• The Korean Journal of Franchise Management
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• v.2 no.2
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• pp.1-23
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• 2011

The Freedom of Information System has been introduced into the society based on the Fair Trade Transactions Act, which was established by Fair Trade Commission (FTC) on May, 2002. However, the system itself has showed limitations in guaranteeing a reliability and transparency of the disclosure document. Thus, since February, 2008, FTC not only made franchisors to register disclosure documents but also adopted the Disclosure Document Registration System, which forced them to provide registered disclosure documents to franchise applicants and franchisee. Franchisors consider the newly adopted Disclosure Document Registration System a restrictive system. However, considering the recent trend of fast growing franchising industry and the importance of being competitive, franchisors need to utilize the disclosure documents to promote their business and to gain trusts from franchise applicants by providing truthful information. In that way, franchisors will be able to establish a foundation that franchising industry might be successful and reduce the agency fee by cutting out conflicts with franchisees. Thus, this study aims to study the ways of effective preparation of disclosure document and its utilization from a franchisor viewpoint.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.582-583
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• 2021

As the production of new and renewable energy such as solar and wind power has diversified, microgrid systems that can simultaneously produce and consume have been introduced. . In general, a decrease in electricity prices through solar power is expected in summer, so producer protection is required. In this paper, we propose a transparent and safe gift power transaction system between users using blockchain in a microgrid environment. A futures is simply a contract in which the buyer is obligated to buy electricity or the seller is obliged to sell electricity at a fixed price and a predetermined futures price. This system proposes a futures trading algorithm that searches for futures prices and concludes power transactions with automated operations without user intervention by using a smart contract, a reliable executable code within the blockchain network. If a power producer thinks that the price during the peak production period (Hajj) is likely to decrease during production planning, it sells futures first in the futures market and buys back futures during the peak production period (Haj) to make a profit in the spot market. losses can be compensated. In addition, if there is a risk that the price of electricity will rise when a sales contract is concluded, a broker can compensate for a loss in the spot market by first buying futures in the futures market and liquidating futures when the sales contract is fulfilled.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.584-585
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• 2021

As the production of new and renewable energy such as solar and wind power has diversified, microgrid systems that can simultaneously produce and consume have been introduced. In general, a decrease in electricity prices through solar power is expected in summer, so producer protection is required. In this paper, we propose a transparent and safe gift power transaction system between users using blockchain in a microgrid environment. A futures is simply a contract in which the buyer is obligated to buy electricity or the seller is obliged to sell electricity at a fixed price and a predetermined futures price. This system proposes a futures trading algorithm that searches for futures prices and concludes power transactions with automated operations without user intervention by using a smart contract, a reliable executable code within the blockchain network. If a power producer thinks that the price during the peak production period is likely to decrease during production planning, it sells futures first in the futures market and buys back futures during the peak production period to make a profit in the spot market. losses can be compensated. In addition, if there is a risk that the price of electricity will rise when a sales contract is concluded, a broker can compensate for a loss in the spot market by first buying futures in the futures market and liquidating futures when the sales contract is fulfilled.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1951-1975
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• 2023

Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.

• Journal of Service Research and Studies
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• v.11 no.2
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• pp.79-93
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• 2021

The size of the domestic art market has increased 21.9% over the past five years as of 2018 to KRW 448.2 billion and the number of transactions has also increased 31.6% to 39,367 points maintaining growth for the fifth consecutive year. Art distribution platforms are diversifying from galleries and auction-style offline to online auctions. The art market consists of three areas: production (creation), distribution (trade), and consumption (buying) of works and as the perception of artistic value as well as economic value spreads interest is also increasing as a means of investment. Consumers who purchase works and think of them as a means of investment technology have an increased need for objective information about their works, but there is a limit to collecting and analyzing objective and reliable statistics because information provision in the art market distribution area is closed and unbalanced. This paper identifies objective and reliable art distribution status and status through big data collection and structured and unstructured data analysis on art market distribution areas. Through this, we want to implement a system that can objectively provide analysis of authors in the current market. This study collected author information from art distribution sites and calculated the frequency of associated words by writer by collecting and analyzing the author's articles from Maeil Business, a daily newspaper. It aims to provide consumers with objective and reliable information.

• The Journal of the Convergence on Culture Technology
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• v.9 no.2
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• pp.493-502
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• 2023

The development of online content is changing the value of society very diversely and rapidly. In particular, the non-face-to-face e-sports industry is growing significantly in the current situation where the COVID-19 Pandemic has not been completely overcome. The use of NFT in the eSports industry is receiving positive reviews as a field with high potential for future growth that protects digital assets of eSports users, but at the same time, it is raising concerns that cash transactions of digital items could encourage gambling. In this study, the characteristics of the recent eSports industry and NFT were identified and classified through case studies using literature, official sites, and online news articles. Through various cases of eSports and NFT, we discussed the potential for future growth and activation plan of the NFT industry of eSports. The result is as follows. First, it is necessary to use NFT using IP of eSports event itself. Second, it is necessary to combine the functional role of the item with NFT to provide features that users can utilize. Third, it is necessary to provide users with opportunities to engage in economic activities using eSports and NFT. Finally, it is necessary to use NFT to strengthen the digital asset protection of eSports users. Through this study, it is expected to be used as a basis for further discussions on the NFT industry of e-sports and as a material for securing competitiveness.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.75-79
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• 2023

ESG management means to thoroughly consider the investor's perspective when evaluating corporate value, and environmental, social, and governance issues are continuous and strategic monitoring issues in identifying risk and opportunity factors related to corporate management activities. In other words, the perspective of value creation is reflected in business relationships. The fundamental purpose of ESG management is continuous business value creation and thorough management of investment risks and business transactions in contractual relationships. It is also a requirement of linked investors. The field that Korean companies are currently experiencing the most is the recognition that 'ESG information collection is necessary and maintenance must be prioritized' in investor IR and global sales and marketing departments, and the primary need for this is emerging. In addition, as the legal affairs office, environmental safety department, and human resources department, which conduct compliance management, carry out related tasks, clarity at the organizational level must precede in order to properly establish an information integration and management system. It covers the scope of securing new market opportunities such as management, disclosure and communication. Therefore, in regard to the newly emerging ESG management and response methods, it is necessary to review and implement it repeatedly so that sustainable exchange profits can be created by simultaneously managing non-financial risks as well as efforts to enhance corporate value for financial returns.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.5
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• pp.199-206
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• 2023

The current software becomes the huge size of source codes. Therefore it is increasing the importance and necessity of static analysis for high-quality product. With static analysis of the code, it needs to identify the defect and complexity of the code. Through visualizing these problems, we make it guild for developers and stakeholders to understand these problems in the source codes. Our previous visualization research focused only on the process of storing information of the results of static analysis into the Database tables, querying the calculations for quality indicators (CK Metrics, Coupling, Number of function calls, Bad-smell), and then finally visualizing the extracted information. This approach has some limitations in that it takes a lot of time and space to analyze a code using information extracted from it through static analysis. That is since the tables are not normalized, it may occur to spend space and time when the tables(classes, functions, attributes, Etc.) are joined to extract information inside the code. To solve these problems, we propose a regularized design of the database tables, an extraction mechanism for quality metric indicators inside the code, and then a visualization with the extracted quality indicators on the code. Through this mechanism, we expect that the code visualization process will be optimized and that developers will be able to guide the modules that need refactoring. In the future, we will conduct learning of some parts of this process.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.5
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• pp.217-228
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• 2023

Video instance segmentation is an intelligent visual task with high complexity because it not only requires object instance segmentation for each image frame constituting a video, but also requires accurate tracking of instances throughout the frame sequence of the video. In special, human instance segmentation in drama videos has an unique characteristic that requires accurate tracking of several main characters interacting in various places and times. Also, it is also characterized by a kind of the class imbalance problem because there is a significant difference between the frequency of main characters and that of supporting or auxiliary characters in drama videos. In this paper, we introduce a new human instance datatset called MHIS, which is built upon drama videos, Miseang, and then propose a novel video data augmentation method, CDVA, in order to overcome the data imbalance problem between character classes. Different from the previous video data augmentation methods, the proposed CDVA generates more realistic augmented videos by deciding the optimal location within the background clip for a target human instance to be inserted with taking rich spatio-temporal context embedded in videos into account. Therefore, the proposed augmentation method, CDVA, can improve the performance of a deep neural network model for video instance segmentation. Conducting both quantitative and qualitative experiments using the MHIS dataset, we prove the usefulness and effectiveness of the proposed video data augmentation method.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.485-491
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• 2022

The traditional economic order quantity (EOQ) model is analyzed under the basic assumption that the purchase price is paid immediately upon receiving the product. However, product suppliers may allow a certain period of deferral of payment for product purchase costs in order to differentiate themselves from competitors. From the distributor's point of view, such a credit transaction can temporarily divert product purchase costs, resulting in a reduction in inventory investment costs, and ultimately, a factor that lowers the selling price for the purpose of increasing end-customer demand can be. In addition, in that credit transactions are provided for the purpose of increasing the demand of suppliers as a means of differentiation from competitors, it is more general to be allowed flexibly according to the transaction volume. In this regard, assuming that the end customer's demand is represented by a linear decreasing function of the distributor's selling price, this study analyzes a model for determining the distributor's pricing and ordering policies under order-size-dependent delay in payments. For the analysis, we also assume that the inventory is depleted not only by customer's demand but also by decaying.