Graph neural network for integrated water network partitioning and dynamic district metered areas.

Water distribution systems (WDSs) are used to transmit and distribute water resources in cities. Water distribution networks (WDNs) are partitioned into district metered areas (DMAs) by water network partitioning (WNP), which can be used for leak control, pollution monitoring, and pressure optimization in WDS management. In order to overcome the limitations of optimal search range and the decrease of recovery ability caused by two-step WNP and fixed DMAs in previous studies, this study developed a new method combining a graph neural network to realize integrated WNP and dynamic DMAs to optimize WDS management and respond to emergencies.

Gravitational Wave-Signal Recognition Model Based on Fourier Transform and Convolutional Neural Network.

The recent detection of gravitational waves is a remarkable milestone in the history of astrophysics. With the further development of gravitational wave detection technology, traditional filter-matching methods no longer meet the needs of signal recognition. Thus, it is imperative that we develop new methods.

Structure of microprismatic Fresnel lenses for creating uniform focal images.

Flat Fresnel lenses are known to form a point image in the focal plane. However, several practical applications require transforming lens to concentrate a parallel light beam into a uniformly illuminated light circle. We previously proposed a novel algorithm for simulating such a transforming Fresnel concentrator.