In this you learn about the topic multiplexer and De-multiplexer in a very easy method.
You learn types of Multiplexer, Types of De-multiplexer,
Relation between Multiplexer (MUX) and De-Multiplexer (Dmux).
Difference between MUX and DMUX
In this you learn about the topic multiplexer and De-multiplexer in a very easy method.
You learn types of Multiplexer, Types of De-multiplexer,
Relation between Multiplexer (MUX) and De-Multiplexer (Dmux).
Difference between MUX and DMUX
Digital computer deals with numbers; it is essential to know what kind of numbers can be handled most easily when using these machines. We accustomed to work primarily with the decimal number system for numerical calculations, but there is some number of systems that are far better suited to the capabilities of digital computers. And there is a number system used to represents numerical data when using the computer.
Dlc{binary to gray code conversion} pptTanish Gupta
BINARY TO GRAY CODE CONVERSION
1- WHAT IS A BINARY CODE ?
-> A binary code represents text or computer processor instructions using the binary number system's two binary digits, 0 and 1. The binary code assigns a bit string to each symbol or instruction.
2- WHAT IS A GRAY CODE ?
-> The reflected binary code(RBC), also known as Gray code after Frank Gray, is a binary numeral system where two successive values differ in only one bit. This code was originally designed to prevent spurious output from electromechanical switches.
THE GRAY CODE{Image in Ppt}
3- Binary-to-Gray code conversion
->
The MSB in the Gray code is the same as corresponding MSB in the binary number.
Going from left to right, add each adjacent pair of binary code bits to get the next Gray code bit. Discard carries.
ex: convert 101102 to Gray code
1 + 0 + 1 + 1 + 0 binary
1 1 1 0 1 Gray
CONVERTING CIRCUIT{Image in Ppt}
LOGIC DIAGRAM OF 4 BIT BINARY TO GRAY CODE CONVERTER{Image in Ppt}
TRUTH TABLE{Image in Ppt}
All images related to topics are in ppt.
THANK YOU
Unit-1 Digital Design and Binary Numbers:Asif Iqbal
these slides contains general discerption about digital signals, binary numbers, digital numbers, and basic logic gates. it covers the first unit of AKTU syllabus.
Inductive programming incorporates all approaches which are concerned with learning programs or algorithms from incomplete (formal) specifications. Possible inputs in an IP system are a set of training inputs and corresponding outputs or an output evaluation function, describing the desired behavior of the intended program, traces or action sequences which describe the process of calculating specific outputs, constraints for the program to be induced concerning its time efficiency or its complexity, various kinds of background knowledge such as standard data types, predefined functions to be used, program schemes or templates describing the data flow of the intended program, heuristics for guiding the search for a solution or other biases.
Output of an IP system is a program in some arbitrary programming language containing conditionals and loop or recursive control structures, or any other kind of Turing-complete representation language.
In many applications the output program must be correct with respect to the examples and partial specification, and this leads to the consideration of inductive programming as a special area inside automatic programming or program synthesis, usually opposed to 'deductive' program synthesis, where the specification is usually complete.
In other cases, inductive programming is seen as a more general area where any declarative programming or representation language can be used and we may even have some degree of error in the examples, as in general machine learning, the more specific area of structure mining or the area of symbolic artificial intelligence. A distinctive feature is the number of examples or partial specification needed. Typically, inductive programming techniques can learn from just a few examples.
The diversity of inductive programming usually comes from the applications and the languages that are used: apart from logic programming and functional programming, other programming paradigms and representation languages have been used or suggested in inductive programming, such as functional logic programming, constraint
programming, probabilistic programming
Research on the inductive synthesis of recursive functional programs started in the early 1970s and was brought onto firm theoretical foundations with the seminal THESIS system of Summers[6] and work of Biermann.[7] These approaches were split into two phases: first, input-output examples are transformed into non-recursive programs (traces) using a small set of basic operators; second, regularities in the traces are searched for and used to fold them into a recursive program. The main results until the mid 1980s are surveyed by Smith.[8] Due to
Digital computer deals with numbers; it is essential to know what kind of numbers can be handled most easily when using these machines. We accustomed to work primarily with the decimal number system for numerical calculations, but there is some number of systems that are far better suited to the capabilities of digital computers. And there is a number system used to represents numerical data when using the computer.
Dlc{binary to gray code conversion} pptTanish Gupta
BINARY TO GRAY CODE CONVERSION
1- WHAT IS A BINARY CODE ?
-> A binary code represents text or computer processor instructions using the binary number system's two binary digits, 0 and 1. The binary code assigns a bit string to each symbol or instruction.
2- WHAT IS A GRAY CODE ?
-> The reflected binary code(RBC), also known as Gray code after Frank Gray, is a binary numeral system where two successive values differ in only one bit. This code was originally designed to prevent spurious output from electromechanical switches.
THE GRAY CODE{Image in Ppt}
3- Binary-to-Gray code conversion
->
The MSB in the Gray code is the same as corresponding MSB in the binary number.
Going from left to right, add each adjacent pair of binary code bits to get the next Gray code bit. Discard carries.
ex: convert 101102 to Gray code
1 + 0 + 1 + 1 + 0 binary
1 1 1 0 1 Gray
CONVERTING CIRCUIT{Image in Ppt}
LOGIC DIAGRAM OF 4 BIT BINARY TO GRAY CODE CONVERTER{Image in Ppt}
TRUTH TABLE{Image in Ppt}
All images related to topics are in ppt.
THANK YOU
Unit-1 Digital Design and Binary Numbers:Asif Iqbal
these slides contains general discerption about digital signals, binary numbers, digital numbers, and basic logic gates. it covers the first unit of AKTU syllabus.
Inductive programming incorporates all approaches which are concerned with learning programs or algorithms from incomplete (formal) specifications. Possible inputs in an IP system are a set of training inputs and corresponding outputs or an output evaluation function, describing the desired behavior of the intended program, traces or action sequences which describe the process of calculating specific outputs, constraints for the program to be induced concerning its time efficiency or its complexity, various kinds of background knowledge such as standard data types, predefined functions to be used, program schemes or templates describing the data flow of the intended program, heuristics for guiding the search for a solution or other biases.
Output of an IP system is a program in some arbitrary programming language containing conditionals and loop or recursive control structures, or any other kind of Turing-complete representation language.
In many applications the output program must be correct with respect to the examples and partial specification, and this leads to the consideration of inductive programming as a special area inside automatic programming or program synthesis, usually opposed to 'deductive' program synthesis, where the specification is usually complete.
In other cases, inductive programming is seen as a more general area where any declarative programming or representation language can be used and we may even have some degree of error in the examples, as in general machine learning, the more specific area of structure mining or the area of symbolic artificial intelligence. A distinctive feature is the number of examples or partial specification needed. Typically, inductive programming techniques can learn from just a few examples.
The diversity of inductive programming usually comes from the applications and the languages that are used: apart from logic programming and functional programming, other programming paradigms and representation languages have been used or suggested in inductive programming, such as functional logic programming, constraint
programming, probabilistic programming
Research on the inductive synthesis of recursive functional programs started in the early 1970s and was brought onto firm theoretical foundations with the seminal THESIS system of Summers[6] and work of Biermann.[7] These approaches were split into two phases: first, input-output examples are transformed into non-recursive programs (traces) using a small set of basic operators; second, regularities in the traces are searched for and used to fold them into a recursive program. The main results until the mid 1980s are surveyed by Smith.[8] Due to
Computers only deal with binary data (0s and 1s), hence all data manipulated by computers must be represented in binary format.
Machine instructions manipulate many different forms of data:
Numbers:
Integers: 33, +128, -2827
Real numbers: 1.33, +9.55609, -6.76E12, +4.33E-03
Alphanumeric characters (letters, numbers, signs, control characters): examples: A, a, c, 1 ,3, ", +, Ctrl, Shift, etc.
So in general we have two major data types that need to be represented in computers; numbers and characters
Introduction
Numbering Systems
Binary & Hexadecimal Numbers
Binary and Hexadecimal Addition
Binary and Hexadecimal subtraction
Base Conversions
Binary addition, Binary subtraction, Negative number representation, Subtraction using 1’s complement and 2’s complement, Binary multiplication and division, Arithmetic in octal, hexadecimal number system, BCD and Excess – 3 arithmetic
UNIT-II ARITHMETIC FOR COMPUTERS
Addition and Subtraction – Multiplication – Division – Floating Point Representation – Floating Point Addition and Subtraction.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
1. Prof. Nitin Ahire 1
Singed number concept
in
8051 Microcontroller
Nitin Ahire
XIE Mahim
2. Prof. Nitin Ahire 2
Singed number concept
• In everyday life, numbers are used that
could be +Ve or –Ve
• In the 8051 the MSB bit is set aside for the
sign
• If MSB(D7) =1 represent negative number
• If MSB(D7) =0 represent positive numbers
• The remaining bit D0 to D6 used for
magnitude.
3. Prof. Nitin Ahire 3
As 8051 is a 8 bit controller here
we consider the 8 bit numbers
D7 D6 D1D2D3D4D5 D0
SIGN MAGNITUDE
4. Prof. Nitin Ahire 4
POSITIVE NUMBERS
• The range of positive numbers can be
represent by the format as shown in figure
• It range from 0 to +127
0 0000 0000
+1 0000 0001
+5 0000 0101
+127 0111 1111
5. Prof. Nitin Ahire 5
NEGATIVE NUMBERS
• For negative number D7=1 however the
magnitude is represented in it’s 2’s
compliment form
• Steps
1 write the magnitude of the number in 8 bit
binary
2 invert each bit
3 add one to it
6. Prof. Nitin Ahire 6
• Show how the 8051 would represent – 5
• Sol:
0000 0101 5 in 8-bit binary
1111 1010 invert bit
1111 1011 add 1 ( which is FB h )
7. Prof. Nitin Ahire 7
• Show how the 8051 would represent -128
• Sol:
1000 0000
0111 1111
1000 0000 ( which become 80h)
9. Prof. Nitin Ahire 9
Overflow problem in signed number
• What is an overflow?
• If the result of an operation on the signed
numbers is too large for the register, an
overflow has occurred
CY AC -OVRS0RS1FO P
10. Prof. Nitin Ahire 10
Example
• Examine the following code and analyze
the result
MOV A,# +96
MOV R1, # +70
ADD A,R1
11. Prof. Nitin Ahire 11
Solution
+ 96 0110 0000 60h
+ 70 0100 0110 46h
-------- ---------------
+166 1010 0110 A6 and OV =1
according to CPU the result -90h which is wrong.
( OV = 1)
+166 is not the valid signed number. ( 0 to +127)
12. Prof. Nitin Ahire 12
When is the OV flag set?
1. There is carry from D6 to D7 but no carry
out of D7 (CY=0).
2. There is a carry from D7 out (CY=1) but
no carry from D6 to D7.
13. Prof. Nitin Ahire 13
Example 1
• MOV A, #-2 (FEh) ( 1111 1110)
• MOV R1,#-5 (FBh) ( 1111 1011)
• ADD A,R1 (F9h=-7, 1111 1001correct),
• So CPU generate OV=0
14. Prof. Nitin Ahire 14
Example 2
MOV A, #-128 ; (80H)
MOV R4,#-2 (FEH)
ADD A,R4 ( A=7EH =+127 INVALID )
So CPU generate OV =1
15. Prof. Nitin Ahire 15
Example 3
• MOV A,#+7; A=0000 0111 (A=07H)
• MOV R1,#+18; R1= 0001 0010 (R1=12H)
• ADD A,R1; A=0001 1001 (A=19H=+25)
According to CPU, this is +25, which is
correct (OV=0)
16. Prof. Nitin Ahire 16
• In any signed number addition OV
indicates whether the result is valid or not
• If OV=1, the result is erroneous
• If OV=0, the result is valid.
17. Prof. Nitin Ahire 17
BCD ADDITION
• Assume that 5 BCD data items are stored
in RAM location starting at 40H, write a
program to find the sum of all numbers.
The result must be in BCD.
18. Prof. Nitin Ahire 18
• Data 40=(71)
• 41=(11)
• 42=(65)
• 43=(59)
• 44=(37)
19. Prof. Nitin Ahire 19
Solution
• MOV R0,#40H
MOV R2,05H
CLR A
MOV R7,A
AGAIN:ADD A,@R0
DA A
JNC NEXT
INC R7
NEXT: INC RO
DJNZ R2,AGAIN
END
