It needs an Operating System like a cable or something that will help it operate look for more and double check
helps us for typing letters, numbers and symbols etc.
Answer:
A. Sandboxing
Explanation:
The best solution to apply for this task would be Sandboxing. This is a software management strategy that isolates applications from critical system resources and other programs. In doing so you effectively add a secondary security layer on top of the application in order to prevent any and all malware from entering and damaging your overall system. Thus effectively reducing the risk.
Answer:
The answer is "Option D".
Explanation:
A system or a group of components that communicate with your environment through the sharing of resources, materials, and knowledge with a view to system regeneration and development is known as an Open system. In other words, we can say that it is a system that includes a non-proprietary hardware and advert-based software which enables third parties to add or interact with products to plug in the system and It is freely available on the internet. In this question, the incorrect options can be described as follows:
- In option A, The management system is used by an organization. It is a paid system that's why it is not correct.
- In option B, This system enables users in online communities and evaluates one another that's why it is not correct.
- In option C, This type of system provides resources for upgrade user knowledge. It is a paid system that's why it is not correct.
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
