This document introduces non-deterministic finite automata (NFA). It defines an NFA as a 5-tuple (Q, Σ, δ, q0, F) where Q is a finite set of states, Σ is a finite input alphabet, q0 is the initial state, F is a set of accepting states, and δ is a transition function that returns a set of states rather than a single state. This allows an NFA to be in multiple states simultaneously and accept inputs if any path reaches an accepting state. The document provides examples of strings being accepted and rejected by NFAs, and explains how epsilon transitions allow the read head to remain in the same position. It concludes by distinguishing NFAs
The string matching problem is a classic of algorithms. In this class, we only look at the Rabin-Karpp algorithm as a classic example of the string matching algorithms
With vocabulary
1. The Statements, Open Sentences, and Trurth Values
2. Negation
3. Compound Statement
4. Equivalence, Tautology, Contradiction, and Contingency
5. Converse, Invers, and Contraposition
6. Making Conclusion
In this slide fourier series of Engineering Mathematics has been described. one Example is also added for you. Hope this will help you understand fourier series.
Abstract—Since the demand for information retrieval increases quickly, indexing structures became an important issue to support fast information retrieval. According to the work in this paper, a new data structure called Dynamic Ordered Multi-field Index (DOMI) for information retrieval has been introduced. It is based on radix trees organized in segments in addition to a hash table to point to the roots of each segment, where each segment is dedicated to store the values of a single field. The hash table is used to access the needed segments directly without traversing the upper segments. So, DOMI improves look-up performance for queries addressing to a single field. In the case of multiple queries addressing, each segment of the radix tree is traversed sequentially without visiting the unrelated branches. The use of segmentation for the proposed DOMI provides flexibility for minimizing communication overhead in the distributed system. Every field in the radix tree is represented by one segment, where each segment can be stored as one block.
In addition to, the proposed DOMI consumes less space comparing to indexes which are built using B or B+ trees. Hence, it is more suitable for intensive-data such as Big Data.
The string matching problem is a classic of algorithms. In this class, we only look at the Rabin-Karpp algorithm as a classic example of the string matching algorithms
With vocabulary
1. The Statements, Open Sentences, and Trurth Values
2. Negation
3. Compound Statement
4. Equivalence, Tautology, Contradiction, and Contingency
5. Converse, Invers, and Contraposition
6. Making Conclusion
In this slide fourier series of Engineering Mathematics has been described. one Example is also added for you. Hope this will help you understand fourier series.
Abstract—Since the demand for information retrieval increases quickly, indexing structures became an important issue to support fast information retrieval. According to the work in this paper, a new data structure called Dynamic Ordered Multi-field Index (DOMI) for information retrieval has been introduced. It is based on radix trees organized in segments in addition to a hash table to point to the roots of each segment, where each segment is dedicated to store the values of a single field. The hash table is used to access the needed segments directly without traversing the upper segments. So, DOMI improves look-up performance for queries addressing to a single field. In the case of multiple queries addressing, each segment of the radix tree is traversed sequentially without visiting the unrelated branches. The use of segmentation for the proposed DOMI provides flexibility for minimizing communication overhead in the distributed system. Every field in the radix tree is represented by one segment, where each segment can be stored as one block.
In addition to, the proposed DOMI consumes less space comparing to indexes which are built using B or B+ trees. Hence, it is more suitable for intensive-data such as Big Data.
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Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
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Palestine last event orientationfvgnh .pptxRaedMohamed3
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A Strategic Approach: GenAI in EducationPeter Windle
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This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
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This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Unit 8 - Information and Communication Technology (Paper I).pdf
Cs419 lec6 lexical analysis using nfa
1. WELCOME TO A
JOURNEY TO
CS419
Dr. Hussien Sharaf
Computer Science Department
dr.sharaf@from-masr.com
2. Dr. Hussien M. Sharaf
NON DETERMINISTIC FINITE AUTOMATA NFA
There is a fixed number of states but we can be in multiple states at one
time.
NFA = “a 5-tuple “ (Q, Σ, , q0, F)
Q A finite set of states
Σ
A finite input alphabet
q0 The initial/starting state, q0 is in Q
F
A set of final/accepting states, which is a subset of Q
δ
A transition function, which is a total function from Q x Σ to 2Q ,
this function:
Takes a state and input symbol as arguments.
Returns a set of states instead a single state as in DFA.
δ: (Q x Σ) –> 2Q -2Q is the power set of Q, the set of all subsets of Q
δ(q,s) is a function from Q x S to 2Q (but not to Q)
2
3. NFA
A finite automaton is deterministic if
It has no edges/transitions labeled with
epsilon/lamda.
For each state and for each symbol in the
alphabet, there is exactly one edge labeled
with that symbol.
4. Dr. Hussien M. Sharaf
NFA
NFA travels all possible paths, and so it remains in many states at once.
As long as at least one of the paths results in an accepting state, the NFA
accepts the input.
Alphabet = {a }
a
q0
q1
a
q2
a
q3
4
5. Dr. Hussien M. Sharaf
NFA
Alphabet =
{a }
Two choices
a
q0
q1
a
q2
a
q3
5
6. Dr. Hussien M. Sharaf
NFA
Alphabet =
{a }
Two choices
a
q0
q1
a
q2
No transition
a
q3
No transition
6
7. Dr. Hussien M. Sharaf
NFA
An NFA accepts a string:
if there is a computation of the NFA
that accepts the string
i.e., all the input string is processed and
the automaton is in an accepting state
7
8. Dr. Hussien M. Sharaf
Acceptance Example 1
NFA
a
a
a
q0
q1
a
q2
a
q3
8
9. Dr. Hussien M. Sharaf
First Choice
NFA
a
a
a
q0
q1
a
q2
a
q3
9
10. Dr. Hussien M. Sharaf
First Choice
NFA
a
a
All input is consumed
a
q0
q1
a
q3
a
q2
“accept”
11. Dr. Hussien M. Sharaf
Second Choice
NFA
a
a
a
q0
q1
a
q3
a
q2
12. Dr. Hussien M. Sharaf
Second Choice
NFA
a
a
Input cannot be consumed
a
q1
a
q2
Automaton Halts
q0
a
q 3 “reject”
13. Dr. Hussien M. Sharaf
NFA
aa is accepted by the NFA:
“accept”
a
q0
q1
q2
a
q0
a
q3
because this
computation
accepts aa
a
q1
a
q2
a
q3
“reject”
this computation
is ignored
13
14. Dr. Hussien M. Sharaf
NFA
An NFA rejects a string:
if there is no computation of the NFA
that accepts the string.
For each computation:
• All the input is consumed and the
automaton is in a non final state
OR
• The input cannot be consumed
14
15. Dr. Hussien M. Sharaf
NFA
a
is rejected by the NFA:
“reject”
a
q0
q1
a
q2
a
q0
a
q 3 “reject”
q1
a
q2
a
q3
All possible computations lead to rejection
15
16. Dr. Hussien M. Sharaf
NFA
aaa is rejected by the NFA:
“reject”
a
q0
q1
a
q2
a
q0
a
q3
q1
a
q2
a
q3
“reject”
All possible computations lead to rejection
16
17. Dr. Hussien M. Sharaf
LAMBDA TRANSITIONS
q0
a
q1
q2
a
q3
17
18. Dr. Hussien M. Sharaf
LAMBDA TRANSITIONS
Acceptance Example 2
a
a
q0
a
q1
q2
a
q3
18
19. Dr. Hussien M. Sharaf
LAMBDA TRANSITIONS
a
a
q0
a
q1
q2
a
q3
19
20. Dr. Hussien M. Sharaf
LAMBDA TRANSITIONS
input tape head does not move
a
a
q0
a
q1
q2
a
q3
21. Dr. Hussien M. Sharaf
LAMBDA TRANSITIONS
all input is consumed
a
a
“accept”
q0
a
q1
q2
a
q3
String aa is accepted
21
22. Dr. Hussien M. Sharaf
LAMBDA TRANSITIONS
Rejection Example 3
a
a
a
q0
a
q1
q2
a
q3
22
23. Dr. Hussien M. Sharaf
LAMBDA TRANSITIONS
a
a
a
q0
a
q1
q2
a
q3
23
24. Dr. Hussien M. Sharaf
LAMBDA TRANSITIONS
(read head doesn’t move)
a
a
a
q0
a
q1
q2
a
q3
24
25. Dr. Hussien M. Sharaf
LAMBDA TRANSITIONS
Input cannot be consumed
a
a
a
Automaton halts
“reject”
q0
a
q1
q2
a
q3
String aaa is rejected
25
26. Dr. Hussien M. Sharaf
LAMBDA TRANSITIONS
Language accepted:
q0
a
q1
L {aa }
q2
a
q3
26
40. Dr. Hussien M. Sharaf
Language accepted
L ( M ) = {λ , 10 , 1010 , 101010 , ... }
= {10 } *
0
q0
1
q1
0, 1
q2
(redundant
state)
40
41. DETERMINISTIC AND
NONDETERMINISTIC AUTOMATA
Deterministic Finite Automata (DFA)
One
transition per input per state
No -moves
Nondeterministic Finite Automata (NFA)
Can
have multiple transitions for one input in a
given state
Can have -moves
41