Continuous advancements in medical device technologies require developing comprehensive frameworks for real-time monitoring, predictive maintenance, and adaptive control of medical devices to ensure patient safety and reliability of devices. Conventional ways of testing and simulation usually require static models, pro...
Anto Lourdu Xavier Raj Arockia Selvarathinam, V. Subha, S. Prathi· Handbook of Smart Healthcare· 0 citations
Code and data: deep reinforcement learning for weekly mosquito-control allocation under an operational capacity ceiling This package reproduces every number, table and figure in the manuscript. Version 2.0.0 extends the original submission with a weekly operational-capacity ceiling, additional algorithms, cross-year va...
Gustave·Kateb· Zenodo (CERN European Organi...· 0 citations
Antibiotics with new mechanisms are highly pursued to address the threat of infections caused by drug-resistant Gram-negative bacteria. Targeting MsbA, a key protein of the lipopolysaccharide biosynthesis pathway, represents a promising strategy to discover new classes of antibiotics. However, currently available MsbA-...
Lei Wang, Bai-Xin Jing, Qing-Xin Liu et al.· bioRxiv· 0 citations
Reconfigurable manufacturing requires robotic workcells that can adapt to changing products, processes, and equipment without extensive redesign or manual reprogramming. This paper presents the R3M framework, a ROS 2 driven integration architecture that connects model based manufacturing knowledge with execution level...
S. A. Syed Asif, Mikel Bueno, Paul Anandan et al.· Robotics and Computer-Integr...· 0 citations
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This paper designs a comprehensive fourlayer architecture featuring semantic-aware intent parsing, distributed decision-making, and dynamic resource orchestration and achieves a high constraint satisfaction rate under dynamic disturbance scenarios, thereby guaranteeing fault tolerance, stability, and system robustness...
Si-Yu Yan, Ying Ouyang, Zi-Yi Tang et al.· International Conference on...· 0 citations
A deep reinforcement learning–based joint orchestration algorithm (DRL-JOA) employing graph attention networks is proposed to solve the sum rate maximization problem in beyond diagonal reconfigurable intelligent surface (BD-RIS)-assisted multicell transportation networks within a space-air-ground integrated network fra...
Zuhaib Nishter, Li Gang, Nada Alzaben et al.· International Journal on Sem...· 0 citations
This study investigates the operations in automated container terminals, in which scheduling decisions need to be generated automatically. Therefore, an integrated optimization model is established considering the two-way transportation process of containers between the berth and the yard with the assignment and schedu...
This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/22775771. Summary The authors tackle a real obstacle in interpretability: you can't compare SAE features across training checkpoints, because separately trained dictionaries assign...
Sneh Pankajbhai Vora· Zenodo (CERN European Organi...· 0 citations
With the rapid advancement of intelligent agriculture and autonomous field operations, the distributed drive electric plant protection vehicle (DDEPPV) is increasingly adopted for paddy-field plant protection. However, in soft-soil, low-adhesion, and highly disturbed environments, the tight coupling among path tracking...
Wenxiang Xu, Xiaoyu Song, Liling Ye et al.· Computers and Electronics in...· 0 citations
The increasing penetration of renewable energy sources introduces significant variability and uncertainty into grid-connected microgrids (MGs), affecting voltage stability, frequency regulation, power quality, fault ride-through capability, and operational resilience at the Point of Common Coupling (PCC). These challen...
Nicholas Nyaika, Cosmas Mwikirize, Andrew Katumba (PhD)3· Zenodo (CERN European Organi...· 0 citations
Abstract Performance anxiety (PA) is common in high-stakes settings, from public speaking to the performing arts, yet its mechanisms remain poorly understood. Using behavioural analysis, computational modelling, and electroencephalography, we examine whether PA is associated with differences in learning from reward and...
Andrea Erazo Hidalgo, Lisa Pearson, T. Oku et al.· Communications Biology· 0 citations
The scaling cost ceiling of RLHF and autonomous falsification via the Universal Intervention Barrier and the Universal Entropy-Threshold Operator. One of 135 dated defensive publications in the CatQualia record. Collection DOI: https://doi.org/10.5281/zenodo.22751107 Original publication: https://catqualia.com/ueto
Christopher Betances· Zenodo (CERN European Organi...· 0 citations
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
MIT News · Artificial Intelligence· news.mit.eduOct 13, 2026
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
Microsoft Research Blog· microsoft.comOct 12, 2026
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 7, 2026
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 6, 2026
