Gamification in mobile apps has a research gap, given the potential for gamification to enhance user repurchase intention in a mobile commerce context. This research investigates the concept of gamified m-commerce platform application through the lenses of customer experience and repurchase intention. The study proposes an empirical model to examine the relationship between hedonic value, utilitarian value, customer experience, and repurchase intention in the context of mobile commerce platform application. It is underscoring the importance of exploring the application of gamified m-commerce platforms and their impact on customer experience and repurchase intention. The findings contribute to the existing body of literature on online retail by offering new insights into the implications of gamified m-commerce platform applications. A quantitative research approach was employed, and an online questionnaire was used to gather data. The collected data from a sample of 270 mobile commerce shoppers was analyzed. The results supported all direct hypothesized associations among variables.

Lung cancer has been the leading cause of cancer death for many decades. With the advent of artificial intelligence, various machine learning models have been proposed for lung cancer detection (LCD). Typically, challenges in building an accurate LCD model are the small‐scale datasets, the poor generalizability to detect unseen data, and the selection of useful source domains and prioritization of multiple source domains for transfer learning. In this paper, a multiround transfer learning and modified generative adversarial network (MTL‐MGAN) algorithm is proposed for LCD. The MTL transfers the knowledge between the prioritized source domains and target domain to get rid of exhaust search of datasets prioritization among multiple datasets, maximizing the transferability with a multiround transfer learning process, and avoiding negative transfer via customization of loss functions in the aspects of domain, instance, and feature. In regard to the MGAN, it not only generates additional training data but also creates intermediate domains to bridge the gap between the source domains and target domains. 10 benchmark datasets are chosen for the performance evaluation and analysis of the MTL‐MGAN. The proposed algorithm has significantly improved the accuracy compared with related works. To examine the contributions of the individual components of the MTL‐MGAN, ablation studies are conducted to confirm the effectiveness of the prioritization algorithm, the MTL, the negative transfer avoidance via loss functions, and the MGAN. The research implications are to confirm the feasibility of multiround transfer learning to enhance the optimal solution of the target model and to provide a generic approach to bridge the gap between the source domain and target domain using MGAN.

This paper explores the potential of utilizing semantic web technologies to improve class management in Chinese schools. By analyzing a comprehensive dataset obtained from the Scopus database, the study investigates publication trends, document types, keyword distributions, and author contributions in the field of semantic web technologies for class management. The findings reveal a growing interest in this research area and highlight the benefits of semantic web technologies in personalized learning, information retrieval, collaboration, and assessment. The paper discusses the practical implications, challenges, and considerations for implementing semantic web technologies in Chinese schools. It aims to provide valuable insights for educators, researchers, policymakers, and educational technology practitioners interested in enhancing class management practices through the innovative use of semantic web technologies.

This paper delves into the dynamic intersection of athletic psychology and emerging technologies, aiming to understand their interplay and implications for sports performance. The study examines the latest research and literature in this field, encompassing the use of social media, digital devices, and virtual reality as technological advancements. It explores the impact of these technologies on athlete psychology, mental resilience, motivation, and goal setting. By analyzing country-specific scientific production, author contributions, and keyword trends, the paper provides insights into the global landscape of research in athletic psychology and emerging technologies. The findings contribute to a better understanding of the evolving relationship between technology and athlete psychology, offering potential avenues for optimizing performance, mental well-being, and training strategies in the realm of sports.

The implementation of industrial robots across various sectors has ushered in unparalleled advancements in efficiency, productivity, and safety. This paper explores the domain of semantic trajectory planning in the area of industrial robotics. By adeptly merging physical constraints and semantic knowledge of environments, the proposed methodology enables robots to navigate complex surroundings with utmost precision and efficiency. In a landscape marked by dynamic challenges, the research positions semantic trajectory planning as a linchpin in fostering adaptability. It ensures robots interact safely with their surroundings, providing vital object detection and recognition capabilities. The proposed ResNet model exhibits remarkable classification performance, bolstering overall productivity. The study underscores the significance of this approach in addressing real-world industrial applications while emphasizing accuracy, precision, and enhanced productivity.

The emergence of the metaverse, a virtual reality space, has ushered in a new era of digital experiences and interactions in global information systems. With its unique social norms and behaviors, this new world presents exciting opportunities for users to connect, socialize, and explore. However, as people spend more time in the metaverse, it has become increasingly apparent that the issue of cyberbullying needs to be addressed. Cyberbullying is a serious problem that can harm victims psychologically and physically. It involves using technology to harass, intimidate, or humiliate individuals or groups in global information systems. The risk of cyberbullying is high in the metaverse, where users are often anonymous. Therefore, it is crucial to establish a safer and more respectful culture within the metaverse to detect and prevent such incidents from happening.