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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...

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...

IntroductionTo optimize radiotherapy treatment and minimize toxicities, effective segmentation of organs-at-risk (OARs) and clinical target volume (CTV) is essential. Deep learning (DL) models can achieve high segmentati...

Imaging is a vital component of the diagnostic and early detection processes for many medical disorders. However, the noise in the images can sometimes interfere with the accuracy of the diagnosis. Speckle noise, Poisson...

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...

Abstract The deep reinforcement learning techniques offers a novel approach to real-time control for hybrid power flow controllers. This paper introduces a bus voltage optimization adjustment strategy, utilizing a Markov...

Abstract Atomic force microscopy (AFM) is a widely used tool for nanoscale characterization across materials science, energy research, and biology. However, its adoption in high-throughput materials discovery and statist...

Traditional malware detection techniques frequently fail to detect and stop malicious activity in an era where cyber threats are becoming more complex. Any software that enters a computer system without the administrator...

Abstract Accurate classification of phonocardiogram (PCG) signals is vital for the early detection of cardiovascular diseases (CVDs), a leading cause of global mortality. However, conventional machine learning and deep l...

Fault Detection and Diagnosis (FDD) is crucial for ensuring safe, reliable, and energy-efficient operation of collaborative robots, especially with the growth of Industry 4.0. Industrial robots are nonlinear, complex, an...

Abstract We propose a continuous stress-detection pipeline that integrates wavelet-based heart-rate-variability (HRV) features with behavioural signals in a staged ensemble. The method computes time-resolved HRV spectral...

Abstract Individualized educational management cannot be avoided in meeting various learner needs in cases where teaching strategies are changed in line with the performance trends and preferences of students. Reinforcem...

Abstract The increase in vehicle ownership and urban population puts a strain on roads and increases traffic congestion within developed and developing nations. Congestion affects an individual’s time and increases an ...

In recent years, convolutional neural networks and deep neural networks have been used extensively in various fields of analytical chemistry. The use of these models for calibration tasks has been highly effective; howev...

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...

IntroductionReliable classification of lung nodules from computed tomography (CT) images remains a challenging problem due to variations in image intensity, noise, and unstable feature representations during deep network...

Abstract In rural areas, unreasonable access of distributed photovoltaic (DPV) may pose a significant challenge to the safe operation of the power network. To address this, determining the maximum hosting capacity of net...

Introduction: Smartphones are widely used by adolescents in their everyday life and help them in communication, learning, and entertainment. However, too much and uncontrolled smartphone use can lead to addiction, which ...

Abstract The use of animal-borne devices to measure acceleration has yielded insights into animal locomotion, behaviour and energy expenditure. We present the first systematic review of accelerometry on animals, spanning...

IntroductionWeather classification plays a crucial role in applications such as environmental monitoring, disaster management, and smart city infrastructure. Accurate and efficient classification of weather conditions fr...

In recent years, the frequency and complexity of financial fraud have been rising and have become an urgent challenge for the global financial system. Traditional rule-based detection methods struggle to cope with new ty...

ABSTRACT: In recent years, the use of computing has increased along with medical skills, and this had impressive results in terms of classification and treatment, in addition to facilitating the matter of medical personn...

Abstract To address the challenge of abnormal tobacco shred detection in cigarette production lines, this study proposes an improved lightweight YOLOv8-based model that balances model efficiency and detection accuracy. F...

Language classification systems are used to classify spoken language from a particular phoneme sample and are usually the first step of many spoken language processing tasks, such as automatic speech recognition (ASR) sy...