AI Model Optimizes High-Density Rail Transit Signals
A new Markov Decision Process model using reinforcement learning significantly reduces wait times and fuel consumption in high-density rail transit.
A new Markov Decision Process model using reinforcement learning significantly reduces wait times and fuel consumption in high-density rail transit.
A scoping review of fifty-two studies demonstrates that applying lean manufacturing principles to hospital layout design significantly reduces transit distances, ...
A systematic review of 172 studies found that evidence on digital health technologies and primary care management outcomes remains fragmented.
A randomised controlled trial in Kent, UK, found that rapid video responses to domestic abuse victims improved satisfaction and trust ...
An exploratory survey of students, faculty, management and administrative staff identifies success factors and barriers for adopting Generative AI in ...
A study of 189 Philippine MSMEs found that higher readiness in digital capability, financial literacy, infrastructure and strategy was strongly ...
New research analysing seventeen Hungarian manufacturing SMEs finds that small firms pursuing Industry 4.0 overwhelmingly prioritise basic operational control and ...
A single-hospital study in Foshan used super-efficiency SBM modeling and quantile regression to assess clinical department efficiency during China's DRG ...
A time-driven process mapping study at a national blood service in sub-Saharan Africa has quantified the full blood component production ...
A seventeen-year study of 143 London Stock Exchange firms finds that green bonds, environmental spending, and emissions policies significantly improve ...
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© 2026 Scienmag - Science Magazine