Extracting and analyzing relevant medical information from large-scale databases such as biobanks poses considerable challenges. To exploit such "big data," attempts have focused on large sampling ...

ABSTRACT: Accurate forecasting of diesel prices is essential for Malaysia, where transportation, agriculture, and industry are highly dependent on this fuel. This study investigates the effectiveness ...

Abstract: We propose a low complexity forward selection algorithm for the sparse signal recovery (SSR) problem based on the sparse Bayesian learning (SBL) formulation. The proposed algorithm, called ...

Introduction: Nitrogen plays a pivotal role in determining cotton yield and fiber quality. Nevertheless, because high-dimensional remote-sensing data are inherently complex and redundant, accurately ...

MicroAlgo Inc. announced the integration of its quantum image LSQb algorithm with quantum encryption technology to create a new system for secure information hiding and transmission. This innovative ...

Arid and semiarid regions face challenges such as bushland encroachment and agricultural expansion, especially in Tiaty, Baringo, Kenya. These issues create mixed opportunities for pastoral and ...

Large language models have made remarkable strides in natural language processing, yet they still encounter difficulties when addressing complex planning and reasoning tasks. Traditional methods often ...

Pre-trained LLMs require instruction tuning to align with human preferences. Still, the vast data collection and rapid model iteration often lead to oversaturation, making efficient data selection a ...