• 한국정보통신학회논문지
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• 제13권8호
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• pp.1608-1614
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• 2009

이러닝 문제은행기반 출제시스템에서 많은 학습자들은 난이도에 따른 자동 출제 문제들을 기반으로 스스로를 진단함으로써 자기 주도적으로 학습을 진행한다. 이러한 방식에서 학습자들의 효율적인 자기 주도적 학습 진행을 위해서는 정당한 방법으로 출제되는 문제가 무엇보다 중요하다. 본 논문에서는 효율적인 자기 진단 평가를 위해, 평가의 종류에 따라 난이도뿐만 아니라 학습 범위와 문제의 키워드를 함께 고려하는 새로운 방법의 문제 출제 알고리즘을 제시한다. 이는 기존의 난이도만을 고려한 자동 출제 방식에 비해 자기 주도적 학습자에게 보다 효과적인 학습 진단 방법을 제공할 수 있다.

• 한국초등과학교육학회지:초등과학교육
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• 제34권2호
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• pp.153-163
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• 2015

In this study, we analyzed elementary school teachers' self-diagnosis on their competency for assessment in science. A questionnaire was administered to 217 elementary school teachers and in-depth group interviews with 6 teachers were also conducted. The results revealed that the mean scores of five subcategories, 'choosing assessment methods', 'developing assessment instruments', 'administering, scoring, and grading', 'analyzing, interpreting, using, and communicating assessment results', and 'recognizing ethics in assessment', were 3.82, 3.50, 3.92, 3.76, and 4.09 on a scale of 5 points, respectively. Teachers having more teaching experience showed higher mean scores in all subcategories. However, only the teachers having more than 20 years of teaching experience were statistically better than those having less than 5 years of teaching experience in four subcategories except for 'recognizing ethics in assessment'. There were no significant differences in terms of major, whereas the mean scores of the teachers having master's degree were statistically higher than their counterpart in some subcategories. In addition, the teachers who had completed training for assessment exhibited statistically higher mean scores than their counterpart in four subcategories except for 'recognizing ethics in assessment'. Educational implications of these findings are discussed.

• 한국인공지능학회지
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• 제8권1호
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• pp.7-9
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• 2020

In this paper, a study was conducted to find a self-diagnosis method to prevent the spread of COVID-19 based on machine learning. COVID-19 is an infectious disease caused by a newly discovered coronavirus. According to WHO(World Health Organization)'s situation report published on May 18th, 2020, COVID-19 has already affected 4,600,000 cases and 310,000 deaths globally and still increasing. The most severe problem of COVID-19 virus is that it spreads primarily through droplets of saliva or discharge from the nose when an infected person coughs or sneezes, which occurs in everyday life. And also, at this time, there are no specific vaccines or treatments for COVID-19. Because of the secure diffusion method and the absence of a vaccine, it is essential to self-diagnose or do a self-diagnosis questionnaire whenever possible. But self-diagnosing has too many questions, and ambiguous standards also take time. Therefore, in this study, using SVM(Support Vector Machine), Decision Tree and correlation analysis found two vital factors to predict the infection of the COVID-19 virus with an accuracy of 80%. Applying the result proposed in this paper, people can self-diagnose quickly to prevent COVID-19 and further prevent the spread of COVID-19.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권3호
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• pp.1167-1187
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• 2020

With the development of medical imaging technology, image registration has been widely used in the field of disease diagnosis. The registration between different modal images of brain magnetic resonance (MR) is particularly important for the diagnosis of brain diseases. However, previous registration methods don't take advantage of the prior knowledge of bilateral brain symmetry. Moreover, the difference in gray scale information of different modal images increases the difficulty of registration. In this paper, a multimodal medical image registration method based on image segmentation and symmetric self-similarity is proposed. This method uses modal independent self-similar information and modal consistency information to register images. More particularly, we propose two novel symmetric self-similarity constraint operators to constrain the segmented medical images and convert each modal medical image into a unified modal for multimodal image registration. The experimental results show that the proposed method can effectively reduce the error rate of brain MR multimodal medical image registration with rotation and translation transformations (average 0.43mm and 0.60mm) respectively, whose accuracy is better compared to state-of-the-art image registration methods.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회A
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• pp.455-460
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• 2007

A self-sensing circuit for piezo inkjet has been designed in order to monitor the operating condition during printing. In order to verify the circuit, both ink droplet images from strobe LED and vibration signals from the laser vibrometer were measured and compared with self-sensing signal. Experimental results show that self-sensing signal was effective in detecting the pressure wave change due to the bubble trapped in inkjet printhead.

• 한국컴퓨터정보학회논문지
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• 제19권5호
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• pp.11-18
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• 2014

본 논문에서는 ART2 알고리즘을 이용하여 질병을 도출하고 증상의 차이를 구분하기 위해서 애매한 증상의 정도를 퍼지 추론 방법에 적용하여 더욱더 정확한 질병 상세를 도출할 수 있는 개선된 자가진단 시스템을 제시한다. 본 논문에서 제안한 방법을 전문의에게 분석을 의뢰한 결과, 본 논문에서 제안된 자가진단 시스템 방법이 이전의 방법보다, 지능형 자가 보조 진단 시스템으로서 사용자에게 더욱 효과적인 도움을 줄 수 있는 가능성을 확인하였다.

• 조명전기설비학회논문지
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• 제30권1호
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• pp.49-54
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• 2016

There is needed the quard channel triple wave lengths pyroelectric infrared flame detector to recognize the unique characteristics of fire sources in various type. This system detects the triple wave lengths of infrared flame emitting maximum radient energy and scattering frequency of flame. The quard channel infrared flame detector detects the duplicate wave lengths of maximum radient energy to enhance the accuracy of detecting fire. Especially this paper focuss on development of the self diagnosis function system including contamination, temperature and input voltage. Therefore, the prevention and early suppression of fire is available.

• 한국항해학회지
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• 제16권1호
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• pp.1-12
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• 1992

In this study, the self test-system for the marine Gyrocompass was developed and the obtained results are summarized as follows : 1) Utilizing the newly developed self-test system, the time length for observing the transient state of Gyrocompass reading which has been over 4 hours can be reduced to less than 20 minutes. In addition, the dynamic characteristics of the Gyrocompass can be measured within 2 hours after starting the system. 2) Prior test and diagnosis was done by checking all parameters recurrently with period of 2.5minutes. 3) Testing and diagnosis results was shown in graphic mode and could be transmitted to INMARSAT unit using personal computer. 4) The results of the newly designed trouble algorithm for the system was found to be applicable under arbitrary given conditions.

• 재활간호학회지
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• 제7권2호
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• pp.127-139
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• 2004

Purpose: This study was to investigate the degree of body image, self esteem and quality of life, to identify general and disease of characteristics on influencing this factors with the intention of providing basal data for developing nursing intervention to promote body image, self esteem and quality of life. Method: Subjects of this study were 91 grown-up congenital heart patients over 18 years in 2 tertiary hospitals. The data on body image, self esteem and quality of life were collected through questionnaire from March to April 2004. The data were analyzed by descriptive statistics, t-test, Pearson's correlation, ANOVA and tukey test using SAS for Windows 8.1 program. Result: 1) The mean scores of body image, self esteem and quality of life were 63.01, 25.29 and 496.79. 2) Body image was correlated with age(p=.0239), educational level(p=.0182), diagnosis(p=.0066), number of operation(p=.0148), cyanosis(p<.0001), complication(p=.0096) and NYHA level(p=.0378). 3) Self esteem was correlated with education level(p=.0026), economic level(p=.0240), number of operation(p=.0113) and cyanosis (p=.0006). 4) Quality of life was correlated with age(p=.0432) and diagnosis(p=.0020), number of operation (p=.0063), duration of last operation(p=.0225), cyanosis(p<.0001), complication(p=.0090) and NYHA level(p<.0001). 5) There was significantly positive relationship between body image, self esteem and quality of life. Subjects with more positive body image had higher self esteem(r=.7897, p<.05) and subjects with higher self esteem had higher quality of life(r=.6091, p<.05).

• Structural Engineering and Mechanics
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• 제86권5호
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• pp.589-605
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• 2023

This paper investigates the ductility demands of steel frames equipped with self-centring fuses under near-fault earthquake motions considering multiple yielding stages. The study is commenced by verifying a trilinear self-centring hysteretic model accounting for multiple yielding stages of steel frames equipped with self-centring fuses. Then, the seismic response of single-degree-of-freedom (SDOF) systems following the validated trilinear self-centring hysteretic law is examined by a parametric study using a near-fault earthquake ground motion database composed of 200 earthquake records as input excitations. Based on a statistical investigation of more than fifty-two (52) million inelastic spectral analyses, the effect of the post-yield stiffness ratios, energy dissipation coefficient and yielding displacement ratio on the mean ductility demand of the system is examined in detail. The analysis results indicate that the increase of post-yield stiffness ratios, energy dissipation coefficient and yielding displacement ratio reduces the ductility demands of the self-centring oscillators responding in multiple yielding stages. A set of empirical expressions for quantifying the ductility demands of trilinear self-centring hysteretic oscillators are developed using nonlinear regression analysis of the analysis result database. The proposed regression model may offer a practical tool for designers to estimate the ductility demand of a low-to-medium rise self-centring steel frame equipped with self-centring fuses progressing in the ultimate stage under near-fault earthquake motions in design and evaluation.