Common use of Homogeneity Clause in Contracts

Homogeneity. To measure the homogeneity of the opinion distribution with the network structure, we examined the local distribution of nodes' opinions. We looked at whether each node's opinion was similar to those of its neighbors, which would suggest that it was in line with the overall opinion distribution over the network. The final homogeneity value was close to zero if the distribution of opinions was close to linear. We have developed a Python simulator that can compute the dynamic FJ (rewiring included), and polarization metrics over time based on the given network and initial opinions. To test the model, we ran simulations on a small network comprising 20 nodes and compared the outcomes of the FJ with rewiring to those without rewiring. For the ER network, we used a vector of uniformly distributed opinions over [-1,1] as the initial opinions. However, for the SBM networks, we employed a different configuration, where the initial opinions were uniformly extracted over the intervals [-0.5,0-0.1] and [0.1,0.5], depending on whether the nodes belonged to one or the other block. In conclusion, this microproject involves the design of a dynamic version of the FJ model for synchronous and asynchronous cases. Additionally, we have developed a new definition of polarization that considers both the distribution of opinions and the network topology. To assess the model's effectiveness, we conducted simulations on two different network types: an ER network and an SBM network. Our findings indicate that the rewiring process has significant effects on polarization, but these effects are dependent on the initial network. What idea of AI? Social and public perception of AI Date Start: 2021-02-01

Homogeneity. To measure the homogeneity of the opinion distribution with the network structure, we examined the local distribution of nodes' opinions. We looked at whether each node's opinion was similar to those of its neighbors, which would suggest that it was in line with the overall opinion distribution over the network. The final homogeneity value was close to zero if the distribution of opinions was close to linear. We have developed a Python simulator that can compute the dynamic FJ (rewiring included), and polarization metrics over time based on the given network and initial opinions. To test the model, we ran simulations on a small network comprising 20 nodes and compared the outcomes of the FJ with rewiring to those without rewiring. For the ER network, we used a vector of uniformly distributed opinions over [-1,1] as the initial opinions. However, for the SBM networks, we employed a different configuration, where the initial opinions were uniformly extracted over the intervals [-0.5,0-0.1] and [0.1,0.5], depending on whether the nodes belonged to one or the other block. In conclusion, this microproject involves the design of a dynamic version of the FJ model for synchronous and asynchronous cases. Additionally, we have developed a new definition of polarization that considers both the distribution of opinions and the network topology. To assess the model's effectiveness, we conducted simulations on two different network types: an ER network and an SBM network. Our findings indicate that the rewiring process has significant effects on polarization, but these effects are dependent on the initial network. What idea of AI? Social and public perception of AI Date Start: 2021-02-01No publications yet. The collaboration is still ongoing.

Homogeneity. To measure the homogeneity of the opinion distribution with the network structure, we examined the local distribution of nodes' opinions. We looked at whether each node's opinion was similar to those of its neighbors, which would suggest that it was in line with the overall opinion distribution over the network. The final homogeneity value was close to zero if the distribution of opinions was close to linear. We have developed a Python simulator that can compute the dynamic FJ (rewiring included), and polarization metrics over time based on the given network and initial opinions. To test the model, we ran simulations on a small network comprising 20 nodes and compared the outcomes of the FJ with rewiring to those without rewiring. For the ER network, we used a vector of uniformly distributed opinions over [[ -1,1] as the initial opinions. However, for the SBM networks, we employed a different configuration, where the initial opinions were uniformly extracted over the intervals [-0.5,0-0.1] and [0.1,0.5], depending on whether the nodes belonged to one or the other block. In conclusion, this microproject Micro-Project involves the design of a dynamic version of the FJ model for synchronous and asynchronous cases. Additionally, we have developed a new definition of polarization that considers both the distribution of opinions and the network topology. To assess the model's effectivenesseffecti veness, we conducted simulations on two different network types: an ER network and an SBM network. Our findings indicate that the rewiring process has significant effects on polarization, but these effects are dependent on the initial network. What idea of AI? Social and public perception of AI Date Start: 2021-02-01.