A Monte Carlo study of identified particle ratio fluctuations at LHC energies is carried out in the framework HIJING model using fluctuation variable ν dyn . The simulated events for Pb-Pb collisions id="M2"> s N = 2.76 and ...

Event causality identification is an essential task for information extraction that has attracted growing attention. Early researchers were accustomed to combining the convolutional neural network or recurrent models with external causal knowledge, but these methods ignore importance of rich semantic representation event. The event more structured, so it abundant representation. We argue elemen...

Understanding events entails recognizing the structural and temporal orders between event mentions to build structures/graphs for input documents. To achieve this goal, our work addresses problems of subevent relation extraction (SRE) (TRE) that aim predict relations two given mentions/triggers in texts. Recent state-of-the-art methods such have employed transformer-based language models (e.g.,...

Wireless Sensor Networks (WSNs) offer inherent packet redundancy since each point within the network area is covered by more than one sensor node. This phenomenon, which is known as sensors co-coverage, is used in this paper to detect unauthenticated events. Unauthenticated event broadcasting in a WSN imposes network congestion, worsens the packet loss rate, and increases the network energy con...