• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.137-148
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• 2024

The purpose of this study is to determine how the use of retailtech technology affects consumers' purchase intention. Furthermore, this study aims to investigate the mediating effects of technology usefulness and ease of use on this influence relationship and whether experiential marketing moderates consumers' purchase intention. The survey was conducted from August 1, 2023 to September 30, 2023, and a total of 257 people participated in the study. For statistical analysis, hierarchical regression analysis, three-stage mediation regression analysis, and hierarchical three-stage controlled regression analysis were conducted to test the hypothesis. The results of the study are as follows. First, it was confirmed that big data-AI utilization, mobile-SNS utilization, live commerce utilization, and IoT utilization affect purchase intention in retail technology utilization. Second, technology usefulness has a mediating effect on IoT utilization, mobile-SNS utilization, and big data-AI utilization. Third, perceived ease of use of technology mediated the effects of IoT utilization, mobile-SNS utilization, live-commerce utilization, and big data-AI utilization. Fourth, escapist experience has a moderating effect on mobile SNS utilization and live commerce utilization. Fifth, esthetic experience has a moderating effect on mobile-SNS utilization and big data-AI utilization. Through this study, we hope that the domestic distribution industry will contribute to national competitiveness by securing the competitive advantage of companies by utilizing new technologies in entering the global market.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.144-150
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• 2020

Reinforcement learning is a technology that can present successful and creative solutions in many areas. This reinforcement learning technology was used to deploy containers from cloud servers to fog servers to help them learn the maximization of rewards due to reduced traffic. Leveraging reinforcement learning is aimed at predicting traffic in the network and optimizing traffic-based fog computing network environment for cloud, fog and clients. The reinforcement learning system collects network traffic data from the fog server and IoT. Reinforcement learning neural networks, which use collected traffic data as input values, can consist of Long Short-Term Memory (LSTM) neural networks in network environments that support fog computing, to learn time series data and to predict optimized traffic. Description of the input and output values of the traffic-based reinforcement learning LSTM neural network, the composition of the node, the activation function and error function of the hidden layer, the overfitting method, and the optimization algorithm.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.587-594
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• 2015

Open operating system, Linux is the traditional Web, E-mail, DNS, FTP server, as well as being used in Cloud and Big data infrastructure. In addition, Linux is also used like a desktop or mobile devices, smart TV and cars. In particular, stepping up to the IoT era at this time is expected to be greater proportion occupied by Linux. As the use of Linux has increased security has emerged as an important factor. User management is core of Linux system security. In this paper, Classifying Linux user and analyzed the role of the user-specific file. Finally, we analyzed the linux management technologies and useful user security tools.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.10
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• pp.1460-1468
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• 2015

As the number of IoT service increases, the interest of lightweight block cipher algorithm, which consists of simple operations with low-power and high speed, is growing. LEA(Leightweight Encryption Algorithm) is recently adopted as one of lightweight encryption standards in Korea. In this paper a pipeline LEA architecture is proposed to process large amounts of data with high throughput. The proposed pipeline LEA can communicate with external modules in the 32-bit I/O interface. It consists of input, output and encryption pipeline stages which take 4 cycles using a muti-cycle pipeline technique. The experimental results showed that the proposed pipeline LEA achieved more than 7.5 Gbps even though the key length was varied. Compared with the previous high speed LEA in accordance with key length of 128, 192, and 256 bits, the throughput of the pipeline LEA was improved 6.45, 7.52, and 8.6 times. Also the throughput per area was improved 2, 1.82, and 2.1 times better than the previous one.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.1-9
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• 2021

In the Internet of Thing (IoT) framework, massive machine-type communications (MMTC) have required large spectral efficiency. For this, non-orthogonal multiple access (NOMA) has emerged as an efficient solution. Recently, a non-successive interference cancellation (SIC) NOMA scheme has been implemented without loss. This lossless NOMA without SIC is achieved via correlated superposition coding (SC), in contrast to conventional independent SC. However, conventional minimum high-correlated SC for only 2-user NOMA schemes was investigated in the lossless 2-user non-SIC NOMA implementation. Thus, this paper investigates a 3-user low-correlated SC scheme, especially for an inflated achievable sum rate, with a design of 3-user low-correlated SC. First, we design the 3-user low-correlated SC scheme by taking the minimum sum rate between 3-user SIC NOMA and 3-user non-SIC NOMA, both with correlated SC. Then, simulations demonstrate that the low correlation in the direction of the first user's power allocation inflates the sum rate in the same direction, compared to that of conventional minimum high-correlated SC NOMA, and such inflation due to low correlation is also observed similarly, in the direction of the second user's power allocation. Moreover, we also show that the two low correlations of the first and second users inflates doubly in the both directions of the first and second users' power allocations. As a result, the proposed 3-user low-correlated SC could be considered as a promising scheme, with the inflated sum rate in the future fifth-generation (5G) NOMA networks.

• Journal of Digital Convergence
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• v.18 no.6
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• pp.53-63
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• 2020

Electronic financial transactions are also actively increasing due to the rapid spread of information communication media such as the Internet, smart devices, and IoT, but as a derivative by-product, threats of financial security such as leakage of various personal information and hacking are also increasing. Therefore, the importance of financial security against this is increasing, but in Korea, financial security technology is relatively insufficient compared to advanced countries in the field of financial security, such as Active-X. Therefore, this study aims to present the major development direction in the domestic financial security field by comparing key technology trends with IPC classification frequency analysis, keyword frequency analysis, and keyword network analysis based on domestic and foreign financial security-related patent data. In conclusion, it seems that recent domestic and foreign trends have focused on the development of related technologies according to the development of smart device-based electronic financial services. Accordingly, it is intended to be used as the basis data for technology development of financial security by mapping the trend of financial security research trend and technology trend analysis through thesis data analysis that reflects the research of the preceding aspect as the technology of commercialization in the future.

• Convergence Security Journal
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• v.17 no.3
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• pp.59-64
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• 2017

Korea is experiencing a rapid increase in the number of elderly living alone accompanying the aging society problem, a nd is making efforts to solve the problem through the policy of 'living alone u-care service'. The purpose of this study is to propose a better u-Care service improvement method by applying new technology to improve the user experience of ucare service for the health and safety of the elderly living alone. First, the improvement of u-Care service for elderly livin g alone by applying IoT technology. It provides remote monitoring service using health information data measured through wearable device, and transmits personal health status to medical institution by using personal device such as smart phone, so that remote medical consultation or telemedicine can be connected in the future. Second, improvement of u-Care service through consideration of emotional stability of elderly living alone as well as simple safety and health care through applica tion of emotional service robot technology.It is expected that it will be able to help independent living of one person's elde rly person in the future by providing caring function service to existing u-care service providing service.

• Journal of Internet of Things and Convergence
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• v.7 no.1
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• pp.71-77
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• 2021

As the IOT technology has developed, it becomes more big issues about IOT device security. An account management is a nerve-in-the-box routine job for the system administrator and users who manage the several hundreds IOT devices(IP camera, Home IOT, the various measuring equipment). This study is to propose the account management system by the hierarchical design and it is efficient for the user to manipulate the account management. The designed system supports 6 functions for the account management and apply the advanced technologies for the existed system. After the performance of the designed system is validated successfully by the authoritative test, the designed system is applied for the relative fields. And it is on going for the development of the smart account management system by applying the AI technique.

• Journal of Internet of Things and Convergence
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• v.7 no.2
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• pp.55-63
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• 2021

The purpose of this study was to investigate the structural relationship between the use motives of the Internet of Things (IoT), which was presented as a technology strategy priority for university students, on usage attitudes, usability performance and life satisfaction. From April 1 to April 30, 2021, a non-face-to-face survey was conducted targeting university students living in Gwangju Metropolitan City and Jeollanam-do, and the study was conducted in a total of 213 copies. The collected questionnaires were analyzed using IBM's SPSS 21.0 and AMOS 21.0 programs. The research results are as follows. First, the motivation for using IoT was found to have an effect on usage attitude, and it was found to have an effect on life satisfaction and also on usage performance. Second, it was found that the attitude of using the Internet of Things had an effect on the usability performance. However, it was found that there was no effect on life satisfaction. Third, it was found that the use of IoT has an effect on the life satisfaction of college students. Fourth, it was found that the indirect effect on the attitude of use had an indirect effect on the relationship between the motivation for use and the performance of use. However, it was found that there was no indirect effect on the relationship between use motivation and life satisfaction. Fifth, the indirect effect on the usability performance was found to have an indirect effect on the relationship between use motivation and life satisfaction, Also, it was found that there was an indirect effect on the relationship between usage attitude and life satisfaction. Sixth, in the relationship between use motivation and life satisfaction, there was no double indirect effect via use attitude and utilization performance. Based on these results, the motivation for using the Internet of Things for college students and a solution to the information gap were proposed.

• Journal of the Korean Society of Safety
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• v.35 no.5
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• pp.74-85
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• 2020

Smart phone zombie or Smombie means pedestrians who walk without attention to their surroundings because they are focused upon their smart phone. Because the traffic accidents and injuries caused by Smombie have been increased rapidly in recent years, the social attention and policies are needed to prevent it. This study was conducted to analyze Smombie's current status and some solutions used before and to propose new improved method through the latest ICT trend. In this study, we did the field survey to check Smombies at several places in Seoul through people counting, and found that a lot of pedestrians still use the smart phone while walking. And we analyzed many case studies about some solutions to prevent Smombies previously. The case studies include legal regulations, government policies, smart phone app services and facilities that are used before. We studied them through internet searches and reference studies and we also checked the current operating situation as visiting several places that the solutions actually has been operated. Therefore, we found there are some limitations in previous solutions in terms of effectiveness and management. To consider new solution that can be expected to overcome the limitations, we analyzed the latest ICT trends focused on features to utilize the Smombie prevention, especially video recognition and digital signage. In these days, video recognition has been developed rapidly with assistance of AI technology and it can recognize the specific pedestrian's characteristics such as holding smart phone as well as hair style, clothes, backpack and etc. On the other hands, the digital signage is the convergence device that includes big display, network connection and various IoT sensors. It can be used as public media in many places for public services as well as advertising. Through these analysis results, we show the requirements and the user scenario for the improved method to prevent Smombie. Finally, we propose to develop R&D technology to recognize Smombie exactly as pedestrian attributes and to spread creative contents to increase pedestrian's interest and engagement for Smombie prevention through digital signage.