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AUVs have essential applications in oceanic investigations, environmental characterization, and subsea surveys where accuracy in positioning and stability for navigation is challenging. AUV proposed in the present work a...

Fast and accurate identification of skin lesions is important for the outcome of patients. The evaluation of lesions is subjective, and poor quality images may limit accuracy. Deep learning models can be an alternative; ...

Automated scoring of mathematical solutions is challenging due to the diversity of solution strategies and the need to assess both correctness and reasoning. We present SymbAlign++, a hybrid framework that combines symbo...

Context. The morphological classification of galaxies is considered a relevant issue and can be approached from different points of view. The increasing growth in the size and accuracy of astronomical data sets brings wi...

Context. Astronomical environments are governed by a complex interplay of physical processes, including gravitational dynamics, radiative transfer, stellar evolution, chemistry, and hydrodynamics. These processes span a ...

Endurance versus payload in UAVs is a direct trade-off governed by airframe mass and structural efficiency. Generative design (GD) and topology optimization (TO) are increasingly used to develop lightweight, high-perform...

Net One of the biggest challenges in industrial robotics working in dynamic environments is reliably recognizing voice commands for human-robot interaction. This article presents a Hybrid Hidden Markov Model, Convolution...

Aims. We investigate whether viscous cold dark matter (vCDM) in a Λ-dominated Friedmann-Lemaître-Robertson-Walker (FLRW) universe can alleviate the Hubble tension, while satisfying thermodynamic constraints. Here, we e...

Robots that are flexible, reconfigurable and universally adaptable and capable of performing various tasks in constrained and dynamic workspaces are in high demand. In this research general forward kinematic model has be...

This study focuses on implementing PowerApps to automate and optimize the calculation of the carbon footprint at ABB, a company dedicated to industrial process automation in the mining sector. The implementation not only...

This paper will offer a unified strategy to the optimization of the chassis of a Formula SAE Supra car and predict structural failures using machine learning and Finite Element Analysis (FEA). The work demonstrates that ...

Background: Patient positioning for proximal femoral nailing (PFN) in unstable intertrochanteric fractures remains controversial and may influence operative efficiency, radiation exposure, and reduction quality. This stu...

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...

Comprehensive navigation and information access remain significant issues in vast educational campuses with linguistic diversities. This re- search proposes an innovative conversational AI system that integrates automati...

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 ...

Federated Learning (FL) has emerged as a privacy-preserving distributed learning paradigm that enables collaborative model training without sharing raw data. Despite its advantages, ensuring trustworthy FL deployment rem...

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...

This paper introduces a hybrid deep learning architecture to precisely detect surface water resources in deserted and dry areas in Central India with Sentinel-2 RGB images. Conventional spectral techniques are affected b...

Robotics has evolved a lot since its origin. The design of these robots is done based on various aspects, and one such aspect is bioinspired robots, which lies one of the most challenging fields were a robot is developed...

Context. Hot cores are signposts of the protostellar activity of dense cores in star-forming regions. W43-MM1 is a young region that is very rich in terms of high-mass star formation, which is highlighted by the presence...

Using recent spectroscopic observations, we show that the triple system AO Vel with an eclipsing BpSi primary is in fact a remarkable quadruple system formed by two double-lined spectroscopic binaries with components clo...

Context. Silver is a key tracer of the weak r-process in late-type stars. However, when the assumption of local thermodynamic equilibrium is relaxed, accurate abundance determinations become even more sensitive to comple...

Synthetic Aperture Radar (SAR) is one of the primary sensing models and is broadly used in numerous remote sensing applications including environmental monitoring, maritime monitoring, and climate change research. Unfort...

One of the most severe consequences of two wheeler accidents is the occurrence of head and spinal injuries, which often cause long term disability or even death. The cervical spine, located in the neck area, is particula...