Researchers in Buildings journal propose the CEACE method, integrating environmental indicators like CF, EF, WF, and CDW to assess sustainability in residential construction in Andalusia, Spain. Analyzing 15 diverse projects, the method offers holistic evaluation, identifies environmental impacts, and suggests improvements, highlighting its effectiveness in promoting sustainable construction practices.
Researchers from the UK demonstrate the efficacy of self-supervised learning for human activity recognition using a vast wearable dataset. By addressing convergence issues and evaluating multi-task self-supervision, they showcase robust models with superior representation quality across diverse populations and activity types.