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This paper explores the evolving role of teachers in AI-enhanced classrooms, particularly within the context of South Korea's upcoming AI Digital Textbook (AIDT) initiative. As AI technology becomes increasingly integrated into educational systems worldwide, this paper argues that teachers remain indispensable, playing critical roles that AI cannot replicate. The MERGE framework--Monitor, Encourage, Reward, Guide, and Evaluate--is proposed as a model to support teachers in effectively merging traditional educational practices with modern AI technologies. Developed initially in South Korea, the MERGE framework is adaptable to various global educational contexts, ensuring that educators worldwide can harness AI to enhance teaching rather than replace vital human elements. By fostering a co-learning environment where both teachers and students can thrive, this paper underscores the potential for AI to elevate education systems globally, emphasizing the importance of human-centered approaches in the age of AI. [ABSTRACT FROM AUTHOR]

Problem solving in real life is a core competency commonly adopted in several subjects recently. The real-world problems were rarely resolved with only one domain of knowledge. Thus, convergence education is becoming a trend in many countries. As on-line education is revitalized because of COVID-19, the need for changes to STEAM education is emerging. In December 2019, the on-line education systems quickly settled in schools because of COVID-19. During the first semester of 2020, most school education was conducted as virtual/distance learning classes. It is necessary to analyze how much technology has been used in the STEAM classes in Korea. This paper analyzes the research papers related to the STEAM education in Korea conducted in the last 10 years. By doing this, we analyze what kind of edutechs we were interested in, what kind of STEAM education actually occurred, and to whom it was conducted. The previous research papers analyzed in this paper are the papers in the Korea Citation Index accredited journals and candidate journals. Finally, this paper proposes educational changing factors to be considered for future technologybased STEAM education. [ABSTRACT FROM AUTHOR]

Implementation of 3D modeling design through morphological systematization represents a cuttingedge design methodology. However, this innovative approach has yet to establish a cohesive theoretical framework. Therefore, this paper utilized principles of Gestalt psychology as a foundation for significant research. By analyzing characteristics of organizational principles, the following eight essential keywords related to morphological systematization were proposed: “similar color,” “similar size,” “similar shape,” “distance,” “response,” “directional,” “overlapping,” and “incomplete.” These keywords were then synthesized to construct a morphological system framework that could allow content developers to aesthetically investigate various forms of 3D modeling and assess the strength of their formative attributes. [ABSTRACT FROM AUTHOR]

This paper evaluated the geographical distribution, chronological and economic patterns of the commercial cinema industry in Seoul, Korea dichotomized by the two main types of cinemas that have been prevalent in the recent Korean history, the first-run cinemas and the double-feature cinemas. This analysis involved computational technologies including the R statistical programing language and the interactive map library known as Leaflet for R in order to scrutinize the aforementioned patterns. Historically the cinema industry has been under the tight control of authoritarian military dictatorships that have run Korea in past decades, and the measures they took to control the cinema industry leading to unexpected ramifications. One of them is the decrease in the quality of domestic films, as competition with international films was reduced, and another is the massive increase in the domestic production of low-quality sex-exploitation B-tier films. The double feature cinemas played a big role in the distribution of the low-quality films. Our electronic maps will clearly represent the hierarchy and differentiation of these cinemas in the cinematic landscape of Seoul. [ABSTRACT FROM AUTHOR]

In this paper, in order to overcome the channel distortion due to doubly selective channel, a new deep learning-based channel estimation scheme is proposed. In the proposed scheme, two neural networks are combined to learn both the temporal and spectral characteristics of the channel. One is the AE (autoencoder) which is trained to track the channel characteristic in the time domain and the other is the LSTM (long short term memory) which is trained to track the channel characteristic in the frequency domain. Firstly, the AE is trained and then the LSTM is sequentially trained based on the AE output. After that, the trained neural network is used to the conventional DPA (data pilot aided) process to estimate the channel values in frequency domain. It is noted that the proposed LSTM network consists of fixed number of LSTM units, so it enables to track the temporal variation of the channel reliably, regardless of the position of the OFDM (orthogonal frequency division multiplexing) symbol in a frame. Therefore, the proposed scheme can enhance the PER (packet error rate) performance more by reducing the error propagation due to the DPA process. Through numerical results, it is confirmed that the proposed scheme shows the best PER performance of the conventional schemes in doubly selective channel environment [ABSTRACT FROM AUTHOR]

This paper presents a five-stage framework for AI learning based on classroom observations. It defines the stages and explores how teachers and students develop confidence in utilizing various AI tools, acknowledging both their constructive advantages and potential risks. The study emphasizes the transformative influence of integrating AI into the dynamics of learning and teacher-student relationships, fostering a more interactive educational environment. Through case studies conducted in South Korean classrooms, this research offers practical steps and considerations for educators and administrators to successfully integrate AI technologies, with the aim of enhancing digital and AI competencies in education. The findings highlight the significance of adopting a comprehensive approach to AI-integrated instruction, taking into account factors such as educational level, subject, and students' preparedness. This framework is designed to provide guidance for the effective utilization of AI in educational settings, supporting the objective of promoting AI literacy and closing educational gaps. [ABSTRACT FROM AUTHOR]

The purpose of this paper was to evaluate the usability of Korean logistics in life (LIL) startups mobile apps that aim to provide more convenience and a better quality of life. Determining an app’s usability requires a different set of evaluation criteria from that of desktop sites or full sites due to the inherent characteristics of the mobile environment. This paper derived 10 evaluation criteria from a literature review, calculated the weights of each criterion, and performed a usability test for 14 Korean LIL apps involving 27 subjects. To highlight areas of improvement, a comparison was done using a top ranked app on Google Play which had the best score in terms of usability (in 10 items test) among the best Korean LIL app. The average usability score of the LIL apps represented an overall lack of high usability. The evaluation criteria of the apps showed higher scores in the error-free, prediction, and consistency variables categories. In contrast, this was not the case for effectiveness, usefulness, and interaction, which were relatively low. Usability and interest had a slightly negative relationship when implementing big data analytics. From the quadrants analysis, it was found that for most of the evaluation criteria, continuous improvement was needed. As a result of logistics 4.0, the number of LIL apps is growing rapidly. This paper is the first to define the concept of LIL and develop an evaluation model for usability, which was then used to identify the ease of use, learnability, effectiveness, and efficiency of representative LIL apps in Korea. [ABSTRACT FROM AUTHOR]

Gut microbiota, regarded as the second genome of the human body, has become a key modulator of cancer treatment. It is an emerging topic in precision medicine, and many studies have reported that the variability in most diseases and individuals is related to gut microbiota characteristics. Numerous clinical studies on cancer treatment have demonstrated a correlation between therapeutic responses to immunotherapeutic cancer drugs and gut immunity or the microbiome. In this paper, we present the current clinical research on herbal medicines and gut microbiota and explore the possibility of integrative cancer treatment with herbal medicines and immunotherapeutic cancer drugs. We identified six clinical trials enrolled in the Clinical Research Information Service and five clinical studies on gut microbiota and herbal medicines in MEDLINE via PubMed. Generally, clinical studies have used 16S rRNA sequencing to analyze the gut microbiota. Study findings have suggested that the gut microbiota can be used as a biomarker to predict the pharmacological effects of herbal medicines. Gut microbiota modifications by herbal medicines may inhibit tumor progression. Herbal medicines are metabolized to active substances through interactions with the microbiome and control the dysbiosis of the gut microbiome. Further research on the possibility of individualized precision medicine by analyzing the gut microbiota after administering herbal medicine is needed. [ABSTRACT FROM AUTHOR]

As the Internet rapidly evolves, online learning has emerged as the third largest scenario in the field of education. Online education, different from the two traditional learning scenarios of the school and society, is characterized with broader learning types and higher freedom. In today’s post-pandemic era, art education, which relies on face-to-face teaching, is of particular significance to expand online education methods. Based on the UTAUT model, this paper posits seven hypotheses about the willingness to continue learning in online art education. After collecting valid data through a questionnaire, a detailed empirical analysis was conducted via SPSS and AMOS. The results of empirical analysis show that less than half of the respondents had experienced the online art education, mirroring that this is a market worth developing. Based on the findings, learning habit does not significantly impact art learners’ willingness to continue learning online. This result and other verified hypotheses are detailed in the discussion part of this paper. This study proves that UTAUT can better explain user behavior than the traditional information system model prior to the improvement, and also has strong explanatory power in the field of art education. The conclusion also posits some operational suggestions from the perspective of practitioners in this field, thereby providing a theoretical basis for art education practitioners. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the impacts of the following four influential factors on flow in digital reading: contents, platforms, motivations, and places. The contents factor was subdivided into "news articles" and "journal papers"; platforms is comprised of "mobile phones," "tablets," and "laptops"; motivations consists of "pleasure" and "assignments"; and "home," "on the go," and "out of home" are the subdivisions of the places factor. We conducted a questionnaire survey with the study's participants and the following results are shown: 1) The flow during the reading of news articles is influenced by motivations, whereas the flow during the reading of journal papers is influenced by platforms. 2) Regarding mobile phones, motivations significantly affected the flow, whereas content types significantly affected the flow for tablets; also, laptops provided the best flow and articles can be read on the platform regardless of motivations. 3) Reading for pleasure rather than for assignments positively influenced the flow for all of the platforms. 4) With respect to news articles, the places providing flow are different across platforms. However, for journal papers, the places out of home provided good flow. For tablets, the places for flow significantly depended on the content type, which is not the case for laptops. [ABSTRACT FROM AUTHOR]

Research on the metaverse has experienced significant growth in recent years, driven by advancements in technology, the thriving gaming industry, the expansion of social media and virtual communities, economic prospects, and the captivating vision of a new digital interface that transcends the current internet environment. To uncover research themes within the metaverse, we conducted a comprehensive analysis of research trends in this field using publications from Scopus, a widely recognized and extensively utilized scholarly database. Employing BERTopic, an advanced topic modeling technique, we analyzed 2,181 research articles focused on the metaverse. The exploration of the metaverse had humble beginnings with a single publication in 1995 but saw a substantial increase after 2020, reaching explosive growth with 1,041 publications in 2022. The application of the BERTopic model revealed 12 primary topics, each associated with significant keywords. These main topics encompass education, healthcare, blockchain, conferences, fashion, NFTs, cybersecurity, web3, research, video streaming, tinyML, and industry. Notably, among these subjects, education, healthcare, and blockchain exhibit significant research activity. In light of the global concern over the digital divide, we conducted investigations focusing on case studies involving digitally disadvantaged groups, such as individuals with visual impairments and the elderly. However, it is noteworthy that we identified only five studies addressing this issue, indicating limited research presence in this crucial area. [ABSTRACT FROM AUTHOR]

This paper aimed to explain the characteristics of North Korean English textbooks included in the textbook corpus analysis. The analysis mainly focused on the North Korean educational periodicals; 23 volumes of "Teachers' Propaganda Notebook" and 54 volumes of "People's Education". The analytic approach was 1) digitize all the English education-related articles included in the analytic materials, 2) use Nvivo 13 to categorize English education articles and their thematic propagation, and 3) relate the thematic categories to the North Korean leaders' statements. The findings were: Articles touch upon English education for the advancement of science and technology, the improvement of students' English skills, the enhancement of revolutionary ideology, and the improvement of English teachers' teaching and learning methods. These categories were derived from North Korean leaders' statements on occasions of field inspections, dialogues with newspapers, and conferences. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel method for developing expressive typography authoring tools with personal emotions. Our goal is to implement an interactive typography system that does not rely on any particular language and provides an easy, natural user interface and allows for immediate interaction. For this purpose, we converted the text data entered by a user to image data. The image data was then used for interaction with the user. The data was synchronized with the user's skeleton information obtained from the depth camera. We decomposed the characters using the formality of language to provide a typographical movement that responds more dynamically to the user's motion. Thus, this system provides interaction as a unit of characters rather than as a whole character, allowing the user to have emotional and aesthetic emotional immersion into his or her creation. [ABSTRACT FROM AUTHOR]

In a wireless mobile communication system, a pilot signal has been considered to be a necessary signal for estimating a changing channel between a base station and a terminal. All mobile communication systems developed so far have a specification for transmitting pilot signals. However, although the pilot signal transmission is easy to estimate the channel,(Ed: unclear wording: it is easy to use the pilot signal transmission to estimate the channel?) it should be minimized because it uses radio resources for data transmission. In this paper, we propose a pilotless channel estimation scheme (PCE) by introducing the clustering method of unsupervised learning used in our deep learning into channel estimation.(Ed: highlight-unclear) The PCE estimates the channel using only the data symbols without using the pilot signal at all. Also, to apply PCE to a real system, we evaluated the performance of PCE based on the resource block (RB), which is a resource allocation unit used in LTE. According to the results of this study, the PCE always provides a better mean square error (MSE) performance than the least square estimator using pilots, although it does not use the pilot signal at all. The MSE performance of the PCE is affected by the number of data symbols used and the frequency selectivity of the channel. In this paper, we provide simulation results considering various effects(Ed: unclear, clarify). [ABSTRACT FROM AUTHOR]

The global impact of the Covid-19 pandemic on education has resulted in the near-complete closure of schools, early childhood education and care (ECEC) facilities, universities, and colleges. To help the educational system with social distancing during this pandemic, in this paper the creation of a simple 3D virtual tour will be of a great contribution. This web cyber tour will be program with JavaScript programming language. The development of this web cyber tour is to help the students and staffs to have access to the university infrastructure at a faraway distance during this difficult moment of the pandemic. The drone and matterport are the two devices used in the realization of this website tour. As a result, Users will be able to view a 3D model of the university building (drone) as well as a real-time tour of its inside (matterport) before uploading the model for real-time display by the help of this website tour. Since the users can enjoy the 3D model of the university infrastructure with all angles at a far distance through the website, it will solve the problem of Covid-19 infection in the university. It will also provide students who cannot be present on-site, with detailed information about the campus. [ABSTRACT FROM AUTHOR]

In the past decade, East Asian Research has received attention from researchers as well as in South Korea society-at-large. The broad category of East Asian Research includes various disciplinary fields, such as "history, economics, and politics; however, few studies have used quantitative analysis to explore its development. In this paper, we used network analysis to identify the disciplines and active research areas, focusing on productivity, collaboration patterns, and citation networks of East Asian Research in South Korea. For this study, 6,646 journal publications related with East Asian Research and indexed by KCI (Korean Citation Index) during the 10-year period of 2004-2013 were considered. Results show that East Asian Research was led during this period by soleresearchers, rather than interdisciplinary studies. Moreover, a co-institution network represents active institutions with a high degree and collaborative centrality. In terms of journal-journal citation networks, journals belonging to both "history" and "Korean literature" disciplines were dominant. [ABSTRACT FROM AUTHOR]

This paper focuses on the recent trends in digital implementation technology and its relationship with cultural heritage restoration. Cultural heritage consists of tangible and intangible elements, including monuments and folklore cultural assets. The utilization of digital restoration and visualization techniques offers boundless possibilities beyond mere technical reproduction, shedding new light on the historical characteristics and values of humanity. Such research is regarded as an essential output that captures the profound social, cultural, and economic significance of cultural heritage. Digital restoration, reflecting Jean Baudrillard's concept of 'Simulacra,' serves as a crucial tool to reinterpret past civilizations based on historical evidence for the public. Through this process, profound insights can be gained from various fields such as society, economy, art, religion, and lifestyle. This approach signifies that the digital restoration transcends its mere technical aspect and helps in understanding its academic significance. [ABSTRACT FROM AUTHOR]

Since vehicles' trajectories are so complex and dense traffic changes in nature frequently, the VANET (Vehicles Ad-hoc Network), using Omni-directional Antenna, has many channel collisions (or overlapping) on Data Link phrases (MAC layers). It is not easy to keep a good seamless communication status for VANET because of its unpredictable network environment. Among VANET research, Directional Antenna have been proposed as one of the most common systematical solutions to reduce (or to mitigate) this misscommunication problems by narrowing communicational ranges and making use of its customized error-detection process. However, even though Directional Antennas help VANET keep good seamless communication, many VANET researchers have reported that Directional VANET still has miss-communicational problems - this has lead to problems like 'Directional Hidden Terminal Problem', 'Deafness', 'Un-accuracy Lobe Scopes' and 'High Deployment Cost' being reported in various papers. To establish wellorganized design assessments for a good Directional VANET MAC protocol to overcome these problems, we rearranged and grouped current Directional VANET' qualitative criteria from several current survey papers using these categories- 'Directional Discovery', 'Directional Forwarding' and 'Directional Handover'. In addition, based on the results of the following analysis, we show the essential design concerns that need to be looked at in order to develop a well-designed Directional-VANET MAC protocol. [ABSTRACT FROM AUTHOR]

With the development of AI (artificial intelligence), animation digital publishing has been integrated with intellectualization. This paper adopts the theory of the global value chain, and analyzes the basic structure of the animation publishing value chain. Then focuses on the analysis of digital technology and artificial intelligence technology to play an active role in the topic selection and content customization of animation digital publishing products, optimization of publishing platforms, and user experience of publishing products. Finally, it proposes the use of artificial intelligence data analysis and deep learning technology. The purpose of this paper is to realize the upgrading of animation digital publishing, product upgrading, industrial chain upgrading, and identify some promotion methods for the value chain, such as copyright protection. [ABSTRACT FROM AUTHOR]

In this paper, we propose an advanced Minimum Mean Square Error (MMSE) channel estimation method for IEEE 802.11p/Wireless Access in Vehicular Environments (WAVE) systems. To improve the performance of MMSE method, we apply the Weighted Sum using Update Matrix (WSUM) scheme to the step of calculating the instantaneously estimated channel and then, a time domain selectively averaging method is applied after the WSUM scheme. Based on that, the accuracy of instantaneously estimated channel increases and then, the accuracy of auto covariance matrix also increases. Consequently, we can achieve the performance gain over the conventional MMSE method. Through simulations based on the IEEE 802.11p standard, it is confirmed that the proposed scheme can outperform the existing channel estimation schemes. [ABSTRACT FROM AUTHOR]

Tidal power generation plays a critical role in reducing greenhouse gas emissions. It uses a tidal force generated by gravitational force between the moon, the earth, and the sun. The change of seawater height generates the tide-generating force, and the magnitude of the change is the tide level. The tide level change has the same period as the tide-generating force twice a day, every 29.5 days, every year, and every 18.6 years. Sihwa Lake Tidal Power Station is Korea's first tidal power plant that began commercial power generation in August 2011 and has been accumulating a large volume of data on electricity production, power generation sales, sluice displacement, and tide levels. The purpose of this paper was to analyze the impact of the inefficiency factors affecting production and the tidal level change on tidal power generation and their characteristics using Sihwa Lake Tidal Power's operational performance data. Throughout this paper we show that tidal power generating operation is accurately predicting the trends of magnitude of tidal force to be periodical for each day. determining the drop to initiate the water turbine generator factoring the constraints on the operation of Sihwa Lake, and reflecting the water discharge through the floodgate and water turbine during the standby mode in the power generation plan to be in the optimal condition until the initiation of the next power generation can maximize power generation. [ABSTRACT FROM AUTHOR]

To improve the cooperation ability of emergency entities, in this research, the emergency activities model, skill contribution degree, entity-relationship strength, activity continuity, and emergency entity cooperation degree were defined. Emergency entity cooperation degree and emergency activity continuity table were constructed with emergency cases, emergency plans, and emergency drill plans, and factors were further excavated which affected them. In this paper, we focus on the factors which affect the cooperation ability of emergency entities, the relationship between the emergency cooperation ability and the number of cooperation, entity-relationship intensity, emergency activity frequency, and skill contribution of fire entities and medical entities were obtained. These data results are of great significance to decision-makers in formulating emergency rescue and emergency plans. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The 2020 US Presidential Election was a highly-anticipated moment for our global society. During the election period, the most intriguing issue was who would be the winner--Trump or Biden Among the possible main themes of the 2020 election, from the COVID-19 pandemic to racism, this study focused on feminism ('women') as a main component of Biden's victory. To explore the character of Biden's supporters, this paper focused on internet spaces as a source of public opinion. To guide the data analysis, this study employed four indices from empirical studies on Big Data analytics: issue salience, attention diversity, emotional mentioning, and semantic cohesion. The main finding of this study was that the representative keyword 'women' appeared more prevalently within content related to Biden than Trump, and the keyword pairs indicated that female voters were the main reason for Trump's failure but the root cause of Biden's victory. The results of this study indicated the role of the internet as a forum for public opinion and a fountain of political knowledge, which requires more rigorous investigation by researchers. [ABSTRACT FROM AUTHOR]

Children's understanding and inheritance of traditional Chinese culture and innovation of Chinese children's picture book art form are of great significance to carry forward traditional culture and strengthen confidence in Chinese culture. As an excellent traditional Chinese opera art, Beijing Opera has an indispensable cultural status. The purpose of this study was to determine cognitive needs of children in view of simplified display form of children's picture books in China through decomposition, extraction, reconstruction, and integration of the Peking Opera character modeling elements, the use of modern design concepts, and the combination of artistic characteristics of picture books. It explored new ideas for the development of traditional culture, proposed application principles, and suggested strategies for the form innovation of children's picture books to make Beijing Opera enter children's life from the traditional stage. [ABSTRACT FROM AUTHOR]

With love as the theme and mythology, ghosts and magic as elements, Korean fantasy TV dramas have set romantic and beautiful plots and attracted a large number of Chinese female audiences. Based on Melodramatic Imagination and Stuart Hall's theory of "encoding/decoding", this paper investigated Chinese female audiences' motives of watching Korean fantasy TV dramas Hotel Druena through the form of focus group interviews to interpret reasons for the popularity of Korean fantasy TV dramas and Chinese women's overall cognition of Korean TV dramas from the perspective of female audiences. Thinking that South Korea's fantasy dramas are good at women's pursuit and desire for emotional elements, women who watch this type of south Korean TV dramas are temporarily relieving pressure of real life, thus satisfying the needs of female gaze and consumption. [ABSTRACT FROM AUTHOR]

Today, cars have developed into intelligent automobiles that combine advanced control equipment and IT technology to provide driving assistance and convenience to users. These vehicles provide infotainment services to the driver, but this does not improve the safety of the driver. Accordingly, V2X communication, which forms a network between a vehicle and a vehicle, between a vehicle and an infrastructure, or between a vehicle and a human, is drawing attention. Therefore, various techniques for improving channel estimation performance without changing the IEEE 802.11p standard have been proposed, but they do not satisfy the packet error rate (PER) performance required by the C-ITS service. In this paper, we analyze existing channel estimation techniques and propose a new channel estimation scheme that achieves better performance than existing techniques. It does this by applying the updated matrix for the data pilot symbol to the construct data pilot (CDP) channel estimation scheme and by further performing the interpolation process in the frequency domain. Finally, through simulations based on the IEEE 802.11p standard, we confirmed the performance of the existing channel estimation schemes and the proposed channel estimation scheme by coded PER. [ABSTRACT FROM AUTHOR]

A citation analysis utilizes the relations among citations and is the most popular bibliometric method. This analysis is based on 1) the evaluation by paper, journal and researcher of the research output, 2) the identification of emerging research topics, 3) the production of a map of the intellectual structure of the research domain and 4) various services for academic information. However, this approach has a limitation in that a citation is treated in a very simple manner, even though the purpose of citation can vary greatly. To address this problem, new approaches have been studied that take into account the citation context. This research separates the citations according to the citation functions and tries to conduct an analysis according to the newly classified citations. Furthermore, research on the citation summarization and visualization based on both the citation context and the citation function of the citations was also attempted. However, since there are very few studies related to citation context in South Korea, more research and development is needed in this area. This study analyzes the status of the research in terms of the citation context. For this, we utilized social network analysis methods. [ABSTRACT FROM AUTHOR]

Industrial integration is the innovative embodiment of regional economic theory. The promotion of industrial integration is conducive to improving the scale effect and spillover effect of the industry. Also, it has the power to radiate, drive, and lead the innovation and development of the whole industrial cluster. The purpose of this paper was to identify the most suitable development pattern of the ice-snow sports tourism industry in Zhangjiakou, one of the host cities of the 2022 Winter Olympics. This study combs the characteristics of the development of the ice-snow sports industry, and analyzes the current situation of the industry in Zhangjiakou based on the SWOT-AHP method. This paper argues that the integrated industry is the most suitable development pattern for the promotion of the ice-snow culture industry in Zhangjiakou. The following content will present effective countermeasures to accelerate the development of the ice-snow culture industry integration in Zhangjiakou from three aspects: industrial resource integration, industrial chain layout, and scientific and technological innovation. The IT live simulation technique facilitates identifying some vital elements during the data collection. [ABSTRACT FROM AUTHOR]

As the elderly population is becoming an aging society, the elderly are experiencing many problems. Social security costs for the elderly are increasing and the un-linked social phenomenon is emerging. Thus, the social infrastructure and welfare system established in the past economic growth period are in danger of not functioning properly. People socially isolated or with chronic diseases among the elderly are exposed to various accidents. Thus, an active healthcare management service is imperative. Additionally, in the event of a dangerous situation, the system must have ways to notify guardians (family or medical personnel) regarding appropriate action. Thus, in this paper, we propose the smartphone-based healthcare and emergency response service platform. The proposed service platform aggregates movement of relevant data in real-time using a smartphone. Based on aggregated data, it will always recognize the user's movements and current state using the human motion recognition mechanism. Thus, the proposed service platform provides real-time status monitoring, activity reports, a health calendar, location-based hospital information, emergency situation detection, and cloud messaging server-based efficient notification to several subscribers such as family, guardians, and medical personnel. Through this service, users or guardians can augment the level of care for the elderly through the reports. Also, if an emergency situation is detected, the system immediately informs guardians so as to minimize the risk through immediate response. [ABSTRACT FROM AUTHOR]

This is an integrative review paper of Augmented Reality (AR)/Virtual Reality (VR) simulation programs in the mental health area including the analysis of the general characteristics, contents, and the impact of the interventions studies. The keywords used to search the studies were "AR/VR" and "medical/nursing students". The author and a postdoctoral research fellow searched four electronic databases: Web of Science, PubMed, EmBase, and CINHA, and as a result nine studies met the inclusion criteria. Among the selected studies AR/VR simulation programs in the mental health area for healthcare professionals were found to be effective in clinical skills as well as for the interpersonal relationship and the stigma of mentally ill patients. Providing an opportunity to experience a safe and effective tool is important when educating health professionals and AR/VR simulation programs are safe and effective. Thus, standardized AR/VR simulation programs are needed to be developed for health professionals. [ABSTRACT FROM AUTHOR]

As the recent developments of artificial intelligence, particularly machine-learning, impact every aspect of society, they are also increasingly influencing creative fields manifested as new artistic tools and inspirational sources. However, as more artists integrate the technology into their creative works, the issues of diversity and fairness are also emerging in the AI-based creative practice. The data dependency of machine-learning algorithms can amplify the social injustice existing in the real world. In this paper, we present an interactive visualization system for raising the awareness of the diversity and fairness issues. Rather than resorting to education, campaign, or laws on those issues, we have developed a web & ML-based interactive data visualization system. By providing the interactive visual experience on the issues in interesting ways as the form of web content which anyone can access from anywhere, we strive to raise the public awareness of the issues and alleviate the important ethical problems. In this paper, we present the process of developing the ML-based interactive visualization system and discuss the results of this project. The proposed approach can be applied to other areas requiring attention to the issues. [ABSTRACT FROM AUTHOR]

To address the limitations of the traditional RBAC (Role-Based Access Control) model, particularly its inability to fulfill the requirements for hierarchical permissions and dynamic management in a business approval system, this paper introduces a new role-based access control model. This novel model is capable of dynamically creating, assigning, or revoking permissions, thereby achieving resource separation and multilevel permission management effectively. To demonstrate the model's feasibility, we applied it to a practical project. In this project, the JavaScript scripting language and the widely-used SSH (Struts2, Spring, Hibernate) framework were employed to implement the new model, which showcases enhanced capabilities in multi-level and dynamic multi-role permissions management. [ABSTRACT FROM AUTHOR]

The health of the human heart is commonly measured using ECG (Electrocardiography) signals. To identify any anomaly in the human heart, the time-sequence of ECG signals is examined manually by a cardiologist or cardiac electrophysiologist. Lightweight anomaly detection on ECG signals in an embedded system is expected to be popular in the near future, because of the increasing number of heart disease symptoms. Some previous research uses deep learning networks such as LSTM and BiLSTM to detect anomaly signals without any handcrafted feature. Unfortunately, lightweight LSTMs show low precision and heavy LSTMs require heavy computing powers and volumes of labeled dataset for symptom classification. This paper proposes an ECG anomaly detection system based on two level BiLSTM for acceptable precision with lightweight networks, which is lightweight and usable at home. Also, this paper presents a new threshold technique which considers statistics of the current ECG pattern. This paper’s proposed model with BiLSTM detects ECG signal anomaly in 0.467 ~ 1.0 F1 score, compared to 0.426 ~ 0.978 F1 score of the similar model with LSTM except one highly noisy dataset. [ABSTRACT FROM AUTHOR]

Subject classification of journals is important because it can be utilized for the improvement of scholarly information services and analysis by research area. The classification by experts in a subject area wastes a lot of time and expense. On the other hand, the simple classification with basic information, such as the journal title has limitations. To solve this problem, this paper suggests the automatic classification of Korean journals using the SCI journals information cited by Korean journals, and an analysis of the classification result. In particular, this study adopted the WoS subject categories for classification to support the base for comparison between the Korean citation database and the global citation database (KSCI vs. SCI). [ABSTRACT FROM AUTHOR]

This paper proposes an approach for visualizing research trends using theme maps and extra information. The proposed algorithm includes the following steps. First, text mining is used to construct a vector space of keywords. Second, correspondence analysis is employed to reduce high-dimensionality and to express relationships between documents and keywords. Third, kernel density estimation is applied in order to generate three-dimensional data that can show the concentration of the set of documents. Fourth, a cartographical concept is adapted for visualizing research trends. Finally, relative vitalization information is provided for more accurate research trend analysis. The algorithm of the proposed approach is tested using papers about Traditional Korean Medicine. [ABSTRACT FROM AUTHOR]

This paper presents a novel method to design and implement mobile u-health system by defining the essential elements of mobile healthcare services. We choose common service elements for the proposed u-healthcare scheme and design the service platform. Especially we focus on automatic feces or urine sensing u-care scheme to prove the effectiveness of our platform. We construct the system with sensing part with a manikin and a diaper, wireless communication part with feces or urine sensing data, and coordinator system based on the u-health platform defined in this paper. Experimental results show that our scheme is useful in the area of u-care service for the handicapped, the elderly, and patients who can hardly move by themselves. In addition the designed scheme offers a realized u-care scheme with the purpose of advanced developing tools for application or service developers. [ABSTRACT FROM AUTHOR]

Despite their various similarities, Seoul's' Gangnam and Seocho districts showed different patterns in the adoption of the RFID household-based waste charging system. Gangnam, one of the 25 wealthiest districts in Seoul, first adopted the RFID system in 2012, but decided abandon it a year later due to inconvenience, sanitation, budget limitations, and management related issues. Unlike Gangnam, Seocho, a largely similar district to Gangnam, started to implement the RFID system in 2015 and successfully adopted this innovation. In this paper, we explain the adoption behaviors of these two districts using a Technology Hype Curve Model with 5 stages. Unlike traditional technology adoption theory, the Hype Curve Model concentrates on the big chasm between early majorities and late majorities, which is a core reason for discontinuity in innovation diffusion. Based on our case study result, the early majority easily gave up adoption due to immature technological and institutional infrastructure. However, Seocho district, who waited until the deficiencies had been sufficiently fixed since late majorities, succeeded at incremental diffusion. Since its invention by Gartner cooperation, the Hype Curve Model has not received enough attention in academia. This paper demonstrates its explanatory power for innovation diffusion. Similarly, this paper focuses on the importance of institutional framework in the diffusion of innovation. Lastly, we compare the behavior of two local governments in supporting and diffusing RFID systems to draw relevant policy implications for innovation diffusion. [ABSTRACT FROM AUTHOR]

Recently, HTTP Adaptive Streaming(HAS), a video streaming service over the HTTP based web platform has become common. The use of HAS service in mobile communication devices such as mobile phones and tablet PCs is rapidly expanding. This paper addresses ways to improve the quality of HAS service by enhancing the terms of viewer satisfaction. HAS systems have several internal operational processes, which can affect viewer satisfaction. Such processes include, the quality determination for the next video chunk, the TCP connections-setup procedure and the congestion control operation of the TCP. This paper proposes a transmission scheme to improve the HAS quality services over mobile web. The proposed scheme takes into consideration the past implicit communication state of the receiver's playback buffer occupancy. The results of these experiments indicate that the proposed scheme can improve the quality of HAS service from the mobile viewer's point of view. [ABSTRACT FROM AUTHOR]

In this study, articles of the science and technology field that had been monitored for the period from 2002 to 2013 using GTB (Global Trends Briefing) were analyzed. Specifically, the VOSviewer was used to analyze the annual science and technology trends by keyword and the science and technology standard-classification information indicated in the GTB articles, and the convergence trends were therefore monitored. The findings of this study show that active studies were under way in the fields of material science and new and renewable energy, and that convergence has progressed. This result indicates that the information of the articles on papers and patents is more reliable, as it can reflect the current trends more rapidly in the science and technology field than the paper information or the patent information that is traditionally used in analyses of science and technology information. [ABSTRACT FROM AUTHOR]

Tensor with missing or incomplete values is a ubiquitous problem in various fields such as biomedical signal processing, image processing, and social network analysis. In this paper, we considered how to reconstruct a dataset with missing values by using tensor form which is called tensor completion process. We applied Tucker factorization to solve tensor completion which was built base on optimization problem. We formulated the optimization objective function using components of Tucker model after decomposing. The weighted least square matric contained only known values of the tensor with low rank in its modes. A first order optimization method, namely Nonlinear Conjugated Gradient, was applied to solve the optimization problem. We demonstrated the effectiveness of the proposed method in EEG signals with about 70% missing entries compared to other algorithms. The relative error was proposed to compare the difference between original tensor and the process output. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to explore how the Confucius Institute Chinese international promotion could better promote the development of China's foreign trade, by analyzing the distribution of the Confucius Institute worldwide, based on the theory of language economics, using SWOT analysis to analyze the advantages and disadvantages of the internal environment, opportunities and challenges of the external environment of Chinese international promotion of Confucius Institute. The following findings were gathered: as a language teaching institution and information exchange platform, Confucius Institute has the ability to share trade information and increase trade opportunities; to improve cultural identity and reduce transaction costs; to promote cultural communication and integration, and drive the development of related industries. The internal disadvantages were mainly reflected in the mismatch between the global regional distribution structure of Confucius Institutes, and the economic and trade structure, such as, the asymmetry between language, culture output, and demand. In addition, the management mechanism was not perfect. External opportunities were mainly new opportunities brought by economic globalization, cultural diversity, and the development of the Belt and Road initiative. External challenges were mainly influenced by the China threat theory and the fierce cultural competition among countries. The corresponding countermeasures were put forward based on the advantages of the platform and grasping the external opportunities: improving the quality of operation and speeding up the localization process; respecting cultural differences and realizing cultural common learning; seeking multilateral cooperation and enhancing the capacity for independent development. [ABSTRACT FROM AUTHOR]

Management systems for electronic library have been developed on the basis of Client/Server or ASP framework in domestic market for a long time. Therefore, both service provider and user suffer from their high cost and effort in management, maintenance, and repairing of software as well as hardware. Recently in addition, mobile devices like smartphone and tablet PC are frequently used as terminal devices to access computers through the Internet or other networks, sophisticatedly customized or personalized interface for n-screen service became more important issue these days. In this paper, we propose a new scheme of integrated management system for electronic library based on SaaS and Web Standard. We design and implement the proposed scheme applying Electronic Cabinet Guidelines for Web Standard and Universal Code System. Hosted application management style and software on demand style service models based on SaaS are basically applied to develop the management system. Moreover, a newly improved concept of duplication check algorithm in a hierarchical evaluation process is presented and a personalized interface based on web standard is applied to implement the system. Algorithms of duplication check for journal, volume/number, and paper are hierarchically presented with their logic flows. Total framework of our development obeys the standard feature of Electronic Cabinet Guidelines offered by Korea government so that we can accomplish standard of application software, quality improvement of total software, and reusability extension. Scope of our development includes core services of library automation system such as acquisition, list-up, loan-and-return, and their related services. We focus on interoperation compatibility between elementary sub-systems throughout complex network and structural features. Reanalyzing and standardizing each part of the system under the concept on the cloud of service, we construct an integrated development environment for generating, test, operation, and maintenance. Finally, performance analyses are performed about resource usability of server, memory amount used, and response time of server etc. As a result of measurements fulfilled over 5 times at different test points and using different data, the average response time is about 62.9 seconds for 100 clients, which takes about 0.629 seconds per client on the average. We can expect this result makes it possible to operate the system in real-time level proof. Resource usability and memory occupation are also good and moderate comparing to the conventional systems. As total verification tests, we present a simple proof to obey Electronic Cabinet Guidelines and a record of TTA authentication test for topics about SaaS maturity, performance, and application program features. [ABSTRACT FROM AUTHOR]

For 3D display applications, auto-stereoscopic display methods that can provide 3D images without glasses have been actively developed. This paper is concerned with developing a display system for elemental images of real space using integral imaging. Unlike the conventional method, which reduces a color image to the level as much as a generated depth image does, we have minimized original color image data loss by generating an enlarged depth image with interpolation methods. Our method was efficiently implemented by applying a GPU parallel processing technique with OpenCL to rapidly generate a large amount of elemental image data. We also obtained experimental results for displaying higher quality integral imaging rather than one generated by previous methods. [ABSTRACT FROM AUTHOR]

In this paper, we design and implement a distributed, moving objects management system for processing locations and sensor data from smart black boxes. The proposed system is designed and implemented based on Apache Kafka, Apache Spark & Spark Streaming, Hbase, HDFS. Apache Kafka is used to collect the data from smart black boxes and queries from users. Received location data from smart black boxes and queries from users becomes input of Apache Spark Streaming. Apache Spark Streaming preprocesses the input data for indexing. Recent location data and indexes are stored in-memory managed by Apache Spark. Old data and indexes are flushed into HBase later. We perform experiments to show the throughput of the index manager. Finally, we describe the implementation detail in Scala function level. [ABSTRACT FROM AUTHOR]

With the rapid growth of genomic data, new requirements have emerged that are difficult to handle with big data storage and analysis techniques. Regardless of the size of an organization performing genomic data analysis, it is becoming increasingly difficult for an institution to build a computing environment for storing and analyzing genomic data. Recently, cloud computing has emerged as a computing environment that meets these new requirements. In this paper, we analyze and compare existing distributed and parallel NGS (Next Generation Sequencing) analysis based on cloud computing environment for future research. [ABSTRACT FROM AUTHOR]

Due to resource constraints, most of Android application developers need to address potential performance problems during application development and maintenance. The coding styles and patterns of Android programming could often affect the execution time and energy efficiency which are utilized by the Android applications. Thus, it is necessary for application developers to apply performance-enhancing programming practices for mobile application development. This paper introduces performance-enhancing best practices for Android programming, and further, it evaluates the impact of these practices on the CPU time of the application. The original version with the performance-worsening code has been refactored to become an efficient version without changing its functionality. To demonstrate the efficiency of the proposed approach, each coding pattern was evaluated by measuring the CPU time under the controlled runtime environment. Furthermore, the Android applications were evaluated and compared via the CPU time of the original version, with that of the refactored version. These experimental results indicate that, by -using the proposed programming practices, the Android developer can develop performance-efficient mobile applications. [ABSTRACT FROM AUTHOR]

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". [ABSTRACT FROM AUTHOR]

This paper aims to propose the educational concept and design model of a Smart Board Game appropriate for lower elementary grade students. The Smart Board Game refers to a hybrid, or 'convergent', game format based on the offline format of the conventional board game augmented through the use of smart devices. The substantive aspects of this game format utilize the procedural deduction and problem-solving skills applicable in storytelling methodologies and games, in order to generate and propose contents ideal for the educational environment. The development of the Smart Board Game is conducted through the following stages. First, the study analyzes a number of Smart Board Games currently popular in Korea and abroad, based on identification of the key components and processes of the board game format. The subsequent review of the science curriculum for lower elementary grades aims to determine the aspects conducive for application to Smart Board Games. Lastly, the theoretical framework outlined through the previous stages is used as the basis for the proposal of a detailed model of contents for the smart board game concept. [ABSTRACT FROM AUTHOR]