Can you write the running time functions (f(n)) in terms of n for the following function and its classification in ters of big-O asymptotic notation. Consider an operation to be variable assigment, data comparision,s arithmetic operations, and conditional statements.bool divisible_12_2(const std::vector<int>& vector){ if (vector.size() < 2) return false; int n = vector.size(); for (int i = 0; i < n; ++i) { for (int j = i +1; j < n; ++j) { if ((vector[i] * vector[j]) % 12 == 0) return true; } } return false;}

B1 Write a function powers array (b) that takes a list (or 1-dimensional numpy array) of length d representing a row vector [bo, ...,ba-1] (for some d) and returns a numpy array representing the matrix bo fd-1 ТТТ 60 d-1 : d-1

I need help Implement this python function. Please help me

Question- Need solution in JavaSomething related to IPO offeringmain gist is we had shares - lets say N which we want to divide among biddersBidders are represented in 2d arrays as[bidder_id, no of shares_bid, price, timestamp]Now build a function returns the bidder_id's in sorted array that did not receive any shares. Shares are allocated following rules- if the price is highest among all the bidders. Allocate shares If the price is same among 2 bidders. Allocate share in iterative fashion, first one get share had earlier timestamp.Like 2 bidders with bidder id 1&2, have same price, timestamp 4 and 1, bids for 5 shares each and N=1.So, in this case only bidder id 1 get share, bidder id 2 will not recieve any shares

Write a function lis_rec(arr) that outputs the length of the longest increasing sequence and the actual longest increasing sequence. This function should use divide and conquer strategy to the solve the problem, by using an auxiliary function that is recursive. For example, one possibility is to define a recursive function, lis_rec(arr, i, prev), that takes the array arr, an index i, and the previous element index prev of LIS (which is part of the array arr before index i), and returns the length of the LIS that can be obtained by considering the subarray arr[i:]. Write a dynamic programming version ofthe function, lis_dp(arr), that outputs the length of the longest increasing sequence and the actual longest increasing sequence by using a table to store the results of subproblems in a bottom-up manner. Test the performance of the two functions on arrays of length n = 100, 500, 1000, 5000, 10000. Compare the running times and memory usage of the two functions.

I need this done in R. Thanks!

Write a function using Java Function Name: winInRowParameters: board: 2D integer array, row: integer, piece: integerReturn: booleanAssume board is valid 2D int array, row is valid index in the board, piece is X==1/O==2Look at indicated row at given index in board. If that row has at least 3 consecutive entries withgiven type of piece (X/O) (3 in a row XXX, OOO), then return true, otherwise false.

Do the part b of the attached question thanks