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Andre45 [30]
2 years ago
11

Some elementary particles are positively or negatively

Computers and Technology
2 answers:
patriot [66]2 years ago
6 0

Answer: she is right so I agree with Emily.

nasty-shy [4]2 years ago
4 0

Answer: adverse particles and fueled particles are negatively particles while charged particles and progressive particles are positively particles hope this help!

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scheduling is approximated by predicting the next CPU burst with an exponential average of the measured lengths of previous CPU
dexar [7]

SJF scheduling is approximated by predicting the next CPU burst with an exponential average of the measured lengths of previous CPU bursts.

<h3>What is SJF in operating system?</h3>

SJF is a term that connote Shortest Job First. It is said to be a type of CPU scheduling whose algorithm is linked with each as it is said to process the length of the next CPU burst.

Note that for one to be able to know the time for the next CPU burst to take place, one need to take the SJF into consideration as that is its function.

Hence, SJF scheduling is approximated by predicting the next CPU burst with an exponential average of the measured lengths of previous CPU bursts.

See options below

A) Multilevel queue

B) RR

C) FCFS

D) SJF

Learn more about scheduling from

brainly.com/question/19309520

#SPJ1

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2 years ago
E-mails that are mailed directly to a consumer without their knowledge or permission are called
gizmo_the_mogwai [7]
E-mails that are mailed directly to a consumer without knowledge or permission are called spam
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3 years ago
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Which is a benefit of traditional SLR cameras over digital cameras? A. They produce negatives to serve as backups. B. They make
VLD [36.1K]

B. They make it easy to take panoramic photographs of the crime scene.

Explanation:

  • SLR is the single-lens reflex analog camera with dated looks. Traditional SLR has more manual controls and no monitor on the rear.  
  • A DSLR or Digital Single Lens Reflex camera is a facelift of the traditional SLRs. They are pricey but have the power of capturing minutest details.  
  • SLRs give more opportunity for creativity. They give an important competition to digital cameras in pixel output too.  
  • However, if the quality is paramount invest in a good SLR.

6 0
3 years ago
Dr. Watson has been kidnaped! Sherlock Holmes was contacted by the kidnapper for ransom. Moments later he received a message fro
adelina 88 [10]

Answer:

please mark me brainlist

Explanation:

This algorithm works for n number of strings in python3

Input:

83217

8213897

683147

Output:

837

from itertools import product

import pdb

import numpy as np

def neigh(index):

N = len(index)

for ri in product((0, -1), repeat=N):

if not all(i == 0 for i in ri):

yield tuple(i + i_rel for i, i_rel in zip(index, ri))

def longestCommonSubSequenceOfN(sqs):

numberOfSequences = len(sqs); # to know number of sequences

lengths = np.array([len(sequence) for sequence in sqs]); # to know length of each sequences placed in # array

incrLengths = lengths + 1; # here we are taking no .of sequences +1

lengths = tuple(lengths); # making lengths into tuple to make it mutable

inverseDistances = np.zeros(incrLengths);

ranges = [tuple(range(1, length+1)) for length in lengths[::-1]]; # finding ranges from 1 to each lengths

for tupleIndex in product(*ranges):

tupleIndex = tupleIndex[::-1];

neighborIndexes = list(neigh(tupleIndex)); # finding neighbours for each tupled index value and # store them in list

operationsWithMisMatch = np.array([]); # creating array which are miss matched

 

for neighborIndex in neighborIndexes:

operationsWithMisMatch = np.append(operationsWithMisMatch, inverseDistances[neighborIndex]);

#appending newly created array with operations miss match and inverseDistances

operationsWithMatch = np.copy(operationsWithMisMatch);

# copying newly generated missmatch indexs

operationsWithMatch[-1] = operationsWithMatch[-1] + 1;

# incrementing last indexed value

chars = [sqs[i][neighborIndexes[-1][i]] for i in range(numberOfSequences)];

# finding a string(chars) with neighbour indexes and checking with other sequences

if(all(elem == chars[0] for elem in chars)):

inverseDistances[tupleIndex] = max(operationsWithMatch);

else:

inverseDistances[tupleIndex] = max(operationsWithMisMatch);

 

subString = ""; # resulted string

mainTupleIndex = lengths; # copying lengths list to mainTupleIndex

while(all(ind > 0 for ind in mainTupleIndex)):

neighborsIndexes = list(neigh(mainTupleIndex));

#generating neighbour indexes with main tuple index in form of list

anyOperation = False;

for tupleIndex in neighborsIndexes:

current = inverseDistances[mainTupleIndex];

if(current == inverseDistances[tupleIndex]): # comparing indexes in main tuple index and inverse #distance tuple index

mainTupleIndex = tupleIndex;

anyOperation = True;

break;

if(not anyOperation): # if anyoperation is False then we are generating sunString

subString += str(sqs[0][mainTupleIndex[0] - 1]);

mainTupleIndex = neighborsIndexes[-1];

return subString[::-1]; # reversing resulted string

sequences = ["83217", "8213897", "683147"]

print(longestCommonSubSequenceOfN(sequences)); #837

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3 years ago
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