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The Gwangju Daein Art Market, once declared as a declined market, was regarded as a success after an inflow of artists. However, the number of resident artists decreased from 100 at the end of 2015 to 39, to 9 in 2018, and to 6 in 2021. The project site showed signs of decline toward the completion of the project, leading to a Longitudinal study on the project’s sustainability. The purpose of this study is to investigate the causes of outflow of artists and the network characteristics of the remaining artists from a sustainability perspective and thereby draw policy implications. As an analysis method, in-depth interviews and surveys were conducted. After that, we checked the remaining artists in 2018 and 2021 and identified the network characteristics. Based on the interview results, the causes of outflow were classified into programmatic, physical, and other factors. The results of a comparison showed that the levels of understanding, satisfaction, and frequency of exchange decreased. The study also provides policy implications. First, a sustainable, long-term program for the artists must involve the improvement of physical space. Second, participation in the market should be encouraged by working with artists on program composition or business progress. Third, programs for supporting exchange among artists should be further strengthened.

This study aims to expose the potential dangers of K-pop through the past and present of K-pop choreography copyrights and to suggest the need to secure digital choreography copyrights for the sustainability of K-pop considering national responsibility. As the content industry quickly sought countermeasures to digital transformation, such as the launch of K-pop platforms and the evolution of OMO (Online Merges with Offline) media commerce in response to changes in the industrial environment due to COVID-19, the annual export of the domestic content industry increased by 6.3% compared to the previous year. Accordingly, our copyright does not require that works be fixed in tangibles, as in Japan and Germany, on the basis of entrusting each country's legislation to determine whether to require fixation on choreographed works. On the other hand, the United States, France and the United Kingdom are demanding that it be fixed. Although choreography is at the center of K-pop and the value and influence of K-pop videos including cover dance through new media are discussed from various perspectives, copyright on choreography that needs to be resolved in business platforms for K-pop scalability The fact that there is such a big difference in problem perception is an area where we must not lose our vigilance. As the development of today's technology, the method of fixing a choreography looks very easy as an image, but at the same time can be stolen very quickly. Therefore, compared to overseas cases, it is urgent to improve the difference in perception of copyright registration for K-pop choreography and to supplement the system include the NFT.

In modern socity, online communication plays a vital role in social interaction of communicities. It is so common for online users to see display advertisements online while surting the Net. Specifically, most web banners diaplayed on portral sites consist of words, phrase, and sentences. Considering that the primary purpose of adversiting is persuation, the advertisement such as web banners is an examplary case to show the interaction among pragmatics, translation and advertising because the linguistic expressions employed in the banners represent its pragmatic use, leading to persuation and functioning as a communicative tool for the smooth communication between source text producers (adversisers) and target audience (online users). This can be part of the so-called translation process. In particular, we can easily witness the use of English words in web banners. Thus, this paper looks at web banners displayed on major four portal sites-Naver, Daum, Nate, and Zum, giving a special attention to the content contained in the web banners as well as the use of English words. As s result, we found that the frequencies of English words in each portal site were higher when the advertised products were targeting young online users, whereas the frequencies were lower when the users are older group than young people. The finding supports the prgramatic perspective that linguistic expressions are understood in social contexts and shows the so-called translation process which involves a shift from semantic meaning of words to their pragmatic use. Finally, we can conclude that the interaction is possible when we have the framework where translation, pragmatics, and advertising are all communitative components for social interaction within social contexts.

VR and AR contents provide a rich user experience [1]. Realistic content with human computer interaction and immersion provides an improved user experience, but there is a limit to producing all elements realistically. In this study, we propose a method to advance the rendering of immersive content using background color information [2]. First, the elements necessary for Kelvin temperature rendering are derived from the color and background as context elements, and the rendering effect has been realized in the soap bubble. For soap bubbles Kelvin temperature rendering, the average color of the background is extracted and the color with the highest similarity is applied by comparing the main color and Kelvin temperature.

In this paper we analyze the effect of the credit period on inventory policy under trade credit with ordering cost including a fixed cost and freight cost, where the freight cost has a quantity discount. For marketing purposes, some supplier offers credit period to his buyer to stimulate the demand for the product he produces. The delay in payments during the credit period has the effect of reducing the buyer’s capital opportunity cost. It is also assumed that the buyer pays the freight cost for the order and hence, the ordering cost consists of a fixed ordering cost and a variable freight cost which depends on the order quantity. As a result, the possibilities of trade credit and discounts on freight costs are expected to play an important role in the buyer’s inventory policy. Based on the economic order quantity inventory model, we analyze how the buyer can determine the optimal inventory policy and we examine the effect of the length of credit period on the buyer's inventory policy.

The generalization of social distancing due to the COVID-19 pandemic has rapidly spread non-face-to-face services, accelerating the speed of non-face-to-face digital conversion technology. The importance of telemedicine, a remote service, has been rekindled in the wearable technology including the medical industry. In a situation where it is not easy for any company to overcome the COVID-19 pandemic, it is a time when collaboration within the industry or between competitors is necessary. In addition to the digital-based online exhibition hall using AR-VR-MR technology, which is a major core technology of the future industry, virtual stores that can receive services such as actual shopping should be actively used. Paradoxically COVID-19 will provide new opportunities to reshape and reconnect the future of the textile and fashion industry. Therefore, the purpose of this study is to investigate the current status of wearable technology products being developed as fashion items for the prevention of COVID-19 and analyze their characteristics. This study results can be used as basic data for future research on the fashion industry and education.

Recently, correlated superposition coding (CSC) has been proposed to implement non-orthogonal multiple access (NOMA) without successive interference cancellation (SIC), without loss of spectral efficiency, in contrast to conventional independent superposition coding (ISC). However, correlation between signals has reduced the average total allocated power, which results in degraded performance. Thus, in order to avoid the reduction of the average total allocated power owing to correlation between signals, this paper proposes a cross-correlated quadrature amplitude modulation (QAM) NOMA scheme under Rayleigh fading channel surroundings. First, we design the cross-correlated QAM NOMA scheme. Then, simulations demonstrate that for the weaker channel gain’s user, the symbol error rate (SER) performance of the proposed cross-correlated QAM NOMA improves largely, whereas for the stronger channel gain’s user, the SER performance of the proposed cross-correlated QAM CSM NOMA degrades little, compared to that of the conventional QAM NOMA.

Recently, as the number of new and variant malicious codes has increased exponentially, malware warnings are being issued to PC and smartphone users. Malware is becoming more and more intelligent. Efforts to protect personal information are becoming more and more important as social issues are used to stimulate the interest of PC users and allow users to directly download malicious codes. In this way, it is difficult to prevent malicious code because malicious code infiltrates in various forms. As a countermeasure to solve these problems, many studies are being conducted to apply deep learning. In this paper, we investigate and analyze various deep learning methods to detect and classify malware.

Currently, to prevent the spread of COVID-19 virus infection, gathering of more than 5 people in the same space is prohibited. The purpose of this paper is to measure the distance between objects using the Yolov5 model for processing real-time images with OpenCV in order to restrict the distance between several people in the same space. Also, Utilize Euclidean distance calculation method in DeepSORT and OpenCV to minimize occlusion. In this paper, to detect the distance between people, using the open-source COCO dataset is used for learning. The technique used here is using the YoloV5 model to measure the distance, utilizing DeepSORT and Euclidean techniques to minimize occlusion, and the method of expressing through visualization with OpenCV to measure the distance between objects is used. Because of this paper, the proposed distance measurement method showed good results for an image with perspective taken from a higher position than the object in order to calculate the distance between objects by calculating the y-axis of the image.

Currently, due to COVID-19, household waste has a lot of impact on the environment due to packaging of food delivery. In this paper, we design and implement Faster-RCNN, SSD, and YOLOv4 models for municipal waste detection and classification. The data set explores two types of plastics, which account for a large proportion of household waste, and the types of aluminum cans. To classify the plastic type and the aluminum can type, 1,083 aluminum can types and 1,003 plastic types were studied. In addition, in order to increase the accuracy, we compare and evaluate the loss value and the accuracy value for the detection of municipal waste classification using Faster-RCNN, SDD, and YoloV4 three models. As a final result of this paper, the average precision value of the SSD model is 99.99%, the average precision value of plastics is 97.65%, and the mAP value is 99.78%, which is the best result.

Currently, cloud computing is being used as a technology that greatly changes the IT field. For many businesses, many cloud services are available in the form of custom, reliable, and cost-effective web applications. Most cloud service providers provide functions such as IoT, machine learning, AI services, blockchain, AR & VR, mobile services, and containers in addition to basic cloud services that support the scalability of processors, memory, and storage. In this paper, we will look at the most used cloud service providers and compare the services provided by the cloud service providers.

In a multi-cloud environment, it is necessary to minimize physical movement for efficient interoperability of distributed source data without building a data warehouse or data lake. And there is a need for a data platform that can easily access data anywhere in a multi-cloud environment. In this paper, we propose a new platform based on data fabric centered on a distributed platform suitable for cloud environments that overcomes the limitations of legacy systems. This platform applies the knowledge graph database technique to the physical linkage of source data for interoperability of distributed data. And by integrating all data into one scalable platform in a multi-cloud environment, it uses the holochain technique so that companies can easily access and move data with security and authority guaranteed regardless of where the data is stored. The knowledge graph database mitigates the problem of heterogeneous conflicts of data interoperability in a decentralized environment, and Holochain accelerates the memory and security processing process on traditional blockchains. In this way, data access and sharing of more distributed data interoperability becomes flexible, and metadata matching flexibility is effectively handled.

Inbody is a tool for measuring health information with high reliability and accuracy to analyze body composition. Unlike the existing method of storing/processing and outputting data on the server side, the health information generated by InBody requires accurate support for health sharing and data analysis services using mobile devices. However, in the process of transmitting body composition measurement information to a mobile service, a problem may occur in data transmission/reception processing. The reason for this is that, since the network network in the cloud environment is used, if the connection is cut off or the connection is changed, it is necessary to provide a global service, not a temporary area, focusing on the mobility of InBody information. In addition, since InBody information is transmitted to mobile devices, a standard schema should be defined in the mobile cloud environment to enable information transfer between standardized InBody data and mobile devices. We propose a mobile cloud system using EMRA(Extended Metadata Registry Access) in which a mobile device processes and transmits body data generated in the inbody and manages the data of each local organization with a standard schema. The proposed system processes the data generated in InBody and converts it into a standard schema using EMRA so that standardized data can be transmitted. In addition, even when the mobile device moves through the area, the coordinator subsystem is in charge of providing access services. In addition, EMRA is applied to the collision problem due to schema heterogeneity occurring in the process of accessing data generated in InBody.

The study has suggested a way to minimize safety accidents found in on-site firefighting activity by analyzing firefighters' [investigation report on accidents to on-sie workers]. The study result is described as follows. First, the result of [investigation report on on-site workers] shows that while accidents are found to most frequently have occurred to low-ranking firefighting officers such as Sobangsa and Sobanggyo and firefighting officers with career of less than 5 years, fire-extinguishing activity proved to be the most prone to accidents in the category of activity. Second, analysis performed to identify variance between injury extent and area based on cause of accident shows statistically significant variance. In addition, the result of verifying difference in cause of accident based on category of activity shows significant difference with 'falling over and sliding' being the highly likely cause of accident in fire containment and rescue activities and 'reckless move' being highly likely case of accident in emergency activities. Third, the result of verifying factors behind the extent of injury done to on-site workers shows that when accident is caused by 'incomplete behavior', it was found that the extent of injury is substantial. It was also found that rescue activity is accompanied by substantial extent of injury. As a solution to this, the study suggested ways to establish, extend and operate safety-specific curriculum for entrants, develop materials regarding risk prognosis training and explicate training-related regulations, set up safety management measure for a single squad team, upgrade performance of private protection equipment, institutionalize SOP by on-site activity stage, materialize and activate swift rescue team and increase objectivity and proficiency of safety accident investigation.

This study is designed to determine how to identify misleading news articles based on natural language processing on Artificial Intelligence & Bigdata. A misleading news discrimination system and method on natural language processing is initiated according to an embodiment of this study. The natural language processing-based misleading news identification system, which monitors the misleading vocabulary database, Internet news articles, collects misleading news articles, extracts them from the titles of the collected misleading news articles, and stores them in the misleading vocabulary database. Therefore, the use of the misleading news article identification system and methods in this study does not take much time to judge because only relatively short news titles are morphed analyzed, and the use of a misleading vocabulary database provides an effect on identifying misleading articles that attract readers with exaggerated or suggestive phrases. For the aim of our study, we propose news article identification methods in natural language processing on Artificial Intelligence & Bigdata.

The purpose of this study is to design and build fake news discrimination systems and methods using fact-checking guidelines. In other words, the main content of this study is the system for identifying fake news using Artificial Intelligence -based Fact-checking guidelines. Specifically planned guidelines are needed to determine fake news that is prevalent these days, and the purpose of these guidelines is fact-checking. Identifying fake news immediately after seeing a huge amount of news is inefficient in handling and ineffective in handling. For this reason, we would like to design a fake news identification system using the fact-checking guidelines to create guidelines based on pattern analysis against fake news and real news data. The model will monitor the fact-checking guideline model modeled to determine the Fact-checking target within the news article and news articles shared on social networking service sites. Through this, the model is reflected in the fact-checking guideline model by analyzing news monitoring devices that select suspicious news articles based on their user responses. The core of this research model is a fake news identification device that determines the authenticity of this suspected news article. So, we propose news article identification methods with fact-checking guideline on Artificial Intelligence & Bigdata. This study will help news subscribers determine news that is unclear in its authenticity.

In this study, we tried to examine how the kinking of the fire hose affects the time taken for initial water discharge by measuring and analyzing the time taken for initial water discharge with different number of kinks at different locations of the hose. The average time taken for initial water discharge was obtained by measuring the time in the unkinked state of the fire hose. Based on this standard, we conducted the experiment by selecting the kinking locations in the hose near the water outlet and nozzle, and setting the number of kinks to 3, 6, 9, and 12. The results of this study are as follows: First, if the fire hose has 5 kinks or more near the nozzle, no water was released. Second, when comparing the case of no kinks and 4 kinks near the nozzle, there was no significant difference in the time taken for initial water discharge. Third, when the fire hose was kinked 10 times near the outlet, the time required for initial water discharge increased by 1.62 seconds on average compared to the case with no kinking, but there was no problem with water discharge. Lastly, regarding the kinking locations of the fire hose, it was found that the greater the number of kinks near the nozzle than near the outlet, the greater the effect on the discharge. As a result, it is concluded that it would be preferable to install non-kinking devices near the nozzle of the fire hose.

The purpose of this study is to suggest that the movement expression activity of intellectually disabled people is effective in the learning process of LMA motion recognition based on Kinect sensor. We performed an ICT motion recognition games for intellectually disabled based on movement learning of LMA. The characteristics of the movement through Laban's LMA include the change of time in which movement occurs through the human body that recognizes space and the tension or relaxation of emotion expression. The design and implementation of the motion recognition model will be described, and the possibility of using the proposed motion recognition model is verified through a simple experiment. As a result of the experiment, 24 movement expression activities conducted through 10 learning sessions of 5 participants showed a concordance rate of 53.4% or more of the total average. Learning motion games that appear in response to changes in motion had a good effect on positive learning emotions. As a result of study, learning motion games that appear in response to changes in motion had a good effect on positive learning emotions

Sponsorship is one of the communication tools that have been used for a long time to raise corporate awareness and establish favorable customer attitude. This study tried to examine the effect of corporate sponsorship, which has recently been attracting increasing attention. We empirically examined whether sponsorship and program fit, identification with a company or brand, and corporate credibility affect the reputation of the sponsoring company. For this, We conducted a survey using a structured questionnaire for 263 college students, and the collected data were analyzed through a structural equation model along with factor analysis. As a result of the study, it was found that sponsorship and program suitability had a positive effect on corporate reputation, and brand identification and reliability also had a positive effect on corporate reputation. Based on the results of the study, it was possible to obtain the implication that it is important to increase the fit of the sponsor and sponsorship program, to improve the corporate brand identification and corporate credibility in order to increase the corporate reputation through sponsorship.