• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1608-1614
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• 2009

Many learners on E-learning databank based selection system making self-directed progress with learning by diagnosis oneself based on automatically selection questions using degrees of difficulty. This methods is most important to choose a questions using right a way for effective self-directed learning progress of learners. This paper present new question selection algorithms consider for degree of difficulty, scope of learning and keyword of questions according to examination type. This algorithm providers more effective learning diagnosis methods as compared with previous algorithm consider for only degrees of difficulty.

• Journal of Korean Elementary Science Education
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• v.34 no.2
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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.

• Korean Journal of Artificial Intelligence
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• v.8 no.1
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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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• v.14 no.3
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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.

• Proceedings of the KSME Conference
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• 2007.05a
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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.

• Journal of the Korea Society of Computer and Information
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• v.19 no.5
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• pp.11-18
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• 2014

In this paper, we propose a self-diagnosis system that is based on the ART2 algorithm in order to extract more detailed disease information by fuzzy reasoning method especially when the boundary of perceived symptoms are not clearly classified into disease categories. With that modification from previous version of the self health pre-diagnosis system, the proposed one is verified as more effective by field experts' evaluation as an intelligent assistant tool for public users before they consult with medical experts.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.30 no.1
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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.

• Journal of the Korean Institute of Navigation
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• v.16 no.1
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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.

• The Korean Journal of Rehabilitation Nursing
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• v.7 no.2
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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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• v.86 no.5
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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.