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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 Bone tissue engineering scaffolds must provide structural support while permitting fluid transport and maintaining safe hydrodynamic conditions for cell activity. Triply Periodic Minimal Surface (TPMS) architect...

Abstract The rising complexity of urban areas, along with growing public safety needs, has made intelligent video surveillance systems more essential. The current surveillance systems that rely on human observation and p...

Abstract Wearable sensor–based human activity recognition (HAR) is central to smart sport and health-monitoring applications, yet existing deep learning models often rely on ad hoc multimodal fusion and offer limited i...

Abstract Cloud computing is quite popular because of its scalability and flexibility merits. However, faces significant security risks from malware, which exploits infrastructure weaknesses to cause unauthorized access, ...

Abstract The rapid adoption of encrypted communication protocols has raised privacy levels but has also dealt a significant blow to traditional intrusion detection systems that rely on payload inspection for anomaly dete...

Abstract Accurate prediction of cascading faults in power grids can ensure system stability and prevent large-scale outages. Existing methods typically require learning effective statistical information from datasets wit...

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 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 ...

Abstract Matching college students with appropriate innovative training projects is a challenging task that often relies on static assignment techniques, which overlook individual interests, skills, and learning styles. ...

Abstract The Error Diffusion Learning Algorithm (EDLA) is a learning scheme that performs synaptically local weight updates driven by a single, globally defined error signal. Although originally proposed as an alternativ...

Abstract This study examined whether defensive pessimism-related processes influence university students’ approaches to learning, psychological well-being, and academic performance indirectly through academic procrasti...

Abstract With the outward expansion of university campuses toward suburban areas, the modern campus has evolved into an increasingly independent social space, providing an organizational setting in which users’ daily a...

Abstract Detecting epileptic seizures from electroencephalogram (EEG) signals presents a significant challenge due to the nonlinear and non-stationary nature of brain activity. In this study, we propose a hybrid classifi...

Abstract Skin diseases affect a considerable part of the world population, but it is not easy to diagnose these diseases on time because of the limited availability of dermatologists and the similarity of lesions. This r...

Abstract Physical sciences are essential to the predictive modeling of complex environmental systems, particularly environmental monitoring and sustainability applications, as they provide the deterministic foundation re...

Abstract The rapid adoption of AI is transforming industrial wastewater treatment by enabling real-time monitoring, predictive control, and operational optimization. Publications on the subject accelerated sharply betwee...

Abstract Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems have significantly advanced data modelling capabilities and improved opportunities for extracting knowledge from vast and heterogeneo...

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...

Abstract This study seeks to address persistent challenges in traditional music education, particularly the subjectivity inherent in assessment criteria and the frequent delays in feedback, by harnessing the capabilities...