• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.159-166
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• 2022

Artificial Intelligence has stimulated every aspect of today's life. Human thinking quality is trying to be involved through digital tools in all research areas of the modern era. The education industry is also leveraging artificial intelligence magical power. Uses of digital technologies in pedagogical paradigms are being observed from the last century. The widespread involvement of artificial intelligence starts reshaping the educational landscape. Adaptive learning is an emerging pedagogical technique that uses computer-based algorithms, tools, and technologies for the learning process. These intelligent practices help at each learning curve stage, from content development to student's exam evaluation. The quality of information technology students and professionals training has also improved drastically with the involvement of artificial intelligence systems. In this paper, we will investigate adopted digital methods in the education sector so far. We will focus on intelligent techniques adopted for information technology students and professionals. Our literature review works on our proposed framework that entails four categories. These categories are communication between teacher and student, improved content design for computing course, evaluation of student's performance and intelligent agent. Our research will present the role of artificial intelligence in reshaping the educational process.

• Quality Improvement in Health Care
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• v.28 no.1
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• pp.2-13
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• 2022

Purpose: This study assessed the status of the Development and Utilization of critical pathways (CP) in South Korea. Methods: We surveyed 195 hospitals obtained on the Korean Hospital Association website. Data were collected using structured questionnaires for staff members in charge of CP management personnel in these hospitals. The questionnaire included CP developed by the institutions, the coverage rates and completion rates of CP in the current year, and management indicators related to CP. The questionnaire also included CP support systems and content within the institutions and questions regarding the advantages of CP utilization and obstacles associated with the CP development process. Results: Analysis of the responses from 70 hospitals (35.9% response rate) showed that a total of 1,370 CP sets were developed. The number of CP related to surgery departments was 365 (26.6%), and CP related to surgery and procedure was 1,093 (79.8%), respectively. The CP coverage rate was the most frequently used indicator to monitor the effect of CP (97.1%), followed by the completion rate (90.0%) and the length of stay in hospital (61.4%). CP managers reported that CP were highly useful for communication (3.39±0.493) and accurate information provision (3.39±0.491). The perception that CP violated doctors' autonomy in treatment was relatively low (2.87±0.645). Conclusion: It is necessary to establish an infrastructure in hospitals for CP. CP can facilitate communication and provide accurate information.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1574-1580
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• 2021

This paper designs and presents the results of an air network simulation radio transmission link applied with a multi-beam active phase array antenna simulator in a testbed system for verifying an air network currently underway as a technology development task. Using the Ku band, the Radio transmission link was designed in consideration of the link budget to satisfy the requirements for the system being developed. Considering short-distance links and long-distance links, the required EIRP and G/T performance scales of multi-beam repeaters and mission planes were applied to confirm the minimum and maximum link margins based on Eb/No. In this Radio Transmission Link design, the application analysis results such as rainfall availability are used to effectively establish standards when selecting the operating radius of the multi-beam relay system and related system standards.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.9-17
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• 2023

In this paper, we propose a one-class vibration anomaly detection system for bearing defect diagnosis. In order to reduce the economic and time loss caused by bearing failure, an accurate defect diagnosis system is essential, and deep learning-based defect diagnosis systems are widely studied to solve the problem. However, it is difficult to obtain abnormal data in the actual data collection environment for deep learning learning, which causes data bias. Therefore, a one-class classification method using only normal data is used. As a general method, the characteristics of vibration data are extracted by learning the compression and restoration process through AutoEncoder. Anomaly detection is performed by learning a one-class classifier with the extracted features. However, this method cannot efficiently extract the characteristics of the vibration data because it does not consider the frequency characteristics of the vibration data. To solve this problem, we propose an AutoEncoder model that considers the frequency characteristics of vibration data. As for classification performance, accuracy 0.910, precision 1.0, recall 0.820, and f1-score 0.901 were obtained. The network design considering the vibration characteristics confirmed better performance than existing methods.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.81-94
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• 2022

Real estate and artworks were considered challenging investment targets for individual investors because of their relatively high average transaction price despite their long investment history. Recently, the so-called fractional investment, generally known as investing in a share of the ownership right for real-life assets, etc., and most investors perceive that they actually own a piece (fraction) of the ownership right through their investments, is gaining popularity. Founded in 2016, Musicow started the first service that allows users to invest in copyright fees related to music distribution. Using the LSTM algorithm, one of the deep learning algorithms, this research predict the price of right to participate in copyright fees traded in Musicow. In addition to variables related to claims such as transfer price, transaction volume of claims, and copyright fees, comprehensive indicators indicating the market conditions for music copyright fees participation, exchange rates reflecting economic conditions, KTB interest rates, and Korea Composite Stock Index were also used as variables. As a result, it was confirmed that the LSTM algorithm accurately predicts the transaction price even in the case of fractional investment which has a relatively low transaction volume.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.4
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• pp.661-671
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• 2022

Due to the COVID-19 pandemic, remote working, e-learning, e-teaching and online collaboration have widely spread and become popular. Accordingly, the usage of IPsec VPN for security reasons has also dramatically increased. With the spread of VPN, VPN vulunerabilities are becoming an important target of attack for attackers, and many studies have been conducted on this. IKE v2 analysis is an essential process not only for developing and building IPsec VPN systems but also for security analysis. Network packet analysis tools such as Wireshark and Tcpdump are used for IKE v2 analysis. Wireshark is one of the most famous and widely-used network protocol analyzers and supports IKE v2 analysis. However Wireshark has many limitations, such as requiring system administrator privileges for IKE v2 analysis. In this paper, we describe Wireshark's limitations in detatil and propose a new analysis method. The proposed analysis method can analyze all encrypted IKE v2 messages in real time from the session key exchange In addition, the proposed analysis method is expected to be used for dynamic testing such as fuzzing as packet manipulation.

• Asia-Pacific Journal of Business
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• v.12 no.3
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• pp.213-233
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• 2021

Purpose - Our study examines the determinant factors of corporate financial fraud and whether the characteristics of outside directors tend to decrease the fraud in China. Design/methodology/approach - The data come from the enforcement actions of the Chinese Securities Regulatory Commission (CSRC). The multiple regression analysis were hired in order to analyze the data. Findings - Firms that have smaller size, higher debt ratio, or lower return of assets are associated with the incidence of fraud. However, the firms that have a high proportion of outside directors on the board or whose outside directors have a high compensation are less likely to engage in fraud. Our results show that outside directors monitor the actions of managers and thus help deter fraudulent acts. On the other hand, fraud is more associated with the local outside directors rather than outside directors who are from other locations. Since local outside directors tend to be more related with managers of firms, they can lose their independence. Research implications or Originality - Our findings have implications for the design of appropriate outside directors systems for China-listed firms. Moreover, our results imply that recruiting outside directors from other regions can improve the expertise and independence of outside directors in China. Our study contributes to provide more useful information about investors' investment decisions or management oversight and regulators' decisions on audit activities by disclosing information relating to the characteristics of outside directors.

• Journal of the Korea Society of Computer and Information
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• v.28 no.5
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• pp.57-66
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• 2023

In this paper, a research trend of attack graph studies for Cyber-Physical System (CPS) environments is surveyed, and we analyse the limitations of previous works and prospect the future directions. 35 among around 150 attack graph studies conducted within 5 years target CPS, and we inspect key features of CPS environment in the security aspect. Also, we categorize and analyze target studies in the aspect of modelling physical systems and considering air gaps, which are derived as key features of the security aspects of CPS. Half of 20 research that we surveyed do not reflect those two features, and other studies only consider one of the two features. In this circumstance, we examine challenges that attack graph studies on CPS environment face. Finally, we expect state-led studies or studies targeting open-spec commercial CPS will dominate.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.341-359
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• 2023

The metaverse applies various technological means such as digital twin modeling, 3D rendering, and holographic imaging, which can provide an immersive tourism service experience. However, since the development of the metaverse is still in its infancy, there is relatively little research on digital tourism from the perspective of the metaverse. This research empirically studies the factors that promote the participation behavior of users on the metaverse platform for digital cultural tourism. Our results show that users' internal motivations for learning and entertainment and the functions provided by metaverse, which are sensory stimulation and social interaction lead to the intention to participate in cultural tourism on metaverse with the mediating effects of immersion experience and perceived pleasure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2188-2208
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• 2023

Quality of Service (QoS) is a critical feature of Wireless Sensor Networks (WSNs) with routing algorithms. Data packets are moved between cluster heads with QoS using a number of energy-efficient routing techniques. However, sustaining high scalability while increasing the life of a WSN's networks scenario remains a challenging task. Thus, this research aims to develop an energy-balancing component that ensures equal energy consumption for all network sensors while offering flexible routing without congestion, even at peak hours. This research work proposes a Gravitational Blackhole Search Optimised splay tree routing framework. Based on the splay tree topology, the routing procedure is carried out by the suggested method using three distinct steps. Initially, the proposed GBSO decides the optimal route at initiation phases by choosing the root node with optimum energy in the splay tree. In the selection stage, the steps for energy update and trust update are completed by evaluating a novel reliance function utilising the Parent Reliance (PR) and Grand Parent Reliance (GPR). Finally, in the routing phase, using the fitness measure and the minimal distance, the GBSO algorithm determines the best route for data broadcast. The model results demonstrated the efficacy of the suggested technique with 99.52% packet delivery ratio, a minimum delay of 0.19 s, and a network lifetime of 1750 rounds with 200 nodes. Also, the comparative analysis ensured that the suggested algorithm surpasses the effectiveness of the existing algorithm in all aspects and guaranteed end-to-end delivery of packets.