• Journal of Digital Convergence
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• v.17 no.11
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• pp.61-70
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• 2019

The The government has recently announced its mid- to long-term plans for promoting art. With the advent of the 4th industrial revolution, contemporary art contents that are integrated with Intelligent Information Technologies such as Artificial Intelligence (AI), Virtual Reality (VR), and Big Data are being introduced, and social interest in humanities and creative convergence is rising. In addition, the industrialization of the art market is expanding amid the rising popularity of art among the general public and the growing interest of art as an investment replacement system, along with the strengthening of the creative personality education of our Education Ministry. Therefore, it is necessary to establish a strategy for transparency and revitalization of the art market by providing comprehensive information such as search functions, analysis data, and criticism by writer and price. This paper has established an information system plan for the establishment of an online supply system for art transaction information, providing auction transaction information for art market, providing report and news for art market, providing public relations platform, and providing art market analysis service and membership relationship management service. To this end, the future model was established through environmental analysis and focus analysis of the art market, and strategic tasks and implementation plans were established accordingly.

• Ecology and Resilient Infrastructure
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• v.7 no.4
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• pp.308-319
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• 2020

In this study, the field applicability of the recently constructed multifunctional fishway in Seomunbo, Yeongcheon-si, and Gyeongsangbuk-do were examined. The analysis variables were R/C slab (S1) and R/C+S/C slab (S2), the underground passage standard areas (width × length) were 1.4 m × 0.2 m, 1.4 m × 0.3 m, and 1.4 m × 0.6 m, and the flow velocities were 0.8, 1.2, and 1.6 m/s. As a result of the analysis, the safety of the design of Seomunbo was evaluated. The analysis showed compared to the Seomoon Weir fishway, the maximum stress of S2 decreased by 24 - 32%, the bending moment of the underground passage decreased by 16 - 33%, the maximum stress of the sidewall decreased by 20 - 36%. In addition, the bending moment of the upper slab decreased by 17 - 33%, the maximum stress of the upper slab decreased by 9 - 28%, and the bending moment decreased by 19 - 33%. Complementation was required in the following percentages: 18% and 14% for the maximum stress and bending moment of the underground passage, respectively, 15% and 17% for the maximum sidewall stress and bending moment, respectively, and 11% and 16% for the upper slab maximum stress and bending moment, respectively. The results showed that S2 was superior to that of the Seomoon Weir fishway, and the underground passage size of 1.4 m × 0.3 m was superior to those of 1.4 m × 0.2 m and 1.4 m × 0.6 m, and R/C+S/C slab was superior to that of R/C slab. The findings are expected to be useful for constructing and designing the multifunctional fishway.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.531-540
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• 2021

As cyber attacks and crimes increase exponentially and hacking attacks become more intelligent and advanced, hacking attack methods and routes are evolving unpredictably and in real time. In order to reinforce the enemy's responsiveness, this study aims to propose a method for developing an artificial intelligence-based security control platform by building a next-generation security system using artificial intelligence to respond by self-learning, monitoring abnormal signs and blocking attacks.The artificial intelligence-based security control platform should be developed as the basis for data collection, data analysis, next-generation security system operation, and security system management. Big data base and control system, data collection step through external threat information, data analysis step of pre-processing and formalizing the collected data to perform positive/false detection and abnormal behavior analysis through deep learning-based algorithm, and analyzed data Through the operation of a security system of prevention, control, response, analysis, and organic circulation structure, the next generation security system to increase the scope and speed of handling new threats and to reinforce the identification of normal and abnormal behaviors, and management of the security threat response system, Harmful IP management, detection policy management, security business legal system management. Through this, we are trying to find a way to comprehensively analyze vast amounts of data and to respond preemptively in a short time.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.77-87
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• 2021

Smart Factory refers to a factory that can be controlled by itself with an intelligent factory that improves productivity, quality and customer satisfaction by combining the entire process of manufacturing and production with digital automation solutions. The manufacturing industry around the world is rapidly changing, with Germany, Europe, and the United States at the center. In order to cope with such changes, the Korean government is also implementing a policy to spread the supply of smart factories for small and medium-sized companies, and related ministries and agencies such as the Ministry of Commerce, Industry and Energy, the Ministry of SMEs and Venture Business, the Korea Institute of Technology and Information Promotion, and local technoparks, as well as large companies such as Samsung, SK and LG are actively investing in smart manufacturing projects to support smart factories[1]. Factory Automation (FA) construction has many issues regarding the connection of heterogeneous equipment. The most difficult aspect of configuring various communications from various equipment is the reason. Although it may not be known if there are standards or products made up of the same company, it is not easy to build equipment that is old, up-to-date, and different use environments through a series of communications. To solve this problem, we would like to propose a method of communication using Modbus, one of FieldBus, which is one of the many industrial devices of PLC, a representative facility control system, and is used as a communication standard.

• Journal of the Korean Geosynthetics Society
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• v.20 no.4
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• pp.1-7
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• 2021

In response to the carbon emission reduction trends and the depletion of natural sand caused by the use of cement in construction works, graphene oxide and porous feldspar were applied as countermeasures in this study. By using (3-aminopropyl)trimethoxysilane-functionalized graphene oxide with enhanced bond characteristics, a concrete specimen was prepared with 5% less cement content than that in a standard mortar mix, and the compressive strengths of the specimens were examined. The compressive strengths of the specimen with (3-aminopropyl)trimethoxysilane-functionalized graphene oxide and porous feldspar and the specimen with standard mixing were 26MPa and 28MPa, respectively, showing only a small difference. In addition, both specimens met the compressive strength of cement mortar required for geotechnical structures. It is believed that a reasonable level of compressive strength was maintained in spite of the lower cement content because the high content of pozzolans, namely SiO₂ and Al₂O₃, in the porous feldspar enhanced the reactions with Ca(OH)₂ during hydration, the nano-sized graphene surface acted as a reactive surface for the hydration products to react actively, and the strong covalent bonding of the carboxyl functional group increased the bonding strength of the hydration products.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.43-57
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• 2022

In this paper, we propose a method of analyzing research papers published by researchers belonging to university departments in the field of disaster & safety for the scientometric analysis of the research status in the field of disaster safety. In order to conduct analysis research, the dataset constructed in previous studies was newly improved and utilized. In detail, for research papers of authors belonging to the disaster prevention and safety engineering type department of domestic universities, institution identification, cited journal identification of references, department type classification, disaster safety type classification, researcher major information, KSIC(Korean Standard Industrial Classification) mapping information was reflected in the experimental data. The proposed method has a difference from previous studies in the field of disaster & safety and data set based on related keyword searches. As a result of the analysis, the type and regional distribution of organizations belonging to the department of disaster prevention and safety engineering, the composition of co-authored department types, the researchers' majors, the status of disaster safety types and standard industry classification, the status of citations in academic journals, and major keywords were identified in detail. In addition, various co-occurrence networks were created and visualized for each analysis unit to identify key connections. The research results will be used to identify and recommend major organizations and information by disaster type for the establishment of an intelligent crisis warning system. In order to provide comprehensive and constant analysis information in the future, it is necessary to expand the analysis scope and automate the identification and classification process for data set construction.

• Environmental and Resource Economics Review
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• v.31 no.4
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• pp.801-824
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• 2022

Recently, United Nations found that 38% of global carbon emissions are generated in the building sector, surpassing other industries (32%) and transportation (23%), and ESG is actively used as a way to reduce carbon emissions in the building sector, led by overseas advanced countries. In Korea, as the National Pension Service announced "Consider ESG with more than 50% of investment assets" this year, the move to introduce ESG in the building sector is accelerating, centering on construction companies and asset management companies. However, as the domestic ESG evaluation system is still mainly focused on corporate governance and social responsibility, interest in the environmental sector is lagging behind that of advanced countries. As ESG in the building sector is expected to grow rapidly over the next 10 years, I would like to suggest the following development directions. The first is the expansion of the incentive system. In order for the government to successfully implement policies related to ESG in the building sector, incentive system such as tax reduction and building standards should be expanded further than now in addition to negative systems such as rent restrictions and punishment taxes due to regulatory violations. Second, standardized ESG standards are established. Rather than creating an independent Korean ESG standard that is far from global standards, it is necessary to organize the common parts of global standards and evaluation methods and create and provide guidelines in the form of standard textbooks that can be used equally by all stakeholders. Third, it is an effort to link ESG in the building sector with Digital Transformation(DX). This is because actual energy savings and carbon emission reduction can be realized only when the operation method of the building sector, which is operated mainly by manpower, is digitalized and converted to an intelligent way.

• Convergence Security Journal
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• v.22 no.4
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• pp.85-97
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• 2022

With the development of big data technology, data is rapidly entering a hyperconnected intelligent society that accelerates innovative growth in all industries. The convergence industry, which holds and utilizes various high-quality data, is becoming a new growth engine, and big data is fused to various traditional industries. In particular, in the medical field, structured data such as electronic medical record data and unstructured medical data such as CT and MRI are used together to increase the accuracy of disease prediction and diagnosis. Currently, the importance and size of unstructured data are increasing day by day in the medical industry, but conventional data security technologies and policies are structured data-oriented, and considerations for the security and utilization of unstructured data are insufficient. In order for medical treatment using big data to be activated in the future, data diversity and security must be internalized and organically linked at the stage of data construction, distribution, and utilization. In this paper, the current status of domestic and foreign data security systems and technologies is analyzed. After that, it is proposed to add unstructured data-centered de-identification technology to the guidelines for unstructured data and technology application cases in the industry so that unstructured data can be actively used in the medical field, and to establish standards for judging personal information for unstructured data. Furthermore, an object feature-based identification ID that can be used for unstructured data without infringing on personal information is proposed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.391-393
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• 2022

In recent years, technologies forecasting demand based on deep learning and big data have accelerated the smartification of the field of e-commerce, logistics and distribution areas. In particular, ports, which are the center of global transportation networks and modern intelligent logistics, are rapidly responding to changes in the global economy and port environment caused by the 4th industrial revolution. Port traffic forecasting will have an important impact in various fields such as new port construction, port expansion, and terminal operation. Therefore, the purpose of this study is to compare the time series analysis and deep learning analysis, which are often used for port traffic prediction, and to derive a prediction model suitable for the future container prediction of Busan Port. In addition, external variables related to trade volume changes were selected as correlations and applied to the multivariate deep learning prediction model. As a result, it was found that the LSTM error was low in the single-variable prediction model using only Busan Port container freight volume, and the LSTM error was also low in the multivariate prediction model using external variables.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.29-40
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• 2024

Recently, the technology of autonomous driving, one of the core of the fourth industrial revolution, is developing, but sensor-based autonomous driving is showing limitations, such as accidents in unexpected situations, To compensate for this, HD-map is being used as a core infrastructure for autonomous driving, and interest in the public and private sectors is increasing, and various studies and technology developments are being conducted to secure the latest and accuracy of HD-map. Currently, NGII will be newly built in urban areas and major roads across the country, including the metropolitan area, where self-driving cars are expected to run, and is working to minimize data error rates through quality verification. Therefore, this study analyzes the spatial relationship of reference objects in the attribute structuring process for rapid and accurate renewal and production of HD-map under construction by NGII, By applying the attribute input automation methodology of the reference object in which spatial relations are established using the library of open source-based PyQGIS, target sites were selected for each road type, such as high-speed national highways, general national highways, and C-ITS demonstration sections. Using the attribute automation tool developed in this study, it took about 2 to 5 minutes for each target location to automatically input the attributes of the spatial relationship reference object, As a result of automation of attribute input for reference objects, attribute input accuracy of 86.4% for high-speed national highways, 79.7% for general national highways, 82.4% for C-ITS, and 82.8% on average were secured.