• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.577-582
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• 2021

Recently, with the development of AR, VR, and smart device technologies, the demand for services based on non-face-to-face environments is also increasing in the fitness industry. The non-face-to-face online home training service has the advantage of not being limited by time and place compared to the existing offline service. However, there are disadvantages including the absence of exercise equipment, difficulty in measuring the amount of exercise and chekcing whether the user maintains an accurate exercise posture or not. In this study, we develop a standard exercise program that can compensate for these shortcomings and propose a new non-face-to-face home training application by using a deep learning-based body posture estimation image processing algorithm. This application allows the user to directly watch and follow the trainer of the standard exercise program video, correct the user's own posture, and perform an accurate exercise. Furthermore, if the results of this study are customized according to their purpose, it will be possible to apply them to performances, films, club activities, and conferences

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.308-317
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• 2022

Researches are underway to efficiently reduce the size of video data transmitted and stored in the image analysis process using deep learning-based machine vision technology. MPEG (Moving Picture Expert Group) has newly established a standardization project called VCM (Video Coding for Machine) and is conducting research on video encoding for machines rather than video encoding for humans. We are researching a multitask that performs various tasks with one image input. The proposed pipeline does not perform all object detection of each task that should precede object detection, but precedes it only once and uses the result as an input for each task. In this paper, we propose a pipeline for efficient multitasking and perform comparative experiments on compression efficiency, execution time, and result accuracy of the input image to check the efficiency. As a result of the experiment, the capacity of the input image decreased by more than 97.5%, while the accuracy of the result decreased slightly, confirming the possibility of efficient multitasking.

• Knowledge Management Research
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• v.23 no.1
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• pp.47-67
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• 2022

Computer and Internet information technologies(ICTs) have changed the modern service industry and people's life style. In particular, the global spread of COVID-19 has attracted more attention to contact service types such as self-service technology. With the increase in labor costs and the enhancement of consumer self-awareness, more and more companies transfer part of their work to customers through their own service technology. This study seeks to answer the following questions. (1) Do technology difficulty and safety perception affect customer value recognition in the self-service technologies? (2) Does customer value recognition influence the intention to use such technologies continuously? This study conducted an empirical analysis with 327 samples to validate the influence of self-service characteristics(technology difficulty and safety perception) on customer value recognition and continuous utilization intentions. Also, it analyzes the moderating effects of age and frequency of use on the relationship between self-service characteristics and customer value recognition. The study results show that the technology difficulty does not affect the customer's perceived value recognition; and the higher the customer's value recognition, the higher the intention of continuous use.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.69-77
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• 2022

Physical experiment through MBL has been used in many schools for a long time since students can check the experiment results immediately and conduct the experiment easily. However, conducting the experiment, not knowing the principle of the device or simply concentrating on the derived data has been raised as the problem of MBL experiment. To supplement this problem, this study measured the acceleration of gravity with the picket fence method, which is often used in MBL experiment, utilizing Arduino, calculated the error rate through a comparison to the actual acceleration of gravity and discussed the educational application of the experiment to measure it. As a result of the experiment, the error rate between the acceleration of gravity calculated by the experiment and the actual acceleration of gravity was about 1%, so it turned out that relatively accurate measurements were possible. Also, the sample mean of the experimental value was included in the confidence interval of 95%, so it could be concluded that it was a significant experiment. In addition, this study showed the possibility of the educational application of the experiment to measure it through the following: It can supplement the structural disadvantages of MBL; it can consider the interaction between Physics and Math; it is possible to converge with information course in STEAM education; and it is inexpensive to be equipped with the equipment. Hopefully, the physical experiment utilizing Arduino will further be revitalized in science gifted education based on this study.

• Journal of Industrial Convergence
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• v.20 no.1
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• pp.53-62
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• 2022

The election broadcast began utilizing virtual studios in the mid-1990s. In 1996, SBS's virtual studio was evaluated as an innovation in Korean broadcasting technology that introduced the world's first virtual studio. However, there have been cases where KBS and MBC named it a virtual studio and used it for election broadcasting. Various CG (Computer Graphics) case studies of election broadcasting have been conducted since the 2000s, but the initial research is inadequate. Therefore, this paper complements existing research by analyzing the cases of the mid-1990s when they actually started using virtual studios. Beginning with SMOCKEY (KBS) and MAGICII (MBC) in 1995, we presented the initial model of the virtual studio, and then with SBS Virtual Studio, each broadcasting company evolved into the names Dream Studio (KBS) and Space 21 Studio (MBC). As a result of the analysis, it was found that the election broadcast is a chart showing the data and the winning prediction, and that the election broadcast was the trigger to compose the story based on the introduction of the virtual studio. It is a form of historical research dealing with the value of the early virtual studios in this paper. It is meaningful to see the process of Remediation.

• 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.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.143-148
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• 2022

The subject of this paper is the practical examples of technoculture that critically thinks network technology, a strong material foundation in the era of data capitalism in the 21st century, and appropriates its socio-cultural metaphor as an artistic potential. In order to analyze its alternatives and the meaning of cultural politics, this paper examines the properties and influence of data capitalism after the 2008 global financial crisis, and the cultural and artistic context formed by its reaction. The first case considered in this paper, Furtherfield's workshop, provided a useful example of how citizens can participate in social change through learning and education in which art and technology are interrelated. The second case, Greek hackerspace HSGR, developed network technology as a tool to overcome the crisis by proposing a new progressive cultural commons due to Greece's financial crisis caused by the global financial crisis and a decrease in the state's creative support. The third case, Paolo Cirio's project, promoted a critical citizenship towards the state and community systems as dominant types of social governance. These technoculture cases can be evaluated as efforts to combine and rediscover progressive political ideology and its artistic realization tradition in the context of cultural politics, paying attention to the possibility of signifying practices of network technology that dominates the contemporary economic system.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.654-664
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• 2022

Immersive content overcomes spatial limitations through convergence with extended reality, artificial intelligence, and photogrammetry technology along with interest due to the COVID-19 pandemic, presenting a new paradigm in the content market such as entertainment, media, performances, and exhibitions. However, it can be seen that in order for realistic content to have sustained public interest, it is necessary to study storytelling method that can increase immersion in content rather than technological freshness. Therefore, in this study, we propose a immersive content storytelling method using artificial intelligence and photogrammetry technology. The proposed storytelling method is to create a content story through interaction between interactive virtual beings and participants. In this way, participation can increase content immersion. This study is expected to help content creators in the accelerating immersive content market with a storytelling methodology through virtual existence that utilizes artificial intelligence technology proposed to content creators to help in efficient content creation. In addition, I think that it will contribute to the establishment of a immersive content production pipeline using artificial intelligence and photogrammetry technology in content production.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.323-332
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• 2022

As various services using AI technology are being developed, much attention is being paid to AI service production. Recently, AI technology is acknowledged as one of ICT services, a lot of research is being conducted for general-purpose AI service production. In this paper, I describe the research results in terms of systems for AI service production, focusing on the distribution and production of machine learning models, which are the final steps of general machine learning development procedures. Three different Ubuntu systems were built, and experiments were conducted on the system, using data from 2017 validation COCO dataset in combination of different AI models (RFCN, SSD-Mobilenet) and different communication methods (gRPC, REST) to request and perform AI services through Tensorflow serving. Through various experiments, it was found that the type of AI model has a greater influence on AI service inference time than AI machine communication method, and in the case of object detection AI service, the number and complexity of objects in the image are more affected than the file size of the image to be detected. In addition, it was confirmed that if the AI service is performed remotely rather than locally, even if it is a machine with good performance, it takes more time to infer the AI service than if it is performed locally. Through the results of this study, it is expected that system design suitable for service goals, AI model development, and efficient AI service production will be possible.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.562-569
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• 2022

The alarm monitoring technology applied to existing operating ships manages data items such as temperature and pressure with AMS (Alarm Monitoring System) and provides an alarm to the crew should these sensing data exceed the normal level range. In addition, the maintenance of existing ships follows the Planned Maintenance System (PMS). whereby the sensing data measured from the equipment is monitored and if it surpasses the set range, maintenance is performed through an alarm, or the corresponding part is replaced in advance after being used for a certain period of time regardless of whether the target device has a malfunction or not. To secure the reliability and operational safety of ship engine operation, it is necessary to enable advanced diagnosis and prediction based on real-time condition monitoring data. To do so, comprehensive measurement of actual ship data, creation of a database, and implementation of a condition diagnosis monitoring system for condition-based predictive maintenance of auxiliary equipment and piping must take place. Furthermore, the system should enable management of auxiliary equipment and piping status information based on a responsive web, and be optimized for screen and resolution so that it can be accessed and used by various mobile devices such as smartphones as well as for viewing on a PC on board. This update cost is low, and the management method is easy. In this paper, we propose CBM (Condition Based Management) technology, for autonomous ships. This core technology is used to identify abnormal phenomena through state diagnosis and monitoring of pumps and purifiers among ship auxiliary equipment, and seawater and steam pipes among pipes. It is intended to provide performance diagnosis and failure prediction of ship auxiliary equipment and piping for convergence analysis, and to support preventive maintenance decision-making.