This document provides an overview of data representation and computer structure. It discusses how computers use binary numbers to represent data, including integers, real numbers, text, and graphics. Different number systems like decimal, binary, hexadecimal are explained. Computer memory types like RAM, ROM, cache are defined along with their functions. The basic concepts of the stored program concept, fetch-execute cycle and CPU components like ALU, control unit and registers are introduced at a high level.
This document discusses how computers represent different types of data using binary numbers. It explains that all data inside a computer is stored as binary digits (bits) that represent ON and OFF switches. Various data types like characters, pictures, sound, programs and integers are represented by grouping bits into bytes. The context determines how a computer interprets each byte. Standards like ASCII, JPEG and WAV define how different data is encoded into binary format and bytes. The document also covers number systems like binary, decimal, hexadecimal and their properties.
The document discusses data representation in computer systems. It begins by explaining that computers use the binary system for logic and arithmetic because it is easy to implement in electronics and switches. It then discusses how integers, floating point numbers, and Boolean logic are represented. The document provides details on bits, bytes, words, and how positional numbering systems like binary represent values. It covers converting between decimal and binary, including fractional values. Finally, it discusses signed integer representation using methods like signed magnitude, one's complement, and two's complement.
The document discusses data representation in computers. It explains that:
1) Data is stored in binary form using bits, with the basic unit being a byte made up of 8 bits. Each byte can represent one character using ASCII codes.
2) When a user types a letter on a keyboard, it is converted to its ASCII binary code and stored in memory. This allows the letter to be processed and displayed on an output device.
3) Common units for measuring data size are kilobytes, megabytes, and gigabytes which are powers of 1024, 1024^2, and 1024^3 bytes respectively. Clock speed of a processor, measured in Hertz, determines how fast it can process data.
The document discusses how computers represent data using binary numbers (1s and 0s). It explains that binary is used because it provides an easy way to represent two states (on/off) in storage devices. It then discusses how different numbers of bits (binary digits) can be used to represent different numbers in binary, and provides examples of converting between binary and decimal numbers. Finally, it briefly introduces the concept of data compression for reducing the size of files.
This document provides an overview of data representation in computer systems. It discusses how computers use binary numeric codes to represent different types of data like text, numbers, graphics and audio. These codes allow computers to interpret raw sequences of 0s and 1s as meaningful information. The document then explains binary number systems in more detail, how decimal numbers can be converted to and from binary, and how bytes and bits are used to store data in computer memory and represent characters. Specific examples are given of how binary representations are used in applications like robotics to control devices.
All computer data is represented as binary numbers consisting of 1s and 0s at the most basic level. A single unit of binary data is called a bit, while 8 bits together form a byte which is used to represent larger pieces of data like letters. The document also explains the binary, octal, decimal, and hexadecimal number systems for representing values in computers.
This document discusses how computers represent and process data. It covers:
1) Computers use binary digits (bits) to represent data, with each bit being either 1 or 0 to represent an on or off state.
2) Eight bits are grouped together to form a byte, which can represent individual characters.
3) There are different coding systems like ASCII to represent characters and numbers with binary codes.
4) Data entered from keyboards is converted to binary codes and stored in memory for processing before being converted back to characters on output devices.
The document provides an overview of computer systems and their components. It can be summarized as follows:
1) A computer system consists of four major hardware components: input devices, output devices, a processor, and storage devices. It requires both hardware and software to function, with software providing instructions to tell the hardware what to do.
2) Common input devices include keyboards, mice, and scanners. Output devices display processed data through monitors, printers, and speakers. Storage holds data and programs, while the processor controls activities and executes instructions.
3) The information processing cycle involves a user inputting data, the processor accessing stored programs and data to process the input, and output devices presenting the processed output back
This document discusses how computers represent different types of data using binary numbers. It explains that all data inside a computer is stored as binary digits (bits) that represent ON and OFF switches. Various data types like characters, pictures, sound, programs and integers are represented by grouping bits into bytes. The context determines how a computer interprets each byte. Standards like ASCII, JPEG and WAV define how different data is encoded into binary format and bytes. The document also covers number systems like binary, decimal, hexadecimal and their properties.
The document discusses data representation in computer systems. It begins by explaining that computers use the binary system for logic and arithmetic because it is easy to implement in electronics and switches. It then discusses how integers, floating point numbers, and Boolean logic are represented. The document provides details on bits, bytes, words, and how positional numbering systems like binary represent values. It covers converting between decimal and binary, including fractional values. Finally, it discusses signed integer representation using methods like signed magnitude, one's complement, and two's complement.
The document discusses data representation in computers. It explains that:
1) Data is stored in binary form using bits, with the basic unit being a byte made up of 8 bits. Each byte can represent one character using ASCII codes.
2) When a user types a letter on a keyboard, it is converted to its ASCII binary code and stored in memory. This allows the letter to be processed and displayed on an output device.
3) Common units for measuring data size are kilobytes, megabytes, and gigabytes which are powers of 1024, 1024^2, and 1024^3 bytes respectively. Clock speed of a processor, measured in Hertz, determines how fast it can process data.
The document discusses how computers represent data using binary numbers (1s and 0s). It explains that binary is used because it provides an easy way to represent two states (on/off) in storage devices. It then discusses how different numbers of bits (binary digits) can be used to represent different numbers in binary, and provides examples of converting between binary and decimal numbers. Finally, it briefly introduces the concept of data compression for reducing the size of files.
This document provides an overview of data representation in computer systems. It discusses how computers use binary numeric codes to represent different types of data like text, numbers, graphics and audio. These codes allow computers to interpret raw sequences of 0s and 1s as meaningful information. The document then explains binary number systems in more detail, how decimal numbers can be converted to and from binary, and how bytes and bits are used to store data in computer memory and represent characters. Specific examples are given of how binary representations are used in applications like robotics to control devices.
All computer data is represented as binary numbers consisting of 1s and 0s at the most basic level. A single unit of binary data is called a bit, while 8 bits together form a byte which is used to represent larger pieces of data like letters. The document also explains the binary, octal, decimal, and hexadecimal number systems for representing values in computers.
This document discusses how computers represent and process data. It covers:
1) Computers use binary digits (bits) to represent data, with each bit being either 1 or 0 to represent an on or off state.
2) Eight bits are grouped together to form a byte, which can represent individual characters.
3) There are different coding systems like ASCII to represent characters and numbers with binary codes.
4) Data entered from keyboards is converted to binary codes and stored in memory for processing before being converted back to characters on output devices.
The document provides an overview of computer systems and their components. It can be summarized as follows:
1) A computer system consists of four major hardware components: input devices, output devices, a processor, and storage devices. It requires both hardware and software to function, with software providing instructions to tell the hardware what to do.
2) Common input devices include keyboards, mice, and scanners. Output devices display processed data through monitors, printers, and speakers. Storage holds data and programs, while the processor controls activities and executes instructions.
3) The information processing cycle involves a user inputting data, the processor accessing stored programs and data to process the input, and output devices presenting the processed output back
This document discusses data representation in computer systems. It covers topics like binary number systems, conversion between number bases, signed and unsigned integers, and binary arithmetic. Specifically, it defines basic units like bits and bytes, explains how to convert decimal numbers to binary and other bases, discusses signed integer representation using the sign-magnitude method and issues with overflow, and outlines the basic rules for binary addition, subtraction, multiplication and division.
This document discusses different data representation methods in computers. It defines binary, octal, hexadecimal and decimal number systems. It describes how numbers are represented using bits and bytes. The relationships between different number systems are explained. Binary addition and subtraction are demonstrated. Character representation using BCD and ASCII are covered. Different methods for converting between number bases are also summarized.
The document discusses how data is represented in computers using binary numbers. It explains that computers use binary, which represents numbers using only two digits (0 and 1) rather than the decimal system's ten digits. This binary system maps well to the two states of on/off in a computer's electrical circuits. The document provides examples of converting decimal numbers to binary and vice versa. It also discusses how signed integers and floating point numbers are represented using binary.
The document discusses data compression using Elias Delta coding. It begins by introducing compression and its purpose of reducing file sizes. It then explains Elias Delta coding which is a lossless compression technique that encodes characters based on their frequency. The more common characters have fewer bits assigned while less common characters have more bits. It provides an example of how Elias Delta coding works by assigning bit sequences to numbers. The document then applies Elias Delta coding to compress a sample text, showing the original string, character set formation, bit lengths, and compressed output which achieved a smaller size than the original text.
The document discusses digital representation and data storage. It explains that a bit is the smallest unit of data that can have a value of 1 or 0. Bytes make up the basic unit of digital storage, with a byte equal to 8 bits. Larger units of data storage are kilobytes, megabytes, gigabytes and terabytes. Converting a decimal number to binary is done by repeatedly dividing the number by 2 and recording the remainders from top to bottom to get the binary equivalent. Storage capacity is measured in bytes, with files and folders taking up space in bytes that is calculated based on their size in kilobytes or megabytes.
The document discusses various number systems used in digital computers including binary, decimal, octal, and hexadecimal. It provides details on:
1) How numbers are represented positionally in these systems, with different radixes (bases) and the meaning of each digit based on its position.
2) Methods for converting between the different number systems, such as dividing the number by the new base and writing the remainders in reverse order.
3) The steps to convert a decimal number to its binary, octal or hexadecimal equivalent and vice versa by calculating the place values of each digit.
This document discusses how computers use binary digits or "bits" represented as 1s and 0s to store and interpret all digital data, including text, numbers, images, and more. It explains that a bit can have one of two values (1 or 0) and how binary codes assign numeric values to different characters. The document also provides an example of converting a decimal number to its binary equivalent through repeated division and collecting the remainders.
Digital computers represent data by means of an easily identified symbol called a digit. The data may
contain digits, alphabets or special character, which are converted to bits, understandable by the computer.
In Digital Computer, data and instructions are stored in computer memory using binary code (or
machine code) represented by Binary digIT’s 1 and 0 called BIT’s.
The number system uses well-defined symbols called digits.
Number systems are classified into two types:
o Non-positional number system
o Positional number system
This document discusses how computers represent and store data using binary sequences. It explains that all digital data is ultimately stored as sequences of zeros and ones at the lowest level of abstraction. Higher-level abstractions include integers, floating point numbers, text strings, and other data types which are interpreted based on how many bits are used. The document also discusses limitations of fixed bit representations and different units for measuring data transmission capabilities.
Data representation computer architecturestudy cse
Digital computers represent all information internally as binary patterns of 1s and 0s. There are several common data representation schemes that determine how different types of data like integers, floating point numbers, characters, etc. are mapped to and interpreted from these binary patterns. The choice of representation depends on factors like the type and range of values, required precision, and hardware support. Standardized formats like IEEE 754 are used to allow portability of floating point data across systems.
This book's author is Zafar Ali Khan .
It consists of all the topics of As Level Computer Science topics that are required to be covered.
All credits goes to Zafar Ali Khan .
This document discusses various methods of data representation in computers, including:
1. Numeric and non-numeric data types. Computers represent numeric data like integers and real numbers, as well as non-numeric data like letters and symbols.
2. Positional number systems like binary, decimal, octal and hexadecimal are used for efficient internal representation in computers. Conversion between different bases is also covered.
3. Fixed point number representation including signed magnitude, 1's complement, and 2's complement representations. Floating point number representation separates the mantissa and exponent is also discussed.
This document provides an overview of data representation in computers. It discusses binary, decimal, hexadecimal, and floating point number systems. Binary numbers use only two digits, 0 and 1, and can represent values as sums of powers of two. Decimal uses ten digits from 0-9. Hexadecimal uses sixteen values from 0-9 and A-F. Negative binary integers can be represented using ones' complement or twos' complement methods. Twos' complement avoids multiple representations of zero and is commonly used in computers. Converting between number bases involves expressing the value in one base using the digits of another.
CSS L03 - Mensuration and Calculation in CSSMarvin Bronoso
This document discusses digital representation and binary conversion. It defines a bit as the basic unit of data in computing and explains how ASCII uses binary codes to represent letters, numbers, and characters. It then demonstrates how to convert between decimal and binary numbers through long division and provides an example of converting 25 to its binary equivalent of 11001. Finally, it includes tables defining bytes, kilobytes, megabytes, gigabytes and terabytes in terms of bits and bytes.
This document discusses different methods of representing data in a computer, including numeric data types, number systems, and encoding schemes. It covers binary, decimal, octal, and hexadecimal number systems. Methods for representing signed and unsigned integers are described, such as signed-magnitude, 1's complement, and 2's complement representations. Floating point number representation with a sign bit, exponent field, and significand is also summarized. Conversion between different number bases and data encodings like binary-coded decimal are explained through examples.
Everything inside a computer is stored as binary numbers (strings of 0s and 1s) and processed by a CPU with millions of tiny switches that are either on or off. There are different number systems like decimal, binary, and hexadecimal used to represent numbers. Decimal is base 10, binary is base 2, and hexadecimal is base 16. A bit is the smallest unit of information (0 or 1) and bits are grouped into bytes of 8 bits to store data. Common units of data storage from small to large are bytes, kilobytes, megabytes, gigabytes, and terabytes.
The document provides an overview of computer structure and components. It discusses the main parts of a computer system including the processor, memory, and buses that connect the components. It describes the fetch-execute cycle that the processor uses to access and execute instructions stored in memory. Different types of memory like registers, cache, main memory, and backing storage are explained based on their speed and purpose. Factors that impact system performance such as clock speed, memory size, and data transfer rates are also covered.
The document discusses various CPU benchmarks used to evaluate performance, including their pros and cons. It notes that synthetic benchmarks like Dhrystone and Whetstone have limitations and are outdated. Better benchmarks measure real applications or standardized workloads like CoreMark, which aims to replace Dhrystone by testing common algorithms like linked lists and matrices. The document also cautions that benchmarks can be manipulated and advocates for transparency in benchmarking methodology and results.
The document discusses different measures used to compare computer performance:
Clock speed measures the number of cycles per second, but the number of cycles needed varies between processors. MIPS measures millions of instructions per second and is affected by instruction complexity. FLOPS measures floating point operations per second and better compares arithmetic speed between processors using similar instructions. Benchmarks use standard tasks to measure overall performance.
This document describes formal verification of a pipelined CISC microprocessor modeled after the Intel IA32 instruction set using the UCLID term-level verifier. The objective was to understand UCLID's strengths and weaknesses for modeling hardware designs and the verification process. A pipelined Y86 processor implementation from a textbook was verified against its sequential reference model. The control logic was automatically translated to UCLID format. Modularity and automation were emphasized to maintain model fidelity during verification.
The Harvard architecture stores instructions and data in separate physical memory units. It originated from the Harvard Mark I computer which stored instructions on punched tape and data in electromechanical counters. In the Harvard architecture, the instruction and data memories can differ in width, timing, technology and addressing structures. Modern CPUs often use a modified Harvard architecture, containing separate instruction and data caches to improve speed by allowing parallel memory access.
The Von Neumann and Harvard architectures are two common computer architectures. The Von Neumann architecture uses a single memory to store both programs and data, accessed via a shared bus, while the Harvard architecture separates memory and uses two separate buses for program and data access. The Von Neumann architecture has advantages of simpler design and lower cost while the Harvard allows parallel instruction and data processing but has higher development costs. They differ primarily in their memory structure and bus configurations.
This document discusses data representation in computer systems. It covers topics like binary number systems, conversion between number bases, signed and unsigned integers, and binary arithmetic. Specifically, it defines basic units like bits and bytes, explains how to convert decimal numbers to binary and other bases, discusses signed integer representation using the sign-magnitude method and issues with overflow, and outlines the basic rules for binary addition, subtraction, multiplication and division.
This document discusses different data representation methods in computers. It defines binary, octal, hexadecimal and decimal number systems. It describes how numbers are represented using bits and bytes. The relationships between different number systems are explained. Binary addition and subtraction are demonstrated. Character representation using BCD and ASCII are covered. Different methods for converting between number bases are also summarized.
The document discusses how data is represented in computers using binary numbers. It explains that computers use binary, which represents numbers using only two digits (0 and 1) rather than the decimal system's ten digits. This binary system maps well to the two states of on/off in a computer's electrical circuits. The document provides examples of converting decimal numbers to binary and vice versa. It also discusses how signed integers and floating point numbers are represented using binary.
The document discusses data compression using Elias Delta coding. It begins by introducing compression and its purpose of reducing file sizes. It then explains Elias Delta coding which is a lossless compression technique that encodes characters based on their frequency. The more common characters have fewer bits assigned while less common characters have more bits. It provides an example of how Elias Delta coding works by assigning bit sequences to numbers. The document then applies Elias Delta coding to compress a sample text, showing the original string, character set formation, bit lengths, and compressed output which achieved a smaller size than the original text.
The document discusses digital representation and data storage. It explains that a bit is the smallest unit of data that can have a value of 1 or 0. Bytes make up the basic unit of digital storage, with a byte equal to 8 bits. Larger units of data storage are kilobytes, megabytes, gigabytes and terabytes. Converting a decimal number to binary is done by repeatedly dividing the number by 2 and recording the remainders from top to bottom to get the binary equivalent. Storage capacity is measured in bytes, with files and folders taking up space in bytes that is calculated based on their size in kilobytes or megabytes.
The document discusses various number systems used in digital computers including binary, decimal, octal, and hexadecimal. It provides details on:
1) How numbers are represented positionally in these systems, with different radixes (bases) and the meaning of each digit based on its position.
2) Methods for converting between the different number systems, such as dividing the number by the new base and writing the remainders in reverse order.
3) The steps to convert a decimal number to its binary, octal or hexadecimal equivalent and vice versa by calculating the place values of each digit.
This document discusses how computers use binary digits or "bits" represented as 1s and 0s to store and interpret all digital data, including text, numbers, images, and more. It explains that a bit can have one of two values (1 or 0) and how binary codes assign numeric values to different characters. The document also provides an example of converting a decimal number to its binary equivalent through repeated division and collecting the remainders.
Digital computers represent data by means of an easily identified symbol called a digit. The data may
contain digits, alphabets or special character, which are converted to bits, understandable by the computer.
In Digital Computer, data and instructions are stored in computer memory using binary code (or
machine code) represented by Binary digIT’s 1 and 0 called BIT’s.
The number system uses well-defined symbols called digits.
Number systems are classified into two types:
o Non-positional number system
o Positional number system
This document discusses how computers represent and store data using binary sequences. It explains that all digital data is ultimately stored as sequences of zeros and ones at the lowest level of abstraction. Higher-level abstractions include integers, floating point numbers, text strings, and other data types which are interpreted based on how many bits are used. The document also discusses limitations of fixed bit representations and different units for measuring data transmission capabilities.
Data representation computer architecturestudy cse
Digital computers represent all information internally as binary patterns of 1s and 0s. There are several common data representation schemes that determine how different types of data like integers, floating point numbers, characters, etc. are mapped to and interpreted from these binary patterns. The choice of representation depends on factors like the type and range of values, required precision, and hardware support. Standardized formats like IEEE 754 are used to allow portability of floating point data across systems.
This book's author is Zafar Ali Khan .
It consists of all the topics of As Level Computer Science topics that are required to be covered.
All credits goes to Zafar Ali Khan .
This document discusses various methods of data representation in computers, including:
1. Numeric and non-numeric data types. Computers represent numeric data like integers and real numbers, as well as non-numeric data like letters and symbols.
2. Positional number systems like binary, decimal, octal and hexadecimal are used for efficient internal representation in computers. Conversion between different bases is also covered.
3. Fixed point number representation including signed magnitude, 1's complement, and 2's complement representations. Floating point number representation separates the mantissa and exponent is also discussed.
This document provides an overview of data representation in computers. It discusses binary, decimal, hexadecimal, and floating point number systems. Binary numbers use only two digits, 0 and 1, and can represent values as sums of powers of two. Decimal uses ten digits from 0-9. Hexadecimal uses sixteen values from 0-9 and A-F. Negative binary integers can be represented using ones' complement or twos' complement methods. Twos' complement avoids multiple representations of zero and is commonly used in computers. Converting between number bases involves expressing the value in one base using the digits of another.
CSS L03 - Mensuration and Calculation in CSSMarvin Bronoso
This document discusses digital representation and binary conversion. It defines a bit as the basic unit of data in computing and explains how ASCII uses binary codes to represent letters, numbers, and characters. It then demonstrates how to convert between decimal and binary numbers through long division and provides an example of converting 25 to its binary equivalent of 11001. Finally, it includes tables defining bytes, kilobytes, megabytes, gigabytes and terabytes in terms of bits and bytes.
This document discusses different methods of representing data in a computer, including numeric data types, number systems, and encoding schemes. It covers binary, decimal, octal, and hexadecimal number systems. Methods for representing signed and unsigned integers are described, such as signed-magnitude, 1's complement, and 2's complement representations. Floating point number representation with a sign bit, exponent field, and significand is also summarized. Conversion between different number bases and data encodings like binary-coded decimal are explained through examples.
Everything inside a computer is stored as binary numbers (strings of 0s and 1s) and processed by a CPU with millions of tiny switches that are either on or off. There are different number systems like decimal, binary, and hexadecimal used to represent numbers. Decimal is base 10, binary is base 2, and hexadecimal is base 16. A bit is the smallest unit of information (0 or 1) and bits are grouped into bytes of 8 bits to store data. Common units of data storage from small to large are bytes, kilobytes, megabytes, gigabytes, and terabytes.
The document provides an overview of computer structure and components. It discusses the main parts of a computer system including the processor, memory, and buses that connect the components. It describes the fetch-execute cycle that the processor uses to access and execute instructions stored in memory. Different types of memory like registers, cache, main memory, and backing storage are explained based on their speed and purpose. Factors that impact system performance such as clock speed, memory size, and data transfer rates are also covered.
The document discusses various CPU benchmarks used to evaluate performance, including their pros and cons. It notes that synthetic benchmarks like Dhrystone and Whetstone have limitations and are outdated. Better benchmarks measure real applications or standardized workloads like CoreMark, which aims to replace Dhrystone by testing common algorithms like linked lists and matrices. The document also cautions that benchmarks can be manipulated and advocates for transparency in benchmarking methodology and results.
The document discusses different measures used to compare computer performance:
Clock speed measures the number of cycles per second, but the number of cycles needed varies between processors. MIPS measures millions of instructions per second and is affected by instruction complexity. FLOPS measures floating point operations per second and better compares arithmetic speed between processors using similar instructions. Benchmarks use standard tasks to measure overall performance.
This document describes formal verification of a pipelined CISC microprocessor modeled after the Intel IA32 instruction set using the UCLID term-level verifier. The objective was to understand UCLID's strengths and weaknesses for modeling hardware designs and the verification process. A pipelined Y86 processor implementation from a textbook was verified against its sequential reference model. The control logic was automatically translated to UCLID format. Modularity and automation were emphasized to maintain model fidelity during verification.
The Harvard architecture stores instructions and data in separate physical memory units. It originated from the Harvard Mark I computer which stored instructions on punched tape and data in electromechanical counters. In the Harvard architecture, the instruction and data memories can differ in width, timing, technology and addressing structures. Modern CPUs often use a modified Harvard architecture, containing separate instruction and data caches to improve speed by allowing parallel memory access.
The Von Neumann and Harvard architectures are two common computer architectures. The Von Neumann architecture uses a single memory to store both programs and data, accessed via a shared bus, while the Harvard architecture separates memory and uses two separate buses for program and data access. The Von Neumann architecture has advantages of simpler design and lower cost while the Harvard allows parallel instruction and data processing but has higher development costs. They differ primarily in their memory structure and bus configurations.
This document discusses the history and characteristics of CISC and RISC architectures. It describes how CISC architectures were developed in the 1950s-1970s to address hardware limitations at the time by allowing instructions to perform multiple operations. RISC architectures emerged in the late 1970s-1980s as hardware improved, focusing on simpler instructions that could be executed faster through pipelining. Common RISC and CISC processors used commercially are also outlined.
This document discusses RISC vs CISC architectures and the Harvard and von Neumann computer architectures. It provides examples of multiplying two numbers in memory using CISC and RISC approaches. CISC uses complex instructions that perform multiple operations, while RISC breaks operations into simpler instructions. Harvard architecture separates program and data memory while von Neumann uses shared memory.
The document discusses performance measurement and its importance in a business organization. It defines performance measurement as quantitatively evaluating products, services, and processes. It explains that performance measures help understand how well an organization is doing, if it's meeting goals, and where improvements are needed. The document also discusses the Baldrige criteria for performance excellence and its seven factors for evaluating organizational performance.
The document discusses different methods of representing data in computers, including:
1. Binary representation of numbers using 0s and 1s. This allows integers and floating point numbers to be stored.
2. Text representation using character encoding standards like ASCII and Unicode which assign binary codes to letters, numbers and symbols.
3. Graphic representations including bitmapped images and vector graphics. Bitmaps store color values for each pixel while vectors store mathematical descriptions of shapes.
The document discusses different methods of representing data in computers, including:
1. Binary representation of numbers using 0s and 1s. This allows integers and floating point numbers to be stored.
2. Text representation using character encoding standards like ASCII and Unicode which assign binary codes to letters, numbers and symbols.
3. Graphic representations including bitmaps which store color values for each pixel, and vectors which store graphical objects as mathematical descriptions.
Data in computers is represented using binary numbers and organized into units like bytes and kilobytes. Binary numbers are used to represent characters, images, sound, and instructions in a computer. Sound and images are converted from analog to digital formats before being stored. Computer instructions are made up of opcodes and operands to define operations and data.
Computer data representation (integers, floating-point numbers, text, images,...ArtemKovera
This document discusses how computers represent different types of data at a low level. It covers binary, octal, and hexadecimal number systems. It also discusses how integers, floating point numbers, text, images, and sound are represented in computer memory in binary format using bits and bytes. Understanding how data is represented is important for programming efficiently and writing secure code.
This document outlines the course content for a Higher Computing course, which is divided into 3 main units: Computer Systems (40 hours), Software Development (40 hours), and Artificial Intelligence (40 hours). The Computer Systems unit covers topics like data representation, computer structure, networking, and computer software across 5 sections. Specific lessons in the Data Representation section discuss how numbers, text, and images are stored in binary and how storage capacities are measured. Graphics representation and compression techniques are also introduced. Students will complete assessments including end of unit tests, coursework tasks, and a written exam.
This document outlines the course content for a Higher Computing course, which is divided into 3 main units: Computer Systems, Software Development, and Artificial Intelligence. The Computer Systems unit covers topics like data representation, computer structure, networking, and computer software. It discusses how numbers, text, images, and other data are stored in binary and converted between binary and decimal. It also covers graphics representation, storage calculations, and compression techniques. Assessment includes end of unit tests, coursework tasks, and a written exam.
Number Systems — Decimal, Binary, Octal, and Hexadecimal
Base 10 (Decimal) — Represent any number using 10 digits [0–9]
Base 2 (Binary) — Represent any number using 2 digits [0–1]
Base 8 (Octal) — Represent any number using 8 digits [0–7]
Base 16(Hexadecimal) — Represent any number using 10 digits and 6 characters [0–9, A, B, C, D, E, F]
Chapter 2Hardware2.1 The System Unit2.2 Data and PEstelaJeffery653
Chapter 2
Hardware
2.1 The System Unit
2.2 Data and Program Representa-
tion
2.2.1 Digital data and numerical data
Most computers are digital computers which use a spe-
cific language to communicate within itself in order to
process information. If there are programs running in
the background or a person is typing up a word docu-
ment for example, the computer needs to be able to in-
terpret the data that is being put into it by the human as
well as communicate to working components within it-
self. This language that digital computers use is called
binary code and is a very basic form of language com-
posed of only two figures; 1 and 0. Whereas the English
language is composed of 26 figures which we commonly
call the alphabet, computers use a language composed of
only two figures, hence its name Binary Code. Binary lit-
erally means two and refers to anything that consists of,
involves, or indicates two. The language known as Binary
Code operates on a system of 1’s and 0’s strung together.
Each 1 or 0 is referred to as a “bit.” “Bits” are the smallest
unit of data that a binary computer can recognize and ev-
ery action, memory, storage, or computation that is done
through a computer is composed of them. From playing
music through your speakers to cropping a photograph, to
typing up a document and preparing an important presen-
tation all the way down the line to browsing the internet
or picking up on a wifi signal in your area, everything
uses “bits” to complete the task needed. “Bits” string
into larger lines of information the way letters string into
words and then sentences. When eight “bits” are com-
pounded in this way they are then referred to as a “byte”.
“Bytes”, which are made up of “bits”, are commonly used
when referring to the size of the information being pro-
vided. For example, a song that is downloaded may con-
tain several kilobytes or perhaps even a few megabytes if
it is a whole c.d. and not just a single track. Likewise, pic-
tures and all other documents in general are stored on the
computer based on their size or amount of bytes they con-
tain. The amount of information that can be stored onto
a computer is also shown or displayed in bytes as is the
amount left on a computer after certain programs or doc-
uments have been stored. Since bytes can be extremely
long, we have come up with prefixes that signify how large
they are. These prefixes increase by three units of ten
so that a Kilobyte represents 1,000 bytes, a Megabyte
represents 1,000,000 bytes or one million bytes, a Giga-
byte represents 1,0000,000,000 or one billion bytes, etc.
Computers components have become so small that we can
now store larger and larger amounts of data bytes in the
same size computers resulting in the use of other larger
prefixes such as Tera, Peta, Exa, Zetta, and Yotta. Be-
low is a chart outlining the name of the prefix used and
powers of ten they symbolize.
0 1 1 0 1 0 0 0
1 1 0 1 0 0 0 0 0
1 0 0 1 1 1 0 1
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The document discusses various computer components including input devices, processors, memory, storage devices and output devices. It describes the features, functions and uses of keyboards, mice, microphones, touchpads, digital cameras, scanners, webcams and other input devices. It also compares these input devices based on characteristics such as resolution, speed and cost. Output devices such as monitors, printers and speakers are also described along with comparisons of their characteristics. Storage devices including hard drives, floppy drives, CDs, DVDs and magnetic tape are outlined.
The document outlines the course content for an Intro to Computing course, which is divided into three main units on computer systems, software development, and artificial intelligence. The computer systems unit covers topics such as data representation, computer structure, networking, and representing graphics. Sample lesson plans describe how numbers, text, and images are stored in binary and how floating point numbers are represented using mantissa and exponent.
This document provides an overview of the aims and content covered in several lessons for a National 5 Computer Science course. It introduces the course structure and rules, outlines the mandatory units, assessment methods, and folders to be created. It discusses various computer system topics including hardware, software, main memory, processors, buses, storage, and number representation. It also covers representing characters, bitmap images, vector graphics, color depth, and compression.
Chapter 3-Data Representation in Computers.pptKalGetachew2
This document provides an overview of key topics related to computer data representation and binary number systems. It discusses how computers use binary switches to represent all data as strings of 0s and 1s. It also introduces different number systems like decimal, binary, octal and hexadecimal. The document explains how to convert between these number systems. Additionally, it covers binary arithmetic operations like addition, subtraction, multiplication and division. Finally, it discusses common units of data representation like bits, bytes and words, as well as coding methods such as BCD, EBCDIC and ASCII that are used to represent alphanumeric characters in binary.
- Bits are the smallest units of data in computing, represented as 0s and 1s. 8 bits form a byte.
- The motherboard contains the CPU, RAM, ROM, and connections for expansion cards and peripherals. RAM is used for active programs and files while ROM contains startup instructions.
- An operating system manages hardware, allows software to interface with the CPU, and provides a user interface like graphical desktops. Common functions include file management, multitasking, and coordinating input/output.
The document discusses key concepts related to computer systems including:
1. It defines data, information, input, output, and processing.
2. It provides an overview of the basic components of a computer system including hardware, system software, and application software.
3. It explains bits and bytes as the basic units of digital information and discusses various numbering systems used in computing like binary, hexadecimal, and decimal.
This document discusses various topics related to digital representation of data including:
1. The differences between FAT32 and NTFS file systems and their advantages and limitations.
2. How data is represented digitally using coding schemes like ASCII and converted between binary and other number systems.
3. An overview of different numbering systems including binary, decimal, octal and hexadecimal; and how to convert between them.
This document discusses various topics related to digital representation of data including:
1. The differences between FAT32 and NTFS file systems and their advantages and limitations.
2. How data is represented digitally using coding schemes like ASCII and converted between binary and other number systems.
3. An overview of different numbering systems including binary, decimal, octal and hexadecimal; and how to convert between them.
This document provides an overview of how data is represented in computers using binary and bytes. It explains that all data, including integers, characters, pictures, sounds and computer programs, is broken down and stored as sequences of binary digits (bits) that represent the on/off states of switches. Bytes, which are 8 bits each, are used to store a single character, pixel, or other basic unit of different data types. The document includes examples of how integers, characters, images and sound waves are converted into and represented by bytes to be processed by the computer.
This document provides information about different computer codes and number systems used in computing. It discusses binary code, which represents data as strings of 0s and 1s that computers can understand. It also describes other positional number systems like decimal, hexadecimal, octal and their use in computing. Various coding systems for converting numeric and alphanumeric data to binary formats are also covered, including binary-coded decimal and ASCII codes. Methods for converting between number systems like binary to decimal are presented.
This lesson is for students taking the Cambridge School certificate exams Computer science subject(2210).I hope that it will of help to students in this period of crisis. Send me your feedback or suggestions on buxooa72@ gmail.com,
20 Comprehensive Checklist of Designing and Developing a WebsitePixlogix Infotech
Dive into the world of Website Designing and Developing with Pixlogix! Looking to create a stunning online presence? Look no further! Our comprehensive checklist covers everything you need to know to craft a website that stands out. From user-friendly design to seamless functionality, we've got you covered. Don't miss out on this invaluable resource! Check out our checklist now at Pixlogix and start your journey towards a captivating online presence today.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
4. 1 Data Representation 1.2.1 BinaryNumbers Computers work in number base 2 which uses 2 symbols, 0 and 1 to represent a value. In computing systems, large numbers are expressed in terms of powers of 2 and use the following abbreviations: 2 1 has a decimal equivalent of 2 2 2 has a decimal equivalent of 4 2 3 has a decimal equivalent of 8 2 4 has a decimal equivalent of 16 2 5 has a decimal equivalent of 32 2 6 has a decimal equivalent of 64 2 7 has a decimal equivalent of 128 2 8 has a decimal equivalent of 256 2 9 has a decimal equivalent of 512 2 10 has a decimal equivalent of 1024 and is abbreviated to 1 kilo 2 20 has a decimal equivalent of 1,048,576 and is abbreviated to 1 Mega 2 30 has a decimal equivalent of 1,073,741,824 and is abbreviated to 1 Giga 2 40 has a decimal equivalent of 1,099,511,627,776 and is abbreviated to 1 Tera
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7. 1 Data Representation 1.2.4 Hexadecimal Long binary numbers can be difficult to read correctly. Computers have memory addresses of 2 or 4 bytes long which give addresses of 16 or 32 bits. Hexadecimal is base 16 and organises the bits into groups of four. The conversion between base 2 and base 16 is very simple. Hex needs the digits 0-9 and letters A-F. E.g. 11010100010110010011001010010110 becomes 1101 0100 0101 1001 0011 0010 1001 0110 which in Hex is D459 3256
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13. Data Representation 1.4 Graphics Most displays use Raster graphics – same as TV. Displays store images as a matrix of pixels in the refresh buffer. Separate images now stored in VRAM (Video RAM). VRAM represents the entire screen area and the term bit map is used to describe the one-to-one mapping of pixels in VRAM to pixels on the screen.
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17. Data Representation 1.4.4 Greyscale A rudimentary greyscale effect provides a ’black’, ’white’ and two levels of ’grey’. As this comprises four different values we need two bits to represent each pixel (00 for black, 01 for darker grey, 10 for lighter grey and 11 for white ). As each pixel now requires twice as many bits, we will require twice as much memory for a given screen size as a black and white image. We can provide more levels of grey by allocating more bits to each pixel. By the time we have eight bits (one byte) to one pixel we can represent 256 different intensities. Monochrome displays are often clearer, especially for text than colour display. The requirement to use colour for such items as colour pictures and user interface issues, dictates that colour displays are more likely to be purchased.
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19. Data Representation 1.4.5 Colour One colour can be represented by one byte giving 256 colours (GIF format). Monitors etc. have 3 primary (additive) colours, Red, Blue and Green. Other colours obtained from adding light. We use 8 bits for Red, 8 for Blue and 8 for Green which give us 256 x 256 x256 colours – over 16 million. We need 3 bytes to describe RGB coded colours. Codes can be used by a programmer to describe colours in Hex code.
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21. 2 Computer Structure 2.1 An Introduction This unit on Computer Structure describes in detail the function of the component parts of a processor in the manipulation of data. This is extended to the methods of transferring data within a processor and between a processor and memory. The concept of a stored program is considered and the steps in the fetch-execute cycle to access and run programs. Memory types are considered, from registers to backing storage and how memory is defined and addressed.
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26. 2 Computer Structure 2.2.2.1 The structure of the CPU (a) Memory Processor Control unit ALU Registers, A, MAR, MDR, PC, SP Address bus – 1 way Data bus – 2 way Control Bus Internal buses
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28. 2 Computer Structure 2.2.3 The stored program concept All computers based on same basic design, known as the Von Neumann Architecture . Computers carry out tasks by executing machine instructions. A series of these instructions is called a machine code program held in main memory as a stored program , a concept first proposed by John Von Neumann in 1945. Central Processing Unit (CPU) fetches, decodes and executes the machine instructions. By altering the stored program it is possible to have the computer carry out a different task.
29. 2 Computer Structure 2.2.4 The fetch execute cycle To execute a machine code program it must first be loaded, together with any data that it needs, into main memory (RAM). Once loaded, it is accessible to the CPU which fetches one instruction at a time, decodes and executes it at electronic speed. Fetch, decode and execute are repeated until a program instruction to HALT is encountered. This is known as the fetch-execute cycle .
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32. 2 Computer Structure 2.2.8 Computer Components and Their Function The components of the CPU and the connections to devices that are external to it are shown.
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38. 2 Computer Structure 2.4 Central Processing Unit Central Processing Unit. The CPU coordinates and controls the activities of all other units in the computer system. It executes program instructions and manipulates data in accordance with the instructions. It uses a standard architecture composed of the following three components: Arithmetic and logic unit (ALU); Control unit; Registers. All three components work together to form the processor.
39. 2 Computer Structure 2.4.1 Architecture of the microprocessor We will now study the internal architecture of the microprocessor (CPU) itself. Because of the stored program concept , we must consider the relationship between the CPU and memory. This is a diagram of a fairly typical microprocessor design, showing the internal structure of the CPU and its relationship to the memory of the computer.
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41. 2 Computer Structure 2.4.2 Accessing Memory (2) To read data from memory , CPU places the address of the memory location into the MAR and activates the memory-read control line of the system bus. This will cause the required data to be transmitted from memory via the data bus to the MDR; To write from the CPU to memory , the CPU places the data to be written in theMDR; the address of the memory location where they are to be written is placed in the MAR; and the memory-write control line is activated. The MAR and MDR registers have a large part to play in the fetch-execute cycle.
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68. 4.2 – Input & Output Devices 4.2.7 Multiscan Monitor The CRT is the basis of most visual display technology. The screen is arranged as a series of lines of dots and each dot is made up of three small areas of red, green and blue called a triad. The intensity of light shone on each triad determines the actual colour of the pixel. The picture is redrawn between 50 and 100 times a second. This is the refresh rate. A monitor which operate at different refresh rates is known as a multiscan or multisync monitor. The refresh rate is controlled by the video adapter. Screen resolution is quantified by the dot pitch, the distance between the dots on the screen. Typically between 0.28 and 0.38mm, corresponding to 100 to 70 dpi.
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71. 4.4 Buffers and Spoolers 4.4.2 Spooling When large amounts of data are to be sent to a peripheral device, or when the peripheral is shared across a network then spooling is a preferred method of compensating for the difference in speeds of the processor and the peripheral. Spooling involves the input or output of data to a tape or a disk. This, for example, allows output to be queued from many different programs and sent to a printer by a print spooler (special operating system software). The print spooler stores the data in files and sends it to the printer when it is ready, using a print queue . Once the data has been printed it is deleted from the storage device.
72. 4.5 – Storage Devices 4.5.1 Magnetic Magnetic storage devices include hard disks, floppy disks, Zip disks and magnetic tape. They are called magnetic storage devices because their recording surfaces are coated with a material that responds to magnetic fields to enable data to be stored. Storage devices can be fixed or removable. Removable storage devices allow the user to disconnect the device and physically transport data from one computer to another. Varieties of removable devices include the Iomega and Syquest hard disks and Jaz cartridges.
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75. 4.5 – Storage Devices 4.5.1.2 Magnetic Tape Storing data on tapes used to be the only solution to backing up hard disks of large capacity. Now, with large, removable magnetic disks and optical CR-RW technology, this is no longer the case. However, removable storage media is comparatively expensive, costs 10 times tape. Tape, therefore, still has the edge in this market. Tape is read and written on a tape drive. Data is written to tape in blocks with inter-block gaps between them. A single operation writes each block Data is stored on magnetic tape as magnetised regions on the surface of the tape induced by the magnetic recording head. To read data, the tape passes under the read/write head and the stored magnetised regions produce very small voltages in the head, leading to a current in the head coil. This current can be analysed to give a representation of the stored binary data.
76. 4.5 – Storage Devices 4.5.1.2 Magnetic Tape Capacity Magnetic tapes have large capacities, reaching up to several gigabytes and come in a variety of sizes and formats. Since their introduction, tape drives have passed through many stages of improvement with extremely reliable Digital Audio Tape (44.1 kHz, 16-bit record and playback DAT) drives representing the current state of the art. A 4mm DAT tape can now store up to 24 Gbytes of data! Access Tapes are sequential access devices. Accessing data on tapes is therefore much slower than accessing data on disks. They are not suitable as storage media for applications where data needs be used regularly - where a disk is a more appropriate medium. Because tapes are so slow, they are generally used only for long-term storage and backup.
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110. 5 Networking 5.4.1 Network Topology - Bus 4 Factors Affecting Performance 4.6. Network Topology - Bus Bus Topology- easy to expand and cheap to set up. e.g. Ethernet in school or college. Data Security – data encryption methods used. High collision rates requiring re-transmission Bandwidth – available bandwidth shared amongst all stations accessing network. Data compression used. Reliability – fault in one station has no effect on rest. Cable fault will lose all that section. Cost – relatively cheap
111. 5 Networking 5.4.2 Network Topology - Star Data Security – higher security as data routed only to the computer that is to receive it. No collisions. Reliability – if a link fails then only that station is off the network. Failure to central controller is fatal. Cost – can be quite expensive due to high cost of cabling. Popular in small self-contained networks as not too expensive (small office). All nodes connected to one central node that routes traffic to the appropriate place.
112. 5 Networking 5.4.3 Network Topology - Ring Ring Topology Similar to Bus in many respects with similar security problems. Control system in charge of transmissions and stations guaranteed access to transmissions. Collisions avoided by use of a token Additional expense for control s/w and system. May have to wait turn to transmit. Network down to add station, but few if any crashes.
113. 5 Networking 5.4.4 Network Topology - Mesh Mesh Topology Fault in one cable does not affect network. Multiple transmissions Lots of wiring Expensive Excellent performance
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124. 6 Using Networks 6.4 Technical Factors Affecting Communications The technical factors which have led to the growth of computer networks have emerged in parallel with t he economic factors which have driven the research into networking technology. As the economic demand or networking technology has grown, the trend has been for equipment prices to fall and performance to increase. Although still in its infancy, the development of wireless networking is likely to follow the same pattern.