• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.64-76
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• 2021

Culture technology (CT) becomes important in the recent environment where digital technology drives content-based innovations. However, technological trends of CT have not been systematically discussed. Especially, the trends of CT should be analyzed from the national perspective, because CT has grown with the help of government-driven innovation. Therefore, this paper aims to analyze CT trends focusing on national research projects. We collected data on CT from the national science and technology information service (NTIS) database, analyzed the keyword co-occurrence network, and identified the patterns of technological innovation using a clustering analysis. As a result, we found that CT has contributed to the digital content and cultural media, and has been actively developed with the help of machine learning technique. Especially, due to the rise of Covid-19, the non-face-to-face online content is rapidly increasing. This study provides important clues for understanding, analyzing CT trends.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.14-24
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• 2020

Google Trends is a useful tool not only for setting search periods, but also for providing search volume to specific countries, regions, and cities. Extant research showed that the big data from Google Trends could be used for an on-line market analysis of opinion sensitive products instead of an on-site survey. This study investigated the market share of tumor necrosis factor-alpha (TNF-α) inhibitor, which is in a great demand pharmaceutical product, based on big data analysis provided by Google Trends. In this case study, the consumer interest data from Google Trends were compared to the actual product sales of Top 3 TNF-α inhibitors (Enbrel, Remicade, and Humira). A correlation analysis and relative gap were analyzed by statistical analysis between sales-based market share and interest-based market share. Besides, in the country-specific analysis, three major countries (USA, Germany, and France) were selected for market share analysis for Top 3 TNF-α inhibitors. As a result, significant correlation and similarity were identified by data analysis. In the case of Remicade's biosimilars, the consumer interest in two biosimilar products (Inflectra and Renflexis) increased after the FDA approval. The analytical data showed that Google Trends is a powerful tool for market share estimation for biosimilars. This study is the first investigation in market share analysis for pharmaceutical products using Google Trends big data, and it shows that global and regional market share analysis and estimation are applicable for the interest-sensitive products.

• Journal of Information Technology Applications and Management
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• v.19 no.4
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• pp.1-18
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• 2012

This paper identifies technology trends of national research and development (national R&D) by exploiting Korean national R&D patents, ranging from 2007 to 2010. In this paper, co-word analysis (CWA), which is a method to identify the relationship among technology terms by using their co-occurrences, is incorporated into network analysis to visualize the relationships among technology keywords of national R&D patents and calculate network indexes concerning inter-relationship diversity and strength of technology keywords. As a result, this research found that inter-relationship among technology keywords in national R&D are getting increasingly strengthening in an overall sense. In addition, the keyword inter-relationship diversity-strength map proposed in this paper revealed some significant technological keywords of national R&D : core technology keywords including "sensor", "film" and "fuel" and emerging keywords including "biosensor" and "thermoelectric". Because the proposed approach helps identify interdisciplinary trends of technology keywords from a massive volume of national R&D patents in a visual and quantitative way, we expect that the approach can be incorporated as a preliminary into the R&D planning process to assist R&D policy makers to understand technology convergence of national R&D and develop relevant R&D policies.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.40-48
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• 2019

Indoor gardens tailored to suit individual tastes offer a place to enjoy plants and to relax to city dwellers to relieve stress from city life. However, there are technical issues to build such indoor gardens. To offer solutions to technical issues, this study aims to analyze development phases of indoor garden-related technologies by studying available patents in detail. Also, the study aims to understand current status and future direction of technologies by examining technological trends for introduction of indoor gardens. Brainstorming method was used to understand technology trends and as a result, two groups were identified for technical features of indoor gardens: indoor greening technology and rest area for users. An analysis on selected patents showed that the number of patents increased until 2010 and declined gradually afterwards. Korea ranked the highest in the number of patents grant followed by USA, Japan and Europe. Similar order was observed with the number of patents granted by nationality of applicants. The number of patents granted by nationality was the highest for Korean nationals. For indoor greening technologies, patents related to structure from 2007 were mostly concentrated in the areas of irrigation control and environment control for plants and vegetation. For rest area related technologies, patent related to structure showed a repetitive pattern of increasing and decreasing, but overall, on downtrend. For further development and dissemination of indoor gardening technology, more R&D work is needed with focus on environmental control technology for designing suitable environment for both human and plant.

• The Science & Technology
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• no.4 s.419
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• pp.104-105
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• 2004

• The Science & Technology
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• no.1 s.416
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• pp.110-111
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• 2004

• The Science & Technology
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• no.3 s.418
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• pp.108-109
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• 2004

• Smart Structures and Systems
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• v.29 no.2
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• pp.361-374
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• 2022

As civil infrastructure has continued to age worldwide, its structural integrity has been threatened owing to material deteriorations and continual loadings from the external environment. Structural Health Monitoring (SHM) has emerged as a cost-efficient method for ensuring structural safety and durability. As SHM research has gradually addressed an increasing number of structure-related problems, it has become difficult to understand the changing research topic trends. Although previous review papers have analyzed research trends on specific SHM topics, these studies have faced challenges in providing (1) consistent insights regarding macroscopic SHM research trends, (2) empirical evidence for research topic changes in overall SHM fields, and (3) methodological validations for the insights. To overcome these challenges, this study proposes a framework tailored to capturing the trends of research topics in SHM through a bibliometric and network analysis. The framework is applied to track SHM research topics over 15 years by identifying both quantitative and relational changes in the author keywords provided from representative SHM journals. The results of this study confirm that overall SHM research has become diversified and multi-disciplinary. Especially, the rapidly growing research topics are tightly related to applying machine learning and computer vision techniques to solve SHM-related issues. In addition, the research topic network indicates that damage detection and vibration control have been both steadily and actively studied in SHM research.

• Journal of Korea Technology Innovation Society
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• v.5 no.3
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• pp.354-366
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• 2002

This study is a case study on the analysis of technological informations and patents in Electric Vehicle(EV). It first discusses technological trend, and second patents trends in comparison with major countries such as USA, Japan, Europe and Korea. Technological activities in EV are increasing year after year in the world. The focuses are concentrated in battery and recharging technology.

• Electronics and Telecommunications Trends
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• v.36 no.6
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• pp.1-12
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• 2021

As the demand for big data and big data-based artificial intelligence (AI) technology increases, the need for privacy preservations for sensitive information contained in big data and for high-speed encryption-based AI computation systems also increases. Fully homomorphic encryption (FHE) is a representative encryption technology that preserves the privacy of sensitive data. Therefore, FHE technology is being actively investigated primarily because, with FHE, decryption of the encrypted data is not required in the entire data flow. Data can be stored, transmitted, combined, and processed in an encrypted state. Moreover, FHE is based on an NP-hard problem (Lattice problem) that cannot be broken, even by a quantum computer, because of its high computational complexity and difficulty. FHE boasts a high-security level and therefore is receiving considerable attention as next-generation encryption technology. However, despite being able to process computations on encrypted data, the slow computation speed due to the high computational complexity of FHE technology is an obstacle to practical use. To address this problem, hardware technology that accelerates FHE operations is receiving extensive research attention. This article examines research trends associated with developments in hardware technology focused on accelerating the operations of representative FHE schemes. In addition, the detailed structures of hardware that accelerate the FHE operation are described.