• Title/Summary/Keyword: Conversion Network

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Development of Convertor supporting Multi-languages for Mobile Network (무선전용 다중 언어의 번역을 지원하는 변환기의 구현)

  • Choe, Ji-Won;Kim, Gi-Cheon
    • The KIPS Transactions:PartC
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    • v.9C no.2
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    • pp.293-296
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    • 2002
  • UP Link is One of the commercial product which converts HTML to HDML convertor in order to show the internet www contents in the mobile environments. When UP browser accesses HTML pages, the agent in the UP Link controls the converter to change the HTML to the HDML, I-Mode, which is developed by NTT-Docomo of Japan, has many contents through the long and stable commercial service. Micro Explorer, which is developed by Stinger project, also has many additional function. In this paper, we designed and implemented WAP convertor which can accept C-HTML contents and mHTML contents. C-HTML format by I-Mode is a subset of HTML format, mHTML format by ME is similar to C-HTML, So the content provides can easily develop C-HTML contents compared with WAP and the other case. Since C-HTML, mHTML and WML are used under the mobile environment, the limited transmission capacity of one page is also similar. In order to make a match table. After that, we apply conversion algorithm on it. If we can not find matched element, we arrange some tags which only can be supported by WML to display in the best shape. By the result, we can convert over 90% contents.

Contactless Data Society and Reterritorialization of the Archive (비접촉 데이터 사회와 아카이브 재영토화)

  • Jo, Min-ji
    • The Korean Journal of Archival Studies
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    • no.79
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    • pp.5-32
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    • 2024
  • The Korean government ranked 3rd among 193 UN member countries in the UN's 2022 e-Government Development Index. Korea, which has consistently been evaluated as a top country, can clearly be said to be a leading country in the world of e-government. The lubricant of e-government is data. Data itself is neither information nor a record, but it is a source of information and records and a resource of knowledge. Since administrative actions through electronic systems have become widespread, the production and technology of data-based records have naturally expanded and evolved. Technology may seem value-neutral, but in fact, technology itself reflects a specific worldview. The digital order of new technologies, armed with hyper-connectivity and super-intelligence, not only has a profound influence on traditional power structures, but also has an a similar influence on existing information and knowledge transmission media. Moreover, new technologies and media, including data-based generative artificial intelligence, are by far the hot topic. It can be seen that the all-round growth and spread of digital technology has led to the augmentation of human capabilities and the outsourcing of thinking. This also involves a variety of problems, ranging from deep fakes and other fake images, auto profiling, AI lies hallucination that creates them as if they were real, and copyright infringement of machine learning data. Moreover, radical connectivity capabilities enable the instantaneous sharing of vast amounts of data and rely on the technological unconscious to generate actions without awareness. Another irony of the digital world and online network, which is based on immaterial distribution and logical existence, is that access and contact can only be made through physical tools. Digital information is a logical object, but digital resources cannot be read or utilized without some type of device to relay it. In that respect, machines in today's technological society have gone beyond the level of simple assistance, and there are points at which it is difficult to say that the entry of machines into human society is a natural change pattern due to advanced technological development. This is because perspectives on machines will change over time. Important is the social and cultural implications of changes in the way records are produced as a result of communication and actions through machines. Even in the archive field, what problems will a data-based archive society face due to technological changes toward a hyper-intelligence and hyper-connected society, and who will prove the continuous activity of records and data and what will be the main drivers of media change? It is time to research whether this will happen. This study began with the need to recognize that archives are not only records that are the result of actions, but also data as strategic assets. Through this, author considered how to expand traditional boundaries and achieves reterritorialization in a data-driven society.

Analysis of media trends related to spent nuclear fuel treatment technology using text mining techniques (텍스트마이닝 기법을 활용한 사용후핵연료 건식처리기술 관련 언론 동향 분석)

  • Jeong, Ji-Song;Kim, Ho-Dong
    • 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.