• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.213-216
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• 2018

As the advantages of smart devices based on artificial intelligence and voice recognition become more prominent, Virtual Assistant is gaining popularity. Virtual Assistant provides a user experience through smart speakers and is valued as the most user friendly IoT device by consumers. The purpose of this study is to investigate whether there are differences in people's perception of the key virtual assistant brand voice recognition. We collected tweets that included six keyword form three companies that provide Virtual Assistant services. The authors conducted semantic network analysis for the collected datasets and analyzed the feelings of people through sentiment analysis. The result shows that many people have a different perception and mainly about the functions and services provided by the Virtual Assistant and the expectation and usability of the services. Also, people responded positively to most keywords.

• Journal of Korean Society of Rural Planning
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• v.26 no.3
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• pp.57-65
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• 2020

Agricultural research and development (R&D) investment has contributed not only to agriculture but also to the overall economic growth of the country. The recent arrival of the fourth industrial revolution has raised the need for agricultural R&D as a preparation. Agriculture R&D is directly related to the fourth industrial revolution in the agricultural and livestock sectors that utilize big data, robots, artificial intelligence and cloud. Meanwhile, subsidies or grants are considered the most widely used means of policy. Therefore, in light of the current situation in which Chinese agriculture values R&D investment, this study attempted to analyze the dynamic relationship between variables by establishing a model of agricultural environment subsidy representing the role of government, agricultural technology progress representing existing agricultural R&D investment, agricultural income representing agricultural development and total agricultural output. The analysis results showed that each variable's reaction to the rise in China's agricultural R&D investment has a positive effect on agricultural development, in line with the theory that the investment in science and technology in the agricultural sector has a positive effect. In addition, the response of each variable to China's rising agricultural environment subsidy is shown to have a positive relationship, which can also be said to be in line with the theory that the government's market-friendly intervention is beneficial to economic development.

• The Research Journal of the Costume Culture
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• v.27 no.5
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• pp.449-460
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• 2019

Today, the fashion business environment of the 4.0 generation is changing based on fashion technology combined with advanced digital technologies such as AI (Artificial Intelligence), big data and IoT (Internet of Things). "Digital Transformation" means a fundamental change and innovation in a digital paradigm including corporate strategy, organization, communication, and business model, based on the utilization of digital technology. Thus, this study examines digital transformation strategies through the fashion brand Burberry. The study contents are as follows. First, it examines the theoretical concept of digital transformation and its utilization status. Second, it analyzes the characteristics of Burberry's digital transformation based on its strategies. For the research methodology, a literature review was performed on books and papers, aligning with case studies through websites, social media, and news articles. The result showed that first, Burberry has reset their main target to Millennials who actively use mobile and social media, and continues to communicate with them by utilizing digital strategy in the entire management. Second, Burberry is quickly delivering consistent brand identity to consumers by internally creating and providing social media-friendly content. Third, they have started real-time product sales and services by using IT to enhance access to brands and to lead consumers towards more active participation. In this study, Burberry's case shows that digital transformation can contribute to increased brand value and sales, keeping up with the changes in the digital paradigm. Therefore, the study suggests that digital transformation will serve as an important business strategy for fashion brands in the future.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.699-706
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• 2021

Existing license plate recognition system is used as an optical character recognition method, but a method of using deep learning has been proposed in recent studies because it has problems with image quality and Korean misrecognition. This requires a lot of data collection, but the collection of license plates is not easy to collect due to the problem of the Personal Information Protection Act, and labeling work to designate the location of individual license plates is required, but it also requires a lot of time. Therefore, in this paper, to solve this problem, five types of license plates were created using a virtual Korean license plate generation program according to the notice of the Ministry of Land, Infrastructure and Transport. And the generated license plate is synthesized in the license plate part of collectable vehicle images to construct 10,147 learning data to be used in deep learning. The learning data classifies license plates, Korean, and numbers into individual classes and learn using YOLOv5. Since the proposed method recognizes letters and numbers individually, if the font does not change, it can be recognized even if the license plate standard changes or the number of characters increases. As a result of the experiment, an accuracy of 96.82% was obtained, and it can be applied not only to the learned license plate but also to new types of license plates such as new license plates and eco-friendly license plates.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.427-436
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• 2021

The purpose of this study is to implement a machine learning language model that learns literary texts. Literary texts have an important characteristic that pairs of question-and-answer are not frequently clearly distinguished. Also, literary texts consist of pronouns, figurative expressions, soliloquies, etc. They hinder the necessity of machine learning using literary texts by making it difficult to learn algorithms. Algorithms that learn literary texts can show more human-friendly interactions than algorithms that learn general sentences. For this goal, this paper proposes three text correction tasks that must be preceded in researches using literary texts for machine learning language model: pronoun processing, dialogue pair expansion, and data amplification. Learning data for artificial intelligence should have clear meanings to facilitate machine learning and to ensure high effectiveness. The introduction of special genres of texts such as literature into natural language processing research is expected not only to expand the learning area of machine learning, but to show a new language learning method.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.261-268
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• 2022

Recently, the number of elderly living alone suffering from loneliness and depression is also increasing significantly due to the rapid aging of the population and nuclear families. In this paper, we propose a smart aging system that increases life satisfaction by providing the elderly with the optimal service tailored to the elderly with the help of IT according to their residential environment and health status. It is possible to provide an advanced customized support system for the elderly by fully utilizing IoT, AI, and Metaverse techniques not only for the elderly who want to live an active life in society but also for the elderly who need care in a nursing hospital. The proposed system provides human satisfaction by providing social connection in real space and virtual space in accordance with the residential environment and health status to the elderly suffering from loneliness in hospital (hospital care) facilities and at home. This paper proposes a new path for future-oriented welfare policy for the elderly by providing a user-customized smart aging system by combining AI and Metaverse technology with a rapidly changing social environment.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.267-277
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• 2022

Recently, the topics of SW liberal-arts education are diversifying, from 'Computational Thinking(CT)' to 'Programming, Data Analysis and Artificial Intelligence(AI)' in universities. We expect that the diversification of SW liberal-arts subjects does not just mean that the learning contents are different, but also differentiates the educational goals and educational effects of each subject. In this paper, we conducted a case study to analyze the educational effect according to the educational goals of two SW liberal-arts subjects, CT and Data Analysis Fundamentals(DA), for humanities college students. We confirmed that the educational effect of 'CT Efficacy' increased significantly in accordance with the common educational goal of 'Improving CT-based SW convergence competency' in both subjects. However, we also analyzed the difference in the educational effects of 'CT(the goal of basic SW education)' and 'DA(the goal of major-friendly SW education)', which have different subject goals. 'CT' mainly showed an educational effect on how to solve general daily problems, and 'DA' showed confidence in how to solve major problems along with general problems.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.179-193
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• 2023

research on user-friendly experience design is crucial to reduce resistance and enhance acceptance of robotaxis. This study analyzes the prioritization of design factors in robotaxi systems and provides design guidelines based on user experience. Using the AHP(Analytic Hierarchy Process) technique, users' perceived importance of four primary design factors and sixteen 16 sub-design elements were assessed, and comfort and safety were top priorities. The results showed that the artificial intelligence agent was the most critical design factor, followed by driving guidance information, interior design, and exterior design. These findings offer valuable insights for robotaxi professionals, and could assist in informed decision-making and creating user-centered design guidelines.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1123-1146
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• 2023

In South Korea, there have been many studies on efficient building-energy management using renewable energy facilities in single zero-energy houses or buildings. However, such management was limited due to spatial and economic problems. To realize a smart zero-energy city, studying efficient energy integration for the entire city, not just for a single house or building, is necessary. Therefore, this study was conducted in the eco-friendly energy town of Chungbuk Innovation City. Chungbuk successfully realized energy independence by converging new and renewable energy facilities for the first time in South Korea. This study analyzes energy data collected from public buildings in that town every minute for a year. We propose a smart city building-energy management model based on the results that combine various renewable energy sources with grid power. Supervised learning can determine when it is best to sell surplus electricity, or unsupervised learning can be used if there is a particular pattern or rule for energy use. However, it is more appropriate to use reinforcement learning to maximize rewards in an environment with numerous variables that change every moment. Therefore, we propose a power distribution algorithm based on reinforcement learning that considers the sales of Energy Storage System power from surplus renewable energy. Finally, we confirm through economic analysis that a 10% saving is possible from this efficiency.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.659-665
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• 2023

The exciter of a ship generator adjusts the magnetic flux through excitation current control to maintain the output terminal voltage constant. The voltage controller inside the exciter typically uses a proportional integral control method. however, the response characteristics determined by the gain and time constant produce unwanted output owing to an inappropriate setting value that can reduce the quality and stability of power within the ship. In this study, a neural network circuit is learned using stable input/output data that can be obtained through the AC4A type exciter model provided by IEEE, and the simulation is performed by replacing the existing proportional integral control type voltage controller with the learned neural network circuit controller. Consequently, overshooting was improved by up to 9.63% compared with that of the previous model, and excellence in stable response characteristics was confirmed.