Answer:
A. 4 CPUs and 6 megabyte cache memory
B. 1.3157 x10^-9 nanoseconds
Explanation:
The Intel core i5 7500 is a seventh generation central processing unit with a 4 CPU core and a 6 megabyte cache memory. It executes task at a clock cycle of 5 clock cycle at a speed of 3.8 GHz.
The relationship between frequency and clock cycle is,
Clock cycle = 1 / ( frequent).
So, One clock cycle = 1 / 3.8 GHz
= 0.3 x10^-9
For five clock cycles = 5 x 0.3 x10^-9
= 1.3157 x10^-9 nanoseconds.
AnswerB
Explanation:Makes since to look over the notes each night before the exam
Answer is a
passphrase
Passphrase consists of characters longer than passwords used
in creating digital signatures. As compared to passwords, passphrases are
easier to remember and considered more secure due to the overall length. Both Passphrase
and passwords serve the same purpose of securing sensitive information.
A type of encoding that involves relating new information to existing knowledge that you already have stored in long-term memory is: Semantic encoding.
Encoding can be defined as a communication process in which the sender of a message transforms an information into an encrypted message, in the form of notable symbols that represent ideas or concepts.
Generally, a message that has been encoded by a sender requires a decoding action by the recipient, in order for the communication process to be complete.
Semantic encoding is a type of encoding which typically involves the relation of new information with respect to an existing knowledge that has been stored in long-term memory.
In conclusion, semantic encoding deals with the encoding of meaning from new information rather than perceptual characteristics such as the meaning of words in English language.
Read more: brainly.com/question/24113575
Answer:
a. This is an instance of overfitting.
Explanation:
In data modeling and machine learning practice, data modeling begins with model training whereby the training data is used to train and fit a prediction model. When a trained model performs well on training data and has low accuracy on the test data, then we say say the model is overfitting. This means that the model is memorizing rather Than learning and hence, model fits the data too well, hence, making the model unable to perform well on the test or validation set. A model which underfits will fail to perform well on both the training and validation set.
