Shapelet-based time series classification methods are widely adopted models for time series classification tasks. However, the high computational cost greatly limits the practicability of the Shapelet-based methods. What is more, traditional Shapelet...
The gravity model developed in the series of papers (Arbuzov et al. 2009; 2010), (Pervushin et al. 2012) is revisited. The model is based on the Ogievetsky theorem, which specifies the structure of the general coordinate transformation group. The the...
Accurately forecasting carbon emission trends in China’s power sector is of great significance for achieving the “dual-carbon” goals, optimizing the energy structure, and formulating low-carbon development strategies. This paper aim...
This study introduces a novel forecasting framework that identifies and predicts recurrently emerging structural patterns in stock trends using rising visibility graphs (RVGs) and the Weisfeiler–Lehman (WL) subtree kernel. The proposed method,...
Modeling the brain dependence network is central to understanding underlying neural mechanisms such as perception, action, and memory. In this study, we present a broad range of statistical methods for analyzing dependence in a brain network. Leverag...
This study introduces an innovative scheme for classifying uncrewed aerial vehicle (UAV)-derived vehicle trajectory behaviors by employing machine learning (ML) techniques to transform original trajectories into various sequences: space–time, s...
Wearable inertial sensing and markerless vision are increasingly integrated to enable objective assessment of locomotor and postural function for sports telerehabilitation, intelligent physiotherapy, and athlete performance monitoring. Before such mu...
In a search for novel therapeutic options for head and neck squamous cell carcinomas (HNSCCs) generally treated with limited therapeutic success, we synthesized a series of novel erlotinib–chalcone molecular hybrids with 1,2,3-triazole and alky...
Background/Objectives: The immunoglobulin heavy-chain variable (IGHV) gene repertoire represents a characteristic feature of chronic lymphocytic leukemia (CLL), although its configuration is not well defined at the early disease stages. The IGHV repe...
This study presents a systematic comparative benchmark between two distinct paradigms for solving nonlinear partial differential equations (PDEs): the data-driven Physics-Informed Neural Networks (PINNs) and the analytical Homotopy Analysis Method (H...