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The recent Zero-Trust Architecture (ZTA) is progressively adopted to the develop network security by assuming no implicit trust within or outside an organization’s boundary. Though, ZTA faces substantial challenge...

Customer feedback is pivotal in enhancing service quality and user satisfaction across digital platforms. However, traditional sentiment analysis methods often struggle with informal languages, contextual nuances, and as...

The success of an economy can bring significant benefits to a country and its society. One way to measure economic growth is by looking at the value of gross domestic product (GDP). The value of a country's GDP is influe...

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...

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...

Abstract Accurate prediction of bio-oil yield from pyrolysis of organic solid waste is still the main problem in the field of biomass valorization, mostly because of high variability in the composition and the heterogene...

Abstract The Boreal Summer Intraseasonal Oscillation (BSISO) is a prominent tropical intraseasonal variability during summer. It propagates northeastward from the northern Indian Ocean to the western North Pacific and ha...

Subsurface temperature uncertainty represents a major risk in geothermal drilling, particularly in volcanic systems where permeability, lithology, and fluid circulation create highly heterogeneous thermal regimes. This s...

Early detection of Parkinson’s disease (PD) through speech analysis offers significant clinical advantages, yet no validated tools exist for Arabic-speaking populations, representing a critical gap in global healthcare...

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...

BackgroundNon-suicidal self-injury (NSSI) is common among adolescents and young adults and remains difficult to detect early using conventional approaches. machine learning (ML) has increasingly been applied to develop p...

Recent advances in computer vision and deep learning, particularly Convolutional Neural Networks (CNNs), have significantly increased road safety. CNNs were used in this work to automatically detect and categorise traffi...

Abstract Background This study aims to explore spatial heterogeneity within tumors, establish and validate an interpretable machine learning model combining habitat radiomics and deep learning, and investigate its predic...

BackgroundTranscriptome−wide association study (TWAS) contributes to discovering novel susceptibility genes related to diseases. Single-cell RNA sequencing (scRNA-seq) has been extensively applied to characterize cellu...

Abstract Background Colorectal signet ring cell carcinoma (CSRCC) is a rare subtype of colorectal cancer characterized by an exceptionally poor prognosis. Currently, accurate survival prediction models for CSRCC are lack...

Abstract Background Carotid atherosclerosis is a kind of systemic atherosclerosis in the carotid arteries. It remains one of the leading causes of ischemic stroke. However, the efficiency of treatment is insufficient. Th...

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 ...

Abstract Background Musculoskeletal diseases, such as Juvenile Idiopathic Arthritis (JIA), can lead to altered joint mobility and changes in gait pattern. While marker-based motion capture systems are considered the gold...

Abstract Proposed research presents a data-driven framework for forecasting municipal solid waste (MSW) generation and emission dynamics in Erode City, India, by employing supervised machine learning algorithms. Leveragi...

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...

Manual Gross Tumor Volume (GTV) delineation for radiotherapy is time‑consuming and prone to inter‑observer variability. Deep Learning (DL)-based auto‑segmentation offers faster and more consistent solutions, but tr...

Cancer is the second-largest cause of death worldwide, constitute about one out of every six deaths. Diagnostic techniques have been developed for the early detection to determine benign and malignant ones and conduct ap...

Prediction of Gate to Gate block time for scheduled flights is considered as one of the challenging tasks in Air Traffic Flow Management (ATFM)system. Establishing an effective and practically reliable model to manage th...

ABSTRACT Intelligent and adaptive defence systems that can quickly thwart changing cyberthreats are becoming more and more necessary in the dynamic and data‐intensive Internet of things (IoT) environment. Using the NSL...