Steps in page replacement:
No frame is free → D
Find a frame to replace → A
Free that frame → E
Update the page table → B
Use the freed frame for the new page → C
Typical DBMS query processing steps:
Scanning, parsing and validating → C
Query optimizer → A
Query code generator → D
Runtime database processor → B
Correct order:
C → A → D → B
Insert words sequentially into BST.
banana → root
peach → right of banana
apple → left of banana
pear → right of peach
coconut → left of peach
mango → right of coconut
papaya → right of mango
Longest path:
banana → peach → coconut → mango → papaya
Number of edges = 4
| List-I | List-II |
| A. Verification | I. White box Testing |
| B. Validation | II. Black box Testing |
| C. Internal logic exercise | III. Quality Control |
| D. Software requirement exercise | IV. Quality Assurance |
Verification → Quality Assurance → IV
Validation → Quality Control → III
Internal logic exercise → White box testing → I
Software requirement exercise → Black box testing → II
Matching:
A → IV
B → III
C → I
D → II
Memory required:
$2048 \times 8$
Each chip:
$128 \times 4$
First match word size:
$8 / 4 = 2$ chips per word.
Now match number of words:
$2048 / 128 = 16$
Total chips:
$16 \times 2 = 32$
A: False when $r=1, p=0$ → Not tautology
B: False when $p=1, r=0$ → Not tautology
C:
$\sim p \rightarrow (p \rightarrow r)$
Always true → Tautology
D:
$(p \land r) \rightarrow (p \rightarrow r)$
Always true → Tautology
E:
$\sim(p \rightarrow r) \rightarrow p$
Always true → Tautology
Thus tautologies:
C, D, E
Sequential circuits depend on previous state (memory).
• Flip-flop → sequential circuit
• Counter → sequential circuit
Multiplexer, Decoder and Adder are combinational circuits.
| List-I | List-II |
| A. Union | I. Virtual Reality |
| B. Function | II. Shadow mask |
| C. Interactive Environment | III. Subroutine |
| D. Output device | IV. User defined data type |
Union → User defined data type → IV
Function → Subroutine → III
Interactive Environment → Virtual Reality → I
Output device → Shadow mask → II
Matching:
A → IV
B → III
C → I
D → II
A Perceptron is a single-layer feed-forward neural network used for linear classification.
| List-I | List-II |
| A. Back Tracking | I. Automata |
| B. Infinite languages with matching numbers | II. Undecidable Problem |
| C. Canonical LR Parser | III. Predictive Parser |
| D. Post Correspondence Problem | IV. Large number of states |
Backtracking → Predictive parsing may require backtracking → III
Infinite languages with matching numbers → handled using Automata → I
Canonical LR parser → requires large number of states → IV
Post Correspondence Problem → Undecidable problem → II
Matching:
A → III
B → I
C → IV
D → II
Online Test Series, Information About Examination,
Syllabus, Notification
and More.
Online Test Series, Information About Examination,
Syllabus, Notification
and More.