Ranking Influential Nodes of Fake News Spreading on Mobile Social Networks

Online fake news can generate a negative impact on both users and society. Due to the concerns with spread of fake news and misinformation, assessing the network influence of online users has become an important issue. This study quantifies the influence of nodes by proposing an algorithm based on information entropy theory. Dynamic process of influence of nodes is characterized on mobile social networks (MSNs). Weibo (i.e., the Chinese version of microblogging) users are chosen to build the real network and quantified influence of them is analyzed according to the model proposed in this paper. MATLAB is employed to simulate and validate the model. Results show the comprehensive influence of nodes increases with the rise of two factors: the number of nodes connected to them and the frequency of their interaction. Indirect influence of nodes becomes stronger than direct influence when the network scope rises. This study can help relevant organizations effectively oversee the spread of online fake news on MSNs

Energy performance and climate control in mechanically ventilated greenhouses: A dynamic modelling-based assessment and investigation

Controlled environment agriculture in greenhouse is a promising solution for meeting the increasing food demand of world population. The accurate control of the indoor environmental conditions proper of greenhouses enhances high crop productivity but, contemporarily, it entails considerable energy consumption due to the adoption of mechanical systems. This work presents a new modelling approach for estimating the energy consumption for climate control of mechanically ventilated greenhouses. The novelty of the proposed energy model lies in its integrated approach in simulating the greenhouse dynamics, considering the dynamic thermal and hygric behaviour of the building and the dynamic response of the cultivated crops to the variation of the solar radiation. The presented model simulates the operation of the systems and the energy performance, considering also the variable angular speed fans that are a new promising energy-efficient technology for this productive sector. The main outputs of the model are the hourly thermal and electrical energy use for climate control and the main indoor environmental conditions. The presented modelling approach was validated against a dataset acquired in a case study of a new fully mechanically controlled greenhouse during a long-term monitoring campaign. The present work contributes to increase the knowledge about the dynamics and the energy consumption of greenhouses, and it can be a valuable decision support tool for industry, farmers, and researchers to properly address an energy efficiency optimisation in mechanically ventilated greenhouses to reach the overall objective of decreasing the rising energy consumption of the agricultural sector