• The Journal of the Korea Contents Association
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• v.17 no.4
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• pp.229-236
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• 2017

Technology foresight is the process which investigate long term science, technology, economic and social effects to derive strategic R&D and future promising technologies. This study shows that new systematic framework based on technology classifications of space and action in human society, future six senses was employed as a new research method for effective process of future technology foresight. In addition, to increase the acceptance, forecasting, and uniqueness of new technology, we derived major issues of future society and demand-base products and services through the new process of ICT future mega trend analysis, the findings and selections of future technology, and future scenario based on human six senses.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.1
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• pp.108-126
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• 2013

Recently, it becomes essential for firms or nations to forecast the future and identify emerging technologies in order to improve R&D efficiency and gain a competitive advantage. Particularly, the mobile communications industry is characterized by rapid advance and wide application of its technology and thus identifying emerging technologies is more important in the industry than in others. Nevertheless, few attempts have been made to explore its emerging technologies. Therefore, this research aims to develop a methodology to identify the future and emerging technologies especially for the industry and applied it to list top ten emerging technologies for 2020 in the industry. For this purpose, firstly, we focused the key issues in the future targeting 2020 and identified user needs relating to them. Then, candidates of emerging technologies were defined from a set of technologies to meet the needs, for which technological and economic feasibility is assessed to determine their priorities. Finally, the top ten most important technologies were selected and verified. This research is distinct from the previous studies in that it takes a market-pull approach instead of a technology-push approach. The research results are expected to provide valuable information to support strategy- and policy-makings in the mobile communications industry.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.4
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• pp.49-63
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• 2015

Keyword indexed in multidisciplinary journals show trends about science and technology innovation. Nature and Science were selected as multidisciplinary journals for our analysis. In order to reduce the effect of plurality of keyword, stemming algorithm were implemented. After this process, we fitted growth curve of keyword (stem) following bass model, which is a well-known model in diffusion process. Bass model is useful for expressing growth pattern by assuming innovative and imitative activities in innovation spreading. In addition, we construct keyword co-occurrence network and calculate network measures such as centrality indices and local clustering coefficient. Based on network metrics and yearly frequency of keyword, time series analysis was conducted for obtaining statistical causality between these measures. For some cases, local clustering coefficient seems to Granger-cause yearly frequency of keyword. We expect that local clustering coefficient could be a supportive indicator of emerging science and technology.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.10
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• pp.2923-2934
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• 2009

This paper presents study on technological forecasting of Next-Generation Display technology. Next-Generation Display technology is one of the emerging technologies lately. So databases on patent documents of this technology were analyzed first. And patent analysis was performed for finding out present technology trend. And the forecast for this technology was made by growth curves which were obtained from forecast models using patent documents. In previous study, Gompertz, Logistic, Bass were used for forecasting diffusion of demand in market. Gompertz, Logistic models which were often used for technological forecasting, too. So, two models were applied in this study. But Gompertz, Logistic models only consider internal effect of diffusion. And it is difficult to estimate maximum value of growth in two models. So, Bass model which considers both internal effect and external effect of diffusion was also applied. And maximum value of growth in Gompertz, Logistic models was estimated by Bass model.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.2
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• pp.240-249
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• 2014

This study aims to identify an assessment system based on multiple patent indices that can predict the likelihood of success in the commercialization of a patented technology in advance. In addition, we examine the effectiveness of our predictive model in identifying valuable technologies early on. We analyzed 3,063 secondary battery technologies patented in the US over the past 10 years. Our analysis identified 22 of the 25 most promising patented technologies, corresponding with the top 50% of industry-patented technologies that directly and indirectly succeeded in commercialization. These results support our claim that it is possible to identify attributes for the assessment of patent commercial potential to a significant degree. Our system presents a useful assessment index in the forecasting and determination of potential commercial success of patented technologies.

• Electronics and Telecommunications Trends
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• v.39 no.2
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• pp.93-102
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• 2024

As the scale of research and development (R&D) increases, countries and companies are consistently establishing R&D directions to meet strategic goals and market demands as well as roadmaps to increase efficiency through concentration and selection. However, establishing an effective roadmap and discovering promising technologies are challenging under the current numerous technological possibilities and uncertainties. The importance of discovering promising technologies to secure future technological competitiveness is recognized worldwide, and Europe, the United States, and Japan are establishing processes to identify promising future technologies and support related R&D. Methods for discovering promising future technologies can be classified into future social needs analysis, forecasting, surveys, use of expert opinions, and data analysis. We describe the types and limitations of technology roadmaps and investigate the status of domestic and foreign organizations using weak signal search through quantitative data analysis.

• Proceedings of the Korea Contents Association Conference
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• 2013.05a
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• pp.365-366
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• 2013

국가나 기업의 연구개발 사업에 있어서 기술예측의 중요성이 더욱 커짐에 따라 그 방법들 또한 다양해지고 있다. 그 중 한 방법으로 특허정보를 분석하여 미래 기술의 향방을 예측하는 방법이 있다. 본 논문에서는 텍스트 마이닝을 이용하여 특허문서에서 키워드를 추출하고 그 키워드들의 평균과 표준편차를 이용한 중요도와 시계열 자료를 이용한 부상도를 분석하여 부상기술을 예측해 보고자 한다. 이를 통해 기술예측 시 보다 신속하고 객관적인 판단을 가능케 하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.650-652
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• 2014

국가와 기업의 연구개발투자 및 경영정책 전략 수립에서 미래 부상기술 예측은 매우 중요한 역할을 한다. 기술예측을 위한 다양한 방법들이 사용되고 있으며 특허를 이용한 기술예측 또한 활발히 진행되고 있다. 최근에는 텍스트마이닝을 이용해 특허데이터의 정량적인 분석이 이루어지고 있다. 본 논문에서는 텍스트마이닝과 지수평활법을 이용한 기술예측 방법을 제안한다.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.199-208
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• 2023

The emergence of COVID-19 virus has shaken almost every aspect of human life including but not limited to social, financial, and economic changes. One of the most significant impacts was obviously healthcare. Now though the pandemic has been over, its aftereffects are still there. Among them, a prominent one is people lifestyle. Work from home, enhanced screen time, limited mobility and walking habits, junk food, lack of sleep etc. are several factors that have still been affecting human health. Consequently, diseases like diabetes, high blood pressure, anxiety etc. have been emerging at a speed never witnessed before and it mainly includes the people at young age. The situation demands an early prediction, detection, and warning system to alert the people at risk. AI and Machine learning has been investigated tremendously for solving the problems in almost every aspect of human life, especially healthcare and results are promising. This study focuses on reviewing the machine learning based approaches conducted in detection and prediction of diabetes especially during and post pandemic era. That will help find a research gap and significance of the study especially for the researchers and scholars in the same field.

• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.327-331
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• 2020

In that this study is a subject and character of risk, emerging security covers non-military areas in addition to traditional military security: environmental security, human security, resource security, and cyber security. The rise of these risks is not only changing the phenomenon of the new expansion of security areas, but also the expansion of the number and scope of security entities and the aspect of security world politics. These risks are transnational security issues at the global level in terms of their nature and extent of the damage, as well as multi-layered ones that affect local and personal security issues at the regional and national levels. In addition to national actors, non-state actors such as international organizations, multinational corporations, and global civil society, and furthermore, technology and social systems themselves are causing risks. Therefore, to solve the new security problem, it is necessary to establish a middle-level and complex governance mechanism that is sought at the regional and global levels beyond the fragmented dimension of the occurrence of new security issues that have been overlooked in the existing frame of perception, and to predict and find ways to respond to new security paradigms that have been identified in a broader sense.