• Journal of the Korean Society for information Management
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• v.32 no.4
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• pp.137-165
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• 2015

This study aimed to investigate the period-specific changes (Library 1.0, Library 2.0, Library 3.0 Period) of job factors and performance features in academic libraries. For this, the study categorized an academic library's job into five dimensions: 1) library administration 2) collection development and management 3) information organization 4) information services and 5) information system development and management, After the categorized library's job was defined in detail, the Delphi survey was conducted twice on librarians and professors of library and information science. The result showed that there were many changes in job factors and performance features in academic libraries towards the period of library 2.0 characterized by user participation, sharing and openness and into library 3.0 characterized by social network and semantic web. Library 3.0 is likely to bring about a significant change in user services with ever changing technological advances stemming from library 2.0, such as mobile services, RFID and NFC etc. The finding of the study suggest that library systems need to be continually upgraded in the period of library 3.0.

• The KIPS Transactions:PartA
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• v.11A no.6
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• pp.459-468
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• 2004

Sharing XML trees on mobile devices has become more and more popular. Optimistic replication of XML trees for mobile devices raises the need for reconciliation of concurrently modified data. Especially for reconciling the modified tree structures, we have to compare trees by node mapping which takes O($n^2$) time. Also, using semantic based conflict resolving policy is often discussed in the literature. In this research, we focused on an efficient reconciliation method for mobile environments, using edit scripts of XML data sent from each device. To get a simple model for mobile devices, we use the XML list data sharing model, which allows inserting/deleting subtrees only for the repetitive parts of the tree, based on the document type. Also, we use keys for repetitive part subtrees, keys are unique between nodes with a same parent. This model not only guarantees that the edit action always results a valid tree but also allows a linear time reconciliation algorithm due to key based list reconciliation. The algorithm proposed in this paper takes linear time to the length of edit scripts, if we can assume that there is no insertion key conflict. Since the previous methods take a linear time to the size of the tree, the proposed method is expected to provide a more efficient reconciliation model in the mobile environment.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.691-704
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• 2021

The development of AI technology has brought about a big change in our lives. The importance of AI and data education is also growing as AI's influence from life to society to the economy grows. In response, the OECD Education Research Report and various domestic information and curriculum studies deal with data literacy and present it as an essential competency. However, the definition of data literacy and the content and scope of the components vary among researchers. Thus, we analyze the semantic similarity of words through Word2Vec deep learning natural language processing methods along with the definitions of key data literacy studies and analysis of word frequency utilized in components, to present objective and comprehensive definition and components. It was revised and supplemented by expert review, and we defined data literacy as the 'basic ability of knowledge construction and communication to collect, analyze, and use data and process it as information for problem solving'. Furthermore we propose the components of each category of knowledge, skills, values and attitudes. We hope that the definition and components of data literacy derived from this study will serve as a good foundation for the systematization and education research of AI education related to students' future competency.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.305-313
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• 2021

This study collected and analyzed big data from 1995 to 2020, focusing on the keywords "unwed mother", "single mother," and "single mom" to present appropriate government support policy directions according to changes in perspectives on unwed mothers. Big data collection platform Textom was used to collect data from portal search sites Naver and Daum and refine data. The final refined data were word frequency analysis, TF-IDF analysis, an N-gram analysis provided by Textom. In addition, Network analysis and CONCOR analysis were conducted through the UCINET6 program. As a result of the study, similar words appeared in word frequency analysis and TF-IDF analysis, but they differed by year. In the N-gram analysis, there were similarities in word appearance, but there were many differences in frequency and form of words appearing in series. As a result of CONCOR analysis, it was found that different clusters were formed by year. This study confirms the change in the perspective of unwed mothers through big data analysis, suggests the need for unwed mothers policies for various options for independent women, and policies that embrace pregnancy, childbirth, and parenting without discrimination within the new family form.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.2
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• pp.37-47
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• 2011

In the recent years, malicious codes called malware are having shown significant increase due to the code obfuscation to evade detection mechanisms. When the code obfuscation technique is applied to malwares, they can change their instruction sequence and also even their signature. These malwares which have same functionality and different appearance are able to evade signature-based AV products. Thus, AV venders paid large amount of cost to analyze and classify malware for generating the new signature. In this paper, we propose a novel approach for detecting metamorphic malwares. The proposed mechanism first converts malware's API call sequences to call graph through dynamic analysis. After that, the callgraph is converted to semantic signature using 128 abstract nodes. Finally, we extract all subgraphs and analyze how similar two malware's behaviors are through subgraph similarity. To validate proposed mechanism, we use 273 real-world malwares include obfuscated malware and analyze 10,100 comparison results. In the evaluation, all metamorphic malwares are classified correctly, and similar module behaviors among different malwares are also discovered.

• Journal of the Korean Society of Earth Science Education
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• v.15 no.2
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• pp.285-298
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• 2022

This study is to investigate the effects and characteristics of science and engineering integrated lessons on elementary students' creative engineering problem solving propensity (CEPSP). The science and engineering integrated lessons used in this study was a 10 lesson-hours STEM program, co-developed by University of Minnesota and Purdue University. The program was implemented in the 6th grade science class of H Elementary School located in P Metropolitan city. The main data of this study are the pre-post CEPSP result and interview with 5 students collected before and after the research. The CEPSP result was analyzed by a paired-sample t-test and hierarchical cluster analysis. As a result of the t-test, it was found that overall, the program has a positive effect on the students' CEPSP score. As a result of cluster analysis, it was confirmed that studnets' CEPSP could be classified into two groups (lower and higher score cluster). Five students whose, CEPSP score has significantly improved after the lessons were interviewed to find out what the characteristics of the program that contribute the significant change are. As a result of conducting centroid analysis of the interview transcription and the hybrid analysis method, it was found that the meaningful experiences that the five students commonly shared were 'problem solving through collaboration' and 'through repeated experiments (redesign)', problem solving' and 'utilization of scientific knowledge'. As minor reactions, 'choice of the best experimental method' and 'difference between science and engineering' appeared.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.33 no.3
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• pp.1-15
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• 2015

Based on the analysis and interpretation of the headwords and poetic words of a group of eleven collecting sceneries of Jeonju, the origin and transformations of the Jeonju-Palkyung(Eight sceneries of Jeonju) investigated by a time-series analysis are as follows. As there is no collection of landscape with a formal structure similar to that of the current Jeonju-Palkyung, prior to the Palkyung by Chujae(秋齋) Cho Soo-Sam(趙秀三, 1762~1849), there is no significant problem in assuming the eight poems in Chujaejib(秋齋集) are the origins of the Jeonju-Palkyung, and it is estimated to have been produced in 1829. In the late-19th century poem 'Wansanseunggyeong(完山勝景)', 'the Palkyung in Yeollyeo Chunhyang Sujeolga', and 'the Palkyung delivered by poet Shin Seokjeong in the Japanese colonial era', only the 'Dongpogwibeom(東浦歸帆)' changed from Dongjipo to Dongchon of Bongdong as for 'Landscape Setting There($L_{ST}$)' according to changes in district administration; despite this change, the fact that they are not too different from the Palkyung of Cho Soo-Sam, also supports this. Moreover, according to the headword concordance analysis, it is proven that the Jeonju-Palkyung was established in the late-19th century and continued to be the region's representative sceneries even during the Japanese colonial era, and later 'Namcheonpyomo(南川漂母)' and 'Gonjimangwol(坤止望月)' were added to expand to the Jeonju-Sipkyung(ten sceneries of Jeonju). But when we see there are famous spots that are the origins of the Jeonju-Sipkyung, including Gyeonggijeon, Geonjisan, Jogyeongdan, Omokdae, and Girinbong, Deokjinyeon, and Mangyeongdae, all of which have great representational significance as the capital of Jeolla Provincial Office as well as of the place of origin for Joseon Dynasty in the grouping of sceneries during the early Joseon Dynasty, including "Paehyangsipyeong (沛鄕十詠)", "Gyeondosipyeong (甄都十詠)", and "Binilheonsipyeong(賓日軒十詠)", the beginnings of the semantic Jeonju-Palkyung should be considered up to the first half of Joseon Dynasty. During this period, not only the fine sceneries with high retrospective merit as the capital of Hubaekje, like Gyeonhwondo(甄萱都), but also the sceneries like Mangyeongdae that reminds people of Jeong Mongju(鄭夢周) and Yi Seonggye(李成桂) in the late period of Goryeo appeared, elevating the status of Jeonju as the capital of Hubaekje and shortening the historical gaps as the place of origin of the Joseon Dynasty. The Jeonju-Palkyung is an organic item that carries the history of the Joseon Dynasty after Hubaekje and has gone through many cycles of disappearing and reappearing, but it has continued to change and transform as the region's representative sceneries. The Jeonju-Palkyung is a cultural genealogy that helps one understand the 'Jeonju Hanpunggyeong(韓風景: the sceneries of Korea in Jeonju)', and the efforts to preserve and pass it down to the next generation would be the responsibility of the people of Jeonju.

• 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.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.4
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• pp.33-49
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• 2019

The purpose of this study was to investigate the changes in the experiences of visitors of Yeonnam-dong during the period covering the development of a linear park, the Gyeongui Line Park. This study used a text mining technique to analyze Naver Blog postings of those who visited Yeonnam-dong from June 2013 to May 2017, divided into four periods -from June 2013 to May 2014, from June 2014 to May 2015, from June 2015 to May 2016 and from June 2016 to May 2017. The keywords used were 'Yeonnam-dong', 'Gyeongui Line' and 'Yeontral Park' and the data was further refined and resampled. A semantic network analysis was conducted on the basis of the co-occurrences of words. The results of the study were as follows. During the entire period, the main experience of visitors to Yeonnam-dong was 'food culture' consistently, but the activities related to 'market', 'browsing', and 'buy' increased. Also, activities such as 'walk', 'play' and 'rest' in the park newly appeared after the construction of the park. Moreover, more diverse opinions about the Yeonnam-dong were expressed on the blog, and Yeonnam-dong began to be recognized as a place where a variety of activities can be enjoyed. Lastly, when the visitors wrote about the theme 'food culture', the scope of the keywords expanded from simple ones, such as 'eat', 'photograph' and 'chatting' to 'market', 'browsing', and 'walk'. The sub-themes that appeared with the park also expanded to various topics with the emergence of the Gyeongui Line Book Street. This study analyzed the change of experiences of visitors objectively with text mining, a quantitative methodology. Due to the nature of text mining, however, the subjective opinions inevitably have been involved in the process of refining. Also, further research is required to assess the direct relationship between these changes and park construction.