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This paper introduces FlexiNet, a novel adaptive feature synthesis network designed for real-time ego vehicle speed estimation in autonomous driving systems. FlexiNet dynamically synthesizes features across multiple scales and modalities, achieving state-of-the-art accuracy while maintaining the throughput required for real-time deployment on vehicle hardware.
This work presents a comprehensive system using Graph Attention Networks for robust recognition of analog circuit structures. A novel data augmentation technique is introduced to improve generalization across diverse schematic layouts. The system achieves high recognition accuracy on real-world IP analog circuits, enabling automation of a previously manual verification task.
A comprehensive generalization approach for GAT-based systems applied to real IP analog-mixed-signal (AMS) schematic structure recognition. The work demonstrates that graph attention architectures generalize across schematic styles and technology nodes without retraining from scratch.
A systematic approach to generalizing analog-mixed-signal schematic recognition systems across vertical abstraction levels — from device-level schematics to block-level topologies. The method enables recognition at multiple levels of hierarchy without separate training pipelines.
Comprehensive study on the technical feasibility, energy output modeling, and environmental impact of deploying massive floating solar panel arrays over Lake Nasser, Egypt. The analysis covers thermal performance, water evaporation reduction, and grid integration potential.
Evaluation of capacitive deionization (CDI) technology as a sustainable, energy-efficient solution for irrigation water desalination in arid regions. The study benchmarks CDI performance against conventional reverse osmosis and assesses viability for small-scale agricultural applications.