The given figure shows the module decomposition of a Use set to represent the grouped modules for integration testing, e.g. (a, b) implies modules a and b are tested together. Which one is correct? 3 5 4 7 8 9 The bottom-up integration should start with (3.5). The bottom-up integration should start with [1,2,6). O The bottom-up integration should start with (1,6). The bottom-up integration should start with (2,3,4,5). O The bottom-up integration should start with (6,7,8,9).

The given figure shows the module decomposition of a Use set to represent the grouped modules for integration testing, e.g. (a, b) implies modules a and b are tested together. Which one is correct? 3 5 4 7 8 9 The bottom-up integration should start with (3.5). The bottom-up integration should start with [1,2,6). O The bottom-up integration should start with (1,6). The bottom-up integration should start with (2,3,4,5). O The bottom-up integration should start with (6,7,8,9).

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

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∑ = {C,A,G,T}, L = { w : w = CAjGnTmC, m = j + n }. For example, CAGTTC ∈ L; CTAGTC ∉ L because the symbols are not in the order specified by the characteristic function; CAGTT ∉ L because it does not end with C; and CAGGTTC ∉ L because the number of T's do not equal the number of A's plus the number of G's. Prove that L ∉ RLs using the RL pumping theorem.
Step 1. Intersection over Union # def intersection_over_union(dt_bbox, gt_bbox): ---> return iou Step 2. Evaluate Sample We now have to evaluate the predictions of the model. To do this, we will write a function that will do the following: Take model predictions and ground truth bounding boxes and labels as inputs. For each bounding box from the prediction, find the closest bounding box among the answers. For each found pair of bounding boxes, check whether the IoU is greater than a certain threshold iou_threshold. If the IoU exceeds the threshold, then we consider this answer as True Positive. Remove a matched bounding box from the evaluation. For each predicted bounding box, return the detection score and whether we were able to match it or not. def evaluate_sample(target_pred, target_true, iou_threshold=0.5): # ground truth gt_bboxes = target_true['boxes'].numpy() gt_labels = target_true['labels'].numpy() # predictions dt_bboxes =…
The compass gradient operators of size 3x3 are designed to measure gradients of edges oriented in eight directions: E, NE, N, NW, W, SW, S, and SE. i) Give the form of these eight operators using coefficients valued 0, 1 or – 1. ii) Specify the gradient vector direction of each mask, keeping in mind that the gradient direction is orthogonal to the edge direction.
SOLVE IN PYTHON A bracket is considered to be any one of the following characters: (, ), {, }, [, or ]. Two brackets are considered to be a matched pair if the an opening bracket (i.e., (, [, or {) occurs to the left of a closing bracket (i.e., ), ], or }) of the exact same type. There are three types of matched pairs of brackets: [],{},and ().A matching pair of brackets is not balanced if the set of brackets it encloses are not matched. For example, {[(])} is not balanced because the contents in between { and } are not balanced. Write a program that take string of bracket pairs from user and reply Yes or No after evaluate. Your program should working like This.{[()]} Yes{[(])} No{{[[(())]]}} Yes
Write a procedure called STRUCTURE-TO-MATRIX that takes an adjacency structure as its only parameter, and returns an equivalent adjacency matrix. Assume there is a procedure MAKE-MATRIX(m, n) that returns an m × n integer matrix, where m ≥ 0 and n ≥ 0. The integers in this matrix are undefined.
a) Design an adjacency Matrix of the alphabets of your full name. In accordance with the following conditions:• If your name has repeated characters (e.g. character E, 2 times) then you will consider only 1 time.• If your Name contains both G and S, then there will be an edge between them and one additional edge from W to each if W is also in your name. • If N is the alphabet in your name, it will have an edge to A and S if it available in your name.• If P is available then it will have an edge with L if it is available.• If there is a blank space in full Name then it will be represented by “_”, and it must have an edge with all alphabets.(Note: Place on in 1 for Edge and 0 for No Edge)b) Sketch an undirected graph of the above designed adjacency matrix.
You are organizing a conference that has received n submitted papers. Your goal is to get people to review as many of them as possible. To do this, you have enlisted the help of k reviewers. Each reviewer i has a cost sij for writing a review for paper j. The strategy of each reviewer i is to select a subset of papers to write a review for. They can select any subset S; C {1,2, ..., n}, as long as the total cost to write all reviews is less than T (the time before the deadline): 2 Sij 1. (b) Show that for B = 2 this fraction is close to 1/3. [Hint: You can consider an instance with 3n + 1 papers and only n will be reviewed.]
A deadlock is the very unpleasant situation that may occur in very dynamic world of running processes, a situation that must be avoided at all costs. One famous algorithm for deadlock avoidance is the Banker's algorithm for deadlock avoidance. The version of this algorithm presented in this module's commentary gives just one solution (the Greedy approach). Consider the Greedy approach to the Banker's algorithm. Give an example of application of this algorithm for 7 processes (named P1, ... , P7) and 5 resource types (named R1, ... , R5). Start by listing the matrices involved in this algorithm, that constitute its input data; also, do not forget to mention the overall resources of each type available in this fictional system. Proceed by describing the algorithm, step by step; for each step, mention the test performed, which process was chosen, what is the old and new status of the Work array, etc. In the end, list the solution, that is the safe sequence of processes resulting from this…
A transaction database is a set of transactions completed in a supermarket database. Each transaction is a set of items. For example, consider the following transaction database. It contains 5 transactions (t1, t2, ..., t5) and 5 items (1,2, 3, 4, 5). For example, the first transaction represents the set of items 1, 3 and 4. It is important to note that an item is not allowed to appear twice in the same transaction and that items are assumed to be sorted by lexicographical order in a transaction. Transaction id Items t1 {1, 3, 4} t2 {2, 3, 5} t3 {1, 2, 3, 5} t4 {2, 5} t5 {1, 2, 3, 5} What is the output of the Apriori algorithm run on the previous transaction database with a minimum support of 40 % (2 out of 5 transactions)?
Q3 In a company, there are several branches. Let us consider a branch of that company having N employees, if the manager is allotted to that branch(s) then he is known to everyone else in that branch. Note that the property of "known to everyone" is unique to a manager. Your task is to find the manager in that branch. Input from the user in main (), the square matrix M where if an element of row i and column j is set to 1 it means that ith person knows jth person. You need to write a function managerId () which returns the id of the manager if present or else returns -1. The function managerId () takes two arguments - the square matrix of N *N and its size N. Call managerId () from the main () output the information about the manager. Assume all diagonal elements to be 1 (as everyone knows him/herself) and there is at most one manager in the company. Example: No of persons N = 3 Input matrix: 0 1 1 1 0 1 Output: manager is person 3 1 0 1
Before using the spark ML library to train the machine learning model; we are required to assemble the features into one vector. If you are given a spark dataframe DF with numerical columns ['featurel','feature2', 'feature3', 'feature4', 'label'] Import all necessary libraries and write a spark code snippet to assemble features Vector for ['featurel','feature2', 'feature3', 'feature4']
Write a MATLAB program that prompt the user to enter a matrix (A), then generate and display the matrix (B) which is the transpose of (A) matrix without use the transpose operator ('). A-[1 2 5; 5 4 7; 321; 689] Hint: use loops.