UGC NET Computer Science 2024 Previous Year Questions (PYQs) – Page 17 of 20
A Place for Latest Exam wise Questions, Videos, Previous Year Papers,
Study Stuff for MCA Examinations
Study Stuff for MCA Examinations
Showing 199 questions
Match List – I with List – II.
| List – I | List – II |
| (A) Natural language processing | (I) A method of training algorithm by rewarding desired behaviour and/or punishing undesired one. |
| (B) Reinforcement learning | (II) System designed to emulate the decision making abilities of a human expert. |
| (C) Support vector machine | (III) A branch of AI focused on understanding and generating human language. |
| (D) Expert system | (IV) A machine learning technique that finds the hyperplane that best separates different classes in a feature space. |
Choose the correct answer from the options given below :
1
2
3
4
Solution
(A) Natural language processing → Understanding human language → (III)
(B) Reinforcement learning → Reward and punishment learning → (I)
(C) Support vector machine → Hyperplane classification method → (IV)
(D) Expert system → Decision making like human expert → (II)
40 software professionals were interviewed for a job.
25 knew PYTHON, 20 knew JAVA and 7 knew neither language.
How many knew both languages?
1
2
3
4
Solution
Total people = 40
People who know neither = 7
So people who know at least one language:
40 − 7 = 33
Use formula:
n(P ∪ J) = n(P) + n(J) − n(P ∩ J)
33 = 25 + 20 − x
33 = 45 − x
x = 12
How does a relational database ensure data integrity?
1
2
3
4
Solution
Relational databases ensure data integrity using:
• Primary keys
• Foreign keys
• Constraints
• Schema rules
Thus integrity is maintained by enforcing rules defined in the schema.
Consider the following code :
#include<stdio.h>
void f1(char *x, char *y) {
char *t;
t = x;
x = y;
y = t;
}
void f2(char **x, char **y) {
char *t;
t = *x;
*x = *y;
*y = t;
}
int main()
{
char *a = "ONE", *b = "TWO";
f1(a, b);
printf("%s %s", a, b);
f2(&a, &b);
printf("%s %s", a, b);
return 0;
}
What will be the output of the above code?
1
2
3
4
Solution
Initial values
a = "ONE"
b = "TWO"
Step 1: f1(a, b)
Function parameters are passed by value.
Inside f1 the pointers swap locally:
x ↔ y
But original variables a and b do not change.
So after f1:
a = ONE
b = TWO
First printf prints:
ONE TWO
Step 2: f2(&a, &b)
Now addresses of pointers are passed.
Inside f2:
t = *x
*x = *y
*y = t
This swaps actual pointers a and b.
After swap:
a = TWO
b = ONE
Second printf prints:
TWO ONE
Read the below passage and answer the questions.
Artificial Neural Networks (ANNs) are computational models inspired by the human brain’s neural networks. They consist of interconnected nodes, or neurons, organized into layers: an input layer, one or more hidden layers and an output layer. Each connection between neurons has a weight that adjusts as learning progresses allowing the network to adapt and improve its performance. ANNs are particularly effective in recognizing patterns making them valuable for tasks such as image and speech recognition, natural language processing and predictive analytics. Learning in ANNs typically involves training algorithms like back propagation, which minimize the error by adjusting the weights. As a subset of machine learning, ANNs have revolutionized the field of Artificial Intelligence by providing solutions to complex problems that traditional algorithms struggle with.
Which of the following is/are the application area(s) of ANN ?
Which of the following is/are the application area(s) of ANN ?
(A) Natural Language Processing
(B) Image Processing
(C) Pattern Recognition
(D) Speech Recognition
Choose the correct answer from the options given below :
1
2
3
4
Solution
The passage clearly states that ANNs are useful in:
• Image recognition
• Speech recognition
• Natural language processing
• Pattern recognition
Thus all listed areas are applications of ANN.
Read the below passage and answer the questions.
Artificial Neural Networks (ANNs) are computational models inspired by the human brain’s neural networks. They consist of interconnected nodes, or neurons, organized into layers: an input layer, one or more hidden layers and an output layer. Each connection between neurons has a weight that adjusts as learning progresses allowing the network to adapt and improve its performance. ANNs are particularly effective in recognizing patterns making them valuable for tasks such as image and speech recognition, natural language processing and predictive analytics. Learning in ANNs typically involves training algorithms like back propagation, which minimize the error by adjusting the weights. As a subset of machine learning, ANNs have revolutionized the field of Artificial Intelligence by providing solutions to complex problems that traditional algorithms struggle with.
What is the role of Back Propagation Algorithm ?
1
2
3
4
Solution
The passage states that back propagation is a training algorithm used in neural networks that minimizes the error by adjusting the weights.
Thus its role is to reduce prediction error during training.
Read the below passage and answer the questions.
Artificial Neural Networks (ANNs) are computational models inspired by the human brain’s neural networks. They consist of interconnected nodes, or neurons, organized into layers: an input layer, one or more hidden layers and an output layer. Each connection between neurons has a weight that adjusts as learning progresses allowing the network to adapt and improve its performance. ANNs are particularly effective in recognizing patterns making them valuable for tasks such as image and speech recognition, natural language processing and predictive analytics. Learning in ANNs typically involves training algorithms like back propagation, which minimize the error by adjusting the weights. As a subset of machine learning, ANNs have revolutionized the field of Artificial Intelligence by providing solutions to complex problems that traditional algorithms struggle with.
Which of the following layers may be more than one in number?
1
2
3
4
Solution
In an Artificial Neural Network:
• Input layer → usually only one
• Output layer → usually only one
• Hidden layers → can be one or more layers
Thus the layer that may be more than one is hidden layer.
Read the below passage and answer the questions.
Artificial Neural Networks (ANNs) are computational models inspired by the human brain’s neural networks. They consist of interconnected nodes, or neurons, organized into layers: an input layer, one or more hidden layers and an output layer. Each connection between neurons has a weight that adjusts as learning progresses allowing the network to adapt and improve its performance. ANNs are particularly effective in recognizing patterns making them valuable for tasks such as image and speech recognition, natural language processing and predictive analytics. Learning in ANNs typically involves training algorithms like back propagation, which minimize the error by adjusting the weights. As a subset of machine learning, ANNs have revolutionized the field of Artificial Intelligence by providing solutions to complex problems that traditional algorithms struggle with.
Artificial Neural Networks (ANNs) are inspired by:
1
2
3
4
Solution
The passage states that ANN models are inspired by the human brain’s neural networks.
Read the below passage and answer the questions.
Artificial Neural Networks (ANNs) are computational models inspired by the human brain’s neural networks. They consist of interconnected nodes, or neurons, organized into layers: an input layer, one or more hidden layers and an output layer. Each connection between neurons has a weight that adjusts as learning progresses allowing the network to adapt and improve its performance. ANNs are particularly effective in recognizing patterns making them valuable for tasks such as image and speech recognition, natural language processing and predictive analytics. Learning in ANNs typically involves training algorithms like back propagation, which minimize the error by adjusting the weights. As a subset of machine learning, ANNs have revolutionized the field of Artificial Intelligence by providing solutions to complex problems that traditional algorithms struggle with.
What is the role of weights in an ANN?
1
2
3
4
Solution
Weights represent the strength of connections between neurons.
During training, weights are adjusted to reduce error and improve performance.
The Banker’s Algorithm is a critical deadlock avoidance method used in operating systems. It is designed to ensure that resource allocation does not lead to a deadlock situation. The algorithm works by maintaining information about the maximum resources each process may require, the currently allocated resources, and the resources available in the system. Using this information, the algorithm evaluates whether granting a resource request will leave the system in a safe state.
A system is considered to be in a safe state if there exists a sequence of process execution such that every process can complete its execution without causing a deadlock. Before allocating resources to a process, the Banker’s Algorithm simulates the allocation and checks whether the resulting state of the system remains safe. If the system remains safe, the request is granted; otherwise, the process must wait.
Each process specifies its maximum resource demand before execution begins. When a process requests additional resources, the system checks whether the request can be satisfied with the currently available resources and whether allocating those resources will keep the system in a safe state. This mechanism helps the operating system avoid deadlocks while efficiently managing system resources.
Which of the following is NOT a requirement for Banker’s algorithm to grant a resource request?
Which of the following is NOT a requirement for Banker’s algorithm to grant a resource request?
1
2
3
4
Solution
Banker’s Algorithm grants a request only if the following conditions are satisfied:
• The requested resources are available in the system.
• The request does not exceed the maximum claim of the process.
• After allocation, the system remains in a safe state.
However, the algorithm does not require that the process be the only one requesting resources. Multiple processes can request resources simultaneously.
Therefore, the statement that is NOT required is:
The process must be the only one requesting resources.
UGC NET Computer Science
Online Test Series, Information About Examination,
Syllabus, Notification
and More.
View More
UGC NET Computer Science
Online Test Series, Information About Examination,
Syllabus, Notification
and More.
View More
Ask Your Question or Put Your Review.
