Earticle

Aesthetic education in a variety of forms in the sublimation of the people's feelings, sublimation of the soul. It is of great significance to inherit and develop rural culture and to maintain cultural diversity. At present, rural characteristic industry is an important form of development to promote rural economic development, protect rural cultural diversity and continue rural culture. It is of great practical significance to guide the development direction of rural characteristic industry, strengthen the value connotation of rural characteristic industry and stimulate the endogenous power of rural characteristic industry. At the same time, it is of great significance to promote the development of aesthetic education and broaden the path of aesthetic education.

This study provides academic implications by considering trends of domestic research regarding therapy for Mental disorder schizophrenia and psychosocial. For the analysis of this study, text mining with the use of R program and social network analysis method have been used and 65 papers have been collected The result of this study is as follows. First, collected data were visualized through analysis of keywords by using word cloud method. Second, keywords such as intervention, schizophrenia, research, patients, program, effect, society, mind, ability, function were recorded with highest frequency resulted from keyword frequency analysis. Third, LDA (latent Dirichlet allocation) topic modeling result showed that classified into 3 keywords: patient, subjects, intervention of psychosocial, efficacy of interventions. Fourth, the social network analysis results derived connectivity, closeness centrality, betweennes centrality. In conclusion, this study presents significant results as it provided basic rehabilitation data for schizophrenia and psychosocial therapy through new research methods by analyzing with big data method by proposing the results through visualization from seeking research trends of schizophrenia and psychosocial therapy through text mining and social network analysis.

We studied learners' perceptions and learning styles of project research activities in the chemical field conducted by 54 science high school students. In a survey of students' perceptions of task research, positive responses were found in "internal motivation," "cooperation," "task solving," and "tenacity and immersion," and statistically significant differences were found in "self-directedness," "cooperation," and "tenacity and immersion" by year. The 'lower' group responded most positively in the 'cooperation' category, and the 'higher' group responded most positively in the 'task solving' category. As a result of investigating the learning styles of the students who conducted the task research, it was found in the order of assimilator, converger, accommodator, and diverger. The assimilators showed the characteristic of systematically and scientifically approaching the problem. Convergers were found to have excellent problem-solving and decision-making ability, are practical, and have experimental-based thinking characteristics. In this study, the characteristics of science high school students showed well in the results of the learning style performed.

Since its inception in 2009, medical tourism in South Korea has continued to progress. Reaching its peak in 2019, the industry experienced a sharp decline in inbound patients after the COVID-19 pandemic in 2020 due to international border closures and a surge in patient numbers. However, from 2021 onwards, there has been a gradual increase in inbound patients. The purpose of this study was to classify the top 12 countries based on the number of actual patients entering the country from 2014 to 2022, using statistics from the Korea Health Industry Development Institute. It also analyzed the changes in the number of foreign patients visiting Korea and the evolving proportion of actual patients compared to short-term visa arrivals on a yearly basis. Through this content, we aim to examine the trends on a country-by-country basis and identify the direction in which the future of South Korean medical tourism should progress. By focusing on healthcare, we intend to pinpoint areas that require attention and improvement, as well as highlight any existing issues. Through modifications and enhancements based on these considerations, we aspire to attract a significant number of foreign patients, thereby promoting South Korea's medical technology on a global scale.

Wearable devices, attached to the human body, track and enhance users' activities, health, and communication. Therefore, considering ergonomic factors in product design is crucial. However, previous research has somewhat overlooked the importance of integrating ergonomic design elements into a broad spectrum of design factors. This study aims to examine the impact of physical attributes inherent in smart wristbands and smartwatches on the perceived functional value, specifically, perceived usefulness, ease of use, and fit. A survey was conducted among 289 US adults who had experience using smart wristbands or smartwatches. The collected data were analyzed using descriptive statistics, factor analysis, Cronbach's alpha, t-test, MANOVA, and regression analysis in SPSS version 29. The results showed that the shape of the front display significantly influenced perceived ease of use, and the product's weight had a substantial impact on both perceived ease of use and fit. Furthermore, distinct technical features on the front display had varied effects on perceived usefulness, ease of use, and fit. Notably, the presence of activity tracking, alarm, and calendar functionalities led to distinct differences in ease of use and fit. Features such as distance tracking, phone call, social media notifications, text messaging, and time display functions showed significant influences on the perception of fit. These findings provide insights into the physical values of smart wristbands and smartwatches as perceived by users.

This study aims to predict uncertain future scenarios that may unfold in South Korea in the near future, utilizing the theory of extreme events(X-events). A group of 32 experts, consisting of government emergency planning officers, was selected as the focus group to achieve this objective. Using the Focus Group Interview (FGI) technique, opinions were gathered from this focus group regarding potential X-events that may occur within the advanced science and technology domains over the next 10 years. The analysis of these opinions revealed that government emergency planning officers regarded the "Obsolescence of current technology and systems," particularly in the context of cyber network paralysis as the most plausible X-event within science and technology. They also put forth challenging and intricate opinions, including the emergence of new weapon systems and ethical concerns associated with artificial intelligence (AI). Given that X-events are more likely to emerge in unanticipated areas rather than those that are widely predicted, the results obtained from this study carry significant importance. However, it's important to note that this study is grounded in a limited group of experts, highlighting the necessity for subsequent research involving a more extensive group of experts. This research seeks to stimulate studies on extreme events at a national level and contribute to the preparation for future X-event predictions and strategies for addressing them.

After ‘emphasizing the development of the precision reconnaissance drone’ in 2021, North Korea unveiled two strategic drones in July 2023, just two years later. Despite the majority of experts offering negative assessments and stating that “the performance may not be good,” North Korea can be seen as having not only enhanced its routine surveillance capabilities through strategic drones but also possessing limited long-range strike capabilities. In other words, although the performance of North Korea's strategic unmanned aerial vehicles (UAVs), namely the 'Satbyol-4' and '9' models, may not match that of U.S. drones, they appear to play a significant role in offsetting North Korea's considerable aerial and surveillance inferiority compared to the joint forces of South Korea and the United States. Based on these trends, North Korea seems to be concentrating on drone development to counterbalance its considerable aerial power and surveillance capabilities deficit compared to the joint forces of South Korea and the United States, especially as the global use of drones continues to increase.

Recent advances in augmented reality (AR) and virtual reality (VR) technologies have led to a significant increase in metaverse platforms. Metaverses are setting a new direction for the digital world. This paper examines the phenomenon of virtual worlds that are becoming an issue these days, focusing on [Ready Player One]. One of the common features of the metaverse platform in [Ready Player One] and the platforms currently in use is the concept of open world. This is a feature that goes beyond simply moving around in a virtual world and allows users to freely reset, participate in, and control the environment. This innovative concept is a hallmark of metaverse platforms, and it is becoming increasingly important and influential. Through this study, we focused on the [open world system] of the platform in the movie and the modern metaverse platform, and suggested and studied how the scalability of the metaverse will present a turning point in the future.

The Army has presented eight game-changers for future warfare through 'Army Vision 2050,' including Intelligent Combat Robots, Super Soldiers, Energy Weapons, Hypersonic Weapons, Non-lethal Weapons, Autonomous Mobile Equipment, Intelligent Command and Control Systems, and Energy Supply Systems. This study focuses on Intelligent Combat Robots, considering them as the most crucial element among the mentioned innovations. How will Intelligent Combat Robots be utilized on the future battlefield? The future battlefield is expected to take the form of combined human-robot warfare, where advancements in science and technology allow intelligent robots to replace certain human roles. Especially, tasks known as Dirty, Difficult, Dangerous, and Dull (4D) in warfare are expected to be assigned to robots. This study suggests three forms of Intelligent Robots: humanoid robots, biomimetic robots, and swarm drones.

In three-dimensional(3D) modeling, texturing plays a crucial role as a visual element, imparting detail and realism to models. In contrast to traditional texturing methods, the current trend involves utilizing AI tools such as Leonardo.Ai and Meshy to create textures for 3D models in a more efficient and precise manner. This paper focuses on 3D texturing, conducting a comprehensive comparative study of AI tools, specifically Leonardo.Ai and Meshy. By delving into the performance, functional differences, and respective application scopes of these two tools in the generation of 3D textures, we highlight potential applications and development trends within the realm of 3D texturing. The efficient use of AI tools in texture creation also has the potential to drive innovation and enhancement in the field of 3D modeling. In conclusion, this research aims to provide a comprehensive perspective for researchers, practitioners, and enthusiasts in related fields, fostering further innovation and development in this domain.

In recent years, the rapid development of VR technology has secured its significant position in the gaming industry. This paper selects the PC and VR versions of Resident Evil 4 as the research objects, aiming to compare the similarities and differences between these two platforms. Through this comparative study, it is evident that the PC version of the game offers most players an excellent gaming control experience through precise and flexible operations. On the other hand, the VR version not only achieves immersive gameplay through virtual reality technology but also delivers more impressive visual effects to players. However, in comparison to the traditional PC version, the VR version incurs higher development costs, necessitating the production team to invest more resources to optimize the gaming experience and strike a better balance between immersion and playability. In conclusion, this study provides a valuable reference for game developers, assisting them in meeting the diverse needs of player groups and enhancing game playability and user satisfaction.

With the rapid development of Artificial Intelligence (AI) technology, there is an increasing variety of methods for creating 3D models. These include innovations such as text-only generation, 2D images to 3D models, and combining images with cue words. Each of these methods has unique advantages, opening up new possibilities in the field of 3D modeling. The purpose of this study is to explore and summarize these methods in-depth, providing researchers and practitioners with a comprehensive perspective to understand the potential value of these methods in practical applications. Through a comprehensive analysis of pure text generation, 2D images to 3D models, and images with cue words, we will reveal the advantages and disadvantages of the various methods, as well as their applicability in different scenarios. Ultimately, this study aims to provide a useful reference for the future direction of AI modeling and to promote the innovation and progress of 3D model generation technology.

This study focuses on the art style research of the 3D Animation <Spider-Man: Across the Spider-Verse>, exploring the film’s innovation in art design. The article first analyzes how the movie skillfully blends American comics, watercolor painting style, Pollock drip painting, and ink painting, among other artistic techniques, to present a unique visual experience for the audience. By specifically dissecting the character design and scene composition in the movie, it explores the specific application of these art styles and their methods in digital image production. Ultimately, the paper emphasizes the contribution of <Spider-Man: Across the Spider-Verse> to 3D Animated cinema, particularly its innovation in the field of art design, as well as its inspiration and possibilities for the diversity of art styles in animated films. Overall, this study aims to provide in-depth academic insight into the field of animated film art design and to promote its development and innovation.

During the initial period of the COVID-19 pandemic, governments around the world implemented non-pharmaceutical interventions. For these policy interventions to be effective, authorities engaged in the political discourse of legitimising their activity to generate positive public attitudes. To understand effective COVID-19 policy, this study investigates public attitudes in South Korea, the United Kingdom, and the United States and how they reflect different legitimisation of policy intervention. We adopt a big data approach to analyse public attitudes, drawing from public comments posted on Twitter during selected periods. We collect the number of tweets related to COVID-19 policy intervention and conduct a sentiment analysis using a deep learning method. Public attitudes and sentiments in the three countries show different patterns according to how policy interventions were implemented. Overall concern about policy intervention is higher in South Korea than in the other two countries. However, public sentiments in all three countries tend to improve following implementation of policy intervention. The findings suggest that governments can achieve policy effectiveness when consistent and transparent communication take place during the initial period of the pandemic. This study contributes to the existing literature by applying big data analysis to explain which policies engender positive public attitudes.

In this study, we explore social awareness, interest, and acceptance of generative AI, including chatGPT, which has revolutionized web search, 30 years after web search was released. For this purpose, we performed a machine learning-based topic modeling analysis based on Korean news big data collected from November 30, 2022, when chatGPT was released, to August 31, 2023. As a result of our research, we have identified seven topics related to chatGPT and generative AI; (1)growth of the high-performance hardware market, (2)service contents using generative AI, (3)technology development competition, (4)human resource development, (5)instructions for use, (6)revitalizing the domestic ecosystem, (7)expectations and concerns. We also explored monthly frequency changes in topics to explore social interest related to chatGPT and Generative AI. Based on our exploration results, we discussed the high social interest and issues regarding generative AI. We expect that the results of this study can be used as a precursor to research that analyzes and predicts the diffusion of innovation in generative AI.

The smart tourism service provides tourists with personal travel planner services and context-awareness-based tour guide services. In this paper, we propose the personal travel planner service that creates my travel itinerary using the smart tourism app and the travel planner system. The smart tourism app provides recommended travel products and POI tourist information used to create my travel itinerary. The smart tourism app also provides the smart tourism chatbot service that allows users to select POI tourist information easily and conveniently. The travel planner system consists of the smart tourism information system and the smart tourism chatbot system. The smart tourism information system provides users with travel planner services, recommended travel products, and POI tourism information through the smart tourism app. The smart tourism chatbot system consists of named entity recognition (NER), dialogue state tracking (DST), and Neo4J servers, and provides chatbot services as a smart tourism app. Users can create their own travel itinerary, modify the travel itinerary while traveling, and then register it as a recommended travel product to users, including acquaintances.

Accurate prediction of wind speed and power is vital for enhancing the efficiency of wind energy systems. Numerous solutions have been implemented to date, demonstrating their potential to improve forecasting. Among these, deep learning is perceived as a revolutionary approach in the field. However, despite their effectiveness, the noise present in the collected data remains a significant challenge. This noise has the potential to diminish the performance of these algorithms, leading to inaccurate predictions. In response to this, this study explores a novel feature engineering approach. This approach involves altering the data input shape in both Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) and Autoregressive models for various forecasting horizons. The results reveal substantial enhancements in model resilience against noise resulting from step increases in data. The approach could achieve an impressive 83% accuracy in predicting unseen data up to the 24th steps. Furthermore, this method consistently provides high accuracy for short, mid, and long-term forecasts, outperforming the performance of individual models. These findings pave the way for further research on noise reduction strategies at different forecasting horizons through shape-wise feature engineering.

Alarm system performance is a critical aspect of safety. While existing research has extensively examined the influence of acoustic attributes on alarm performance, consonance’s impact remains largely uncharted territory. This study bridges this research gap by investigating the effect of consonance on alarm systems. We extend our investigation to encompass not only the sound characteristics of the alarm but also the acoustic qualities of the surrounding environment, recognizing their potential impact on alarm efficacy. Prior studies consistently link consonance to annoyance levels, resulting in a negative user experience. Thus, we explore the relationship between consonance and alarm system performance, with a particular focus on modulating annoyance as an explanatory factor. Utilizing an oddball paradigm, we categorized standard and oddball sounds into consonant and dissonant types, creating four sound combinations. Participants were asked to respond to the irregularly presented oddball sounds while ignoring the constantly presented standard sounds. Our results reveal significant differences between groups, with the Standard Consonant/Oddball Dissonant (SC/OD) group displaying notably slower response times than the Standard Dissonant/Oddball Consonant (SD/OC) group. This reaction time variation aligns with differences in annoyance levels, as the SC/OD group reports higher annoyance, suggesting that reaction time discrepancies may be linked to increased arousal due to heightened annoyance.

AI blockchain technology, which is attracting attention as a core technology of the 4th Industrial Revolution, is a technology that can be used as an important means of innovation not only in the current gaming industry but also in various industrial fields. This paper extracts the platforms and types of blockchain games currently ranked within the top 100 on the blockchain app (DApp) sites State Of The DApps, DApp.com, and Dapp Rader and introduces the top games on major platforms. As a result of extracting platforms and types, the top games were mainly based on Ethereum, EOS, and Steam. However, the results showed that there are significantly more games based on the Ethereum platform, which are stable, easy to apply, and have a low barrier to entry due to the large number of users and DApps. We plan to improve awareness of blockchain games by studying the characteristics that only blockchain games have.

Currently , the growth of various platforms is remarkable , both at home and abroad . With the growth of various platforms such as PC, console, and VR as well as mobile, the global gaming industry market size has grown to reach KRW 151 trillion . However , in order to revitalize the domestic game market , which is growing at a slower pace, improve the concentration phenomenon that is concentrated on mobile and PC platforms , and select one of the games using IP that is being discussed as a new breakthrough , and determine what form the game will take. Through this study, we would like to suggest whether multi -platform is appropriate. The Digimon series generally attracts many fans through animation , and the Digimon story Cyber Sleuth, which utilizes new scenarios to satisfy them and arouse interest at the same time , can be seen as a representative success example We believe that through this interaction, users can continue to play the main content on their PC, and create synergy by being able to play and enjoy minimal content through mobile anytime , anywhere while doing other things.

This is a single-group pre-post study conducted to determine the effect of a calligraphy program on nursing students' career decision-making self-efficacy and self- leadership. The data collected from 231 second-year nursing students were analyzed using SPSS WIN 25.0 to determine descriptive statistics, paired t-test to analyze the effect of calligraphy, and Pearson correlation coefficient to determine the relationship between career decision self-efficacy and self-leadership. After the program, both career decision self-efficacy (t=7.23, p<.001) and self-leadership (t=6.81, p<.001) improved. The analysis of career decision self-efficacy and self-leadership after the program showed a strong correlation (r=.849, p<.001). The results of this study are significant in that they validate the effectiveness of a calligraphy program in promoting self-leadership and career decision-making self-efficacy among nursing students who do not have clear career goals. Students' overall satisfaction with the calligraphy program was 4/5 points, and they most highly evaluated the smooth interaction between fellow students through the program. At a time when the importance of cultural arts education is gradually increasing in social and educational fields around the world, calligraphy has the advantage of laying the foundation for the promotion of basic arts for the revitalization of cultural arts, so educational support is needed not only in terms of improving the quality of life and pursuing self-actualization of individuals with emotional expression and creative problem-solving skills, but also at the social level.

From the mid-to-late 2010s, technology was frequently mentioned in the definition of digital transformation. In the early stages, the private sector started actively using it, and the public sector started to take it seriously. Divided into “providing value and cultural change, the main goals of digital transformation were accomplished, and the ideas of creating new values in social and industrial systems and applying digital technology appeared to be related. Digital transformation, defined as the idea of combining digital solutions to boost competitiveness and add value, necessitates social innovation and cultural shifts at the national level. In order to encourage the digital transformation of the industry, the Industrial Digital Transformation Promotion Act was passed in December 2021. This set the groundwork for a comprehensive and organized approach to facilitating the use of industrial information. We will examine the nature and extent of digital transformation in this study, as well as discover the organizations and regulations that support it. We also want to examine the essential standards and technologies needed to put the digital transformation plan into practice. Lastly, We’ll make some conclusions about how this will affect public services’ digital transformation.

Artificial Intelligence (AI) technology has recently grown explosively and is being used in a variety of application fields. Accordingly, the number of AI models is rapidly increasing. AI models are adapted and developed to fit a variety of data types, tasks, and environments, and the variety and volume of models continues to grow. The need to share models and collaborate within the AI community is becoming increasingly important. Collaboration is essential for AI models to be shared and improved publicly and used in a variety of applications. Therefore, with the advancement of AI, the introduction of Model Hub has become more important, improving the sharing, reuse, and collaboration of AI models and increasing the utilization of AI technology. In this paper, we collect data on the model hub and analyze the characteristics of the model hub and the AI models provided. The results of this research can be of great help in developing various multimodal AI models in the future, utilizing AI models in various fields, and building services by fusing various AI models.

The purpose of this study is to explore adolescent depression, increase understanding of social problems, and develop prevention and intervention strategies. As a research method, social big data was used to collect information related to 'youth depression', and related factors were identified through data mining and analysis of related rules. We used 'Sometrend Biz Tool' to collect and clean data from the web and then analyzed data in various languages . The study found that online articles about depression decreased during the school holidays (January to March), then increased from March to the end of June, and then decreased again from July. Therefore, it is important to establish a government-wide depression management monitoring system that can detect risk signs of adolescent depression in real time. In addition, regular stress relief and mental health education are needed during the semester , and measures must be prepared to deal with at-risk youth who share their depressed feelings in cyberspace. Results from these studies can be expected to provide important information in investigating and preventing youth depression and to contribute to policy development and intervention.

We conducted this study to identify the components of H&B store app service quality and their effect on customer satisfaction. The survey was conducted through an online survey for teenagers or older with experience in using H&B store app. A total of 330 copies were distributed and a total of 282 copies were used for the final analysis. The results of this study are summarized as follows: First, eight factors such as ease of use & design, fulfillment, playfulness, responsiveness, personalization, security, contextual usefulness, interactivity were derived as service quality components of H&B store app. Second, as a result of regression analysis, the six service quality components, such as ‘ease of use & design’, ‘fulfillment’, ‘playfulness’, ‘responsiveness’, ‘security’, and ‘interactivity’ were found to have a significant positive (+) effect on customer satisfaction (p<0.05) and ‘playfulness (β=.372)’ had the greatest effect on customer satisfaction. Based on the results of this study, we should strive to establish effective marketing strategies in the H&B industry.

As modern society develops, the number of diseases caused by bad smells is increasing. As it can harm people's health, it is important to predict in advance the extent to which bad smells may occur, inform the public about this, and take preventive measures. In this paper, we propose a hybrid neural network structure of CNN and LSTM that can be used to detect or predict the occurrence of odors, which are most required in manufacturing or real life, using odor complex sensors. In addition, the proposed learning model uses a complex odor sensor to receive four types of data, including hydrogen sulfide, ammonia, benzene, and toluene, in real time, and applies this data to the inference model to detect and predict the odor state. The proposed model evaluated the prediction accuracy of the training model through performance indicators based on accuracy, and the evaluation results showed an average performance of more than 94%.