• Journal of Digital Convergence
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• v.11 no.1
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• pp.13-25
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• 2013

After studying FSMA 24, We found that the insolvency rule of financial institutions in FSMA consists of eight provisions: 1) voluntary arrangement, 2) administration order, 3) receiverships, 4) voluntary winding up, 5) winding up by the court, 6) bankruptcy, 7) provisions against debt avoidance, and 8) supplemental provisions in insurance cases. Insolvency provisions in FSMA explain powers and accountabilities of FSA in relation to these insolvency proceedings. Although there are some differences in proceedings, provisions entitle FSA the same status as creditors to petition the court, with a right to participate in related meetings and to be notified of any matters involving insolvency proceedings. The differences and implications between U.K.'s FSMA and Korean regulations are related to the insolvency rule of financial institutions. First, in FSMA, FSA has a comprehensive power to manage insolvency proceedings of financial institutions in a centralized way. However, Korean regulations have special laws to regulate insolvency in a decentralized way. The offices executing those laws are the Financial Services Committee, the Financial Supervisory Service, and the Financial Deposit Insurance Corporation. This characteristic results from an accelerated legislation procedures related to financial reform in 1997 Korean financial crisis. Second, FSA contains special provisions on continuation of contracts of long-term insurance considering the characteristics of insurance industry related to insolvency of financial institution. However, Korean insolvency rules applied to financial institutions do not consider industrial differences and the characteristics of financial contracts, so need to be supplemented in the future.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.347-352
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• 2021

In this paper, we propose a method for finding feature subsets that are effective for classification in an input dataset by using a multi-agent reinforcement learning method. In the field of machine learning, it is crucial to find features suitable for classification. A dataset may have numerous features; while some features may be effective for classification or prediction, others may have little or rather negative effects on results. In machine learning problems, feature selection for increasing classification or prediction accuracy is a critical problem. To solve this problem, we proposed a feature selection method based on reinforced learning. Each feature has one agent, which determines whether the feature is selected. After obtaining corresponding rewards for each feature that is selected, but not by the agents, the Q-value of each agent is updated by comparing the rewards. The reward comparison of the two subsets helps agents determine whether their actions were right. These processes are performed as many times as the number of episodes, and finally, features are selected. As a result of applying this method to the Wisconsin Breast Cancer, Spambase, Musk, and Colon Cancer datasets, accuracy improvements of 0.0385, 0.0904, 0.1252 and 0.2055 were shown, respectively, and finally, classification accuracies of 0.9789, 0.9311, 0.9691 and 0.9474 were achieved, respectively. It was proved that our proposed method could properly select features that were effective for classification and increase classification accuracy.

• Journal of Digital Convergence
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• v.19 no.9
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• pp.189-199
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• 2021

In order to increase the self-reliance rate of new and renewable energy in order to respond to the mandatory domestic zero-energy buildings, the taller the building, the more limited the site area, and installing PV modules on the roof is not enough. Therefore, BIPV (Building integrated photovoltaic, hereinafter BIPV) is the industry receiving the most attention as a core energy source that can realize zero-energy buildings. Therefore, this study conducted a survey on the problems of the BIPV industry in a self-discussing method for experts with more than 10 years of experience of designers, builders, product manufacturers, and maintainers in order to suggest the right direction and revitalize the BIPV industry. Industrial problems of BIPV adjustment are drawn extention range of standard and certification for products, range improvement for current small condition of various kind productions, need to revise standards for capable of accomodating roof-type, color-module and louver-module, necessary of barrier in flow of foreign modules into korea through domestic certification mandatory, difficulty in obtaining BIPV information, request to prevent confusion among participants by exact guidelime about architectural application part of BIPV, and lack of the BIPV definition clearness, support policy, etc. Based on the improvements needed for the elements, giving change and competitiveness impacts aims to present and propose counter measures and direction.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.475-487
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• 2019

The purpose of this study was to investigate whether there are any differences in the recognition of the level of the guarantee of the rights of infants and toddlers according to the teachers' variables(gender, age, working experience) and institutional variables (institution type, establishment type, scale, area). We surveyed 365 special education teachers and found out differences. The results are as follows. First, there was no difference in the recognition according to gender. Second, there was no difference in the recognition according to age. Third, there was no difference in the recognition by working experience. Fourth, the recognition by type of educational institution showed that there were differences in the ambit of rights to life, protection, development, and participation. Fifth, the recognition according to the establishment type showed there were differences in the rights to life and development. On the other hand, there was no difference in the rights to protection and participation. Sixth, there were differences in the recognition about the rights to life, protection, development, and participation according to the scale of the education institutions. Seventh, there were no differences in the region. The results of this study can be used as basic data for establishing policy for the promotion of educational rights for infants with disabilities.

• Journal of Digital Convergence
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• v.17 no.10
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• pp.453-459
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• 2019

This study was conducted to investigate the effects of video - based movement therapy program on emotional variables (anxiety, depression, panic disorder) and EEG on panic disorder patients. The following conclusions were obtained. The results of the 12 - week video - based behavior therapy program showed that there were statistically significant differences (p <.05) in the anxiety scale of the exercise group. There were statistically significant differences (p <.05) between the left brain L-Beta region of the exercise group and the left brain H-Beta and the right brain L-Beta regions of the control group and no significant difference was found between the groups. The results of this study suggest that the performance of the video-based behavioral therapy program for panic disorder patients did not affect the emotional variables and EEG changes. However, in the case of emotional variables, It is considered that the longer the program execution period, the more result will be obtained. In addition, it is expected that more positive study results can be expected if the program is run after having had enough familiarity and adaptation time of the operation treatment program omitted in this study.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.357-363
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• 2021

In general, people choose clothes to wear when they go out, referring to real-time weather and temperature. However, it is difficult for an individual to use real-time weather information and his or her temperature sensitivity information to choose the right clothes from among the clothes he or she owns. Existing clothing recommendation systems developed to help with these problems have problems recommending clothes that are not clearly set in the clothing category and are not in the possession of the user. In addition, user-specific temperature sensitivity is not taken into account, resulting in inappropriate clothing recommendations for users. To solve these problems, this study developed a system that determines and registers clothing categories for the clothing owned by the user, and recommends customized clothing for each user by considering temperature sensitivity and real-time weather information. In the case of weather information, not only weather information such as temperature and wind direction, but also clothes based on temperature sensitivity were recommended based on the calculation of temperature sensitivities. A satisfaction survey of 65 university students was conducted to assess the system. As a result, 80% of the respondents were satisfied with the recommended clothing, indicating that the satisfaction of the system was good. Therefore, it is expected that this system will be highly utilized in real life as it will be recommended based on clothes owned by individuals, reflecting individual temperature sensitivity.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.525-531
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• 2020

In today's IT environment where various pieces of information are distributed in large volumes, recommendation systems are in the spotlight capable of figuring out users' needs fast and helping them with their decisions. The current recommendation systems, however, have a couple of problems including that user preference may not be reflected on the systems right away according to their changing tastes or interests and that items with no relations to users' preference may be recommended, being induced by advertising. In an effort to solve these problems, this study set out to propose a Fuzzy-AHP-based movie recommendation system by applying the BRNN(Bidirectional Recurrent Neural Network) language model. Applied to this system was Fuzzy-AHP to reflect users' tastes or interests in clear and objective ways. In addition, the BRNN language model was adopted to analyze movie-related data collected in real time and predict movies preferred by users. The system was assessed for its performance with grid searches to examine the fitness of the learning model for the entire size of word sets. The results show that the learning model of the system recorded a mean cross-validation index of 97.9% according to the entire size of word sets, thus proving its fitness. The model recorded a RMSE of 0.66 and 0.805 against the movie ratings on Naver and LSTM model language model, respectively, demonstrating the system's superior performance in predicting movie ratings.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.389-399
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• 2020

Diverse official policies in community are available for caregivers to take care of the elderly in the US and the UK. This study aims to examine the recent changes in government supports based on The Recognize, Assist, Include Support and Engage (RAISE) in the US, and those by Carer Act 2014 in the UK, to take any good lessons for Korean policy. Caregivers will play a new role to develop innovative treatment for patient-centered care. The UK strengthens to provide various efforts for working carers while assuring economic efficiency in labor market with empirical evidence. The major four ways to support carers were developed agreed with the acknowledge of caregiving value and their human right; financial support, direct services for carers, flexible work time, and advocacy. Korean supports policies for carers in long-term care and social welfare will be more effective in community care system if more evidence based policies are prepared.

• Journal of Digital Convergence
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• v.19 no.1
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• pp.29-43
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• 2021

Coinciding with the advent of COVID-19, online education is on the rise both domestically and globally, and has become an absolutely necessary and irreplaceable form of education. It is a very curious question what the perception of people about the suddenly growing form of education is, and how it has changed. This study investigated changes in consumers' perception of online education using big data. To this end, we divided the time into four stages: before COVID-19 (November to December 2019), after the triggering of COVID-19 (January to February 2020), right after the online classes started (March to April 2020), after experiencing some online education (May to June 2020). Then we conducted text mining, namely, keyword frequency analysis, network analysis, word cloud analysis, and sentiment analysis were performed. The implications derived as a result of the analysis can help education policy makers and educators working in the field to improve online education quality and establish its future directions.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.423-432
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• 2021

The purpose of this study is to investigate the effect of role recognition of students participating in middle school soccer club activities applying sports education model on responsibility and self-directed learning. In order to achieve this purpose, 410 samples were selected from male students based in Busan using the convenience sampling method. Among them, and 370 data were finally verified through frequency analysis, exploratory factor analysis, Cronbach's α coefficient calculation, and correlation analysis using the SPS statistics 25.0 program. Finally, a regression analysis was performed for hypothesis testing, and the results were as follows. First, the awareness of the role of the student participating in middle school soccer club activities, which applied the sports education model, was found to have a positive effect in part on the sense of responsibility. Second, the role recognition of students participating in middle school soccer club activities, which applied the sports education model, was found to have a partial positive influence on self-directed learning. Finally, the responsibility of students participating in middle school soccer club activities, which applied the sports education model, was found to have a positive effect on self-directed learning in part. Therefore, physical education teachers should ensure that students can choose the right roles for themselves through various role experiences in soccer classes so that more active learning can take place.