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Lately, more and more people are talking about the introduction of neural networks, artificial intelligence
systems, and machine learning into various spheres of human activity. This involves new
projects such as unmanned vehicles, DNA sequence decryption programs, vacuum cleaning robots,
spacecraft robots, robots for functioning in harmful environments, human speech recognition systems,
and human speech synthesis. But most often manufacturers of smartphones talk about using artificial
intelligence in their new products.
Currently, many smartphone manufacturers compete with each other in the market for goods and
services, fighting for customers, seeking to draw attention to their products; they are conducting advertising
campaigns in which they claim that their products have artificial intelligence.
A processor with a neuromorphic module emulating artificial intelligence functions allows machine
learning to be used and makes the smartphone as responsive as possible to user habits. A neuromorphic
module can predict which applications the user will soon need, loading them into memory in advance
and optimizing their work. That is, the advertised artificial intelligence is reduced only to setting
up the user's habits using neural-like devices — neural networks.
Now most of the portable devices that use machine learning, have a lack of capacity to run artificial
intelligence programs, so they resort to using cloud servers. But the use of artificial intelligence
programs that work autonomously can significantly improve the performance of smartphones, reduce
the time delay between the user's request and the device's response to this request.
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The article is devoted to the study of various methods of payment fraud in online trading, which
are most common in recent years. The paper describes the features of various types of fraud, effective
and popular programs to prevent fraud in online trading, and investigates the characteristics of the
programs to track suspicious transactions. The article is intended to form an idea of the most common
methods of payment fraud in online trading and a set of measures to prevent them.
The development of modern information and computer technologies affects all spheres of human
life and activity. And even traditional trading is increasingly shifting towards online trading, leading
to various ways of scamming online trading. Fraud in trade is called payment fraud, which refers
to any kind of illegal or improperly executed transaction. Payment fraud is a long-standing problem.
For quite a long time, the favorite method of fraudsters was the theft of a Bank card and subsequent
purchases using this card. This is still happening, but a relatively new type of fraud — online trading
fraud — is becoming more common. There are many schemes of fraud in online trading, some of
which can be called advanced and difficult to prevent, so it may seem that the losses of online stores
in connection with the activities of scammers are inevitable. But modern transaction monitoring technologies
and an advanced authentication system can allow companies from the online trading sector
to minimize these losses.
This article analyzes the different ways of fraud in online trading, their main features. The purpose
of this work is to identify methods of detecting fraud in online trading and develop a set of measures
that can help to track and prevent this fraud. The object of the study are the processes of fraud.
The subject of the study is the methods of fraud detection, and measures to track and prevent fraud.
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This article describes the construction of an expert-diagnostic system (EDS) for analyzing the precrisis
enterprises state of the metallurgical complex using growing pyramidal networks. The development
took into account the analytical results of the main trends in the metallurgical complex of the
Russian Federation development. The use of growing fuzzy pyramidal networks is justified quite reasonably.
The features of computer technology for obtaining expert opinions are considered. Scheme
for combining MatLab modeling software with an expert diagnostic system in the Caché DBMS is
given. The diagram of the main classes in the expert-diagnostic system is considered. Designing and
developing an expert diagnostic system is a technically complex and time-consuming process, involving
the use of intelligent methods for analyzing weakly structured expert information. Therefore, the
search for solutions that reduce the complexity and complexity of the process of design and practical
development of EDS, is currently one of the priorities of the developers involved in this specific area.
Using a growing fuzzy pyramid network based on various financial and economic indicator's analysis
of an industrial enterprise, it is possible to promptly determine the time to reach the pre-crisis state and
develop further actions with the specified enterprise aimed at overcoming crisis situation.
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Lighting devices represent a wide group of lighting products, the main role of the optical system
is to perform the redistribution of light from a light source. Optical calculation of such systems is reduced
to tracing the light rays emitted by light sources, based on their geometric models. The analytical
approach can be used only for very simple forms of optical systems. For the demanded LED lighting
devices, lenses and reflectors are used as optical elements. They allow to obtain various radiation
patterns of LEDs. However, their shape can be very complex. In this case, to simulate the propagation
of radiation in the form of ray tracing, it is advisable to use specialized algorithms. For ray tracing, a
preliminary approximation of the surface by triangular elements is needed, as a result a triangulation
grid is obtained. The search algorithm for the intersection of the ray with the surface is reduced to a
sequential enumeration of all the triangles that make up the optical system of the device, and checking
for the intersection of the ray with the current triangle. The algorithm consists in repeated simulation
of random ray trajectories in the studied medium. The article is also devoted to the description
of the developed algorithm for ray tracing in the optical system and aspects of its implementation in a
C# program. The described algorithm is accompanied by listings and schematic images. This method
allows you to simulate the interaction of light rays with the optical system of the light device and to
obtain the desired light distribution.
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The article deals with the problem of protecting information from the threat of unauthorized access
(theft, destruction, modification). A method of biometric authentication by keystroke dynamics using
an artificial immune system is proposed. Keystroke dynamics is a characteristic dependent on the
time and state of the operator. A feature of the approach is the use of a new architecture of computing
elements (detectors) at the core of the immune system. The detector is a separate measure of proximity,
which determines the distance to the template in the space of only a part of the possible features.
All detectors differ in “interaction interfaces” with a recognizable sample (a set of processed features)
and the principle of sample processing (each detector can be based on a separate measure of proximity).
In the aggregate, the detectors verify the biometric samples for belonging to the classes “Own”
or “Alien”. The developed artificial immune system (network) is capable of self – learning, each authentication
increases the reliability of its solutions. Also, an artificial immune network can determine
the degree of aging of the template and the fact that the user is authenticated in an altered functional
state. This information can be used in the implementation of access control procedures. The experimentally
achieved reliability indicators for solutions EER = 1.5–4% (depending on the state of the
subject). The comparison of the obtained result with the world level in this area has been carried out.
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About 40 years ago, scientists began to think about the consequences of combining quantum mechanics
with a classic Turing machine. Today, before our eyes, a new era is emerging in the field of
information technology, based on the power of quanta. In the paper a brief bibliometric analysis of
the development of research in the field of quantum information processing for the period 2000-2017
is presented. The main global players (countries and groups of countries), as well as sources of sponsorship
of published results are identified. The twists and turns in course of ongoing scientific rivalry
are shown, including benchmarking of Russia against its main competitors. It was established that,
despite the seemingly high level of confidentiality, extensive international cooperation is typical for
research in the field. Considered domestic research landscape. A significant concentration of research
in metropolitan research centers, which is characteristic for this emerging field has been shown; identified
the ten most productive domestic organizations, as well as the scientists who made the largest
publication contribution. The intensity and characteristic structure of international co-authorship
links of Russian scientists, as well as the main domestic and foreign sources of research support are
revealed. Information for analysis is obtained from the most authoritative in the world polythemic database
Science Citation Index Expanded.
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