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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...

Abstract Multi-label chest X-ray classification faces three critical challenges: (i) inadequate modeling of inter-pathology dependencies despite clinical co-occurrence patterns, (ii) severe class imbalance (11.2−47.6...

Transformer-based protein language models (PLMs) learn meaningful representations from millions of unlabeled sequences, capturing evolutionary patterns and functional relationships. Recent advances include ESM-2’s syst...

Abstract Contemporary distribution transformers face modern technological and integration challenges due to modern electrification and load increase. Motivated by the need for improvement of transformer safety, lifetime,...

Abstract River water quality forecasting on directed river networks requires jointly modeling temporal dynamics and directional spatial dependencies among monitoring sites. Existing spatio-temporal models often emphasize...

ABSTRACT Transformers have been widely applied to hyperspectral image classification, leveraging their self‐attention mechanism for powerful global modelling. However, two key challenges remain as follows: excessive me...

Stellar population measurements in integral field unit surveys are often limited by low signal-to-noise ratios (S/Ns) in low-surface-brightness spaxels. Using controlled synthetic experiments, we investigate whether a de...

Abstract Integrated chem-bio characterization of microbial strain libraries can streamline natural product discovery by prioritizing candidate producers. Here, we employ language- and transformer-based models to extract ...

In the busy and stressful modern world, people tend to disregard mental health, still it is an important factor of overall health. The constant pressure to achieve success, the invasive nature of technology, and the cons...

Abstract This research proposes an innovative Arabic financial forecasting model that integrates linguistic relation extraction with advanced deep learning and machine learning techniques. The framework combines Arabic O...

Passive SONAR has attracted significant attention in covert operations, enabling vessel detection and classification through spectrogram analysis of received signals without active transmission. However, in realistic oce...

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 ...

Electricity consumption measurement system with an embedded system device with Arduino-based technology combined with a current transformer sensor TA12-100 which is connected to the load of electricity consumption. Ardui...

Dynamic gesture recognition is a core technology for human–computer interaction, yet existing methods face prominent limitations in hand spatial topology modeling, long–short-term temporal feature fusion, and general...

Fast and accurate identification of skin lesions is important for the outcome of patients. The evaluation of lesions is subjective, and poor quality images may limit accuracy. Deep learning models can be an alternative; ...

Estimating three-dimensional morphological traits such as volume from two-dimensional RGB images presents inherent challenges due to the loss of depth information, projection distortions, and occlusions under field condi...

Video snapshot compressive imaging is a computational imaging technique based on compressed sensing that acquires high-speed frames through a 2D compressed measurement, followed by an algorithmic reconstruction. Current ...

Abstract The transformer architecture has demonstrated significant performance in image super-resolution (SR). However, for existing Transformer-based models, there are common drawbacks. They often fall short in local fe...

ABSTRACT Integrating healthcare systems with intelligent transportation networks represents a critical frontier in modern urban infrastructure, where efficient resource allocation and timely service delivery can signific...

A novel mesh-free methodology for the coupled magnetic field-circuit simulation of power transformers is presented in this paper. The proposed methodology employs equivalent models for the conductors and the iron core, w...

Organizations have become highly reliant on a range of data sources that span structured, semi-structured, and unstructured data types. These repositories allow large-scale storage for faster ingestion and analytics but ...

Abstract Accurate monitoring and prediction of Chlorophyll-a (Chl-a) concentrations are critical for protecting desalination systems from algal blooms. This study presents an advanced framework employing the Graph Neural...

Oil–paper insulation aging is a major cause of power transformer deterioration, yet key indices, such as paper degree of polymerization (DP), oil breakdown voltage (Ubd), and dielectric loss factor (tanδ), are still m...

We will try to approach to some aspects of the phenomenon of social movements in Latin Amercia through the light of one of the most important questions: which is the political potential of social and political change of ...