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As a non-destructive and rapid technique, optical scatterometry has gained widespread use in the measurement of film thickness and optical constants. The recent advances in deep learning have presented new and powerful a...

Wildfires are among the most destructive natural disasters and pose significant risks to ecosystems, infrastructure, and human lives. This study focuses on wildfire susceptibility mapping in Los Angeles County, a region ...

Intelligent mining area detection is fundamental for ecological monitoring and sustainable development of mining areas. However, current remote sensing detection lacks high-quality multimineral rotated object detection d...

Abstract Background Surgical site infections (SSIs) continue to exert a substantial burden on healthcare systems, particularly in resource-limited settings where they contribute to prolonged hospitalizations, escalated c...

Di-Higgs production at the LHC associated with missing transverse energy is explored in the context of simplified models that generically parameterize a large class of models with heavy scalars and dark matter candidates...

Abstract The Broad Learning System (BLS) provides an effective framework for nonlinear mapping, offering advantages over traditional deep neural networks through its expanded input node architecture. While BLS has demons...

Abstract Model instability remains a core challenge for data‐driven parameterizations, especially those developed with supervised algorithms, and rigorous methods to address it are lacking. Here, by integrating machine...

This paper addresses the challenge of packet-based information routing in large-scale communication networks. The problem is framed as a constrained statistical learning task, where each network node operates using only ...

IntroductionAcute Lymphoblastic Leukemia (ALL) is a hematological malignancy, which is life-threatening and demands rapid and precise diagnosis to either enhance or worsen the survival chances. Traditional diagnostic met...

While physics models for predicting system states can reveal fundamental insights owing to their parsimonious structure, they may not always yield the most accurate predictions, particularly for complex systems. As an al...

Vegetation optical depth (VOD), as a key parameter of vegetation, plays an important role in the process of vegetation growth and change. The spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) technolog...

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,...

Modern communication environments ranging from smart mobility infrastructures to digitally integrated health care systems demand adaptable and trustworthy network security. In this situation, software-defined networks (S...

With the constant advancement of the smart grid, zero-day attack processes in Advanced Metering Infrastructure (AMI) and Supervisory Control and Data Acquisition (SCADA) networks are also continually evolving. This study...

Industry 4.0 has brought numerous advantages, such as increasing productivity through automation. However, it also presents major cybersecurity issues, such as cyberattacks affecting industrial processes. Federated Learn...

Photonic reservoir computing has been demonstrated to be able to solve various complex problems. Although training a reservoir computing system is much simpler compared to other neural network approaches, it still requir...

Sevgi Ünal,1 Remzi Gürfidan2 1Department of Radiology, Izmir Katip Celebi University Ataturk Training and Research Hospital, Izmir, Türkiye; 2Database, Network Design and Management, Isparta University of Applied Scie...

Diabetic retinopathy (DR) is one of the leading causes of preventable blindness worldwide, making timely and accurate detection crucial for effective management. This study introduces DR-NetFusion, a novel hybrid deep le...

Properties of massive galaxy clusters, such as mass abundance and concentration, are sensitive to cosmology, making cluster statistics a powerful tool for cosmological studies. However, favoring a more simplified, spheri...

Unmanned surface vehicles (USVs) operating in open-sea environments experience significant roll motion due to wave-induced excitation. The dynamic roll response depends on various factors, including vessel speed, wave en...

Abstract Accurate prediction of terrestrial water cycle variables like soil moisture (SM) and evapotranspiration (ET) is crucial, yet existing Deep Learning (DL) models face limitations. Many adopt Single-Task Learning (...

Many empirical studies confirm the relationship between internationalization and innovativeness of firms. There is also a rich research stream on the role of networks in creating innovations and networking as conducive f...

Extensive research has demonstrated that music enhances cognitive functions, such as learning, reasoning, and memory. This study investigated the influence of music on short- and long-term memory while learning through t...

People are increasingly reliant on the internet for communication and various devices in their daily lives. The Internet of Things (IoT) has dramatically changed many industries by allowing more automation and easy data ...