NTA-NET (Based on NTA-UGC) Computer Science (Paper-II): Questions 512 - 516 of 2104
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Question number: 512
» Image Processing » Image Registration
Appeared in Year: 2012
Question
You are given four images represented as
The value of entropy is maximum for image (December Paper III)
Choices
| Choice (4) | Response | |
|---|---|---|
a. |
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b. |
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c. |
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d. |
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Question number: 513
» Linear Programming Problem » LPP Standard Form, LPP in Canonical Form
Appeared in Year: 2012
Question
In a Linear Programming Problem, suppose there are 3 basic variables and 2 non-basic variables, then the possible number of basic solutions are (December Paper III)
Choices
| Choice (4) | Response | |
|---|---|---|
a. | 6 | |
b. | 8 | |
c. | 10 | |
d. | 12 | |
Question number: 514
» Data and File Structures » Trees & Graphs
Appeared in Year: 2012
Question
58 lamps are to be connected to a single electric outlet by using an extension board each of which has four outlets. The number of extension boards needed to connect all the light is (December Paper III)
Choices
| Choice (4) | Response | |
|---|---|---|
a. | 29 | |
b. | 19 | |
c. | 20 | |
d. | 28 | |
Question number: 515
» Programming in C and C Plus Plus » O-O Programming Concepts » Inheritance, Polymorphism, Abstraction, Encapsulation and Overloading
Appeared in Year: 2012
Question
When a programming Language has the capacity to produce new datatype, it is called as, (December Paper III)
Choices
| Choice (4) | Response | |
|---|---|---|
a. | Extensible Language | |
b. | Abstraction Language | |
c. | Overloaded Language | |
d. | Encapsulated Language | |
Question number: 516
» Neural Networks and AI » Application
Appeared in Year: 2012
Question
Match the following: (December Paper III)
| List-Ⅰ (Group I) | List-Ⅱ (Group II) |
|---|---|
(A) Inductive learning | (i) Manual labels of inputs are used. |
(B) Unsupervised learning | (ii) Manual labels of inputs are not used. |
(C) Supervised learning | (iii) The decision system receives rewards for its action at the end of a sequence of steps |
(D) Re- inforcement learning | (iv) System learns by example |
Choices
| Choice (4) | Response | |
|---|---|---|
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a. |
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b. |
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c. |
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d. |
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