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In the present study, the transmission error (TE) behaviour of an identical involute spur gear pair dynamically coupled with an attached subsystem is investigated through numerical modelling. The surrounding mechanical s...

To achieve high accuracies in deep learning-based inspection of IC markings, a large number of manually labeled images of good and defective markings are needed. In many IC production lines, only a handful of labeled ima...

Due to the limitation of lacking elevation resolution, ground-based interferometric radar suffers from serious layover problem when applied to building deformation monitoring. Ground-based tomographic arc-scanning synthe...

Machine learning has evolved into a potent tool for analysing patterns and making predictions from complex data. In this machine learning era, we employed neural network techniques to estimate the parameters of statistic...

Hollow-core photonic bandgap fibers (HC-PBGFs) exhibit exceptional environmental stability, making them as prime candidates for next-generation, high-precision fiber optic gyroscopes (FOGs). High fiber birefringence is n...

This paper introduces CONV_GBERT, a hybrid deep learning framework for robust sentiment classification. The model integrates the bidirectional contextual understanding of BERT, the generative capabilities of GPT, and the...

Few-shot object detection (FSOD) recently garnered increasing attention in remote sensing images (RSIs). Although FSOD has achieved success in natural sense, the large size and complex backgrounds of RSIs make FSOD espec...

The ceiling effect, a phenomenon in which rotor thrust increases near a ceiling wall, holds significant potential for applications in energy-efficient drones and aerial manipulation. However, previous studies have not re...

User populations in modern recommendation systems consist of diverse communities with distinct and often non-overlapping preferences. However, most existing models, such as traditional Variational Autoencoders (VAEs), op...

In this paper, permanent magnet synchronous generators, electrically excited synchronous generators, and hybrid excited synchronous generators are compared to evaluate the difference in performance and cost efficiency fo...

This study compares seven quantum algorithms—Variational Quantum Eigensolver (VQE), Variational Quantum Deflation (VQD), Quantum Approximate Optimization Algorithm (QAOA), Quantum Amplitude Estimation (QAE), Quant...

Presents corrections to the paper, (Demand Forecasting in Data-Scarce and Resource-Restricted Environments).

Dairy farms increasingly deploy sensor networks that generate high-frequency behavioral and spatial data, yet translating these multimodal streams into actionable welfare insights remains a key challenge. This study pres...

Infrared thermal radiation signals are highly susceptible to environmental interference, leading to dynamic fluctuations. Consequently, weak targets are frequently submerged in heavy clutter backgrounds under extreme sce...

With the rapid advancement of remote sensing technology, target detection in remote sensing imagery plays a crucial role in military reconnaissance, urban planning, and other fields. However, there are problems such as l...

The field of remote sensing change detection (RSCD) has witnessed remarkable progress. Most existing RSCD methods currently follow the encoder-feature interaction-decoder architecture. However, these methods often treat ...

Heart disease is rapidly increasing. For early and accurate prediction, advanced machine learning (ML) models are needed. However, the sensitive nature of clinical data, along with strict regulatory constraints, creates ...

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...

This paper presents an inductorless design methodology for compact single-pole double-throw (SPDT) switches in Sub-6 GHz applications. To achieve compactness and meet key performance metrics below 5.0 GHz, the methodolog...

This paper presents the design and experimental validation of a two-dimensional (2-D) circularly cylindrical phased array antenna with integrated wide-angle beam-switching capability for multibeam radiation in the Ku-ban...

Public service organisations, particularly universities, lack structured methods to evaluate their operational readiness for digital transformation, hindering strategic planning in the Industry 4.0 era. This paper addres...

Efficient UAV path planning in large and dynamic environments requires adaptive strategies that account for varying regional importance. Traditional coverage or Reinforcement Learning-based methods often suffer from redu...

Electrochemical migration (ECM) is a major concern in modern electronics because miniaturization has reduced insulation distances and electronics are now operated in harsher environments than before. Previous studies on ...

Spiking neural networks (SNNs) offer a biologically inspired, energy-efficient alternative to conventional artificial neural networks (ANNs). However, deep SNNs struggle to process complex EEG signals because their spike...