• Korea Journal of Hospital Management
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• v.24 no.4
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• pp.13-32
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• 2019

Purposes: This research is an empirical research to analyze the effect of self-leadership on the job satisfaction and organizational citizenship behavior and the mediating effect of psychological capital. Methods: This research investigates the effect of self-leadership and psychological capital on job satisfaction and organizational citizenship behavior of public health workers. The analysis was carried out to 4 local medical staffs in Chungcheongnam-do province, which distributed 330 copies and recovered 313 copies (94.8% recovery) and analyzed 304 copies (effective response rate 92.1%). Findings: First, causality was found in self-leadership and psychological capital. Second, it was found to have a significant effect on psychological capital and job satisfaction. Third, psychological capital was found to have a significant effect on organizational citizenship behavior. Fourth, psychological capital has a positive effect on both Self-leadership's behavior-oriented strategy, natural reward strategy, and strategic thinking pattern strategy. In the job satisfaction relationship, there was a partial mediating effect. Fifth, psychological capital has a positive effect on both self-leadership and organizational citizenship behavioral behavior-oriented strategy, natural reward strategy, and strategic thinking pattern strategy. The organizational citizenship behavioral relationship was found to have a partial mediating effect. Practical Implications: Taken together, the results indicate that the members of the four public health care organizations run by Chungcheongnam-do have a high weight on the natural reward strategy of achieving job satisfaction through the pleasures of doing their favorite activities or jobs.

• Journal of dental hygiene science
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• v.2 no.2
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• pp.75-83
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• 2002

By extracting the variables related to the work stress generated from dental hygiene, identifying their relationships, this study aims to contribute to academic progress on work stress. The test results of this study are as follows for each hypothesis: 1. Among the work stress sensing factors, role ambiguity showed correlation to the active coping strategy and the passive coping strategy, whereas it did not have any correlation to the evasive reation. However, the physical resource environmental factor showed correlation to the active coping strategy, whereas it did not have any correlation to the other reation. 2. The passive coping strategy, among the work stress coping strategies, influences the role ambiguity, B type, work ambiguity, physical resource environmental factor by about 18.7%. 3. The active coping strategy, among the work stress coping strategies, influences the social support, role ambiguity, work place of health center factor by about 18.9%. 4. The evasive reaction, among the work stress coping strategies, was influenced by only the 36 years old over factor by approximately 4.2%. 5. It was found in all work stress sensing factors that the group with lower social support had a more degree of experiencing stress than the group with higher social support. In case of the behavior pattern, the type A experienced more stress than the type B only in role ambiguity. 6. It was found that the group with the higher social support tended to choose more active coping strategy than the lower social support. In case of behavior pattern, the type B coped more actively than type A in the passive coping strategy.

• Journal of Korean Institute of Industrial Engineers
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• v.5 no.2
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• pp.37-43
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• 1979

A sufficient condition for a Stackelberg strategy to coincide with an equilibrium point is presented. Information pattern of a Stackelberg strategy is essentially different from that of an equilibrium solution and therefore the two strategies need not be the same. However, under score restrictions on the cost functions the difference in information patterns between the two strategies can be disregarded so that the two strategies coincide. The result is extended to the case of discrete-time dynamic games.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1787-1792
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• 2016

Previous walking pattern generation methods could generate walking patterns that allow only straight walking on flat and uneven terrain. They were unable to generate modifiable walking patterns whereby the sagittal and lateral step lengths and walking direction can be changed at every footstep. This paper proposes a novel walking pattern generation method to realize modifiable walking of humanoid robots on unknown uneven terrain. The proposed method employs a walking pattern generator based on the 3-D linear inverted pendulum model (LIPM), which enables a humanoid robot to vary its walking patterns at every footstep. A control strategy for walking on unknown uneven terrain is proposed. Virtual spring-damper (VSD) models are used to compensate for the disturbances that occur between the robot and the terrain when the robot walks on uneven terrain with unknown height. In addition, methods for generating the foot and vertical center of mass (COM) of the 3-D LIPM trajectories are developed to realize stable walking on unknown uneven terrain. The proposed method is implemented on a small-sized humanoid robot platform, DARwIn-OP and its effectiveness is demonstrated experimentally.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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• pp.1712-1732
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• 2011

Cloud provides dynamically scalable virtualized computing resources as a service over the Internet. To achieve higher resource utilization over virtualization technology, an optimized strategy that deploys virtual machines on physical machines is needed. That is, the total number of active physical host nodes should be dynamically changed to correspond to their resource usage rate, thereby maintaining optimum utilization of physical machines. In this paper, we propose a pattern-based prediction model for resource provisioning which facilitates best possible resource preparation by analyzing the resource utilization and deriving resource usage patterns. The focus of our work is on predicting future resource requests by optimized dynamic resource management strategy that is applied to a virtualized data center in a Cloud computing environment. To this end, we build a prediction model that is based on user request patterns and make a prediction of system behavior for the near future. As a result, this model can save time for predicting the needed resource amount and reduce the possibility of resource overuse. In addition, we studied the performance of our proposed model comparing with conventional resource provisioning models under various Cloud execution conditions. The experimental results showed that our pattern-based prediction model gives significant benefits over conventional models.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.655-660
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• 2003

In general, Support Vector Machine has a good performance in binary classification, but it has the limitation on multi-pattern classification. So, we proposed an Import Vector Voting model for two or more labels classification. This model applied kernel bagging strategy to Import Vector Machine by Zhu. The proposed model used a voting strategy which averaged optimal kernel function from many kernel functions. In experiments, not only binary but multi-pattern classification problems, our proposed Import Vector Voting model showed good performance for given machine learning data.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.986-1016
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• 2019

Mobile user interface pattern (MUIP) is a kind of structured representation of interaction design knowledge. Several studies have suggested that MUIPs are a proven solution for recurring mobile interface design problems. To facilitate MUIP selection, an effective clustering method is required to discover hidden knowledge of pattern data set. In this paper, we employ the semi-supervised kernel fuzzy c-means clustering (SSKFCM) method to cluster MUIP data. In order to improve the performance of clustering, clustering parameters are optimized by utilizing the global optimization capability of particle swarm optimization (PSO) algorithm. Since the PSO algorithm is easily trapped in local optima, a novel PSO algorithm is presented in this paper. It combines an improved intuitionistic fuzzy entropy measure and a new population search strategy to enhance the population search capability and accelerate the convergence speed. Experimental results show the effectiveness and superiority of the proposed clustering method.

• ETRI Journal
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• v.29 no.3
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• pp.336-352
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• 2007

Sequential pattern mining has become an essential task with broad applications. Most sequential pattern mining algorithms use a minimum support threshold to prune the combinatorial search space. This strategy provides basic pruning; however, it cannot mine correlated sequential patterns with similar support and/or weight levels. If the minimum support is low, many spurious patterns having items with different support levels are found; if the minimum support is high, meaningful sequential patterns with low support levels may be missed. We present a new algorithm, weighted interesting sequential (WIS) pattern mining based on a pattern growth method in which new measures, sequential s-confidence and w-confidence, are suggested. Using these measures, weighted interesting sequential patterns with similar levels of support and/or weight are mined. The WIS algorithm gives a balance between the measures of support and weight, and considers correlation between items within sequential patterns. A performance analysis shows that WIS is efficient and scalable in weighted sequential pattern mining.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.9
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• pp.623-635
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• 1987

A new suboptimal PWM is proposed, intended particularly for the reduction of acoustic noise and harmonics of the output current in the inverter-fed induction motor drive system. This strategy is based of the Regular PWM and applied optimal techniqe. And it could solve a problem that computation time is very much when switching strategy is determined at the Optimal PWM. In case that the number of switching increases infinitely, this strategy could determine the switching pattern, and can realize Online, Real time of microprocessor. Also, this strategy is applied to 1(Hp), three phase induction motor, and compared with the other PWMs. From the results, the validity of this strategy could be verified.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.12
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• pp.637-644
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• 2004

This paper proposes an expert system with the knowledge learning capability which can enhance the safety and effectiveness of substation operation in the automated substation as well as existing substation by inferring multiple events such as main transformer fault, busbar fault and main transformer work schedule under multiple inference mode and multiple objective mode and by considering totally the switch status and the main transformer operating constraints. Especially inference mode includes the local minimum tree search method and pattern recognition method to enhance the performance of real-time bus reconfiguration strategy. The inference engine of the expert system consists of intuitive inferencing part and logical inferencing part. The intuitive inferencing part offers the control strategy corresponding to the event which is most similar to the real event by searching based on a minimum distance classification method of pattern recognition methods. On the other hand, logical inferencing part makes real-time control strategy using real-time mode(best-first search method) when the intuitive inferencing is failed. Also, it builds up a knowledge base or appends a new knowledge to the knowledge base using pattern learning function. The expert system has main transformer fault, main transformer maintenance work and bus fault processing function. It is implemented as computer language, Visual C++ which has a dynamic programming function for implementing of inference engine and a MFC function for implementing of MMI. Finally, it's accuracy and effectiveness is proved by several event simulation works for a typical substation.