• Journal of KSNVE
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• v.10 no.2
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• pp.331-337
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• 2000

The necessity of diagnosis of the rotating machinery which is widely used in the industry is increasing. Many research has been conducted to manipulate field vibration signal data for diagnosing the fault of designated machinery. As the pattern recognition tool of that signal, neural network which use usually back-propagation algorithm was used in the diagnosis of rotating machinery. In this paper, self-organizing feature map(SOFM) which is unsupervised learning algorithm is used in the abnormal defect diagnosis of rotating machinery and then learning vector quantization(LVQ) which is supervised learning algorithm is used to improve the quality of the classifier decision regions.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.832-835
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• 2002

This paper presents a new approach integrated Case-Based Reasoning with Self. Organization Map(SOM) in diagnosis systems. The causes of faults are obtained by case-base trained from SOM. When the vibration problem of rotating machinery occurs, this provides an exact diagnosis method that shows the fault cause of vibration problem. In order to verify the performance of algorithm, we applied it to diagnose the fault cause of the electric motor.

• Proceedings of the Korea Contents Association Conference
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• 2015.05a
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• pp.3-4
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• 2015

A self-organizing map (SOM) is a good tool to visualize applied data in the form of a feature map. With the help of such functions, a disaster risk diagnosis based on the residential house structure is tried in this study. According to some computer simulations with actual residential data, it is found that overall tendencies in the developed feature map are acceptable. Then, it is concluded that the proposed method is an effective means to estimate disaster risk appropriately.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.10
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• pp.69-74
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• 2013

There is needed the triple pyroelectric Infrared flame detector to really recognize problem, for the prevention and early suppression of fire. This system recognizes the characteristics of fire sources in various type and is communicated the message to the operators. Therefore, the prevention and early suppression of fire is available. Especially this paper focuss on development of the self diagnosis type flame detector for preventing malfunction comparing of basic and detected values.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.358-362
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• 2013

RFID reader platform with self-diagnosis function studied in this paper has an automatic state recognition function, a report function, and an automatic upgrade function. Also, since it uses frequency operation policy in multiple reader environments, it will be frequently used in the large operation environment and multi-readers environment. Therefore, the technology can meet the demands not only in the domestic RFID market, but in the global market.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2150-2157
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• 2007

In this paper, we have proposed a self disease diagnosis system for ordinary persons to help the decision of access methods to a specialized medical management, and for medical specialities to discover new diseases and their symptoms easily, using verification of an individual#s health status by a series of processes performed by oneself. In the proposed self disease diagnosis system, illness is decided by 60 kinds of diseases selected using the report called #Diseases that Koreans take seriously# published by Ministry of Health & Welfare and medical contents called #Engel Pharm#, and also using 161 representative symptoms for the 60 kinds of diseases. An individual#s health information is extracted by diagnosis of one#s health status by a clustering of the 60 kinds of diseases using enhanced ART2 algorithm and input vectors from the results of questions for symptoms of each disease.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.328-330
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• 2004

In this paper, ECG based cardiac disease diagnosis models are developed. Conventionally, ECG monitoring equipments can only measure and store ECG signals and they always require medical doctor's diagnosis actions which are not desirable for continuous ambulatory monitoring and diagnosis healthcare systems. In this paper, two kinds of neural based self cardiac disease diagnosis engines are developed and tested for four kinds of diseases, sinus bradycardia, sinus tachycardia, left bundle branch block and right bundle branch block. For diagnosis engines, error backpropagation neural network (BP) and probabilistic neural network (PNN) were applied. Five signal features including heart rate, QRS interval, PR interval, QT interval, and T wave types were selected for diagnosis characteristics. To show the validity of proposed diagnosis engine, MIT-BIH database were used to test. Test results showed that BP based diagnosis engine has 71% of diagnosis accuracy which is superior to accuracy of PNN based diagnosis engine. However, PNN based diagnosis engine showed superior diagnosis accuracy for complex-disease diagnoses than BP based diagnosis engine.

• The Journal of Korean Society for School & Community Health Education
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• v.12 no.3
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• pp.1-15
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• 2011

Objectives: We describe the development of a smoking and drinking prevention program for adolescents, using intervention mapping. Methods: The study sample consisted of 1,000 high school second-grade students from 6 high schools in Seoul. The PRECEDE model was applied for the needs assessment. We carried out a social diagnosis by assessing the factors such as the quality of life, happiness level, and satisfaction with school life; an epidemiological diagnosis on the perceived health status, stress levels, and priority of health issues; a behavioral diagnosis on the smoking and drinking rate and the intention to smoke and drink; and an educational diagnosis on knowledge, beliefs, attitudes, self-efficacy, outcome expectations, social norms and life skills. Results: The development process included a needs assessment, identifying factors that influence smoking and drinking among adolescents. Intention, knowledge, perceived norms, perceived benefit, perceived cost, perceived susceptibility, self-efficacy, and life skills were identified as determinants. Three performance objectives were formulated to describe what an individual needs to do in order to avoid smoking and drinking. Subsequently, we constructed an intervention matrix by crossing the performance objectives with the selected determinants. Each cell describes the learning objectives of the smoking and drinking prevention program. The program used methods from the transtheoretical model, such as consciousness raising, outcome expectations, self-reevaluation, self-liberation, counterconditioning, environmental reevaluation, and stimulus control. The program deals with the effects of smoking and drinking, self-improvement, decision making, understanding advertisements, communication skills, social relationships, and assertiveness. Conclusions: By using the process of intervention mapping, the program developer was able to ensure a systematical incorporation of empirical and new data and theories to guide the intervention design. Programs targeting other health-related behavior and other methods or strategies can also be developed using this intervention mapping process.

• Journal of Korean Public Health Nursing
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• v.29 no.3
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• pp.582-593
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• 2015

Purpose: This study was conducted to examine the effectiveness of a self-management program on patients with thyroid cancer, particularly during the time of waiting for surgery after cancer diagnosis. Psychological distress, biological responses of immune cell counts, and quality of life were the variables of this study. Methods: One group pre-post test design was used with the nature of a pilot study. Ten newly diagnosed thyroid cancer patients were recruited through physicians' referrals. After drop out of 4 participants, final data were collected from six participants. Small group technique, a one and half hour-session per week for one month (total 4 sessions, 6 hours) was used. Relaxation techniques, meditation training, and strategies to reduce distress were provided by researchers. Standardized questionnaires and an established bio-assay were used for collection of data. Results: Participants showed significant lowering of psychological distress (p<.05) and improvement in global quality of life (p<.05). Biological responses of immune cell counts did not show statistical significance. Conclusion: The self-management program may reduce psychological distress and improve quality of life of patients with thyroid cancer between the time of diagnosis and surgery. The self-management program would be a valuable approach for patients with an unexpected cancer diagnosis to prepare for their disease experience in a community setting.

• Journal of Hospice and Palliative Care
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• v.19 no.2
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• pp.170-179
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• 2016

Purpose: This study examined self-efficacy, self-care behavior, posttraumatic growth, and quality of life in cancer patients and their levels by disease characteristics groups to identify patient groups that require psychosocial intervention. Methods: We surveyed 107 patients using a structured questionnaire about the four factors and analyzed the factors by stratifying the patients by the period after the cancer diagnosis, by stage and by current treatment status. Results: The mean score for self-efficacy was 37.78, and that for self-care behavior 49.96. Patients who were diagnosed less than one year ago scored higher on medication, a sub-category of self-care behavior, than the post-diagnosis period of 1~2 year group. The score was higher in the currently-treated group than the follow-up and distant metastasis groups. For posttraumatic growth, the mean was 56.17, and the factor was higher in the 1~2 year post-diagnosis group after than the less than one year group. The score was higher in the follow-up group than the currently-treated group. With regard to quality of life, the mean score was 25.79, and no significant correlation was found with disease characteristics. Conclusion: A shorter post-diagnosis period increased self-care behavior, and the greatest posttraumatic growth was reported by the 1~2 year post-diagnosis group. It may be necessary to provide cancer patients with an education program and other strategies less than one year after the diagnosis to improve self-efficacy and self-care behavior. To promote post-traumatic growth, it may be helpful to provide patients with psychosocial intervention within two years after the diagnosis.