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Abstract Semiconductor lithography, a pivotal process in integrated circuit (IC) fabrication, accounts for approximately 30% of production costs and faces significant challenges as feature sizes shrink to sub-nanometer s...

Abstract Echo State Networks are recurrent neural networks that leverage a random reservoir’s dynamics, training only a simple readout layer. This approach is computationally efficient but limits network performance. B...

Abstract Parkinson’s Disease (PD) is a progressive neurodegenerative disorder that causes motor and cognitive impairments, affecting approximately 1% of individuals over 60 years of age. Speech impairments are among th...

Abstract When human instructors guide learners through motor tasks, they seamlessly coordinate physical touch with verbal explanations - a dance teacher positions a student’s arms while describing the movement, a thera...

Abstract The increasing adoption of Industrial Internet of Things (IIoT) devices introduces significant cybersecurity and privacy challenges, particularly anomaly detection and secure data sharing. This study presents Se...

Abstract Data pruning is a key technique for reducing training costs and improving model performance. However, most existing methods rely on fixed pruning rates or single metrics, which are largely designed for static tr...

Abstract The article presents a novel audio zero-watermarking technique that is free of creating any watermark data in the original audio. The strategy depends on the robust features of the audio in order to generate an ...

Abstract Carbon markets play a critical role in emission reduction and sustainable economic transition; however, carbon price series exhibit high volatility, nonlinear dynamics, and complex cross-feature interactions, ma...

Abstract Multimodal industrial documents–such as operation manuals, circuit diagrams, and parameter tables–contain domain knowledge distributed across text, images, and document layout. However, most existing retriev...

Abstract Inventory management is a core part of supply chains, and over the years it has been increasingly challenged by the need to balance economic performance with environmental considerations. While prior reinforceme...

Abstract Unsupervised visible-infrared person re-identification (USL-VI-ReID) aims to match person images across visible and infrared modalities without any labeled data, which is severely hindered by the large cross-mod...

Abstract Microrobotic systems offer significant potential for precision medicine by enabling minimally invasive interventions in complex fluidic environments. However, effective operation in these settings requires actua...

Abstract This paper proposes a novel hybrid ensemble machine learning framework integrated with Explainable AI (XAI) to overcome the fundamental trade-off between non-detection zones (NDZ) and false positives in conventi...

Abstract DriveEmo-FL presents a privacy-preserving, radar-based emotion-recognition framework tailored for autonomous-vehicle (AV) cabins. Leveraging a compact embedded mmWave radar, the system captures upper-body emotio...

Abstract Large-scale mining equipment operates under extreme conditions, making accurate fault prediction and remaining useful life (RUL) estimation essential for predictive maintenance strategies. This paper proposes a ...