Point clouds are a fundamental sensing modality for object perception, scene understanding, and robotic interaction in modern three-dimensional sensing systems. Effective point-cloud understanding requires representations that preserve intrinsic geom...
Autoencoder-based models have become a fundamental component of unsupervised and self-supervised learning in natural language processing (NLP), enabling models to learn compact latent representations through input reconstruction. From early denoising...
Multi-objective optimization provides the mathematical foundation for reasoning about trade-offs in complex decision problems, from engineering design to resource allocation. Software testing exemplifies such problems: practitioners must simultaneous...
Tourism destinations are cultural heritage and spatial landscape systems of organic coexistence between humans and the Earth, and are formed through the long historical evolution of a specific geographical environment. With the development of large-s...
Digital twins are essential in Agriculture 5.0, providing an accurate digital representation of agricultural objects and processes, enabling data-driven decision-making, the simulation of future scenarios, and innovation for a more efficient and sust...
Background: While region-based models have informed pain neuroscience, chronic pain is now increasingly conceptualized as a network disorder. This narrative review aimed to critically examine the conceptual evolution of chronic pain models from regio...
Driven by the recent technological advancements within the field of artificial intelligence research, deep learning has emerged as a promising representation learning technique across all of the machine learning classes, especially within the reinfor...
The regional differences in the Yellow River Basin have increased, and the aggravation of this unbalanced state has seriously restricted the high-quality development of the Yellow River Basin during the accelerated urbanisation that has taken place i...
Rotating machinery prognostics is essential for ensuring the reliability and operational safety of industrial systems. Although gated recurrent units (GRUs) have achieved competitive performance in remaining useful life (RUL) prediction, whether thei...
Global industry is at the heart of its fourth industrial revolution, being driven by the emergence of new digital solutions: Augmented reality allows us to consider the evolution towards the “the augmented operator”. This technology is cu...
Traditional ethnographic methods have long been employed to study craft practices, yet they often fall short of capturing the full depth of embodied knowledge, material interactions, and procedural workflows inherent in craftsmanship. This paper intr...
Manufacturing systems are undergoing a fundamental transition as efficiency-driven optimisation paradigms prove increasingly inadequate for meeting net-zero, resource-efficiency, and resilience objectives. Digital twins have emerged as a central enab...
This research concerns the issue of landscape risk due to the progressive spread of construction in rural areas through the creation of a “site-specific” analysis and evaluation model and its application to the context of the municipal ar...
Ordered-risk assessment is a safety-critical learning problem in which delayed or biased risk estimation can affect prioritization and response planning. Existing expert-knowledge and data-driven approaches face a trade-off among transparent indicato...
We are currently witnessing an unprecedented era of digital transformation in sports, driven by the revolutions in Artificial Intelligence (AI), Virtual Reality (VR), Augmented Reality (AR), and Data Visualization (DV). These technologies hold the pr...
Intelligent perception systems are essential for precision agriculture, yet their deployment in agricultural field environments is significantly challenged by dense target occlusion and strict resource constraints on edge devices. To address this iss...