• Journal of Korean Academy of Fundamentals of Nursing
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• v.25 no.4
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• pp.269-281
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• 2018

Purpose: The purpose of this study was to build a model to predict the fall prevention behavior of nurses in small and medium sized hospitals. Methods: Participants were 382 nurses from 13 hospitals who responded to the structured self-reported questionnaire. The research model was based on previous study of fall prevention, theory of planned behavior, and the health belief model. Results: The modified model generally showed higher levels than recommended level of model fit indices and acceptable explanation. Of 17 hypothetical paths, 14 were supported. Predicting variables explained 51.6% of fall prevention behavior. The fall prevention behavior of nurses showed a direct influence of fall prevention expectations, fall prevent threats, perceived behavioral control for fall prevention, and intention to prevent falls and an indirect of influence of patient safety culture, attitude toward fall prevention, and the subjective norm. Conclusion: Findings show a need to identify a range of barrier factors to increase the benefits of fall prevention behavior and enhance the perceived control of fall prevention so that nurses will be able to promote fall prevention behavior in hospitals. Also, it is critical to increase awareness of patient safety culture among nurses.

• Advances in aircraft and spacecraft science
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• v.9 no.3
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• pp.217-242
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• 2022

This paper proposes a novel time-domain homogenization model combining the viscoelastic constitutive law with Eshelby's inclusion theory-based micromechanics model to predict the mechanical behavior of the particle reinforced composite material. The proposed model is intuitive and straightforward capable of predicting composites' viscoelastic behavior in the time domain. The isotropization technique for non-uniform stress-strain fields and incremental Mori-Tanaka schemes for high volume fraction are adopted in this study. Effects of the imperfectly bonded interphase layer on the viscoelastic behavior on the dynamic mechanical behavior are also investigated. The proposed model is verified by the direct numerical simulation and DMA (dynamic mechanical analysis) experimental results. The proposed model is useful for multiscale analysis of viscoelastic composite materials, and it can also be extended to predict the nonlinear viscoelastic response of composite materials.

• Journal of Korean Academy of Nursing
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• v.29 no.2
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• pp.281-292
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• 1999

This study was designed to construct a model that predicts the health promoting behavior of the Korean elderly. Data were collected by self-reported questionaires from 254 Korean elderly in seoul, from June 1 to July 15, 1998. Data were analyzed by descriptive statistics and correlational analysis using pc-SAS program. The Linear Structural Modeling(LISREL) 8.0 program was used to find the best fit model which predicts causal relationships of variables. The overall fit of the hypothetical model to the data was moderate［X$^2$＝249.83(df＝83, p＝.00), RMR＝.07, GFI＝.90, NNFI＝.92, NFI ＝.91］. The predictable variables of health promoting behavior of the Korean elderly were social activity. social support. self-integrity and helplessness except the perceived health status. These variables explained 17.1% of health promoting behavior of the Korean elderly.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.11
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• pp.80-85
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• 2001

In Part 2, dynamic cutting force model, thermal behavior model, and feed drive model are presented for development of a virtual machine tool. Some relevant results with brief descriptions for each model are presented to verify the proposed models. Experimental results for each model agreed well with the estimated ones. The developed models in this two-part paper are partially integrated as a comprehensive software environment.

• Journal of Sensor Science and Technology
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• v.15 no.1
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• pp.34-39
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• 2006

This study provides the electrical model of combustible catalytic gas sensor. Physical characteristics such as thermal behavior, resistance change were included in this model. The finite element method analysis for sensor device structure showed that the thermal behavior of sensor is expressed in a simple electrical equivalent circuit that consists of a resistor, a capacitor and a current source. This thermal equivalent circuit interfaces with real electrical circuit using two parts. One is 'power to heat' converter. The other is temperature dependent variable resistor. These parts realized with the analog behavior devices of the SPICE library. The gas response tendency was represented from the mass transferring limitation theory and the combustion theory. In this model, Gas concentration that is expressed in voltage at the model, is converted to heat and is flowed to the thermal equivalent circuit. This model is tested in several circuit simulations. The resistance change of device, the delay time due to thermal capacity, the gas responses output voltage that are calculated from SPICE simulations correspond well to real results from measuring in electrical circuits. Also good simulation result can be produced in the more complicated circuit that includes amplifier, bios circiut, buffer part.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.491-496
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• 2003

This paper proposes modeling of human behavior and a method of finding irregular human behavior. At first, human behavior model is proposed by paying attention to habitual human behavior at home. Generally, it is difficult to obtain the information of individual life pattern because of high cost for setting sensors such as cameras to observe human action. Therefore we capture turning on/off consumer electronic equipments as actual human behavior action, where some or many consumer electric equipments were used such as television, room light, video and so on in our daily life. Noting that are some relations between turning on/off those consumer electric equipments and our action, we proposes how to construct a human behavior knowledge by analyzing human behavior based on observation of human habitual life. Also an algorithm to identify on find irregular behavior different from habitual life behavior are described. Finally, the significance of the proposed method is shown by some experimental results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.965-983
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• 2014

Concurrent behaviors of multithreaded programs cannot be described effectively by automata-based models. Thus, concurrent program intrusion attempts cannot be detected. To address this problem, we proposed the process algebra-based detection model for multithreaded programs (PADMP). We generate process expressions by static binary code analysis. We then add concurrency operators to process expressions and propose a model construction algorithm based on process algebra. We also present a definition of process equivalence and behavior detection rules. Experiments demonstrate that the proposed method can accurately detect errors in multithreaded programs and has linear space-time complexity. The proposed method provides effective support for concurrent behavior modeling and detection.

• Proceedings of the Korea Society for Simulation Conference
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• 1994.10a
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• pp.12-12
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• 1994

Simulation output knowledge analysis is one of problem-solving and/or knowledge adquistion process by investgating the system behavior under study through simulation . This paper describes an approach to simulation outputknowldege analysis using fuzzy neural network model. A fuzzy neral network model is designed with fuzzy setsand membership functions for variables of simulation model. The relationship between input parameters and output performances of simulation model is captured as system behavior knowlege in a fuzzy neural networkmodel by training examples form simulation exepreiments. Backpropagation learning algorithms is used to encode the knowledge. The knowledge is utilized to solve problem through simulation such as system performance prodiction and goal-directed analysis. For explicit knowledge acquisition, production rules are extracted from the implicit neural network knowledge. These rules may assit in explaining the simulation results and providing knowledge base for an expert system. This approach thus enablesboth symbolic and numeric reasoning to solve problem througth simulation . We applied this approach to the design problem of broadband communication network.

• The Korean Journal of Food And Nutrition
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• v.34 no.2
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• pp.242-253
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• 2021

The purpose of this study was to investigate the sustainable practices of nutrition science teachers and dietitians working in school food service operations, and identify the social and psychological factors which affect the overall efficacy of the system. The research model was constructed based on the Extended Theory of Planned Behavior (ETPB) in order to analyze how individual motivation affects the sustainable practices of nutrition science teachers and dietitians. The data were collected through e-mail and postal mail from nutrition science teachers and dietitians all across Korea, and self-administered surveys were conducted. SPSS and AMOS programs were used for statistical analysis. First, the sustainable practices of nutrition science teachers and dietitians were analyzed in 6 different categories. Second, the significant pathways were 6 out of 9 in the ETPB model. Sustainable food service practices in school can contribute to the formation of more a sustainable culture, such as through the encouragement of more healthy eating habits, and higher level of environmental awareness and community awareness. The factors influencing these practices can be applied to the design of improvement programs aimed at increasing sustainable practices.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.817-828
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• 2018

Modern software, especially web-based software, is broadly used in various fields. Most web applications employ design patterns, such as a model-view-controller (MVC) pattern and a factory pattern as development technology, so the application can have a good architecture to facilitate maintenance and productivity. A web application, however, may have defects and developers must fix the defects when a user submits bug reports. In this paper, we propose a novel approach to improving fault traceability in web application by using software revision information and software behavior model to reduce costs and effectively handle the software defect. We also provide a case study to show effectiveness of our approach.