The
piston engine uses the crankshaft to convert the reciprocating motion of the
piston into rotary motion.
<span>The
crankshaft is used to convert reciprocating motion of the piston into rotary
motion, while the conversion process is called torque, which is a twisting
force. Aside from crankshaft, there are a total of four parts of the engine
that work together in order to convert the reciprocating motion into rotary
motion namely cylinder, or also called the chamber of the piston, the piston itself,
and the connecting rod.</span>
Answer:
The correct answer is A.
Explanation:
Moore's Law states/predicts that the maximum number of transistors that can be used on integrated circuits (processors etc.) will be doubled every two years so it basically predicts an exponential growth in terms of transistors used.
Doubling the number of transistors used means that it will almost certainly increase the performance of the processors. Of course there are a lot of other variables that the performance depends on but Moore's Law is proven to be true and is being used since 1960's. The answer given in option A is the one that best reflects on this law.
I hope this answer helps.
Microsoft Expression Web 4 is
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Component of Expression Studio
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Design and Develop Web Pages using HTML5, CC3, ASP.Net, and more
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Requires .Net Framework & Silverlight 4.0
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Answer:
40
Explanation:
Given that:
A neural network with 11 input variables possess;
one hidden layer with three hidden units; &
one output variable
For every input, a variable must go to every node.
Thus, we can calculate the weights of weight with respect to connections to input and hidden layer by using the formula:
= ( inputs + bias) × numbers of nodes
= (11 + 1 ) × 3
= 12 × 3
= 36 weights
Also, For one hidden layer (with 3 nodes) and one output
The entry result for every hidden node will go directly to the output
These results will have weights associated with them before computed in the output node.
Thus; using the formula
= (numbers of nodes + bais) output, we get;
= ( 3+ 1 ) × 1
= 4 weights
weights with respect to input and hidden layer total = 36
weights with respect to hidden and output layer total = 4
Finally, the sum of both weights is = 36 + 4
= 40
