• International Area Studies Review
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• v.15 no.3
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• pp.325-348
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• 2011

This paper analyses how China is likely to be able to sustain its current pace of growth. The results of analysis show that China's economic growth matches standard growth patterns identified by the models of economic development such as structural change, catching up model. Furthermore, China's economic growth, within these analytical frameworks, matches those of Korea at an earlier stage of her development. So Korea's growth patterns may well apply to the future of China such as the benefits of free society with economics and politics which generate technical progress and innovations. A country with a high innovative capacity is one whose institutions - educational, economic, political, legal, and so forth - allow it to dynamically and continually generate new products and services in a myriad of sectors. These are the way how China is likely to be able to sustain her economic development.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.169-170
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• 2019

Lately, as artificial intelligence becomes a source of global competitiveness, the government is strategically fostering artificial intelligence that is the base technology of future new industries such as autonomous vehicles, drones, and robots. Domestic artificial intelligence research and services have been launched mainly in Naver and Kakao, but their size and level are weak compared to overseas. Recently, deep learning has been conducted in recent years while recording innovative performance in various pattern recognition fields including speech recognition and image recognition. In addition, deep running has attracted great interest from industry since its inception, and global information technology companies such as Google, Microsoft, and Samsung have successfully applied deep learning technology to commercial products and are continuing research and development. Therefore, we will look at artificial intelligence which is attracting attention based on previous research.

• Journal of Information Technology Services
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• v.19 no.6
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• pp.131-144
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• 2020

As the blockchain technology attracts attention, interest in cryptocurrency that is received as a reward is also increasing. Currently, investments and transactions are continuing with the expectation and increasing value of cryptocurrency. Accordingly, prediction for cryptocurrency price has been attempted through artificial intelligence technology and social sentiment analysis. The purpose of this paper is to develop a deep learning ensemble model for predicting the price fluctuations and one-day lag price of cryptocurrency based on the design science research method. This paper intends to perform predictive modeling on Ethereum among cryptocurrencies to make predictions more efficiently and accurately than existing models. Therefore, it collects data for five years related to Ethereum price and performs pre-processing through customized functions. In the model development stage, four LSTM models, which are efficient for time series data processing, are utilized to build an ensemble model with the optimal combination of hyperparameters found in the experimental process. Then, based on the performance evaluation scale, the superiority of the model is evaluated through comparison with other deep learning models. The results of this paper have a practical contribution that can be used as a model that shows high performance and predictive rate for cryptocurrency price prediction and price fluctuations. Besides, it shows academic contribution in that it improves the quality of research by following scientific design research procedures that solve scientific problems and create and evaluate new and innovative products in the field of information systems.

• Fashion & Textile Research Journal
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• v.23 no.3
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• pp.347-357
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• 2021

This study analyzed the effects of optimism and innovativeness, the two drivers of a consumer's technological readiness to use an augmented reality(AR) fashion shopping service within the framework of the Technology Acceptance Model (TAM). The survey was conducted on 249 people (males = 58; females = 191) in their 20s who were willing to participate in the AR experience. Data were analyzed using confirmatory factor analysis (CFA) and structural equation modeling by AMOS 22.0. The results indicated that a greater level of perceived optimism had a positive influence on the ease of use and usefulness of the technology. The findings also show that consumers with a high degree of innovativeness tend to have a higher level of playfulness toward AR fashion shopping. Regarding the effects of user beliefs, ease of use had a positive effect on the perception of usefulness and playfulness with higher levels implying a higher consumer intention to adopt an AR fashion shopping service. In addition, this study reveals the moderating effect of consumers with high-fashion versus those with low-fashion innovativeness. For the latter, technological innovation had an insignificant effect on playfulness, thus indicating that consumers with low interest in fashion did not enjoy AR fashion shopping even if the technology was highly innovative. Nevertheless, the analysis confirms the possibility that experiencing a fashion product through AR technology could replace the actual experience of wearing the products.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.1
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• pp.165-181
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• 2022

The fashion industry is creating innovative business models using artificial intelligence. To efficiently utilize artificial intelligence (AI), fashion data must be classified. Until now, such data have been classified focusing only on the objective properties of fashion products. Their subjective attributes, such as fashion brand sensibilities, are holistic and heuristic intuitions created by a combination of design elements. This study aims to improve the performance of collaborative filtering in the fashion industry by extracting fashion brand sensibility using computer vision technology. The image data set of fashion brand sensibility consists of high-end fashion brand photos that share sensibilities and communicate well in fashion. About 26,000 fashion photos of 11 high-end fashion brand sensibility labels have been collected from the 16FW to 21SS runway and 50 years of US Vogue magazines beginning from 1971. We use EfficientNet-B1 to establish the main architecture and fine-tune the network with ImageNet-ILSVRC. After training fashion brand sensibilities through deep learning, the proposed model achieved an F-1 score of 74% on accuracy tests. Furthermore, as a result of comparing AI machine and human experts, the proposed model is expected to be expanded to mass fashion brands.

• Journal of Soil and Groundwater Environment
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• v.27 no.4
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• pp.1-9
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• 2022

This study was conducted to supplement new-normal strategies on management plans of rural groundwater resources in the era of Post COVID-19. Global outbreak of COVID-19 has damaged across all areas including public policy, economics, industrial services, and others without exception, which has resulted in establishing new-normal strategies in order to restore balance and functions as for these areas. The new-normal ones were represented as enhancing preventative management on infectious diseases, expanding non face-to-face services, enhancing protective trades and food securities, and preparing growth policies on public services using the 4^th industrial revolution techniques. In this study, G-WASH_AD (Groundwater supply, sanitation, and hygiene with attraction and digitization) was suggested to be new-normal strategies on rural groundwater resources. The G-WASH_AD was consisted of three detailed action plans: a preventative plan on waterborne-diseases of groundwater (PP), a groundwater-tourism plan with rural heritage (GP), and an application plan of the 4^th industrial revolution techniques to groundwater facilities and its data (P4). The PP can contribute to protect human health from waterborne-diseases and minimize hazardous effects on crop cultivation. The GP accompanied with high-quality groundwater resources is able to strengthen rural tourism, to promote marketing activities on local agricultural products, and to increase household incomes of rural communities. The P4 can reinforce fast, comfortable, and scientific management on groundwater facilities and its data, creating a virtuous cycle between innovative management on groundwater and growth of technology related to it. Results of the G-WASH_AD strategies can encourage a green growth engine in field of rural groundwater management keeping up with Post COVID-19.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.515-520
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• 2022

Metaverse is at the center of heated debates in many areas recently. Coupled with real world, metaverse is extending its domain into social and cultural activities in addition to economic value creation as untact activities increase. Global companies are investing in R&D for metaverse. The reason is that metaverse is supposed to create new value by converging virtual and real worlds thanks to technology advancement such as AI, big data, 3D graphic, 5G, cloud computing, etc. Thus, innovative changes are expected in the economic, social and cultural areas. However, there are many problems to be solved yet for connecting virtual world and real one. Also, epoch-making development of products and services should be done for realistic experience and profit creation using virtual space in various industries beyond untact social activities against pandemic situation. The essence, present condition, development and its application areas of metaverse will be analyzed, and expected problems researched so that the strategy and methodology for securing global competitiveness will be addressed in coming metaverse era.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.12
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• pp.1710-1720
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• 2007

Environmental changes, including intensive international competition, unpredictable consumer demand, and market trends of variety and short product life cycles, have compelled the U. S. textiles and apparel industry to focus increasingly on the consumer as a way to meet these challenges. The industry began expanding into mass customization that used information technology, flexible processes, and organizational structures to deliver a wide range of products and services that met specific needs of individual customers but on a mass scale. This paper presents cases of leading-edge technology application on customization and breakthrough concepts in personalization, with a view to raising the level of debate on these issues to its highest level.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.37 no.4
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• pp.420-426
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• 2024

This study proposes an innovative methodology for developing flexible printed circuit boards (FPCBs) capable of conforming to three-dimensional shapes, meeting the increasing demand for electronic circuits in diverse and complex product designs. By integrating a traditional flat plate-based fabrication process with a subsequent three-dimensional thermal deformation technique, we have successfully demonstrated an FPCB that maintains stable electrical characteristics despite significant shape deformations. Using a modified polyimide substrate along with Ag flake-based conductive ink, we identified optimized process variables that enable substrate thermal deformation at lower temperatures (~130℃) and enhance the stretchability of the conductive ink (ε ~30%). The application of this novel FPCB in a prototype 3D-shaped sensor device, incorporating photosensors and temperature sensors, illustrates its potential for creating multifunctional, shape-adaptable electronic devices. The sensor can detect external light sources and measure ambient temperature, demonstrating stable operation even after transitioning from a planar to a three-dimensional configuration. This research lays the foundation for next-generation FPCBs that can be seamlessly integrated into various products, ushering in a new era of electronic device design and functionality.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.731-737
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• 2024

This study conducted a quantitative research on the artistic perception and acceptance of value among buyers of commodified digital art known as NFT artworks. NFTs, digital assets, have shown rapid growth as investment products, but recently there has been a trend of declining value. However, NFT art, characterized by uniqueness and scarcity, continues to undergo continuous development to create new opportunities and values. Nonetheless, there are also negative opinions regarding NFT art itself as a form of technological art, as well as concerns about copyright disputes and fears of a bubble due to the conversion of physical artworks into NFTs. Predicting the value of artworks targeting specific demographics is difficult, and the value of innovative art such as NFT art, which changes along with the fluctuation of cryptocurrency values, is even more challenging to predict. Therefore, through research on the buyers who play a crucial role in the growth and development of this new form of art, the study aims to contribute to the expansion of NFT art.