#### Name

Lutsenko Yevgeniy Veniaminovich

#### Scholastic degree

•

#### Academic rank

professor

#### Honorary rank

â€”

#### Organization, job position

Kuban State Agrarian University

#### Web site url

## Articles count: 271

#### HOW TO SOLVE THE TASK OF CLASSIFICATION OF TYPES OF RIFLE AMMUNITION USING THE METHOD OF ASCANALYSIS

In forensics there is an urgent need to determine the
type of rifle (automatic, rifle, large caliber pistol) depending
on its used ammunition found at the scene of
the use of weapons. We offer a solution to this problem
with the use of new innovative method of artificial
intelligence: automated system-cognitive analysis
(ASC-analysis) and its program toolkitwhich is a universal
cognitive analytical system called "Eidos". In
the "Eidos" system we have implemented the software
interface that allows posting of images and identifying
their outer contours. By multivariable typing, the system
creates a systemic-cognitive model, the use of
which, if the model is sufficiently accurate, may be
helpful in solving problems of system identification,
prediction, classification, decision support and research
of the modeled object by studying its model.
For this task the following stages: 1) input images of
ammunitions into the "Eidos" system and creation of
their mathematical models; 2) the synthesis and verification
of the models of generalized images of ammunition
for types of weapons based on the contour images
of specific munitions (multiparameter typing); 3) improving
the quality of the model by separating classes
for typical and atypical parts; 4) quantification of the
similarities-the differences between specific types of
munitions with generic images of different types of
ammunition of the weapon (system identification); 5)
quantification of the similarity-differences between
types of ammunition, i.e. cluster-constructive analysis
of generalized images of ammunition. A numerical example is given. We also possess a successful experience
of solving similar problems in other subject areas

#### HOW TO SOLVE THE TASK OF CLASSIFICATION OF TYPES OF RIFLE AMMUNITION USING THE METHOD OF ASCANALYSIS

In criminology, there are actual problems of determining
the type (machine gun, rifle, large caliber, pistol)
and a particular model of small rifle for its ammunition,
in particular, discovered in the use of weapons.
The article proposes a solution to this problem with the
use of a new innovative method of artificial intelligence:
automated system-cognitive analysis (ASCanalysis)
and its programmatic toolkit â€“ a universal
cognitive analytical system called "Eidos". In the system
of "Eidos", we have implemented a software interface
that provides input to the system images, and the
identification of their external contours on the basis of
luminance and color contrast. Typing by multiparameter
contour images of specific ammunition, we create
and verify the system-cognitive model, with the use of
which (if the model is sufficiently reliable), we can
solve problems of system identification, classification,
study of the simulated object by studying its model
and others. For these tasks we perform the following
steps: 1) enter the images of ammunitions into the system
of "Eidos" and create mathematical models of
their contours; 2) synthesis and verification of models
of the generalized images of ammunition for types of
weapons based on the contour images of specific munitions
(multivariate typology); 3) quantification of the
similarities-differences of the specific ammunition
with generalized images of ammunition of various
types and models of small rifle (system identification);
4) quantification of the similarities-differences of the
types of munitions, i.e. cluster-constructive analysis

The article discusses the application of automated system-cognitive
analysis (ASC-analysis), its mathematical
model which is system theory of information and
its software tool, which is intellectual system called
"Eidos" for solving problems related to identification
of types and models of aircraft by their silhouettes on
the ground, to be more precise, their external contours:
1) digitization of scanned images of aircraft and creation
of their mathematical models; 2) formation of
mathematical models of specific aircraft with the use
of the information theory; 3) modeling of the generalized
images of various aircraft types and models and
their graphic visualization; 4) comparing an image of a
particular plane with generalized images of various
aircraft types and models, and quantifying the degree
of similarities and differences between them, i.e., the
identification of the type and model of airplane by its
silhouette (contour) on the ground; 5) quantification of
the similarities and differences of the generalized images
of the planes with each other, i.e., clusterconstructive
analysis of generalized images of various
aircraft types and models. The article gives a new approach
to digitizing images of aircraft, based on the
use of the polar coordinate system, the center of gravity
of the image and its external contour. Before digitizing
images, we may use their transformation, standardizing
the position of the images, their sizes (resolution,
distance) and the angle of rotation (angle) in three dimensions.
Therefore, the results of digitization and
ASC-analysis of the images can be invariant (independent)
relative to their position, dimensions and
turns. The shape of the contour of a particular aircraft
is considered as a noise information on the type and
model of aircraft, including information about the true
shape of the aircraft type and its model (clean signal)
and noise, which distort the real shape, due to noise
influences, both of the means of countering detection
and identification, and environment. Software tool of
ASC-analysis, i.e. Eidos intellectual system, provides
identification of the type and the model of airplane by
its silhouette, as it was shown in a simplified numerical
example

The creation of artificial intelligence systems is one
of important and perspective directions of
development of modern information technology.
Since there are many alternatives of mathematical
models of systems of artificial intelligence, there is a
need to assess the quality of these models, which
requires their comparison. To achieve this goal we
require free access to the source data and
methodology, which allows to convert these data
into a form needed for processing in artificial
intelligence. A good choice for these purposes is a
database of test problems for systems of artificial
intelligence of repository of UCI. In this work we
used the database "Iris Data Set" from the bank's
original task of artificial intelligence â€“ UCI
repository, which solved the problem of
formalization of the subject area (development of
classification and descriptive dials and graduations
and the encoding of the source data, resulting
training sample, essentially representing a
normalized source data), synthesis and verification
statistical and system-cognitive models of the
subject area, identify colors with classes, which
serve varieties of Iris, as well as studies of the
subject area by studying its model. To solve these
problems we used the automated system-cognitive
analysis (ASC-analysis) and its programmatic
Toolkit â€“ intellectual system called "Eidos"

In the article, the embodying of operation of integrating of systems, being generalization of operation of
integrating of sets within the limits of system generalization of the theory of sets is considered. This operation is similar to bulean integrating operation of the
classical theory of sets. However, unlike the classical
theory of sets, the concrete algorithm of integrating of
systems in its system generalization is offered and the
quantitative standard system effect (synergetic, emergetic) arising with the application of integrating of
systems is proved. For this standard, the unique name
is offered: Â«The generalized coefficient of emerge by
R.HartleyÂ» because of likeness of its mathematical
form to the local coefficient of emerge by Hartley,
reflecting a degree of difference of system from the set
of its base elements. The reference to the author's program realizing offered algorithm and providing numerical modeling of integrating of systems at various restrictions on complexity of systems and at various
power of generating set is given, some effects of numerical modeling are given

The article describes the application of the Eidos intellectual technologies for the implementation of already developed psychological, pedagogical and profession oriented tests and super tests without programming in the form, convenient for mass testing, for the analysis of the results and the formulation of individual rec-ommendations

In the article the approach to increase of adequacy of semantic information models of management by knowledge after passage by modeled object of a point of bifurcation (change of ergodity period), realized in universal cognitive analytical Eidos system is examined

Results of computational experiments on increasing
of semantic information models adequacy with
different sets of astrosigns by means of separation
of generalized social categories (astrosociotypes) on typical and atypical parts are casted in the article.

The idea of systemic generalization of mathematics was substantiated by the author and the first step on its realization was done: variant of systemic information theory was proposed. There was done an attempt to do the second step in the same way: one of the possible approaches to the systemic generalization of
mathematic understanding of set on the conceptual level, namely the approach, based on systemic information theory. It is supposed that this approach can become the basic one for systemic generalization of set theory and creation of mathematic theory of systems.