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mr Goodwill [35]

3 years ago

6

What do you remember about the difference between Canadian and US dollar (which one is greater)? Also, explain which online tool

would you use to convert 10 Canadian dollars into US dollars and how much USD will you get?

Computers and Technology

1 answer:

Talja [164]3 years ago

8 0

I’m not sure about USD but Canadian dollars are greater, one dollar CAD is equal to $0.79 US. So $10 CAD is equal to $7.90 US.

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A_______VPN connection is a private network that uses a public

goldfiish [28.3K]

Answer:

letter c. point to site po sagot diyan

3 0

3 years ago

A contiguous subsequence of a list S is a subsequence made up of consecutive elements of S. For example, if S is 5,15,-30,10,-5,

Sindrei [870]

Answer:

We made use of the dynamic programming method to solve a linear-time algorithm which is given below in the explanation section.

Explanation:

Solution

(1) By making use of the dynamic programming, we can solve the problem in linear time.

Now,

We consider a linear number of sub-problems, each of which can be solved using previously solved sub-problems in constant time, this giving a running time of O(n)

Let G[t] represent the sum of a maximum sum contiguous sub-sequence ending exactly at index t

Thus, given that:

G[t+1] = max{G[t] + A[t+1] ,A[t+1] } (for all 1<=t<= n-1)

Then,

G[0] = A[0].

Using the above recurrence relation, we can compute the sum of the optimal sub sequence for array A, which would just be the maximum over G[i] for 0 <= i<= n-1.

However, we are required to output the starting and ending indices of an optimal sub-sequence, we would use another array V where V[i] would store the starting index for a maximum sum contiguous sub sequence ending at index i.

Now the algorithm would be:

Create arrays G and V each of size n.

G[0] = A[0];

V[0] = 0;

max = G[0];

max_start = 0, max_end = 0;

For i going from 1 to n-1:

// We know that G[i] = max { G[i-1] + A[i], A[i] .

If ( G[i-1] > 0)

G[i] = G[i-1] + A[i];

V[i] = V[i-1];

Else

G[i] = A[i];

V[i] = i;

If ( G[i] > max)

max_start = V[i];

max_end = i;

max = G[i];

EndFor.

Output max_start and max_end.

The above algorithm takes O(n) time .

4 0

3 years ago

Someone plzzzz help me

IgorC [24]

Answer:

Data base

Explanation:

Database holds all your information.

8 0

3 years ago

public class Questions { public static void main(String[] args) { System.out.print("Here "); System.out.println("There " "Everyw

In-s [12.5K]

Answer:

The output of this code can be given as follows:

Output:

Here There Everywhere

But notin Texas

Explanation:

In the give java code a class "Questions" is defined inside this class the main method is defined in the main method we use three print function that can be described as follows:

In the first print function, we print the message that is "Here".
In the second and third print function, we use println that print data or message in the next line that is "There Everywhere" and in the next line "But not" and "in Texas".

6 0

3 years ago

Statement: There are two files. One file, "badIP_list.txt" has a listing of known bad IP addresses. These addresses were extract

lapo4ka [179]

Answer:

See explaination

Explanation:

SOURCE CODE IN PYTHON:

inp=open('badIP_list.txt', 'r') #opening file for input

badIPs=[i.rstrip('\n') for i in inp.readlines()] #reading bad IPs

inp.close() #closing file

inp=open('server_logs.txt', 'r') #opening file for input

IPs=[i.rstrip('\n') for i in inp.readlines()] #reading all IPs from log

inp.close() #closing file

uniqueBadIPs=[] #to store unique bad IPs

countBadIPs=0 #to store count of bad IPs

countIPs=0 #to store count of all IPs

for IP in IPs: #iterating through the log of IPs

if IP in badIPs: #checking if IP is bad

countBadIPs+=1

if IP not in uniqueBadIPs: #checking if bad IP is unique

uniqueBadIPs.append(IP)

countIPs+=1

out=open('filter_list.txt', 'w') #opening file for output

out.write('_________________________________________________________\n')

out.write('Date : 26/07/2018\nName : Last, First\nMajor: CS\n\n')

out.write('Server logs contained these known bad IP addresses:\n')

for IP in uniqueBadIPs: #output the unique bad IPs

out.write(IP+'\n')

out.write('\n')

out.write('Total unique known bad IP\'s detected:\n'+str(len(uniqueBadIPs))+'\n\n')

out.write('Percentage of bad IP addresses in server logs:\n{:.2f}%\n'.format(countBadIPs*100/countIPs))

out.write('_________________________________________________________')

out.close() #closing file

5 0

4 years ago