• Journal of Digital Convergence
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• v.19 no.1
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• pp.77-88
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• 2021

Cloud computing is getting a lot of attention by many people and businesses due to IT environmental changes such as the proliferation of smart devices, the increase of digital data, and the cost of IT resources. More individuals use personal cloud computing services for storing and managing information and data. Therefore, this study proposed determinants that are expected to have an influence on evaluating the value of cloud computing based on the value-based adoption model, examining the relationship between the continuous use intention of cloud computing. Results of the study show that usefulness, convenience of information access, extensibility had a positive impact on perceived value while privacy concerns and costs had a negative impact on perceived value. In addition, perceived value was found to have a significant effect on the intention to continue use of cloud computing. Finally, trust was found to have a significant effect on the perceived value and the intention to continue use of cloud computing. The findings are expected to provide useful information for understanding the factors that individual users consider important in the steadily growing cloud computing market.

• The Korean Journal of Franchise Management
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• v.10 no.3
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• pp.25-35
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• 2019

Purpose - The major objective of this study was to investigate the effect of franchisor's (economic and philanthropic) CSR in inspiring franchisee's loyalty for the franchisor. Another aim of this investigation also was to clarify the mediating role of economic and social satisfaction in the relationship between franchisor's CSR and franchisee's loyalty. Research design, data, and methodology - This study explores the structural relationship between franchisor's CSR and franchisee's loyalty and in these relationships, the mediating role of relationship satisfaction. Data were gathered from employees(above manager) in food-service franchisee companies in Seoul, Korea. The questionnaires were distributed to managers of the franchise stores. A total of 251 questionnaires were collected. Data management and analysis were performed using SPSS 21.O and SmartPLS 3.0. Evaluation of measurement model and structural model was carried out using confirmatory factor analysis and correlation analysis. Result - The results of this study show as follows. First, economic CSR had positive effects on economic satisfaction and social satisfaction. Second, philanthropic CSR had positive effects on social satisfaction. Third, economic satisfaction and social satisfaction had positive effects on franchisee's loyalty to the franchisor. Conclusions - The important implications of this study have as follows. First, this study has found that economic CSR can create a high economic satisfaction and social satisfaction of franchisee. Second, this findings suggest that the philanthropic CSR can improve the social satisfaction of franchisee. Third, this results demonstrate, for the first time, that the economic satisfaction and social satisfaction of franchisees can play a crucial role to improve their loyalty for the franchisor and pursue mutual development by maintaining the stable business relationship with a franchisor. In this investigation there are at least three limitations. First, Because the research sample is limited to the foodservice franchisee in Seoul, it is not possible to be representativeness of the national franchisee. Second, CSR activities are mostly focused on large franchise companies. Therefore, there is a limit to the research approach. Finally, this study examined the effect of economic CSR and philanthropic CSR on the loyalty of franchisors, but in the future study, it is necessary to analyze the relationship between CSR and loyalty of franchise companies by collecting specific quantitative data such as re-contract rate and management performance of franchisees.

• Journal of the Korean Geotechnical Society
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• v.38 no.4
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• pp.21-32
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• 2022

Steel pile foundations are widely used for offshore constructions due to their high bearing capacity and efficiency. Typically, offshore structures that have reached the end of their design life are required to be demolished. However, pile foundations are often left on site due to technical and economic limitations. The pile left on the site not only pollutes the environment, but can also cause obstacles for the construction of new structures. Therefore, research is required to completely eliminate these foundations at the site. In this study, a new type of double-wall pile foundation that can drastically reduce the pull-out load was conceptually proposed, and a series of model tests were performed to validate the performance of the double-wall pile foundation. The installation and extraction of the double-wall pile were simulated in dry sand in the model test, and the measured up-lift load was compared to that of the conventional pile. According to the result, the maximum up-lift load induced by the decommissioning of the double-wall pile was reduced by 45% when compared to the traditional pile in dense sand. This study verified the mechanism for reducing the up-lift load of the double-wall foundation and confirmed the possibility of completely decommissioning a pile that has reached the end of its nominal service life.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.345-352
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• 2022

Recent LiDAR(Light Detection And Ranging) sensor is used for scanning object around in real-time. This sensor can detect movement of the object and how it has changed. As the production cost of the sensors has been decreased, LiDAR begins to be used for various industries such as facility guard, smart city and self-driving car. However, LiDAR has a large input data size due to its real-time scanning process. So another way for processing a large amount of data are needed in LiDAR system because it can cause a bottleneck. This paper proposes edge computing to compress massive point cloud for processing quickly. Since laser's reflection range of LiDAR sensor is limited, multiple LiDAR should be used to scan a large area. In this reason multiple LiDAR sensor's data should be processed at once to detect or recognize object in real-time. Edge computer compress point cloud efficiently to accelerate data processing and decompress every data in the main cloud in real-time. In this way user can control LiDAR sensor in the main system without any bottleneck. The system we suggest solves the bottleneck which was problem on the cloud based method by applying edge computing service.

• Korean Association of Arts Management
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• no.59
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• pp.73-99
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• 2021

Free admission policies have been gradually extended for the public to use cultural facilities free of charge, which lowered the barriers to use those facilities and has a great effect on increasing visitor demands. However, the annual number of visitors which is open to the public isn't quite accurate and varies from institution to institution, which means just a head count. Especially people counter overestimates the number of visitors because it counts visitors in duplicate. Therefore, the purpose of this study is to prepare effective way of grasping the number of visitors using cultural infrastructure. First, comparable number of visitors should be measured by defining the notion of visitor clearly, which has been measured vaguely. Secondly, the problem of duplicate count, which is considered the most problematic, should be solved. Thirdly, the various analysis of visitor behavior should be conducted to provide a high-quality service. To work out the problems above, new measurement will be presented here. This study suggests a state-of-the-art wireless signal-based measurement that could eliminate the duplicate data by collecting MAC address -smart device's distinct signal value. And it also could analyze diverse visitor behaviors by understanding a flow of visitor traffic, duration of stay and revisitation. I would like to examine the possibility and effectiveness of this new measurement by testing it.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.405-413
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• 2022

Since the COVID-19 outbreak, the active utilization of new health care service utilizing the ICT technology and data science such as telemedicine, smart hospital, AI dignosis has been increasingly found. In this study we examined the business model of Amazon healthcare which leads disruptive innovation in U.S. health care industry with the introduction of hybrid model of telemedicin, in-person care and customer-centric online drug delivery, home-use diagnostic kit, characterized by the integrated model combining medical care, drug delivery and the use of diagnostic kit. We showed using the multiproduct competition model that the synergy effect between the Amazon's original business areas and the healthcare business area causes the active market penetration and the increase in the customer value from utilization of the Amazon care. Using Hotelling's spatial competition model, we also showed that the competition in the health care market can be greater when consumer's choice of health care providers are available in telemedicine platform. In the long, run the issue of competition being weakened due to the exit of less competent healthcare providers may arise, to which the policymakers in the charge of fair competition in health care industry should pay attention.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.29-35
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• 2022

UV rays have beneficial or harmful effects on the human body depending on the degree of exposure. An accurate UV information is required for proper exposure to UV rays per individual. The UV rays' information is provided by the Korea Meteorological Administration as one component of daily weather information in Korea. However, it does not provide an accurate UVI at the user's location based on the region's Ultraviolet index. Some operate measuring instrument to obtain an accurate UVI, but it would be costly and inconvenient. Studies which assumed the UVI through environmental factors such as solar radiation and amount of cloud have been introduced, but those studies also could not provide service to individual. Therefore, this paper proposes a deep learning model to calculate UVI using solar object information and sunlight characteristics to provide an accurate UVI at individual location. After selecting the factors, which were considered as highly correlated with UVI such as location and size and illuminance of sun and which were obtained through the analysis of sky images and solar characteristics data, a data set for DNN model was constructed. A DNN model that calculates the UVI was finally realized by entering the solar object information and sunlight characteristics extracted through Mask R-CNN. In consideration of the domestic UVI recommendation standards, it was possible to accurately calculate UVI within the range of MAE 0.26 compared to the standard equipment in the performance evaluation for days with UVI above and below 8.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.31-38
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• 2022

An electrocardiogram(ECG) is a recoding of electrical signals of the heart's cyclic activity and an important body information for diagnosing myocardial rhythm. Large amount of information are generated continuously and a significant period of cumulative signal is required for the purpose of diagnosing a specific disease. Therefore, research on compression including clinically acceptable lossy technique has been developed to reduce the amount of information significantly. Recently, wearable smart heart monitoring devices that can transmit electrocardiogram(ECG) are being developed. The use of electrocardiogram, an important personal information for healthcare service, is rapidly increasing. However, devices generally have limited capability and power consumption for user convenience, and it is often difficult to apply the existing compression method directly. It is essential to develop techniques that can process and transmit a large volume of signals in limited resources. A method for compressing and transmitting the ECG signals efficiently by using the cumulative average (template) of the unit waveform is proposed in the paper. The ECG is coded lovelessly using template matching. It is analyzed that the proposed method is superior to the existing compression methods at high compression ratio, and its complexity is not relatively high. And it is also possible to apply compression methods to template matching values.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.148-163
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• 2021

The diversification of the New Deal urban regeneration projects, that started in 2017 in accordance with the "Special Act on Urban Regeneration Activation and Support", generated the increased demand for the accuracy of data-driven diagnosis and project type forecast. Thus, this research was conducted to develop an application model able to identify the most appropriate New Deal project type for "eup", "myeon" and "dong" across the country. Data for application model development were collected through Statistical geographic information service(SGIS) and the 'Urban Regeneration Comprehensive Information Open System' of the Urban Regeneration Information System, and data for the analysis model was constructed through data pre-processing. Four models were derived and simulations were performed through polynomial regression analysis and multinomial logistic regression analysis for the application of the appropriate New Deal project type. I verified the applicability and validity of the four models by the comparative analysis of spatial distribution of the previously selected New Deal projects by targeting the sites located in Seoul by each model and the result showed that the DI-54 model had the highest concordance rate.

• Korean Association of Arts Management
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• no.54
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• pp.59-93
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• 2020

The development of digital technology has made consumers more knowledgeable about products than ever before. In this regard, experts have defined consumers in the digital age as knowledge seekers and pointed out that they are proficient in acquiring and sharing product knowledge prior to purchase. For service goods such as musicals, product prior knowledge executes strong effect due to such characteristics as intangibility, inseparabilit y,and heterogeneity. Prior studies in the field of performing arts, including musicals, have revealed that the prior knowledge of the audience has a positive effect on the satisfaction of the audience and WOM(word-of-mouth) intention. However, studies in the marketing field argue that consumers' high prior knowledge may have a negative impact on customer satisfaction and product evaluation depending on conditions, as they are more likely to compare, review, and expect products more closely. Therefore, in this study, we tried to identify under what conditions the musical prior knowledge enhances audience satisfaction and WOM intention. According to the results of previous studies, a mediating effect model was established in which the musical prior knowledge enhances the WOM intention through the mediation of the audience satisfaction. Then, Transportation was introduced as a mediation variable and it was verified whether the level changed the audience satisfaction and WOM intention. The reason for the introduction of the transportation construct reflects the results of previous research that the story is important component of musical. The results showed that the musical prior knowledge has a significant effect on WOM intention through the mediation of audience satisfaction. The moderating effect of transport was also significant on the relationship between musical prior knowledge and audience satisfaction. Lastly, through moderated-mediation analysis, it was confirmed that transportation moderates the mediating effect that prior knowledge affects on the WOM intention through audience satisfaction. Based on the results, we demonstrated that a musical story is fairly important to satisfy audiences with high prior knowledge. This study could contribute to the related filed in that it introduced the transportation construct for the first time, thereby broadening the understanding of the musical audiences in the era of smart consumers.