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Abstract In the world of the Internet of Things (IoT), wireless sensor networks (WSNs) play a vital role in enabling seamless communication between connected devices. In a WSN data prediction system based, clustering and...

Downscaling is a critical step to bridge the gap between large-scale climate information and local-scale impact assessments. However, steep and complex mountainous terrain induces highly heterogeneous local-scale meteoro...

For the structural health monitoring of composite materials, data analysis technology must be very sophisticated, capable of detecting fault patterns that are multi-level and complicated. A comprehensive deep learning pa...

The effect of imbalanced data on the optical character recognition of Braille text is investigated by applying two techniques to a set of convolutional neural network image classification models. A multilabel classificat...

The rapid growth and increasing complexity of Internet of Things (IoT) networks require efficient real-time monitoring and anomaly detection mechanisms. Traditional machine learning approaches often struggle to handle th...

Scintillation-based X-ray imaging can provide convenient visual observation of absorption contrast by standard digital cameras, which is critical in a variety of science and engineering disciplines. More efficient scinti...

Abstract Graph Neural Networks have emerged as a powerful paradigm for artificial intelligence driven drug discovery, offering molecular representation learning that surpasses many conventional approaches. Traditional ex...

Airport planning depends to a large extent on the levels of activity that are anticipated. To plan the facilities and infrastructures of an airport system and to be able to satisfy future needs, it is essential to predic...

In this work, we investigate how flight instructors observe aviator scan patterns and assign quality to an aviator's gaze. We first establish the reliability of instructors to assign similar quality to an aviator's scan ...

Abstract Training deep learning models requires substantial financial and human resources, so once deployed in untrusted environments, these models immediately attract the attention of attackers who seek to steal and mis...

ABSTRACT Deep learning profoundly impacts various areas, such as face recognition and language translation. Owing to the increasingly high computational costs of training neural architectures, it is intractable to manual...

As a key element of human settlements and fundamental features in maps, buildings play a critical role in urban planning and environmental monitoring. Automatically extracting buildings from remote sensing images is of s...

Remote sensing enables urban planners to gain macroscopic insights into urban structures and issues. Pan-sharpening plays a key role by merging multispectral and panchromatic images, combining high spatial resolution wit...

To achieve an optimal trade-off between processing efficiency and dimensional precision in the assisted electrode electrochemical discharge machining (AE-ECDM) of thermal barrier coating (TBC)-coated superalloys, a 1D co...

This study proposes and validates a conceptual framework using a sign language (SL) chatbot in the e-commerce domain to improve accessibility. Currently, the use of SL is a less-explored area in online platforms. It is d...

Car classification is important in daily life because there are many distinct types of automobiles made by various manufacturers. Although there are numerous methods for classifying autos, machine learning technologies h...

Abstract Timely and accurate detection of COVID-19 is essential for rapid intervention and preventing the spread of the disease, especially among vulnerable populations. This study introduces a new two-stage methodology ...

Abstract Early and reliable smoke detection is critical for preventing fire-related disasters, safeguarding human lives, and ensuring infrastructure safety. Conventional sensor-based systems, however, are often constrain...

Abstract To address the limitations of existing oil-well production forecasting models, particularly suboptimal hyperparameter selection, difficulties in fine-tuning, insufficient global search capability, and slow conve...

Tuberculosis (TB) continues to be one of the foremost public health issues in the world, and remains the second most salient communicable cause of death after COVID-19. In 2022, TB accounted for 10.6 million new infectio...

Abstract Satellite Image Classification is a process in remote sensing that aims at classifying pixels of satellite imagery into usable information of land use and land cover. This information is not only limited to seve...

Abstract Purpose This study introduces a new Convolutional Neural Network (CNN) architecture, EyeDiagNet, for the classification of fundus images into four classes: normal, cataract, diabetic retinopathy (DR), and glauco...

Coronal mass ejections (CMEs) are eruptions originating from the solar corona, usually carrying a large amount of fast-flowing plasma into interplanetary space, accompanied by an enhanced magnetic field. CMEs can form sh...

Meta-optics have opened new possibilities for portable, high-performance microscopy, offering ultrathin and highly customizable wavefront control in scenarios where bulky optics limit adoption. Here, we use this capabili...