With the success of large knowledge graphs, research on automatically acquiring commonsense knowledge is revived. One kind of knowledge that has not received attention is that of human activities. This paper presents an information extraction pipeline for systematically distilling activity knowledge from a corpus of movie scripts. Our semantic frames capture activities together with their parti...

The state evolution of the initial optical noon state is investigated. The residue entanglement of the state is calculated after it is damped by amplitude and phase damping. The relative entropy of entanglement of the damped state is exactly obtained. The performance of direct application of the damped noon state is compared with that of firstly distilling the docoherence damped state then appl...

We study the effects of post-selection measurements on both the non-classicality of the state of a mechanical oscillator and the entanglement between two mechanical systems that are part of a distributed optomechanical network. We address the cases of both Gaussian and nonGaussian measurements, identifying in which cases simple photon counting and Geiger-like measurements are effective in disti...

Due to the over-parameterization of neural networks, many model compression methods based on pruning and quantization have emerged. They are remarkable in reducing size, parameter number, computational complexity model. However, most models compressed by such need support special hardware software, which increases deployment cost. Moreover, these mainly used classification tasks, rarely directl...

There has been some confusion as to whether KM is part of BI or BI is part of KM. The lack of clarity is seen to be, in part, dependent on how the two concepts are defined. Their relationship is clarified. BI focuses on explicit knowledge, but KM encompasses both tacit and explicit knowledge. Both concepts promote learning, decision-making, and understanding. Yet, KM can influence the very natu...