• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.391-404
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• 2022

Actor-network theory (ANT) pays attention to the relational effect between human and non-human actors, and transforms numerous networks between these actors by treating non-humans as human-like actors. This paper investigated various non-human actors related to the context before and after the introduction of NCS-based curriculum through ANT. This approach is because as a new system is introduced, the impact on the existing network and conflict situations can be looked at more closely. To this end, the researcher reviewed data from October 2014, when S College discussed whether to introduce an NCS-based curriculum, to February 2017, when practical operation was carried out and graduates were produced. In order to understand ANT theory, we analyzed based on the four stages of translation as claimed by Callon in the ANT theory. As a result, some meanings were confirmed in the case of reforming the curriculum of S College where the NCS-based curriculum was introduced. First, it is an in-depth analysis of the situation surrounding the curriculum, which has been overlooked by research on the existing curriculum. Second, it contributed to interpreting the 'hidden meaning' beyond the 'superficial meaning' of the curriculum within the university. Third, it was possible to indirectly check the conflicts and conflicts with the existing system that appeared in the process of introducing the new system to the College.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.119-133
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• 2022

Due to the improvement of surveying, mapping and communication techniques, various apps for road direction guides and vehicle navigations have been developed. Although such a development has impacted on walking and driving, there is a limit to improving the daily convenience of the socially impaired people. This is mainly due to the fact that the software have been developed for normal pedestrians and drivers. Therefore, visually impaired people still have problems with the confusion of direction and/or non-provision of risk factors in walking. This study aimed to propose a scheme which constructs data for mobility-impaired or traffic-impaired people based on various geospatial information. The factors and components related to walking for the visually impaired are selected by geospatial data and a walking route guidance network that can be applied to a commercial software. As a result, it was confirmed that road direction guidance would be possible if additional contents, such as braille blocks (dotted/linear), sound signals, bus stops, and bollards are secured. In addition, an initial version of the application software was implemented based on the suggested data model and its usefulness was evaluated to a visually impaired person. To advance the stability of the service in walking for the visually impaired people, various geospatial data obtained by multiple institutes are necessary to be combined, and various sensors and voice technologies are required to be connected and utilized through ICT (Information and Communications Technologies) technology in near future.

• Smart Media Journal
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• v.11 no.3
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• pp.39-53
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• 2022

Cloud of Things (CoT) can provide IoT applications with unlimited storage functions and processing power supported by cloud services. However, in a centralized cloud of things, it can create a single point of failure that can lead to bottleneck problems, outages of the CoT network. In this paper, to solve the problem of centralized cloud of things and interoperate between different service domains, we propose an IoT service interoperability system using distributed fog computing and blockchain technology. Distributed fog is used to provide real-time data processing and services in fog systems located at a geographically close distance to IoT devices, and to enable service interoperability between each fog using smart contracts and distributed ledgers of the blockchain. The proposed system provides services within a region close to the distributed fog entrusted with the service from the cloud, and it is possible to access the services of other fogs without going through the cloud even between fogs. In addition, by sharing a service right token issuance information between the cloud and fog nodes using a blockchain network, the integrity of the token can be guaranteed and reliable service interoperability between fog nodes can be performed.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.57-65
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• 2021

A hyper-connected intelligence information society is emerging that creates new value by converging IoT, AI, and Bigdata, which are new technologies of the fourth industrial revolution, in all industrial fields. Everything is connected to the network and data is exploding, and artificial intelligence can learn on its own and even intellectual judgment functions are possible. In particular, the Internet of Things provides a new communication environment that can be connected to anything, anytime, anywhere, enabling super-connections where everything is connected. Artificial intelligence technology is implemented so that computers can execute human perceptions, learning, reasoning, and natural language processing. Artificial intelligence is developing advanced technologies such as machine learning, deep learning, natural language processing, voice recognition, and visual recognition, and includes software, machine learning, and cloud technologies specialized in various applications such as safety, medical, defense, finance, and welfare. Through this, it is utilized in various fields throughout the industry to provide human convenience and new values. However, on the contrary, it is time to respond as intelligent and sophisticated cyber threats are increasing and accompanied by potential adverse functions such as securing the technical safety of new technologies. In this paper, we propose a new data modeling method to enable IoT integrated security control by utilizing artificial intelligence technology as a way to solve these adverse functions.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.794-807
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• 2022

Although registration of dogs is mandatory according to the revision of the Animal Protection Act, the registration rate is low due to the inconvenience of the current registration method. In this paper, a performance improvement study was conducted on the dog face recognition technology, which is being reviewed as a new registration method. Through deep learning learning, an embedding vector for facial recognition of a dog was created and a method for identifying each dog individual was experimented. We built a dog image dataset for deep learning learning and experimented with InceptionNet and ResNet-50 as backbone networks. It was learned by the triplet loss method, and the experiments were divided into face verification and face recognition. In the ResNet-50-based model, it was possible to obtain the best facial verification performance of 93.46%, and in the face recognition test, the highest performance of 91.44% was obtained in rank-5, respectively. The experimental methods and results presented in this paper can be used in various fields, such as checking whether a dog is registered or not, and checking an object at a dog access facility.

• Journal of Dairy Science and Biotechnology
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• v.40 no.2
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• pp.57-65
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• 2022

This study was conducted to evaluate the potential use of milk mineral (MM) as the calcium source for the production of calcium-fortified yogurt. MM was composed of 83% minerals, 7.5% lactose, 3.3% protein, and < 1% fat. Calcium (Ca) content in MM was about 46%; calcium: phosphorous ratio was 1.28:1. The aqueous solubility of Ca increased with the decrease in pH; the solubility at pH 4 and 5 was 98% and 53%, respectively. Ca-fortified yogurt with up to 200 mg Ca/100 mL did not show significant differences in acid production and number of viable cells; however, the viscosity increased significantly (p<0.05) with the increase in Ca levels. Microstructure analysis of Ca-fortified yogurt using confocal scanning laser microscopy indicated that the protein network became denser with increasing fortification with MM. There was no significant difference in the sensory quality between the control and Ca-fortified yogurts. Therefore, MM could be used for the production of Ca-fortified yoghurt without compromising the quality characteristics of yogurt.

• Journal of Korean Home Economics Education Association
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• v.33 no.2
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• pp.1-25
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• 2021

The purpose of this paper is to explore ways to prepare for the high school credit system in the home economics educational community through the case of high school credit system research school operation. To this end, the operation process of H high school in Gangwon-do, which operated a high school credit system in 2019, was monitored for 5 months, and surveys and interviews were conducted with students, parents, and teachers to determine the operation of the curriculum. Suggestions based on the case of H high school's operation of the high school credit system for home economics educational community are as follows. Home economics teachers should make active efforts to provide attractive and meaningful home economics lessons to their students by improving instruction and assessment, and implementing a variety of elective courses within the subject of home economics, including collaborative online curricula. Home economics teacher communities and related associations should build a solid network that connects local home economics subject research groups, share information related to curriculum operation, and use it as a channel for disseminating class research results. Home economics teacher training institutions should innovate the curriculum to help prospective teachers develop the ability to guide multiple classes in line with the changing teacher training policy, and develop and provide high-quality online and offline programs for field teacher re-education.

• Journal of the Society of Disaster Information
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• v.17 no.1
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• pp.165-175
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• 2021

Purpose: The purpose of this study is to quantitatively present the carbon dioxide(CO₂) emission change according to the application of autonomous driving technology at the network level for waste vehicles in the metropolitan area. Method: The target year was set to 2030, and the analysis method estimated the carbon dioxide (CO₂) emissions for each road link through user equilibrium assignment when unapplied scenario. The application scenario performed traffic assignment using route data on the premise that the group was running in accordance with the application of autonomous driving technology to waste vehicles. In addition, the other means estimated the carbon dioxide emissions through user balance allocation by reflecting the results of the waste vehicle allocation. Result: As a result of the analysis, carbon dioxide(CO₂) emissions were found to be reduced by about 56.9ton/day from the national network level, and the Seoul metropolitan area was analyzed to be reduced by about 54.7ton/day. Conclusion: This study quantitatively presented environmental impacts among various social effects that autonomous driving technology will bring, and in the future, development of various analytical methodologies and related studies should be continuously conducted.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.537-542
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• 2021

This paper improves the possibility of recognizing fast-moving objects through the YOLO (You Only Look Once) deep learning recognition model in an application environment for object recognition in images. The purpose was to study the method of collecting semantic data through processing. In the recognition model, the moving object recognition error was identified as unrecognized because of the difference between the frame rate of the camera and the moving speed of the object and a misrecognition due to the existence of a similar object in an environment adjacent to the object. To minimize the recognition errors by compensating for errors, such as unrecognized and misrecognized objects through the proposed data collection method, and applying vision processing technology for the causes of errors that may occur in images acquired for sports (tennis games) that can represent real similar environments. The effectiveness of effective secondary data collection was improved by research on methods and processing structures. Therefore, by applying the data collection method proposed in this study, ordinary people can collect and manage data to improve their health and athletic performance in the sports and health industry through the simple shooting of a smart-phone camera.

• Korean small business review
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• v.42 no.3
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• pp.275-304
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• 2020

The purpose of this study is to present implications for revitalizing start-ups and contribute to enhancing the success rate of start-ups by clarifying factors and processes for converting workers with knowledge, experience and networks in related fields into entrepreneur. Based on the Shapero's Entrepreneurial Event Model, this study demonstrated whether the job insecurity and entrepreneurship of the workers were precipitating events of the entrepreneurial intention and whether the perceived desirability and feasibility of the entrepreneurial behaviour mediated between them. According to the results of the study, first, it was confirmed that job insecurity, innovativeness, and risk-taking of workers are factors that increase the entrepreneurial intention. Second, the indirect effect of perceived desirability between all components of job insecurity and entrepreneurial intentions was not significant, but all components of entrepreneurship appeared to improve entrepreneurial intention through perceived desirability. Third, it has been confirmed that job insecurity, innovativeness, and risk-taking strengthen the entrepreneurial intention through the perception of feasibility for entrepreneurial behavior. Through this study, it is confirmed that in order to convert workers into entrepreneur, it is necessary to strengthen entrepreneurship education and support for internal ventures for workers to increase their positive attitude and confidence in implementation. Therefore, it is expected to help solve job problems and revive the sluggish economy by contributing to boosting start-ups.