<｜begin▁of▁sentence｜>### Instruction:
As an Urban Designer, consider a scenario where you're working on the development of a new urban community. To optimize the layout and design, you want to leverage network analysis techniques. You have a dataset representing the connections between various elements in the community, such as buildings, parks, streets, and public spaces. Using the Bayan community detection method in the cdlib library, you aim to identify distinct clusters within the network. You want to specify parameters such as the optimality gap threshold, allowable execution time, and resolution parameter for the modularity function to customize the analysis. Once the communities have been detected, you need to generate and print a JSON representation of the identified clusters for further planning and development.
### Response:
import networkx as nx
from cdlib import algorithms

# Read the graph
G = nx.read_gml('adjnoun.gml')

# Apply the Bayan community detection algorithm
com = algorithms.bayan(G, threshold=0.001, time_allowed=100, resolution=1.0)

# Generate JSON representation of the communities
communities_json = com.to_json()
print(communities_json)
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