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This study aimed to scrutinize transformation of school violence in the wake of COVID-19 by investigating posts on Naver Knowledge-iN. We expected that the pattern of school violence to be significantly changed after COVID-19 as students were detached from schools and the use of digital devices was increased. Our focus was split between two demographic groups (before and after COVID-19). We collected data from Knowledge-iN by tracking posts with hashtags #청소년학교폭력 (teenage school violence) and #학폭 (school violence). We analyzed crawled data by visualizing word frequency ranking, relation matrix, and network graphs. Visualizations revealed that students were more likely to be exposed to domestic violence and that the role of the school had changed as students spent more time at home than in school. Furthermore, school violence and sexual crimes changed their forms due to increase of digital device usage. Overall, this research provides valuable insights into the changing landscape of school and domestic violence in the context of COVID-19, calling for educational institutions to take proactive measures in developing a support system for students vulnerable to violence both within the school’s boundaries and beyond.

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Building a blockchain network is time-consuming and challenging. It requires extensive information technology (IT) knowledge and relevant skills. To simplify this task, global IT companies provide cloud-based blockchain services. In this paper, we proposed a cloud-based construction and management tool called smart blockchain network constructor (SBC) that could allow blockchain developers, operators and enterprises to easily deploy blockchain networks within their infrastructure and save time and cost. SBC employs Hyperledger Fabric, a well-known private blockchain platform. Ansible is an open-source IT automation engine that could support network-wide deployment. Instead of complex and repetitive text commands, SBC provides a user-friendly web interface that allows users to setup, deploy, and interact seamlessly with blockchain networks. To verify its usefulness and convenience, a blockchain network that could conduct food safety checks and an electronic voting decentralized app were built and tested with SBC. The process of blockchain network construction, which involves writing more than ten settings files and executing numerous command lines, can be replaced with simple input and click operations from a graphical user interface. A Hyperledger Fabric channel was used to enable independent and reliable tasks in both food safety and smart election tasks. As a result, an automated system was created to simulate the necessary manual work in constructing blockchain networks. We observed that the proposed automated system dramatically reduced the time consumption of blockchain network construction compared to manual construction. We strongly believe that this system will be highly beneficial to both blockchain operators and developers for their applications built on blockchain technology.

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Giving AI speakers with opportunities for cognitive and emotional decision-making leads to issues of trust in AI speakers. Computers Are Social Actors paradigm and attribution theory can explain the relationship between trust targets and identify which factors affect trust in them. We focus on the cognitive and emotional decision-making of AI speakers, and aim to find out whether people trust AI’s decision and why they trust it. We conducted a survey, and the results showed that perceived autonomy and perceived empathy of AI speakers have a very positive effect on trust in AI speakers. Also, people trust AI speakers because they are human-like. Finally, people who want conversational AI speakers with social communication trust AI more when they perceive empathy in AI speakers. Results are meaningful in extending the CASA paradigm, which can establish social relationships with computers, to connections with AI speakers.

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This paper proposed a new channel estimation scheme to enhance packet error rate (PER) performance in WAVE communication systems. The proposed scheme was based on conventional enhanced time domain reliable test frequency domain interpolation (ETRFI). PER performance was maximized by iteratively estimating and updating channel coefficients. In the proposed scheme, channel coefficients were initially estimated by the ETRFI scheme. Information bits were then decoded based on estimated channel values. After data symbols were reconstructed with a receiver using decoded information bits, channel coefficients were updated using reconstructed data symbols as pilot symbols. Data symbols reconstructed from decoded information bits showed very high accuracy. Its PER performance was better than performances of conventional schemes. Moreover, as the number of iterations increased, PER performance was further improved. The optimal number of iterations to maximize the PER performance was dependent on channel fluctuation. Therefore, as the channel varied rapidly in time and frequency domains, the optimal number of iterations also increased. Numerical results showed that the PER performance of the proposed scheme was better than those of conventional schemes. In addition, the optimal number of iterations was 2 in the channel environment of Cross Non-line-of-sight (NLOS) with 126km/h. On the other hand, it was 3 in Highway NLOS with 252 km/h which varied more rapidly than Cross NLOS in the time domain.

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With advancement of mobile technologies and wireless communication, many healthcare apps have been developed to promote habitual physical activity and facilitate health self-healthcare. However, studies examining the effectiveness of these mobile health (mHealth) apps in enhancing exercise adherence are insufficient. Thus, the aim of this study was to help development of mHealth apps for continuous participation of exercise participants. In this study, a total of 379 questionnaires were analyzed using SPSS 23.0 and AMOS 23.0 programs. First, there was a significant difference in internal motivation for participation motivation according to the use of mHealth apps. On the other hand, no difference was found between amotivation and external motivation. There was a significant difference between exercise commitment and exercise adherence. Exercise commitment of leisure sports club participants, in particular, influenced exercise adherence. However, the direct moderating effect of exercise commitment did not significantly affect exercise adherence. The use of mHealth apps did not show a moderating effect. The use of the mHealth apps might enhance exercise adherence of the study population. The content design of mHealth apps can be considered to improve exercise adherence in future research.

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Open-world games strongly restrict gaming environment, either because of technical limitations or in-game limitations imposed by game linearity. Hierarchical Task Network (HTN) planning frequently used in simulated virtual world, restricting the plan-space to finite and ensuring decision-making is limited by scalability, especially when high situation variability is desirable. We developed a late-binding planning technique that ensures situational diversity and is still scalable enough to run practical simulation systems. This technique enables any partially ordered set of functionally interrelated events to be defined as composite events, suggesting layered organization. It is a two-level planning, involving inter- and intra-event dimensions for functional forms, which are dynamically channeled into multi-event situations against the common background. We first analyzed the viability of a functional language based on our approach with respect to situational variability and scalability over a constraint language as HTN, and demonstrated its feasibility by implementing a composite scenario.

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Adolescents who are living in the recent IT technology and social distancing environment are experiencing expansion and limitation at the same time in order to adapt to internal and external conditions and role changes. As they adapt to such conditions and changes, they suffer from significant stress and mental health difficulties. This study aimed to provide empathetic exchange and support by applying a half-duplex communication method to have emotional awareness and understanding by developing a ‘Music Autobiography Program’ to record and share music, a representative interest of youth, according to the chronology of growth. Considering that this will be a realistic and useful art healing content instead of treatment barriers and limitations, this study develops a music autobiography program for a mobile application for mindfulness of adolescents and discusses its meaning.

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Innovative exploration of transmission and dissemination of intangible cultural heritage plays a key role in national development, international exchange, and sustainable social development. This review presents the current state of digital preservation in China in the field of intangible cultural heritage based on contemporary approaches via study and development of interactive digital resources such as shadow puppets. Using design-based research, quasi-experimental methods, and literature review, this study provides an understanding of the current status of the development and preservation of intangible cultural heritage. Three different versions of shadow puppet interactive digital resources are presented using storyline software. Subjects learned best when viewing the global-no-catalog type of interactive resources, moderately well when viewing the left-right layout type, and the least when viewing the top-down layout.

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The purpose of this study was to investigate how Korean college students perceived online and offline classes in terms of their social interactions (with their peers and instructor) and senses of classroom community during their online and offline classes. To accomplish this purpose, two research questions were constructed: 1) How did Korean college students perceive online classes in terms of their social interactions and senses of classroom community? 2) How did they perceive offline classes in terms of their social interactions and senses of classroom community? Thirty-three students responded to the Rovai’s (2002) 20-item Classroom Community Scale modified for the current study. An independent sample t-test as a main analysis method was employed. Findings of data analysis indicated that, first, students perceived two different learning environments in nearly the same way in terms of social interactions with their peers and the instructor. Second, students were more likely to rely on or trust others in online classes than in offline classes. It indicated that they might have been more used to online classes than offline classes because they had longer experience with online classes because of the pandemic. Pedagogical implications and suggestions for further research are presented.

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The essence of PHM technology is to process the collected information with the help of the system information collected by sensors, using information fusion, artificial intelligence, big data, reasoning algorithms and other technologies, and realize the monitoring management, status evaluation and fault prediction functions of the target system. PHM is an important part of the intelligent equipment detection and maintenance system. Its application and realization in the railway field is the key link of the intelligent operation and maintenance of multiple units, and is an important means to realize the shift from planned preventive maintenance to digital and accurate condition maintenance. It is of great significance for China's high-speed railway to maintain the world's advanced level and move towards higher quality, efficiency and efficiency. With the improvement of operation speed and the growth of application scale of High-Speed Electric Multiple Units in China, hereinafter referred to as EMU, the technical challenges of operation safety and security of EMUs are increasingly prominent. As a kind of equipment health management technology, PHM can realize equipment status monitoring, abnormal prediction, fault diagnosis, maintenance prediction and maintenance decision-making. In order to improve the safety assurance capability of high-speed EMU, reduce the maintenance cost and improve the maintenance efficiency, this paper deeply integrates big data technology, algorithm model and PHM technology, and explores the theory and method of intelligent fault prediction of key components of high-speed EMU based on PHM technology. Focus on the research of EMU condition monitoring and fault diagnosis technology based on HSMM and DBN algorithms, as well as the component maintenance prediction and maintenance decision-making technology based on fixed repair schedule prevention, so as to transfer the theoretical basis and technical support for the maintenance mode of EMU from "planned repair" to "planned repair predictive maintenance".