The document provides information about a course on the theory of automata. It includes details such as the course title, prerequisites, duration, lectures, laboratories, and topics to be covered. The topics include finite automata, deterministic finite automata, non-deterministic finite automata, regular expressions, properties of regular languages, context-free grammars, pushdown automata, and Turing machines. It also lists reference books and textbooks, and the marking scheme for the course.
A short presentation to share knowledge about topic Decidability of Theory of Automata Course.
To make people to be aware how to know which formal languages are decidable and why...!
Decision tree is a type of supervised learning algorithm (having a pre-defined target variable) that is mostly used in classification problems. It is a tree in which each branch node represents a choice between a number of alternatives, and each leaf node represents a decision.
A short presentation to share knowledge about topic Decidability of Theory of Automata Course.
To make people to be aware how to know which formal languages are decidable and why...!
Decision tree is a type of supervised learning algorithm (having a pre-defined target variable) that is mostly used in classification problems. It is a tree in which each branch node represents a choice between a number of alternatives, and each leaf node represents a decision.
K-Nearest neighbor is one of the most commonly used classifier based in lazy learning. It is one of the most commonly used methods in recommendation systems and document similarity measures. It mainly uses Euclidean distance to find the similarity measures between two data points.
FellowBuddy.com is an innovative platform that brings students together to share notes, exam papers, study guides, project reports and presentation for upcoming exams.
We connect Students who have an understanding of course material with Students who need help.
Benefits:-
# Students can catch up on notes they missed because of an absence.
# Underachievers can find peer developed notes that break down lecture and study material in a way that they can understand
# Students can earn better grades, save time and study effectively
Our Vision & Mission – Simplifying Students Life
Our Belief – “The great breakthrough in your life comes when you realize it, that you can learn anything you need to learn; to accomplish any goal that you have set for yourself. This means there are no limits on what you can be, have or do.”
Like Us - https://www.facebook.com/FellowBuddycom
Automata theory - describes to derives string from Context free grammar - derivation and parse tree
normal forms - Chomsky normal form and Griebah normal form
K-Nearest neighbor is one of the most commonly used classifier based in lazy learning. It is one of the most commonly used methods in recommendation systems and document similarity measures. It mainly uses Euclidean distance to find the similarity measures between two data points.
FellowBuddy.com is an innovative platform that brings students together to share notes, exam papers, study guides, project reports and presentation for upcoming exams.
We connect Students who have an understanding of course material with Students who need help.
Benefits:-
# Students can catch up on notes they missed because of an absence.
# Underachievers can find peer developed notes that break down lecture and study material in a way that they can understand
# Students can earn better grades, save time and study effectively
Our Vision & Mission – Simplifying Students Life
Our Belief – “The great breakthrough in your life comes when you realize it, that you can learn anything you need to learn; to accomplish any goal that you have set for yourself. This means there are no limits on what you can be, have or do.”
Like Us - https://www.facebook.com/FellowBuddycom
Automata theory - describes to derives string from Context free grammar - derivation and parse tree
normal forms - Chomsky normal form and Griebah normal form
Digital marketing strategy and planning | About BusinessGaditek
Introduction
Respondent profiles
About Business
Adoption of digital transformation programs
Investing In Digital Marketing
Top Online Marketing Channels
What should the planning horizon for digital planning be?
Integration Of Digital And Traditional Marketing Activities
EXECUTIVE SUMMARY
Intro to social network analysis | What is Network Analysis? | History of (So...Gaditek
Social network analysis is a method by which one can analyze the connections across individuals or groups or institutions. That is, it allows us to examine how political actors or institutions are interrelated.
Marketing ethics and social responsibility | Criticisms of MarketingGaditek
Identify the major social criticisms of marketing.
Define consumerism and environmentalism and explain how they affect marketing strategies.
Describe the principles of socially responsible marketing.
Explain the role of ethics in marketing.
understanding and capturing customer value | What Is a Price?Gaditek
Discuss the importance of understanding customer value perceptions and company costs when setting prices.
Identify and define the other important internal and external factors affecting a firm’s pricing decisions.
Describe the major strategies for pricing imitative and new products.
Explain how companies find a set of prices that maximizes the profits from the total product mix.
Discuss how companies adjust their prices to take into account different types of customers and situations.
Discuss key issues related to initiating and responding to price changes.
The marketing environment | Suppliers | Marketing intermediariesGaditek
Describe the environmental forces that affect the company’s ability to serve its customers.
Explain how changes in the demographic and economic environments affect marketing decisions.
Identify the major trends in the firm’s natural and technological environments.
Explain the key changes in the political and cultural environments.
Discuss how companies can react to the marketing environment.
strategic planning | Customer Relationships | Partnering to Build Gaditek
Explain companywide strategic planning and its four steps.
Discuss how to design business portfolios and growth strategies.
Explain marketing’s role in strategic planning and how marketing works with its partners to create and deliver customer value.
Describe the elements of a customer-driven marketing strategy and mix, and the forces that influence it.
List the marketing management functions, including the elements of a marketing plan.
Define marketing and the marketing process.
Explain the importance of understanding customers and identify the five core marketplace concepts.
Identify the elements of a customer-driven marketing strategy and discuss the marketing management orientations.
Discuss customer relationship management and creating value for and capturing value from customers.
Describe the major trends and forces changing the marketing landscape.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
4. Reference Books:
K.L.P. Mishra, N.
Chandrasekaran,
Theory of Computer Science
(Automata, Languages &
Computation), Second Edition,
Prentice Hall of India, 1999
6. Reference Books:
John.E. Hopcroft, R. Motwani, and J.D.
Ullman, Introduction to Automata
Theory, Language and Computation,
Second Edition, Pearson Education
Asia, 2001.
9. AUTOMATA
Automata is Greek letters .Automata is a word
formulated from automation, which means machine
designing or replacing human beings with machines.
Every machine design requires some hardware part
and some software part.
A machine could be a finite state machine ,a Turing
Machine, a pushdown automata, or any other
restricted version of a Turing machine.
10. Input File
Sequence of symbols
Internal State
of Control Unit
Next-State Transition Function
May have Temporary Storage
Input File
Storage
Control Unit
Output
Automata
12. Sets
Sets are collections in which order of elements and duplication of
elements do not matter.
{1,a,1,1} = {a,a,a,1} = {a,1}
Size
Size of set mean number of elements in set e.g. |{a,b,c}| = 3
Special Sets
Empty Set
Universal Set U
13. Set Relations
Subset {a,c} {a,b,c}
Proper Subset {a,c} {a,b,c}
is-element-of b {a,b,c}
Set Operations
Union X Y
Intersection X Y
Difference X – Y
Complement X (always with respect to Universe)
Disjoint S1 S2 =
• Powerset 2x
• Is it possible for |S| = |2S|?
A x B = {(a,b): for all a A and b B}
14. DeMorgan’s Laws
S1 S2 = S1 S2
S1 S2 = S1 S2
Functions : S1 S2
S1 = Domain
S2 = Range
S1 may be same as S2
Equivalence Relations
Reflexive
Symmetric
Transitive
a, b S, we write a b if a is equivalent to b
15. What is a graph?
It's an abstract notion, used to represent the idea of some
kind of connection between pairs of objects.
A graph consists of:
A collection of "vertices", draw as small circles.
A collection of "edges", each connecting some two vertices.
Mathematical Definition
G = (V, E)
V = {v1,v2,…,vn} = Vertices
E = {e1, e2, …, em} = Edges
16. Graph Terminology
Walk = Sequence of edges
Path = Walk with no repeated edges
Simple Path = No vertices repeated
Cycle = Path from vi back to vi
Simple Cycle = Cycle with no vertices repeated
17. Character or Alphabet: An alphabet S is a set of symbols (characters, letters).
or
A finite set of symbols/ An abstract set of distinct symbols over which a
language is defined
String :A string (or word) over S is a sequence of symbols. The empty string is
the string containing no symbols at all, and is denoted by ε.
Length/Size of String: The length of a string is the number of symbols that it
contains (repetitions allowed). Absolute values are used to denote length.
The length of a string w is denoted |w|.
For example |00100| = 5
|aab| = 3
| epsilon | = 0
18. Concatenation : The concatenation of two strings is the string
resulting from putting them together from left to right.
If u=one and v=two then u · v=onetwo and
v · u=twoone.
Dot is usually omitted; just write uv for u · v.
Laws:
u · (v · w) = (u · v) · w
u · ε = u
ε · u = u
|u · v| = |u| + |v|
19. Regular Expression/Relational Expression
• Let Σ be an alphabet. The regular expressions(regex) are
defined inductively as follows:
– ø is a regular expression denoting {},
– ε is a regular expression denoting {},
– for each a Є Σ¸ a is a regular expression denoting
{a},
– Assume r and s are regular expressions denoting
sets R and S, then
. rs denotes RS,
. r + s denoted R υ S,
. r* denotes R*
21. Proof of Kleene Star
Let L0 and Li =L.L i-1 where i>=1 then Kleene closure of
L
is L*.L* is the set such that L* =Ui=0 Li i=0
L0={ε}
Solution
Suppose L={01,10}
L* = L0 U L1 U L2 U ………Ln
Its given that L0={ε}
Take i=1
L1 =L L 1-1
22. L1 =L L0
L1={01,10}.{ε}
L1={01 ε,10 ε}
L1={01,10}
Now Take i=2
L2 =L.L 2-1
L2 =L.L1
L2={01,10}. {01,10}
L2={0101,0110,1001,1010}
Now L*=L0 U L1 U L2 ….U Ln
L*={ε} U {01,10} U {0101,0110,1001,1010}…….
In a Kleene Star form it may be written as L*={01,10}*
23. Regular Language/Rational Language, Recognizable
Language.
A regular, rational, or recognizable language is one
that fulfils
one of the following equivalent criteria:
L is defined by a regular expression.
There are a finite number of L-cones.
L is recognized by a finite state automaton or FSA.
24. Language Expression Meaning Transition
Graph/Automata
L={0,1} r.e=(0+1)
r.e=(0/1)
r.e=(0 1)
choosing
from r1 or r2
L={0,1} r.e=(0.1)
r.e=(01)
r.e=(o∩1)
concatenati
on of r1 and
r2
L={0} r*=(0) zero or
more times
(Kleene
closure)
L={0} r+ =(0) one or more
times
0
1
0 1
0
0
0 0
27. What is the difference between the
two?
Is there a single DFA for a
corresponding NFA?
Why do we want to do this anyway?
28. Deterministic Finite Automata
For every state and every alphabet symbol there is exactly one
move that the machine can make
Mathematical Definition
A Deterministic Finite Automata is a 5-tuple (Q, Σ, δ, qo, F)
where
Q→Total numbers of State(s)
Σ→Input(s)/Alphabets(s)
δ→Transition Function QXΣ
q0→Initial State(s)
F→Final State(s)
29. Finite Automata State Graphs
An Input
A state
The start state
An accepting state
A transition a
a,b,…0,1,2…
30. Example r.e =a.b
Q→Total numbers of State(s) = {q0,q1,q2}
Σ→Input(s)/Alphabets(s)={a,b}
q0→Initial State(s)={q0}
F→Final State(s)={q2}
δ→Transition Function QXΣ
QXΣ Input a Input b
q0 q1 є
q1 є q2
q2 є є
q0
q1 q2
a b
q2
Acceptance State
/Final State
Initial
State
31. Nondeterministic Finite Automata
At each state, for each symbol, the machine can move into
0 or more states.
Mathematical Definition
A Non-Deterministic Finite Automata is a 5-tuple (Q,Σ,δ, qo,
F)
where
Q→Total numbers of State(s)
Σ→Input(s)/Alphabets(s)
δ→Transition Function 2 pow Q
q0→Initial State(s)
F→Final State(s)
33. Non-Deterministic Finite Automata
Example L={a}
a
a
a
1q 2q
3q
0q No transition:
the automaton hangs
Acceptance state/Final State
Two choices
QX Σ Input a
q0 q1 U q3
q1 q2
q2 є
q3 є
34. Nondeterministic Finite Automata
Non-determinism
When machine is in a given state and reads a
symbol, the machine will have a choice of
where to move to next.
There may be states where, after reading a
given symbol, the machine has nowhere to go.
Applying the transition function will give, not 1
state, but 0 or more states.
39. REGULAR EXPRESSION
Theorem If L is accepted by a DFA, then L is
denoted by a regular expression.
The language of FA (regular language) is the set of
strings that label paths that go from the start state
to some accepting state.
The languages accepted by DFA, NFA,
e-NFA, Regular Expressions are called
regular languages
40. REGULAR EXPRESSION
The regular expressions over are the
smallest set of expressions including
where
where A,B are rexp over
" " "
where A is a rexp over
‘c’
A+B
AB
A*
e
c
41. Regular Expression Notation
a: an ordinary letter
ε: the empty string
r1 | r2: choosing from r1 or r2
r1r2 : concatenation of r1 and r2
r*: zero or more times (Kleene closure)
r+: one or more times
42. NFA to DFA Conversion
What is the difference between the two?
Is there a single DFA for a corresponding
NFA?
Why do we want to do this anyway?
43. Nondeterministic Finite Automata
Non-determinism
When machine is in a given state and reads a
symbol, the machine will have a choice of
where to move to next.
There may be states where, after reading a
given symbol, the machine has nowhere to go.
Applying the transition function will give, not 1
state, but 0 or more states.
44. Nondeterministic Finite Automata
At each state, for each symbol, the machine can
move into 0 or more states.
A Non-Deterministic Finite Automata is a
5-tuple (Q, S, d, qo, F) where
Input alphabet, i.e.
Transition function 2 pow Q
Initial state i.e.
Final states i.e.
:Q
:
:
:0q
:F
Set of states, i.e. { q0, q1, q2, q3, q4}
{1,0}
{q0}
{q4}
45. Nondeterministic Finite Automata
Two non-deterministic elements:
Lambda transitions or epsilon transitions
2 out arcs with same symbol
46. For every state and every alphabet symbol
there is exactly one move that the machine can
make
A Deterministic Finite Automata is a
5-tuple (Q, S, d, qo, F) where
Deterministic Finite Automata
:Q
:
:
:0q
:F
Input alphabet
Transition function Q x I
Initial state
Final states
Set of states
51. For re=r1*
e
e
e r1 eS A B Fstart
r1 r1
S BAF Astart
r1
NFA (e-move)
DFA
States/
input
r1
S BFBA=BAF
A BAF
B
F
BAF BAF
Transaction table:
r1*BAFS
r1
start
r1
NFA ->DFA (EXAMPLE-1)
52. NFA ->DFA (EXAMPLE-2)
For re=r1.r2
NFA (e-move)
For r1 For r2
For r1.r2
A B
r1
start C D
r2
start
A B C D
er1 r2
start
53. NFA ->DFA (EXAMPLE-2 cont….)
State
s/
input
r1 r2
A BC
B
C D
D
BC D
DFA
Transaction table:
A BC Dr2r1
start
CA BC D
r2r1 r2
start
r1.r2
54. NFA ->DFA (EXAMPLE-3)
For re=r1+r2
For r1 For r2
C D
r2
startA B
r1
start
e e
A B
r1
C D
r2
start S F
ee
For r1+r2
55. NFA ->DFA (EXAMPLE-3 cont….)
FD
State
s/inpu
t
r1 r2
S BF DF
A BF
B
C DF
D
F
BF
DF
Transaction table:
DFA
BDFstart
r1/r2
S
r1+r2
r1r1
BF A
DF Cr2
start S
r2
BF
DF
start S
r1
r2
56. NFA ->DFA (EXAMPLE-1)
q0 q1 q2start
a b
a,b
q0 q0q1 q0q2start
a b
b
a
a
b
States
/
input
a b
q0 q1q0 q0
q1 q2
q2
q1q0 q1q0 q0q
2
q0q2 q1q2 q0
Transaction table:
NFA
Equivalent DFA
57. NFA ->DFA (EXAMPLE-2)
B A
C
start
0
0
1
10
B ABCstart
0
0
1
AC
1
A
B ABCstart
0
0
1
AC
1
NFA
Equivalent DFA
States
/
input
0 1
B BAC
A AC
C
ABC ABC AC
AC AC
Transaction table: