• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.205-211
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• 2022

Various radioactive materials exist around us. In recent years, as interest in health has increased along with the improvement of the quality of life, examinations using radiation are also increasing. This research defined aforementioned radiation as a living radiation and developed a measurement to measure general knowledge people have on it. Eighteen reliable items were developed; current status on general knowledge regarding the safety of living radiation was analyzed using the items. As a result, a group with radiation-related education got statistically higher score than a group without such education. Correlation analysis and regression analysis showed that higher attention on usual safety leads into the greater knowledge on safety of living radiation. Therefore, this research shed lights on the necessity of radiation safety-related education in current educational course in schools.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.791-797
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• 2022

Through recent metaverse marketing case studies, success factors and activation methods were analyzed from the perspective of content, platform, network, and device of the metaverse ecosystem in each industry. The importance of contents and platform of metaverse could be found in entertainment, fashion, office space and real estate, education, advertisement and commerce industries. In order to vitalize the metaverse, firstly, it is necessary to strengthen active participation and retention by providing a stable revenue model for market participants. Secondly, the importance of attractive content to expand subscribers is a key trigger for metaverse activation. Thirdly, it is necessary to increase the convenience of using metaverse service by using a light and simple device for the user. Fourthly, a win-win cooperation strategy should be supported in the value chain of the industry through ecosystem scalability. In addition, business opportunities for market participants and additional revenue models should be continuously provided.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.4
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• pp.487-494
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• 2022

With the recent demand for analysis using data, the size of the knowledge graph, which is the data to be analyzed, gradually increased, reaching about 82 billion edges when extracted from the web as a knowledge graph. A lot of knowledge graphs are represented in the form of Resource Description Framework (RDF), which is a standard of W3C for representing metadata for web resources. Because of the characteristics of RDF, existing RDF storages have the limitations of processing time overhead when converting and storing large amounts of RDF data. To resolve these limitations, in this paper, we propose a method of compressing and converting large amounts of RDF data into integer IDs using MapReduce, and vertically partitioning and storing them. Our proposed method demonstrated a high performance improvement of up to 25.2 times compared to RDF-3X and up to 3.7 times compared to H2RDF+.

• Journal of Industrial Convergence
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• v.20 no.7
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• pp.65-71
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• 2022

With the development of ICT, as the era of the 4th industrial revolution arrives, the amount of data is enormous, and as big data technologies emerge, technologies for processing, storing, and processing data are becoming important. In this paper, we propose a system that detects events through monitoring and judges them using hash values because the damage to important files in case of leakage in industries and public places is serious nationally and property. As a research method, an optional event method is used to compare the hash value registered in advance after performing the encryption operation in the event of a file leakage, and then determine whether it is an important file. Monitoring of specific events minimizes system load, analyzes the signature, and determines it to improve accuracy. Confidentiality is improved by comparing and determining hash values pre-registered in the database. For future research, research on security solutions to prevent file leakage through networks and various paths is needed.

• Journal of Industrial Convergence
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• v.20 no.6
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• pp.7-15
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• 2022

Recently, due to the development of AI and big data technologies following the advent of the era of the 4th Industrial Revolution, the emerging metaverse industry is emerging as a new business, and in particular, from this point of view, this paper analyzes the history of metaverse and the pros and cons of "Geppetto", which is the most popular in the Korean metaverse market, and aims to give an appropriate direction for future development based on this. In order to carry out this study, we first used SWOT analysis techniques as an initial enterprise analysis method to examine the strengths and weaknesses, opportunities and threat requirements, and derive the status of each factor. Based on the factors in each of the subsequent derivatives, we wanted to explore the TOWS development strategy and present significant implications based on this.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.517-525
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• 2022

In the era of big data, various data mining techniques have been proposed as major analysis methodologies. As complex and diverse data is mass-produced, data mining techniques have attracted attention as a method that forms the foundation of data science. In this paper, we focused on the decision tree, which is frequently used in practice and easy to understand as one of representative data mining methods. Specifically, we analyzed the effect of the splitting method of decision trees on the model performance. We compared the prediction power and structures of decision tree models with different split methods based on various simulated data. The results show that the linear combination split method can improve the prediction accuracy of decision trees in the case of data simulated from nonlinear models with complex structure.

• Journal of Internet of Things and Convergence
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• v.7 no.4
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• pp.9-14
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• 2021

In computing systems that require high reliability, the method of predicting the lifetime of a storage device is one of the important factors for system management because it can maximize usability as well as data protection. The life of a solid state drive (SSD) that has recently been used as a storage device in several storage systems is linked to the life of the NAND flash memory that constitutes it. Therefore, in a storage system configured using an SSD, a method of accurately and efficiently predicting the lifespan of a NAND flash memory is required. In this paper, a method for optimizing the lifetime prediction of a flash memory-based storage device using the frequency of NAND flash memory failure is proposed. For this, we design a cost matrix to collect the frequency of defects that occur when processing data in units of Drive Writes Per Day (DWPD). In addition, a method of predicting the remaining cost to the slope where the life-long finish occurs using the Gradient Descent method is proposed. Finally, we proved the excellence of the proposed idea when any defect occurs with simulation.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.27-33
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• 2021

With increasing interest in key areas of the 4th industrial revolution such as artificial intelligence, deep learning and big data, scientific approaches have developed in order to overcome the limitations of traditional decision-making methodologies. These scientific techniques are mainly used to predict the direction of financial products. In this study, the factors of apartment prices, which are of high social interest, were analyzed through SOM. For this analysis, we extracted the real prices of the apartments and selected a total of 16 input variables that would affect these prices. The data period was set from 1986 to 2021. As a result of examining the characteristics of the variables during the rising and faltering periods of the apartment prices, it was found that the statistical tendencies of the input variables of the rising and the faltering periods were clearly distinguishable. I hope this study will help us analyze the status of the real estate market and study future predictions through image learning.

• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.191-199
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• 2021

Based on survey and data analysis, this paper established a separate and hierarchical design process for lady bags. The design process is divided into four parts: survey, concept extraction, separation and hierarchy design and detail improvement. In light of the influence value grade of lady bag design elements, the data of key elements of lady bags were analyzed, and elements related to new product design were extracted to form conceptual elements, and integrated into design experiments at different levels. Then, their usable proportion in design was measured and applied in design to complete the design of new products. Through the experiment, this design process can provide designers with a new design perspective and improves the timeliness and practicability of fashion design.

• Journal of Korea Trade
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• v.25 no.3
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• pp.153-168
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• 2021

Purpose - In this study, we aim to explore new distribution strategies for sustainable growth in the era of the 4th industrial revolution, focusing on SMEs (small and medium-sized enterprises) in Korea, and suggest ways to upgrade the government's official distribution channel to the next level. Design/methodology - First of all, this paper explored the prior research, the current status of sales support for SMEs, and the changes in the distribution industry due to COVID-19 pandemic. Based on Moon (2016)'s ABCD strategic model - Agility, Benchmarking, Convergence, and Dedication, the study then derived directions in which official distribution channels should move and the new distribution strategy for Korean SMEs to secure competitive advantage. Findings - First, in terms of 'Agility', in order to upgrade official distribution channels, which are currently at some competitive disadvantages compared to private distribution companies, we must quickly introduce technologies for the 4th industrial revolution, such as AI, Big Data, etc., and establish precise strategies to strengthen the capabilities of SMEs. Second, in terms of 'Benchmarking', the use of "Chamelezones" has been increasing to enhance the competitiveness of offline stores in line with recent ontact trends. Therefore, official distribution channels should also benchmark such cases, strengthening their competitiveness by utilizing offline spaces more efficiently and effectively. Third, in terms of 'Convergence', in line with the rapidly changing trend of the times, official distribution channels should also promote active partnerships with media commerce, e-commerce and ICT platforms, as well as cooperation with private retailers, and focus on creating synergy effects through them. Finally, from the perspective of 'Dedication', digitalization should be promoted step by step, finding the sector that can accelerate digital among the value chains of official distribution channels, and continuing to discuss how to digitize it realistically. Originality/value - Based on this analysis, we have presented strategies and implications for innovating official distribution channels for SMEs, which will contribute to enhancing the competitive advantage of official distribution channels in the post COVID-19 pandemic era.