• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.430-434
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• 2001

Virtual manufacturing system is integrated computer model that represents the precise and whole structure of manufacturing system and simulates its physical and logical behavior in operation.[1] A virtual machine is computer model that represents a CNC machine tool and one of core elements of virtual manufacturing system. In this paper, it is emphasized that a virtual machine must be web-based system for serving information to all attendants in a real machine tool without the restriction of time or location, and then in the fault diagnosis, one of important modules of a virtual machine, the methods of both using the controller signal and web-based expert system are proposed.

• 제어로봇시스템학회논문지
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• 제16권7호
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• pp.661-667
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• 2010

This paper presents a failure diagnosis and accommodation strategy which is capable of tolerating faulty actuators of a submersible vehicle. The proposed method is mainly based on a sliding mode control technique. The primary ideas include a performance index to describe the effectiveness of actuators, and a controller reconfiguration strategy using the actuator effectiveness index. The actuator effectiveness proposed in this work is defined as the relationship between the sliding surface and the controlled system behavior. The resulting actuator effectiveness is then used in reconfiguring the controller in order to counteract for the deteriorated control performance in the presence of a faulty actuator. The effectiveness of the proposed method is demonstrated by means of numerical simulations with a submersible vehicle.

• The Korean Journal of Pain
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• 제31권3호
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• pp.147-154
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• 2018

Fibromyalgia (FM) is a contested illness with ill-defined boundaries. There is no clearly defined cut-point that separates FM from non-FM. Diagnosis of FM has been faced with several challenges that occur, including patients' health care-seeking behavior, symptoms recognition, and FM labeling by physicians. This review focuses on important but less visible factors that have a profound influence on under- or over-diagnosis of FM. FM shows different phenotypes and disease expression in patients and even in one patient over time. Psychosocial and cultural factors seem to be a contemporary ferment in FM which play a major role in physician diagnosis even more than having severe symptom levels in FM patients. Although the FM criteria are the only current methods which can be used for classification of FM patients in surveys, research, and clinical settings, there are several key pieces missing in the fibromyalgia diagnostic puzzle, such as invalidation, psychosocial factors, and heterogeneous disease expression. Regarding the complex nature of FM, as well as the arbitrary and illusory constructs of the existing FM criteria, FM diagnosis frequently fails to provide a clinical diagnosis fit to reality. A physicians' judgment, obtained in real communicative environments with patients, beyond the existing constructional scores, seems the only reliable way for more valid diagnoses. It plays a pivotal role in the meaning and conceptualization of symptoms and psychosocial factors, making diagnoses and labeling of FM. It is better to see FM as a whole, not as a medical specialty or constructional scores.

• 여성건강간호학회지
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• 제25권3호
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• pp.273-284
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• 2019

Purpose: As the number of infertile couples has grown, many infertile women have experienced depression during the diagnosis and treatment of their infertility. This study aimed to identify the factors related to depression in infertile women who underwent reproductive treatments. Methods: The study subjects were 149 infertile women who underwent reproductive treatments. The data were collected by self-administered questionnaires from August 1 to December 24, 2018. The questionnaire consisted of questions about fatigue, health-promoting behavior, and depression. Analyses of the descriptive statistics, t-tests, one-way analysis of variance, correlation, and multiple regression were conducted using the SPSS 25.0 Windows program. Results: Thirty-six of the women in the study (24.2%) were in the probably depressed group and 113 (75.8%) were in the definitely depressed group and 100% of the subjects experienced symptoms of depression. Depression was positively correlated with fatigue and negatively correlated with health-promoting behavior. Multiple regression analysis revealed that fatigue and interpersonal relationships were factors significantly related to depression in the model (p<.001), with an explanatory power of 42.6%. Conclusion: The results confirmed that fatigue and interpersonal relationships, which is a subfactor of health-promoting behavior, were factors related to depression. To alleviate depression in infertile women, efforts should be made to identify and reduce psychological and physical fatigue. In addition, minimizing relational difficulties that they experience during an infertility diagnosis and treatment and strengthening positive interpersonal relationships can be positive strategies to alleviate depression.

• 성인간호학회지
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• 제25권6호
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• pp.610-621
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• 2013

Purpose: The study was designed to identify influencing and mediating factors of health behaviors of stroke patients based on the hypothetical model constructed in this study. Methods: Non-experimental correlational research design was used. One hundred and five stroke patients were conveniently selected from one university hospital located in Incheon. Data were collected with survey and analyzed by path analysis to examine the significant influencing and mediating factors of health behaviors in stroke patients. Results: Age, diagnosis, disability in ADL, knowledge related to health behavior, and self-efficacy had significant direct causal influences on health behavior. And it was shown that knowledge and self-efficacy mediated influence of cohabitation status with family( whether or not living together with family) on health behavior. Self-efficacy also mediated influence of knowledge on health behavior. Conclusion: From the results, it was proposed that providing knowledge related to health behavior and enhancing self-efficacy by educating skill necessary for health behaviors and promoting health related beliefs might increase health behavior particularly for stroke patients living together with family.

• 보건의료산업학회지
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• 제7권3호
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• pp.261-273
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• 2013

The purpose of this study is a chronic liver disease that affects the drinking behavior is to identify the factors. The subjects of the study was diagnosed with chronic liver disease outpatient visit were studied in 120 patients. The collected data were analyzed by using SPSS WIN 18.0. Drinking behavior of chronic liver disease to determine the factors influencing the results of the multiple regression analysis, the regression model was found to be significant(F=8.58, p<.001), drinking behavior of chronic liver disease a major contributor to the drinking habits(${\beta}$ = -.29, p = .004)was found in, followed by drinking motives(${\beta}$ = .20, p = .044), drinking refusal self-efficacy(${\beta}$ = -.17, p = .037), after which the diagnosis of the disease(${\beta}$ = .15, p = .041), respectively. These variables showed explanatory power of 44.1%. Drinking behavior is a serious health problem in patients with chronic liver disease. The factors that influence drinking behavior by considering the management of chronic liver disease drinking continued to provide information and education is needed abstinence.

• 드라이브 ㆍ 컨트롤
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• 제9권4호
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• pp.8-13
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• 2012

Recently, researches about the eco-friendly vehicles such as hybrid electric vehicle, fuel cell vehicle and electric vehicle have been actively carried out. The regenerative braking system is a key technology to improve the vehicle energy utilization efficiency because it transforms the kinetic energy to the electric energy through the electric motor. This new braking system requires cooperative control between electric controlled brake and regenerative brake. Therefore, it is necessary to establish fault-diagnosis and fail-safe evaluation criteria to secure reliability of the regenerative braking system. In this paper, the failure types and causes in regenerative braking system were analyzed. The transient behavior characteristics were examined based on fault-diagnosis and fail-safe upon failure of regenerative braking system.

• 중환자간호학회지
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• 제5권1호
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• pp.34-43
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• 2012

Purpose: This study is a descriptive correlational study to examine the effects of spousal supports and self-efficacy on adherent behavior and to describe nursing intervention programs for patients with percutaneous coronary intervention. Methods: The subjects for this study were 120 patients treated with percutaneous coronary intervention in H hospital in B city > 6 months. The data was collected from June 1 to September 30, 2010. Spousal supports were measured by the Family Support questionnaire. Self-efficacy was measured by revised Self Efficacy questionnaire. Adherent behavior was measured by revised Adherence Behavior questionnaire. Results: A multiple regression analysis showed that the most significant predictor of adherent behavior was self-efficacy, followed by spousal support, whether the subjects do regular exercise and the type of diagnosis. Conclusion: Findings suggest that intervention focusing on self-efficacy and spousal support will be needed to improve the adherent behavior among patients with percutaneous coronary intervention.

• 보건교육건강증진학회지
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• 제10권1호
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• pp.9-20
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• 1993

This study was conducted to show one case model for a community nutrition program as a part of the public health systems. The purpose of this study is to evaluate the effect of the nutrition education through the Knowledge(K), Attitude(A), and Practice of the nutrition that is the Behavior-Diagnosis(Be-D). The Nutrition Education was done for 33 housewives whom live in Sudong-Myeun, Namyangju-Kun, Kyungki-Do. It had been performed eight times during April 3rd through May 30th, 1991. We investigated actual conditions of objects about K, A, Be-D in the nutrition, and the Food Environment(En) separately before and after the nutrition education by questionnaire and interview. The results of the research turned out as follows ; 1. The comparison of the scores before and after nutrition education showed significant increase in the knowledge and attitude. 2. The scores of the Be-D were also significantly higher after education, especially in the number of foods taken per day, the balanced diet, the general food habits for adult, and amounts of intake of nutrients showed significant increase of lipid, calcium, Vit. A, $Vit B_2$, Vit. C after nutrition education. 3. Multiple regression analysis showed that the scores of the Knowledge and En were significantly associated with the number of food taken per day for condition of adjusting socio-demografic factor and A effect. Also, En was important variable in explanation of the balanced diet and A, En were important in the general food habits for adult.

• International Journal of Advanced Culture Technology
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• 제12권3호
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• pp.148-158
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• 2024

We investigate Autism Spectrum Disorder (ASD), which is typified by deficits in social interaction, repetitive behaviors, limited vocabulary, and cognitive delays. Traditional diagnostic methodologies, reliant on expert evaluations, frequently result in deferred detection and intervention, particularly in South Korea, where there is a dearth of qualified professionals and limited public awareness. In this study, we employ advanced deep learning algorithms to enhance early ASD screening through automated video analysis. Utilizing architectures such as Convolutional Long Short-Term Memory (ConvLSTM), Long-term Recurrent Convolutional Network (LRCN), and Convolutional Neural Networks with Gated Recurrent Units (CNN+GRU), we analyze video data from platforms like YouTube and TikTok to identify stereotypic behaviors (arm flapping, head banging, spinning). Our results indicate that the LRCN model exhibited superior performance with 79.61% accuracy on the augmented platform video dataset and 79.37% on the original SSBD dataset. The ConvLSTM and CNN+GRU models also achieved higher accuracy than the original SSBD dataset. Through this research, we underscore AI's potential in early ASD detection by automating the identification of stereotypic behaviors, thereby enabling timely intervention. We also emphasize the significance of utilizing expanded datasets from social media platform videos in augmenting model accuracy and robustness, thus paving the way for more accessible diagnostic methods.