Postagens

Network Studies - Modularity

In graph theory and network analysis, modularity measures detect communities or modules in networks. Which of the following statements about modularity is NOT true? a) Modularity measures the strength of dividing a network into modules or communities. High modularity indicates dense connections within modules and sparse connections between modules. b) Modularity is a specific measure that can only be applied to undirected, unweighted graphs. c) Modularity optimization is an approach used to detect communities in networks, but it can potentially lead to resolution issues, especially for larger networks. d) Modularity values range from -1 to 1. A value of 1 indicates perfectly modular, while a value of 0 indicates no modular structure. Negative modularity can arise when links within modules are less than expected. e) None of the above. Original idea by: Leonardo Henrique de Braz.

The Bianconi-Barabási Model

Which of the following statements accurately describes the preferential attachment mechanism in the Bianconi-Barabási model? A) Nodes are added to the network based on a random process without considering the existing nodes' connectivity. B) New nodes connect to existing nodes equally, resulting in a uniform degree distribution. C) Nodes are added to the network based on their fitness, independently of the connectivity of existing nodes. D) New nodes preferentially attach to high-degree nodes, resulting in a power-law degree distribution.  E) None of above Original idea by: Leonardo Henrique de Braz

Network Studies - Barabasi-Albert model

In the context of the Barabasi-Albert model, what is the main difference between a scale-free network and a random network? A) Scale-free networks exhibit a higher clustering coefficient, while random networks exhibit a uniform degree distribution. B) Scale-free networks exhibit an exponential degree distribution, while random networks exhibit a power-law degree distribution. C) Scale-free networks exhibit a power-law degree distribution, while random networks exhibit an exponential degree distribution. D) Scale-free networks and random networks exhibit similar degree distributions but differ in how nodes are connected E) None of the above. Original idea by: Leonardo Henrique de Braz.

Network Studies - Calculus

Consider the integral: \[ \int_{}^{} 3x^2 - 2x + 5 \,dx \] Which of the following represents the correct antiderivative ? a. x^3 - x^2 + 5x + C b. x^3 - 2x^2 + 5x + C c. (3/2)x^3 - x^2 + 5x + C d. (3/2)x^3 - (4/3)x^3 + 5x + C e. None of above Original idea by: Leonardo Henrique de Braz

Network Question - Scale-free networks

About scale-free networks, choose the correct option below: a) Scale-free networks are networks that each node has the same degree b) Scale-free networks are networks that the degree distribution follows the Gaussian distribution c) Scale-free networks are networks that the degree distribution follows the power-law d) Scale-free networks are networks where connectivity between nodes is random e) None of above  Original idea by: Leonardo H. de Braz

Network Question - First Concepts

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 The figure below is a dependency graph about the discipline requirements in a school. The requirement relationship is defined by a direct link, in which a discipline describes its prerequisite to be attended. For example: Discipline D has discipline A as a prerequisite; and Discipline E has disciplines A and B as a prerequisite. Note: the discipline is a node, the prerequisite is a link, and the image is a network. On the figure, consider the following sentences and mark them as true (T) or false (F): The node with the highest (and only) degree is node M; The nodes A, B, and C do not have prerequisites; Discipline G is a prerequisite for discipline H; The incoming degree for discipline O is 2; The outcoming degree for discipline H is 2; The correct option that matches the sentences is: a) T-T-F-F-T b) F-T-F-F-T c) F-F-T-T-T d) T-T-F-T-F e) none of above Original idea by: Leonardo H. de Braz