• Journal of Korean Academy of Nursing
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• v.50 no.2
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• pp.210-227
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• 2020

Purpose: This study aimed to develop a scale to measure variables related to alcohol drinking prevention behavior in early elementary school, based on the theory of planned behavior. Methods: A scale was developed to measure variables related to alcohol drinking prevention behavior. Initial items for direct evaluation were constructed through a literature review, and those for belief-based indirect measure were generated through interviews with 30 second- and third-grade elementary school students. The collected data from 286 third-grade elementary school students were then subjected to item analysis, exploratory and confirmative factor analysis, criterion-related validity testing, and internal consistency assessment. Results: The final scale consisted of 35 items. Intention, attitudes, subjective norms, and perceived behavioral control explained 82.7% of the variance; behavioral beliefs, normative beliefs, and control beliefs explained 65.6% of the variance; and evaluation of outcome, motivation to comply, and power of control beliefs explained 72.8% of the variance. The confirmatory factor analysis indicated that the theoretical models had a satisfactory goodness of fit. Criterion-related validity was confirmed between the direct evaluation variables and the indirect measure variables (attitudes r=.64, p<.001; subjective norms r=.39, p<.001; perceived behavioral control r=.62, p<.001). Cronbach's α was .89 for the direct evaluation variables and .93 for the indirect measure variables. Conclusion: The scale developed in this study is valid and reliable. It could be used to measure and explain variables related to alcohol drinking prevention behavior in early elementary school.

• Smart Structures and Systems
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• v.31 no.3
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• pp.247-257
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• 2023

In structural health monitoring of large-scale structures, optimal sensor placement plays an important role because of the high cost of sensors and their supporting instruments, as well as the burden of data transmission and storage. In this study, a vibration sensor placement algorithm based on deep reinforcement learning (DRL) is proposed, which can effectively solve non-convex, high-dimensional, and discrete combinatorial sensor placement optimization problems. An objective function is constructed to estimate the quality of a specific vibration sensor placement scheme according to the modal assurance criterion (MAC). Using this objective function, a DRL-based algorithm is presented to determine the optimal vibration sensor placement scheme. Subsequently, we transform the sensor optimal placement process into a Markov decision process and employ a DRL-based optimization algorithm to maximize the objective function for optimal sensor placement. To illustrate the applicability of the proposed method, two examples are presented: a 10-story braced frame and a sea-crossing bridge model. A comparison study is also performed with a genetic algorithm and particle swarm algorithm. The proposed DRL-based algorithm can effectively solve the discrete combinatorial optimization problem for vibration sensor placements and can produce superior performance compared with the other two existing methods.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.607-612
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• 2002

An automatic design method of behaviors in behavior-based robotics is proposed. With this method, a robot can design its behaviors by itself without aids of human designer. Automating design procedure of behaviors can make the human designer free from somewhat tedious endeavor that requires to predict all possible situations in which the robot will work and to design a suitable behavior for each situation. A simple reinforcement learning strategy is the main frame of this method and the key parameter of the learning process is significant change of reward value. A successful application to mobile robot navigation is reported too.

• Journal of Korean Academy of Nursing
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• v.54 no.2
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• pp.178-192
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• 2024

Purpose: This study aimed to examine the predictive factors of COVID-19 vaccination behavior by evaluating the moderating effect of perceived behavioral control on the theory of planned behavior. Methods: Data were collected from August 6 to August 31, 2022 from 235 college students (aged 20~29 years) across 12 universities using a structured web-based survey. Statistical analyses were conducted using the SPSS and AMOS software. Results: Attitudes toward COVID-19 vaccination, subjective norms, and intention to be vaccinated significantly influenced COVID-19 vaccination behavior. Attitudes and subjective norms indirectly affected COVID-19 vaccination behavior through intention to vaccinate, whereas intention to vaccinate had a direct effect. The moderating effect of perceived behavioral control on the relationship between subjective norms and intention to vaccinate was significant. Conclusion: Interventions that foster a positive attitude toward COVID-19 vaccination and bolster subjective norms and perceived behavioral control can boost the intention to be vaccinated and facilitate the uptake of COVID-19 vaccination.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.249-254
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• 2001

Abstract In this paper, we propose a method of cooperative control based on artifical intelligent system in distributed autonomous robotic system. In general, multi-agent behavior algorithm is simple and effective for small number of robots. And multi-robot behavior control is a simple reactive navigation strategy by combining repulsion from obstacles with attraction to a goal. However when the number of robot goes on increasing, this becomes difficult to be realized because multi-robot behavior algorithm provide on multiple constraints and goals in mobile robot navigation problems. As the solution of above problem, we propose an architecture of fuzzy system for each multi-robot speed control and fuzzy-neural network for obstacle avoidance. Here, we propose an architecture of fuzzy system for each multi-robot speed control and fuzzy-neural network for their direction to avoid obstacle. Our focus is on system of cooperative autonomous robots in environment with obstacle. For simulation, we divide experiment into two method. One method is motor schema-based formation control in previous and the other method is proposed by this paper. Simulation results are given in an obstacle environment and in an dynamic environment.

• The Korean Journal of Food And Nutrition
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• v.25 no.3
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• pp.579-589
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• 2012

This study was performed to investigate the eating habit, body image, and weight control behavior by BMI in Korean female high school students. Data on the 16,574 subjects was obtained from the sixth Korea Youth Risk Behavior Web-based Survey (2010). Only 52.2% of the subjects had regular breakfast. The rate of skipping breakfast was higher in the underweight group than in the obese group, but the rate of skipping dinner was on the contrary to this. Underweight students had a higher intake frequency of fruits, fast food, instant noodle, and snacks than the obese groups. 3.5% of underweight students considered themselves to be overweight or obese. 53.4% of obese students considered themselves to be overweight. The experience of weight control increased according to BMI, but underweight students considered weight control as an effort to be slimmer. Meal restriction was used more frequently to control weight. The perceived stress level was higher in obese student, especially due to appearance. Therefore, an appropriate, integrated and personalized high school nutrition program should be established for proper body image perception and to develop the self-esteem of female high school students.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.532-532
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• 2000

Conventional artificial intelligence systems are not properly responding under dynamically changing environments. To overcome this problem, reactive planning systems implementing new Al principles, called behavior-based Al or emergent computation, have been proposed and confirmed their usefulness. As another alternative, biological information processing systems may provide many feasible ideas to these problems. Immune system, among these systems, plays important roles to maintain its own system against dynamically changing environments. Therefore, immune system would provide a new paradigm suitable for dynamic problem dealing with unknown environments. In this paper, a new approach to behavior-based Al by paying attention to biological immune system is investigated. The feasibility of this method is confirmed by applying to behavior control of an autonomous mobile robot in cluttered environment.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2464-2466
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• 2001

In this paper, a behavior-based fuzzy control of mobile robots for autonomous navigation is presented. Behaviors of mobile robots are divided into two categories: reactive behavior and purposeful behavior, which are incompatible with each other. The former is reaction performed in terms of the sensory data and the latter is action for achieving the goal. The presented method generates appropriate control inputs to the robot to trade-off between the reactive and purposeful behaviors using fuzzy inferences. The method is applied to an synchro-drive type mobile robot and shown to be useful for autonomous robot navigation by providing simulation results.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.2
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• pp.63-72
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• 2018

Researches based on the pattern of planned behavior holds that the three variables of entrepreneurial attitudes, subjective norms, and perceived behavior control influence each other and influence entrepreneurial intentions respectively. However, there are also different, even conflicting research conclusions that continue to emerge. Researches based on the pattern of alertness, believe that profit opportunities and individuals' pursuit to truth are the driving forces. Many scholars have demonstrated the impact of individual entrepreneurial alertness on entrepreneurial intentions. However, as an exogenous causal agent, profit opportunities have a logical problem: if there are no other assumptions, the mere existence of opportunities does not adequately explain entrepreneurial alertness. To address this gap, this study considered samples from mainland China, where entrepreneurial activities are very active currently, to test the role that entrepreneurial alertness is assumed to play in the planned behavior model. The results show that the three dimensions of alertness, individually partly intermediate the influence of entrepreneurial attitude on entrepreneurial intention, the influence of subjective norms on entrepreneurial intention, and that of perceived behavior control on entrepreneurial intention. This article studied the production of entrepreneurial intention by integrating the two patterns of planned behavior and alertness through empirical analysis, and opened up a new field for subsequent research on entrepreneurial intention.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.6
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• pp.95-104
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• 2022

This study investigates the complex mechanism of work-family conflict affecting counterproductive behavior of employees based on resource conservation theory and 417 valid samples by using polynomial regression and response surface analysis. Counterproductive work behavior refers to any intentional behavior of an individual that has potential harm to the legitimate interests of the organization or its stakeholders. Results show that first, work-to-family conflict (WFC) and family-to-work conflict (FWC) had four matching types. Compared with "high WFC-low FWC," "low WFC-high FWC" and "low WFC-low FWC" matching conditions, the employee self-control resource depletion and counterproductive work behavior (CWB) are at their highest under "high WFC-high FWC" congruence matching condition. Second, the joint effect of WFC and FWC has a U-shaped relationship with counterproductive behavior. Compared with the "high WFC-low FWC" match state, the level of CWB in the "low WFC-high FWC" match state is higher. Third, the depletion of self-control resources played a mediating role in the effect of WFC on counterproductive behavior. Fourth, emotional intelligence moderated the relationship between the congruence of WFC and FWC and self-control resource depletion. Emotional intelligence was higher, and the positive relationship between the congruence of WFC and FWC and self-control resource depletion was weaker.