• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.6
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• pp.1467-1482
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• 2017

Recently, Interests on The Fourth Industrial Revolution has been increased. In the manufacturing sector, the introduction of Smart Factory, which automates and intelligent all stages of manufacturing based on Cyber Physical System (CPS) technology, is spreading. The complexity and uncertainty of smart factories are likely to cause unexpected problems, which can lead to manufacturing process interruptions, malfunctions, and leakage of important information to the enterprise. It is emphasized that there is a need to perform systematic management by analyzing the threats to the Smart Factory. Therefore, this paper systematically identifies the threats using the STRIDE threat modeling technique using the data flow diagram of the overall production process procedure of Smart Factory. Then, using the Attack Tree, we analyze the risks and ultimately derive a checklist. The checklist provides quantitative data that can be used for future safety verification and security guideline production of Smart Factory.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.7
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• pp.339-344
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• 2016

With increasing complexity of automotive software it has become important issue in the automotive safety. So, Automotive SPICE process have been proposed to solve this problem. The integrated management system and tools are needed for perform the Automotive SPICE process. It is difficult to adopt an integrated management system and tools because small business are lack of human resource and tools. Therefore, HIS scope items comply with Automotive SPICE minimum requirement should be targeted for the small business. In this paper, an open-source system based on process management tool required to perform the Automotive HIS scope items is proposed. The proposed system can perform the Automotive SPICE HIS scope items are carried and it showed that satisfy the Automotive SPICE HIS scope items.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4B
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• pp.403-418
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• 2009

IP version 6 (IPv6) is a new If addressing scheme that has 128-bit address space. IPv6 is proposed to solve the address space problem of IP version 4 (IPv4) which has 32-bit address space. For a given IPv6 routing set, if a forwarding table is built using a trio structure, the trio has a lot more levels than that for IPv4. Hence, for IPv6 address lookup, the binary search on trio levels would be more appropriate and give better search performance than linear search on trio levels. This paper proposes a new IPv6 address lookup algorithm performing binary search on trio levels. The proposed algorithm uses a Bloom filter in pre-filtering levels which do not have matching nodes, and hence it reduces the number of off-chip memory accesses. Simulation has been performed using actual IPv6 routing sets, and the result shows that an IPv6 address lookup can be performed with 1-3 memory accesses in average for a routing data set with 1096 prefixes.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.1
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• pp.395-404
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• 2019

South Korea's economic growth was rapid, It was occasioned the concentration of resources in the metropolitan area. On the other hand, the province has a narrow economic base compared to the metropolitan area, and the underpopulation have been identified. Thus, The government announced the 'National balanced development law' in 2004 to reduce the problem of regional imbalances. The study collected data on 95 of relocated public institutions, and unlike previous studies, Mamquist analysis was used to compare the productivity before and after each public institutions' s relocation. The study focused on how the relocation of public institutions affected the productivity of public institutions through Malmquist Analysis. The results of the analysis show that productivity is declining after most public institutions have moved. And two independent samples T-test result, respective yearly average is nonsignificant.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.7
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• pp.783-790
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• 2017

An acceptable proximity assessment collision probability is widely considered to be less than $10^{-4}$ in maritime traffic safety audit schemes. In the 1970s, Fujii, Macduff and colleagues introduced various models for collision probability of aberrancy in the community. Although existing studies ensured acceptable proximity collision probability, around $10^{-4}$, they were constrained by assumptions. A lack of support for the proximity probability criterion has been investigated in this study for practical use. The appropriate proximity probability for different size vessels in both straight and curved lanes has been analyzed based on GICOMS data. As a result, reasonable proximity collision probabilities were determined for various vessel traffic conditions. Accordingly, necessary improvements in the maritime traffic system have been suggested in consideration for various maritime traffic situations and conditions.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.05a
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• pp.142-143
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• 2019

Busan Port ranked 6th in the world with 21.67 million TEUs of container handling in 2018, but the ship supply industry has fallen short of that. Despite its technological prowess, Korea's ship supply industry lacks competitive edge in many aspects such as government support, integrated platform, and infrastructure compared to overseas ship supply industries. The use of code, which is not standardized, can be cited as a leading factor that undermines the competitiveness of Korea's ship supply industries. In the ship supply industry, the use of non-standardized codes can make it difficult to manage or analyze meaningful statistics, and, by extension, can lead to the loss of new business opportunities. Therefore, in this study, we intend to use local ship supply transaction data to study how to standardize item code to solve the problem.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.3
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• pp.129-136
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• 2019

There are a variety of entities in natural language such as people, organizations, places, and products. These entities can have many various meanings. The ambiguity of entity is a very challenging task in the field of natural language processing. Entity Linking(EL) is the task of linking the entity in the text to the appropriate entity in the knowledge base. Pairwise based approach, which is a representative method for solving the EL, is a method of solving the EL by using the association between two entities in a sentence. This method considers only the interdependence between entities appearing in the same sentence, and thus has a limitation of global interdependence. In this paper, we developed an Entity2vec model that uses Word2vec based on knowledge base of RDF type in order to solve the EL. And we applied the algorithms using the generated model and ranked each entity. In this paper, to overcome the limitations of a pairwise approach, we devised a pairwise approach based on comprehensive interdependency and compared it.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.261-267
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• 2021

The mission of the reserve forces unit is to prepare good training for reserve forces during peacetime. For good training, units require proper organization support agents, but they have difficulties due to a lack of unit members. For that reason, the units forecast the monthly attendance rate of reserve forces (using the x-1 year's result) to organize support agents and unit schedule. On the other hand, the existing planning method can have more errors compared to the actual result of the attendance rate. This problem has a negative effect on the training performance. Therefore, it requires more accurate forecast models to reduce attendance rate errors. This paper proposes an attendance rate forecast model using data mining. To verify the proposed data mining based model, the existing planning method was compared with the proposed model using real data. The results showed that the proposed model outperforms the existing planning method.

• Korean Journal of Construction Engineering and Management
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• v.23 no.1
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• pp.113-117
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• 2022

Additive manufacturing (AM, also known as 3D printing) technology is digitalized technology, making it easy to predict and manage quality and also, have design freedom ability. With these advantages, AM technology is applied to various industries. In particular, a method of manufacturing buildings and infrastructure with AM technology is being proposed to the construction industry. However, the application of AM technology is restricted due to problems such as insufficient history and quality of technology, lack of construction management methods, and certification of manufacturing products. Therefore, the manufacture of architectural products is implemented with indirect AM technology. In particular, it manufactures formwork using AM and injecting building materials to implement the architectural product. In this study, hybrid type material extrusion AM is used to manufacture large-sized formwork and implement building products. Moreover, we identify factors that can predict productivity and economic feasibility in the additive manufacturing process. As a result, design optimization results are proposed to reduce the production cost and time of architecture buildings.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.225-238
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• 2022

Although the importance of literacy in Artificial Intelligence (AI) education is increasing, there is a lack of testing tools for measuring such competency. To address this gap, this study developed a testing tool that measures AI literacy among middle school students. This goal was achieved through the establishment of an expert group that was enlisted to determine the relevant factors and items covered by the proposed tool. To verify the reliability and validity of the developed tool, a field review, exploratory factor analysis, and confirmatory factor analysis were conducted. These procedures resulted in a testing tool comprising six domains that encompass 30 items. The domains are the social impact of AI (eight items), the understanding of AI (six items), AI execution plans (five items), problem solving with AI (five items), data literacy (four items), and AI ethics (two questions). The items are to be rated using a five-point Likert scale. The internal consistency of the tool was .970 (total), while that of the domains ranged from .861 to .939. This study can serve as reference for developing the analysis of AI literacy, teaching and learning, and evaluation in AI education.