• Journal of the Korea Society of Computer and Information
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• v.29 no.7
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• pp.169-179
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• 2024

Currently, information technologies such as blockchain and metaverse are being innovatively developed in Korea and around the world. The government has defined the innovation of these cyber-related technologies as the fourth industrial revolution and presented the Digital New Deal as an important policy of the Korean version of the New Deal, and is implementing various policies and systems related to it. This situation is expected to affect the development of the real estate registration system in Korea. Moreover, as the Supreme Court is currently promoting the transition to a future registration system, it is necessary to examine whether blockchain technology, which allows parties to exchange value without a third party guaranteeing the transaction, can be used in the real estate registration system. In order to secure the credibility of the real estate registration as electronic information under the registration system that introduces electronic registration and blockchain system, the transparency of transaction identification and real estate registration details should also be recorded using the blockchain system as a way to prevent such crimes and legal disputes. As a solution, it is worth considering how to improve the reliability of transaction identification, recognize the actual examination rights of the registrar in the foundation system of the real estate register, and increase public trust by going through the notarization stage when recording rights such as real rights, and consider how to introduce a blockchain system at this stage to ensure integrity and reliability. In the stage before the current real estate registration and study system is converted to a blockchain system, the clarity, transparency, and consistency of the real estate registration entries with the actual real estate must be established so that the real estate study can finally be recognized as authoritative, thereby ensuring the trust of the transaction parties to the real estate study system that has adopted the blockchain system in the future, and bringing us closer to the goal of real estate transactions in the form of smart contracts between the parties who have trusted it based on transparency and integrity of real estate study in the real estate transaction market.

• Journal of Platform Technology
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• v.11 no.6
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• pp.56-67
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• 2023

The increased demand for electronic components, spurred by the Fourth Industrial Revolution and the COVID-19 pandemic, has facilitated human life but also escalated the production of e-waste. Discussions on the impact of e-waste have primarily revolved around environmental, health, and social issues, with global legislations focusing on addressing these concerns. However, e-waste poses unique security risks, such as potential technological and personal information leaks, unlike conventional waste. Current discourse on e-waste security is notably insufficient. This study aims to empirically analyze the relatively overlooked trends in e-waste security, employing three methodologies. Firstly, it assesses the general trend in discussions on e-waste by analyzing year-wise documents and media reports. Secondly, it identifies key trends in e-waste security by examining documents on the subject. Thirdly, the study reviews national security guidelines related to e-waste disposal to assess the necessity of designing security strategies for e-waste management. This research is significant as it is one of the first in korea to address e-waste from a security perspective and offers a multi-dimensional analysis of e-waste security trends. The findings are expected to enhance domestic awareness of e-waste and its security issues, providing an opportunity for proactive response to these security risks.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.95-95
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• 2017

Lodging is a serious issue in rice production, because it drastically decreases the biomass production and grain yield. Since the Green Revolution, the lodging resistance has been increased by lowering the moment of above-ground parts due to the short culm by the semi-dwarf gene sd1. However, it has been pointed out that sd1 alone has suppressive effects for biomass production and yield. To increase rice yield, the long-culm and large panicle type varieties with a superior lodging resistance need to be developed. To improve the lodging resistance and yield of these type varieties, it would be effective to identify novel alleles for these traits underlying natural variations in rice and to pyramid these alleles to a single rice variety. In order to perform this strategy, we have developed new rice lines derived from crosses among varieties with superior alleles. At first, TULT-gh-5-5 was selected from a cross between strong culm and high biomass variety Leaf Star and high-yielding variety Takanari, and TUAT-32HB was selected from a cross between high-yielding variety Akenohoshi and Takanari. Then, we developed the super thick-culm and super grain-bearing line, LTAT-29 derived from a cross between TULT-gh-5-5 and TUAT-32HB. In the current study, to identify the QTLs and genes relating to the strong culm and the high yield of LTAT-29, we performed QTL analysis using SNPs markers with $F_2$ population derived from a cross between LTAT-29 and Takanari. LTAT-29 has never lodged throughout the growth period despite it had long culms and heavy panicles. LTAT-29 had a larger outer diameter of the culm and twice the size of the section modulus than Takanari. As a result, the bending moment at breaking of LTAT-29 was significantly larger than that of Takanari. Brown rice yield of LTAT-29 was $9.2t\;ha^{-1}$ about 10% higher than that of Takanari due to the larger number of spikelets per panicle. LTAT-29 had a greater number of secondary branches per panicle. In the $F_2$ population between LTAT-29 and Takanari, we found continuous frequency distributions in the section modulus and the spikelet number per panicle. Two QTLs increased the section modulus by the alleles of LTAT-29 were detected on Chr.1L and Chr.2L. One QTL increased the spikelet number per panicle of Takanari by the allele of LTAT-29 was detected on Chr.1L, and two QTLs increased the number of secondary branches per panicle by the alleles of LTAT-29 were detected on Chr.1L and Chr.4L. It was found that the alleles of these QTLs were the japonica type originated from Leaf Star or Akenohoshi. The novel QTLs for the traits related to super thick-culm and super grain-bearing and their combinations could be utilized for improving the lodging resistance and yield in rice varieties.

• Management & Information Systems Review
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• v.3
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• pp.287-316
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• 1999

Cyberspace permits us to more beyond traditional face-to-face, mail and telephone surveys, yet still to examine basic issues regarding the quality of data collection: sampling, questionnaire design, survey distribution, means of response, and database creation. This article address each of these issues by contrasting and comparing traditional survey methods(Paper-and-Pencil) with Internet or Personal Computer networks-mediated (Screen-and-Keyboard) survey methods also introduces researchers to this revolutionary and innovative tool and outlines a variety of practical methods for using the Internet or Personal Computer Networks. The revolution in telecommunications technology has fostered the rapid growth of the Internet all over the world. The Internet is a massive global network and comprising many national and international networks of interconnected computers. The Internet or Personal Computer Networks could be the comprehensive interactive tool that will facilitate the development of the skills. The Internet or Personal Computer Networks provides a virtual frontier to expand our access to information and to increase our knowledge and understanding of public opinion, political behavior, social trends and lifestyles through survey research. Comparable to other technological advancements, the Internet or Personal Computer Networks presents opportunities that will impact significantly on the process and quality of survey research now and in the twenty-first century. There are trade-offs between traditional and the Internet or Personal Computer Networks survey. The Internet or Personal Computer Networks is an important channel for obtaining information for target participants. The cost savings in time, efforts, and material were substantial. The use of the Internet or Personal Computer Networks survey tool will increase the quality of research environment. There are several limitations to the Internet or Personal Computer Network survey approach. It requires the researcher to be familiar with Internet navigation and E-mail, it is essential for this process. The use of Listserv and Newsgroup result in a biased sample of the population of corporate trainers. However, it is this group that participates in technology and is in the fore front of shaping the new organizations of interest, and therefore it consists of appropriate participants. If this survey method becomes popular and is too frequently used, potential respondents may become as annoyed with E-mail as the sometimes are with mail survey and junk mail. Being a member of the Listserv of Newsgroup may moderate that reaction. There is a need to determine efficient, effective ways for the researcher to strip identifiers from E-mail, so that respondents remain anonymous, while simultaneously blocking a respondent from responding to a particular survey instrument more than once. The optimum process would be on that is initiated by the researcher : simple, fast and inexpensive to administer and has credibility with respondents. This would protect the legitimacy of the sample and anonymity. Creating attractive Internet or Personal Computer Networks survey formats that build on the strengths of standardized structures but also capitalize on the dynamic and interactive capability of the medium. Without such innovations in survey design, it is difficult to imagine why potential survey respondents would use their time to answer questions. More must be done to create diverse and exciting ways of building an credibility between respondents and researchers on the Internet or Personal Computer Networks. We believe that the future of much exciting research is based in the Electronic survey research. The ability to communicate across distance, time, and national boundaries offers great possibilities for studying the ways in which technology and technological discourse are shaped. used, and disseminated ; the many recent doctoral dissertations that treat some aspect of electronic survey research testify to the increase focus on the Internet or Personal Computer Networks. Thus, scholars should begin a serious conversation about the methodological issues of conducting research In cyberspace. Of all the disciplines, Internet or Personal Computer Networks, emphasis on the relationship between technology and human communication, should take the lead in considering research in the cyberspace.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.836-848
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• 2019

This paper aims at providing a critical view over the cybernetics theory especially of first generation on which the artificial intelligence heavily depends nowadays. There has been a commonly accepted thought that the conception of artificial intelligence could not has been possible without being influenced by N. Wiener's cybernetic feedback based information system. Despite the founder of contemporary cybernetics' ethical concerns in order to avoid an increasing entropy phenomena(social violence, economic misery, wars) produced through a negative dynamics of the western modernity regarded as the most advanced form of humanism. In this civilizationally changing atmosphere, the newly born cybernetic technology was thus firmly believed as an antidote to these vices deeply rooted in humanism itself. But cybernetics has been turned out to be a self-organizing, self-controlling mechanical system that entails the possibility of telegraphing human brain (which are transformed into patterns) through the uploading of human brain neurons digitalized by the artificial intelligence embedded into computing technology. On this background emerges posthuman (or posthumanism) movement of which concepts have been theorized mainly by its ardent apostles like N. K. Hayles, Neil Bedington, Laurent Alexandre, Donna J. Haraway. The converging of NBIC Technologies leading to the opening of a much more digitalizing society has served as a catalyst to promote the posthuman representations and different narratives especially in the contemporary visual arts as well as in the study of humanities including philosophy and fictional literature. Once Bruno Latour wrote "Modernity is often defined in terms of humanism, either as a way of saluting the birth of 'man' or as a way of announcing his death. But this habit is itself modern, because it remains asymmetrical. It overlooks the simultaneous birth of 'nonhumaniy' - things, or objects, or beasts, - and the equally strange beginning of a crossed-out God, relegated to the sidelines."4) These highly suggestive ideas enable us to better understand what kind of human beings would emerge following the dazzlingly accelerating advancement of artificial intelligence technology. We wonder whether or not this newly born humankind would become essentially Homo Artificialis as a neuronal man stripping off his biological apparatus. However due to this unprecedented situation humans should deal with enormous challenges involving ethical, metaphysical, existential implications on their life.

• Journal of the Korean Society for Marine Environment & Energy
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• v.15 no.3
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• pp.263-272
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• 2012

Carbon dioxide, emitted by human activities since the industrial revolution, is regarded as a major contributor of global warming. There are many efforts to mitigate climate change, and carbon dioxide capture and geological storage (CCS) is recognized as one of key technologies because it can reduce carbon dioxide emissions from large point sources such as a power station or other industrial installation. The inclusion of CCS as clean development mechanism (CDM) project activities has been considered at UNFCCC as financial incentive mechanisms for those developing countries that may wish to deploy the CCS. Although the Conference of the Parties serving as the Meeting of the Parties to the UNFCCC's Kyoto Protocol (CMP), at Cancun in December 2010, decided that CCS is eligible as CDM project activities, the issues identified in decision 2/CMP.5 should be addressed and resolved in a satisfactory manner. Major issues regarding modalities and procedure are 1) Site selection, 2) Monitoring, 3) Modeling, 4) Boundaries, 5) Seepage Measuring and Accounting, 6) Trans-Boundary Effects, 7) Accounting of Associated Project Emissions (Leakage), 8) Risk and Safety Assessment, and 9) Liability Under the CDM Scheme. The CMP, by its decision 7/CMP.6, invited Parties to submit their views to the secretariat of Subsidiary Body for Scientific and Technological Advice (SBSTA), SBSTA prepared a draft modalities and procedure by exchanging views of Parties through workshop held in Abu Dhabi, UAE (September 2011). The 7th CMP (Durban, December 2011) finally adopted the modalities and procedures for CCS as CDM project activities (CMP[2011], Decision-/CMP.7). The inclusion of CCS as CDM project activities means that CCS is officially accredited as one of $CO_2$ reducing technologies in global carbon market. Consequently, it will affect relevant technologies and industry as well as law and policy in Korea and aboard countries. This paper presents a progress made on discussion and challenges regarding the issue, and aims to suggest some considerations to policy makers in Korea in order to demonstrate and deploy the CCS project in the near future. According to the adopted modalities and procedures for CCS as CDM project activities, it is possible to implement relevant CCS projects in Non-Annex I countries, including Korea, as long as legal and regulatory frameworks are established. Though Korea enacted 'Framework Act on Low Carbon, Green Growth', the details are too inadequate to content the requirements of modalities and procedures for CCS as CDM project. Therefore, it is required not only to amend the existing laws related with capture, transport, and storage of $CO_2$ for paving the way of an prompt deployment of CCS CDM activities in Korea as a short-term approach, but also to establish the united framework as a long-term approach.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.186-196
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• 2018

Junior colleges are higher education institutions that have played a major role in the economic development of Korea by providing the necessary human resources for its industrial development. Recently, however, they have experienced difficulties due to the reduction in the number of students. Therefore, it is time for junior colleges as a representative higher vocational education institution to change their role in this rapidly changing environment, and adopt a survival strategy through mutual cooperation and competition. The purpose of this study was to analyze the current state of the national health universities, to investigate the policy changes adopted by colleges and universities, and to utilize the results as data. This study analyzed the current status of health science colleges nationwide and investigated the policy changes as well as the directions presented to the colleges, in order to use the results as the basic data to promote the diversification of the class periods and degree programs. This study surveyed 636 professors from health sciences departments and industry workers from May 1 to May 30, 2017. 70.7% of the respondents supported the transition of the existing three-year systems of the health science departments to four-year systems. The reason for this is that it is possible to strengthen the field practice and personality education of the students by having a sufficient number of class periods, and to provide them with an equal educational background. The most anticipated effect of the transition to a four-year system is to improve the social status of medical personnel and to improve the educational environment of the colleges/universities. Moreover, the universities, associations of medical personnel and Ministry of Education are expected to play a leading role in the transition to the four-year system. Based on the results of this study, it was concluded that a more systematic and advanced vocational education system for the training of professional healthcare workers is needed in the upcoming fourth Industrial Revolution era. Also, this transition is expected to actively foster the education of advanced health care workers thanks to the diversification of the degree programs through the adjustment of the class periods which can be completed by general university (4-year) graduates.

• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.109-135
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• 2021

his study classified the development process of artificial intelligence (AI) speakers through analysis of the news text of artificial intelligence (AI) speakers shown in traditional news reports, and identified the characteristics of each product by period. The theoretical background used in the analysis are news frames and topic frames. As analysis methods, topic modeling and semantic network analysis using the LDA method were used. The research method was a content analysis method. From 2014 to 2019, 2710 news related to AI speakers were first collected, and secondly, topic frames were analyzed using Nodexl algorithm. The result of this study is that, first, the trend of topic frames by AI speaker provider type was different according to the characteristics of the four operators (communication service provider, online platform, OS provider, and IT device manufacturer). Specifically, online platform operators (Google, Naver, Amazon, Kakao) appeared as a frame that uses AI speakers as'search or input devices'. On the other hand, telecommunications operators (SKT, KT) showed prominent frames for IPTV, which is the parent company's flagship business, and 'auxiliary device' of the telecommunication business. Furthermore, the frame of "personalization of products and voice service" was remarkable for OS operators (MS, Apple), and the frame for IT device manufacturers (Samsung) was "Internet of Things (IoT) Integrated Intelligence System". The econd, result id that the trend of the topic frame by AI speaker development period (by year) showed a tendency to develop around AI technology in the first phase (2014-2016), and in the second phase (2017-2018), the social relationship between AI technology and users It was related to interaction, and in the third phase (2019), there was a trend of shifting from AI technology-centered to user-centered. As a result of QAP analysis, it was found that news frames by business operator and development period in AI speaker development are socially constituted by determinants of media discourse. The implication of this study was that the evolution of AI speakers was found by the characteristics of the parent company and the process of co-evolution due to interactions between users by business operator and development period. The implications of this study are that the results of this study are important indicators for predicting the future prospects of AI speakers and presenting directions accordingly.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.33-54
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• 2021

With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.