Trap method in ensuring data security

This paper presents the results of data analysis from a geographically distributed honeypot network. Such honeypot servers were deployed in Samara, Rostov on Don, Crimea and the USA two years ago. Methods for processing statistics are discussed in detail for secure remote access SSH. Lists of attacking addresses are highlighted, and their geographical affiliation is determined. Rank distributions were used as the basis for statistical analysis. The intensity of requests to each of the 10 installed services was then calculated.

Using high-performance deep learning platform to accelerate object detection

Object classification with use of neural networks is extremely current today. YOLO is one of the most often used frameworks for object classification. It produces high accuracy but the processing speed is not high enough especially in conditions of limited performance of a computer. This article researches use of a framework called NVIDIA TensorRT to optimize YOLO with the aim of increasing the image processing speed. Saving efficiency and quality of the neural network work TensorRT allows us to increase the processing speed using an optimization of the architecture and an optimization of calculations on a GPU.

Increasing signal/acoustic interference ratio in telecommunications audio exchange by adaptive filtering methods

The paper deals with the issues of increasing signal/noise ratio in telecommunication audio exchange systems. The study of characteristics of speech signals and acoustic noises, such as mathematical expectation, dispersion, relative intensity of acoustic speech signals and various types of acoustic noises and interference is carried out. It is shown that in the design of telecommunications systems, in particular loudspeaker systems operating under the influence of external acoustic noise of high intensity, it is necessary to solve the problem of developing algorithms to effectively suppress the above mentioned interference to ensure the necessary signal/noise ratio in communication systems. A mathematical model of the autocorrelation function of the speech signal by using the Lagrange interpolation polynomial of order 10, considered the creation of adaptive algorithms to suppress acoustic noise by linear filtering methods. Thus suppression of acoustic noises and hindrances is possible at the expense of operated change of area of a cutting in the interval from 0 Hz to 300-1000 Hz, depending on a hindrance conditions.

Data-driven profiling of traffic flow with varying road conditions

The article describes the road, institutional and weather conditions that affect the traffic flow. I proposed a method for traffic flow profiling using a data-driven approach. The method operates with macroscopic traffic flow characteristics and detailed data of road conditions. The article presents the results of traffic flow speed and intensity profiling taking into account weather conditions. The study used road traffic and conditions data for the city of Aarhus, Denmark. The results showed that the method is effective for traffic flow forecasting due to varying road conditions.

Multi-channel data storage format definition for visualization tasks on the example of SPOT-4 images

One of the features of a remote sensing data storage is the widespread utilization of large-capacity disk arrays. Emergency situations arising from the use of arrays can lead to the fact that the remote sensing data, usually stored in uncompressed form, may become partially damaged. But even with incomplete recovery, this kind of data can be used in the future to solve production problems. However, this recovery is sometimes hampered by incomplete knowledge of the format of the corrupted data. The article describes an approach to automatic recognition of multichannel data interleaving type (BIP, BIL or BSQ) and its application to a recovery of SPOT-4 remote sensing data stored in the segment format "SEG", which were damaged after a disk array failure.

Big Data, Internet of Things, Augmented Reality: technology convergence in visualization issues

The paper reviews the current situation of the Augmented Reality and Internet of Things markets. The implementing possibilities of AR for Big Data visualization from IoT devices are considered in this paper. The review and the analysis of methods, tools, products and data system of the visualization are presented. The paper provides an overview of the programs and devices of Augmented Reality, and an overview of development environments. The paper presents the existing classifications of computerized data visualization tools and proposes new classification, which takes into account interactive visualization, the purpose of the tool, the type of software product, the availability of ready-made templates, and other characteristics. The article proposes the architecture of the system for collecting data from IoT endpoint devices based on the Heltec modules. Experiments based on the developed experimental stand were carried out with Heltec devices of both versions to determine the number of losses with increasing distance between the sending device and the receiving device. The results of measuring the power consumption of these devices are presented in two modes: in standby mode and when sending a message to the Heltec endpoint device and in standby mode and when receiving a message for the base station. These studies were conducted using various data transfer protocols (LoRa, Wi-Fi and Bluetooth). The paper presents the result of the development of a digital twin of a university building and the development of augmented reality software for receiving data from real-time data collection devices.

Distributed stream data processing system in multi-agent safety system of infrastructure objects

The solution of the problem of resource management in distributed computing systems of processing stream data in safety systems of distributed objects is considered. The tasks of streaming data processing in a multi-level multi-agent evacuation system in an infrastructure object are considered. The features of the mathematical model of a distributed stream data processing system are discussed.

Modelling and forecasting of quasi-periodic processes in technical objects based on cylindrical image models

Accurate forecasting of the state of technical objects is necessary for effective management. The technical condition of the object is characterized by a system of time series of monitored indicators. The time series often have difficultly predictable irregular periodicity (quasi-periodicity). In this paper, to improve the accuracy of such series forecasting, models of quasi-periodic processes in the form of samples of a cylindrical image are used. The application of these models is demonstrated by forecasting of a hydraulic unit vibrations. It is shown that the use of these models provides a higher accuracy of prediction compared with the classical approaches.

Expert system of food sensory evaluation for mobile and tablet

One of the main directions of statistics in sensory evaluation is an assessment of the dependence between experimental variables and measured characteristics. Statistical criteria are used to assess a degree of interaction between variables, a level of experimental effects, and allow accepting or rejecting hypothesis proposed. In sensory evaluation, people act as measurement instruments, and a variation associated with the human factor arises. This proves that the use of statistical methods is necessary. This article represents a network computer system for collection and evaluation of food sensory indicators based on the methods of rank correlation and multifactorial analysis of variance in real time. The article describes information technology of expert sensory evaluation of food quality by individual panelists and sensory panels regarding the indicators that are not measured by technical means of control, based on client-server network architecture. The software implementation of system for collecting and statistical processing of sensory data based on the principles of multifactorial analysis of variance in real-time mode makes it possible to evaluate the influence of the human factor on objectiveness and reliability of sensory evaluation results, as well as to visualize the data of expert scores by various expert panels.

Using ontology merging for the integration of information systems and the production capacity planning system

This article describes the method of integrating information systems of an aircraft factory with the production capacity planning system based on the ontology merging. The ontological representation is formed for each relational database (RDB) of integrated information systems. The ontological representation is formed in the process of analyzing the structure of the relational database of the information system (IS). Based on the ontological representations merging the integrating data model is formed. The integrating data model is a mechanism for semantic integration of data sources.