In 2 1 2 Out 1 Out 2 In _ 1 A "path" in 2D space can be defined as a list of 2D points, where each 2D point is expressed with its x-y coo 3 A 3 A 1926 ^ example of path with three points is given below. path_example = [(1, 1), (2, 3), (3, 8)] path_example [(1, 1), (2, 3), (3, 8)] [(1, 1), (2, 3), (3, 8)] Write a function, path_length(), which takes a "path" as input and calculates the total distance of the path the points map out, starting from the first point in the list to the second, the second to the third, and so on. The total distance is the sum of all of the distances of segments forming the path. The function path_length() should return this total distance. It is assumed that the list of points is already in the correct order. The function definition has been started for you below. Complete it with your answer • On successful implementation, execution of this cell will print success (5 points) ⠀

In 2 1 2 Out 1 Out 2 In _ 1 A "path" in 2D space can be defined as a list of 2D points, where each 2D point is expressed with its x-y coo 3 A 3 A 1926 ^ example of path with three points is given below. path_example = [(1, 1), (2, 3), (3, 8)] path_example [(1, 1), (2, 3), (3, 8)] [(1, 1), (2, 3), (3, 8)] Write a function, path_length(), which takes a "path" as input and calculates the total distance of the path the points map out, starting from the first point in the list to the second, the second to the third, and so on. The total distance is the sum of all of the distances of segments forming the path. The function path_length() should return this total distance. It is assumed that the list of points is already in the correct order. The function definition has been started for you below. Complete it with your answer • On successful implementation, execution of this cell will print success (5 points) ⠀

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

See similar textbooks

Similar questions

A star configuration of a network represents its structure as a graph with an edge from a single, central node to each remaining node. A point-to-point configuration represents a network as a complete graph. Draw a picture of an example of each kind of configuration with four nodes, and use big-O notation to state the efficiency of adding or removing a given node in each type of configuration. You can assume for now that removing each edge is a constant-time operation. *Python
The highway distance between 6 cities named (A ... G) are illustrated in the following adjacency matrix:A B C D E FA 0 7 19   28B 7 0 10 18 40 C 19 10 0 16  17D  18 16 0 14 10E  40  14 0 12F 28  17 10 12 a) Draw the graph that represent such adjacency matrix b) List the right sequence of nodes traversed by the DFS and BFS algorithm starting from node A. c) Does this graph possess a Euler circuit/path? , why? If any of them does not exist, how the graph can be modified to have one? d) Draw the minimum spanning tree of this graph . e) Use the Dijkstra's algorithm to determine the shortest paths from city (A) to all other cities . Determine the shortest path and cost from node A to node E .[Hint: implement the algorithm step by step to show which node will be added in sequence] f) Determine the shortest paths between all pairs of nodes using Floyd-Warshall algorithm.
Question 1: In graph theory, a graph X is a "complement" of a graph F if which of the following is true? Select one: a. If X is isomorph to F, then X is a complement of F. b. If X has half of the vertices of F (or if F has half of the vertices of X) then X is a complement of F. c. If X has the same vertex set as F, and as its edges ONLY all possible edges NOT contained in F, then X is a complement of F. d. If X is NOT isomorph to F, then X is a complement of F. Question 2: Which statement is NOT true about Merge Sort Algorithm: Select one: a. Merge Sort time complexity for worst case scenarios is: O(n log n) b. Merge Sort is a quadratic sorting algorithm c. Merge Sort key disadvantage is space overhead as compared to Bubble Sort, Selection Sort and Insertion Sort. d. Merge Sort adopts recursive approach
A network topology specifies how computers, printers, and other devices are connected over a network. The figure below illustrates three common topologies of networks: Ring, Star, and Fully Connected Mesh. You are given a boolean matrix A[0..n−1, 0..n−1], where n > 3, which is supposed to be the adjacency matrix of a graph modeling a network with one of these topologies. Your task is to determine which of these three topologies, if any, the matrix represents. Design a brute-force algorithm for this task and indicate its time efficiency class.
Although the plot function is designed primarily for plotting standard xy graphs, it can be adapted for other kinds of plotting as well. b. Make a plot of the curve, which is defined parametrically by the equations x = 2cosθ + cos2θ, y = 2sinθ - sin2θ, where 0 < θ < 2π. Take a set of values of θ between zero and 2π and calculate x and y for each from the equations above, then plot y as a function of x. b. Taking this approach a step further, one can make a polar plot r = f(θ) for some function f by calculating r for a range of values of θ and then converting r and θ to Cartesian coordinates using the standard equations x = r cosθ, y = r sinθ. Use this method to make a plot of the function r = ecosθ – 2 cos(4θ) + sin5 (θ/12) in the range 0 <= θ <= 24π. use python code to answer the highlight one
3. Assume a graph G = (V, E) represents a computer network where the vertices represent computers and the edges represent point-to-point network connections between the computers. Assume each edge (u, v) of G is associated with a real number f(u,v) between 0 and 1 which represents the probability that the corresponding network connection is faulty. Assume these probabilities are independent. a. Propose an algorithm that finds a path between two given vertices u and v with the smallest probability of being faulty (a path is faulty if at least one of its edges is faulty). b. Analyze the complexity of your algorithm.
Prolog Consider the (directed) network in the attached document. We could represent this network with the following Prolog statements: link(a,b). link(a,c). link(b,c). link(b,d). link(c,d). link(d,e). link(d,f). link(e,f). link(f,g). Now, given this network, we say that there is a "connection" from a node "X" to a node "Y" if we can get from "X" to "Y" via a series of links, for example, in this network, there is a connection from "a" to "d", and a connection from "c" to "f", etc. Formulate the appropriate Prolog rule "connection(X,Y)" which is true if (and only if) there is a "connection" from "X" to "Y" as described above --- note that this rule will be recursive. Test this rule out on the above network, to see if it is working correctly. Once it is working correctly, you will note that, e.g., the query "connection(a,e)." will give "true" multiple times. This means something, actually:
Given: Language L3 = {w ϵ {a,b}* | w starts in ab and ends in bb} Construct the DFA representing the given language L3. Assume the layout of the DFA is as follows: ->A->B->C->D->E*. That is, the number of states are five (5) and A is the starting state and E is the accepting state. How many edge/s goes to null state in the constructed DFA representing the given language L3?
R-13.7 - Let G be a graph whose vertices are the integers 1 through 8, and let the adjacent vertices of each vertex be given by the table below: Vertex: 1 2 3 4 5 6 7 8 Adjacent Vertices: (2, 3, 4) (1, 3, 4) (1, 2, 4) (1, 2, 3, 6) (6, 7, 8) (4, 5, 7) (5, 6, 8) (5, 7) Assume that, in a traversal of G, the adjacent vertices of a given vertex are returned in the same order as they are listed in the table above. a. Draw G. b. Give the sequence of vertices of G visited using a DFS traversal starting at vertex 1. c. Give the sequence of vertices visited using a BFS traversal starting at vertex 1.
Consider a system that handles railway connections as it associates (source) cities to all their corresponding destinations. The requirements of the system are as follows: 1. A source city may have connections to possibly multiple destination cities. 2. Multiple source cities may share the same group of destination cities. We introduce type CITY . A possible state of the system is shown below as it is captured by variable connections:connections ={Montreal → {Ottawa, Kingston, Quebec, Halifax},Ottawa → {Montreal, Toronto},Toronto → {Montreal, Ottawa},Halifax → {Montreal, Quebec},Quebec → {Montreal, Halifax},Kingston → {Montreal}} 1. Is connections a binary relation? Explain why, and if so express this formally. 2. In the expression connections ∈ (...), what would the RHS be? 3. Is connections a function? If so, define the function formally, and reason about the properties of injectivity, surjectivity and bijectivity. 4. Describe the meaning and evaluate the following…
The relations from Exercise 3 are: a. (1,1), (1,3), (2,2), (3,1), (3,3) b. (1,2), (2,2), (3,2) c. (1,1), (1,2), (1,3), (2,1), (2,3), (3,1), (3,2), (3,3) There will be 3 directed graphs. One representing a, then b, then c
QUESTION ONE (20 MARKS)1.1 Consider the state space graph shown below. P is the start state and V is the goal state. The costs for each edge are shown on the graph. Each edge can be traversed in both directions.1.1.1 Use Breadth-First Search to generate the shortest path from P to V. (10)1.1.2 Apply the Depth First Search method to find a path from P to V. (10)QUESTION TWO (20 MARKS)2.1 Compute the truth table for the following expressions and their subexpressions.2.1.1 (p → q) ≡ (NOT p OR q) (5)2.1.2 p → (q → (r OR NOT p)) (5)2.1.3 (p OR q) → (p AND q) (5)2.1.4 (p AND q) → (p OR r) (5)QUESTION THREE (10 MARKS)3.1 The binary exclusive-or function, ⊕, is defined to have value TRUE if and only if exactly one of its arguments are TRUE.3.3.1 Draw the truth table for ⊕. (5)3.3.2 Is ⊕ commutative? Is it associative? (5)PQRSTVUQUESTION FOUR (20 MARKS)4.1 Translate the following sentences into a Prolog program (10)Everyone who teaches programming module is smart.Craig teaches the programming…