• The Journal of the Korea Contents Association
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• v.19 no.9
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• pp.81-91
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• 2019

Recently, the nation has been suffering from a variety of problems, such as the rapid aging of the population and the weakening of the family's role due to rapid industrialization, such as the problem of supporting the elderly or the decline in the quality of supporting them. Among them, the issue of supporting the sentiment of the elderly is a major issue in terms of the quality of the stimulus. The best solution would be to resolve this issue of emotional support through various physical and human support. However, due to various limitations, access to efficient utilization of resources is being sought, among which support efforts through the convergence of digital technologies need to be noted. In this study, we took note of the problems of aging population shortage due to aging phenomenon and the problems of the emotional side of the problem of declining quality of the service, and analyzed the types of digital technology applied to support the emotional side through the convergence of digital technology. Among them, the Commission proposed emotional support through smart speakers, confirming the possibility of supporting the elderly through smart speakers. In addition, the Commission proposed guidelines for smart speaker communication systems to support the sentiment of older adults by conducting an in-depth interview with the In-Depth interview with the evaluation of the usability of smart speakers for older people. Based on the results of this study, it is expected that it will be the basic data for designing a communication system when developing smart speakers to support the emotions of the elderly.

• The Journal of Bigdata
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• v.3 no.2
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• pp.59-70
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• 2018

In order to provide stable district heat supplying service to the certain limited residential area, it is the most important to forecast the short-term future demand more accurately and produce and supply heat in efficient way. However, it is very difficult to develop a universal heat demand forecasting model that can be applied to general situations because the factors affecting the heat consumption are very diverse and the consumption patterns are changed according to individual consumers and regional characteristics. In particular, considering all of the various variables that can affect heat demand does not help improve performance in terms of accuracy and versatility. Therefore, this study aims to develop a demand forecasting model using deep learning based on only limited information that can be acquired in real time. A demand forecasting model was developed by learning the artificial neural network of the Tensorflow using past data consisting only of the outdoor temperature of the area and date as input variables. The performance of the proposed model was evaluated by comparing the accuracy of demand predicted with the previous regression model. The proposed heat demand forecasting model in this research showed that it is possible to enhance the accuracy using only limited variables which can be secured in real time. For the demand forecasting in a certain region, the proposed model can be customized by adding some features which can reflect the regional characteristics.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.17-24
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• 2019

Since the information of $4^{th}$ Industrial Revolution is introduced in WEF (World Economic Forum) in 2016, IoT, AI, Big Data, 5G, Cloud Computing, 3D/4DPrinting, Robotics, Nano Technology, and Bio Engineering have been rapidly developed as business applications as well as technologies themselves. Among the diverse business applications for IoT, wearable devices are recognized as the leading application devices for final customers. This longitudinal study is compared to the results of the 1st study conducted to identify customer needs of activity trackers, and links the identified users' needs with the well-known marketing frame of marketing mix. For this longitudinal study, a survey was applied to university students in June, 2018, and ANOVA were applied for major variables on usable features. Further, potential customer needs were identified and visualized by Word Cloud Technique. According to the analysis results, different from other high tech IT devices, activity trackers have diverse and unique potential needs. The results of this longitudinal study contribute primarily to understand usable features and their changes according to product maturity. It would provide some valuable implications in dynamic manner to activity tracker designers as well as researchers in this arena.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.199-208
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• 2021

In this paper, the effect of artificial intelligence convergence education program that provides STEAM education using machine learning platform on elementary school students' STEAM literacy and learning flow was analyzed. A homogeneous group of 44 elementary school 6th graders was divided into an experimental group and a control group. The control group received 10 lessons of general subject convergence class, and the experimental group received 10 lessons of STEAM-based artificial intelligence convergence education using Machine learning for Kids. To develop the artificial intelligence convergence education program, the goals, achievement standards, and content elements of the 2015 revised curriculum to select subjects and class contents is analyzed. As a result of the STEAM literacy test and the learning flow test, there was a significant difference between the experimental group and the control group. In particular, it can be confirmed that the coding environment in which the artificial intelligence function is expanded has a positive effect on learners' learning flow and STEAM literacy. Among the sub-elements of convergence talent literacy, significant differences were found in the areas of personal competence such as convergence and creativity. Among the sub-elements of learning flow, significant differences were found in the areas such as harmony of challenge and ability, clear goals, focus on tasks, and self-purposed experiences. If further expanded research is conducted in the future, it will be a basic research for more effective education for the future.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.847-857
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• 2021

Recently, domestic schools are increasingly interested in environmental education related to COVID-19 and the severe climate crisis, as well as artificial intelligence education related to the 4th industrial revolution that is rapidly approaching us. In particular, AI education is highly likely to be applied to 5th to 6th graders of elementary school, so measures related to connection with 1st to 4th graders are needed. There are many students who are not proficient in computers in the lower grades of elementary school, so there may be many restrictions in using the currently used teaching aids. Therefore, this study tried to develop an artificial intelligence education program for the lower grades of elementary school to secure the linkage of artificial intelligence education. The theme of the program was developed based on the topic of environmental education, which has recently increased in interest. As for the educational method, considering the developmental stage of the lower grades of elementary school, the STEAM education method was used, which was fused with various subjects and unplugged using play and games without a computer. of the program. For validity verification, Lawshe (1975)'s content validity ratio (CVR) calculation formula was used. The verification results were analyzed to be suitable for the purpose of development of all programs. In the future, it is necessary to measure the degree of effectiveness by applying the program proposed in this study to the lower grades of elementary school.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.123-131
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• 2021

The Fourth Industrial Revolution was triggered by data-driven digital technologies such as AI and big data. There is a rapid movement to expand the scope of data utilization to the privacy area, which was considered only a protected area. Through the revision of the Data 3 Act, laws and systems were established that allow personal information to be freely transferred and utilized under their consent. But, it will be necessary to support the platform that encompasses the entire process from collecting personal information to managing and utilizing it. In this paper, we propose a platform model that can be applied to building mydata ecosystem using personal information. It describes the six essential functional requirements for building MyData platforms and the procedures and methods for implementing them. The six proposed essential features describe consent, sharing/downloading/ receipt of data, data collection and utilization, user authentication, API gateway, and platform services. We also illustrate the case of applying the MyData platform model to real-world, underprivileged mobility support services.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.3
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• pp.63-83
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• 2021

The appearance of education is also rapidly changing in social changes represented by social networks. And the development of information and communication technology is also having a widespread effect on the education field. In the era of untact caused by Covid-19, education through smart learning is having a greater effect on students as well as adult learners more quickly and broadly. In addition, smart learning is not just limited to learning content, but is developing into personalized, convergence, and intelligent. The purpose of this study is to identify the factors of ARCS motivation theory that can determine the learning motivation of smart learning users, and to empirically study the casual relationship between these factors on education achievement through practical value and hedonic value. Specifically, I would like to examine how the independent variables ARCS motivation factors (attention, relevance, confidence, and satisfaction) affect learners' education achievement through the parameters of practical value and hedonic value. To this end, a research model was presented that applied the main variables of attention, relevance, confidence, and satisfaction, which are four elements of ARCS motivation theory, a specific and systematic motivational strategy to induce and maintain learners' motivation. In order to empirically verify the research model of this study, a survey was carried out on learners with experience using smart learning. As a result of the study, first attention was found to have a positive effect on the hedonic value. Second, relevance was found to have a positive effect on the hedonic value. Third, it was found that confidence did not have a positive effect on the practical value and the hedonic value. Forth, satisfaction was found to have a positive effect on the practical value and the hedonic value. Fifth, practical value was found to have a positive effect on the education achievement. Sixth, hedonic value was found to have a positive effect on the education achievement. Through this, it can be seen that the intrinsic motivation of learners using smart learning affects the education achievement of users through intrinsic and extrinsic value. A variety of smart learning that combines advanced IT technologies such as AI and big data can contribute to improving learners' education achievement more effectively and efficiently. Furthermore, it can contribute a lot to social development.

• The Korea Journal of Herbology
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• v.36 no.5
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• pp.101-108
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• 2021

Objectives : A root of Dipsacus asperoides C. Y. Cheng et T. M. Ai (D. asperoides) has been traditionally used as a medicinal resource in several Asian countries, including Korean and traditional Chinese medicine that has been traditionally used for treating several medical conditions including pain, arthritis, and bone fractures in Korea. In the present study, we investigated potential subacute toxicities of D. asperoides extract. Methods : C57BL/6 mice (male, 7weeks) were randomly divided into 4 groups of 5 mice. Except for the control group, the mice were orally administrated D. asperoides extract at doses of 50, 150, or 450 mg/kg/day for 2 weeks. At the end of the treatment period, all mice were euthanized, and the following parameters were examined: mortality, body weight, clinical signs, gross findings, hematology, serum biochemistry, organ weight, and histopathology. Results : There were no abnormalities in mortality, clinical signs, body weight, gross findings, or organ weight after repeated administration of D. asperoides extract for 2 weeks, compared with the control group. In addition, there were no significant changes in hematological, serum biochemical, and histopathological parameters between the control group and D. asperoides extract administrated groups with doses of up to 450 mg/kg/day. Conclusion : In this study, D. asperoides extract showed no significant toxicities at a dose of up to 450 mg/kg/day in mice. Although we could not confirm the toxic dose of D. asperoides extract, it can be considered safe for further pharmacological use.

• Journal of Internet Computing and Services
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• v.22 no.4
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• pp.1-11
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• 2021

As the Internet developed, various and complex cyber attacks began to emerge. Various detection systems were used outside the network to defend against attacks, but systems and studies to detect attackers inside were remarkably rare, causing great problems because they could not detect attackers inside. To solve this problem, studies on the lateral movement detection system that tracks and detects the attacker's movements have begun to emerge. Especially, the method of using the Remote Desktop Protocol (RDP) is simple but shows very good results. Nevertheless, previous studies did not consider the effects and relationships of each logon host itself, and the features presented also provided very low results in some models. There was also a problem that the model could not explain why it predicts that way, which resulted in reliability and robustness problems of the model. To address this problem, this study proposes an interpretable RDP-based lateral movement detection system using page rank algorithm and SHAP(Shapley Additive Explanations). Using page rank algorithms and various statistical techniques, we create features that can be used in various models and we provide explanations for model prediction using SHAP. In this study, we generated features that show higher performance in most models than previous studies and explained them using SHAP.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.283-289
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• 2021

Many people with disabilities have shown interest in artificial intelligence speakers that serves as the main hub of the smart home. Therefore, the purpose of this study was to identify the intention of people with disabilities to use such speakers. The focus is on those with physical disabilities, a segment that accounts for the largest number of disability types. Based on the theoretical model of technology acceptance, the effect of perceived ease of use and perceived usefulness of artificial intelligence speakers by people with disabilities was analyzed using Structural Equation Modeling (SEM). Research has confirmed that the technology acceptance model is suitable for identifying the intention to use artificial intelligence speakers by people with disabilities, and specifically that the perceived ease of use has a significant impact on usefulness. Furthermore, the perceived ease of use for people with disabilities did not have a statistically significant effect on their intent to use whereas the perceived usefulness was shown to have a significant effect on the same. This study is meaningful as a foundation for developing customized artificial intelligence speaker services and improving the use of artificial intelligence speakers by people with disabilities.