• Journal of radiological science and technology
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• v.47 no.1
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• pp.7-12
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• 2024

Medical institutions wishing to install and operate diagnostic radiation generators must complete appointment training within one year of appointment based on the 「Medical Act」 and the 「Rules on Safety Management of Diagnostic Radiation Generator Devices」 which will come into effect on January 1, 2024. Additionally, You must receive supplementary education every three years from the date you received it. The strengthening of safety management for diagnostic radiation generators used in medical institutions means that although the radiation exposure that may occur when using diagnostic radiation generators is low, the risk of carcinogenesis may be higher than previously evaluated. In addition, safety management of diagnostic radiation generators can be said to be an essential requirement because it has been reported that the incidence of leukemia and other diseases is increasing in diagnostic radiation tests. However, the safety management training targets and programs for radiation exposure management operated by other organizations other than diagnostic radiation generators are significantly different. In addition, since the public institutions that are responsible for radiation safety management are divided, there is a risk of duplicative, excessive, and under-administrative application to medical institutions and educational institutions that install and operate diagnostic radiation generators. Therefore, we would like to determine their consistency by comparing domestic and foreign related cases and the provisions of the 「Medical Act」 and the 「Nuclear Safety Act」.

• The Korean Society of Law and Medicine
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• v.14 no.2
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• pp.119-142
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• 2013

It is not easy to regulate the amount of radiation used for the medical purpose as there usually is more good than harm to the patient's health and life caused by the medical exposure to the radiation. However, the rapid increase of the use of diagnostic radiation involves a high possibility of increasing the radiation hazard exposure. Therefore, it is imperative to implement effective regulations in order to secure the safety of diagnostic radiation. The one and only rule we currently have for the diagnostic radiation is "Medicine Act" with only one clause dedicated to regulate the safety management that does not include any rules for the medical radiation. A set of inclusive rules for the whole medical radiation inclusive of diagnostic radiation and therapeutic radiation need to be based on the "Medicine Act" rather than "Nuclear Safety Act" in order to protect the medical professionals, patients and the guardians of patients from the hazards of diagnostic and/or therapeutic radiation that was not used the purpose of medical treatment. If there is an administrative measure to be imposed to secure the safety of diagnostic radiation, it is considered as exertion of governmental authority of administrative agency. There must be clear and realistic legal guidelines for in-fringe on people's interests. The administrative measures for the safety management of the diagnostic radiation must be clearly and specifically based on the law and the detailed standards for the administrative measures must be dele-gated by the presidential decree or departmental ordinance. Accordingly, the restrictions imposed by the administrative measures to the "Safety Inspection Institute of Radiation along with Radiation Exposure Measuring Institutes" should have clear legal basis as well and the detailed standards for the administrative measures should be regulated by the Ministry of Health and Welfare decree instead of the notification by the Director of Korean Centers for Disease Control and Prevention. While securing the safety of radiation on one side, careful review and up-grade on our legal system for the safety management of the diagnostic radiation is required on the other side to guarantee the legality, interest balance and reliability of the administrative measures.

• The Korean Society of Law and Medicine
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• v.23 no.2
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• pp.97-118
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• 2022

The use of diagnostic radiation in medical institutions is rapidly increasing. Accordingly, the collective effective dose is on the rise every year. Therefore, it is necessary to reduce the radiation exposure of the person undergoing the radiation examination as low as reasonably achievable. And we must establish a legal system to perform the safe management of radiation for diagnosis efficiently. In this way, I went over the problems of the Act and Subordinate Statutes regarding radiation safety management for diagnosis. As a result, the main contents are as follows. First, in the 「Medical Service Act」, there is no basis for the Safety Inspection Institute of Radiation and Radiation Exposure Measuring Institutes. And there are no provisions concerning delegation of administrative disposition. Therefore, it is necessary to secure legal justification by providing the basis for the Safety Inspection Institute of Radiation along with Radiation Exposure Measuring Institutes and the basis for administrative dispositions against these institutions in the 「Medical Service Act」. Second, the 「Rules on the Installation and Operation of Special Medical Equipment 」 should be integrated with the 「Rules on the Safety Management of Radiation Generators for Diagnostics」 to unify administrative procedures such as reporting for radiation special medical equipment for diagnosis. Third, in the case of violating the diagnostic radiation safety management standards in the 「Rules on the Safety Management of Radiation Generators for Diagnostics」, it is necessary to supplement the insufficient sanctions such as administrative disposition. Fourth, regulating diagnostic radiation and therapeutic radiation used in medical institutions with the dual legal system of the 「Medical Act」 and the 「Nuclear Safety Act」 is not efficient in the safety management of diagnostic radiation. Therefore, it is necessary to uniformly regulate diagnostic radiation and all medical radiation, including therapeutic radiation and nuclear medicine, in the 「Medical Service Act」 system.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.6
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• pp.494-501
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• 2001

In this paper an ANFIS(Adativo Neuro-Fuzzy Inference System)- based fault detection and diagnosis for a closed loop control system is proposed. The proposed diagnostic system contains two ANFIS. One is run as a parallel model within the model in closed loop control(MCL) and the other is run as a series-parallel model within the process in closed loop(PCL) for the generation of relevant symptoms for fault diagnosis. These symptoms are further processed by another classification logic with simple rules and neural network for process and controller fault diagnosis. Experimental results for a DC shunt motor control system illustrate the effectiveness of the proposed diagnostic scheme.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.16-21
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• 2008

Aero-engine, as one kind of rotating machinery with complex structure and high rotating speed, has complicated vibration faults. Therefore, condition monitoring and fault diagnosis system is very important for airplane security. In this paper, a vibration data acquisition and intelligent fault diagnosis system is introduced. First, the vibration data acquisition part is described in detail. This part consists of hardware acquisition modules and software analysis modules which can realize real-time data acquisition and analysis, off-line data analysis, trend analysis, fault simulation and graphical result display. The acquisition vibration data are prepared for the following intelligent fault diagnosis. Secondly, two advanced artificial intelligent(AI) methods, mapping-based and rule-based, are discussed. One is artificial neural network(ANN) which is an ideal tool for aero-engine fault diagnosis and has strong ability to learn complex nonlinear functions. The other is data mining, another AI method, has advantages of discovering knowledge from massive data and automatically extracting diagnostic rules. Thirdly, lots of historical data are used for training the ANN and extracting rules by data mining. Then, real-time data are input into the trained ANN for mapping-based fault diagnosis. At the same time, extracted rules are revised by expert experience and used for rule-based fault diagnosis. From the results of the experiments, the conclusion is obvious that both the two AI methods are effective on aero-engine vibration fault diagnosis, while each of them has its individual quality. The whole system can be developed in local vibration monitoring and real-time fault diagnosis for aero-engine.

• The Journal of Korean Association of Computer Education
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• v.6 no.4
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• pp.95-113
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• 2003

We introduce an AFES(Adaptive Fuzzy Evaluation System) that applies an evaluation system used to existing LCMS(Learning Contents Management System) to a fuzzy reasoning rule. The AFES confers a course level on the learner through a fuzzy diagnostic evaluation before the learner enters a learning course. After the learner completes a learning course through the tailored learning path that is suitable for the learner's level, the AFES confers a final grade on the learner by means of fuzzy final evaluation. The biggest characteristic of the AFES is a grade rule of the final grade. Although different learners get the same number of correct answers to the same number of Questions, AFES flexibly confers the different final grade on the learner by means of the number of 125's fuzzy reasoning rules.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.211-216
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• 2004

Fuzzy neural networks have been successfully applied to analyze/generate predictive rules for medical or diagnostic data. However, most approaches proposed so far have not considered the weights for the membership functions much. This paper presents a neural network with weighted fuzzy membership functions. In our approach, the membership functions can capture the concentrated and essential information that affects the classification of the input patterns. To verify the performance of the proposed model, well-known Iris data set is performed. According to the results, the weighted membership functions enhance the prediction accuracy. The architecture of the proposed neural network with weighted fuzzy membership functions and the details of experimental results for the data set is discussed in this paper.

• IE interfaces
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• v.3 no.2
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• pp.1-11
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• 1990

In this study, we will present a knowledge-based consulting system, called THYCONS, for diagnosing thyroid disorders. It has been developed to make the knowledge and expertise of the human expert more widely available, therefore achieving a high-quality diagnosis. Frames will be used to represent the medical knowledge of thyroid disorders, and several rules are attached in each slot of a frame. The uncertainty of diagnostic processes is manipulated by the subjective Bayesian method under the assumption that the pieces of evidence are conditionally independent. Searching for the group of diagnostic tests to be carried out and their optimum sequences will be established in order to infer a more correct diagnosis on the basis of maximum information gain with cost and time restrictions. Additionally. differential diagnosis will be carried out based on the information gained.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.859-861
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• 1996

This paper presents the novel fault diagnostic expert system based on dissolved gas analysis(DGA) techniques in power transformer. The uncertainty of key gas analysis, norm threshold, and gas ratio boundaries are managed by using a fuzzy set concept. The uncertainty of rules are handled by fuzzy measures. Trend analysis through the monthly increment of key gas and DGA analysis are combined by the Dempster-Shafer theory, and the state of transformer and confidence factor are yielded by using this combined analysis. To verify the effectiveness of the proposed diagnosis technique, the expert system has been tested by using KEPCO's transformer gas records.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.143-145
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• 1996

This paper presents the hybrid type based expert system for fault diagnosis in transformers. The proposed system uses the novel fault diagnostic technique based on dissolved gas analysis(DGA) in oil-immersed transformers. The uncertainty of key gas analysis, norm threshold, and gas ratio boundaries are managed by using a fuzzy set. Also, the uncertainty of the fault diagnostic rules are handled by using fuzzy measures. Finally, kohnen's feature map performs fault classification in transformers. To verify the effectiveness of the proposed diagnosis technique, the hybrid type based expert system for fault diagnosis has been tested by using KEPCO's transformer gas records.