Encyclopedia of Informatics. Great Soviet Encyclopedia - computer science

In English-speaking countries, the term computer science is used - computer science.

The theoretical basis of informatics is a group of fundamental sciences such as: information theory, theory of algorithms, mathematical logic, theory of formal languages ​​and grammars, combinatorial analysis, etc. In addition to them, computer science includes such sections as computer architecture, operating systems, database theory, programming technology, and many others. Important in defining computer science as a science is that, on the one hand, it deals with the study of devices and principles of operation of computer technology, and, on the other hand, with the systematization of techniques and methods for working with programs that control this technology.

Information technology is a set of specific technical and software tools, which perform various operations on information processing in all spheres of our life and activity. Information technology is sometimes referred to as computer technology or applied informatics.

Information analog and digital.

The term "information" originates from Latin informatio, – explanation, exposition, awareness.

Information can be classified different ways, and different sciences do it in different ways. For example, in philosophy distinguish between objective and subjective information. Objective information reflects the phenomena of nature and human society. Subjective information is created by people and reflects their view of objective phenomena.

In computer science, analog information and digital information are considered separately. This is important, because a person, thanks to his senses, is used to dealing with analog information, while computer technology, on the contrary, mainly works with digital information.

A person perceives information through the senses. Light, sound, heat are energy signals, and taste and smell are the result of exposure to chemical compounds, which are also based on energy nature. A person experiences energy impacts continuously and may never encounter the same combination of them twice. There are no two identical green leaves on one tree and two absolutely identical sounds - this is analog information. If different colors are given numbers, and different sounds- notes, then analog information can be turned into digital.

Music, when listened to, carries analog information, but when it is notated, it becomes digital.

The difference between analog information and digital information is, first of all, that analog information is continuous, while digital information is discrete.

Digital devices include personal computers - they work with information presented in digital form, and music players of laser compact discs are also digital.

Information encoding.

Information encoding is the process of forming a certain representation of information. .

In a narrower sense, the term "coding" is often understood as the transition from one form of information presentation to another, more convenient for storage, transmission or processing.

A computer can only process information presented in numerical form. All other information (sounds, images, instrument readings, etc.) must be converted into numerical form for processing on a computer. For example, to quantify musical sound, one can measure the intensity of sound at certain frequencies at short intervals, presenting the results of each measurement in numerical form. Via computer programs you can transform the received information, for example, "superimpose" sounds from different sources on top of each other.

Similarly, textual information can be processed on a computer. When entered into a computer, each letter is encoded by a certain number, and when output to external devices(screen or print) for human perception, images of letters are built on these numbers. The correspondence between a set of letters and numbers is called a character encoding.

As a rule, all numbers in the computer are represented using zeros and ones (and not ten digits, as is customary for people). In other words, computers usually operate in binary number system, since in this case the devices for their processing are much simpler.

Units of measurement of information. Bit. Byte.

A bit is the smallest unit of information representation. Byte - the smallest unit of information processing and transmission .

Solving various problems, a person uses information about the world around us. One often hears that a message carries little information or, conversely, contains exhaustive information, while different people who receive the same message (for example, after reading an article in a newspaper) estimate the amount of information contained in it differently. This means that people's knowledge of these events (phenomena) before receiving the message was different. The amount of information in a message thus depends on how new the message is to the recipient. If, as a result of receiving a message, complete clarity on a given issue is achieved (i.e., the uncertainty disappears), they say that exhaustive information has been received. This means that there is no need for additional information on this topic. On the contrary, if after receiving the message the uncertainty remained the same (the reported information was either already known or not relevant), then no information was received (zero information).

Tossing a coin and watching it fall provides certain information. Both sides of the coin are "equal", so both sides are equally likely to come up. In such cases, the event is said to carry information in 1 bit. If we put two balls of different colors in a bag, then by blindly drawing one ball, we will also get information about the color of the ball in 1 bit.

The unit of measurement of information is called a bit (bit) - an abbreviation for the English words binary digit, what does a binary digit mean.

In computer technology, a bit corresponds to the physical state of the information carrier: magnetized - not magnetized, there is a hole - there is no hole. In this case, one state is usually denoted by the number 0, and the other by the number 1. Choosing one of the two possible options also allows you to distinguish between logical truth and falsehood. A sequence of bits can encode text, image, sound, or any other information. This method of presenting information is called binary coding. (binary encoding) .

In computer science, a quantity called a byte is often used and is equal to 8 bits. And if the bit allows you to choose one option out of two possible, then the byte, respectively, is 1 out of 256 (2 8). Along with bytes, larger units are used to measure the amount of information:

1 KB (one kilobyte) = 2\up1210 bytes = 1024 bytes;

1 MB (one megabyte) = 2\up1210 KB = 1024 KB;

1 GB (one gigabyte) = 2\up1210 MB = 1024 MB.

For example, a book contains 100 pages; 35 lines per page, 50 characters per line. The volume of information contained in the book is calculated as follows:

The page contains 35 × 50 = 1750 bytes of information. The volume of all information in the book (in different units):

1750 × 100 = 175,000 bytes.

175,000 / 1024 = 170.8984 KB.

170.8984 / 1024 = 0.166893 MB.

File. File formats.

A file is the smallest unit of information storage that contains a sequence of bytes and has a unique name.

The main purpose of files is to store information. They are also designed to transfer data from program to program and from system to system. In other words, a file is a repository of stable and mobile data. But, a file is more than just a data store. The file usually has name, attributes, modification time and creation time.

A file structure is a system for storing files on a storage device, such as a disk. Files are organized into directories (sometimes called directories or folders). Any directory can contain an arbitrary number of subdirectories, each of which can store files and other directories.

The way data is organized into bytes is called the file format. .

In order to read a file, such as a spreadsheet, you need to know how the bytes represent the numbers (formulas, text) in each cell; to read a text editor file, one must know which bytes represent characters and which fonts or fields, and other information.

Programs can store data in a file in a manner chosen by the programmer. It is often expected, however, that the files will be used by different programs, so many application programs support some of the more common formats so that other programs can understand the data in the file. Software companies (who want their programs to become "standards") often publish information about the formats they create so that they can be used in other applications.

All files can be conditionally divided into two parts - text and binary.

Text files are the most common type of data in the computer world. One byte is most often allocated to store each character, and text files are encoded using special tables in which each character corresponds to a certain number not exceeding 255. A file for encoding which uses only 127 first numbers is called ASCII- file (short for American Standard Code for Information Intercange - American standard code for information interchange), but such a file cannot contain letters other than Latin (including Russian). Most national alphabets can be encoded using an eight-bit table. For the Russian language, three encodings are currently the most popular: Koi8-R, Windows-1251 and the so-called alternative (alt) encoding.

Languages ​​such as Chinese contain significantly more than 256 characters, so multiple bytes are used to encode each character. To save space, the following trick is often used: some characters are encoded using one byte, while others use two or more bytes. One attempt to generalize this approach is the Unicode standard, which uses a range of numbers from zero to 65,536 to encode characters. Such a wide range allows the characters of a language from any corner of the planet to be represented numerically.

But pure text files are becoming rarer. Documents often contain pictures and diagrams, and various fonts are used. As a result, formats appear that are various combinations of textual, graphical and other forms of data.

Binary files, unlike text files, are not as easy to view, and they usually do not contain familiar words - only a lot of obscure characters. These files are not intended to be directly readable by humans. Examples of binary files are executable programs and graphics files.

Examples of binary encoding of information.

Among the variety of information processed on a computer, a significant part is numeric, textual, graphic and audio information. Let's get acquainted with some ways of encoding these types of information in a computer.

Number encoding.

There are two main formats for representing numbers in computer memory. One of them is used to encode integers, the second (the so-called floating-point representation of a number) is used to specify a certain subset of real numbers.

The set of integers that can be represented in computer memory is limited. The range of values ​​depends on the size of the memory area used to store the numbers. V k-bit cell can store 2 k different values ​​of integers .

To get the internal representation of a positive integer N stored in k-bit machine word, you need:

1) translate the number N into the binary number system;

2) the result obtained is supplemented on the left with insignificant zeros up to k digits.

For example, to get the internal representation of the integer 1607 in a 2-byte cell, the number is converted to binary: 1607 10 = 11001000111 2 . The internal representation of this number in the cell is: 0000 0110 0100 0111.

To write the internal representation of a negative integer (–N), you need:

1) get the internal representation of a positive number N;

2) get the return code of this number, replacing 0 with 1 and 1 with 0;

3) add 1 to the received number.

The internal representation of a negative integer is -1607. Using the result of the previous example, the internal representation of the positive number 1607 is written: 0000 0110 0100 0111. The reverse code is obtained by inverting: 1111 1001 1011 1000. One is added: 1111 1001 1011 1001 - this is the internal binary representation of the number -1607.

The floating point format uses a real number representation R as a product of the mantissa m based on the number system n to some extent p, which is called the order: R=m * np.

The representation of a number in floating point form is ambiguous. For example, the following equalities are true:

12.345 \u003d 0.0012345 × 10 4 \u003d 1234.5 × 10 -2 \u003d 0.12345 × 10 2

Most often, computers use a normalized representation of a number in floating point form. The mantissa in this representation must satisfy the condition:

0.1 p J m p . In other words, the mantissa is less than 1 and the first significant digit is not zero ( p is the base of the number system).

In the computer memory, the mantissa is represented as an integer containing only significant digits (0 integers and a comma are not stored), so for the number 12.345, the number 12,345 will be stored in the memory cell allocated for storing the mantissa. To uniquely restore the original number, it remains only to save it order, in this example is 2.

Text encoding.

The set of characters used to write text is called an alphabet. The number of characters in an alphabet is called its cardinality.

To represent textual information in a computer, an alphabet with a capacity of 256 characters is most often used. One character from such an alphabet carries 8 bits of information, since 2 8 \u003d 256. But 8 bits make up one byte, therefore, the binary code of each character occupies 1 byte of computer memory.

All characters of such an alphabet are numbered from 0 to 255, and each number corresponds to an 8-bit binary code from 00000000 to 11111111. This code is the ordinal number of the character in the binary number system.

For different types of computers and operating systems, different encoding tables are used, which differ in the order in which alphabetic characters are placed in the encoding table. The already mentioned ASCII encoding table is the international standard on personal computers.

The principle of sequential alphabet coding is that in the ASCII code table, Latin letters (uppercase and lowercase) are arranged in alphabetical order. The arrangement of numbers is also ordered in ascending order of values.

Only the first 128 characters are standard in this table, i.e. characters with numbers from zero (binary code 00000000) to 127 (01111111). This includes letters of the Latin alphabet, numbers, punctuation marks, brackets and some other symbols. The remaining 128 codes, starting with 128 (binary code 10000000) and ending with 255 (11111111), are used to encode letters of national alphabets, pseudographics and scientific symbols.

Coding of graphic information.

The video memory contains binary information about the image displayed on the screen. Almost all images created, processed or viewed using a computer can be divided into two large parts - raster and vector graphics.

Raster images are a single-layer grid of dots called pixels (pixel, from the English picture element). The pixel code contains information about its color.

For a black-and-white image (without halftones), a pixel can take only two values: white and black (lights up - does not light up), and one bit of memory is enough to encode it: 1 - white, 0 - black.

A pixel on a color display can have different colors, so one bit per pixel is not enough. Two bits per pixel are required to encode a 4-color image because two bits can take on 4 different states. For example, this color coding option can be used: 00 - black, 10 - green, 01 - red, 11 - brown.

On RGB monitors, all the variety of colors is obtained by combining the basic colors - red (Red), green (Green), blue (Blue), from which you can get 8 basic combinations:

Of course, if you have the ability to control the intensity (brightness) of the glow of the basic colors, then the number of different options for their combinations, generating various shades, increases. Number of different colors - TO and the number of bits to encode them - N are interconnected by a simple formula: 2 N = TO.

As opposed to raster graphics vector image layered. Each element vector image– a line, a rectangle, a circle or a piece of text – is located in its own layer, the pixels of which are set independently of other layers. Each element of a vector image is an object that is described using a special language (mathematical equations of lines, arcs, circles, etc.). Complex objects (broken lines, various geometric shapes) are represented as a set of elementary graphic objects.

Vector image objects, unlike raster graphics, can change their size without losing quality (graininess increases when a raster image is enlarged).

Sound coding.

We know from physics that sound are air vibrations. If you convert sound into an electrical signal (for example, using a microphone), you can see a voltage that changes smoothly over time. For computer processing, such an analog signal must somehow be converted into a sequence of binary numbers.

This is done, for example, like this - the voltage is measured at regular intervals and the resulting values ​​\u200b\u200bare recorded in the computer's memory. This process is called sampling (or digitizing), and the device that performs it is called an analog-to-digital converter (ADC).

To reproduce the sound encoded in this way, you need to do the inverse conversion (for this, a digital-to-analog converter is used). - DAC), and then smooth the resulting step signal.

The higher the sampling rate and the more bits allocated for each sample, the more accurately the sound will be represented, but the size of the sound file will also increase. Therefore, depending on the nature of the sound, the requirements for its quality and the amount of memory occupied, some compromise values ​​are chosen.

Described coding method sound information quite versatile, it allows you to imagine any sound and transform it in a variety of ways. But there are times when it is more beneficial to act differently.

A fairly compact way of representing music has long been used - musical notation. It indicates with special symbols what height the sound is, on which instrument and how to play. In fact, it can be considered an algorithm for a musician, written in a special formal language. In 1983, leading manufacturers of computers and music synthesizers developed a standard that defined such a system of codes. It's called MIDI.

Of course, such a coding system allows you to record not every sound, it is suitable only for instrumental music. But it also has undeniable advantages: an extremely compact recording, naturalness for a musician (almost any MIDI editor allows you to work with music in the form of ordinary notes), ease of changing instruments, changing the tempo and key of the melody.

There are other, purely computer, music recording formats. Among them is the MP3 format, which allows you to encode music with very high quality and compression, while instead of 18–20 musical compositions, about 200 are placed on a standard compact disc (CDROM). One song occupies approximately 3.5 Mb, which allows It is easy for Internet users to exchange musical compositions.

The computer is a universal information machine.

One of the main purposes of a computer is the processing and storage of information. With the advent of computers, it became possible to operate with previously unthinkable volumes of information. Libraries containing scientific and fiction literature are being converted into electronic form. Old photo and film archives are given new life in digital form.

Anna Chugainova

INFORMATION (English informatics), the science of extracting information from messages, creating information resources, programming the behavior of machines and other entities related to the construction and use of a human-machine environment for solving problems of modeling, design, interaction, learning, etc. It studies the properties of information , methods for extracting it from messages and presenting it in a given form; properties, methods and means of information interaction; properties of information resources, methods and means of their creation, presentation, storage, accumulation, search, transfer and protection; properties, methods and means of constructing and using programmable machines and human-machine environment for solving problems.

Scientific production of informatics

The scientific production of informatics serves as a methodological basis for constructing a human-machine environment for solving problems (Fig. 1) related to various fields of activity.

The results of studies of entities (usually called objects in science) are represented by their symbolic and/or physical models. Symbolic models are descriptions of acquired knowledge [see. Symbolic modeling(s-modeling)], and physical ones are prototypes of the objects under study, reflecting their properties, behavior, etc. The scientific result is a model of a knowledge system (or a component of a previously defined and published model) that describes a set of objects, including the object under study, and the relationships between them . The description of the model is presented in the form of a message designed for recognition and interpretation by the scientific community. The value of the result depends on the predictive power, reproducibility and applicability of the model, as well as on the properties of the message containing its description.

Examples of results that have played an outstanding role in the methodological support of building a human-machine environment for solving problems can be: the model of a digital electronic machine invented by J. von Neumann with program instructions and data stored in a shared memory [known as the von Neumann model] and the von Neumann architecture] ; invented by the creator of the Web (cf. The World Wide Web) T. Berners Lee HTTP protocol (eng. Hypertext transfer protocol - hypertext transfer protocol), which is an application layer protocol that defines the rules for transferring messages in hypermedia (see Multimedia) systems, and a uniform resource identifier URI (eng. Uniform Resource Identifier), which has become the standard for recording a resource address posted on the Internet. It is difficult to find today (2017) a field of activity where the scientific products of informatics are not applied. Based on it, email, the Web, search engines, IP telephony, the Internet of things and other Internet services were created (see Internet); digital audio, photo and video recording; computer-aided design systems (CADs); computer simulators and robots (see. Computer modelling), systems digital communications, navigation systems, 3D printers, etc.

Basic concepts

The ongoing formation of informatics is accompanied by the development of its conceptual apparatus and the refinement of the subject of research. In 2006 at the Institute of Informatics Problems Russian Academy Sciences (IPI RAS) a new area of ​​research was created - symbolic modeling of arbitrary objects in a human-machine environment (abbreviated- With symbolic simulation or s-simulation). One of the first scientific projects in this area was devoted to the methodology for constructing a symbolic model of the informatics knowledge system in a human-machine environment. . In the theory of symbolic modeling (s-modeling) created in 2009, the next version of the symbolic model of the core of the system of computer science concepts was proposed, which includes the following concepts.

Message(English message) is considered as a finite ordered set of symbols (visual, audio, etc.; see Symbol in computer science) or its code (see Code in computer science) that satisfies the protocol of interaction between the source and the recipient. The existence of a message presupposes the existence of a message source, a recipient, a carrier, a transmission medium, a means of delivery, and a protocol for the interaction between the source and the recipient. In the human-machine environment for solving problems (s-environment), people with the help of programmable machines (s-machines) form messages, presenting them in query languages, programming, etc.; perform various conversions (eg, from analog to digital and vice versa; from uncompressed to compressed and vice versa; from one form of document representation to another); recognize, use messages to construct new messages (programs, documents, etc.); interpret on models of concept systems (which are stored in the memory of the interpreter also in the form of messages); exchange messages using software and hardware-implemented rule systems (network protocols, see below). Computer network); save and accumulate messages (by creating electronic libraries, encyclopedias and other information resources), solve the problems of searching and protecting messages.

Message interpreter is studied as a builder of the output message according to the input in accordance with the given system of interpretation rules. A necessary condition for constructing a message interpreter is the existence of models of the input and output languages, as well as models of concept systems on which messages written in the input and output languages ​​should be interpreted.

Data(eng. data) - a message necessary to solve a certain problem or set of problems, presented in a form designed for recognition, transformation and interpretation by the solver (program or person). A person perceives data (text, images, etc.) in symbolic form, while a computer program or computer device (smartphone, digital camera, etc.) perceives it in code.

Information(English information) is studied as a result of the interpretation of the message on the model of the system of concepts [see. Symbolic modeling(s-simulation)]. To extract information from a message, it is necessary to have the received message presented in a form designed to be recognized and interpreted by the recipient of the message; concept system models stored in the interpreter's memory, among which is the one necessary for interpreting the received message; mechanisms for searching for the necessary model, interpreting the message, presenting the result of interpretation in a form designed for the recipient (Fig. 2).

For example, the result of interpreting the message ma , presented in language a , received by the translator (human or robot) in the form of a message mb in language b , is the information extracted from the message ma .

Programmable task(s-problem) is considered as a set (Formul , Rulsys , Alg , Prog ), where Formul is the problem statement; Rulsys - a set of systems of mandatory and orienting rules for solving a problem, aligned with Formula; Alg is the union of sets of algorithms, each of which corresponds to one element from Rulsys ; Prog is the union of sets of programs, each of which is assigned to one of the elements of Alg . Each element from Rulsys , Alg and Prog must be given an application description. Descriptions of the use of Rulsys elements include specification of the type of problem solver (autonomous s-machine, network cooperation of s-machines, human-s-machine cooperation, etc.), information security requirement, etc. Descriptions of the use of elements from Alg include data on acceptable problem solver operation modes (automatic local, automatic distributed, interactive local, etc.), requirements for the result obtained, etc. Descriptions of the application of programs include data on implementation languages, operating systems, etc.

Algorithm– a formalized description of a finite set of steps for solving the problem, corresponding to one of the elements of Rulsys and allowing one-to-one correspondence with a given set of input data to the resulting set of output data.

Program– an algorithm implemented in a high-level programming language, a machine-oriented language and/or in a system of machine instructions. Presented in the form of a message that defines the behavior of an s-machine problem solver with given properties. Exists in symbolic, code and signal incarnations, connected by translation relations (see Compiler in computer science).

Symbol(English symbol) - a substitute for a natural or invented object, denoting this object and being an element of a certain system for constructing symbolic messages (texts, musical notations, etc.), designed to be perceived by a person or a robot. For example, the Russian alphabet is a system of text symbols; the letter A in this system is a symbol that replaces the corresponding sound from the system of speech audio symbols of the Russian language; The letter A corresponds to a tactile textural symbol (perceived by touch with the fingers) in a text messaging system for the blind known as Braille (see Fig. Braille). The set of visual, audio and other symbols chosen to build messages of a certain type is considered as a set of elementary constructive objects, each of which is endowed with a set of attributes and a set of allowed operations. The creation of structures from the elements of this set is determined by the system of rules for constructing symbolic models [for more details, see the article Symbol in computer science (s-symbol)].

The code(English code) - a substitute for a symbol or symbolic message used to represent them in computers, smartphones and other programmable machines and designed to build, save, transmit and interpret symbolic messages [for more details, see the article Code in computer science ( s-code)].

Signal(eng. signal) - optical, sound or other impact perceived by the human senses or machine sensors, or the representation of the code in the form of a frequency electromagnetic radiation, compositions of electrical voltage values, or another, designed to be perceived by the hardware of the machine (for example, the central processing unit of a computer, microprocessor car navigator). Symbols, codes and signals are interconnected by transformation relations. Each symbol and symbolic construction, designed for perception by a human or a robot, can be assigned one-to-one correspondence with codes designed to manipulate them with the help of computer software and computer devices.

Concept system model. The S-model Cons of a system of concepts is considered as a pair (ConsSet , ConsRel ), where ConsSet is a set of concepts; ConsRel is a family of relationships defined on ConsSet . Definition of a system of concepts - a description of its model, accompanied by an indication of the scope. The description is presented in the form of a message designed for interpretation by the recipient, presentation, storage, distribution, accumulation and search in the human-machine environment of intellectual activity. A system of concepts considered to be definite should not include concepts that do not have definitions (and at the same time are not related to concepts-axioms). Determining the scope of model applicability - description of the types of correspondent (to whom the definition is addressed), the goal in the process of achieving which the definition makes sense (classes of tasks in the study of which the definition can be useful), the stage at which it is advisable to use the definition (concept, solution methodology, etc.) d.).

Knowledge system model. The concept of "know" in s-modeling [see. Symbolic modeling(s-simulation)] is defined as the state of the message receiver when the output message resulting from the interpretation of the input message is recognized as already known and does not require changes in the models of concept systems stored in the memory of the message receiver. The concept of "knowledge" is defined as a complex ability to extract information from messages containing the conditions of tasks of a certain class (these can be tasks of pattern recognition, translation from one language to another, or other classes of tasks). The S-model of the knowledge system is considered as a triad (Cons , Lang , Interp ), where Cons is the s-model of the concept system; Lang is the s-model of the set of message languages ​​interpreted on Cons ; Interp is the s-model of the collection of interpreters on Cons of messages composed in languages ​​from Lang .

The interpretation of the message on the Cons model includes:

1) building an output message (extraction of information) according to a given input message (messages are presented in languages ​​from the set Lang );

2) analysis of the output message (whether changes are required in the Cons model);

3) if required, then change the Cons model; if not, end.

For example, the brain center of a modern computer-aided design (CAD) system is the knowledge system. The productivity of design depends on how well it is built.

Programmable machine(s-machine) is a software and hardware structure for solving problems. Supercomputers, mainframes, personal computers, laptops, smartphones, navigators, digital cameras and video cameras are all s-cars. Keyboards, mice, trackballs, touchpads and other input devices are components of s-machines that convert characters into codes accepted by drivers (see Driver in computer science) of the corresponding devices. Monitors of personal computers, displays of laptops, navigators, etc. convert codes generated by video controllers into symbolic compositions designed for the human visual channel.

(s-environment) - an association of computer networks and individual programmable machines used to solve various problems. Means of informatization of various types of activity. The S-environment must provide the representation of digital codes of symbolic models and the manipulation of such codes with the help of s-machines. At the heart of modern digital communication technologies, computer-aided design, etc., there is an idea that is remarkable in terms of the consequences of its implementation - to reduce all symbolic diversity to digital codes [and each of them to a single code (they still have a binary code)] and instruct work with codes to programmable machines, combined into a human-machine environment for solving problems.

Information interaction in the s-medium(Fig. 3) is studied as a set of interfaces such as "man - man", "man - program", "man - hardware of a programmable machine", "program - program", "program - hardware" (see Interface Port in computer science ). A person perceives input analog signals (light, sound, etc.) with the help of visual, auditory and other input devices of biointelligence (a biological system that ensures the functioning of the intellect). He converts the signals he is interested in into symbolic visual, audio and other constructions used in the processes of thinking. The output signals of biointelligence are realized through gestures (for example, used when entering from the keyboard and mouse), speech, etc. . The input and output of the programs are the input data and result codes (see Fig. The code in computer science), and the input and output of the hardware are signals. Input analog signals are converted to digital signals using analog-to-digital converters(ADC), and the output digital to analog using digital-to-analog converters(DAC).

In the modern (2017) s-environment, natural means of human signal perception, processing and storage are supplemented by invented ones: digital photo and video cameras, smartphones, etc. A well-known part of information interaction technologies is represented by rapidly developing Internet services. Used to interact with people Email(English e-mail), various types of Internet connection [ Internet telephony(IP-telephony); for example, implemented in the Skype Internet service; messengers (English messenger - connected); for example, the Telegram Internet service), social networks (English social networks), etc. For the interaction of things used by people (lighting systems, temperature maintenance, etc.) between themselves and with the external environment, information technologies of the “Internet of things” are used (see. Internet ).

Basic task classes

Based on the study of properties and patterns symbolic modeling(s-simulation) the following classes of basic computer science problems are defined.

Representing Arbitrary Object Models, designed for human perception and programmable machines, is associated with the invention of message languages ​​that meet certain requirements. This class studies the symbol and code systems used in human- and machine-oriented languages, respectively. The first includes languages ​​of specification, programming, queries, the second - systems of machine instructions. This class also includes data presentation tasks. It includes the tasks of representing models of concept systems on which messages are interpreted. At the top level of the task hierarchy of this class is the representation of models of knowledge systems.

Converting types and representation forms of symbolic models allows you to establish correspondence between models. The tasks of converting types (for example, speech to text and vice versa) and forms (for example, analog to digital and vice versa; uncompressed to compressed and vice versa; *.doc to *.pdf) are a necessary addition to the tasks of representing models.

Message recognition implies the need to present it in a format known to the recipient. When this condition is met, to recognize the message, the tasks of matching with model models, or matching the properties of the recognized model with the properties of model models, are solved. For example, in the task of biometric identification of a person, his biometric data (input message) is compared with a biometric sample from the database of the biometric system.

Model building concept systems, knowledge systems, message interpreters on models of concept systems; task models, programming technologies, interaction in the s-environment; architecture models of s-machines, computer networks, service-oriented architectures; message models and means of their construction, documents and workflow. At the top level of the hierarchy of this class are the tasks of constructing s-environment models and symbolic modeling technologies.

Message interpretation(information extraction) presupposes the existence of the received message, the model of the system of concepts on which it should be interpreted, and the mechanism of interpretation. Solving problems in the human-machine environment is the interpretation of the initial data (input message) on the model of the system of concepts presented in the algorithm. The result of the solution is the output message (information extracted from the input message). If the interpreter is an executable program, then the source data, the program, and the result of solving the problem are represented by the corresponding codes (see Code in Computer Science). For the microprocessor of the programmable machine, the messages to be interpreted and the results of the interpretation are represented by signals corresponding to machine instruction and data codes. For example, when shooting with a digital camera, a message (in the form of a light signal) acts on a photosensitive matrix, is recognized by it, and then converted into a digital image code, which is interpreted by a program that improves image quality. The resulting result is converted and recorded (on the camera's built-in storage or memory card) as a graphic file.

Message exchange: the tasks of constructing interfaces of the type "man - man", "man - program", "man - hardware of a programmable machine", "program - program", "program - hardware" (see Interface in computer science), "hardware - hardware” (see Port in computer science); tasks of messaging in a human-machine environment for solving problems (with typing of senders and recipients; means of sending, transmitting and receiving messages; messaging environments). Systems of message exchange rules (network protocols) are invented; network architectures; document management systems. For example, messages are exchanged between processes operating systems(OS), s-machine programs in a computer network, e-mail users, etc.

Saving, accumulating and searching messages: memory and storage devices, their control mechanisms are studied and typified; forms of conservation and accumulation; media, methods of preservation, accumulation and search; databases and software libraries. Models of the subject of search (by model, by features, by description of properties) and search methods are studied.

Information protection: the problems of prevention and detection of vulnerabilities, access control, protection against intrusions, malware, interception of messages and unauthorized use are studied.

Research areas

The most important scientific ideas influencing the development of informatics are embodied in the methodological support for the construction of tools to support the processes of cognition, information interaction and automated solution of various problems. At the present stage (2017) of the development of informatics, the following interconnected complexes of research areas are relevant.

Automation of calculations(computing with the help of programmable machines): models, architectures and command systems of programmable machines are studied; algorithmization of programmable tasks [algorithms and data structures, distributed algorithms (Distributed Algorithms), randomized algorithms (Randomized Algorithms), etc.]; distributed computing (Distributed Computing), cloud computing (Cloud Computing); complexity and resource intensity of calculations.

Programming: systems of text symbols and codes are studied; programming languages ​​and task specifications; translators; program libraries; system Programming; OS; instrumental programming systems; database management systems; programming technologies; online services for solving problems, etc.

Human-machine environment for problem solving(s-environment): models, methods and tools for constructing an s-environment, computer networks, digital communication networks, the Internet are studied.

Perception and presentation of messages, interaction in the s-environment: models, methods and means of perception and presentation of visual, audio, tactile and other messages are studied; computer vision, hearing and other artificial sensors; formation of audio, visual, tactile and other messages (including combined ones) designed for a person and a partner robot; recognition of audio, visual and other messages (speech, gestures, etc.); image processing, computer graphics, visualization, etc.; message exchange (message models, methods and means of their reception and transmission); interfaces of the user, programs, hardware, programs with hardware; online interaction services (messengers, social networks, etc.).

Information resources and systems for solving problems in the s-environment: models, methods and means of constructing, representing, saving, accumulating, searching, transferring and protecting information resources are studied; electronic document management; electronic libraries and other information systems; web (see The World Wide Web).

Information security and cryptography: methods of prevention and detection of vulnerabilities are studied; access control; protection of information systems from intrusions, malware, interception of messages; unauthorized use of information resources, software and hardware.

Artificial Intelligence: models, methods and tools for building intelligent robots used as human partners (for solving security problems, situational control, etc.) are studied; expert decision-making methods.

Symbolic modeling: systems of visual, audio, tactile and other symbols are studied, considered as constructive objects for building models of arbitrary entities designed for a person (systems of concepts and knowledge systems, environmental objects and objects invented by people); systems of codes, put in accordance with systems of symbols, which are intended for the construction of code equivalents of symbolic models designed for manipulation with the help of programs; languages ​​for describing symbolic models; typing of symbolic models and their code equivalents; methods for constructing symbolic models of concept systems and knowledge systems (including knowledge systems about programmable tasks) [for more details, see the article Symbolic modeling(s-simulation)].

The formation of computer science

Symbolic modeling of objects under study has long served as the main tool for presenting acquired knowledge. The invention of symbols (gestural, graphic, etc.) and the symbolic message models built from them, the representation and accumulation of such models in the external environment have become key means for the formation and development of intellectual abilities. The dominant role of symbolic models in intellectual activity is determined not only by their compactness and expressiveness, but also by the fact that there are no restrictions on the types of media used to store them. The media can be human memory, paper sheet, digital camera matrix, digital voice recorder memory or something else. The costs of building, copying, transferring, saving and accumulating symbolic models are incomparably less than similar costs associated with non-symbolic models (for example, models of ships, buildings, etc.). Without symbolic modeling tools, it is difficult to imagine the development of science, engineering, and other activities.

In the early stages of the development of modeling, the variety of objects being modeled was limited to what is commonly called environmental objects, and the models of these objects were physical. The development of sound, gesture and other means of symbolic modeling of meanings, caused by the need to report danger, the placement of hunting objects and other objects of observation, contributed to the improvement of the mechanisms of cognition, mutual understanding and learning. Message languages ​​began to form, including sound and gesture symbols. The desire to model behavior (including one's own) has posed new challenges. It can be assumed that initially this desire was associated with teaching rational behavior on the hunt, in everyday life, during natural disasters. At a certain stage, they thought about creating such modeling tools that would allow building models that allow their storage, copying and transfer.

The desire to increase the effectiveness of the explanations accompanying the show led to the improvement of the conceptual apparatus and the means of its speech embodiment. The development of symbolic models in the form of graphic schemes and the improvement of speech led to a graphical model of speech. Writing was created. It became not only an important stage in the development of symbolic modeling, but also powerful tool in the development of intellectual activity. Now descriptions of modeling objects and relationships between them could be represented by compositions of texts, diagrams and drawings. A toolkit was created to display observations, reasoning and plans in the form of symbolic models that could be stored and transmitted. The tasks of inventing media, tools for writing and creating images, coloring agents, etc. became topical. These were the first tasks on the way to building a symbolic modeling environment.

An important stage in graphic modeling is associated with models of schematic images (the progenitors of drawings) - the basis of design. Presentation of the projected three-dimensional object in three two-dimensional projections, which show the dimensions and names of parts, played a decisive role in the development of engineering. On the way from handwritten texts, drawings and diagrams to typography and graphic models in design, from sound recording, photography and radio to cinema and television, from computers and local networks to the global network, virtual laboratories and distance education, the role of symbolic models that a person creates with machines.

The productivity of problem solvers is a key problem of the productivity of intellectual activity, which is constantly in the focus of attention of inventors. The need for quantitative assessments of material objects has long stimulated the invention of systems of sound, gesture, and then graphic symbols. For a while, they managed with the rule: each value has its own symbol. Counting using pebbles, sticks and other objects (objective counting) preceded the invention of symbolic counting (based on graphic representation quantities). As the number of objects that had to be used increased, the task of symbolic representation of quantities became more urgent. The formation of the concept of "numbers" and the idea of ​​saving symbols when modeling numbers led to the invention of number systems. The idea of ​​positional number systems deserves special mention, one of which (binary) in the 20th century. was destined to play a key role in the invention of digital programmable machines and the digital coding of character models. Changing the meaning of a symbol with a change in its position in the sequence of symbols is a very productive idea that provided advancement in the invention of computing devices (from the abacus to the computer).

Tools for increasing the productivity of problem solvers. In 1622–33, the English scientist William Otred proposed a variant slide rule, which became the prototype of slide rules that engineers and researchers around the world have been using for more than 300 years (before personal computers became available). In 1642, B. Pascal, trying to help his father in the calculations when collecting taxes, creates a five-digit adding device ("Pascaline" ), built on the basis of gear wheels. In subsequent years, he created six- and eight-digit devices that were designed to add and subtract decimal numbers. In 1672, the German scientist G.W. Leibniz creates a digital mechanical calculator for arithmetic operations on twelve-digit decimal numbers. It was the first calculator that did everything arithmetic operations. The mechanism, called the "Leibniz Wheel", until the 1970s. reproduced in various handheld calculators. In 1821, the industrial production of adding machines began. In 1836–48 C. Babbage completed the project of a mechanical decimal computer (called by him an analytical engine), which can be considered as a mechanical prototype of future computers. The calculation program, data and result were recorded on punched cards. Automatic execution programs provided control device. The car was not built. In 1934 - 38 K. Zuse created a mechanical binary computer (word length– 22 binary digits; memory– 64 words; floating point operations). Initially, the program and data were entered manually. Approximately a year later (after the start of designing), a device for entering the program and data from a perforated film was made, and the mechanical arithmetic unit (AU) was replaced by an AU built on telephone relays. In 1941, Zuse, with the participation of the Austrian engineer H. Schreier, created the world's first working fully relay binary computer with program control (Z3). In 1942, Zuse also created the world's first control digital computer (S2), which was used to control projectile aircraft. Due to the secrecy of the work performed by Zuse, their results became known only after the end of the 2nd World War. The world's first high-level programming language Plankalkül (German Plankalkül - calculus plan) was created by Zuse in 1943-45, published in 1948. The first digital electronic computers, starting with the American ENIAC computer [(ENIAC - Electronic Numerical Integrator and Computer - electronic numerical integrator and calculator); beginning of development - 1943, presented to the public in 1946], were created as a means of automating mathematical calculations.

Creating the Science of Computing with Programmable Machines. All R. 20th century the production of digital computers began, which in the USA and Great Britain were called computers (computers), and in the USSR - electronic computers (computers). Since the 1950s in the UK and from the 1960s in the USA, the science of computing with the help of programmable machines began to develop, called Computer Science (computer science). In 1953 University of Cambridge a program was formed in the specialty Computer Science; in the USA a similar program was introduced in 1962 at Purdue University.

In Germany, Computer Science was called Informatik (computer science). In the USSR, the field of research and engineering devoted to the construction and application of programmable machines was called "computer technology". In December 1948, I. S. Bruk and B. I. Rameev received the first in the USSR copyright certificate for the invention of an automatic digital machine. In the 1950s created the first generation of domestic computers ( element base- vacuum tubes): 1950 - MESM (the first Soviet electronic computer, developed under the leadership of S. A. Lebedev ); 1952 - M-1, BESM (until 1953 the fastest computer in Europe); 1953 - "Arrow" (the first mass-produced computer in the USSR); 1955 - Ural-1 from the Ural family of general-purpose digital computers (chief designer B. I. Rameev).

Improving the methods and means of automation. With the growing availability of computers for users from various fields of activity, which began in the 1970s, there is a decrease in the share of mathematical problems solved using computers (originally created as a means of automating mathematical calculations), and an increase in the share of non-mathematical problems (communication, search, etc.). .). When in the second half of the 1960s. computer terminals with screens began to be produced, the development of screen editor programs for entering, saving and correcting text with displaying it on a full screen began [one of the first screen editors was O26, created in 1967 for console operators of CDC 6000 series computers; in 1970, vi was developed, the standard screen editor for Unix and Linux operating systems]. The use of screen editors not only increased the productivity of programmers, but also created the prerequisites for significant changes in the tools for automated construction of symbolic models of arbitrary objects. For example, using screen editors to generate texts for various purposes(scientific articles and books, textbooks, etc.) already in the 1970s. allowed to significantly increase the productivity of creating text information resources. In June 1975, American researcher Alan Kay [the creator of the object-oriented programming language Smalltalk and one of the authors of the idea of ​​a personal computer] in the article "Personal Computing" (« Personal Computing» ) wrote: “Imagine yourself as the owner of an autonomous knowledge machine in portable case, which is the size and shape of a regular notepad. How would you use it if its sensors were superior to your sight and hearing, and its memory allowed you to store and retrieve, if necessary, thousands of pages of reference materials, poems, letters, recipes, as well as drawings, animations, music, graphics, dynamic models and something else that you would like to create, remember and change? . This statement reflected the turn that had taken place by that time in the approach to the construction and application of programmable machines: from automation tools, mainly mathematical calculations, to tools for solving problems from various fields of activity. In 1984 Kurzweil Music Systems (KMS), created by American inventor Raymond Kurzweil, produced the world's first digital music synthesizer, the Kurzweil 250. It was the world's first dedicated computer that converted gesture characters entered from the keyboard into musical sounds.

Improvement of methods and means of information interaction. In 1962, American researchers J. Licklider and W. Clark published a report on online human-machine interaction. The report contained a justification for the expediency of building a global network as an infrastructure platform that provides access to information resources hosted on computers connected to this network. The theoretical substantiation of packet switching in the transmission of messages in computer networks was given in an article published in 1961 by the American scientist L. Kleinrock.In 1971 R. Tomlinson (USA) invented e-mail, in 1972 this service was implemented. The key event in the history of the creation of the Internet was the invention in 1973 by American engineers V. Cerf and R. Kahn of the transmission control protocol - TCP. In 1976 they demonstrated the transmission of a network packet over the TCP protocol. In 1983, the TCP/IP protocol family was standardized. In 1984, the Domain Name System (DNS) was created (see. Domain in computer science). In 1988, the chat protocol [Internet Real Time Text Messaging Service (IRC - Internet Relay Chat)] was developed. In 1989, the Web project was implemented (see. The World Wide Web) developed by T. Berners Lee. 6.6.2012 - a significant day in the history of the Internet: major Internet providers, equipment manufacturers for computer networks and web companies began to use the IPv6 protocol (along with the IPv4 protocol), practically solving the problem of scarcity of IP addresses (see Internet). The high rate of development of the Internet is facilitated by the fact that since its inception, professionals involved in the scientific and technical tasks of building the Internet have been exchanging ideas and solutions without delay using its capabilities. The Internet has become an infrastructural platform for a human-machine environment for solving problems. It serves as a communication infrastructure Email, Web, search engines, Internet telephony(IP-telephony) and other Internet services used in the informatization of education, science, economics, public administration and other activities. Electronic services created on the basis of the Internet have made possible the successful functioning of a variety of commercial and non-commercial Internet entities: online stores, social networks [Facebook (Facebook), VKontakte, Twitter (Twitter), etc.], search engines [Google (Google), Yandex (Yandex) and others], encyclopedic web resources [Wikipedia (Wikipedia), Webopedia, etc.], electronic libraries [World Digital Library (World Digital Library), Scientific electronic library eLibrary, etc.], corporate and government information portals and etc.

Since the 2000s, the number of Internet solutions has been intensively growing - Smart House, Smart Grid, etc., embodying the concept of The Internet of Things. M2M solutions (M2M - Machine-to-Machine) based on information technologies of machine-to-machine interaction and designed to monitor temperature sensors, electricity meters, water meters, etc. are successfully developing; tracking the location of moving objects based on GLONASS and GPS systems (see. Satellite positioning system); access control to protected objects, etc.

Official registration of informatics in the USSR. Informatics was officially formalized in the USSR in 1983, when the Department of Informatics, Computer Engineering and Automation was formed as part of the USSR Academy of Sciences. It included the Institute of Informatics Problems of the USSR Academy of Sciences, established in the same year, as well as the Institute of Applied Mathematics of the USSR Academy of Sciences, the Computing Center of the USSR Academy of Sciences, the Institute for Information Transmission Problems of the USSR Academy of Sciences, and a number of other institutes. At the first stage, research in the field of hardware and software for mass computing and systems based on them was considered the main one. The results obtained were to become the basis for the creation of a family of domestic personal computers (PC) and their application for the informatization of scientific, educational and other relevant activities.

Problems and prospects

Methodological support for the construction of a personal s-environment. In the coming years, one of the topical areas of methodological support for improving the s-environment will be associated with the creation of personalized problem solving systems, the hardware of which is placed in the user's equipment. Speeds advanced technologies Wireless communications are already sufficient for solving many problems based on Internet services. It is expected that by 2025 the speed and prevalence of wireless communication technologies will reach levels at which part of the wired interfaces of today will be replaced by wireless ones. The reduction in prices for Internet services will also contribute to the promotion of technologies for personalizing the user's s-environment. Actual problems associated with the personalization of the s-environment are: the creation of more advanced symbolic and coding systems; hardware-software conversion of audio and tactile messages sent by a person into graphics, represented by a composition of text, hypertext, special characters and images; technological improvement and unification of wireless interfaces [primarily video interfaces (output at the user's choice: on special glasses, monitor screens, TV or other video output device)].

The methodological support for building a personal s-environment should be based on the results of research in the field of artificial intelligence aimed at building not a machine simulator of human intelligence, but an intelligent partner controlled by a person. The development of technologies for building a personal s-environment involves the improvement of methodologies for distance learning, interaction, etc.

List of articles

1. Measurement of information - alphabetical approach

2. Measuring information - a meaningful approach

3. Information processes

4. Information

5. Cybernetics

6. Encoding information

7. Information processing

8. Transfer of information

9. Representation of numbers

10. Number systems

11. Information storage

The main objects of study of the science of computer science are information and information processes. Informatics as an independent science arose in the middle of the 20th century, but scientific interest in information and research in this area appeared earlier.

At the beginning of the twentieth century, technical means of communication (telephone, telegraph, radio) were actively developing.
In this regard, the scientific direction "Theory of communication" appears. Its development gave rise to coding theory and information theory, the founder of which was the American scientist C. Shannon. Information theory solved the problem measurements information transmitted over communication channels. There are two approaches to measuring information: meaningful and alphabetical.

The most important task posed by the theory of communication is the fight against the loss of information in data transmission channels. In the course of solving this problem, a theory was formed coding , within which methods of presenting information were invented that made it possible to convey the content of the message to the addressee without distortion, even in the presence of losses in the transmitted code. These scientific results are of great importance even today, when the volume of information flows in technical communication channels has grown by many orders of magnitude.

The forerunner of modern computer science was the science of "Cybernetics", founded by the works of N. Wiener in the late 1940s - early 50s. In cybernetics there was a deepening of the concept of information, the place of information in control systems in living organisms, in social and technical systems was determined. Cybernetics explored the principles of program control. Arising simultaneously with the advent of the first computers, cybernetics laid the scientific foundations both for their constructive development and for numerous applications.

EVM (computer) - automatic device designed to solve information problems by implementing information processes : storage, processing and transmission of information. Description of the basic principles and patterns of information processes also refers to the theoretical foundations of informatics.

The computer does not work with the content of information that only a person can perceive, but with data representing information. Therefore, the most important task for computer technology is presentation of information in the form of data suitable for their processing. Data and programs are encoded in binary form. The processing of any type of data in a computer is reduced to calculations with binary numbers. That is why computer technology is also called digital. The concept of number systems, about representation of numbers in the computer belong to the basic concepts of computer science.

The concept of "language" comes from linguistics. Language - it a system of symbolic representation of information used for its storage and transmission. The concept of language is one of basic concepts computer science, since both data and programs in a computer are represented as symbolic structures. The language of communication between a computer and a person is increasingly approaching the forms of natural language.

TO fundamentals computer science refers to the theory of algorithms. concept algorithm introduced in the article “Information processing”. This topic is covered in detail in the fifth section of the encyclopedia.

1. Information measurement. Alphabetical approach

The alphabetical approach is used to measure amount of information in a text represented as a sequence of characters of some alphabet. This approach is not related to the content of the text. The amount of information in this case is called information volume of the text, which is proportional to the size of the text - the number of characters that make up the text. Sometimes this approach to measuring information is called the volumetric approach.

Each character of the text carries a certain amount of information. He is called symbol information weight. Therefore, the information volume of the text is equal to the sum of the information weights of all characters that make up the text.

Here it is assumed that the text is a consecutive string of numbered characters. In formula (1) i 1 denotes the informational weight of the first character of the text, i 2 - the informational weight of the second character of the text, etc.; K- text size, i.e. the total number of characters in the text.

The whole set of different characters used to write texts is called alphabetically. The size of the alphabet is an integer called the power of the alphabet. It should be borne in mind that the alphabet includes not only the letters of a certain language, but all other characters that can be used in the text: numbers, punctuation marks, various brackets, spaces, etc.

Determining the information weights of symbols can occur in two approximations:

1) under the assumption of equal probability (same frequency of occurrence) of any character in the text;

2) taking into account the different probability (different frequency of occurrence) of various characters in the text.

If we assume that all characters of the alphabet in any text appear with the same frequency, then the information weight of all characters will be the same. Let N- power of the alphabet. Then the proportion of any character in the text is 1/ N th part of the text. According to the definition of probability (cf. “Measurement of information. Content approach”) this value is equal to the probability of the occurrence of a character in each position of the text:

According to the formula of K. Shannon (see. “Measurement of information. Content approach”), the amount of information a symbol carries is calculated as follows:

i = log2(1/ p) = log2 N(bit) (2)

Therefore, the informational weight of the symbol ( i) and the cardinality of the alphabet ( N) are interconnected by the Hartley formula (see “ Measurement of information. Content approach” )

2 i = N.

Knowing the informational weight of one character ( i) and the size of the text, expressed as the number of characters ( K), you can calculate the information volume of the text using the formula:

I= K · i (3)

This formula is a particular version of formula (1), in the case when all symbols have the same information weight.

From formula (2) it follows that at N= 2 (binary alphabet) the information weight of one character is 1 bit.

From the standpoint of the alphabetical approach to measuring information 1 bit -is the informational weight of a character from the binary alphabet.

A larger unit of information is byte.

1 byte -is the information weight of a character from an alphabet with a power of 256.

Since 256 \u003d 2 8, then the connection between a bit and a byte follows from the Hartley formula:

2 i = 256 = 2 8

From here: i= 8 bits = 1 byte

To represent texts stored and processed in a computer, an alphabet with a capacity of 256 characters is most often used. Hence,
1 character of such text "weighs" 1 byte.

In addition to the bit and byte, larger units are also used to measure information:

1 KB (kilobyte) = 2 10 bytes = 1024 bytes,

1 MB (megabyte) = 2 10 KB = 1024 KB,

1 GB (gigabyte) = 2 10 MB = 1024 MB.

Approximation of different probability of occurrence of characters in the text

This approximation takes into account that in a real text different characters occur with different frequencies. It follows that the probabilities of the appearance of different characters in a certain position of the text are different and, therefore, their information weights are different.

Statistical analysis of Russian texts shows that the frequency of the letter “o” is 0.09. This means that for every 100 characters, the letter “o” occurs on average 9 times. The same number indicates the probability of the letter “o” appearing in a certain position of the text: p o = 0.09. It follows that the information weight of the letter “o” in the Russian text is equal to:

The rarest letter in the texts is the letter “f”. Its frequency is 0.002. From here:

A qualitative conclusion follows from this: the information weight of rare letters is greater than the weight of frequently occurring letters.

How to calculate the information volume of the text, taking into account the different information weights of the symbols of the alphabet? This is done according to the following formula:

Here N- size (power) of the alphabet; nj- number of repetitions of character number j in the text; i j- information weight of symbol number j.

Alphabetical approach in the computer science course at the foundation of the school

In the course of informatics in the main school, students get acquainted with alphabetical approach to the measurement of information most often occurs in the context of computer representation of information. The main statement goes like this:

The amount of information is measured by the size of the binary code with which this information is represented.

Since any kind of information is represented in computer memory in the form of a binary code, this definition is universal. It is valid for symbolic, numerical, graphic and sound information.

One character ( discharge)binary code carries 1bit of information.

When explaining the method of measuring the information volume of a text in the basic informatics course, this issue is revealed through the following sequence of concepts: alphabet-character binary code size-information volume of the text.

The logic of reasoning unfolds from particular examples to obtaining a general rule. Let there be only 4 characters in the alphabet of some language. Let's denote them:, , , . These symbols can be encoded using four two-digit binary codes: - 00, - 01, - 10, - 11. Here, all placement options of two characters by two, the number of which is 2 2 = 4, are used. A 4-character alphabet is equal to two bits.

The next special case is an 8-character alphabet, each character of which can be encoded with a 3-bit binary code, since the number of placements of two characters in groups of 3 is 2 3 = 8. Therefore, the information weight of a character from an 8-character alphabet is 3 bits. Etc.

Generalizing particular examples, we obtain a general rule: using b- bit binary code, you can encode an alphabet consisting of N = 2 b- symbols.

Example 1. To write the text, only lowercase letters of the Russian alphabet are used and a “space” is used to separate words. What is the information volume of a text consisting of 2000 characters (one printed page)?

Solution. There are 33 letters in the Russian alphabet. Reducing it by two letters (for example, “ё” and “й”) and entering a space character, we get a very convenient number of characters - 32. Using the approximation of equal probability of characters, we write the Hartley formula:

2i= 32 = 2 5

From here: i= 5 bits - informational weight of each character of the Russian alphabet. Then the information volume of the entire text is equal to:

I = 2000 5 = 10,000 bit

Example 2. Calculate the information volume of a text with a size of 2000 characters, in the record of which the alphabet of computer representation of texts with a capacity of 256 is used.

Solution. In this alphabet, the information weight of each character is 1 byte (8 bits). Therefore, the information volume of the text is 2000 bytes.

In practical tasks on this topic, it is important to develop the skills of students in converting the amount of information into different units: bits - bytes - kilobytes - megabytes - gigabytes. If we recalculate the information volume of the text from example 2 into kilobytes, we get:

2000 bytes = 2000/1024 1.9531 KB

Example 3. The volume of a message containing 2048 characters was 1/512 of a megabyte. What is the size of the alphabet with which the message is written?

Solution. Let's translate the information volume of the message from megabytes to bits. To do this, we multiply this value twice by 1024 (we get bytes) and once by 8:

I = 1/512 1024 1024 8 = 16384 bits.

Since this amount of information is carried by 1024 characters ( TO), then one character accounts for:

i = I/K= 16 384/1024 = 16 bits.

It follows that the size (power) of the used alphabet is 2 16 = 65 536 characters.

Volumetric approach in the course of computer science in high school

Studying computer science in grades 10–11 at the basic general education level, students can leave their knowledge of the volumetric approach to measuring information at the same level as described above, i.e. in the context of the amount of binary computer code.

When studying computer science at the profile level, the volumetric approach should be considered from more general mathematical positions, using ideas about the frequency of characters in a text, about probabilities and the relationship of probabilities with the information weights of symbols.

Knowledge of these issues is important for a deeper understanding of the difference in the use of uniform and non-uniform binary coding (see. “Information Encoding”), to understand some data compression techniques (see. “Data Compression”) and cryptographic algorithms (see "Cryptography" ).

Example 4. In the alphabet of the MUMU tribe, there are only 4 letters (A, U, M, K), one punctuation mark (dot) and a space is used to separate words. It was calculated that the popular novel "Mumuka" contains only 10,000 characters, of which: letters A - 4000, letters U - 1000, letters M - 2000, letters K - 1500, dots - 500, spaces - 1000. How much information contains book?

Solution. Since the volume of the book is quite large, it can be assumed that the frequency of occurrence in the text of each of the symbols of the alphabet calculated from it is typical for any text in the MUMU language. Let's calculate the frequency of occurrence of each character in the entire text of the book (i.e. probability) and the information weights of the characters

The total amount of information in the book is calculated as the sum of the products of the information weight of each symbol by the number of repetitions of this symbol in the book:

1) a person receives a message about some event; while it is known in advance uncertainty of knowledge person about the expected event. The uncertainty of knowledge can be expressed either by the number of possible variants of the event, or by the probability of the expected variants of the event;

2) as a result of receiving the message, the uncertainty of knowledge is removed: from a certain possible number of options, one was chosen;

3) the formula calculates the amount of information in the received message, expressed in bits.

The formula used to calculate the amount of information depends on situations, which can be two:

1. All possible variants of the event are equally probable. Their number is finite and equal N.

2. Probabilities ( p) possible variants of the event are different and they are known in advance:

(p i ), i = 1.. N. Here is still N- the number of possible variants of the event.

Incredible events. If denoted by i the amount of information in the message that one of the N equiprobable events, then the quantities i and N are interconnected by the Hartley formula:

2i=N (1)

Value i measured in bits. From this follows the conclusion:

1 bit is the amount of information in the message about one of two equally probable events.

Hartley's formula is an exponential equation. If i is an unknown quantity, then the solution of equation (1) will be:

i = log 2 N (2)

Formulas (1) and (2) are identical to each other. Sometimes in the literature the Hartley formula is called (2).

Example 1. How much information does the message contain that the queen of spades was taken from a deck of cards?

There are 32 cards in a deck. In a shuffled deck, the loss of any card is an equiprobable event. If i- the amount of information in the message that a particular card has fallen (for example, the queen of spades), then from the Hartley equation:

2 i = 32 = 2 5

From here: i= 5 bits.

Example 2. How much information does the message contain about the roll of a face with the number 3 on a six-sided dice?

Considering the loss of any face as an equally probable event, we write the Hartley formula: 2 i= 6. Hence: i= log 2 6 = 2.58496 bit.

Disprobable events (probabilistic approach)

If the probability of some event is p, a i(bit) is the amount of information in the message that this event has occurred, then these values ​​\u200b\u200bare related by the formula:

2 i = 1/p (3)

Solving the exponential equation (3) with respect to i, we get:

i = log 2 (1/ p) (4)

Formula (4) was proposed by K. Shannon, therefore it is called the Shannon formula.

The discussion of the relationship between the amount of information in a message and its content can take place at different levels of depth.

Qualitative approach

Qualitative approach, which can be used at the level of propaedeutics of the basic computer science course (grades 5–7) or in the basic course (grades 8–9).

At this level of study, the following chain of concepts is discussed: information - message - informativeness of the message.

original package: information- this is the knowledge of people received by them from various messages. The next question is: what is a message? Message- this is an information flow (data flow), which, in the process of transmitting information, comes to the subject receiving it. The message is both the speech we are listening to (a radio message, a teacher's explanation), and the visual images we perceive (a movie on TV, a traffic light), and the text of the book we are reading, etc.

question about informative message I should discuss the examples offered by the teacher and students. Rule: informativelet's callmessage, which replenishes human knowledge, i.e. carries information for him. For different people, the same message in terms of its informativeness can be different. If the information is “old”, i.e. a person already knows this, or the content of the message is not clear to a person, then this message is not informative for him. Informative is the message that contains new and understandable intelligence.

Examples of non-informative messages for an 8th grade student:

1) “The capital of France - Paris” (not new);

2) “Colloid chemistry studies the dispersion states of systems with a high degree of fragmentation” (not clear).

An example of an informative message (for those who did not know this): “The Eiffel Tower has a height of 300 meters and a weight of 9000 tons.”

The introduction of the concept of “informativeness of a message” is the first approach to studying the issue of measuring information within the content concept. If the message is not informative for a person, then the amount of information in it, from the point of view of this person, is equal to zero. The amount of information in the informative message is greater than zero.

Quantitative approach in the equiprobability approximation

This approach can be studied either in the advanced version of the basic course at the basic school, or when studying computer science in grades 10–11 at the basic level.

The following chain of concepts is considered: equiprobable events - knowledge uncertainty - bit as a unit of information - Hartley's formula - solution of the exponential equation for N equal to integer powers of two.

Revealing the concept equiprobability, one should build on the intuitive representation of children, backing it up with examples. Events are equally likelyif none of them has an advantage over the others.

Having introduced the particular definition of a bit that was given above, it should then be generalized:

A message that reduces the uncertainty of knowledge by a factor of 2 carries 1 bitinformation.

This definition is supported by examples of messages about one event out of four (2 bits), out of eight (3 bits), and so on.

At this level, you can not discuss options for values N, not equal to integer powers of two, so as not to encounter the problem of calculating logarithms, which have not yet been studied in the course of mathematics. If children have questions, for example: “How much information does the message carry about the result of throwing a six-sided die,” then the explanation can be built as follows. From Hartley's equation: 2 i= 6. Since 2 2< 6 < 2 3 , следовательно, 2 < i < 3. Затем сообщить более точное значение (с точностью до пяти знаков после запятой), что i= 2.58496 bits. Note that with this approach, the amount of information can be expressed as a fractional value.

Probabilistic approach to measuring information

It can be studied in grades 10–11 as part of a general education course at a profile level or in an elective course on the mathematical foundations of computer science. A mathematically correct definition of probability must be introduced here. In addition, students should know the logarithm function and its properties, be able to solve exponential equations.

Introducing the concept of probability, it should be reported that the probability of an event is a value that can take values ​​from zero to one. The probability of an impossible event is zero(for example: “tomorrow the sun will not rise above the horizon”), the probability of a certain event is equal to one(for example: “Tomorrow the sun will rise over the horizon”).

The following provision: the probability of some event is determined by multiple observations (measurements, tests). Such measurements are called statistical. And the more measurements are made, the more accurately the probability of an event is determined.

The mathematical definition of probability is: probabilityis equal to the ratio of the number of outcomes that favor this event to the total number of equally possible outcomes.

Example 3. Two bus routes stop at a bus stop: No. 5 and No. 7. The student is given the task: to determine how much information is contained in the message that bus No. 5 has approached the stop, and how much information is in the message that bus No. 5 has approached 7.

The student did the research. During the entire working day, he calculated that the buses approached the bus stop 100 times. Of these, bus number 5 approached 25 times and bus number 7 approached 75 times. Assuming that buses run with the same frequency on other days, the student calculated the probability of bus number 5 at the stop: p 5 = 25/100 = 1/4, and the probability of bus #7 spawning is: p 7 = 75/100 = 3/4.

Hence, the amount of information in the message about bus number 5 is: i 5 = log 2 4 = 2 bits. The amount of information in the message about bus number 7 is:

i 7 \u003d log 2 (4/3) \u003d log 2 4 - log 2 3 \u003d 2 - 1.58496 \u003d 0.41504 bit.

Notice the following qualitative output: the lower the probability of an event, the greater the amount of information in the message about it. The amount of information about a certain event is zero. For example, the message “Tomorrow morning will come” is reliable and its probability is equal to one. From formula (3) it follows: 2 i= 1/1 = 1. Hence, i= 0 bit.

Hartley's formula (1) is a special case of formula (3). If available N equally probable events (the result of throwing a coin, a dice, etc.), then the probability of each possible variant is equal to p = 1/N. Substituting into (3), we again obtain the Hartley formula: 2 i = N. If in example 3 buses #5 and #7 would come to a stop 100 times each 50 times, then the probability of each of them appearing would be equal to 1/2. Therefore, the amount of information in the message about the arrival of each bus is i= log 2 2 = 1 bit. We came to the well-known variant of information content of the message about one of two equally probable events.

Example 4. Consider another version of the bus problem. Buses No. 5 and No. 7 stop at the stop. The message that bus No. 5 has approached the stop carries 4 bits of information. The probability of bus number 7 appearing at the stop is two times less than the probability of bus number 5 appearing. How many bits of information does the message about bus number 7 appearing at the stop carry?

We write the condition of the problem in the following form:

i 5 = 4 bits, p 5 = 2 p 7

Recall the relationship between probability and amount of information: 2 i = 1/p

From here: p = 2 –i

Substituting into equality from the condition of the problem, we get:

The conclusion follows from the result obtained: a decrease in the probability of an event by 2 times increases the information content of the message about it by 1 bit. The opposite rule is also obvious: an increase in the probability of an event by 2 times reduces the information content of the message about it by 1 bit. Knowing these rules, the previous problem could be solved “in the mind”.

The subject of study of the science of informatics is information and information processes. As there is no single generally accepted definition of information (cf. "Information"), there is also no unity in the interpretation of the concept of “information processes”.

Let's approach the understanding of this concept from a terminological position. Word process stands for some event occurring in time: litigation, production process, educational process, living organism growth process, oil refining process, fuel combustion process, spacecraft flight process, etc. Every process is associated with some actions performed by man, the forces of nature, technical devices, as well as due to their interaction.

Every process has object of influence Keywords: defendant, students, oil, fuel, spaceship. If the process is associated with the purposeful activity of a person, then such a person can be called process executor: judge, teacher, astronaut. If the process is carried out with the help of an automatic device, then it is the executor of the process: a chemical reactor, an automatic space station.

Obviously, in information processes the object of influence is information. In the textbook S.A. Beshenkova, E.A. Rakitina gives the following definition: “In the most general form, the information process is defined as a set of sequential actions (operations) performed on information (in the form of data, information, facts, ideas, hypotheses, theories, etc.) to obtain any result (achievements). goals)".

Further analysis of the concept of “information processes” depends on the approach to the concept of information, on the answer to the question: “What is information?”. If accept attributive point of view on information (cf. "Information"), then it should be recognized that information processes occur both in living and inanimate nature. For example, as a result of physical interaction between the Earth and the Sun, between electrons and the nucleus of an atom, between the ocean and the atmosphere. From the position functional concept information processes occur in living organisms (plants, animals) and in their interaction.

WITH anthropocentric point of view, the executor of information processes is a person. Information processes are a function of human consciousness (thinking, intellect). A person can carry them out independently, as well as with the help of tools of information activity created by him.

Any, arbitrarily complex information activity of a person is reduced to three main types of actions with information: storage, reception / transmission, processing. Usually, instead of “reception-transmission”, they simply say “transmission”, understanding this process as a two-way one: transmission from source to receiver (synonymous with “transportation”).

Storage, transmission and processing of information are the main types of information processes.

The implementation of these actions with information is associated with its presentation in the form of data. All kinds of tools of human information activity (for example: paper and pen, technical communication channels, computing devices, etc.) are used for storage, processing and transmission data.

If we analyze the activities of any organization (the personnel department of an enterprise, accounting, a scientific laboratory) that works with information “in the old fashioned way”, without the use of computers, then three types of means are required to ensure its activities:

Paper and writing instruments (pens, typewriters, drawing instruments) for fixing information for the purpose of storage;

Communication facilities (couriers, telephones, mail) for receiving and transmitting information;

Computing tools(abacus, calculators) for information processing.

Nowadays, all these types of information activities are carried out using computer technology: data is stored on digital media, transmission takes place using e-mail and other computer network services, calculations and other types of processing are performed on a computer.

The composition of the main devices of a computer is determined precisely by the fact that the computer is designed to carry out storage, processing and data transmission. To do this, it includes memory, processor, internal channels and external input / output devices (see. "Computer").

In order to terminologically separate the processes of working with information that occur in the human mind, and the processes of working with data that occur in computer systems, A.Ya. Friedland suggests calling them differently: the first - information processes, the second - information processes.

Another approach to the interpretation of information processes is offered by cybernetics. Information processes occur in various control systems that take place in wildlife, in the human body, in social systems, in technical systems ah (including in the computer). For example, the cybernetic approach is applied in neurophysiology (cf. "Information"), where the management of physiological processes in the body of an animal and a person, occurring at an unconscious level, is considered as an information process. In neurons (brain cells) stored and processed information is carried along the nerve fibers broadcast information in the form of signals of an electrochemical nature. Genetics has established that hereditary information stored in the DNA molecules that make up the nuclei of living cells. It determines the program for the development of the organism (i.e. controls this process), which is realized at an unconscious level.

Thus, in the cybernetic interpretation, information processes are reduced to the storage, transmission and processing of information presented in the form of signals, codes of various nature.

At any stage of studying informatics at school, ideas about information processes carry a systematizing methodological function. By studying the device of a computer, students should get a clear understanding of what devices are used to store, process and transfer data. When studying programming, students should pay attention to the fact that the program works with data stored in the computer's memory (like the program itself), that the program instructions determine the actions of the processor for processing data and the action of input-output devices for receiving and transmitting data. Mastering information technologies, one should pay attention to the fact that these technologies are also focused on the storage, processing and transmission of information.

See articles “ Data storage”, “Data processing”, “Transfer of information” 2.

The word "information" comes from the Latin information, which translates as clarification, presentation. V explanatory dictionary IN AND. Dahl does not have the word “information”. The term "information" came into use in Russian speech from the middle of the twentieth century.

To the greatest extent, the concept of information owes its spread to two scientific areas: communication theory and cybernetics. The result of the development of communication theory was information theory founded by Claude Shannon. However, K. Shannon did not give a definition of information, at the same time, defining amount of information. Information theory is devoted to solving the problem of measuring information.

In science cybernetics founded by Norbert Wiener, the concept of information is central (cf. "Cybernetics" 2). It is generally accepted that it was N. Wiener who introduced the concept of information into scientific use. Nevertheless, in his first book on cybernetics, N. Wiener does not define information. “ Information is information, not matter or energy”, wrote Wiener. Thus, the concept of information, on the one hand, is opposed to the concepts of matter and energy, on the other hand, it is put on a par with these concepts in terms of their degree of generality and fundamentality. Hence, at least it is clear that information is something that cannot be attributed to either matter or energy.

The science of philosophy deals with understanding information as a fundamental concept. According to one of the philosophical concepts, information is a property of everything, all material objects of the world. This concept of information is called attributive (information is an attribute of all material objects). Information in the world arose together with the Universe. In this sense information is a measure of orderliness, structuredness of any material system. The processes of development of the world from the initial chaos that occurred after the "Big Bang" to the formation of inorganic systems, then organic (living) systems are associated with an increase information content. This content is objective, independent of human consciousness. A piece of coal contains information about events that took place in ancient times. However, only an inquisitive mind can extract this information.

Another philosophical concept of information is called functional. According to the functional approach, information appeared with the emergence of life, as it is associated with the functioning of complex self-organizing systems, which include living organisms and human society. You can also say this: information is an attribute inherent only to living nature. This is one of the essential features that separate the living from the non-living in nature.

The third philosophical concept of information is anthropocentric, according to which information exists only in human consciousness, in human perception. Information activity is inherent only to man, occurs in social systems. By creating information technology, a person creates tools for his information activity.

We can say that the use of the concept of "information" in everyday life occurs in an anthropocentric context. It is natural for any of us to perceive information as messages exchanged between people. For example, mass media - mass media are designed to disseminate messages, news among the population.

In the 20th century, the concept of information permeates science everywhere. Information processes in living nature are studied by biology. Neurophysiology (section of biology) studies the mechanisms of the nervous activity of animals and humans. This science builds a model of information processes occurring in the body. The information coming from the outside is converted into signals of an electrochemical nature, which are transmitted from the sense organs along the nerve fibers to the neurons (nerve cells) of the brain. The brain transmits control information in the form of signals of the same nature to muscle tissues, thus controlling the organs of movement. The described mechanism is in good agreement with the cybernetic model of N. Wiener (see. "Cybernetics" 2).

In another biological science - genetics, the concept of hereditary information embedded in the structure of DNA molecules present in the nuclei of cells of living organisms (plants, animals) is used. Genetics has proven that this structure is a kind of code that determines the functioning of the whole organism: its growth, development, pathologies, etc. Through DNA molecules, hereditary information is transmitted from generation to generation.

Studying informatics at the basic school (basic course), one should not delve into the complexity of the problem of determining information. The concept of information is given in a meaningful context:

Information - this is the meaning, the content of messages received by a person from outside world through his senses.

The concept of information is revealed through the chain:

message - meaning - information - knowledge

A person perceives messages with the help of his senses (mostly through sight and hearing). If a person understands meaning enclosed in a message, then we can say that this message carries a person information. For example, a message in an unfamiliar language does not contain information for a given person, but a message in a native language is understandable, therefore informative. Information perceived and stored in memory replenishes knowledge person. Our knowledge- this is a systematized (related) information in our memory.

When revealing the concept of information from the point of view of a meaningful approach, one should start from the intuitive ideas about information that children have. It is advisable to conduct a conversation in the form of a dialogue, asking students questions that they are able to answer. Questions, for example, can be asked in the following order.

Tell us where you get your information from?

You will probably hear back:

From books, radio and TV shows .

In the morning I heard the weather forecast on the radio .

Seizing on this answer, the teacher leads the students to the final conclusion:

So, at first you did not know what the weather would be like, but after listening to the radio, you began to know. Therefore, having received information, you received new knowledge!

Thus, the teacher, together with the students, comes to the definition: informationfor a person, this is information that supplements a person’s knowledge, which he receives from various sources. Further, on numerous examples familiar to children, this definition should be fixed.

Having established a connection between information and people's knowledge, one inevitably comes to the conclusion that information is the content of our memory, because human memory is the means of storing knowledge. It is reasonable to call such information internal, operational information that a person possesses. However, people store information not only in their own memory, but also in records on paper, on magnetic media, etc. Such information can be called external (in relation to a person). In order for a person to use it (for example, to prepare a dish according to a recipe), he must first read it, i.e. turn it into an internal form, and then perform some actions.

The question of the classification of knowledge (and therefore information) is very complex. In science, there are different approaches to it. Specialists in the field of artificial intelligence are especially engaged in this issue. Within the framework of the basic course, it is enough to confine ourselves to dividing knowledge into declarative and procedural. The description of declarative knowledge can be started with the words: “I know that…”. Description of procedural knowledge - with the words: "I know how ...". It is easy to give examples for both types of knowledge and invite children to come up with their own examples.

The teacher should be well aware of the propaedeutic significance of discussing these issues for the future acquaintance of students with the device and operation of the computer. A computer, like a person, has an internal - operational - memory and an external - long-term - memory. The division of knowledge into declarative and procedural in the future can be linked with the division of computer information into data - declarative information and programs - procedural information. Using the didactic analogy between the information function of a person and a computer will allow students to better understand the essence of the design and operation of a computer.

Based on the position “human knowledge is stored information”, the teacher informs students that smells, tastes, and tactile (tactile) sensations also carry information to a person. The rationale for this is very simple: since we remember familiar smells and tastes, we recognize familiar objects by touch, then these sensations are stored in our memory, and therefore, they are information. Hence the conclusion: with the help of all his senses, a person receives information from the outside world.

Both from a substantive and methodological point of view, it is very important to distinguish between the meaning of the concepts “ information" and " data”. To the representation of information in any sign system(including those used in computers) term should be used “data". A information- it the meaning contained in the data, embedded in them by a person and understandable only to a person.

A computer works with data: it receives input data, processes it, and transmits output data to a person - results. The semantic interpretation of the data is carried out by a person. Nevertheless, in colloquial speech, in the literature, they often say and write that a computer stores, processes, transmits and receives information. This is true if the computer is not separated from the person, considering it as a tool with which a person carries out information processes.

The word “cybernetics” is of Greek origin, literally meaning the art of control.

In the IV century BC. in the writings of Plato, this term was used to denote management in a general sense. In the 19th century, A. Ampère suggested calling cybernetics the science of managing human society.

In a modern interpretation cybernetics- a science that studies the general laws of control and relationships in organized systems (machines, living organisms, in society).

The emergence of cybernetics as an independent science is associated with the publication of the books of the American scientist Norbert Wiener "Cybernetics, or Control and Communication in Animal and Machine" in 1948 and "Cybernetics and Society" in 1954.

The main scientific discovery of cybernetics was the justification unity of control laws in natural and artificial systems. N. Wiener came to this conclusion by building an information model of management processes.

Norbert Wiener (1894–1964), USA

A similar scheme was known in the theory of automatic control. Wiener generalized it to all types of systems, abstracting from specific communication mechanisms, considering this connection as informational.

Feedback control scheme

The direct communication channel transmits control information - control commands. The feedback channel transmits information about the state of the controlled object, about its response to the control action, as well as about the state of the external environment, which is often a significant factor in management.

Cybernetics develops the concept of information as the content of signals transmitted through communication channels. Cybernetics develops the concept of an algorithm as control information that a control object must have in order to perform its work.

The emergence of cybernetics occurs simultaneously with the creation of electronic computers. The connection between computers and cybernetics is so close that these concepts were often identified in the 1950s. Computers were called cybernetic machines.

The connection between computers and cybernetics exists in two aspects. Firstly, a computer is a self-governing automaton in which the control device, which is part of the processor, plays the role of a manager, and all other devices are control objects. Direct and feedback communication is carried out through information channels, and the algorithm is presented in the form of a program in machine language (a language “understandable” by the processor) stored in the computer memory.

Secondly, with the invention of the computer, the prospect of using the machine as a control object in a variety of systems opened up. It becomes possible to create complex systems with program control, to transfer many types of human activity to automatic devices.

The development of the line "cybernetics - computers" led in the 1960s to the emergence of science informatics with a more developed system of concepts related to the study of information and information processes.

At present, the general provisions of theoretical cybernetics are acquiring a philosophical meaning to a greater extent. At the same time, applied areas of cybernetics are actively developing, related to the study and creation of control systems in various subject areas: technical cybernetics, biomedical cybernetics, economic cybernetics. With the development of computer learning systems, we can talk about the emergence of pedagogical cybernetics.

There are various ways to include questions of cybernetics in the general education course. One way is through the line of algorithmization. Algorithm regarded as control information in the cybernetic model of the control system. In this context, the theme of cybernetics is revealed.

Another way is to include the topic of cybernetics in the meaningful line of modeling. By revising management process as a complex information process gives an idea of N. Wiener's scheme how models of such a process. In the version of the educational standard for the basic school (2004), this topic is present in the context of modeling: “cybernetic model of management processes”.

In the work of A.A. Kuznetsova, S.A. Beshenkova et al. “Continuous informatics course” named three main areas of the school informatics course: information modeling , information processes and information bases of management. Content lines are the detailing of the main directions. Thus, the cybernetic theme - the theme of management, is given even more weighty importance than the content line. This is a multifaceted topic that allows you to touch on the following issues:

Elements of theoretical cybernetics: cybernetic model of feedback control;

Elements of applied cybernetics: structure of computer systems of automatic control (systems with program control); appointment of automated control systems;

Fundamentals of the theory of algorithms.

Elements of theoretical cybernetics

Talking about the cybernetic control model, the teacher should illustrate it with examples that are familiar and understandable to students. In this case, the main elements of the cybernetic control system should be highlighted: control object, managed object, direct and feedback channels.

Let's start with obvious examples. For example, a driver and a car. The driver is the manager, the car is the controlled object. Direct communication channel - car control system: pedals, steering wheel, levers, keys, etc. Feedback channels: instruments on the control panel, view from windows, driver's hearing. Any action on the controls can be considered as transmitted information: “increase speed”, “slow down”, “turn right”, etc. Information transmitted through feedback channels is also necessary for successful management. Offer students a task: what happens if one of the direct or feedback channels is turned off? The discussion of such situations is usually very lively.

Feedback control is called adaptive control. The manager's actions are adapted (i.e. adjusted) to the state of the control object, the environment.

The closest example to students of management in a social system: a teacher who manages the learning process in the classroom. Discuss various forms of the teacher's control over students: speech, gestures, facial expressions, notes on the blackboard. Have students list different forms of feedback; explain how the teacher adapts the course of the lesson based on the results of feedback, give examples of such adaptation. For example, the students did not cope with the proposed task - the teacher is forced to repeat the explanation.

When studying this topic in high school, one can consider the ways of management in large social systems: management of an enterprise by the administration, management of the country by state bodies, etc. Here it is useful to use material from the course of social studies. When analyzing the mechanisms of feed-forward and feedback in such systems, draw students' attention to the fact that in most cases there are many channels of feed-forward and feedback. They are duplicated in order to increase the reliability of the control system.

Algorithms and control

This topic allows you to reveal the concept of an algorithm from a cybernetic point of view. The expansion logic is as follows. Management is a purposeful process. It must provide a certain behavior of the control object, the achievement of a certain goal. And for that, there must be a management plan. This plan is implemented through a sequence of control commands transmitted over a direct link. Such a sequence of commands is called a control algorithm.

Control algorithm is an information component control systems. For example, a teacher teaches a lesson according to a predetermined plan. The driver drives the car along a predetermined route.

In control systems, where the role of the manager is performed by a person, the control algorithm can change, be refined in the process of work. The driver cannot plan in advance each of his actions while driving; The teacher adjusts the lesson plan as it goes. If the process is controlled by an automatic device, then a detailed control algorithm must be embedded in it in advance in some formalized form. In that case it is called management program. To store the program, the automatic control device must have program memory.

This topic should explore the concept self-managed system. This is a single object, an organism, in which all the components of control systems noted above are present: control and controlled parts (organs), direct and feedback information, control information - algorithms, programs and memory for storing it. Such systems are living organisms. The most perfect of them is man. Man controls himself. The main control organ is the human brain, controlled - all parts of the body. There is conscious management(I do what I want) and eat subconscious(management of physiological processes). Similar processes occur in animals. However, the proportion of conscious control in animals is less than in humans due to a higher level of human intellectual development.

The creation of artificial self-governing systems is one of the most difficult tasks of science and technology. Robotics is an example of such a scientific and technical direction. It combines many areas of science: cybernetics, artificial intelligence, medicine, mathematical modeling, etc.

Elements of Applied Cybernetics

This topic can be disclosed either in an in-depth version of the study of the basic course of computer science, or at the profile level in high school.

To tasks technical cybernetics includes the development and creation of technical control systems at manufacturing enterprises, in research laboratories, in transport, etc. Such systems are called systems with automatic control - ACS . Computers or specialized controllers are used as a control device in the ACS.

The cybernetic control model in relation to the ACS is shown in the figure.

Scheme of the automatic control system

This is a closed technical system that works without human intervention. The person (programmer) prepared management program, brought it into the computer's memory. Then the system works automatically.

Considering this issue, students should pay attention to the fact that they have already met with the conversion of information from analog to digital and vice versa (DAC - ADC conversion) in other topics or will meet again. By the same principle, a modem works in computer networks, a sound card when inputting / outputting sound (see. “ Sound presentation” 2).In this system, an analog electrical signal passing through the feedback channel from the sensors of the controlled device via analog-to-digital converter(ADC), turns into discrete digital data, entering the computer. Works on a direct line DAC - digital-to-analog converter, which the performs reverse conversion - digital data coming from the computer into an analog electrical signal supplied to the input nodes of the controlled device.

Another direction of applied cybernetics: automated control systems (ACS). ACS is a human-machine system. As a rule, automated control systems are focused on managing the activities of production teams and enterprises. These are systems of computer collection, storage, processing of various information necessary for the operation of the enterprise. For example, data on financial flows, availability of raw materials, volumes of finished products, personnel information, etc. etc. The main purpose of such systems is to quickly and accurately provide the managers of the enterprise with the necessary information for making management decisions.

The tasks solved by means of automated control systems belong to the area economic cybernetics. As a rule, the technical basis of such systems are local computer networks. ACS uses a variety of information technologies: databases, computer graphics, computer modeling, expert systems, etc.

The code -a system of conventional signs (symbols) for the transmission, processing and storage of information (messages).

Coding - the process of presenting information (messages) in the form of a code.

The whole set of characters used for encoding is called coding alphabet. For example, in the memory of a computer, any information is encoded using a binary alphabet containing only two characters: 0 and 1.

The scientific foundations of coding were described by K. Shannon, who studied the processes of information transmission over technical channels connections ( communication theory, coding theory). With this approach coding understood in a narrower sense: transition from representing information in one symbol system to representing it in another symbol system. For example, converting a written Russian text into Morse code for transmission by telegraph or radio. Such coding is connected with the need to adapt the code to the technical means of working with information used (see “ Transfer of information” 2).

Decoding - the process of converting code back to the form of the original character system, i.e. get the original message. For example: translation from Morse code into a written text in Russian.

More broadly, decoding is the process of recovering the content of an encoded message. With this approach, the process of writing text using the Russian alphabet can be considered as encoding, and reading it is decoding.

The encoding of the same message can be different. For example, we are used to writing Russian text using the Russian alphabet. But the same can be done using the English alphabet. Sometimes you have to do this by sending an SMS to a mobile phone that does not have Russian letters on it, or by sending email in Russian from abroad, if there is no Russified software on the computer. For example, the phrase: “Hello, dear Sasha!” I have to write like this: “Zdravstvui, dear Sasha!”.

There are other ways to encode speech. For instance, shorthand - quick way to record spoken language. It is owned by only a few specially trained people - stenographers. The stenographer manages to write down the text synchronously with the speech of the speaking person. In the transcript, one icon denoted a whole word or phrase. Only a stenographer can decipher (decode) a transcript.

The examples given illustrate the following important rule: different ways can be used to encode the same information; their choice depends on a number of factors: purpose of coding, conditions, available funds. If you need to write down the text at the pace of speech, we use shorthand; if it is necessary to transfer the text abroad - we use the English alphabet; if it is necessary to present the text in a form understandable for a literate Russian person, we write it down according to the rules of the grammar of the Russian language.

Another important circumstance: the choice of how information is encoded may be related to the intended way of processing it. Let's show it on an example of representation of numbers - the quantitative information. Using the Russian alphabet, you can write the number "thirty-five". Using the alphabet of the Arabic decimal number system, we write: “35”. The second method is not only shorter than the first, but also more convenient for performing calculations. Which entry is more convenient for performing calculations: “thirty-five times one hundred twenty-seven” or “35 x 127”? Obviously the second one.

However, if it is important to keep the number without distortion, then it is better to write it in text form. For example, in monetary documents, the amount is often written in text form: “three hundred and seventy-five rubles.” instead of "375 rubles". In the second case, the distortion of one digit will change the entire value. When using the text form, even grammatical errors may not change the meaning. For example, an illiterate person wrote: “Three hundred and seventy-five rubles.” However, the meaning has been preserved.

In some cases, there is a need to classify the text of a message or document so that it cannot be read by those who are not supposed to. It is called protection against unauthorized access. In this case, the secret text is encrypted. In ancient times, encryption was called cryptography. Encryption is the process of converting plaintext into ciphertext, and decryption- the process of inverse transformation, in which the original text is restored. Encryption is also coding, but with a secret method known only to the source and addressee. Encryption methods are dealt with by a science called cryptography(cm . "Cryptography" 2).

With the advent of technical means of storing and transmitting information, new ideas and coding techniques have arisen. The first technical means of transmitting information over a distance was the telegraph, invented in 1837 by the American Samuel Morse. A telegraph message is a sequence of electrical signals transmitted from one telegraph apparatus through wires to another telegraph apparatus. These technical circumstances led S. Morse to the idea of ​​using only two types of signals - short and long - to encode a message transmitted over telegraph lines.

Samuel Finley Breeze Morse (1791–1872), USA

This encoding method is called Morse code. In it, each letter of the alphabet is encoded by a sequence of short signals (dots) and long signals (dashes). The letters are separated from each other by pauses - the absence of signals.

The most famous telegraph message is the SOS distress signal ( S ave O ur S ouls- save our souls). Here's what it looks like in Morse code applied to the English alphabet:

–––

Three dots (letter S), three dashes (letter O), three dots (letter S). Two pauses separate the letters from each other.

The figure shows the Morse code in relation to the Russian alphabet. There were no special punctuation marks. They were written down with the words: “dot” - a dot, “spt” - a comma, etc.

A characteristic feature of Morse code is variable length code of different letters, so Morse code is called uneven code. Letters that occur more often in the text have a shorter code than rare letters. For example, the code for the letter “E” is one dot, and the code for a solid character consists of six characters. This is done in order to shorten the length of the entire message. But because of the variable length of the code of letters, there is a problem of separating letters from each other in the text. Therefore, it is necessary to use a pause (skip) for separation. Therefore, the Morse telegraph alphabet is ternary, since it uses three characters: dot, dash, space.

Uniform telegraph code was invented by the Frenchman Jean Maurice Baudot at the end of the 19th century. It used only two different types of signals. It doesn't matter what you call them: dot and dash, plus and minus, zero and one. These are two different electrical signals. The length of the code of all characters is the same and is equal to five. In this case, the problem of separating letters from each other does not arise: each five signals is a text sign. Therefore, a pass is not required.

Jean Maurice Emile Baudot (1845–1903), France

The Baudot code is the first method in the history of technology to encode information in binary.. Thanks to this idea, it was possible to create a direct-printing telegraph apparatus that looks like a typewriter. Pressing a key with a certain letter generates the corresponding five-pulse signal, which is transmitted over the communication line. The receiving machine, under the influence of this signal, prints the same letter on a paper tape.

Modern computers also use a uniform binary code to encode texts (see “ Text coding systems” 2).

The topic of information coding can be presented in the curriculum at all stages of studying computer science at school.

In a propaedeutic course, students are often offered tasks that are not related to computer data coding and are, in a sense, a game form. For example, on the basis of the Morse code code table, it is possible to propose both encoding tasks (encode Russian text using Morse code) and decoding tasks (decrypt text encoded using Morse code).

The execution of such tasks can be interpreted as the work of a cryptographer, offering various simple encryption keys. For example, alphanumeric, replacing each letter with its ordinal number in the alphabet. In addition, punctuation marks and other symbols should be added to the alphabet in order to fully encode the text. Have students come up with a way to distinguish between lowercase and uppercase letters.

When performing such tasks, students should pay attention to the fact that a separating character is required - a space, since the code turns out to be uneven: some letters are encrypted with one digit, some with two.

Invite students to think about how they can get by without separating letters in the code. These reflections should lead to the idea of ​​a uniform code, in which each character is encoded by two decimal digits: A - 01, B - 02, etc.

Collections of tasks for encoding and encrypting information are available in a number of textbooks for the school.

In the basic computer science course for the main school, the topic of coding is more associated with the topic of representing various types of data in a computer: numbers, texts, images, sounds (see “ Information Technology” 2).

In the upper grades, the content of a general education or elective course may deal in more detail with issues related to the coding theory developed by K. Shannon in the framework of information theory. There exists whole line interesting tasks, the understanding of which requires an increased level of mathematical and programming training of students. These are the problems of economical coding, universal coding algorithm, error correction coding. Many of these issues are discussed in detail in the textbook "Mathematical Foundations of Informatics".

7. Information processing

Data processing - the process of systematic change in the content or form of information presentation.

The processing of information is carried out in accordance with certain rules by some subject or object (for example, a person or automatic device). We will call him information processing executor.

The processing performer, interacting with the external environment, receives from it input information which is being processed. The result of processing is imprint transmitted to the external environment. Thus, the external environment acts as a source of input information and a consumer of output information.

Information processing occurs according to certain rules known to the performer. Processing rules, which are a description of the sequence of individual processing steps, are called the information processing algorithm.

The processing executor must include a processing unit, which we will call a processor, and a memory block in which both the processed information and the processing rules (algorithm) are stored. All of the above is shown schematically in the figure.

Information processing scheme

Example. The student, solving the problem in the lesson, carries out the processing of information. The external environment for him is the atmosphere of the lesson. The input information is the condition of the task, which is reported by the teacher leading the lesson. The student memorizes the condition of the problem. To facilitate memorization, he can use notes in a notebook - an external memory. From the teacher's explanation, he learned (remembered) the way to solve the problem. The processor is the mental apparatus of the student, using which to solve the problem, he receives an answer - output information.

The scheme shown in the figure is a general information processing scheme that does not depend on who (or what) is the processing executor: a living organism or a technical system. This is the scheme implemented technical means in computer. Therefore, we can say that a computer is a technical model of a “live” information processing system. It includes all the main components of the processing system: processor, memory, input devices, output devices (see “ Computer Device” 2).

Input information presented in symbolic form (characters, letters, numbers, signals) is called input data. As a result of processing by the performer, output. Input and output data can be a set of values ​​- individual data elements. If the processing consists in mathematical calculations, then the input and output data are sets of numbers. The following figure X: {x 1, x 2, …, xn) denotes the set of input data, and Y: {y 1, y 2, …, ym) - set of output data:

Data Processing Scheme

Processing is to transform the set X into the multitude Y:

P( X) Y

Here R denotes the processing rules used by the performer. If the executor of information processing is a person, then the processing rules according to which he acts are not always formal and unambiguous. A person often acts creatively, not formally. Even the same mathematical problems can be solved in different ways. The work of a journalist, scientist, translator and other specialists is a creative work with information that they do not follow formal rules.

To designate formalized rules that determine the sequence of information processing steps, computer science uses the concept of an algorithm (see “ Algorithm" 2). The concept of an algorithm in mathematics is associated with a well-known method for calculating the greatest common divisor (GCD) of two natural numbers, which is called the Euclid algorithm. In verbal form, it can be described as follows:

1. If two numbers are equal, then take their common value as GCD, otherwise go to step 2.

2. If the numbers are different, then replace the larger of them with the difference between the larger and smaller of the numbers. Return to step 1.

Here the input is two natural numbers - X 1 and X 2. Result Y is their greatest common divisor. Rule ( R) is Euclid's algorithm:

Euclid's algorithm ( X 1, X 2) Y

Such a formalized algorithm is easy to program for a modern computer. The computer is the universal executor of data processing. The formalized processing algorithm is presented in the form of a program placed in the computer memory. For a computer, processing rules ( R) - This program.

Explaining the topic “Information processing”, one should give examples of processing, both related to obtaining new information, and related to changing the form of information presentation.

The first type of processing: processing related to receiving new information, new knowledge content. This type of processing includes the solution of mathematical problems. The same type of information processing includes the solution of various problems by applying logical reasoning. For example, the investigator on a certain set of evidence finds a criminal; a person, analyzing the circumstances, makes a decision about his further actions; a scientist solves the mystery of ancient manuscripts, etc.

The second type of processing: processing associated with changing the form, but not changing the content. This type of information processing includes, for example, the translation of text from one language to another: the form changes, but the content must be preserved. An important type of processing for computer science is coding. Coding- it transformation of information into a symbolic form convenient for its storage, transmission, processing(cm. " Coding” 2).

Data structuring can also be classified as a second type of processing. Structuring is associated with the introduction of a certain order, a certain organization in the information storage. The arrangement of data in alphabetical order, grouping according to some criteria of classification, the use of a tabular or graph representation are all examples of structuring.

A special type of information processing is Search. The search task is usually formulated as follows: there is some storage of information - information array(telephone directory, dictionary, train schedule, etc.), you need to find the necessary information in it that meets certain search terms(phone number of this organization, translation of this word into English, time of departure of this train). The search algorithm depends on the way information is organized. If the information is structured, then the search is faster, it can be optimized (see “ Data Search” 2).

In a propaedeutic informatics course, “black box” problems are popular. The processing performer is considered as a “black box”, i.e. system, the internal organization and mechanism of which we do not know. The task is to guess the data processing rule (P) that the performer implements.

The processing executor calculates the average value of the input values: Y = (X 1 + X 2)/2

At the input - a word in Russian, at the output - the number of vowels.

The deepest mastery of information processing issues occurs when studying algorithms for working with quantities and programming (in basic and high school). The executor of information processing in this case is a computer, and all processing capabilities are embedded in the programming language. Programming there is description of the rules for processing input data in order to obtain output data.

Students should be given two types of tasks:

Direct task: to create an algorithm (program) for solving the problem;

Inverse problem: given an algorithm, it is required to determine the result of its execution by tracing the algorithm.

When solving an inverse problem, the student puts himself in the position of a processing performer, step by step executing the algorithm. The results of execution at each step should be reflected in the trace table.

Components of the information transfer process

The transfer of information occurs from the source to the recipient (receiver) of information. source information can be anything: any object or phenomenon of living or inanimate nature. The process of information transfer takes place in some material environment that separates the source and recipient of information, which is called channel transfer of information. Information is transmitted through a channel in the form of a certain sequence of signals, symbols, signs, which are called message. Recipient information is an object that receives a message, as a result of which certain changes in its state occur. All of the above is shown schematically in the figure.

Transfer of information

A person receives information from everything that surrounds him, through the senses: hearing, sight, smell, touch, taste. A person receives the greatest amount of information through hearing and sight. Sound messages are perceived by ear - acoustic signals in a continuous medium (most often in the air). Vision perceives light signals that carry the image of objects.

Not every message is informative for a person. For example, a message in an incomprehensible language, although transmitted to a person, does not contain information for him and cannot cause adequate changes in his state (see “ Information").

An information channel can either be of a natural nature (atmospheric air through which sound waves are transmitted, sunlight reflected from observed objects), or be artificially created. In the latter case, we are talking about technical means of communication.

The first technical means of transmitting information over a distance was the telegraph, invented in 1837 by the American Samuel Morse. In 1876, the American A. Bell invents the telephone. Based on the discovery of electromagnetic waves by the German physicist Heinrich Hertz (1886), A.S. Popov in Russia in 1895 and almost simultaneously with him in 1896 G. Marconi in Italy, radio was invented. Television and the Internet appeared in the twentieth century.

All of the above technical ways information communications are based on the transmission of a physical (electrical or electromagnetic) signal over a distance and are subject to certain general laws. The study of these laws is communication theory that emerged in the 1920s. Mathematical apparatus of communication theory - mathematical theory of communication, developed by the American scientist Claude Shannon.

Claude Elwood Shannon (1916–2001), USA

Claude Shannon proposed a model for the process of transmitting information through technical communication channels, represented by a diagram.

Technical information transmission system

Encoding here means any transformation of information coming from a source into a form suitable for its transmission over a communication channel. Decoding - inverse transformation of the signal sequence.

The operation of such a scheme can be explained by the familiar process of talking on the phone. The source of information is the speaking person. An encoder is a handset microphone that converts sound waves (speech) into electrical signals. The communication channel is the telephone network (wires, switches of telephone nodes through which the signal passes). The decoding device is a handset (headphone) of the listening person - the receiver of information. Here the incoming electrical signal is converted into sound.

Modern computer systems transmission of information - computer networks operate on the same principle. There is an encoding process that converts a binary computer code into a physical signal that type, which is transmitted over the communication channel. Decoding is the reverse transformation of the transmitted signal into computer code. For example, when using telephone lines in computer networks, the functions of encoding and decoding are performed by a device called a modem.

Developers of technical information transmission systems have to solve two interrelated tasks: how to ensure the highest speed of information transfer and how to reduce information loss during transmission. Claude Shannon was the first scientist who took on the solution of these problems and created a new science for that time - information theory.

K.Shannon determined the method of measuring the amount of information transmitted over communication channels. They introduced the concept channel bandwidth,as the maximum possible information transfer rate. This speed is measured in bits per second (as well as kilobits per second, megabits per second).

The throughput of a communication channel depends on its technical implementation. For example, computer networks use the following means of communication:

telephone lines,

Electrical cable connection,

fiber optic cabling,

Radio communication.

Throughput of telephone lines - tens, hundreds of Kbps; the throughput of fiber optic lines and radio communication lines is measured in tens and hundreds of Mbps.

Noise, noise protection

The term "noise" refers to various kinds of interference that distort the transmitted signal and lead to loss of information. Such interference primarily occurs due to technical reasons: poor quality of communication lines, insecurity from each other of various information flows transmitted over the same channels. Sometimes, while talking on the phone, we hear noise, crackling, which make it difficult to understand the interlocutor, or the conversation of completely different people is superimposed on our conversation.

The presence of noise leads to loss transmitted information. In such cases noise protection is necessary.

First of all, technical methods are used to protect communication channels from the effects of noise. For example, using shielded cable instead of bare wire; the use of various kinds of filters that separate the useful signal from noise, etc.

Claude Shannon developed coding theory, which gives methods for dealing with noise. One of the important ideas of this theory is that the code transmitted over the communication line must be redundant. Due to this, the loss of some part of the information during transmission can be compensated. For example, if you are hard to hear when talking on the phone, then by repeating each word twice, you have a better chance that the interlocutor will understand you correctly.

However, you can not make the redundancy too large. This will lead to delays and higher communication costs. Coding theory allows you to get a code that will be optimal. In this case, the redundancy of the transmitted information will be the minimum possible, and the reliability of the received information will be the maximum.

In modern digital communication systems, the following technique is often used to combat the loss of information during transmission. The whole message is divided into portions - packages. For each package is calculated check sum(sum of binary digits) that is transmitted with this packet. At the place of reception, the checksum of the received packet is recalculated and, if it does not match the original sum, the transmission of this packet is repeated. This will continue until the initial and final checksums match.

Considering the transfer of information in propaedeutic and basic courses Informatics, first of all, this topic should be discussed from the position of a person as a recipient of information. The ability to receive information from the surrounding world is the most important condition for human existence. The human sense organs are the information channels of the human body, carrying out the connection of a person with the external environment. On this basis, information is divided into visual, auditory, olfactory, tactile, and gustatory. The rationale for the fact that taste, smell and touch carry information to a person is as follows: we remember the smells of familiar objects, the taste of familiar food, we recognize familiar objects by touch. And the content of our memory is stored information.

Students should be told that in the animal world the informational role of the senses is different from the human one. The sense of smell performs an important informational function for animals. The heightened sense of smell of service dogs is used by law enforcement agencies to search for criminals, detect drugs, etc. The visual and sound perception of animals differs from that of humans. For example, bats are known to hear ultrasound, and cats are known to see in the dark (from a human perspective).

Within the framework of this topic, students should be able to give specific examples of the process of transmitting information, determine for these examples the source, receiver of information, and the channels used for transmitting information.

When studying computer science in high school, students should be introduced to the basic provisions of the technical theory of communication: the concepts of coding, decoding, information transfer rate, throughput channel, noise, noise protection. These issues can be considered within the framework of the topic “Technical means of computer networks”.

Numbers in mathematics

The number is the most important concept of mathematics, which has evolved and evolved over a long period of human history. People have been working with numbers since ancient times. Initially, a person operated only with positive integers, which are called natural numbers: 1, 2, 3, 4, ... For a long time there was an opinion that there is the largest number, “more than this the human mind can understand” (as they wrote in the Old Slavonic mathematical treatises) .

The development of mathematical science has led to the conclusion that there is no largest number. From a mathematical point of view, the series of natural numbers is infinite, i.e. is not limited. With the advent of the concept of a negative number in mathematics (R. Descartes, XVII century in Europe; in India much earlier), it turned out that the set of integers is unlimited both “left” and “right”. The mathematical set of integers is discrete and unlimited (infinite).

The concept of a real (or real) number was introduced into mathematics by Isaac Newton in the 18th century. From a mathematical point of view the set of real numbers is infinite and continuous. It includes many integers and an infinite number of non-integers. Between any two points on the number axis lies an infinite set of real numbers. The concept of a real number is associated with the idea of ​​a continuous numerical axis, any point of which corresponds to a real number.

In computer memory numbers are stored in binary number system(cm. " Number systems” 2). There are two forms of representing integers in a computer: unsigned integers and signed integers.

Integers without a sign - it the set of positive numbers in the range, where k- this is the bit depth of the memory cell allocated for the number. For example, if a memory cell of 16 bits (2 bytes) is allocated for an integer, then the largest number will be:

In decimal, this corresponds to: 2 16 - 1 \u003d 65 535

If all digits of the cell are zeros, then it will be zero. Thus, 2 16 = 65 536 integers are placed in a 16-bit cell.

Signed integers is the set of positive and negative numbers in the range[–2 k–1 , 2 k-eleven]. For example, when k= 16 integer representation range: [–32768, 32767]. The high order of the memory cell stores the sign of the number: 0 - positive number, 1 - negative number. The largest positive number 32,767 has the following representation:

For example, the decimal number 255, after being converted to binary and inserted into a 16-bit memory cell, will have the following internal representation:

Negative integers are represented in two's complement. Additional code positive number N- it is its binary representation, which, when added to the number code N gives value 2 k. Here k- the number of bits in the memory cell. For example, the additional code for the number 255 would be:

This is the representation of the negative number -255. Let's add the codes of numbers 255 and -255:

The one in the highest order “dropped out” of the cell, so the sum turned out to be zero. But this is how it should be: N + (–N) = 0. The computer processor performs the subtraction operation as an addition with the additional code of the subtracted number. In this case, the overflow of the cell (exceeding the limit values) does not cause the interruption of the program execution. This circumstance the programmer must know and take into account!

The format for representing real numbers in a computer is called floating point format. real number R represented as a product of the mantissa m based on the number system n to some extent p, which is called the order: R= m ? np.

The representation of a number in floating point form is ambiguous. For example, for the decimal number 25.324, the following equalities are true:

25.324 = 2.5324? 10 1 = 0.0025324? 10 4 \u003d 2532.4? 10 -2, etc.

To avoid ambiguity, we agreed to use the computer a normalized representation of a number in floating point form. Mantissa in the normalized representation must satisfy the condition: 0.1 nm < 1 n. In other words, the mantissa is less than one and the first significant digit is not zero. In some cases, the normalization condition is taken as follows: 1 n m < 10 n .

V computer memory mantissa represented as an integer containing only significant digits(0 integers and commas are not stored). Therefore, the internal representation of a real number is reduced to the representation of a pair of integers: mantissa and exponent.

Used in different types of computers various options representations of numbers in floating point form. Consider one of the variants of the internal representation of a real number in a four-byte memory cell.

The cell must contain the following information about the number: the sign of the number, the exponent, and the significant digits of the mantissa.

The sign of the number is stored in the most significant bit of the 1st byte: 0 means plus, 1 means minus. The remaining 7 bits of the first byte contain machine order. The next three bytes store the significant digits of the mantissa (24 bits).

Binary numbers in the range from 0000000 to 1111111 are placed in seven binary digits. This means that the machine order varies in the range from 0 to 127 (in decimal number system). There are 128 values ​​in total. The order, obviously, can be either positive or negative. It is reasonable to divide these 128 values ​​equally between positive and negative order values: from -64 to 63.

Machine order biased relative to the mathematical and has only positive values. The offset is chosen so that the minimum mathematical value of the order corresponds to zero.

The relationship between machine order (Mp) and mathematical order (p) in the case under consideration is expressed by the formula: Mp = p + 64.

The resulting formula is written in the decimal system. In binary, the formula looks like: Mp 2 = p 2 + 100 0000 2 .

To write the internal representation of a real number, you must:

1) translate the modulus of a given number into a binary number system with 24 significant digits,

2) normalize a binary number,

3) find the machine order in the binary system,

4) taking into account the sign of the number, write out its representation in a four-byte machine word.

Example. Write the internal representation of the number 250.1875 in floating point form.

1. Let's translate it into a binary number system with 24 significant digits:

250,1875 10 = 11111010,0011000000000000 2 .

2. Let's write in the form of a normalized binary floating point number:

0.111110100011000000000000 H 10 2 1000 .

Here is the mantissa, the base of the number system
(2 10 \u003d 10 2) and the order (8 10 \u003d 1000 2) are written in binary.

3. Calculate the machine order in the binary system:

MP2 = 1000 + 100 0000 = 100 1000.

4. Let's write the representation of the number in a four-byte memory cell, taking into account the sign of the number

Hexadecimal form: 48FA3000.

The range of real numbers is much wider than the range of integers. Positive and negative numbers are arranged symmetrically about zero. Therefore, the maximum and minimum numbers are equal in absolute value.

The smallest absolute number is zero. The largest floating-point number in absolute value is the number with the largest mantissa and the largest exponent.

For a four-byte machine word, this number would be:

0.11111111111111111111111 10 2 1111111 .

After converting to the decimal number system, we get:

MAX = (1 - 2 -24) 2 63 10 19 .

If, when calculating with real numbers, the result is outside the allowable range, then the program execution is interrupted. This happens, for example, when dividing by zero, or by a very small number close to zero.

Real numbers whose mantissa bit length exceeds the number of bits allocated for the mantissa in a memory cell are represented in the computer approximately (with a “truncated” mantissa). For example, the rational decimal number 0.1 in a computer will be represented approximately (rounded) because in the binary system its mantissa has an infinite number of digits. The consequence of this approximation is the error of machine calculations with real numbers.

The computer performs calculations with real numbers approximately. The error of such calculations is called machine rounding error.

The set of real numbers that can be exactly represented in the computer memory in floating point form is limited and discrete. Discreteness is a consequence of the limited number of digits of the mantissa, as discussed above.

The number of real numbers that can be exactly represented in computer memory can be calculated using the formula: N = 2 t · ( U – L+ 1) + 1. Here t- the number of binary digits of the mantissa; U- the maximum value of the mathematical order; L- minimum order value. For the representation option considered above ( t = 24, U = 63,
L= -64) it turns out: N = 2 146 683 548.

The topic of representing numerical information in a computer is present both in the standard for elementary school and for high school.

In the basic school (basic course) it is enough to consider the representation of integers in a computer. The study of this issue is possible only after getting acquainted with the topic “Number systems”. In addition, from the principles of computer architecture, students should be aware that a computer works with a binary number system.

Considering the representation of integers, the main attention should be paid to the limited range of integers, to the connection of this range with the capacity of the allocated memory cell - k. For positive numbers (unsigned): , for positive and negative numbers (signed): [–2 k–1 , 2 k–1 – 1].

Obtaining the internal representation of numbers should be analyzed with examples. After that, by analogy, students should independently solve such problems.

Example 1 Get the signed internal representation of the integer 1607 in a two-byte memory location.

1) Convert the number to the binary system: 1607 10 = 11001000111 2 .

2) Adding zeros to 16 digits on the left, we get the internal representation of this number in the cell:

It is desirable to show how the hexadecimal form is used for the compressed form of this code, which is obtained by replacing each four binary digits with one hexadecimal digit: 0647 (see “ Number systems” 2).

More difficult is the problem of obtaining the internal representation of a negative integer (– N) - additional code. You need to show the students the algorithm of this procedure:

1) get the internal representation of a positive number N;

2) get the return code of this number by replacing 0 with 1 and 1 with 0;

3) add 1 to the resulting number.

Example 2. Get the internal representation of a negative integer -1607 in a two-byte memory location.

It is useful to show students what the internal representation of the smallest negative number looks like. In a two-byte cell, this is -32,768.

1) it is easy to convert the number 32 768 to the binary number system, since 32 768 = 2 15. Therefore, in binary it is:

1000000000000000

2) write the reverse code:

0111111111111111

3) add one to this binary number, we get

The one in the first bit means the minus sign. No need to think that the received code is minus zero. This is -32,768 in two's complement form. These are the rules for machine representation of integers.

After showing this example, have the students prove for themselves that adding the number codes 32767 + (-32768) results in the number code -1.

According to the standard, the representation of real numbers should be studied in high school. When studying computer science in grades 10–11 at the basic level, it is enough to tell students about the main features of a computer with real numbers: about the limited range and interrupting the program when it goes beyond it; about the error of machine calculations with real numbers, that the computer performs calculations with real numbers more slowly than with integers.

Studying at the profile level requires a detailed analysis of how to represent real numbers in floating point format, an analysis of the features of performing calculations on a computer with real numbers. A very important problem here is the estimation of the calculation error, the warning against loss of value, against interruption of the program. Detailed material on these issues is available in the training manual.

Number system - this is a way of representing numbers and the corresponding rules for operating on numbers. The various number systems that existed before and are used today can be divided into non-positional and positional. Signs used when writing numbers, are called numbers.

V non-positional number systems the value of a digit does not depend on its position in the number.

An example of a non-positional number system is the Roman system (Roman numerals). In the Roman system, Latin letters are used as numbers:

Example 1. The number CCXXXII consists of two hundred, three tens and two units and is equal to two hundred and thirty two.

Roman numerals are written from left to right in descending order. In this case, their values ​​are added. If a smaller number is written on the left, and a large number on the right, then their values ​​are subtracted.

VI = 5 + 1 = 6; IV \u003d 5 - 1 \u003d 4.

MCMXCVIII = 1000 + (-100 + 1000) +

+ (–10 + 100) + 5 + 1 + 1 + 1 = 1998.

V positional number systems the value denoted by a digit in a number entry depends on its position. The number of digits used is called the base of the positional number system.

The number system used in modern mathematics is positional decimal system. Its base is ten, because Any numbers are written using ten digits:

0, 1, 2, 3, 4, 5, 6, 7, 8, 9.

The positional nature of this system is easy to understand by the example of any multi-digit number. For example, in the number 333, the first three means three hundred, the second - three tens, the third - three units.

To write numbers in a positional system with a base n Must have alphabet from n digits. Usually for this n < 10 используют n first Arabic numerals, and n> 10 letters are added to ten Arabic numerals. Here are examples of alphabets from several systems:

If it is required to indicate the base of the system to which the number belongs, then it is assigned a subscript to this number. For instance:

1011012, 36718, 3B8F16.

In the base number system q (q-ary number system) units of digits are successive powers of a number q. q units of any category form the unit of the next category. To write a number to q-ary number system required q various characters (numbers) representing the numbers 0, 1, ..., q– 1. Writing a number q v q-ary number system has the form 10.

Expanded form of writing a number

Let Aq- number in the base system q, ai - digits of a given number system present in the notation of a number A, n+ 1 - the number of digits of the integer part of the number, m- the number of digits of the fractional part of the number:

Expanded form of a number A is called a record in the form:

For example, for a decimal number:

The following examples show the expanded form of hexadecimal and binary numbers:

In any number system, its base is written as 10.

If all the terms in the expanded form of a non-decimal number are presented in the decimal system and the resulting expression is calculated according to the rules of decimal arithmetic, then a number in the decimal system equal to the given one will be obtained. According to this principle, a conversion from a non-decimal system to a decimal one is made. For example, the conversion to the decimal system of the numbers written above is done like this:

Integer Translation

integer decimal number X needs to be transferred to a system with a base q: X = (a n a n-1 …a 1 a 0) q . Find the significant digits of a number: . Let's represent the number in expanded form and perform the identical transformation:

From here it is clear that a 0 is the remainder after dividing the number X per number q. The expression in parentheses is the integer quotient of this division. Let's designate it as X 1. Performing similar transformations, we get:

Hence, a 1 is the remainder of the division X 1 on q. Continuing the division with a remainder, we will get a sequence of digits of the desired number. Number an in this chain of divisions will be the last private, smaller q.

Let's formulate the resulting rule: for to convert a whole decimal number to a number system with a different base, you need:

1) express the base of the new number system in the decimal number system and perform all subsequent actions according to the rules of decimal arithmetic;

2) sequentially divide the given number and the resulting partial quotients by the basis of the new number system until we get an incomplete quotient less than the divisor;

3) the resulting remainders, which are the digits of the number in new system calculus, bring it into line with the alphabet of the new number system;

4) compose a number in the new number system, writing it down starting from the last private number.

Example 1. Convert the number 37 10 to the binary system.

To denote numbers in the notation of a number, we use symbolism: a 5 a 4 a 3 a 2 a 1 a 0

Hence: 37 10 = l00l0l 2

Example 2. Convert the decimal number 315 to octal and hexadecimal systems:

It follows from here: 315 10 = 473 8 = 13B 16. Recall that 11 10 = B 16 .

Decimal X < 1 требуется перевести в систему с основанием q: X = (0, a –1 a –2 … a–m+1 a–m) q . Find the significant digits of a number: a –1 ,a –2 , …, a-m. We represent the number in expanded form and multiply it by q:

From here it is clear that a–1 X per number q. Denote by X 1 fractional part products and multiply it by q:

Hence, a –2 there is a whole part of the work X 1 per number q. Continuing multiplication, we will get a sequence of digits. Now let's formulate the rule: in order to convert a decimal fraction to a number system with a different base, you need:

1) successively multiply the given number and the resulting fractional parts of the products by the basis of the new system until the fractional part of the product becomes equal to zero or the required accuracy of representing the number in the new number system is reached;

2) the resulting integer parts of the products, which are the digits of a number in the new number system, bring them into line with the alphabet of the new number system;

3) make up the fractional part of the number in the new number system, starting with the integer part of the first product.

Example 3. Convert decimal 0.1875 to binary, octal and hexadecimal.

Here, the integer part of the numbers is in the left column, and the fractional part is in the right column.

Hence: 0.1875 10 = 0.0011 2 = 0.14 8 = 0.3 16

The translation of mixed numbers containing integer and fractional parts is carried out in two stages. The integer and fractional parts of the original number are translated separately according to the corresponding algorithms. In the final record of a number in the new number system, the integer part is separated from the fractional comma (dot).

The topic “Number systems” is directly related to the mathematical theory of numbers. However, in the school course of mathematics, as a rule, it is not studied. The need to study this topic in a computer science course is related to the fact that numbers in computer memory are represented in a binary number system, and hexadecimal or octal systems are used to externally represent the contents of memory, memory addresses. This is one of the traditional topics of a computer science or programming course. Being related to mathematics, this topic also contributes to the fundamental mathematical education of schoolchildren.

For a computer science course, the main interest is familiarity with the binary number system. The use of the binary number system in a computer can be considered in two aspects: 1) binary numbering, 2) binary arithmetic, i.e. performing arithmetic calculations on binary numbers.

Binary numbering

With binary numbering, students meet in the topic “Representing text in computer memory”. When talking about the encoding table, the teacher must inform the students that the internal binary code of a character is its serial number in the binary number system. For example, the number of the letter S in the ASCII table is 83. The eight-digit binary code of the letter S is equal to the value of this number in the binary system: 01010011.

Binary Computing

According to the principle of John von Neumann, the computer performs calculations in the binary system. Within the framework of the basic course, it is enough to confine ourselves to considering calculations with binary integers. To perform calculations with multi-digit numbers, you need to know the rules for addition and the rules for multiplying single-digit numbers. Here are the rules:

The principle of permutation of addition and multiplication works in all number systems. Techniques for performing calculations with multi-digit numbers in the binary system are similar to decimal. In other words, the procedures for adding, subtracting and multiplying by a “column” and dividing by a “corner” in the binary system are performed in the same way as in the decimal system.

Consider the rules for subtracting and dividing binary numbers. The subtraction operation is the inverse of addition. From the addition table above, the subtraction rules follow:

0 - 0 = 0; 1 - 0 = 1; 10 - 1 = 1.

Here is an example of multi-digit subtraction:

The result obtained can be checked by adding the difference with the subtrahend. It should be a decreasing number.

Division is the inverse operation of multiplication.
In any number system, you cannot divide by 0. The result of division by 1 is equal to the dividend. Dividing a binary number by 102 moves the decimal point one place to the left, just like decimal division by ten. For instance:

Dividing by 100 shifts the decimal point 2 places to the left, and so on. In the basic course, you can not consider complex examples of dividing multi-valued binary numbers. Although able students can cope with them, having understood the general principles.

The representation of information stored in computer memory in its true binary form is very cumbersome due to the large number of digits. This refers to the recording of such information on paper or displaying it on the screen. For these purposes, it is customary to use mixed binary-octal or binary-hexadecimal systems.

There is a simple relationship between the binary and hexadecimal representation of a number. When translating a number from one system to another, one hexadecimal digit corresponds to a four-bit binary code. This correspondence is reflected in the binary-hexadecimal table:

Binary hexadecimal table

Such a relationship is based on the fact that 16 = 2 4 and the number of different four-digit combinations of the digits 0 and 1 is 16: from 0000 to 1111. Therefore converting numbers from hexadecimal to binary and vice versa is done by formal conversion by binary-hexadecimal table.

Here is an example of translating a 32-bit binary code into a hexadecimal system:

1011 1100 0001 0110 1011 1111 0010 1010 BC16BF2A

If a hexadecimal representation of the internal information is given, then it is easy to translate it into binary code. The advantage of the hexadecimal representation is that it is 4 times shorter than the binary. It is desirable that students memorize the binary-hexadecimal table. Then indeed for them the hexadecimal representation will become equivalent to binary.

In binary octal, each octal digit corresponds to a triad of binary digits. This system allows you to reduce the binary code by 3 times.

A person stores information in his own memory, as well as in the form of records on various external (in relation to a person) media: on stone, papyrus, paper, magnetic and optical media, etc. Thanks to such records, information is transmitted not only in space (from person to man), but also in time - from generation to generation.

Information may be stored in various types: in the form of texts, in the form of figures, diagrams, drawings; in the form of photographs, in the form of sound recordings, in the form of film or video recordings. In each case, their carriers are used. Carrier - it the material medium used to record and store information.

The main characteristics of information carriers include: information volume or density of information storage, reliability (durability) of storage.

Paper media

The carrier with the most massive use is still paper. Invented in the 2nd century AD. in China, paper has served people for 19 centuries.

To compare the volumes of information on different media, we will use a universal unit - byte, assuming that one character of the text "weighs" 1 byte. A book containing 300 pages, with a text size of approximately 2000 characters per page, has an information volume of 600,000 bytes, or 586 KB. The information volume of the secondary school library, which fund is 5000 volumes, is approximately equal to 2861 MB = 2.8 GB.

As for the durability of storing documents, books and other paper products, it very much depends on the quality of the paper, on the dyes used to write the text, and on the storage conditions. Interestingly, until the middle of the 19th century (since that time, wood began to be used as paper raw material), paper was made from cotton and textile waste - rags. The inks were natural dyes. The quality of handwritten documents of that time was quite high, and they could be stored for thousands of years. With the transition to a wood base, with the spread of typewriting and copying tools, with the use of synthetic dyes, the shelf life of printed documents has decreased to 200–300 years.

Magnetic media

Magnetic recording was invented in the 19th century. Initially, magnetic recording was only used to preserve sound. The very first magnetic recording medium was steel wire with a diameter of up to 1 mm. At the beginning of the 20th century, rolled steel tape was also used for these purposes. The quality characteristics of all these carriers were very low. The production of a 14-hour magnetic recording of oral presentations at the International Congress in Copenhagen in 1908 required 2,500 km, or about 100 kg of wire.

In the 1920s, there appeared magnetic tape first on paper, and later on a synthetic (lavsan) basis, on the surface of which a thin layer of ferromagnetic powder is applied. In the second half of the 20th century, they learned how to record an image on magnetic tape, video cameras and video recorders appeared.

On computers of the first and second generations, magnetic tape was used as the only type of removable media for external memory devices. About 500 Kb of information were placed on one reel of magnetic tape, which was used in the tape drives of the first computers.

Since the early 1960s, computer magnetic disks: an aluminum or plastic disc coated with a thin layer of magnetic powder a few microns thick. Information on a disk is arranged along circular concentric tracks. Magnetic disks are hard and flexible, removable and built into a computer drive. The latter are traditionally called hard drives, and removable floppy disks are called floppy disks.

The hard drive of a computer is a package of magnetic disks put on a common axis. The information capacity of modern hard drives is measured in gigabytes - tens and hundreds of GB. The most common type of floppy disk with a diameter of 3.5 inches holds 2 MB of data. Floppy disks have recently fallen out of use.

Plastic cards have become widespread in the banking system. They also use the magnetic principle of recording information with which ATMs work, cash registers associated with the information banking system.

Optical media

The use of the optical, or laser, method of recording information begins in the 1980s. Its appearance is associated with the invention of a quantum generator - a laser, a source of a very thin (thickness of the order of a micron) beam of high energy. The beam is capable of burning a binary code of data with a very high density on the surface of a fusible material. Reading occurs as a result of reflection from such a “perforated” surface of a laser beam with less energy (“cold” beam). Due to the high recording density, optical discs have a much larger information volume than single-disk magnetic media. The information capacity of an optical disc is from 190 to 700 MB. Optical discs are called CDs.

In the second half of the 1990s, digital versatile video discs (DVD) appeared. D digital V ersatile D isk) with a large capacity, measured in gigabytes (up to 17 GB). The increase in their capacity compared to CDs is due to the use of a laser beam of a smaller diameter, as well as two-layer and two-sided recording. Think back to the school library example. Her entire book fund can be placed on one DVD.

Currently, optical discs (CD - DVD) are the most reliable material carriers of digitally recorded information. These types of media are either write-once - read-only, or rewritable - read-write.

Flash memory

Recently, a lot of mobile digital devices have appeared: digital cameras and video cameras, MP3 players, PDAs, mobile phones, e-book readers, GPS navigators and much more. All of these devices require portable storage media. But since all mobile devices are quite miniature, they also have special requirements for storage media. They must be compact, have low power consumption during operation and be non-volatile during storage, have a large capacity, high write and read speeds, and a long service life. All these requirements are met flash cards memory. The information volume of a flash card can be several gigabytes.

As an external medium for a computer, flash key fobs (“flash drives” - they are called colloquially), the release of which began in 2001, were widely used. A large amount of information, compactness, high read-write speed, ease of use are the main advantages of these devices. The flash key fob connects to a computer's USB port and allows you to download data at a speed of about 10 Mb per second.

“Nano-carriers”

In recent years, work has been actively carried out to create even more compact information carriers using the so-called “nanotechnologies”, working at the level of atoms and molecules of matter. As a result, a single CD made using nanotechnology can replace thousands of laser discs. According to experts, in about 20 years, the density of information storage will increase to such an extent that every second of a human life can be recorded on a medium with a volume of about a cubic centimeter.

Information is stored on media so that it can be viewed, search for the necessary information, required documents, replenish and change, delete data that has lost its relevance. In other words, the stored information is needed by a person to work with it. The convenience of working with such information repositories is highly dependent on how the information is organized.

Two situations are possible: either the data is not organized in any way (this situation is sometimes called a heap), or the data structured. With the increase in the amount of information, the “heap” option becomes more and more unacceptable due to the complexity of its practical use (search, update, etc.).

The words “data are structured” mean the presence of some order of data in their storage: in a dictionary, schedule, archive, computer database. Reference books, dictionaries, encyclopedias usually use the linear alphabetical principle of organizing (structuring) data.

Libraries are the largest repository of information. Mentions of the first libraries date back to the 7th century BC. With the invention of printing in the 15th century, libraries began to spread throughout the world. Librarianship has centuries of experience in organizing information.

To organize and search for books in libraries, catalogs are created: lists of the book fund. The first library catalog was created in the famous Alexandrian Library in the 3rd century BC. With the help of the catalog, the reader determines the availability of the book he needs in the library, and the librarian finds it in the book depository. When using paper technology, a catalog is an organized set of cardboard cards with information about books.

There are alphabetical and systematic catalogs. V alphabetical catalogs, the cards are arranged in alphabetical order of the names of the authors and form linear(single-level)data structure. V systematic catalog cards are systematized according to the content of the books and form hierarchical data structure. For example, all books are divided into art, educational, scientific. Educational literature is divided into school and university. Books for school are divided into classes, etc.

In modern libraries, paper catalogs are being replaced by electronic ones. In this case, the search for books is carried out automatically by the information system of the library.

Data stored on computer media (disks) have a file organization. A file is like a book in a library. Like a library directory, the operating system creates a directory on disk, which is stored on dedicated tracks. The user searches for the desired file by browsing the directory, after which the operating system finds this file on the disk and provides it to the user. The first small-capacity disk media used a single-level file storage structure. With the advent hard drives large volume began to be used hierarchical structure file organization. Along with the concept of “file”, the concept of a folder appeared (see “ Files and file system” 2).

More flexible system data storage and retrieval organizations are computer databases (see . “Database” 2).

The problem of information storage reliability is associated with two types of threats to stored information: destruction (loss) of information and theft or leakage of confidential information. Paper archives and libraries have always been in danger of physical extinction. The destruction of the Library of Alexandria mentioned above in the 1st century BC brought great damage to civilization, since most of the books in it existed in a single copy.

The main way to protect information in paper documents from loss is their duplication. The use of electronic media makes duplication easier and cheaper. However, the transition to new (digital) information technologies has created new problems of information security. See the article “ Data protection” 2.

In the process of studying the computer science course, students acquire certain knowledge and skills related to the storage of information.

Students learn to work with traditional (paper) sources of information. The standard for the primary school notes that students must learn to work with non-computer sources of information: reference books, dictionaries, library catalogs. To do this, they should be familiarized with the principles of organizing these sources and with the methods of optimal search in them. Since these knowledge and skills are of great general educational importance, it is desirable to give them to students as early as possible. In some programs of the propaedeutic informatics course, much attention is paid to this topic.

Students must master the techniques of working with removable computer storage media. Increasingly rare in recent years, floppy magnetic disks have been used, which have been replaced by capacious and fast flash media. Students should be able to determine the information capacity of the media, the volume free space, compare the volumes of saved files with it. Students should understand that optical discs are the most suitable medium for long-term storage of large amounts of data. If you have a CD burner, teach them how to write files.

An important point training is an explanation of the dangers to which computer information is exposed from malicious programs - computer viruses. Children should be taught the basic rules of "computer hygiene": to carry out anti-virus control of all newly arriving files; regularly update anti-virus databases.

Language - it a certain system of symbolic representation of information. In the school computer science dictionary compiled by A.P. Ershov, the following definition is given: “ Language- a set of symbols and a set of rules that determine how to compose meaningful messages from these symbols". Since a meaningful message is understood as information, then this definition essentially the same as the first.

Languages ​​are divided into two groups: natural and formal. natural languages- it historically formed languages ​​of national speech. Most modern languages ​​are characterized by the presence of oral and written forms of speech. The analysis of natural languages ​​is mostly the subject of philological sciences, in particular, linguistics. In computer science, the analysis of natural languages ​​is carried out by specialists in the field of artificial intelligence. One of the goals of the development of the fifth generation computer project is to teach the computer to understand natural languages.

Formal languages ​​are artificially created languages ​​for professional use. They are usually international in nature and have a written form. Examples of such languages ​​are the language of mathematics, the language of chemical formulas, musical notation - the language of music, etc.

The following concepts are associated with any language: alphabet - many symbols used; syntax- rules for writing language constructs(text in language); semantics - semantic side of language constructions; pragmatics - practical consequences of using text in a given language.

For formal languages characterized by belonging to a limited subject area(mathematics, chemistry, music, etc.). Purpose of formal language - an adequate description of the system of concepts and relationships inherent in a given subject area. Therefore, all the above-mentioned components of the language (alphabet, syntax, etc.) are focused on the specifics of the subject area. A language can develop, change, and be supplemented along with the development of its subject area.

Natural languages ​​are not limited in their application, in this sense they can be called universal. However, it is not always convenient to use only natural language in highly specialized areas. In such cases, people resort to the help of formal languages.

There are known examples of languages ​​that are in an intermediate state between natural and formal. Language Esperanto was created artificially for communication between people of different nationalities. A Latin, which in ancient times was spoken by the inhabitants of the Roman Empire, has become the formal language of medicine and pharmacology in our time, having lost the function of a spoken language.

Information circulating in a computer is divided into two types: processed information (data) and information that controls the operation of the computer (commands, programs, operators).

Information presented in a form suitable for storage, transmission and processing by a computer is called data. Examples of data: numbers when solving a mathematical problem; character sequences in text processing; an image entered into a computer by scanning, to be processed. The way data is represented in a computer is called data presentation language.

Each data type has a different external and internal data representation. External view human-oriented, determines the type of data on output devices: on the screen, on the printout. Internal representation- it representation on storage media in a computer, i.e. in memory, in the lines of information transmission. The computer directly operates on the information in the internal representation, and the external representation is used to communicate with the person.

In the most general sense, we can say that the language for representing computer data is binary code language. However, from the point of view of the above properties that any language should have: alphabet, syntax, semantics, pragmatics, one cannot speak of one common language binary codes. The only thing it has in common is the binary alphabet: 0 and 1. But for different data types, the rules of syntax and semantics of the internal representation language differ. The same sequence of binary digits for different data types has a completely different meaning. For example, the binary code “0100000100101011” in the integer representation language denotes the decimal number 16683, and in the character data representation language it denotes two characters - “A+”. In this way, different data types use different internal representation languages. All of them have a binary alphabet, but differ in the interpretation of character sequences.

External data representation languages ​​are usually close to the form familiar to humans: numbers are represented in the decimal system, when writing texts, natural language alphabets, traditional mathematical symbols, etc. are used. In the presentation of data structures, a convenient tabular form is used (relational databases). But even in this case, there are always certain rules of syntax and semantics of the language, a limited set of valid symbols is used.

The internal language for representing actions on data (the language for managing computer operation) is computer processor command language. External languages ​​for representing actions on data include high level programming languages, input languages ​​of application packages, operating system command languages, data manipulation languages ​​in DBMS etc.

Any high-level programming language includes both means of representing data - the data section, and means of representing actions on data - the operator section (see “ Programming languages” 2). The same applies to the other types of computer languages ​​listed above.

Among the formal languages ​​of science, the closest to computer science is the language of mathematics.
In turn, from many mathematical disciplines greatest application in computer science have number theory and mathematical logic.
In this regard, we can say that the topics of number systems (the language for representing numbers) and the foundations of mathematical logic (the language of logic) are related to the fundamental foundations of computer science (see “ Number systems" and " Boolean expressions” 2).

In propaedeutic and basic informatics courses, a conversation about languages ​​in relation to a person is of great educational importance. The term “language” familiar to students takes on a new meaning in their minds. A whole system of scientific concepts is built around this term. The concept of language is one of the most important backbone concepts of the informatics course.

When studying each new ICT tool, students should be drawn to the fact that in order to work with it, the user must master a certain formalized language, that its use requires strict adherence to the rules of the language: knowledge of the alphabet, syntax, semantics and pragmatics. This rigor is due to the fact that formalized languages, as a rule, do not have redundancy. Therefore, any violation of the rules (use of a character that is not included in the alphabet, incorrect use of separating characters, for example, a comma instead of a dot, etc.) leads to an error.

Students should pay attention to the commonality of some language constructs used in various technologies. For example, the rules for writing formulas in spreadsheets and arithmetic expressions in programming languages ​​are almost the same. There are also differences that you should also pay attention to. For example, in programming languages, logical connectives (NOT, AND, OR) are signs of operations, and in spreadsheets, they are function names.

To simplify the user's work in modern software, various kinds of shells are often used to provide a convenient user interface. It should be explained to students that behind these shells, as a rule, a certain formalized language is hidden. For example, behind the graphical shell of the operating Windows systems hides the command language of the OS. Another example: MS Access DBMS provides the user with the opportunity to use the table designer to create a database, and the query designer to build queries. However, behind these high-level tools, SQL is “hidden” - a universal language for describing data and manipulating data. By switching to the appropriate mode, you can show how the SQL commands generated as a result of working with the constructor look like.

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2. Beshenkov S.A.,Rakitina E.A. Informatics. Systematic course. Textbook for 10th grade. Moscow: Basic Knowledge Laboratory, 2001, 57 p.

3.Wiener N. Cybernetics, or Control and Communication in the Animal and the Machine. Moscow: Soviet radio, 1968, 201 p.

4. Computer science. Taskbook-workshop in 2 volumes / Ed. I.G. Semakina, E.K. Henner. T. 1. M.: BINOM. Knowledge Lab, 2005.

5. Kuznetsov A.A., Beshenkov S.A., Rakitina E.A., Matveeva N.V., Milokhina L.V. Continuous course of informatics (concept, system of modules, model program). Informatics and Education, No. 1, 2005.

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M.: FIZMATLIT, 2006. - 768 p.

The encyclopedic reference dictionary contains more than 18 thousand Russian and English terms, thematically systematized into the following major sections: I. Fundamentals information technology; II. Automation of information processes and automated systems (AC); III. Technical support of the AU; IV. AS software; V. Multimedia, hypermedia, virtual reality, machine vision; VI. Network technologies for data processing and transmission; VII. Computer and network slang; VIII. Pictograms used in email; IX. Abbreviations of words and expressions used on the Internet.

Dictionary entries are of an extended nature and include reference data on the objects of description, as well as links to primary documentary sources for a more complete acquaintance with them for interested users.

The structure and content of the dictionary make it possible to use it for a systematic study of materials on the thematic sections and subsections of interest to the reader, to carry out a preliminary study of decisions related to the design of heterogeneous automated information and telecommunication systems, and also to prepare on its basis educational and methodological, review, reference, etc. documentation.

The dictionary is aimed at a wide range of users whose professional activities or interests are related to modern information technologies.

Format: djvu

The size: 7.1Mb

Download: yandex.disk

CONTENT
Preface to the encyclopedic edition of the dictionary .............................. 7
Preface to the third edition of the dictionary, about the reference dictionary and its author... 9
From the author .................................................. .... eleven
About using the dictionary............................................... 13
I. Fundamentals of information technology............................... 15
1.1. Data, information, knowledge, logic....................................... 15
1.2. Information resources, information theory, informatics 19
1.3. Data carriers, documents, documentation, publications...................... 22
1.4. Principles of Structured Representation of Documents and Data....... 27
1.4.1. Information elements and their types .............................. 27
1.4.2. Record, File, Array, Key.................................... 30
1.4.3. Structures, data models and related terms 34
1.4.4. Format, data field and related terms .............................. 45
1.5. Information technology.............................................. 49
1.5.1. General concepts and terms.............................. 49
1.5.2. Handling and Processing of Documents and Data.................................. 52
1.5.3. Entering documents and data into a computer .............................. 58
1.5.4. Information retrieval ^ general concepts and terms ............... 63
1.5.5. Indexing, search image of documents and queries 66
1.6. Information technology security.............................................. 74
1.6.1. General concepts and terms................................... 74
1.6.2. Encoding and Decoding Documents and Data.............................. 83
1.6.3. Cryptology and Related Concepts ....................... 87
II. Automation of information processes and automated information systems 93
2.1. General concepts and terms .............................................. 93
2.2. Automation of information and library processes....................... 95
2.2.1. Terms related to automation............................... 95
2.3. Automated systems................................... 98
2.3.1. General concepts and terms.............................. 98
2.3.2. Functionally ^oriented automated systems..... 106
2.4. Linguistic and information support of automated systems 117
2.4.1. Linguistic support ^ general concepts and terms ......... 117
2.4.2. Information retrieval languages ​​and AIS dictionaries....... 119
2.4.3. AIS metadata and formats 128
2.4.4. Information support of AIS .............................. 147
2.5. Personnel and users of automated systems .............................. 153
2.5.1. AIS Developers and Personnel .............................. 153
2.5.2. AIS Users .............................................. 157
2.5.3. Certification of specialists in AIS .............................. 159
2.6. Processes of creation and operation of automated systems .......... 162
2.6.1. Design of automated systems.............................. 162
2.6.2. AIS Life Cycle and System Integration.................................. 165
III. Technical support of automated systems .......... 169
3.1. Computers, their types and general classification 169
3.2. Architecture, configuration, computer platform....................... 175
3.3. Personal computers (PCs) ............................... 178
3.4. Portable PCs and stand-alone digital devices for various purposes ... 185
3.4.1. Types of laptops............................................... 185
3.4.2. Digital playback and recording devices 188
3.5. System unit and elements of its design ........................ 191
3.5.1. Processors, their types and related terms....................... 192
3.5.2. Computer memory ^ concepts and terms .......................... 202
3.5.3. Functional devices of computer memory .......................... 208
3.5.4. Adapters, Interfaces, and Related Terms....................... 216
3.5.5. Boards, Ports, Buses, Slots....................................... 224
3.6. Peripheral (external) computer devices .............................. 233
3.6.1. External computer memory, drives and related terms ..... 233
3.6.2. CDs and related terms............................... 251
3.6.3. Data input devices, manipulators ........................... 260
3.6.4. Output Devices............................................... 271
3.6.5. Modems, encoders, power supplies....................... 286
3.7. PC Cards ............................................................... .. 289
3.8. Microelectronic computer base .................................. 294
3.9. Optoelectronic devices................................... 299
IV. Software for automated systems .......... 303
4.1. Algorithms, programs, programming.................................... 303
4.1.1. General concepts and terms 303
4.1.2. Programming languages................................... 307
4.1.3. Programming-Related Terms............................... 319
4.2. General software............................... 327
4.2.1. Operating systems................................... 328
4.2.2. General software service tools 338
4.3. Application software for automated systems....... 339
4.3.1. General concepts and terms.............................. 339
4.3.2. Application Programs................................... 342
4.3.3. Computer viruses and antiviruses ........................ 346
4.4. Terms related to the operation of software tools 350
4.4.1. Some general concepts and terms ........................ 350
4.4.2. Archiving, Compressing-Restoring Data Records............... 352
4.4.3. Access, address and related terms.............................. 364
V. Multimedia, hypermedia, virtual reality, machine vision. 372
5.1. Multimedia systems and related terms. ................. 372
5.2. Means of providing musical and speech accompaniment .......... 375
5.2.1. General concepts and terms.............................. 375
5.2.2. Sound files, their standards and formats .................................. 380
5.3. Machine (computer) graphics ........................... 389
5.3.1. General concepts and terms.............................. 389
5.3.2. Graphic files and their formats............................... 392
5.3.3. Computer graphics technology.............................. 400
5.4. Computer Video, Digital Television and Animation .............................. 408
5.4.1. General concepts and terms.............................. 408
5.4.2. Video technology ............................................ 412
5.4.3. Animation Technology.............................. 416
5.4.4. Digital TV 420
5.5. Virtual reality, parallel worlds. ...................... 424
5.6. Computer Vision.............................................. 427
VI. Network technologies. Means of processing and transmitting information 430
6.1. General concepts and terms ............................... 430
6.2. Local Area Networks.............................................. 433
6.3. Distributed Computing Networks.............................. 441
6.3.1. General concepts and terms.............................. 441
6.3.2. Intranet.............................. 450
6.3.3. ETHERNET ............................... 455
6.4. Global Computing Networks, Internet ........................ 471
6.4.1. General concepts and terms.............................. 471
6.4.2. Web Technology.............................................. 482
6.4.3. Technologies for data transmission over Internet channels....................... 489
6.4.4. Services and service tools on the Internet.............................. 499
6.4.5. Integrated Digital Network Services - ISDN .............................. 518
6.4.6. cellular and computer telephony ................... 520
6.4.7. Telecommunication equipment of buildings .................................. 526
6.4.8. Development of technical means and complexes based on the use of telecommunication technologies 532
6.4.9. Subjects of legal relations on the Internet .............................. 533
6.5. Means and technologies for protecting computer networks.................................. 536
6.6. Basic standards for data networks. ....................... 541
6.6.1. ISO Standards ............................................... . 541
6.6.2. IEEE Standards ............................... 543
6.6.3. ITU-T Standards ............................................... 554
6.6.4. Other Standards and Protocols.............................. 560
VII. Computer and network slang .............................. 565
VIII. E-mail Icons and Emoticon Symbols.............. 592
IX. Abbreviations of words and expressions used on the Internet ...... 594
References ............................................... 597
English alphabetical index............................................... 644
Russian Alphabetical Index.................................................. 708

The general name "documentation", which sometimes serves as a synonym for the term "I.". In 1931 the International Bibliographical Institute was founded by P. Otlet and a Belgian lawyer and public figure. La Fontaine in 1895, was renamed the International Documentation Institute, and in 1938 - the International Documentation Federation, which continues to be the main international organization that brings together specialists in . and scientific and information activities (see Documentation International Federation). In 1945, the American scientist and engineer W. Bush published The Possible Mechanism of Our Thinking, in which for the first time the question of the need to mechanize information retrieval was widely raised. International conferences according to scientific information (London, 1948; Washington, 1958) marked the first stages in the development of I. The study of the patterns of scattering of scientific publications carried out was of great importance. Bradford (UK, 1948). Until the mid 60s. 20th century mainly principles and methods of information retrieval and technical means of their implementation were developed. W. Batten (Great Britain), . Muers and. Taube (USA) laid the foundations for coordinate indexing; . Vickery, . Fosket (Great Britain), J. Perry, A. Kent , J. Costello, . P. Lun, . Bernier (USA), . C. Garden (France) developed the fundamentals of the theory and methodology of information retrieval; S. Cleverdon (Great Britain) investigated methods for comparing the technical efficiency of information retrieval systems various types ; R. Shaw (USA) and J. Samin (France) created the first information retrieval devices on microfilms and diamicrocards, which served as prototypes for many special information machines; K. Muller and C. Carlson (USA) proposed new methods of document reproduction, which formed the basis of modern reprography techniques. The present stage in the development of information (the 1970's) is characterized by a deeper understanding of the general scientific significance of scientific information activity and the ever wider use of electronic computers in it. D. Price (USA), developing the ideas of J. Bernal (Great Britain), pointed out the possibility of measuring the development of science using indicators and means of I.; . Garfield (USA) developed and introduced new methods of scientific information service; G. Menzel and W. Garvey (USA) investigated the information needs of scientists and specialists, the importance of various processes of scientific communication. The general theory of I. abroad is formed in the works of A. Avramescu (Romania), A. Vysotsky and M. Dembovskaya (Poland), I. Koblitz (GDR), A. Merta (Czechoslovakia), I. Polzovich (Hungary), . Peach (Germany), A. Rees, R. Taylor, J. Shira (USA), R. Fairthorn (Great Britain) and others. In the USSR, the development of scientific and information activities went hand in hand with the development of Soviet science and the national economy. In the 30s. 20th century the Commission for the Publication of Indexes (Indexes) of Scientific Literature worked, abstract journals of the Academy of Sciences of the USSR in the physical and mathematical sciences, chemistry, etc. began to appear (see Bibliography). This activity began to develop especially intensively from the 50s. The formation of I. as an independent scientific discipline dates back to the end of the 40s and the beginning of the 50s. In the USSR, information was institutionalized in 1952, when the Institute of Scientific Information of the Academy of Sciences of the USSR, now the All-Union Scientific and Technical Institute of Information (VINITI), was established. Since 1959, the Council of Ministers of the USSR has adopted a number of resolutions aimed at improving and developing a unified nationwide system of scientific and technical information. Three all-Union conferences on the automated processing of scientific information (in 1961, 1963, and 1966) were important stages in the development of information technology in the USSR. Of great importance for the development of the theory of I. was the international symposium of the member countries of the Council for Mutual Economic Assistance and Yugoslavia on theoretical problems of computer science (Moscow, 1970), and for the improvement of technical means of I. - the international exhibitions "Inforga-65" and "Interorgtekhnika-66", which demonstrated the technical means of complex mechanization and automation of the processes of processing, storage, search and dissemination of scientific information. Many studies of Russian I. formed the basis for its further development: in the field of the general theory of I. - the work of V. A. Uspensky, Yu. A. Shreider; construction of information retrieval systems - G. E. Vladutsa, D. G. Lakhuti, E. . Skorokhodko, V. P. Cherenina; scientific problems of I. - G. M. Dobrova, V. V. Nalimova; documentaries - G. G. Vorobyova, K. R. Simona,. I. Shamurina; creation of information retrieval devices and other technical means - . I. Gutenmakher, V. A. Kalmanson, B. M. Rakov, and others. I. is divided into the following sections: theory of I. (subject and methods, content, structure, and properties of scientific information), scientific communication (informal and formal processes, scientific information activity), information retrieval, dissemination and use of scientific information, organization and history of scientific information activity. The main theoretical tasks of I. are to reveal the general laws governing the creation of scientific information, its transformation, transmission, and use in various spheres of human activity. I. does not study and does not develop criteria for assessing the truth, novelty and usefulness of scientific information, as well as methods for its logical processing in order to obtain new information. The applied tasks of I. are to develop more effective methods and means of implementing information processes, to determine the optimal scientific communication both within science and between science and industry. For the study of particular problems and the solution of applied problems of information technology, separate methods are used: cybernetics (in formalizing the processes of scientific information activity for their automation, in the construction of information logical machines, etc.); mathematical theory of information (when studying the general properties of information, to ensure its optimal coding, long-term storage, distance transmission); mathematical logic (for formalizing the processes of logical inference, developing methods for programming information algorithms, etc.); semiotics (when building information retrieval systems, drawing up translation rules from natural languages ​​to artificial and vice versa, developing indexing principles, studying text structure transformations that do not change its meaning, etc.); linguistics (in developing the principles of automatic translation and information retrieval languages, indexing and summarizing, methods of transcription and transliteration, in compiling thesauri, streamlining terminology); psychology (when studying the thought processes of creating and using scientific information, the nature of information needs and their formulation into queries, when developing effective reading methods, machine information service systems, designing information devices ); bibliology, library science, bibliography, archival science (when developing optimal forms of a scientific document, improving the formal processes of scientific communication, the system of secondary publications); science of science (when studying the informal processes of scientific communication, developing the organizational principles of an information service system, forecasting the development of science, assessing its level and pace, studying various categories of consumers of scientific information); technical sciences (to provide technical means for the processes of scientific and information activities, their mechanization and automation). Some I. methods, in turn, find application in library science and bibliography (in compiling catalogs, indexes, etc.). Scientific information reflects the objective laws of nature, society and thinking adequately to the current state of science and is used in socio-historical practice. Since the basis of the process of cognition is social practice, the source of scientific information is not only scientific research, but also all types of vigorous activity of people to transform nature and society. Scientific information is divided into types according to the areas of its receipt and use (biological, political, technical, chemical, economic, etc.), by purpose (mass and special, etc.). Hypotheses and theories, which later turn out to be erroneous, are scientific information for the entire time that systematic study and verification of their provisions are carried out in practice. The criterion of use in socio-historical practice makes it possible to distinguish scientific information from well-known or outdated truths, science fiction ideas, etc. The totality of the processes of presenting, transmitting and receiving scientific information constitutes scientific communication. Without exception, scientists or specialists are always involved in all processes of scientific communication. The degree of their participation may be different and depends on the specifics of the process. Distinguish between "informal" and "formal" processes. “Informal” refers to those processes that are mainly performed by scientists or specialists themselves: a direct dialogue between them about ongoing research or development, visiting the laboratory of their colleagues and scientific and technical exhibitions, speaking to an audience, exchanging letters and reprints of publications, preparing research results or developments for publication. The "formal" include: editorial, publishing and printing processes; dissemination of scientific publications, including bookselling, library and bibliographic activities; scientific literature exchange processes; archiving; actually scientific and information activity. All “formal” processes, except for the last one, are not specific to scientific communication and are included in the sphere of mass communication, the main means of which are print, radio, television, etc. The increased complexity of scientific work and the need to increase its efficiency lead to its further division, which takes place in different planes: on theoretical and experimental research, on scientific research, scientific information and scientific and organizational activities. The information services are given to perform increasingly complex tasks of selecting and processing scientific information, which can be solved only with the simultaneous use of the achievements of both information and the theories and methods of specific branches of science. Scientific information activity consists in the collection, processing, storage and search of scientific information fixed in documents, as well as in its provision to scientists and specialists in order to increase the efficiency of research and development. This activity is increasingly carried out by integrated information systems based on the principle of a single exhaustive processing of each scientific document by highly qualified specialists, entering the results of such processing into a machine complex consisting of a computer and a phototypesetting machine, and reusing these results to solve various information problems: publishing abstract journals , bulletins of signal information, analytical reviews, collections of translations, for conducting selective dissemination of information (see Information language), reference and information work, copying documents, and other types of information services. Since the mid 40s. 20th century the first major journals on I. appear in different countries: the Journal of Documentation (L., since 1945); "Tidskrift for Documentation" (Stockh., since 1945); "American Documentation" (Wash., since 1950, since 1970 - "Journal of the American Society for Information Science"); "Nachrichten fur Documentation" (Fr./M., since 1950); "Documentation" (Lpz., since 1953, since 1969 - "Informatik"). Since October 1961, the USSR has been publishing the monthly collection "Scientific Technical information”, which since 1967 has been published in two series: “Organization and Methods of Information Work” and “Information Processes and Systems”. Since 1963, VINITI began to publish first every 2 months, and since 1966 - monthly abstract journal "Scientific and Technical Information", which since 1970 has been published under the name "Informatics". Since 1967 this magazine has also been published in English. The following abstract journals on I. are published abroad: in Great Britain - "Library and Information Science Abstracts" (L., since 1969; in 1950-68 it was called "Library Science Abstracts"), in the USA - "Information Science Abstracts" (Phil. , since 1969; in 1966-68 it was called "Documentation Abstracts"), in France - "Bulletin signaletique. Information scientifique et technique” (P., since 1970). Since 1964, the express information "Theory and Practice of Scientific Information" has been published, and since 1965 - collections of translations of foreign publications on I. Since 1969, a periodical collection "Science and Informatics" has been published in Kiev. The training of scientific workers in I. has been carried out since 1959 through the graduate school of VINITI, the training of personnel for scientific and information activities - since 1963 at the advanced training courses for leading engineering and technical and scientific workers (since 1972 - the Institute for Advanced Studies of Information Workers), the training of young scientists - future consumers of information - since 1964 at the Department of Scientific Information of Moscow State University. M. V. Lomonosov, engineers for the mechanization and automation of information processes - in a number of polytechnic and machine-building institutes. Abroad, information disciplines are taught at universities and higher technical schools. There is a tendency to unite in one educational specialization a complex of problems of I. and computer technology. Lit .: Mikhailov A. I., Cherny A. I., Gilyarevsky R. S., Fundamentals of Informatics, 2nd ed., M., 1968; them, Information problems in modern science, M., 1972; Theoretical problems of informatics. Sat. Art., M., 1968; International Forum on Informatics. Sat. Art., vol. 1-2, M., 1969; Bush V., As we may think, Atlantic Monthly, 1945, July, p. 101-108; Annual review of information science and technology, v. 1-7, N. Y. - a. o., 1966-72; Dembowska M., Documentation and scientific information, Warsaw, 1968. A. I. Mikhailov, A. I. Cherny, R. S. Gilyarevsky.