java – Print SubArray of Maximum Contiguous product in Array

Maximum Product Subarray
Given an array that contains both positive and negative integers, find the subarray of the maximum product .
Examples:

Input: arr[] = {6, -3, -10, 0, 2}
Output: The subarray is {6, -3, -10}

Input: arr[] = {-1, -3, -10, 0, 60}
Output: The subarray is {60}

Input: arr[] = {-2, -3, 0, -2, -40}
Output: The subarray is {-2, -40}

old wallet.dat in password protected zip – looking for contiguous plaintext

So I have an old BTC wallet (~2013) in a zip file, protected by a password I can no longer remember (crazy days). I’m planning on trying to use ‘bkcrack’, provided I can meet the required data for the attack:

Data required

The attack uses at least 12 bytes of contiguous plaintext. The larger the known plaintext, the faster the attack.

Can anyone shed some light on some plain text an old wallet would contain, like headers or something? I don’t remember any wallet addresses or anything like that.

dynamic programming – $ O (n) $ algorithm related to contiguous subsequences

This problem boils down to counting the number $ N $ of contiguous subsets whose sum of elements is equal to $ 2 $ module $ 4 $.

Let the input matrix be $ A = langle a_1, dots, a_n rangle $ and let $ B = langle b_0, dots, b_n rangle $ be a set of $ n + 1 $ elements where $ b_i = sum_ {j = 1} ^ i a_i $. It should be easy to see what you can build $ B $ in linear time.

by $ k = $ 0.1.2.3, leave $ eta_k $ be the number of elements in $ B $ which are equal to $ k $ module 4.

A contiguous subset $ langle a_ {i + 1}, dots, a_j rangle $ of $ A $ has sum 2 module 4 if and only if $ b_j – b_i = 2 pmod {4} $ so we can count the number of ways to select two different indices $ i, j in {0, dots, n } $ such that $ b_j – b_ {i} = 2 pmod {4} $ .

This only happens if $ {b_i, b_j } $ is one of $ {0, 2 } $or $ {1, 3 } $.

exist $ eta_0 cdot eta_2 $ sets of $ {b_i, b_j } $ the first type, and $ eta_1 cdot eta_3 $ sets of the second type.

Thus:
$$
N = eta_0 cdot eta_2 + eta_1 cdot eta_3.
$$

Windows: Why does NTFS store files in contiguous but separate chunks?

I get seemingly conflicting information from contig in a file:

>contig -nobanner -a -v "C:UsersbrunoDownloadspp.big"
------------------------
Processing C:UsersbrunoDownloadspp.big:
Scanning file...
[Cluster] Runlength
  [0] 31272
  [31272] 20376
  [51648] 20652
  [72300] 19452
  [91752] 21269
  [113021] 20674
  [133695] 22565
  [156260] 6409
  [162669] 23291
  [185960] 230176
  [416136] 320942
File size: 3019070010 bytes
C:UsersbrunoDownloadspp.big is in 4 fragments
------------------------
Summary:
     Number of files processed:      1
     Number unsuccessfully procesed: 0

It lists 11 fragments but then says there are only 4 fragments. I used FSCTL_GET_RETRIEVAL_POINTERS to confirm that the first 8 chunks are really consecutive, but why does NTFS register them as separate chunks?

algorithms – how to find all the contiguous subsequence of a matrix is ​​less than O (N ^ 2) time complexity?

I can't find the product of each contiguous subsequence of a matrix in less than O (N ^ 2) time complexity.

 ```
 public class PrintAllSubArrays {

public void printSubArrays(int () arrA){

    int arrSize = arrA.length;
    //start point
    for (int startPoint = 0; startPoint 

}
`` ''

Algorithms: Divides the matrix into contiguous subgroups of approximately the same sums

Looking for an algorithm to divide the matrix of $ n $ positive numbers in $ N $ contiguous subarrys ($ N <n $) of approximately the same sums:

$$
min _ { text {splits}} , ( max_j S_j – min_j S_j),
$$

where $ S_j $ is the sum of numbers in $ j $-th subarray.

For example, the best division of $ 100, 1, 1, 103, 90 $ in three subarrays is $ 100,1,1 | 103 | $ 90.

Typically $ n approx ~ 10 ^ 6-10 ^ 7 $, $ N approx 100 $.

I suspect it would be a greedy approach …

data structures – Number of contiguous subsequences that add up to a given goal

Here is a simple random $ O (n) $ algorithm of time. We begin by reformulating your problem a bit. Suppose that the original matrix is $ a_1, ldots, a_n $. Form a new matrix $ b_0, ldots, b_n $ that contains the current sums of the previous matrix:
$$
b_0 = 0, qquad b_i = a_1 + cdots + a_i.
$$

Realise $ a_i + cdots + a_j = b_j – b_ {i-1} $. Therefore, we can reformulate the problem as follows:

Given a matrix $ b_0, ldots, b_n $ and a goal $ t $, find the number of pairs $ i <j $ such that $ b_j = b_i + t $.

As an example, if $ A = 2,5,6, -1 $ so $ B = 0.2,7,13,12 $, and to $ t = 5 $ we get two solutions: $ 7 – 2 = 12 – 7 = 5 $.

The idea is now very simple: we scan. $ B $ From left to right, and for each $ b_j $, we count the number of values $ b_j-t $ that have previously occurred, storing them using a hash table.

  1. Initialize the solution count: $ N gets $ 0.
  2. Initialize a hash table $ H $ containing a single entry: $ B[b_0] get $ 1.
  3. by $ j = 1, ldots, n $:
    • Yes $ b_j – t in B $, leave $ N gets N + H[b_j – t]$.
    • Yes $ b_j notin H $, leave $ H[b_j] get $ 1, and otherwise leave $ H[b_j] get H[b_j] + $ 1.
  4. He came back $ N $.

The same algorithm can be implemented in deterministic. $ O (n log n) $ time using a self-balancing binary search tree.

Is it valid to travel to the UK with TB that is not contiguous?

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