Earticle

This study conducts a comparative analysis of various models for predicting Bitcoin prices. The models utilized in this research include the Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM), and Random Forest. Their performance was evaluated using key metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R-squared (R²). The findings reveal that the GRU model outperformed the other two models, achieving an R² value of 0.9301, which indicates its superior ability to explain the data. The LSTM model demonstrated relatively high explanatory power with an R² of 0.8252, yet it exhibited lower predictive accuracy compared to the GRU. On the other hand, the Random Forest model recorded the lowest MAE (1557.44) and RMSE (1766.95), reflecting strong short-term prediction capabilities. However, its R² of 0.6110 highlighted limitations in capturing the intricate temporal patterns of the dataset. The significance of this study lies in several aspects. First, it empirically demonstrates that the GRU model, with its more streamlined architecture, can achieve superior predictive performance compared to the LSTM and Rando Forest models. Additionally, while Random Forest showed promising results for short-term predictions, it underscored limitations in modeling the complexities of temporal data patterns. Future research should aim to incorporate broader datasets and integrate external economic variables to enhance predictive accuracy. Furthermore, the potential of ensemble approaches, combining diverse models, holds promise for further improving predictive performance in this domain.

This study analyzed the internal changes and narrative structure of the main character Pou through the Kung Fu Panda series, and explored how his growth process is connected to the fulfillment of human desires and the process of psychological development. To this end, we applied Greimas's actant model, Maslow's need theory, and the Enneagram personality type theory to specifically analyze how the narrative structure of each series is connected to the psychological transformation of the main character's growth process. The results of the study showed that Pou's growth goes beyond simple external success and includes internal changes and psychological maturity, and shows a gradual process that is consistent with Maslow's level of needs. In the first part, Poe is an optimistic and passionate dragon warrior. He satisfies his needs for belonging and love. In the second part, he becomes confused due to his curiosity about his past, but overcomes his internal conflict through training. In the process, Poe finds his inner self and satisfies the need for esteem. In the third part, he protects Panda Village from the villain Kai with the help of the pandas, defeats the villain, and protects the village. In the process, he satisfies his need for self-esteem. In the fourth part, Poe's altruistic appearance of raising a successor goes beyond the self-actualization stage, and his actions of sharing his accomplishments with others for the sake of the village community satisfies his need for more in-depth self-actualization.

Hong Kong cinema has undergone significant changes, shifting from an actor-driven, story-rich industry to one influenced by large-scale productions and global trends. This study applies topic modeling to analyze audience reviews of Hong Kong films from two periods: pre-2000 and post-2000. Using Latent Dirichlet Allocation (LDA), it identifies key thematic changes, highlighting a decline in acting quality and storytelling depth. Findings indicate that pre-2000 films were praised for strong performances and engaging narratives, while post-2000 films prioritized large-scale productions and high-budget visuals but faced criticism for weaker storytelling and predictable plots. The study suggests that Hong Kong cinema has struggled to retain its distinct identity amid globalization and competition from Hollywood and mainland Chinese productions. To regain its prominence, a balance between high production values and compelling storytelling is necessary. Future research should explore cross-cultural comparisons and industry perspectives to further understand audience engagement trends.

The cryptocurrency market has seen a dramatic surge in value since November 2024, garnering significant attention from scholars and investors alike. In particular, Bitcoin has shown a remarkable rise, with its price surpassing $100,000 by January 2025. This study employs Wavelet Coherence analysis to explore the synchronization of prices among leading cryptocurrencies, including Bitcoin, and applies bubble diagnostic techniques to examine their interconnections. The findings indicate that Bitcoin has notably entered a distinct phase of a price bubble during this period, characterized by a significant decoupling in price movements from other major cryptocurrencies, especially over long-term frequencies. Furthermore, the research highlights a previously dominant trend where Bitcoin led the price movements of other cryptocurrencies. Recently, however, this influence has begun to wane, with each cryptocurrency starting to exhibit more independent price behavior. This decoupling indicates a move towards a less interconnected market structure. Ultimately, the study confirms that price bubbles in specific periods are predominantly driven by Bitcoin, the leading cryptocurrency, rather than by collective market movements. These insights are crucial for assessing the stability of the cryptocurrency market and have important implications for policy-making and future regulatory measures.

This study examines issues arising from AI creation of culture & arts and explores the direction of co-creation between humans and AI. In the era of AI art, the shift in media paradigm not only requires conceptual and theoretical interpretation of creation, but also raises legal and ethical challenges. First, the current status of AI creation in cultural arts. AI assists in the creation of all storytelling, including novels, and is utilized in digital art and art restoration. In addition, stage design and lighting AI technology increases the immersion of performances and creates new forms of art. AI changes the method of artistic creation, and human-AI creations express unique artistic values. Second, issues such as data bias, copyright, and legal and ethical deficiencies are increasing in the AI creative process. Bias and distortion of AI learning data can undermine the fairness and reliability of AI, lead to linguistic and socioeconomic inequality, and cause cultural diversity to be eliminated due to bias toward specific cultures and languages. The legal status of AI creations is unclear, and there are no clear standards for copyright protection, so whether or not they are legally protected is being discussed. Third, the AI creative model for culture & arts should be able to learn effectively with a small amount of data and generate creative contents without copyright infringement. As the integration of AI creation fundamentally changes the way humans interact with digital tools, the co-creation of human-AI is evolving in a direction that goes beyond human creativity. This study did not cover the detailed technical elements of AI. In follow-up studies, it is necessary to closely analyze the implementation method and creative process of the AI model for culture & arts. Although policy response measures for AI creation have been partially discussed, comparative analysis of AI copyright laws by country has not been conducted. In future studies, it is necessary to analyze legal response measures to protect AI products and creators.

The emergence of generative AI, such as ChatGPT, developed based on large language models, has brought significant changes to chatbot technology. Rapid technological advancements have substantially improved the performance and quality of generative AI services and their outputs. As a result, the scope of generative AI utilization by companies is gradually expanding. Building on these technological advancements, this study presents prompt writing strategies for effectively utilizing ChatGPT to develop entrepreneurial business models and derive affordance design strategies. An experimental study compared and analyzed the impact of providing affordances and prompt writing strategies on satisfaction with ChatGPT utilization. The study divided the tasks for developing entrepreneurial business models into data exploration and idea generation. The findings of this study offer important implications for entrepreneurs developing business models by providing practical prompt writing guidelines tailored to specific task characteristics. Additionally, it suggests affordance design strategies for companies offering generative AI services to optimize user experience.

Digital transformation emphasizes digital literacy as an essential skill for modern individuals and has led to the consumption of digital content through digital platforms. This study examined the impact of digital information literacy, digital content creation literacy, digital communication literacy, and digital problem solving literacy on the intention to use digital content, mediated by digital engagement and self-efficacy. The results of the study revealed that digital information literacy, digital content creation literacy, digital communication literacy, and digital problem solving literacy all influenced digital engagement and self-efficacy, and self-efficacy was found to affect digital engagement. Both digital engagement and self-efficacy influenced the intention to use digital content, and it was confirmed that digital information literacy, digital content creation literacy, digital communication literacy, and digital problem solving literacy impacted the intention to use digital content through a sequential mediation effect of self-efficacy and digital engagement. This study suggests that digital literacy can be an important competency in the field of culture and arts, and based on these results, it is expected that future research utilizing digital literacy will be applied and utilized in various domains.