Phase averaging on CSI from commercial 802.11ac devices detects bird motion several meters off LOS in outdoor low-multipath settings while keeping vegetation effects negligible below 3 m/s wind.
Internet based remote control for a robotic catheter manip- ulating system
5 Pith papers cite this work. Polarity classification is still indexing.
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Systematic review of teleoperated endovascular robots finds navigation feasible over 7000 km with 30-163 ms latency and 100% success in small human trials, mostly from animal and phantom models.
A probabilistic graphical model framework with graph neural network inference computes Bayesian posteriors for discrete structural states, claimed to match traditional Bayesian results while scaling to high-dimensional problems via topology-informed learning and scale-adaptive training.
A quantum-assisted agentic DAI framework formulates microgrid dispatch as QUBO problems solved by solver portfolios with agentic selection and belief-shaped storage valuation, achieving exact optimum in a 24-hour simulation with 97.83% renewable utilization.
Evaluates concept drift effects on ML phishing detectors and explores mitigation strategies.
citing papers explorer
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CSI Phase Averaging for High-Sensitivity Wi-Fi Sensing in Low-Multipath Environments
Phase averaging on CSI from commercial 802.11ac devices detects bird motion several meters off LOS in outdoor low-multipath settings while keeping vegetation effects negligible below 3 m/s wind.
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Remote Teleoperation of Endovascular Intervention Robots: A Systematic Review
Systematic review of teleoperated endovascular robots finds navigation feasible over 7000 km with 30-163 ms latency and 100% success in small human trials, mostly from animal and phantom models.
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Probabilistic Graphical Model using Graph Neural Networks for Bayesian Inversion of Discrete Structural Component States
A probabilistic graphical model framework with graph neural network inference computes Bayesian posteriors for discrete structural states, claimed to match traditional Bayesian results while scaling to high-dimensional problems via topology-informed learning and scale-adaptive training.
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A Quantum-Assisted Agentic Distributed Artificial Intelligence Framework for Deadline-Bounded Orchestration of Hybrid Renewable Microgrids
A quantum-assisted agentic DAI framework formulates microgrid dispatch as QUBO problems solved by solver portfolios with agentic selection and belief-shaped storage valuation, achieving exact optimum in a 24-hour simulation with 97.83% renewable utilization.
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Evaluating and Combating the Impact of Concept Drift on the Performance of Machine Learning-Based Phishing Detection Systems
Evaluates concept drift effects on ML phishing detectors and explores mitigation strategies.