• International journal of advanced smart convergence
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• v.12 no.4
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• pp.370-377
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• 2023

Previous research has demonstrated that happy moods are known to promote feeling-based processing, whereas sad moods promote reason-based processing. The current research investigates a boundary condition for the effects of a happy mood on feeling-based decision making. This research proposes that the level of control (low vs. high) one exercises in a happy situation can promote a greater reliance on feelings (vs. reasons) in making judgments and decisions. Specifically, we hypothesize that (1) a happy individual in a situation where control level is low (vs. high) will be more likely to choose a cognitively (vs. affectively) superior option (hypothesis 1), and (2) a happy individual in a situation where control level is low (vs. high) will exert reason- (vs. feeling-) based processing (hypothesis 2). Consistent with the hypothesis 1, the results of two experiments show that happy individuals are more likely to choose cognitively versus affectively superior options in a situation where control level is low (vs. high). Moreover, the mediation analysis confirms that happy individuals are more likely to rely on cognitive, reason-based decision making when their control level is low, which supports the hypothesis 2.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.98-103
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• 2000

This paper suggests a method to recognize the various defect patterns of a cold mill strip using a binary decision tree automatically constructed by a genetic algorithm(GA). In classifying complex patterns with high similarity like the defect patterns of a cold mill stirp, the selection of an optimal feature set and an appropriate recognizer is important to achieve high recognition rate. In this paper a GA is used to select a subset of the suitable features at each node in the binary decision tree. The feature subset with maximum fitness is chosen and the patterns are classified into two classes using a linear decision function. This process is repeated at each node until all the patterns are classified into individual classes. In this way, the classifier using the binary decision tree is constructed automatically. After constructing the binary decision tree, the final recognizer is accomplished by having neural network learning sits of standard patterns at each node. In this paper, the classifier using the binary decision tree is applied to the recognition of defect patterns of a cold mill strip, and the experimental results are given to demonstrate the usefulness of the proposed scheme.

• Water Engineering Research
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• v.5 no.4
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• pp.157-176
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• 2004

This research presents a prototype development and implementation of Decision Support System (DSS) for integrated river basin water management for the flood control. The DSS consists of Relational Database Management System, Hydrologic Data Monitoring System, Spatial Analysis Module, Spatial and Temporal Analysis for Rainfall Event Tool, Flood Forecasting Module, Real-Time Operation of Multi Reservoir System, and Dialog Module with Graphical User Interface and Graphic Display Systems. The developed DSS provides an automated process of alternative evaluation and selection within a flexible, fully integrated, interactive, centered relational database management system in a user-friendly computer environment. The river basin decision-maker for the flood control should expect that she or he could manage the flood events more effectively by fully grasping the hydrologic situation throughout the basin.

• Water for future
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• v.18 no.3
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• pp.225-233
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• 1985

To develop a simulation strategy of multi-reservoir operation in flood season, the single dam operations methed for the Chungju dam are investigated in the Han river basin. Thus, spillway rule curve, rigid ROM, and linear decision rules are applied for control operations, subject to the restrictions imposed by the river and the reservoir characteristics. The storage and release and control/utility efficiencies for several floods are calculated. The variation of control coefficients with respect to the return period are also examined. As the results of this comparative study, the optimal operation method can be selected in terms of the magnitude of flood. With inflow forecasting, the flood control operation can be greatly improved by variable coefficients rigid ROM and linear decision rules.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.240-249
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• 2019

This study was conducted to examine the effects of awareness of infection control, career decision making self efficacy and critical thinking disposition on the performance of infection control among nursing students. The study subjects were 404 third and fourth year nursing students at 4 colleges in D and K cities. The data were collected from November 5 to December 21, 2018 by using a structured questionnaire. The data were analyzed by using the SPSS WIN 17.0 program to conduct descriptive statistics, independent t-test, one-way ANOVA, post-hoc Duncan's test, Pearson's correlation coefficients, and multiple regression. The average score of awareness of infection control was 4.75 points, career decision making self efficacy was 3.02 points, critical thinking disposition was 4.73 points and performance of infection control was 4.46 points. Performance of infection control was positively influenced by age, awareness of infection control and career decision making self efficacy. The explanatory power of the model was 38.6%. Therefore, these results imply the need to develop an education program to improve the awareness of infection control and career decision making self efficacy, which will enhance the performance of infection control of nursing students.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.1
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• pp.10-14
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• 2013

High precision machining technology has become one of the important parts in the development of a precision machine. Such a machine requires high precision positioning as well as high speed on a large workspace. For machining systems having a high precision positioning with a long stroke, it is necessary to examine the repeatability of reference position decision. Though ball-screw driven linear stages equipped linear scale have high precision feed drivers and a long stroke, they have some limitations for reference position decision if they have not equipped the accurate home sensor. This study is performed to experimentally examine the repeatability for home position decision of a magnetic sensor as a home switch of ball-screw driven linear stage by using capacitance probe.

• Nuclear Engineering and Technology
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• v.39 no.6
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• pp.703-716
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• 2007

As digital and computer technologies have grown, human-machine interfaces (HMIs) have evolved. In safety-critical systems, especially in nuclear power plants (NPPs), HMIs are important for reducing operational costs, the number of necessary operators, and the probability of accident occurrence. Efforts have been made to improve main control room (MCR) interface design and to develop automated or decision support systems to ensure convenient operation and maintenance. In this paper, an integrated decision support system to aid operator cognitive processes is proposed for advanced MCRs of future NPPs. This work suggests the design concept of a decision support system which accounts for an operator's cognitive processes. The proposed system supports not only a particular task, but also the entire operation process based on a human cognitive process model. In this paper, the operator's operation processes are analyzed according to a human cognitive process model and appropriate support systems that support each cognitive process activity are suggested.

• Journal of Korean Academy of Nursing Administration
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• v.13 no.1
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• pp.82-97
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• 2007

Purpose: This study was to investigate the relationships among nurse managers' participation in decision-making process relation to human resource management and the influencing factors. Method: The subjects were 198 nurse managers who were in general hospitals over 900 beds. The data were collected from January 13 to March 13, 2006. The SPSS PC+ 12.0 program was used to analyze the data. Result: The nurse managers had greater participation in the identification phase of decision making than selection phase. The mean scores of three phases were significantly different. The satisfaction of decision making was evaluated. The higher participation in decision making, the higher satisfaction of decision making. Nurse managers' decision style tended to be more participative than autocratic. Personal and organizational factors(age and decentralization) influenced positively on participation in decision making. Decentralization and span of control influenced positively on satisfaction in decision making. Conclusion: It is necessary to permit the participation in decision making for nurse managers.

• Korean Journal of Construction Engineering and Management
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• v.9 no.2
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• pp.125-135
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• 2008

A controller who is responsible for visiter's safety makes a decision about measures for visiter safety in human-based decision making process. Many potential accidents that are caused by human error lurk in results of the process. The accidents can be decreased by changing the decision making process from human-based into technology-based. Technology-based decision making process can catch a controller's attention through data filtering, alarm filtering, and so on. So, the controller can get information on occurrence of an unforeseen accident pro-actively. The objective of this study is to suggest a concept of 3D spatial information control system for visitor flow control in multi complex building using technology-based decision making process. This study shows utilization of the system and contribution.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.694-698
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• 1987

In this paper, the primitive and double combined motion classification of the arm is discussed using pattern recognition of EM signal. The EM signals are detected from Ag-Ag/Cl surface electrodes, and IBM PC, calculated the Likelyhood probability and the decision function on the feature space of integral absolute value. Multiclass decision rule is introduced for higher decision rate. On our experimental results from expert simulator, the decision rate of more than 78% can be obtained.