• Journal of Korean Society for Quality Management
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• v.46 no.2
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• pp.225-242
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• 2018

Purpose: Recent trends have shown that the usage of big data analysis is becoming the core of identifying promising future technologies and emerging technologies. Accordingly, applying these trends by analyzing defense related data in such sources as journals, articles, and news will provide crucial clues in predicting and identifying core future technologies that can be used to develop creative and unprecedented future weapon systems that could change the warfare. Methods: To identify technology fields that are closely related to the 4th industrial revolution and recent technology development trends, environmental analysis, text mining, and military applicability survey have been included in the process. After the identification of core technologies that are militarily applicable, future weapon systems based on these technologies as well as their operation concepts are suggested. Results: Through the study, 73 important trends, from which 11 mega trends are derived, are identified. These mega trends can be expressed by 13 promising technology fields. From these technology fields, 248 promising future technologies are identified. Afterwards, further assessment is performed, which leads to the selection of 63 core technologies from the pool. These are named as "future defense technologies" which then become the bases for 40 future weapons systems that the military can use. Conclusion: Predicting future technologies using text mining analysis have been attempted by various organizations across the globe, especially in the fields related to the 4th industrial revolution. However, the application of it in the field of defense industry is unprecedented. Therefore, this study is meaningful in that it not only enables the military personnel to see promising future technologies that can be utilized for future weapon system development, but helps one to predict the future defense technologies using the method introduced in the paper.

• Electronics and Telecommunications Trends
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• v.16 no.5 s.71
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• pp.167-178
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• 2001

코스닥 및 나스닥 시장의 붕괴로 인한 벤처투자 시장의 급냉이 벤처기업뿐만 아니라 벤처캐피탈업계에도 커다란 악영향을 주고 있다. 벤처투자 시장의 실패와 성공의 엇갈린 결과들이 속출되고 있는 가운데, 벤처기업에 대한 국내 벤처캐피탈의 투자동향, 투자특성 및 향후 IT 투자방향을 분석해 봄으로써 IT 벤처기업 육성을 위한 벤처캐피탈들의 나아가야 할 방향 및 시사점을 제시하고자 한다.

• Korean Medical Education Review
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• v.20 no.2
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• pp.91-102
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• 2018

This study explored medical students' major research topics and research methods by analyzing 184 academic articles pertaining to the characteristics of medical students from 2007 to 2017. Results showed many papers dealing with medical students' emotional and cognitive aspects, student counseling, clinical practice education, and curriculum management. According to the medical education accreditation board, research trends were found mostly in the student and curriculum areas of learner characteristics, medical humanities, student counseling, clinical practice education, and curriculum management. Common research topics have been steadily increasing since the introduction of the evaluation accreditation standard in 2012. Medical students predominantly used quantitative research methods for the studies. In the future, it is necessary to ensure that research topics such as CQI, digital- and performance-based clinical practice, and convergent curriculum within the Fourth Industrial Revolution are being studied. In addition, it is crucial to investigate learners' unique, dynamic, and qualitative characteristics through qualitative and mixed methods.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.4
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• pp.164-170
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• 2020

Recently, the aviation industry faced a major crisis due to the impact of COVID-19. However, despite the sluggish passenger transportation, the cargo transportation sector is relatively maintained or increasing depending on the item. In this study, we will look at the trends before and after COVID-19, focusing on the cargo export field, which is a concern of the aviation industry. First, it analyzes the entire air cargo and then analyzes the trends of each item and country in detail. In particular, it examines the process of changes in air transport costs, which increased significantly immediately after COVID-19, and conducts future trends and prospects in the cargo export field. As a result of the study, some characteristics of air cargo exports before and after COVID-19 were found in an analysis by item and country, and transportation costs varied according to route distance.

• Electronics and Telecommunications Trends
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• v.37 no.4
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• pp.1-10
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• 2022

As the response to climate change becomes a more pressing global issue, so do expectations for climate change in the green information and communication technology (ICT) industry and the possibility of solving environmental problems through ICT. However, because the green ICT industry is still in its early stages, there is little research on it. Understanding the startup ecosystem in the industry is helpful for recognizing innovation trends in emerging technologies such as green ICT. In this regard, this paper investigates the current state and characteristics of the green ICT ecosystem and presents implications based on an examination of startup venture capital investment trends and submarket identification in the green ICT industry as emphasized by the carbon neutrality paradigm shift. The analysis included 4,807 companies and 3,990 funding records, as well as exploratory data analysis and "k-means" clustering techniques.

• Journal of dental hygiene science
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• v.21 no.2
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• pp.104-110
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• 2021

Background: Regardless of countries, the myth that rain makes the body ache has been worded in various forms, and a number of studies have been reported to investigate this. However, these studies, which depended on the patient's experience or memory, had obvious limitations. Google Trends is a big data analysis service based on search terms and viewing videos provided by Google LLC, and attempts to use it in various fields are continuing. In this study, we endeavored to introduce the 'value as a research tool' of the Google Trends, that has emerged along with technological advancements, through research on 'whether toothaches really occur frequently on rainy days'. Methods: Keywords were selected as objectively as possible by applying web crawling and text mining techniques, and the keyword "bi" meaning rain in Korean was added to verify the reliability of Google Trends data. The correlation was statistically analyzed using precipitation and temperature data provided by the Korea Meteorological Agency and daily search volume data provided by Google Trends. Results: Keywords "chi-gwa", "chi-tong", and "chung-chi" were selected, which in Korean mean 'dental clinic', 'toothache', and 'tooth decay' respectively. A significant correlation was found between the amount of precipitation and the search volume of tooth decay. No correlation was found between precipitation and other keywords or other combinations. It was natural that a very significant correlation was found between the amount of precipitation, temperature, and the search volume of "bi". Conclusion: Rain seems to actually be a cause of toothache, and if objective keyword selection is premised, Google Trends is considered to be very useful as a research tool in the future.

• The Journal of Information Systems
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• v.30 no.3
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• pp.201-216
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• 2021

Purpose The purpose of this study is to analyze the trend of patent technology in textile materials using text mining methodology based on Dynamic Embedded Topic Model and Structural Topic Model. It is expected that this study will have positive impact on revitalizing and developing textile materials industry as finding out technology trends. Design/methodology/approach The data used in this study is 866 domestic patent text data in textile material from 1974 to 2020. In order to analyze technology trends from various aspect, Dynamic Embedded Topic Model and Structural Topic Model mechanism were used. The word embedding technique used in DETM is the GloVe technique. For Stable learning of topic modeling, amortized variational inference was performed based on the Recurrent Neural Network. Findings As a result of this analysis, it was found that 'manufacture' topics had the largest share among the six topics. Keyword trend analysis found the fact that natural and nanotechnology have recently been attracting attention. The metadata analysis results showed that manufacture technologies could have a high probability of patent registration in entire time series, but the analysis results in recent years showed that the trend of elasticity and safety technology is increasing.

• The Journal of Economics, Marketing and Management
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• v.11 no.4
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• pp.53-63
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• 2023

Purpose: The purpose of this study is to examine the research trends in the papers published by Korean researchers related to traditional markets, to check what topics have been studied, and to make various suggestions for research directions and effective ways to revitalize traditional markets. Research design, data and methodology: To this end, this study conducted word frequency analysis, co-occurrence frequency analysis, BERTopic, LDA, dynamic topic modeling and OLS regression analysis using Python 3.7 on the English abstracts of a total of 502 papers extracted through ScienceON. Results: As a result of word frequency analysis and co-occurrence frequency analysis, it was found that studies related to traditional markets have been conducted not only on factors related to customers, but also on traditional market merchants and government policies, and the degree of service, quality, and satisfaction perceived by customers using traditional markets. Through BERTopic and LDA, three topics such as 'Traditional market safety management' were identified, and among them, it was found that 'Traditional market safety management' is relatively less attention by researchers. Conclusions: The results of this study suggest that future research on the revitalization of traditional markets should be conducted from a specific consulting perspective along with the establishment of various data, a causal model study from various perspectives such as the characteristics of merchants as well as consumers, and an integrated and convergent approach to policy formulation by the government and local governments.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.4
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• pp.601-608
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• 2023

Homomorphic encryption is a promising technology that has been extensively researched in recent years. It allows computations to be performed on encrypted data, without the need to decrypt it. In this paper, we perform bibliometric analysis to objectively and quantitatively analyze the research trends of homomorphic encryption technology using 6,047 homomorphic encryption papers from the Scopus database. Specifically, we analyze the number of papers by year, keyword co-occurrence, topic clustering, changes in related keywords over time, and country of homomorphic encryption research institutions. Our analysis results provide strategic directions for research and application of homomorphic encryption and can be a great help for subsequent research and industrial applications.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.279-291
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• 2023

In recent years, language model-based generative AI technologies have made remarkable progress. In particular, it has attracted a lot of attention due to its increasing potential in various fields such as summarization and code writing. As a reflection of this interest, the number of patent applications related to generative AI has been increasing rapidly. In order to understand these trends and develop strategies accordingly, future forecasting is key. Predictions can be used to better understand the future trends in the field of technology and develop more effective strategies. In this paper, we analyzed patents filed to date to identify the direction of development of language model-based generative AI. In particular, we took an in-depth look at research and invention activities in each country, focusing on application trends by year and detailed technology. Through this analysis, we tried to understand the detailed technologies contained in the core patents and predict the future development trends of generative AI.