Answer:
performance -processor speeds increases because the smaller the transistor, the faster it can operate. Additionally, the transistors become closer to each other which reduces the latency between them.
2.Complexity-for a given size the number of transistors doubles with the reduction in feature size
Explanation:
Answer:
It happens to me as well. Maybe check emails? It could also be a bug.
Explanation:
Answer:
Check the explanation
Explanation:
#!usr/bin/python
#FileName: sieve_once_again.py
#Python Version: 2.6.2
#Author: Rahul Raj
#Sat May 15 11:41:21 2010 IST
fi=0 #flag index for scaling with big numbers..
n=input('Prime Number(>2) Upto:')
s=range(3,n,2)
def next_non_zero():
"To find the first non zero element of the list s"
global fi,s
while True:
if s[fi]:return s[fi]
fi+=1
def sieve():
primelist=[2]
limit=(s[-1]-3)/2
largest=s[-1]
while True:
m=next_non_zero()
fi=s.index(m)
if m**2>largest:
primelist+=[prime for prime in s if prime] #appending rest of the non zero numbers
break
ind=(m*(m-1)/2)+s.index(m)
primelist.append(m)
while ind<=limit:
s[ind]=0
ind+=m
s[s.index(m)]=0
#print primelist
print 'Number of Primes upto %d: %d'%(n,len(primelist))
if __name__=='__main__':
sieve()
Answer:
The videos contain the answers.
Explanation:
Answer: b) Standardizing how the process is completed
Explanation:
Occurrence of error in a process can be due to several reason like human error,equipmental error, qualitative error etc.It includes internal as well as external factor.To eliminate the occurrence of fault in process, it is better to follow standard and systematic working in uniform way so that any kind of manipulation and modification does not lead to error.
- Other options are not appropriate because trying harder will not correct chances of fault rather it will only waste the efforts.Not depending on technology is also not the solution to gain accuracy in process.
- Thus, the correct option is option(b).
