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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 ...

This study examines the relationship between preschool children’s emotional expression and colour use in digital drawings produced during an authentic classroom activity. A total of 216 children created drawings a...

The Zulfikar sword is a highly standardized sacred weapon symbol in Shia visual culture, forming a stable iconographic lineage across the Middle East and the Irano-Ottoman world. However, it is notably absent from Chines...

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. ...

The growth of variable renewable energy sources has increased the occurrence of curtailment in power systems, particularly in regions affected by transmission constraints and limited operational flexibility. Reliable for...

Forest growth and yield projection is essential for sustainable forest management planning. In Brazil, the Clutter model is widely applied for yield forecasting and commonly achieves prediction errors below 10%. However,...

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...

Full self-attention in video diffusion transformers scales quadratically with the spatio-temporal token count, making processing high-resolution video generation prohibitively slow and memory-intensive. We introduce NABL...

Current watermarking approaches for LLM-generated text typically embed watermarks during the generation process, using a secret key controlled by the LLM. Although this enables verification of LLM-generated content, it m...

This study investigates the long-term aging effects and structural degradation mechanisms of photovoltaic (PV) modules integrated into smart city furniture, with a particular focus on panels of 10 W, 25 W, and 40 W nomin...

ARM-based systems are widely deployed in edge and IoT settings, where penetration-testing tools must operate under strict memory, power, and thermal constraints, yet prior work offers limited deployment-oriented guidance...

This paper introduces CONV_GBERT, a hybrid deep learning framework for robust sentiment classification. The model integrates the bidirectional contextual understanding of BERT, the generative capabilities of GPT, and the...

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...

The ceiling effect, a phenomenon in which rotor thrust increases near a ceiling wall, holds significant potential for applications in energy-efficient drones and aerial manipulation. However, previous studies have not re...

User populations in modern recommendation systems consist of diverse communities with distinct and often non-overlapping preferences. However, most existing models, such as traditional Variational Autoencoders (VAEs), op...

In this work, a structured hierarchy of hyperdatasets for Monkeypox image classification is presented, aiming to evaluate the robustness and generalization ability of deep classification models for Mpox detection. A syst...

Driven by satellite remote sensing observations, deep learning models provide a promising solution for the rapid estimation of subsurface thermohaline structures. By learning from large-scale paired surface–subsur...

This study focuses on the explainability of AI operations for diagnosing degradations in cloud applications. Log data can provide essential contextual information on misbehaving applications in monitoring, evaluated agai...

Terrestrial evaporation ($E$) plays a crucial role in the water, energy, and carbon cycles and modulates climate change through multiple feedback mechanisms. While process-based models estimate $E$ using satellite-derive...

Botnet communications often rely on Domain Generation Algorithms (DGAs) to establish channels among attack orchestrators and compromised hosts (bots). Our approach leverages on Artificial Intelligence (AI) to differentia...

Mobility-as-a-Service (MaaS) orchestration faces critical challenges in managing the Service Quality Index (SQI), Fleet Utilization Ratio (FUR), and Dynamic Pricing Index (DPI) under uncertain and time-varying urban dema...

Modern edge–cloud deployments integrate devices, edge servers, private networks, and cloud platforms into heterogeneous, multi-layer systems. Each layer exposes distinct metrics, measurement granularities, and tim...

Federated Prompt Learning (FPL) enables efficient collaborative adaptation of large-scale models, but it remains vulnerable to data heterogeneity: locally optimized prompts may become biased, thereby weakening the aggreg...