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Network flow

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A company launched a new gadget C to produce globally for North America and Latin American markets. The company uses just-in-time as a logistic strategy with no warehouse. Still, it has a quality control standard with the assistance of laboratories in the United Kingdom, Spain, and South Africa. The company has some contractors in the Asia-Pacific that make two types of components A and B, to create product C ( to produce one container of product C used two containers of component A and three containers of component B ). In the graph, the logistic circuit of factories(components A in blue arrow and components B) and ensemble centers (located in Singapur Dubai and Egypt) to produce gadget C (The flow of the production and distribution is shown with purple arrows). The number near to arrows shows the capacity to transport from one location to another location. How is the production and distribution in the manufacturing supply chain to deliver the maximum quantity of gadget
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Robustness

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In a power grid, we have tree communities: Red, Blue and Purple . As Figure shows (Each node with number represents a power substation) You are at a networking party to meet influential people. At this party, you meet a man running for governor in a state. Based on the power grid topology (on the figure), the politician asks you about the robustness and the sequence of potential attacks on the power grid. Which of the following statements could you said to the politician: Community Purple is more robust, and community Brown is more vulnerable. Community Red has a decentralized topology. Therefore, in a random attack, community Red will be more resilient. In a targeted attack, the sequence of attacks on power substations is : 37,24 and 18 In a targeted attack, the sequence of attacks on power substations is : 7,18 and 25 Chose the right answer. II and III I and III II and IV I and IV None of the above. Original
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Evolving Networks

We have a model that consider the degree distribution formulation in an induced small-degree saturation of evolving networks with initial attractiveness of 12 . For a degree of 20 the degree distribution is 2.98x10 −8 . And when the degree is 52 , the degree distribution is 9.31x10 −10 . Find the degree exponent. γ=5.0 γ=5.25 γ=5.5 γ=5.75 None of the above. Original idea by: Alexander Valle Rey
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Barabási–Albert model

A student is making some simulations about a Barabási–Albert model with different preferential attachment conditions. He is analyzing a particular network model for different scenarios for α=[0, 0.35, 1, 1.6] When the model is in the superlinear attachment, he found that kmax is 20 at the time t0=5. However, when the model is the linear phase at the time 49 kmax is 28 and when the time is 289, kmax=68, find the degree exponent γ He is using. when the model is the sublinear phase at time t0, kmax=2, find kmax at the time 824. γ=2.5 , kmax=18 γ=3 , kmax=19 γ=2.5 , kmax=19 γ=3, kmax=18 None of the above. Original idea by: Alexander Valle Rey
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Scale-free networks

Complete the sentences with RN or SFN in the following statements, When we compare random networks (RN) and scale-free networks (SFN). I) In ___, most nodes have the same number of links. II) In ___, many nodes with only a few links. III) In ___, there are A few hubs with a huge number of links. IV) In ___, there are Not highly connected nodes. V) In ___, the size of the largest node grows logarithmically or slower with N, implying that hubs will be tiny even in a very large ___. VI) In__ the size of the hubs grows polynomially with network size; hence they can grow quite large in ___. VII) A ___ follows a Poisson distribution, quite similar to a bell curve. VIII) In __ the distribution, most nodes have only a few links. A few highly connected hubs hold together these numerous small nodes. A) RN: I, II,IV, VI,VII and SFN:III, V, VIII B) RN: II, III,IV, Vand
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Graph theory

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In this example, in the picture, a container ship traveled across routes between Asia and Europe. This ship visited 11 countries.The countries are the nodes in this picture, and their travel ruts are the links. If we start from Singapore(sg) using the BFS algorithm, considering the alphabetical order of the name of nodes, the distances of Italy(it), France(fr), and Turkey(tr) are: I) 5,4,2 II) 5,4,3 Using the algorithm DFS the path from Grece(gr) to Italy(it) is: III) gr-tr-eg-ae-it IV) gr-eg-ae-it V) gr-eg-fr-ae-it A) I,IV B)II,IV. C)I,V D) II,III E) None of the above. Original idea from: Rolan Alexander Valle Rey Sánchez. imagen modified from: Wang, Z., Claramunt, C., & Wang, Y. (2019). Extracting Global Shipping Networks from Massive Historical Automatic Identification System Sensor Data: A Bottom-Up Approach. Sensors (Basel, Switzerl
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Basic concepts

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In this example, in the picture, a container ship traveled across routes between Asia and Europe. This ship visited 11 countries, 19 ports, and 22 terminals. The countries are the nodes in this picture, and their travel ruts are the links. Which country, if its ports were closed by an epidemic, could stop the travel of the container ship to other countries following its travel network? A. Spain, Singapore, or China B. Singapore or China C. China or Grecia D. Greece, Egypt, or the United Arab Emirates E. None of the above. Original idea from: Rolan Alexander Valle Rey Sánchez. imagen from: Wang, Z., Claramunt, C., & Wang, Y. (2019). Extracting Global Shipping Networks from Massive Historical Automatic Identification System Sensor Data: A Bottom-Up Approach. Sensors (Basel, Switzerland), 19. http://dx.doi.org/10.3390/s19153363
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