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Reservoirs are critical infrastructure for global water, food, and energy security, yet their storage dynamics remain poorly characterized across most of the world. Accurate and timely knowledge of reservoir storage is e...

This paper proposes beam training algorithms for robust line-of-sight (LoS) multi-input and multi-output (MIMO) systems with subarray-based beamforming functionality at both the transmitter (TX) and receiver (RX). In gen...

Few-shot object detection (FSOD) recently garnered increasing attention in remote sensing images (RSIs). Although FSOD has achieved success in natural sense, the large size and complex backgrounds of RSIs make FSOD espec...

Dairy farms increasingly deploy sensor networks that generate high-frequency behavioral and spatial data, yet translating these multimodal streams into actionable welfare insights remains a key challenge. This study pres...

Heart disease is rapidly increasing. For early and accurate prediction, advanced machine learning (ML) models are needed. However, the sensitive nature of clinical data, along with strict regulatory constraints, creates ...

Public service organisations, particularly universities, lack structured methods to evaluate their operational readiness for digital transformation, hindering strategic planning in the Industry 4.0 era. This paper addres...

Cybersecurity education often struggles to engage learners while effectively conveying complex web vulnerabilities. This challenge is particularly evident in topics such as cross-site scripting (XSS), where understanding...

The remarkable success of large language models (LLMs) in code generation has transformed software development, with systems like Codex, CodeGen, and StarCoder demonstrating strong capabilities in synthesizing functional...

In classical vernacular Chinese fiction, inferring affective stance in the presence of rhetorical devices often depends on implicit semantics and contextual cues, which poses substantial challenges for joint pragmatic mo...

Despite the impressive strides of large language models (LLMs) in text summarization, their effectiveness still hinges on well-crafted prompts, a process that remains labor-intensive, subjective, and difficult to scale. ...

Sign Language Translation (SLT) is fundamentally a process of intersemiotic translation, involving the transfer of meaning between visual-gestural and spoken language systems. However, most existing SLT studies focus on ...