• Journal of Digital Convergence
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• v.14 no.7
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• pp.175-184
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• 2016

The purpose of the study focuses on increasing dangers of using smartphones while driving recently, and then is to come up with measures to reduce traffic accidents caused by using devices like a smartphone. This study conducted a survey of drivers using their smartphones while driving to understand risks caused by using a smartphones while operating vehicles. Results showed that a lot of activities may lead to distracted driving, such as texting, making phone calls, using GPS or road maps, game, etc. In this paper, we presented that functions of smartphone should be controlled partially while driving for safe driving performance. These results suggest that using IoT-based smart devices like a beacon and a smartphone application implemented, tentatively called "Safe driving solution", while driving can reduce traffic accidents. Thus, in order to effectively prevent dangerous driving due to the use of smartphones, a "Safe driving solution" which restricts all functions except for calls and driver assistance functions is suggested.

• Journal of the Korea Convergence Society
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• v.11 no.5
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• pp.183-189
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• 2020

This study was carried out to find out the acquisition effect by measurement periods of adult learners learning through English pattern practice. The subjects of this study were divided into adult learner groups including the learners in their 40s and those who were over 65 and the child group who were 8 years old as a comparative group. After the subjects had a pre-test at first, person agreement and tense were instructed though English pattern practice and right after that, they had a post-test. Then 4 weeks later, they had a delayed test. As a result, the acquisition result of adult learners learning though English pattern practice showed the largest rise by those in their 40s and the learners of those over 65. However the adult learners aged over 65 showed the largest drop in delayed test of the reading comprehension. Based on these results, it is necessary to develop teaching method for adult learners in consideration of their characters and weak points.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.3
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• pp.190-197
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• 2004

This paper presents automated prediction of transient ischemic episodes using neural networks(NN) based pattern matching method. The learning algorithm used to train the multilayer networks is a modified backpropagation algorithm. The algorithm updates parameters of nonlinear function in a neuron as well as connecting weights between neurons to improve learning speed. The performance of the method was evaluated using ECG signals of the MIT/BIH long-term database. Experimental results for 15 records(237 ischemic episodes) show that the average sensitivity and specificity of ischemic episode prediction are 85.71% and 71.11%, respectively. It is also found that the proposed method predicts an average of 45.53［sec］ ahead real ischemia. These results indicate that the NN approach as the pattern matching classifier can be a useful tool for the prediction of transient ischemic episodes.

• Journal of the Korea Convergence Society
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• v.10 no.10
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• pp.7-13
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• 2019

The natural gas (NG), mostly methane leaks into the air, it is a big problem for the climate. detected NG leaks under U.S. city streets and collected data. In this paper, we introduced a Deep Neural Network (DNN) classification of prediction for a level of NS leak. The proposed method is OrdinalEncoder(OE) based K-means clustering and Multilayer Perceptron(MLP) for predicting NG leak. The 15 features are the input neurons and the using backpropagation. In this paper, we propose the OE method for labeling target data using k-means clustering and compared normalization methods performance for NG leak prediction. There five normalization methods used. We have shown that our proposed OE based MLP method is accuracy 97.7%, F1-score 96.4%, which is relatively higher than the other methods. The system has implemented SPSS and Python, including its performance, is tested on real open data.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.147-154
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• 2021

This study focused on the fitting window structure provided by the virtual fitting service web page. We analyzed the current cases and identified the user's needs for the service through usability assessment, survey, and FGI experiments. As a result of the design, the fitting window of the existing web page was opened at the same time as the site was accessed to improve the hassle of using the icons due to their small size and poor visibility. In the case of fitting windows, the problem of information delivery was supplemented so that even the initial user could understand the fitting map of the existing method, and additional items needed for user propensity were provided so that the service could be used accurately and easily. As a result of this study, it can be used as a basic research material in future virtual fitting service studies and is expected to provide good implications to fashion marketers.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.187-194
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• 2022

LNG is known as the transitional energy source for the future eco-friendly, attracting enormous market attention due to global eco-friendly regulations, Covid-19 Pandemic, Russia-Ukraine War. In addition, since new LNG suppliers such as the U.S. and Australia are also diversifying, the LNG spot market is expected to grow. On the other hand, research on the LNG transportation market has been marginalized. Therefore, this study attempted to predict short-term LNG 160K spot rates and compared the prediction performance between artificial neural networks and the ARIMA model. As a result of this paper, while it was difficult to determine the superiority and superiority of ARIMA and artificial neural networks, considering the relative free of ANN's contraints, we confirmed the feasibility of ANN in LNG 160K spot rate prediction. This study has academic significance as the first attempt to apply an artificial neural network to forecasting LNG 160K spot rates and are expected to contribute significantly in practice in that they can improve the quality of short-term investment decisions by market participants by increasing the accuracy of short-term prediction.

• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.109-118
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• 2021

This study is a descriptive research study to understand the relationship between childcare teachers' ego-resilience, optimism, and job stress and the relationship between these variables and to identify factors affecting job stress. The study method was targeted to 191 childcare teachers working in D Metropolitan City from March to April 2021. The self-reliance, optimism, and job stress of childcare teachers were surveyed using a survey instrument. For data analysis, frequency, percentage, reliability analysis, t-test, ANOVA, correlation, and multiple regression were performed using SPSS WIN 20.0 program. As a result of this study, first, ego resilience and optimism showed a positive correlation, ego resilience and job stress had a negative correlation, and optimism and job stress had a negative correlation. Second, as a result of analyzing the factors affecting the job stress of childcare teachers, it was found that ego resilience had an effect. According to these results, in order to lower the job stress of childcare teachers, a program that can improve self-resilience and lower job stress should be developed and provided.

• Journal of The Korean Society of Integrative Medicine
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• v.9 no.2
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• pp.43-52
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• 2021

Purpose : Chronic neck pain negatively impacts the quality of life and causes various problems in daily life due to pain, insomnia, and sleep disturbances in patients with this condition. Therapeutic interventions to solve these problems in rehabilitation and physical therapy are being introduced; however, the evidence of the efficacy of myofascial release (MFR) is still insufficient. This study aimed to investigate the effects of applying MFR on pain, insomnia, and sleep disturbances in patients with chronic neck pain. Methods : Ten patients with chronic neck pain were randomly selected and grouped into the experimental group (n₁ = 10) and control group (n₂ = 10) by cross-over design. Pain was measured before and after MFR intervention. Moreover, insomnia was measured only after MFR intervention. Polysomnography was performed after MFR intervention. Wilcoxon signed rank test and Mann-Whitney U test were used for the visual analog scale (VAS). Independent sample t-test was separately performed to measure insomnia and sleep. Results : After MFR intervention, the VAS score of the experimental group (p = 0.005) significantly decreased than that of the control group (p = 0.002). The insomnia score of the experimental group significantly decreased than that of the control group (p = 0.001). The total sleep time (p = 0.001), sleep efficiency (p = 0.001), and sleep latency (p = 0.001) of the experimental group significantly increased than those of the control group in the polysomnographic measurement. Conclusion : The application of MFR of the neck and upper trunk may have a positive effect on pain, insomnia, and sleep disturbances in patients with chronic neck pain. It was also suggested that an objective and quantitative polysomnography can be used more often in the field of rehabilitation and physical therapy.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.467-474
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• 2024

This study analyses customer data from a US online lending platform to empirically document the discriminatory treatment that low- and middle-income borrowers face in financial markets. Researchers are using financial data from nearly 2.93 million loans between 2007~2020 of the Lending Club on the open-source Kaggle platform. We find that thin-filers borrowers, especially those with lower credit scores, receive loans at higher interest rates. This discriminatory treatment undermines financial inclusion and has the potential to increase social inequality. The significance of this research is that it sheds substantial light on the problem of inequality in financial markets and, based on the findings, suggests concrete measures to ensure equitable access to finance for all customers and enhance sustainable financial inclusion. In doing so, we propose a shift towards enhancing the social responsibility of institutions.

• Journal of Industrial Convergence
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• v.19 no.4
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• pp.29-35
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• 2021

Fintech, a new form of financial industry that converges IT, is developing rapidly in developed countries such as the US and China. The U.S. and China lowered barriers to entry through deregulation to develop and expand the fintech industry, and, for example, encouraged startup companies to incorporate various ideas through negative regulations that are more relaxed or do not apply regulations for a certain period of time. The U.S. and China did not apply existing financial regulations to the fintech industry, providing an environment where fintech startups could grow more easily. Currently, in Korea, fintech technologies such as 'Samsung Pay', 'Toss' and 'Kakao Pay' have been developed and are being activated, and also their scale is expanding. Although various systems are being reorganized and regulated for the development of Fintech, Fintech's growth rate is slow due to unfriendly and unopened regulations in the financial sector and various markets. This paper examines the status of fintech, focusing on advanced fintech and Korea, and examines fintech-related regulations that hinder the development of the fintech industry. We propose a more flexible way of easing excessive regulation in the financial sector, such as post-regulation.