• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.11
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• pp.2152-2156
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• 2011

In this paper, we propose the novel behavior control algorithm by using the efficient searching method based on the characteristic of the swarm robots in unknown space. The proposed method consists of identifying the position and moving state of a robot by the dynamic modelling of a wheel drive vehicle, and planing behavior control rules of the swarm robots based on the sensor range zone. The cooperative search for unknown space is carried out by the proposed behavior control. Finally, some experiments show the effectiveness and the feasibility of the proposed method.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.5
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• pp.27-34
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• 2005

To accomplish various and complex tasks by intelligent robots, improvement is needed not only in mechanical system architecture but also in control system architecture. Hybrid control architecture has been suggested as a mutually complementing architecture of the weak points of a deliberative and a reactive control. This paper addresses a control architecture of robots, and a behavior representation methodology. The suggested control architecture consists of three layers of deliberative, sequencing, and reactive as hybrid control architecture. Multi-layer behavior model is employed to represent desired tasks. 3D simulation will be conducted to verify the applicability of suggested control architecture and behavior representation method.

• Research in Community and Public Health Nursing
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• v.24 no.2
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• pp.195-204
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• 2013

Purpose: This study was carried out to find factors affecting weight-control behavior intention in female college students based on the theory of planned behavior. Methods: The subjects were 453 female students from everywhere other than the Gangwon Province and Jeju Island. Data were collected by using a questionnaire. Results: The factors affecting weight-control behavior intention in female college students within 2 weeks were attitudes and subjective norms. These two factors accounted for 20.0% of weight-control behavior intention. Also, when body shape satisfaction and BMI were added to variables of the theory of planned behavior like attitudes, subjective norms, and perceived behavior control, these 5 factors accounted for a total of 34.1%. Conclusion: Due to their distorted perception in preferring skinny body shapes, female college students are likely to attempt at inappropriate weight control behavior. Through intervention with such factors as attitudes and body image satisfaction, which have been derived from the results of this study, healthy weight control behavior should be pursued in practice.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1079-1085
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• 2000

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). An immune system is the living bodys self-protection and self-maintenance system. these features can be applied to decision making of the optimal swarm behavior in a 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. When the environmental condition (antigen) changes, a robot selects an appropriate behavior strategy (antibody). And its behavior strategy is stimulated and suppressed by other robots using communication (immune network). Finally, much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and immune network hypothesis, and it is used for decision making of the optimal swarm strategy. Adaptation ability of the robot is enhanced by adding T-cell model as a control parameter in dynamic environments.

• Research in Community and Public Health Nursing
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• v.26 no.2
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• pp.128-139
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• 2015

Purpose: The purpose of this study was to identify factors affecting health promotion behavior among workers with high risk of metabolic syndrome. This study was based on the planned behavior theory. Methods: The participants were 167 workers at high risk of metabolic syndrome. Data were collected using a structured questionnaire. Surveyed variables were attitude, subjective norm, perceived behavioral control, intention, and health promotion behavior. Data were analyzed using descriptive statistics, t-test, ANOVA, Pearson's correlation coefficients, and hierarchical regression analysis with SPSS/WIN 22.0. Results: Perceived behavioral control affected the intention of health promotion behavior among the workers with high risk of metabolic syndrome. It explained 62% of variance in the intention of health promotion behavior (F=40.09, p<.001). Perceived behavioral control and occupation affected health promotion behavior among the risk workers with high risk of metabolic syndrome. The two factors explained 16% of variance in health promotion behavior (F=4.95, p<.001). Conclusion: The findings of this study suggest that perceived behavioral control is the only factor affecting health promotion behavior when the theory of planned behavior was applied. Therefore, intervention programs for improving health promotion behavior should be focused on strengthening perceived behavioral control.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.23 no.3
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• pp.245-255
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• 2016

Purpose: This study was conducted to compare self-care behaviors and self-care behavior related factors for groups of patients with good, inadequate and poor glycemic control. The study was based on variables of the Theory of Planned Behavior by Ajzen, habit and family support. (1991). Methods: Participants were 134 patients with type 2 diabetes (good glycemic control group: 57, inadequate glycemic control group: 40, poor glycemic control group: 37). Self-care behaviors, intention to self-care behavior and self-care behavior related variables (attitude, subjective norms, perceived behavior control, habits and family support) were measured. Data were collected from August 12 to September 25, 2014 and were analyzed using $x^2$-test, Fisher's exact test, ANCOVA, and logistic regression with SPSS/WIN 21.0. Results: Among the three glycemic groups, there were significant differences in self-care behavior, subjective norms, perceived behavior control, family support, and habits. Multinomial logistic regression showed that poor blood glucose probability was associated with duration of diabetes mellitus, method of DM therapy, perceived behavior control and habits. Conclusion: The study findings reveal the important role of self-care behavior, subjective norms, perceived behavior control, family support, and habits in blood glucose control in adults with type 2 diabetes.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.124-127
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• 1997

In this paper, we propose a method of cooperative control based on immune system in distributed autonomous robotic system(DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For the purpose of applying immune system to DARS, a robot is regarded as a B lymphocyte(B cell), each environmental condition as an antigen, and a behavior strategy as an antibody 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 simulated and suppressed by other robot using communication. Finally much simulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy.

• International Journal of Human Ecology
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• v.12 no.2
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• pp.13-24
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• 2011

This study compared actual weight with perceived weight, described the prevalence of unhealthy weight control behavior, determined the differences in psychological and personal variables between participants that reported unhealthy weight control behavior and those who did not, and examined the relationship of eating habits to unhealthy weight control behavior for Korean adolescents. The study population consisted of a nationally representative sample of middle and high school students who completed the Fifth Korea Youth Risk Behavior Web-based Survey (KYRBWS): Fifth in 2009. Among the 75,066 participants of KYRBWS, 35,473 (n = 18,851 girls and 16,622 boys) were eligible for a research focused on unhealthy weight control behavior. The results of this research were as follows: First, there were considerable discrepancies (45.1% of girls and 32.8% of boys) between the perceived weight and the actual weight. Second, overall, unhealthy weight control behavior was more prevalent in girls and fasting was the most commonly reported behavior. Third, participants that reported unhealthy weight control behavior scored significantly lower on scaled measures of happiness, health, academic achievement, and economic status; in addition, they scored higher on stress measures. Fourth, girls and boys shared common protective factors of having breakfast and vegetables more often, perceiving their weight as underweight rather than overweight, and having a correct weight conception. Protective factors unique to girls were having lunch and dinner more often. Girls and boys shared common risk factors of the consumption of soda, fast food, instant noodles, and snacks more often, while consumption of fruit more often was a risk factor only for girls. The improvement of protective factors and minimization of risk factors through Home Economics classes (and other classes relevant to health) may mitigate unhealthy weight control behavior of adolescents.

• 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.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.115-119
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• 2020

Recently, CCTV installations are rapidly increasing in the public and private sectors to prevent various crimes. In accordance with the increasing number of CCTVs, video-based abnormal behavior detection in control systems is one of the key technologies for safety. This is because it is difficult for the surveillance personnel who control multiple CCTVs to manually monitor all abnormal behaviors in the video. In order to solve this problem, research to recognize abnormal behavior using deep learning is being actively conducted. In this paper, we propose a model for detecting abnormal behavior based on the deep learning model that is currently widely used. Based on the abnormal behavior video data provided by AI Hub, we performed a comparative experiment to detect anomalous behavior through violence learning and fainting in videos using 2D CNN-LSTM, 3D CNN, and I3D models. We hope that the experimental results of this abnormal behavior learning model will be helpful in developing intelligent CCTV.