• Journal of Korean Academy of Fundamentals of Nursing
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• v.22 no.2
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• pp.180-189
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• 2015

Purpose: The purpose of this study was to identify the types of errors that occurred and were recovered in a simulated transfusion scenario by nursing students. Methods: Twenty-eight teams of a total of 89 nursing students participated in a transfusion simulation using a high fidelity simulator. Data were collected by observing rule based errors and built in errors recovered according to the framework of Eindhoven model. Reflective journaling was used to identify perceived safety-threatening errors and commitment to improvement. Data were analyzed using descriptive statistics. Results: All teams committed the rule based errors in the scenario. The most common errors occurred in the coordination category related to communication with physician. Most of students perceived the transfusion reaction as a safety-threatening error. Conclusion: The findings indicate that students lack patient safety competence. The simulation training to decrease errors and improve safe practice provides nursing students with an effective strategy to develop patient safety competence.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.398-403
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• 1993

A rule based fuzzy expert system to self-tune PID controllers is proposed in this paper. The proposed expert system contains two rule bases, where one is responsible for "Long term tuning" and the other for "Incremental tuning". The rule for "Long term tuning" are extracted from the Wills'map and the knowledge about the implicit relations between PID gains and important long term features of the output response such as overshoot, damping and rise time, etc., while 'Incremental tuning" rules are obtained from the relations between PID gains and short term features, error and change in error. In the PID control environment, the proposed expert system operates in two phases sequentially. In the first phase, the long term tuning is performed until long term features meet their desired values approximately. Then the incremental tuning tarts with PID gains provided by the long term tuning procedure. It is noticeable that the final PID gains obtained in the incremental tuning phase are only the temporal ones. Simulation results show that the proposed rule base for "Long term tuning" provides superior control performance to that of Litt and that further improvement of control performance is obtained by the "Incremental tuning'.ance is obtained by the "Incremental tuning'.ing'.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.1
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• pp.19-27
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• 2014

As frequency resource has taken on greater importance, Cognitive Radio(CR) technology has been considered as the solution to improve spectrum utilization by allowing a secondary user to utilize a licensed band when the primary user is absent. So spectrum sensing is significant part of CR for high performance. Recently, cooperative spectrum sensing that secondary users share each sensing results is proposed to improve spectrum sensing accuracy. In this paper, OR rule based cooperative spectrum sensing scheme using reporting error probability which occurs in user to fusion center(FC) channel The simulation results show that proposed scheme mitigates false alarm probability limitation which appears in existing cooperative spectrum sensing scheme by restricting the number of cooperating users using reporting error probability.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.699-701
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• 2004

This paper proposes the algorithm of servo- writing based on feedback error learning neural networks. The controller consists of feedback controller using PID and feedforward controller using gaussian radial basis function network. Because the RBFNs are trained by on-line rule, the controller has adaptation capability. The performance of the proposed controller is compared to that of conventional PID controller. Proposed algorithm shows better performance than PID controller.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.563-566
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• 1991

This paper discusses the possibility of applying fuzzy logic controller in a microprocessor - based servomotor controller, such as servomotor position controller, which requires faster and more accurate response compared with other industrial processes. According to the fuzzy control rule made by tie analysis of error and error change, one Look-up table that contains various quantized step is made and appropriate initial error change is selected to the good responses.

• Journal of the Ergonomics Society of Korea
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• v.30 no.1
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• pp.169-177
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• 2011

The aim of this study is to review previous studies on human errors in the service delivery processes. Service industry is sharply growing in the advanced countries. Many people are looking for something to contribute to the service industry. Although there are many research topics related to service domain that human factors and ergonomics specialists can do contribute, a few researchers are studying such topics. This paper indicated how previous researches on human factors and human errors have addressed the service domain, in order to prompt human factor study on the service domain. A variety of sources were inspected for literature reviews, including books and journals of managements, medicine, psychology, consumer behavior as well as human factor and ergonomics. The characteristics of human errors in the service domain were investigated. Human error studies in several service sectors were summarized such as medical service, automotive service operation, travel agent service and call center service. Until now, human factors community was not much interested in human errors in service domain. However, there is much space to contribute to service domain; human error identification, human error analysis and control of human error. The research of human error in service domain can provide clues to improve service quality. This paper helps to guide to identify human error of service domain and to design service systems.

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.382-385
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• 1999

In this paper, by means of Lyapunov second method, the stability of IPD control servo systems is analyzed in the time domain for the first time. Based on the results of the stability analysis, the design rule to select the gain of IPD control is suggested such that the maximum error of output to the nominal system is guaranteed for all uncertainty and load variations. An example of a position control of a brushless dc motor is given to prove the unusefulness of the gain design rule.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.70-74
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• 1998

In this paper, by means of Lyapunov second method, we analyze the stability of IP control servo systems in the time domain for the first time. Based on the results on the stability analysis, the design rule to select the gain of IP control is suggested such that the maximum error of output to the nominal system is guaranteed for all uncertainty and load variations. An example of a speed control of brushless dc motor given to prove the unusefulness of the gain design rule.

• Journal of Advanced Navigation Technology
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• v.18 no.1
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• pp.74-77
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• 2014

This paper suggested an error control for multi-channel running on machine to machine environment. This system is suitable for recovering software fault for multimedia CSCW(Computer Supported Cooperative Works) based on machine to machine environment. It is necessary for the system to be protected by reactivity of media service instance instead of breaking process of session. This paper explains a performance analysis of an error recovery system of M2M based computing collaboration environment using rule-based DEVS modeling and simulation techniques.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.44-51
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• 2003

Knowledge acquisition is a bottleneck in knowledge-based system implementation. Decision tree induction is a useful machine learning approach for extracting classification knowledge from a set of training examples. Many real-world data contain fuzziness due to observation error, uncertainty, subjective judgement, and so on. To cope with this problem of real-world data, there have been some works on fuzzy classification rule learning. This paper makes a survey for the kinds of fuzzy classification rules. In addition, it presents a fuzzy classification rule learning method based on decision tree induction, and shows some experiment results for the method.