SinoXivNeuroscience and artificial intelligence, the convergence of neuroscience and artificial intelligence has presented revolutionary sports performance optimization. This paper is a comprehensive Neuro. ...
Multimodal music information retrieval has gained significant momentum, producing a wide range of datasets for machine learning and deep learning tasks. However, these resources remain overwhelmingly ...
As a key branch of probability theory and mathematical statistics, probability limit theory focuses on analyzing the convergence properties of random variable sequences and their associated distributi...
This study develops and examines a sociotechnical framework for digital government implementation, focusing on how technical, organisational, and institutional conditions shape implementation outcomes...
This study proposes a Machine Learning-Optimized 3D Hybrid Chaotic Map (Logistic–Tent–Hénon–Chebyshev) for secure and energy-efficient encryption of images and multimedia data in resource-constrained ...
This paper proposes a novel deep learning model named RTEU-Transformers (Residual Temporal Enhancement Unit) for abstractive text summarization, specifically applied to the Samsum dataset, which consi...
Data heterogeneity remains one of the most significant challenges in federated learning (FL), impacting model performance, convergence, and scalability. This issue is especially critical in healthcare...
IoT-blockchain convergence has the potential to improve smart agriculture by supporting immutable provenance chains, cryptographic data integrity, and decentralized trust mechanisms across agricultura...
As Large Language Models (LLMs) are increasingly deployed in autonomous, high-stakes environments, the fragility of current Reinforcement Learning from Human Feedback (RLHF) alignment protocols remain...
Mobile health (mHealth) recommender systems for physical activity increasingly employ sophisticated personalization, yet few integrate clinical-guideline-grounded user modeling, explainability, and fa...
