Каширин И.Ю.

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Characteristic

Characteristics of the department for election to the position of professor


Igor Yuryevich Kashirin, Doctor of Technical Sciences, Professor of the Department of Computational and Applied Mathematics, Honorary Worker of Higher Education of the Russian Federation Kashirin I.Yu., date of birth 18.01.1960, graduated with honors from the Ryazan Radio Engineering Institute (RRTI) in 1982 with a degree in "Mechanization and automation of information processing and issuance processes".
Since 1982, he has worked as a research engineer at the Department of Automation of Information Processes at the RRTI.

In 1984, he entered the full-time postgraduate program of the Computing Center of the USSR Academy of Sciences, which he graduated in 1987 with an early defense of his dissertation for the degree of Candidate of Physical and Mathematical Sciences in the specialty "Mathematical and software software of computers, complexes, systems and networks" on the subject of "Artificial Intelligence". At the same time, he was a responsible executive or the scientific director of research works on the introduction of intelligent systems in the field of logistics of agriculture (VNIIMS), recognized as the most important research projects.

From 1987 to 1988, he worked as a senior researcher at the Department of Automation of Information Technology, received the title of senior researcher. He led research in the field of automation of scientific and technical information processing (Ryazan Central Research Institute). From 1989 to 1996 he worked as an associate professor of the Department of Computational and Applied Mathematics. He led research in the field of intellectual property management of the higher education system of the Russian Federation. Concurrently, he worked as the head of the department of the Scientific and Information Center for Intellectual Property Problems (NITSPRIS, Moscow) at the Ministry of Education of the Russian Federation.

In 1996 he was elected a corresponding member, and in 1998 - a full member of the International Academy of Informatization. In 1998, he was elected Vice-President of the Ryazan branch of the International Academy of Informatization, recognized by UNESCO.

In 1997, he defended his dissertation for the degree of Doctor of Technical Sciences on the topic "Information technology and artificial intelligence".

Since 1998, he has been a professor at the Department of Computational and Applied Mathematics, and received the title of professor. From 2004 to 2008, he was the Vice-rector for Informatization of the Ryazan State Radio Engineering University.

In 2005, he received the title of Honorary Worker of Higher Education of the Russian Federation.

In 2004-2005, he was the scientific supervisor of works in the field of artificial intelligence in fifth-generation avionics (Ryazan State Instrument Plant). Currently, he works as a professor at the Department of Computational and Applied Mathematics. The subject of his scientific works is "Artificial intelligence and information technology".

He was the supervisor of about 20 contractual research projects. He has more than 200 scientific papers, including 12 monographs. Under his leadership, 15 PhD theses have been successfully defended. He is a participant of more than 25 international conferences. For 45 years, the scientific seminar "Theory and Practice of Artificial intelligence" has been operating under his leadership. He developed programs in 17 programming languages, two of which he developed himself with the software implementation of the corresponding compilers.

One of the first in 2007. The Russian Federation has developed and put into commercial operation the Web portal of municipal services of the Ryazan City Administration (Ryazan City Administration).

In 2011, he was the first in Russia to develop and put into commercial operation an electronic kindergarten registration service as well as an electronic queue service for a multifunctional center, which has not yet been surpassed in terms of functionality by any of the similar state Web services. He is still personally involved in the development of Web-oriented software systems, develops and administers the official Internet resources of state-owned enterprises and the administration of the city of Ryazan.
Since 2022, he has been working under a business agreement in the field of Data Mining, Big Data, and neural networks.

The latest results (2023-2024) were hierarchical numbers and ICF ontologies used in practical developments to create artificial neural networks that determine the ideological orientation and presence of mind control tools in English-speaking media around the world.

Definition of Hierarchical Numbers

Kashirin I.

 

Hierarchical numbers are numbers of the form [s] a0 . a1 . a2 . ... . ai . ... .an ,

where ai are positive integers from the set N = {0, 1, 2, 3...}. s is the symbol of the "+" or "-" sign,

a positive sign may not be specified.

 

 

For example, hierarchical numbers may look like this:

 

 

0.0.12.48.0 or -2.33.0.0.4 .

 

 

The symbol denoting the set of hierarchical numbers is H.

 

Applied definition . Hierarchical numbers are a branch of mathematical number theory that allows you to adequately operate on the main characteristics of taxonomies. In the theory of knowledge representation of artificial intelligence, hierarchical numbers allow:

− to determine the semantic similarity of concepts;

− calculate indexes of hyperonyms and hyponyms;

− receive regular knowledge structures;

− verify trees of generic and causal classifications.

 

 

The idea of hierarchical numbers was first proposed in 2020 in an article 

 I.Yu.Kashirin. Hierarchical numbers for designing artificial intelligence ICF taxonomies  / 

2020. № 71.  P.71-82 (rus)

 Let N be a set of positive integers with elements ni ϵ N, let there also be a highlighted character ".".

The set A = N ᴗ "." ᴗ L is defined as an alphabet with integers n, where "ᴗ" is the operation of combining sets, and is an empty character.

Then the grammar is:

ĥ → L,

ĥ → h,

ĥ → - h,

h → < n >,

h → < n > . <h>

describes a set of hierarchical numbers H with elements ĥ.

 

The rule  ĥ → - h   allows for the full range of hierarchical numbers, including the middle negative elements of the number:

 

0.10.-1.-1.127 

 

 These numbers are already used in one way or another in the practice of classification or addressing, for example: a universal decimal code or the IP address of a computer on a global network. However, the introduction of

an algebraic system of hierarchical numbers makes it possible to perform operations with them similar to formal arithmetic, and to isolate binary relations for their comparison and analysis of non-trivial properties of operations and relations.

 

Consider the algebra of binary hierarchical numbers.

 

Let B be a set of numbers with elements {0, 1}, n ϵ B (n = 0 or n = 1), let there also be a highlighted character ".".


The set A = B ᴗ "." ᴗ  L is defined as an alphabet with integers from B, where "ᴗ" is an operation combinations of sets, and L is an empty character. Then the grammar is:


ĥ → L, ĥ → h, ĥ → -h,


h → < n >, h → < n > . <h>


describes a set of binary hierarchical numbers H with elements of h.

 

Examples of binary hierarchical numbers can be given: 0.1.0.0.1 or 1.0.-1.0 .


Binary hierarchical numbers are numerical indices of the vertices of two


binary trees: positive and negative with one common vertex 0.


The generation of a vertex to the left of 0 is performed by the binary operation 0+0 = 0.0, the generation of a vertex to the right is performed by the binary operation 0 + 1 = 0.1.


The generation of negative vertices is performed by the operation "-", respectively:


0-0 = -0.0, 0-1 = -0.1.


Graphically, this can be represented by a tree spreading in a positive or negative direction (Figure 1):

 

Fig 1

 

  

 Figure 1 – An image of algebraic operations in the form of trees

  

However, using negative elements can make the meaning of operations more complicated. For example, the generation of the "+" trace may look like this:


0.1 + 1.1 = 0.1.1.1, 0 + 0.1 = 0.0.1


However, the example 0.0.-1 + 1.1 = 0.0.-1.1.1 indicates the presence of more complex tree travel routes using not only descent but also local ascents. This application of hierarchical numbers will be discussed further with specific examples.


The reverse operation of generation, the removal of the terminal vertex "--", is unary:


0.1.1.1-- = 0.1.1, 0.1.0-- = 0.1, 0.-1.-1 -- = 0.-1.-1 .

 

In graphical interpretation, the number can be considered the absolute index of any vertex, i.e. starting from the top of the tree 0 or relative, displaying the path through the tree from one of any vertices to other vertices up and down.

 

The absolute index always starts with the character 0.


When solving practical problems, only the positive part of the algebra of binary hierarchical numbers can be considered. In this case, operations claiming to receive a negative index will have a result of 0.


One more rather popular operation can be cited, namely, the calculation of the most common vertex, which is interpreted as a search for a common ancestor of two argument vertices: 

 

 Fig 2

 Figure 2 – Another example of hierarchy

 

This generalization/multiplication operation is commutative, i.e. a º b = b º a.

  Multiplying a positive number by a negative number always equals 0.

The important operation is "Ù" as the calculation of the path from the vertex given by the first argument to the vertex given by the second argument. For the previous figure, examples of such calculations could be given:

 

 0.1.0  Ù  0.1.1.1   = 0.1.0.  0.1.  0.1.1.  0.1.1.1

 

  0.1.1.1   Ù  0.1.0  = 0.1.1.1  0.1.1.  0.1  0.1.0

  

 0.1.0.  0.1.  0.1.1.  0.1.1.1    @  0.1.1.1  0.1.1.  0.1  0.1.0

 

 Here “@” relation of equality of lengths of two hierarchical numbers.

 

  However, such a calculation leads to an unnecessarily complex result.

 Note that the common ancestor for 0.1.1.1 and 0.1.0 is 0.1, from which both numbers begin.

 As a result, when calculating the operation Ù vertex to the second.

 This is necessary to get an idea of the complexity of the path from the first vertex to the second, regardless of the depth of the tree.

 Then the correct operation Ù will be like this:

 

 

0.1.0 Ù 0.1.1.1 = [0.1.]0. [0.1.] [ 0.1.]1. [ 0.1].1.1 = 0.1.1.1

 

0.1.1.1 Ù 0.1.0 = [0.1.]1.1 [0.1.]1. [0.1] [0.1.]0 = 1.1.1.0

 

0.1.1.1 @ 1.1.1.0

 

 

After considering the semantics of the above operations, we can define a universal arithmetic algebra of hierarchical 

 numbers H:

                                                 H = < H, Ω >, Ω = {+, -, --, º , Ù, ⊕},

 

where Ω is the signature of the algebra, i.e. many operations.

  All operations are binary, except for "--", which is unary. The meaning of the operation “⊕” will be discussed later, 

 using relevant examples.

 The considered algebra can be supplemented to the algebraic system 

 

H = < H, Ω, R > by introducing a set of relations R = {< , >, @ , = },

 

where the relations “a > b” and “b < a”, respectively, “the number a is more complex numbers b" and "number b is 

 shorter than number a."

 

A brief example of a taxonomy is shown in the figure.

 

fig-g

 

 

 Figure 3 – Brief taxonomy example

 

More examples on this site in articles about icf taxonomies.

Continue. Theory Of Hierarchical Numbers

The idea of hierarchical numbers

-

Binary hierarchical numbers
Kashirin I.Yu. ( Каширин И.Ю. )

 

The simplest description of the theory of hierarchical numbers

for knowledge representation models.

It can be used to calculate the semantic proximity of words and sentences in a natural language. 

The idea of hierarchical numbers was first proposed in 2020 in an article

 I.Yu.Kashirin. Hierarchical numbers for designing artificial intelligence ICF taxonomies/2020. № 71.  P.71-82 (rus)

 

 

They are numerical indices of the vertices of two binary trees: positive and negative with one common vertex 0.


The generation of a vertex to the left of 0 is performed by the binary operation 0+0 = 0.0, the generation of a vertex to the right is performed by the binary operation      0+1 = 0.1.


The generation of negative vertices is performed by the "-" operation, respectively:
0-0 = -0.0, 0-1 = -0.1.


Graphically, it looks like this:

Fig 1

 

 

  The operation of generating the "+" trace may be more complicated:


0.1 + 1.1 = 0.1.1.1
0 + 0.1 = 0.0.1


The reverse operation of generation, removal of the terminal vertex "--", is unary:


0.1.1.1-- = 0.1.1
0.1.0-- = 0.1


To consider a number as an absolute or relative index of the vertex of a binary tree is determined by a person solving an applied problem using hierarchical numbers. The absolute index always starts with the character 0.


Only the positive part of the algebraic system of binary hierarchical numbers can be considered. In this case, operations claiming to receive a negative index will have a result of 0.


Calculating the most common vertex is interpreted as a search for their common ancestor:

  

     Fig 2

 

 

  0.1.1.1 º 0.1.0 = 0.1.0 º 0.1.1.1 = 0.1


This generalization/multiplication operation is commutative. The operation can also be designated as "*".


Multiplying a positive number by a negative number is always 0.


The concept of the inverse element (number) can be described as follows.


What can be said about the numbers 0.1.1.0 and 1.0.0.1 ?
They are obtained by the complete inversion of atomic elements 0 and 1 in all digits.


Multiplying such numbers will always give a zero result. Obviously, these numbers cannot be considered absolute (counted from the root of the tree).

 
However, the access paths to the terminal vertices for these numbers are completely opposite: if we consider "1" to be a positive choice

and "0" to be a negative one, then any descent in the tree one level lower for the first number will be the opposite of the choice determined by the second number.

 

 

When the first number says "yes", the second one definitely says "no" and vice versa.

 
If we always talk only about absolute numbers, then the first digit "0" can be omitted.

 

An important operation is "Ù" as the calculation of the path from the vertex specified by the first argument to the vertex specified by the second argument.

Examples of such calculations can be given for the previous figure:

 

0.1.0 Ù 0.1.1.1 = 0.1.0. 0.1. 0.1.1. 0.1.1.1
      0.1.1.1 Ù 0.1.0 = 0.1.1.1 0.1.1. 0.1 0.1.0

 

0.1.0. 0.1. 0.1.1. 0.1.1.1 @ 0.1.1.1 0.1.1. 0.1 0.1.0

 

Here " @ " is the ratio of the equality of the lengths of two hierarchical numbers.

 

 

However, the common ancestor for 0.1.1.1 and 0.1.0 is 0.1, which is where these numbers begin.

 

 

As a result, when calculating the operation Ù, these fragments are omitted for all vertices of the path from the first vertex to the second.

 

This is necessary to get an idea of the complexity of the path from the first vertex to the second, regardless of the depth of the tree.

 

Then the correct operation is like this:

 

0.1.0 Ù 0.1.1.1 = [0.1.]0. [0.1.] [ 0.1.]1. [ 0.1].1.1 = 0.1.1.1

 

0.1.1.1 Ù 0.1.0 = [0.1.]1.1 [0.1.]1. [0.1] [0.1.]0 = 1.1.1.0

 

0.1.1.1 @ 1.1.1.0

 

 

 

What is considered a right or left descendant? This is in the application of numbers in practice. First, the left descendant is written, then the right one.

Orderliness needs to be specifically specified.

 

(Static Dynamics) (Beautiful Ugly) (Good Bad) (Small Big)


(Simple Complex) (Delicious Tasteless) (Friend Enemy)

(Cause Consequence) (Yesterday Tomorrow)

 

Continue. Theory Of Hierarchical Numbers

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