• Journal of Internet of Things and Convergence
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• v.8 no.3
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• pp.63-68
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• 2022

Due to COVID-19, many paradigm shifts in existing manufacturing facilities and the expansion of non-face-to-face services are accelerating worldwide. A representative technology is digital twin technology. Such digital twin technology, which existed only conceptually in the past, has recently become feasible with the construction of a 5G-based network. Accordingly, this paper designed and implemented a part of the USB process to enable digital twins based on OPC UA communication, which is a standard interlocking structure, between real object objects and virtual reality-based USB process in accordance with this paradigm change. By reflecting the physical characteristics of real objects together, it is possible to simulate real-time synchronization of these with real objects. In the future, this can be applied to various industrial fields, and it is expected that it will be possible to reduce costs for decision-making and prevent dangerous accidents.

• Journal of Engineering Education Research
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• v.26 no.4
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• pp.22-35
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• 2023

As information and communication technology has developed remarkably, it has become possible to analyze various types of large-volume data generated at a speed close to real time, and based on this, reliable value creation has become possible. Such big data analysis is becoming an important means of supporting decision-making based on scientific figures. The purpose of this study is to develop a big data analysis tool that can analyze large amounts of data generated through engineering education. The tasks of this study are as follows. First, a database is designed to store the information of entries in the National Creative Capstone Design Contest. Second, the pre-processing process is checked for analysis with big data analysis tools. Finally, analyze the data using the developed big data analysis tool. In this study, 1,784 works submitted to the National Creative Comprehensive Design Contest from 2014 to 2019 were analyzed. As a result of selecting the top 10 words through topic analysis, 'robot' ranked first from 2014 to 2019, and energy, drones, ultrasound, solar energy, and IoT appeared with high frequency. This result seems to reflect the current core topics and technology trends of the 4th Industrial Revolution. In addition, it seems that due to the nature of the Capstone Design Contest, students majoring in electrical/electronic, computer/information and communication engineering, mechanical engineering, and chemical/new materials engineering who can submit complete products for problem solving were selected. The significance of this study is that the results of this study can be used in the field of engineering education as basic data for the development of educational contents and teaching methods that reflect industry and technology trends. Furthermore, it is expected that the results of big data analysis related to engineering education can be used as a means of preparing preemptive countermeasures in establishing education policies that reflect social changes.

• Smart Media Journal
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• v.12 no.8
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• pp.60-68
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• 2023

After COVID-19, hotel industry is rapidly experiencing changes in the business environment, and under the influence of the Fourth Industrial Revolution, hotel industry is striving to secure competitive advantages through differentiation, including the use of big data and the IoT in service provision, as well as the introduction of artificial intelligence(AI) robot services. This study analyzed the perceived value of AI robot services and their impact on usage attitudes and behavioral intentions of customers who have used hotels that have introduced AI robot services. The results of the study showed that the value of robot services perceived by customers who have used robot services in hotels is categorized into three dimensions: social, experiential, and functional, and all of them have a positive effect on usage attitudes, with social, functional, and experiential values having a positive effect on usage attitudes in that order. Attitude toward use was also analyzed to have a positive effect on behavioral intention, which is consistent with the value-attitude-behavior model. Therefore, it is necessary for hotels to improve the satisfaction of hotel guests through diversified services of AI robot service.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.125-130
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• 2024

With the rapid growth of mobility technology, the industrial sector is demanding storage devices that can reliably process data from various equipment and sensors in vehicles. NAND flash memory is being utilized as a storage device in mobility environments because it has the advantages of low power and fast data processing speed as well as strong external shock resistance. However, flash memory is characterized by data corruption due to long-term exposure to high temperatures. Therefore, a dedicated system for temperature management is required in mobility environments where high temperature exposure due to weather or external heat sources such as solar radiation is frequent. This paper designs a dedicated temperature management system for managing storage device temperature in a mobility environment. The designed temperature management system is a hybrid of traditional air cooling and water cooling technologies. The cooling method is designed to operate adaptively according to the temperature of the storage device, and it is designed not to operate when the temperature step is low to improve energy efficiency. Finally, experiments were conducted to analyze the temperature difference between each cooling method and different heat dissipation materials, proving that the temperature management policy is effective in maintaining performance.

• Convergence Security Journal
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• v.24 no.2
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• pp.189-200
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• 2024

In recent years, the development of defense technology has become digital with the introduction of advanced assets such as drones equipped with artificial intelligence. These assets are integrated with modern information technologies such as industrial IoT, artificial intelligence, and cloud computing to promote innovation in the defense domain. However, the convergence of the technology is increasing the possibility of transfer of cyber threats, which is emerging as a problem of increasing the vulnerability of defense assets. While the current cybersecurity methodologies focus on the vulnerability of a single asset, interworking of various military assets is necessary to perform the mission. Therefore, this paper recognizes these problems and presents a mission-based asset management and evaluation methodology. It aims to strengthen cyber security in the defense sector by identifying assets that are important for mission execution and analyzing vulnerabilities in terms of cyber security. In this paper, we propose a method of classifying mission dependencies through linkage analysis between functions and assets to perform a mission, and identifying and classifying assets that affect the mission. In addition, a case study of identifying key assets was conducted through an attack scenario.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.163-169
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• 2020

Recently, research on automation and unmanned operation of machines in the industrial field has been conducted with the advent of AI, Big data, and the IoT, which are the core technologies of the Fourth Industrial Revolution. The machines for these automation processes are controlled based on the data collected from the sensors attached to them, and further, the processes are managed. Conventionally, the abnormalities of sensors are periodically checked and managed. However, due to various environmental factors and situations in the industrial field, there are cases where the inspection due to the failure is not missed or failures are not detected to prevent damage due to sensor failure. In addition, even if a failure occurs, it is not immediately detected, which worsens the process loss. Therefore, in order to prevent damage caused by such a sudden sensor failure, it is necessary to identify the failure of the sensor in an embedded system in real-time and to diagnose the failure and determine the type for a quick response. In this paper, a deep neural network-based fault diagnosis system is designed and implemented using Raspberry Pi to classify typical sensor fault types such as erratic fault, hard-over fault, spike fault, and stuck fault. In order to diagnose sensor failure, the network is constructed using Google's proposed Inverted residual block structure of MobilieNetV2. The proposed scheme reduces memory usage and improves the performance of the conventional CNN technique to classify sensor faults.

• The Journal of Industrial Distribution & Business
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• v.10 no.8
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• pp.33-44
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• 2019

Purpose - As the scope of existing digital transformation expanded to various degrees, the Fourth Industrial Revolution came into being. In 2016, Klaus Schwab, Chairman of the World Economic Forum (WEF), said that the new technologies that lead the fourth industrial revolution are AI, Block chain, IoT, Big Data, Augmented Reality, and Virtual Reality. This technology is expected to be a full-fledged fusion of digital, biological and physical boundaries. Everything in the world is connected to the online network, and the trend of 'block chain' technology is getting attention because it is a core technology for realizing a super connective society. If the block chain is commercialized at the World Knowledge Forum (WKF), it will be a platform that can be applied to the entire industry. The block chain is rapidly evolving around the financial sector, and the impact of block chains on logistics, medical services, and public services has increased beyond the financial sector. Research design, data, and methodology - Figure analysis of data and social science analytical software of IBM SPSS AMOS 23.0 and IBM Statistics 23.0 were used for all the data researched. Data were collected from hotel employees in China from 25th March to 10th May. Results - The purpose of this study is to investigate the effect of the block chain characteristics of the existing hotel reservation system on the intention to use and to examine the influence of the block chain characteristics of the hotel reservation system on the intention to use, We rearranged the variables having the same or similar meaning and analyzed the effect of these factors on the intention to use the block chain characteristic of the hotel reservation system. 339 questionnaires were used for analysis. Conclusions - There are only sample hotel workers in this study, and their ages are in their 20s and 30s. In future studies, samples should be constructed in various layers and studied. In this study, the block chain characteristics are set as five variables as security, reliability, economical efficiency, availability, and diversity. Among them, Security and reliability made positive effects on the perceived usefulness. Also, security and economics did on the perceived ease. Availability and diversity did on both perceived usefulness and perceived ease. Perceived ease did on perceived usefulness. And perceived ease and perceived usefulness did on user intent. But security and economics did not on the perceived usefulness

• The Journal of Society for e-Business Studies
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• v.21 no.4
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• pp.137-150
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• 2016

A variety of O2O (Online to Offline) services such as Uber, Airbnb, and KakaoTaxi that create new values by connecting offline and online have emerged in the world. O2O services support the convenience of online services and the real-life capability of offline services simultaneously. Thanks to the development of ICTs such as mobility, IoT (Internet of Things), Fin-tech, and big data technologies, the market size of O2O industry is growing very rapidly. This paper reviews various O2O services and industry trends in Korea. In addition, important issues on O2O services and industry promotion are reviewed and presented. Specifically, legislative issues regulating the O2O industry in Korea, interest conflicts between new O2O platform providers and existing traditional offline service providers, current technology infrastructures for O2O services, and negative or side effects of O2O services are reviewed and summarized. Finally, comprehensive policy directions are proposed based on these reviewed issues. It is expected that the proposed policy directions would be adopted by the government and this research could consequently contribute to strengthening the competitiveness of the O2O industry in Korea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.325-333
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• 2021

With the rapidly changing era of the fourth industrial revolution, the utilization of IT technology is increasing. In addition, the demand for security authentication is increasing as shared services or IoT technologies are being developed as new business models. Security authentication is becoming increasingly important for all intelligent devices such as self-driving cars. However, most location-based security authentication technologies are being developed mainly with technologies that utilize server proximity or satellite location tracking, which limits the scope of their physical use. Location-based security authentication technology has recently been developed as a complementary replacement technology. In this study, we introduce location-based security authentication technology using cell broadcasting technology, which has a wider range of applications and is more convenient and business-friendly than existing location-based security authentication technologies. We also introduced application cases and business models related to this. In addition to the current status of technology development, we analyzed current changes in business models being employed. Based on our analysis results, this study draws the implication that technology diversification is necessary to improve the performance of innovative technologies. It is meaningful that it has found and studied advanced technologies other than existing location authentication methods and systems.

• Journal of Industrial Convergence
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• v.22 no.4
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• pp.1-9
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• 2024

Smart factories represent production facilities where cutting-edge information and communication technologies are fused with manufacturing processes, reflecting rapid advancements and changes in the global manufacturing sector. They capitalize on the integration of robotics and automation, the Internet of Things (IoT), and the convergence of artificial intelligence technologies to maximize production efficiency in various manufacturing environments. However, the smart factory environment is prone to security threats and vulnerabilities due to various attack techniques. When security threats occur in smart factories, they can lead to financial losses, damage to corporate reputation, and even human casualties, necessitating an appropriate security response. Therefore, this paper proposes a security authentication mechanism for safe communication in the smart factory environment. The components of the proposed authentication mechanism include smart devices, an internal operation management system, an authentication system, and a cloud storage server. The smart device registration process, authentication procedure, and the detailed design of anomaly detection and update procedures were meticulously developed. And the safety of the proposed authentication mechanism was analyzed, and through performance analysis with existing authentication mechanisms, we confirmed an efficiency improvement of approximately 8%. Additionally, this paper presents directions for future research on lightweight protocols and security strategies for the application of the proposed technology, aiming to enhance security.