• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.289-294
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• 2021

With the development of artificial intelligence, a wave of the 4th industrial revolution is taking place around the world. With the technologies such as big data and Internet of Things-based artificial intelligence, we are heading to a hyper-connected society where everything converges into one. Accordingly as educational talents in the era of artificial intelligence, we are pursuing the cultivation of creative convergence-type talents and emotional creative talents. With human creativity and emotion at the center, we should be able to collaborate with artificial intelligence and create new things by converging knowledge in various fields. By developing a program that combines humanities-oriented Korean language with engineering-oriented artificial intelligence, this research attempted to help students experience solving problems creatively by combining humanistic knowledge with engineering thinking skills. The educational program consists of two kinds of contents(i.e., "Books with AI" and "A Play with AI") and 15 classes that provide students with opportunities to solve humanities problems with artificial intelligence.

• Journal of the Korea Convergence Society
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• v.7 no.6
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• pp.249-258
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• 2016

In this research, we analyzed the research and development process of small and medium enterprises, and diagnosed the problem of the research and development process of domestic small and medium enterprises, and evaluated the influence of innovative ability on the speed of research and development and corporate performance. In evaluating these effects, it is possible to grasp the direction of power generation according to the type of analysis, taking into account the meltdown factor of factors related to innovative capabilities. The main purpose of this research is to confirm the influence on the speed of research and development according to the innovative capacity and business environment and to verify the reliability and validity of the research by Klumbach alpha Was used. In this research, we analyzed how the speed of R & D affects R & D activities, it is a research aimed at the necessity of a resource-based approach to the internal capacity of a company, Have a valuable value. Based on the influence on the company, each factor is a research that analyzed the influence on R & D and financial indicators through maintaining company's development level, Research that has practical value that can base on the development of R & D capacity on corporate strategy formulation.

• Journal of Environmental Impact Assessment
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• v.22 no.3
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• pp.195-201
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• 2013

Local governments are establishing their own greenhouse gas reduction goal and are playing a important role to respond to climatic changes. However, there are difficulties in quantitative analyses such as estimation of future greenhouse gas emission and computation of reduction potential, which are procedures required to establish mid to long term strategies to realize of low carbon society by each local governments. Also, reduction measures must reflect characteristics of each local government, since the reduction power of each local government can differ according to characteristics of each. In order to establish strategies that reflect characteristics of local governments, types of greenhouse gas emission from cities were classified largely into residential city, commercial city, residential commercial city, agriculture and fishery city, convergence city, and industrial city. As a result of analyzing basic unit of greenhouse gas emission by local government during 2007 in terms of per population, household and GRDP based on the type classification, significant results were deduced for each type. To manage the amount of the national greenhouse gas, reduction measures should be focused on the local governments that emits more than the average of each type's GHG emission.

• Fashion & Textile Research Journal
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• v.25 no.5
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• pp.560-567
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• 2023

This study aims to rediscover the industrial value of a borderless service in the hyper-connected era by producing fashion content at the forefront of the cultural industry as XR content and contributing to developing fashion content for edutech. The research method employed design aesthetic theory, while the empirical proposal utilized scientific knowledge information to build a framework for 3D convergence content. The characteristics of fashion content exhibitions that apply the neumorphism technique are as follows: The first is a virtual space that produces clothing culture by type. Africa, where dyeing and crafts are developed, selects a product-oriented exhibition type; Asia, where weaving and textiles are excellent, selects a random movement type; and Europe, where the evolution of clothing design over time is evident, selects a guided movement type to create a three-dimensional fashion edutech. The goal was to produce content. The second is creative reproducibility, which combines a new fashion design that embraces the aura of the original with a trendy sense. The realistic folk costume style of the original allowed for its implementation in the AR exhibition space using historical traditional style techniques such as weaving and textiles. The third is building organic, modular content. By designing and then saving/editing/arranging the basic VP zone for each style, learners and instructors can freely edit the content for each fashion class topic and create various presentations to ensure that it functions as non-face-to-face edutech content around the world.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.209-214
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• 2017

Most of the present potential transformers of train vehicles are of the oil-type filled with insulating oil and are susceptible to problems such as explosion due to the increase in the internal pressure during train operation and poor reliability near the end of their life cycle. As a solution to this problem, it is necessary to develop a molded dry-type potential transformer with excellent pressure-resistance performance using insulating resin. In order to localize the product, the Korea Railroad Research Institute has been developing a molded dry-type potential transformer. As part of this research, it is necessary to analyze the vibration characteristics of the developed product and to check the transformer performance in a vibration environment. In this study, a resonance test and simulated long-term life test of the developed product were conducted according to the KS R 9144 and IEC 61373 standards, respectively, which are vibration test methods for railway vehicle parts. Their natural frequencies were analyzed by comparing the results of the numerical modal analysis and resonance test, in order to confirm their adherence to the standards. Also, the performance test after the simulated long-term life test confirmed that the operation of the developed transformer was not problematic even in a long-time vibration environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.12
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• pp.511-517
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• 2016

Current oil-type potential transformers for trains are filled with insulating oil, which could have problems like explosions due to rising inner pressure during train operation. Therefore, mold and dry-type potential transformers are being developed to prevent explosions. One problem in manufacturing mold-type transformers is preventing void formation around the coiled core inside the mold during epoxy filling, which could cause an electrical spark. Micro voids can remain in the resin after filling, and macro voids can occur due to the structure shape. A transformer that is being developed has a cavity at the junction of the core and the coil for better performance, and when highly viscous epoxy flows inside the cavity channel, macro voids can form inside it. Therefore, in this study, the free-surface flow of the mold filling procedure was analyzed numerically by applying the VOF method. The results were used to understand the phenomena of void formation inside the cavity and to modify the process conditions to reduce voids.

• 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.

• Journal of Advanced Navigation Technology
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• v.21 no.2
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• pp.171-178
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• 2017

In this paper, in order to verify the performance of a localization algorithm using GPS as an auxiliary sensor, the algorithm was applied to a hovering-type autonomous underwater vehicle (AUV) to perform a field test. The applied algorithm is an algorithm to improve the accumulated positional error of dead reckoning using doppler velocity logger(DVL) and tilt-compensated compass module (TCM) mounted on the AUV. GPS when surfaced helps the algorithm to estimate the position and the heading bias error of TCM for geodetic north, which makes it possible to perform dead reckoning on north-east-down (NED) coordinates. As a result of field test performing heading control, it was judged that the algorithm could improve the positional error, enhance the operational capability of AUV and contribute to the research of underwater navigation depending on a magnetic compass.

• Journal of Industrial Convergence
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• v.20 no.3
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• pp.33-40
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• 2022

Recently, IoT-linked services have been used in various environments, and IoT and artificial intelligence technologies are being fused. However, since technologies that process IoT data stably are not fully supported, research is needed for this. In this paper, we propose a processing technique that can optimize IoT data after generating embedded vectors based on machine learning for IoT data. In the proposed technique, for processing efficiency, embedded vectorization is performed based on QR such as index of IoT data, collection location (binary values of X and Y axis coordinates), group index, type, and type. In addition, data generated by various IoT devices are integrated and managed so that load balancing can be performed in the IoT data collection process to asymmetrically link IoT data. The proposed technique processes IoT data to be orthogonalized based on hash so that IoT data can be asymmetrically grouped. In addition, interference between IoT data may be minimized because it is periodically generated and grouped according to IoT data types and characteristics. Future research plans to compare and evaluate proposed techniques in various environments that provide IoT services.

• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1213-1216
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• 2017

Recently due to the increasing uncertainty of the disaster environment caused by climate change the effects of disasters have become larger due to the confluence and solidification diversification into disaster type and secondary damage. In this paper, we apply ICBMS through intelligent information technology and big data analysis to all processes of disaster safety management to minimize human, social, economic and environment damage from accidents or disasters, and prevention by control technology preparation by education and training expansion to remember by body, response by advanced technology of disaster response unmanned technology restoration by creation of local community environment ecosystem, investigation and analysis by intelligent information technology learn about disaster safety management 4.0. In addition, technical limitation and problems in the $4^{th}$ industrial revolution and the application of big data were analyzed and suggested alternatives and strategies to overcome.