Results 41 to 50 of about 9,473 (177)
Network Latency Estimation for Telesurgery Using Deep Reinforcement Learning
SmartBot, EarlyView.Overview of the proposed two‐stage deep reinforcement learning framework for network latency prediction in telesurgery. The pipeline includes data collection from simulated catheter navigation sessions (Philippines–Botswana), feature engineering, DQN‐based direction prediction (85.8% accuracy), direction‐to‐value transformation, and value forecasting ...
Bakang Kgopolo +2 more
wiley +1 more source
Denoise Stepwise Signals by Diffusion Model‐Based Approach
Small Methods, EarlyView.This work presents SSDM, a diffusion‐model‐based framework for denoising stepwise signals in single‐molecule measurements. By learning the statistical structure of state transitions and noise, SSDM reconstructs signal levels and identifies transition time points more accurately than conventional approaches, enabling robust analysis of signals across ...
Xingdi Tong, Chenyu Wen
wiley +1 more source
Impacts of Change‐Type and State‐Type System Qualities on Complex System Architectures
Systems Engineering, EarlyView.ABSTRACT System qualities, such as scalability, expandability, and reconfigurability, are key requirements of complex systems. Requirements associated with system qualities are important factors in design trade space analyses, but systems engineering design methodologies make only limited use of these qualities, hindering a holistic understanding of ...
Christina F. Bridges +1 more
wiley +1 more source
DQN‐Guided Subset‐Induced OCSVM Kernel Approximation for Imbalanced Anomaly Detection
IEEJ Transactions on Electrical and Electronic Engineering, EarlyView.Anomaly detection under limited normal data remains a fundamental challenge due to severe class imbalance and scarcity of anomalies. We propose a novel framework that reformulates support vector selection in One‐Class SVM as a sequential decision‐making problem.
Wenqian Yu, Jiaying Wu, Jinglu Hu
wiley +1 more source
The performance of drones and artificial intelligence for monitoring sage‐grouse at leks
Wildlife Biology, EarlyView.Accurately monitoring sage‐grouse populations is critical for conservation, yet traditional ground‐based visual surveys face challenges in scalability and consistency, prompting the exploration of innovative drone‐based methodologies enhanced by artificial intelligence.
Lance B. McNew +2 more
wiley +1 more source
Linking telemetry data with forage availability maps advances information for moose management
Wildlife Biology, EarlyView.Evidence‐based forest and wildlife management requires precise estimates of forage availability for spatial planning and conflict mitigation. Recently, novel datasets and associated maps have been developed for use in Swedish forest and wildlife management.
Lukas Graf +3 more
wiley +1 more source
Reinforcement Learning With Timed Constraints for Robotics Motion Planning
Artificial Intelligence for Engineering, EarlyView.This work presents a unified automata‐based reinforcement learning framework that enforces MITL time‐bounded task specifications in both MDPs and POMDPs. Results from grid‐world and office scenarios show robust policy learning under stochastic dynamics and partial observability.
Zhaoan Wang +3 more
wiley +1 more source
Artificial Intelligence for Engineering, EarlyView.We present a three‐stage training framework combining Behaviour Cloning warm‐starting with auxiliary‐regularised Deep Reinforcement Learning PPO fine‐tuning for 2D drone waypoint navigation under stochastic wind. Persistent imitation regularisation prevents catastrophic forgetting, achieving robust generalisation to unseen targets and out‐of ...
Ahmet Bilgehan Serçe, Necati Aksoy
wiley +1 more source
Cascade Deep Learning With Physics Guidance for Typhoon Intensity Prediction
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Typhoons pose a significant threat to both human safety and economic stability. As a crucial metric for assessing their destructive potential, typhoon intensity (TI) prediction has become an important research focus, with numerous methods developed.
Zhengya Sun +4 more
wiley +1 more source
Alternative seed trait strategies are linked to a trade‐off between spatial and temporal dispersal
Functional Ecology, EarlyView.Read the free Plain Language Summary for this article on the Journal blog. Abstract Seed dispersal allows plants to seek favourable conditions or spread the risk of unfavourable conditions through space and time. While theory predicts a trade‐off between spatial and temporal dispersal, empirical tests have been stymied by the difficulty of measuring ...
Marina L. LaForgia +5 more
wiley +1 more source