal of the Society of Naval Architects of Korea
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• v.40 no.2
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• pp.41-48
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• 2003

The human behavior is very important in development of simulation system for evacuation analysis. The walking speed of passenger is especially affected by dynamic effect and list due to damage and ship motion in wave. There are various methods to get an useful data for evacuation simulation. The onboard experimental approach is one of the most strong method. In this paper, the onboard experiment is performed to obtain human behavioral data. To realize ship trim and heel due to maritime casuality, the passage model for experiment is made. The experiment is carried out at dynamic and static condition respectively using the ship with passage model. The result is evaluated and it will be reflected in evacuation simulation tool.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.176-180
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• 1998

We may gaze at some peculiar scenes of flocking of birds and fishes. This paper demonstrates that multiple agent mobile robots show complex behaviors from efficient and strategic rules. The simulated flock are realized by a distributed behavioral model and each mobile robot decides its own motion as an individual which moves constantly by sensing the dynamic environment.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.5
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• pp.187-194
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• 2021

A person's behavioral recognition is the recognition of what a person does according to joint movements. To this end, we utilize computer vision tasks that are utilized in image processing. Human behavior recognition is a safety accident response service that combines deep learning and CCTV, and can be applied within the safety management site. Existing studies are relatively lacking in behavioral recognition studies through human joint keypoint extraction by utilizing deep learning. There were also problems that were difficult to manage workers continuously and systematically at safety management sites. In this paper, to address these problems, we propose a method to recognize risk behavior using only joint keypoints and joint motion information. AlphaPose, one of the pose estimation methods, was used to extract joint keypoints in the body part. The extracted joint keypoints were sequentially entered into the Long Short-Term Memory (LSTM) model to be learned with continuous data. After checking the behavioral recognition accuracy, it was confirmed that the accuracy of the "Lying Down" behavioral recognition results was high.