• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.140-146
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• 2021

As the environment using intelligent IoT devices increases, various studies are underway to ensure the integrity of information sent and received from intelligent IoT devices. However, all IoT information generated in heterogeneous environments is not fully provided with reliable protocols and services. In this paper, we propose an intelligent-based multi-blockchain model that can extract only critical information among various information processed by intelligent IoT devices. In the proposed model, blockchain is used to ensure the integrity of IoT information sent and received from IoT devices. The proposed model uses the correlation index of the collected information to trust a large number of IoT information to extract only the information with a high correlation index and bind it with blockchain. This is because the collected information can be extended to the n-tier structure as well as guaranteed reliability. Furthermore, since the proposed model can give weight information to the collection information based on blockchain, similar information can be selected (or bound) according to priority. The proposed model is able to extend the collection information to the n-layer structure while maintaining the data processing cost processed in real time regardless of the number of IoT devices.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.1-6
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• 2021

In the field of speech recognition, as the DNN is applied, the use of speech recognition is increasing, but the amount of calculation for parallel training needs to be larger than that of the conventional GMM, and if the amount of data is small, overfitting occurs. To solve this problem, we propose an efficient method for robust voice feature extraction and voice signal noise removal even when the amount of data is small. Speech feature extraction efficiently extracts speech energy by applying the difference in frame energy for speech and the zero-crossing ratio and level-crossing ratio that are affected by the speech signal. In addition, in order to remove noise, the noise of the speech signal is removed by removing the noise of the speech signal with an average predictive improved LMS filter with little loss of speech information while maintaining the intrinsic characteristics of speech in detection of the speech signal. The improved LMS filter uses a method of processing noise on the input speech signal by adjusting the active parameter threshold for the input signal. As a result of comparing the method proposed in this paper with the conventional frame energy method, it was confirmed that the error rate at the start point of speech is 7% and the error rate at the end point is improved by 11%.

• Journal of Convergence for Information Technology
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• v.11 no.7
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• pp.242-252
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• 2021

This study examines the mediating effect of self-directed learning between the self-leadership and academic self-efficacy of beauty major Chinese(CN) students and examines the variables affecting the academic-self-efficacy of CN students. The study aims to obtain basic data to help improve college life in foreign countries. A survey was conducted upon 440 beauty major CN students in universities across Seoul. The results of the study showed differences in self-directed learning according to the number of semesters they have been in Korea and in academic self-efficacy according to their TOPIK levels. Self-directed learning was found to have a partial mediating effect between self-leadership and academic self-efficacy of CN students. These results showed that self-leadership and self-directed learning are major predictors of the academic self-efficacy, which is further reinforced when self-leadership and self-directed learning are promoted together. These results imply that there should be preceding efforts to promote both self-leadership and self-directed learning to increase the self-efficacy of CN students majoring in beauty.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.54-67
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• 2021

This study is a secondary data study that analyzes the factors affecting the quality of life of the elderly with metabolic syndrome and the elderly with metabolic syndrome with osteoporosis using data from the 7th year of the National Health and Nutrition Survey (2018). The subjects of this study were 639 patients with metabolic syndrome and 161 patients with metabolic syndrome with osteoporosis. For data analysis, the composite sample Rao-Scott χ2 test, general linear model t-test, and regression model were used. As a result of the study, the factors that lowered the quality of life of metabolic syndrome were age, cohabitation, strength training, subjective health status, activity restriction, body mass index and depression, and the explanatory power was 50.4% (F=515.96, p<.001). In metabolic syndrome with osteoporosis, age, subjective health status, activity restriction, and stress were the factors that lowered the quality of life, and the explanatory power was 48.6% (F=10.42, p<.001). Based on these results, it is necessary to develop and provide an intensive multidisciplinary program for the elderly with metabolic syndrome accompanied by osteoporosis to solve the problem of activity restrictions and manage stress reduction through positive acceptance of health status, instrumental and social support, and caring support.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.68-76
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• 2021

This study was attempted to understand the relationship between the attitudes toward abortion, euthanasia, and the level of perception of good death among nursing college students and related factors. The data were collected by using structured questionnaires and the subjects were selected in C and G city. The research method was a descriptive research study, and the mean, standard deviation, frequency analysis, and Pearson's correlation coefficients were analyzed for the variables. The results of this study are as follows. The degree of support for the abortion opposition was 2.51±.56 (score range 1-4), and the opposition to abortion was superior to the approval..The perception of euthanasia was 3.06±.47 points (4 point scale), which was positively recognized at a higher level than the middle, and the good death perception was 2.97±.47 points (4 point scale), which was moderate. 97.1% of the respondents said that they had abortion decisions, and 5.7% of the university students experienced abortion. The attitude toward abortion showed negative correlation with the attitude toward euthanasia (r=-.374, p<.001), showing that the more supportive the anti-abortion, the more positive the attitude toward euthanasia. Therefore, it is necessary to educate the subjects to protect and respect the human rights of patients based on the dignity of life and humanistic thinking while providing nursing services.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.111-118
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• 2022

This study is an analysis of auditor's response to audit risk. Specifically, audit risk is measured by the amount of correction of the current financial statements, and auditor's response is measured by the rate of change of audit hour in next auditing. The amount of correction can be viewed as audit risk recognized by auditor because the degree of auditor's correction will increase as the company's financial statement preparation ability is lower or the profit management amount is larger. Auditor's response is measured as the rate of change of audit hour because audit risk would be incorporated in audit plan. Although auditing is performed by a team, auditor's response would differ depending on their roles. It is expected the leaders who establish the audit plan and manage the audit quality would respond more sensitively to audit risk than the other auditors. The results show that when the amount of correction is greater than a certain level, auditors recognize it as audit risk and increase total(and leaders') audit hour in next year audit.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.219-230
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• 2022

This study aims to evaluate the effect of sleep duration on obesity in Korean adult using data from the 8th Korea National Health And Nutrition Examination Survey in 2019. The study subjects were 5,213, and we performed frequency analysis, descriptive statistics, and multivariate regression analysis using the SPSS Win 27.0 program. The average sleep duration of the subjects was 6.8 hours per day, and the average body mass index (BMI) was 23.9 kg/m². As a result of bivariate analysis of factors affecting sleep duration, age, education level, stress, depression, diabetes, hypertension, and arthritis were significantly associated with sleep duration. The body mass index (BMI) of the group with less than 6 hours of sleep duration was 24.4, which was higher than that of other groups, and there was a significant negative correlation between sleep duration and BMI (B=-0.247; 95% CI=-0.334~ -0.160). In conclusion, in order to prevent obesity in adults, various efforts from the country and local communities are needed to increase sleep duration.

• Journal of Convergence for Information Technology
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• v.12 no.1
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• pp.109-118
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• 2022

This study was conducted to emphasize the importance of oral health education by identifying the relationship between the oral health knowledge level, the oral health education request level, and Geriatric Oral Health Assessment Index(GOHAI) of the elderly. The survey was conducted on 191 elderly people aged 65 and over living in Chungbuk from January 6, 2020 to February 7, 2020, and for data analysis, χ2-test, t-test, Pearson correlation analysis, logistic regression analysis were performed. As a result, it was found that the quality of life as measured by GOHAI increased when they had oral health education experience, had a high level of oral health knowledge and oral health education request level, and had regular oral examinations. Based on the above results, in order to improve the quality of life related to oral health of the elderly, it is necessary to prepare policies to increase the participation rate by developing and continuously expanding opportunities for oral health education in various ways.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.30-37
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• 2021

Various devices are connected to the Internet, and attacks using the Internet are occurring. Among such attacks, there are attacks that use malicious URLs to make users access to wrong phishing sites or distribute malicious viruses. Therefore, how to detect such malicious URL attacks is one of the important security issues. Among recent deep learning technologies, neural networks are showing good performance in image recognition, speech recognition, and pattern recognition. This neural network can be applied to research that analyzes and detects patterns of malicious URL characteristics. In this paper, performance analysis according to various parameters was performed on a method of detecting malicious URLs using neural networks. In this paper, malicious URL detection performance was analyzed while changing the activation function, learning rate, and neural network structure. The experimental data was crawled by Alexa top 1 million and Whois to build the data, and the machine learning library used TensorFlow. As a result of the experiment, when the number of layers is 4, the learning rate is 0.005, and the number of nodes in each layer is 100, the accuracy of 97.8% and the f1 score of 92.94% are obtained.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.232-241
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• 2021

This study was conducted to prepare a countermeasure for turnover due to the effect of education satisfaction at franchise stores on turnover factors through the medium of education requirements. In the method of collecting data, 237 copies of the questionnaire method were used as the final data. The results are first, the analysis of educational requirements in general characteristics shows that academic background (F=5.655, p<).01), Analysis of the factors for turnover shows that position (t=-2.809, p<).Significant differences were shown in 01. Second, educational satisfaction is the educational requirement (r=-.16, p<).The correlation between 05) and turnover factors (r=-.18) is significant, and the educational requirement is turnover factors (r=.53, p<).It is shown to be a significant static correlation with 01. Third, designers (B=.25), t=2.332, p<.05) and educational requirements (B=.88, t=9.313, p<).001) has been shown to have significant static effects. Fourth, the educational requirements for educational satisfaction and turnover factors are significant (β=.52, p<).We can see that it is fully mediated by 001.Therefore, it is believed that it will be possible to investigate quarterly satisfaction and demand after communication and training with workers at direct stores, and reduce turnover through various curriculum education.