NSCT PAST PAPERS AND SYLLABUS
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- Increases noise
- Reduces smoothing
- Increases smoothing and reduces detail
- Has no effect
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Explanation
A kernel is used to smooth data by averaging nearby values.
Increasing kernel size means more neighboring points are considered.
This results in stronger smoothing of the data.
However, it also removes fine details and sharp features.
So larger kernels increase smoothing but reduce detail.
- A path can repeat vertices but not edges
- A cycle cannot start and end at the same vertex
- The shortest path always has the maximum number of edges
- Graphs cannot have isolated vertices
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Explanation
A path may revisit vertices but cannot reuse the same edge.
A cycle actually starts and ends at the same vertex, so B is incorrect.
The shortest path minimizes edges or weight, not maximizes them.
Graphs can have isolated vertices with no connections.
- Image classification
- Object detection
- Image filtering
- Edge enhancement
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Explanation
Image classification assigns each pixel or region in an image to a specific category.
In satellite imagery, categories could include roads, mountains, and houses.
Object detection identifies objects and their locations but may not label all pixels.
Image filtering and edge enhancement improve image quality but don’t classify content.
- Higher true positives
- Lower true positives
- Higher false positives
- No effect on model performance
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Explanation
False negatives (FN) occur when the model misses positive cases.
Reducing FN usually means the model is more likely to predict positive.
This increases true positives (TP) but also can increase false positives (FP).
- To write code faster
- To provide guidance for users and developers
- To compile the program
- To secure software
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Explanation
Software documentation explains how a program works and how to use it.
It helps developers understand the code for maintenance or updates.
It guides end-users on using software features effectively.
- Agile
- Waterfall
- Spiral
- Incremental
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Explanation
- The Waterfall model is a sequential SDLC approach.
- Each phase (requirements, design, implementation, testing, deployment) is completed before the next begins.
- It works best when requirements are clear and unlikely to change.
- Agile and Incremental models are better for changing or evolving requirements.
- Spiral focuses on risk management and iterative development.
- RSA
- AES
- SHA-256
- Diffie-Hellman
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Explanation
- AES (Advanced Encryption Standard) is a symmetric encryption algorithm.
- Symmetric encryption uses the same key for encryption and decryption.
- RSA and Diffie-Hellman are asymmetric algorithms using public/private keys.
- SHA-256 is a hash function, not an encryption algorithm.
- Confidentiality
- Integrity
- Availability
- Authentication
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Explanation
Integrity ensures that data is accurate and unaltered.
It protects against unauthorized modifications or tampering.
- Undefined
- Empty string ("")
- []
- 0
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Explanation
In JavaScript, the + operator performs string concatenation if any operand is a string.
[] (an empty array) is converted to an empty string when used with +.
So [] + [] becomes "" + "" → "" (empty string).
This is due to type coercion in JavaScript.
The result is not undefined, [], or 0—it’s an empty string.
- 'hello'
- Undefined
- ['h', 'e', 'l', 'l', 'o']
- 'lo'
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Explanation
The spread operator ... in JavaScript expands iterable objects like strings or arrays.
"hello" is a string, which is iterable.
[..."hello"] spreads each character into a new array.
Resulting array: ['h', 'e', 'l', 'l', 'o'].
It is not a single string or 'lo', and definitely not undefined.
