• Journal of the Korean Data and Information Science Society
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• v.7 no.2
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• pp.257-262
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• 1996

When we are estimate the smoothing parameter in spline regression model, we deal the diagnostic of influence observations as posteriori analysis. When we use Generalized Maximum Likelihood Function as the estimation method of smoothing parameter, we propose the diagnostic measure for influencial observations in the obtained estimate, and we introduce the finding method of the proper smoothing parameter estimate.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2272-2275
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• 2002

PCA(Principle Component Analysis) has emerged as a useful tool for process monitoring and fault diagnosis. The general approach requires the user to identify the root cause by interpreting the residual or principle components. This could be tedious and often impossible for a large process. In this paper, PCA scheme is combined with the FCM-based fault diagnostic algorithm to enhance the diagnosistic results. The implementation of the PCA-FCM based fault diagnostic system is done and its application is illustrated on the two-tank system.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.4
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• pp.109-116
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• 2009

In the paper, we designed an automatic security diagnostic evaluation System(SeDES) based on a security diagnostic evaluation model(SeDEM) for an organization's security assurance. The SeDEM evaluates a security level of an organization quantitatively by a security evaluation formula which is composed of security variables and security index as applying the statistical CAEL model for evaluate risk level of banks. The SeDES has a good expandability as changing security variables according to an organization scale, characteristics and so on. And it also has a excellent usage because it inputs only numeric data got from statistical technique to security index. We can understand more a security level correctly than the existent risk assessment system because it is possible to assess quantitatively with an security grade as well as score. analysis.

• Journal of information and communication convergence engineering
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• v.17 no.2
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• pp.128-134
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• 2019

Based on the concept of Industry 4.0, various sensors are attached to facilities and equipment to collect data in real time and diagnose faults using analyzing techniques. Diagnostic technology continuously monitors faults or performance degradation of facilities and equipment in operation and diagnoses abnormal symptoms to ensure safety and availability through maintenance before failure occurs. In this paper, we propose a model to analyze the data and diagnose the state or failure using machine learning. The diagnosis model is based on a support vector machine (SVM)-based diagnosis model and a self-learning one-class SVM-based diagnostic model. In the future, it is expected that this model can be applied to facilities used in the entire industry by applying the actual data to the diagnostic model proposed in this paper, conducting the experiment, and verifying it through the model performance evaluation index.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.1377-1380
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• 2010

자동차 내부 네트워크 데이터를 이용하는 자동차-IT 융합 기술은 자동차 안전 및 진단, 텔레매틱스, ITS등 새로운 서비스 시장을 형성하며 산업적인 파급 효과가 클 것으로 전망된다. 이러한 자동차 내부 네트워크 데이터 중 가장 최근에 많이 사용되고 있는 것이 CAN(Controller Area Network) 이다. 그리고 현실적으로 자동차 내부의 데이터 중 사용할 수 있는 가장 적절한 데이터가 Diagnostic CAN 데이터이다. 본 논문에서는 자동차-IT 융합 기술에서 사용할 수 있는 CAN 데이터 중에서 진단용 CAN 데이터에 대하여 알아보고 이를 제품개발에서 사용할 수 있도록 하기 위한 데이터를 수집하고 제공하는 방법에 대하여 알아본다.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.97-102
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• 2013

Objective: The aim of this study was to develop an automated computer-aided diagnostic system for diagnosis of thyroid cancer pattern in fine needle aspiration cytology (FNAC) microscopic images with high degree of sensitivity and specificity using statistical texture features and a Support Vector Machine classifier (SVM). Materials and Methods: A training set of 40 benign and 40 malignant FNAC images and a testing set of 10 benign and 20 malignant FNAC images were used to perform the diagnosis of thyroid cancer. Initially, segmentation of region of interest (ROI) was performed by region-based morphology segmentation. The developed diagnostic system utilized statistical texture features derived from the segmented images using a Gabor filter bank at various wavelengths and angles. Finally, the SVM was used as a machine learning algorithm to identify benign and malignant states of thyroid nodules. Results: The SVMachieved a diagnostic accuracy of 96.7% with sensitivity and specificity of 95% and 100%, respectively, at a wavelength of 4 and an angle of 45. Conclusion: The results show that the diagnosis of thyroid cancer in FNAC images can be effectively performed using statistical texture information derived with Gabor filters in association with an SVM.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.2 no.3
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• pp.61-71
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• 2003

This paper suggests a wireless diagnostic technique using SMS (Short Message Service) of mobile telecommunication network for pole transformer. The temperature and current of pole transformer are acquired and the average and standard deviation are transmitted using SMS of mobile telecommunication network when transformer is overloaded The algorithm and protocol is design to fit the wireless diagnostic technique. By using the wireless method, the weak point of accessability can overcome. It is possible to manage, control, and monitor many transformers with just one server.

• Korean Journal of Digital Imaging in Medicine
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• v.14 no.1
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• pp.13-20
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• 2012

In a normal x-ray examination, the cooperation of a patient in positioning greatly influences the improvement of work performance, the quality of the images and the reduction in time spent on the examination. An attempt was made to discover the connection between an examination information printout and the effects of the examination by informing the patient before the examination on the examination positions in order to increase the level of cooperation by the patient and by surveying the degree of satisfaction of the patient during the examination proceedings. An examination information printout was prepared on five positions that patients consider to be difficult while receiving normal x-ray examinations and were shown to 257 male and female patients between the ages of 30 to 79 who had visited this hospital between January 1 to February 29, 2012 or to a person who had accompanied the patients before the examination to research the degree of satisfaction regarding the printout. In addition, the examination explanation printout was given to Radiologic Technologists with over 1 year experience in this hospital to use while taking the x-rays and the degree of satisfaction was surveyed and it was examined if the increase of the degree of satisfaction had an effect on the reduction in the examination time. The patients who utilized the examination information printout revealed results of approximately a 7.8% higher degree of satisfaction among the patients who had previous experience receiving x-ray examinations compared to those were having an x-ray for the first time. In the age groups between 30 to 70 years of age, the age group in the 30's revealed the lowest level of satisfaction at approximately 69% and the group in the 50's showed the highest degree of satisfaction of 87.94%. In the survey of the Radiologic Technologists, 85% responded that they were satisfied. In the question that stated "Will the examination information printouts reduce the time involved in unnecessary conversations with the patients?," the responses showed a 95% degree of satisfaction. The degree of satisfaction was high over the examination information printout by both the patients and the Radiologic Technologists. Although the effects of examination time reduction varied based on the ages of the patients and physical conditions that they were in and could not be given measurement values, it was able to be seen through the survey that reduction of the unnecessary communication between the patient and the Radiologic Technologists contributed to the increase in the degree of satisfaction. As a result, both the patients and the Radiologic Technologists had an increased degree of satisfaction over the examination information printout and it was possible for improvements to be made in the quality of medical service provided as well. Nevertheless, it is considered that a more developed manual in terms of quality and quantity must be produced using a more systematic approach and design.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.1
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• pp.95-113
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• 1997

This paper outlines a framework for a diagnosis of a complex system with uncertain information. Sensor validation ploys a vital role in the ability of the overall system to correctly determine the state of a system monitored by imperfect sensors. Here, emphases are put on the heuristic technology and post-processor for reasoning. Heuristic Sensor Validation (HSV) exploits deeper knowledge about parameter interaction within the plant to cull sensor faults from the data stream. Finally the modified probability distributions and validated data are used as input to the reasoning scheme which is the runtime version of the influence diagram. The output of the influence diagram is a diagnostic mapping from the symptoms or sensor readings to a determination of likely failure modes. Once likely failure modes are identified, a detailed diagnostic knowledge base suggests corrective actions to improve performance. This framework for a diagnostic expert system with sensor validation and reasoning under uncertainty applies in $HEATXPRT^{TM}$ a data-driven on-line expert system for diagnosing heat rate degradation problems in fossil power plants [1].

• Proceedings of the Korean Society of Veterinary Clinics Conference
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• 2009.04a
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• pp.265-265
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• 2009