Information Processing Algorithms Research Articles

A Broadband Information Metasurface-Assisted Target Jamming System for Synthetic Aperture Radar

In recent years, jamming strategies for Synthetic Aperture Radar (SAR) pertaining to target detection and identification, such as the creation of false targets, electromagnetic (EM) deception, and signal spoofing, have been increasingly emphasized. Distinct from traditional SAR jamming approaches, the introduction of an innovative artificial material cloak in SAR target jamming presents augmented capabilities. These methods demonstrate a proficient redirection of incident EM waves in specific or arbitrary directions, effectively masking the vital information linked to critical targets. This study introduces a broadband SAR target jamming system employing an information metasurface that incorporates intelligent information processing algorithms in conjunction with a space-time-coding digital metasurface, endowing it with the capacity to adeptly modulate incident EM waves. This integration facilitates a versatile approach to jamming, enabling the deployment of multi-mode protective measures against critical targets. The conducted simulation and experiment results validate the system’s ability to adjustably produce EM deception and generate multiple false targets independently of the SAR system. The outcomes of this research significantly advance the practicality of SAR protection strategies, pushing the boundaries toward more dynamic, broadband, and controllable scenarios, thereby substantially improving the concealment of critical targets in highly sensitive conflict areas.

Design and Application of Intelligent Transportation Systems Based on Optoelectronic Information Processing and Time-optimal Algorithms

The project employs photoelectric information acquisition technology and integrates it with an intersection waiting time optimization algorithm to achieve traffic light control at urban intersections through photoelectric acquisition, data analysis, data processing, and module control. Its objective is to efficiently and effectively address the issue of traffic congestion at intersections, providing a solution for the development of intelligent urban transportation.

ИНСТРУМЕНТАРИЙ БУХГАЛТЕРСКОГО УЧЕТА В ЦИФРОВОЙ ЭКОНОМИКЕ И ЕГО ГАРМОНИЗАЦИЯ

The paper examines the issues of using accounting tools necessary to systematize information on the performance of economic entities of various groups: commercial organizations of the real sector; non-profit organizations of the real and public sectors; organizations of the budgetary sphere; taking into account the possibility of its harmonization in order to bring together the methodology of national accounting for external and internal control of the reliability of information. The characteristics of the main accounting tools are given, taking into account the content of the requirements of modern legal regulation. The methodological basis of the work was general scientific principles and research methods: analysis and synthesis, logical linking, systematization. The author’s position on the issue of harmonization of accounting tools for economic entities of various groups in relation to accounts and accounting registers is presented. The proposed structure of the accounting account is based on the structure of the budget accounting account, since its structure is more suitable for detailing information that can be used for management purposes, which is especially important in modern conditions. Accounting registers can be harmonized based on those used in the public sector. Transaction journals group information in a chronological and systematic manner based on the source document, indicating its number and date, which is preferable from the point of view of internal control. For commercial organizations, they can also be generated in an accounting program. The need to harmonize accounting tools is due to the fact that federal standards for the commercial sector and the public sector implement the same principles of accounting and reporting. Conceptual approaches to accounting are disclosed in the Law «On Accounting», establishing the same accounting rules for the same objects of accounting supervision. The proposed author’s approach to the harmonization of accounting tools for various groups of economic entities, and its use to reflect information about accounting objects, can be implemented in the process of improving legal regulation in order to control the activities of commercial organizations, especially those that receive funding from state budget. The main results obtained by the author make it possible to standardize information processing algorithms in the digital environment.

INFORMATION CAPABILITIES OF THE TRANSITION FUNCTION OF THE HYDROGEN STORAGE AND SUPPLY SYSTEM GAS GENERATOR TO ASSESS ITS FIRE HAZARD LEVEL

To estimate the level of fire hazard of hydrogen storage and supply systems, it is advisable to use reliability indicators, in particular, of their core element, which is a gas generator. Such indicators include indicators of amplitude and phase reliability of the gas generator, which are determined through the Laplace function. The arguments of this function are the relative errors of the parameters of the gas generator, which are determined by its transition function. Three options for determining the parameters of the gas generator have been developed, the feature of which is obtaining information about its parameters at two a priori given moments. The magnitudes of these moments do not exceed the time of the transient process. In the a priori specified moments, the values of the transient fraction are measured (option 1), and the values of its derivative (option 2) or the value of the integral of the transient function (option 3) are additionally measured. Algorithms for processing the received information have been developed for all options, the implementation of which ensures the determination of gas generator parameters. In terms of its structure, the second option for determining gas generator parameters is the simplest, which has 1.5 times fewer arithmetic operations compared to the first option. In addition, the second option for determining the parameters of the gas generator is invariant to the value of the time parameters that determine the measurement moments. The results of determining the parameters of the gas generator and their nominal values are used to determine the arguments of the Laplace functions. We have specified that when determining the parameters of the gas generator, the complexing method can be used, which involves the implementation of all three information processing algorithms. As an example of the second option of determining gas generator parameters, the structural diagram of the algorithm is presented. We have emphasised that the implementation of the developed algorithms for determining the parameters of the gas generator has no subjective factor associated with the use of expert judgments. Keywords: gas generator, fire hazard level, transition function.

Automated models of visual information processing

The article presents a study devoted to the development and research of an automated model of visual information processing. The goal of the research was to create a comprehen-sive model capable of automatically processing and analyzing various forms of visual data, such as images and videos. The model is developed on the basis of a combined approach that combines various algorithms and methods of visual information processing. The literature review conducted within the scope of this study allowed us to study the existing methods and algorithms for visual information processing. Various image processing approaches were analyzed, including segmentation, pattern recognition, object classification and detection, video analysis, and other aspects. As a result of the review, the advantages and limitations of each approach were identified, as well as the areas of their application were determined. The developed model showed high accuracy and efficiency in visual data processing. It can suc-cessfully cope with the tasks of segmentation, recognition and classification of objects, as well as video analysis. The results of the study confirmed the superiority of the proposed model. Potential applications of the automated model are considered, such as medicine, robotics, security, and many others. However, limitations of the model such as computational resource requirements and quality of input data are also noted. Further development of this research can be aimed at optimizing the model, adapting it to specific tasks and expanding its func-tionality. In general, the study confirms the importance of automated models of visual infor-mation processing and its important place in modern technologies. The results of the research can be useful for the development of new systems based on visual data processing and con-tribute to progress in the field of computer vision and artificial intelligence.

Tensometric measurement system for experimental research of mechanisms, machines and robots

The paper shows a tensometric measurement system for the experimental research of mechanisms, machines and robots. The tensometric measuring system is built on the basis of intelligent digital sensors of the ZETSENSOR series with a CAN interface. The information processing algorithm and the visualization of the measured signals is carried out using the ZETLAB SENSOR software. The tensometric measurement system is used to determine such parameters as: displacement, forces, deformations and stresses in the links of mechanisms, machines and robots. A tensometric measurement system was used for the experimental study of the crank press. The obtained experimental results confirmed the simplicity and convenience of its use for dynamic measurements.

Effective detection algorithm of electronic information and signal processing based on multi-sensor data fusion

Appropriate vibration diagnostics when cutting a variety of products is critical for cutting quality and scrap and consumables reduction. Collecting and combining data from various sensors allows for real-time data collection during processing for system monitoring. The purpose of this study is to develop a method for effectively diagnosing milling machine vibrations using multi-sensor data fusion. It is proposed that sound and frequency signals be preprocessed to isolate specific vibration features, and then classified and aggregated for a complete vibration diagnostics system. After preliminary wavelet signal conversion, a deep belief network has been developed for each sensor to classify vibration features. When combining classification results, the fuzzy Choquet integral algorithm is used. Thus, a comprehensive judgment is obtained. It has been demonstrated that for neural networks, 100 epochs are sufficient for learning to take place. It has been discovered that the accuracy of classification and inference of the correct solution increases from 75% to 98% as the number of vibration feature combinations increases. When compared to the Dempster-Schafer evidence theory, the fuzzy integral fusion algorithm provides a high level of vibration detection accuracy of up to 98.7%. The resulting diagnostic procedure is simple and effective. It can be used to control the cutting process on machine tools in industrial settings. Improvements to the scheme are suggested, including the use of intelligent technologies to automate the process.

System-Information and Cognitive Technologies of Man-Made Infrastructure Cyber Security

The complication of technological processes due to the modernization of complex technological processes aggregates with a distributed spatial infrastructure requires the use of new control systems and computer and information network technologies. Accordingly, this poses the problem of revising the basic concepts of information-measuring systems building, developing software and hardware for the implementation of the target management process. This requires development of new approaches to presentation, processing, and display of data about the aggregates state of energy-active objects and the entire information structure. For management under threat conditions, it is necessary to take into account the features of the information infrastructure, data selection and processing methods, methods and algorithms for classifying the situation, which are formed from blocks of data obtained from each unit and the technological process as a whole. Information about the current state of system and infrastructure is necessary for the formation, adoption and implementation of management decisions which is the basis for coordination strategies synthesis. Appropriate target orientation, reasonable indicators of real process trajectories divergence from the target state determine the probability of object attack. Knowledge and decision-making procedures for the coordination of managerial actions is based on the strategic target orientation of the structure, their professionalism and the level of intellectual, cognitive and scientific training which is the basis for correct situation interpretation of countermeasures against threats formation. In the event of active threats complex on man-made systems in a certain region (resource, cognitive, system, information) and natural disasters or military operations, the threats lead to active destruction or failure of the production process. In order to functionally withstand related production structures, when loyal to the industrial relations concept, they need to integrate at the strategic management level on common goal basis to reduce risks. If necessary, to increase sustainability, they can be integrated at operational management level using interconnections at the production and resource levels. To do this, it is necessary to develop a strategic and goal-oriented management system behaviour line, which requires informational and intelligent data processing at the highest level using cognitive creative methods. For each level of the infrastructure hierarchy, oriented towards strategic goals in the global infrastructure dynamic environment, methods of assessing the situation to detect failures and the actions of attacks have been developed, based on which countermeasures are formed depending on the type of threats.

Smart Clothing System With Multiple Sensors Based on Digital Twin Technology

Smart clothing is widely used for social safety, health monitoring, and sports monitoring. Current research focuses on the use of various materials or sensors to implement smart clothes with different functions, which implies that the functionality of smart clothing depends on the number of sensors used. For existing smart clothing systems, the greatest attention has been given to information processing algorithms and assembly of sensors, and the interaction between users and systems is ignored. To address this gap, this article considers a multifunctional smart clothing system constructed with several sensors. The smart clothing system proposed in this article mainly consists of a hardware module and a software module. Four types of sensors are incorporated into the hardware module to monitor the heart rate, blood oxygen saturation, body temperature, locating information, and activity states; the software module includes the 3-D model based on the user and the feedback system based on digital twin (DT) technology. The DT technology can map the fundamental states of users in terms of the monitoring indices from the hardware module, and give correspondent advice to users. This novel smart clothing system overcomes the lack of an interaction function in existing methods and introduces DT technology into smart wearable devices for the first time.

Hinged Set of Guidance of a Controlled Fire-extinguishing Bomb

The guidance system of a fire-extinguishing bomb in the form of a hinged guidance kit is considered, which turns the bomb into a simple and fairly cheap fire-extinguishing device of the "throw and forget" type, optimized for mass production and use. In order to increase the accuracy of dropping a fire-extinguishing bomb, it is proposed to install a cheap high-precision and compact GPS navigation satellite system and a strapdown inertial system on an ordinary fire-extinguishing bomb. The algorithm of complex information processing of their systems, built on the basis of the improved method of the mutual compensation, in which for improve the quality of the error estimation procedure, the sluggishness of second-order Butterworth filters is compensated is proposed. The guidance system controls the trajectory of the fire-extinguishing bomb as a means of "first strike" and this increases the efficiency of further use of traditional flood systems by 50...70 times.

Information Processing Algorithms in the Steel-Teeming Ladles Tracking System in Steelmaking

Purpose of research. The purpose of research is to increase the efficiency of control over the movement of steel ladles in steelmaking, through the development of mathematical and software.Methods. The control of the movement of steel-pouring ladles can be divided into 2 parts: the first is the object detection in the image from a camera located on a certain section of the route, followed by determining the position of the object in the frame, and the second part is identification based on an array of data from different systems. Methods used in research are: mathematical modeling, neural networks, the basics of the theory of algorithms construction, as well as software and hardware of modern computer technologies. The article describes a model for the routes generation for the movement of steel ladles, on the basis of which the control of the movement of steel ladles is carried out. Algorithmic support is a combination of such algorithms as: an algorithm for generating possible routes for moving steel ladles, an algorithm for determining the position of a steel ladle on a route for moving steel ladles, an algorithm for identifying a steel ladle and a generalized algorithm for processing information. The structuralfunctional organization of the tracking system for steel-pouring ladles in steel-smelting production is given.Results. Experimental verification of algorithmic support was carried out on a test data set, which was formed from real technological data. Adaptation and tuning of the algorithms and software will make it possible to apply this software system in steelmaking plants with a different composition of plant units.Conclusion. Control over the movement of steel ladles allows build the process so that the movement of liquid steel will cause minimal heat loss. The need to heat steel in secondary processing units is correlates with energy costs. Thus, reducing heat loss and downtime of steel ladles will reduce energy costs for the entire process.

Approach and Algorithm for Evaluating the Allowed Signal/Noise Ratio of Robotic Lidars under External Influences

Purpose or research. The aim of the study is to ensure the safe operation of robotics by developing methods, approaches and algorithms for information processing, and describing their functioning.Methods. The paper proposes an approach to estimation allowed signal/noise ratio (SNR) for robotic LiDARs based on the predetermined probability of occurrence of «false alarm» under unintended influences. The synthesized probabilistic approach is based on the physical fundaments of infrared radiation, and the Bayesian theory using the Neyman-Pearson criterion. The feature of the proposed approach is the use of the given threshold of «false alarm» occurrence, and the probability of occurrence of interference in the analytical apparatus, as well as consideration of the characteristics of photodetectors. This allows expressing analytically and calculating the value of the allowed SNR when stabilizing the level of «false alarms» against background noise caused by this type of interference.Results. The formed and presented dependencies can be used as one of the operating characteristics in the development and selection of optoelectronic system of LiDAR’s measurement system. Based on the fixed value of «false alarm», and the resulting graphical expression of the operating characteristic (obtained characteristics) it is possible to choose a LiDARs system with necessary technical parameters.Conclusion. The probabilistic approach and the corresponding algorithm for selecting the threshold SNR value based on the Neyman-Pearson criterion were developed. The approach allows minimizing the probability of «ignoring» the object when scanning, since the probability of «false alarm» does not exceed the given threshold value. Mathematical and methodological support for the design of LiDARs is presented, taking into account a priori estimation of the allowed SNR value, and the probability of reflected pulse detection, without preliminary estimates of probabilistic characteristics of object detection. The presented algorithm has a set of raw data (in the form of the values of the received signal with a noise component) as an input. Its output is represented by a set of error probability dependencies for different SNR thresholds.

The Coupled Reactance-Less Memristor Based Relaxation Oscillators for Binary Oscillator Networks

This paper discusses the application of coupled reactance-less memristor-based oscillators (MBO) with binary output signals in oscillatory networks. A class of binary-coupled memristor oscillators provides simple integration with standard CMOS logic elements. Combining MBOs with binary logic elements ensures the operation of complex information processing algorithms. The analysis of the simplest networks based on MBOs is performed. The typical reactance-less MBO with current and potential inputs is considered. The output responses for input control signals are analyzed. It is shown that the current input signal impacts primarily the rate of memristor resistance variation, while the potential input signal changes the thresholds. The exploit of the potential input for the synchronization of coupled MBOs and current control input in order to provide the necessary encoding of information is suggested. The example of the application of coupled MBOs in oscillatory networks is given, and results of simulation are presented.

РАЗРАБОТКА СИСТЕМЫ МОНИТОРИНГА БЕЗОПАСНОСТИ ИНФОРМАЦИОННОЙ СРЕДЫ ПРЕДПРИЯТИЯ

The relevance The urgency of ensuring information security (IS) is due to the increase in the volume of information circulating in local area networks (LAN) and the expansion of the range of tasks solved with the help of information systems (IS), there is a problem associated with an increase in the number of threats and increased vulnerability of information resources. This is due to the action of factors such as: expanding the range of tasks solved by the IP; increasing the complexity of information processing algorithms; increasing the volume of processed information; complication of LAN software and hardware components, and, accordingly, an increase in the likelihood of errors and vulnerabilities; increased aggressiveness of external data sources (global networks); the emergence of new types of threats. Traditional means of ensuring the information security of corporate networks include antiviruses, vulnerability detectors, firewalls and intrusion detectors. The functions of such information security systems are specific and solve individual tasks of ensuring the information security of a corporate network and, as a rule, can be overcome with the teamwork of a qualified group of violators. Such groups are aware of the capabilities of the security tools used in the corporate network, respond to updates of the vulnerability database of widely used software (software) published in special publications and the Internet, promptly exchange the results of probing the protection of the attacked corporate network and flexibly change the tactics of the invasion. Aim of research Implementation of Zabbix SCS monitoring system and pfsense firewall/ router with implementation of information traffic management. Research methods: — Zabbix programming environment; — pfsense programming environment. Results This article discusses the creation of the Zabbix monitoring system and the pfsence system at the AST LLC enterprise, Bashkortostan Republic, Sterlitamak. As a result of the configuration and creation of rules, as well as the implementation of SCS monitoring, the enterprise receives a system of protection against unauthorized access and a system of protection against corporate network attacks.

Development of a gesture-based system of interaction with the interface of adaptive information systems

The implementation of gesture control is an actual direction in the field of organizing interaction with adaptive information systems. This study considers the development of a neural network-based gesture control system for hand recognition and gesture classification. When implementing such systems, it is necessary to ensure the maximum accuracy of gesture recognition, as well as high performance (video stream processing speed). At the first stage of the study, the task of optimizing gesture control system was posed, including analysis of the information processing algorithms used for optimization according to the criteria of classification accuracy and performance. In the course of solving the optimization problem, the structure and parameters of the neural network were determined that provide the best accuracy indicators, and the necessary changes were made in the software of the gesture control system to achieve the required level of performance. The developed software for the gestural interaction system was tested when integrating with the interface of adaptive information systems implemented on the basis of the Unity game engine. The results obtained can be used in the implementation of interfaces for interaction with virtual reality with a high level of immersion.

Reconfigurable matrix multiplier with on-site reinforcement learning.

Matrix multiplication is a fundamental building block for modern information processing and artificial intelligence algorithms. Photonics-based matrix multipliers have recently attracted much attention due to their advantages of low energy and ultrafast speed. Conventionally, achieving matrix multiplication relies on bulky Fourier optical components, and the functionalities are unchangeable once the design is determined. Furthermore, the bottom-up design strategy cannot easily be generalized into concrete and practical guidelines. Here, we introduce a reconfigurable matrix multiplier driven by on-site reinforcement learning. The constituent transmissive metasurfaces incorporating varactor diodes serve as tunable dielectrics based on the effective medium theory. We validate the viability of tunable dielectrics and demonstrate the performance of matrix customization. This work represents a new avenue in realizing reconfigurable photonic matrix multipliers for on-site applications.

Study of the machine learning algorithms’ effectiveness for traffic classification in mobile networks

The development of mobile networks and implementation of new standards, such as 5G and 6G, in the future, will lead to increased traffic volume in the network and new types of traffic creation. Also, new traffic types demand specific service requirements. Currently, existing traffic processing methods are not adapted to such changes, which can impair the Quality of Service. A possible solution for improving the efficiency of information processing is introducing new algorithms for classifying and prioritizing traffic. That is why in this work, the main focus is on analyzing the effectiveness of machine learning algorithms to solve the problem of traffic classification in mobile networks in real-time. The accuracy of classification and performance for the most common machine learning algorithms is analyzed, and the criterion of classification accuracy determines the optimal algorithm to achieve the goal. The results of the comparative analysis showed that the best accuracy could be achieved when using ANN algorithms (the number of latent network layers is 200) and RF. At the same time, the advantages of ANN include high efficiency and reliability of information processing and simple algorithm learning. Also, the RF algorithm is a quick and powerful classification algorithm, but it has shortcomings during the interpretation of the solution and works poorly for small data. In addition, the work assessment of the importance of the dataset fields for classification was evaluated. These improvements can be implemented both on final devices and base stations. They will improve the quality of classification, clustering, and processing of packets, which will generally increase the efficiency of the intellectual mobile network management system. Further development of the topic may be using the studied algorithms to solve the problems of detecting anomalies in traffic to increase the network’s security.

Modelling Conformational Flexibility in a Spectrally Addressable Molecular Multi‐Qubit Model System

AbstractDipolar coupled multi‐spin systems have the potential to be used as molecular qubits. Herein we report the synthesis of a molecular multi‐qubit model system with three individually addressable, weakly interacting, spin centres of differing g‐values. We use pulsed Electron Paramagnetic Resonance (EPR) techniques to characterise and separately address the individual electron spin qubits; CuII, Cr7Ni ring and a nitroxide, to determine the strength of the inter‐qubit dipolar interaction. Orientation selective Relaxation‐Induced Dipolar Modulation Enhancement (os‐RIDME) detecting across the CuII spectrum revealed a strongly correlated CuII‐Cr7Ni ring relationship; detecting on the nitroxide resonance measured both the nitroxide and CuII or nitroxide and Cr7Ni ring correlations, with switchability of the interaction based on differing relaxation dynamics, indicating a handle for implementing EPR‐based quantum information processing (QIP) algorithms.

Modelling Conformational Flexibility in a Spectrally Addressable Molecular Multi-Qubit Model System.

Dipolar coupled multi-spin systems have the potential to be used as molecular qubits. Herein we report the synthesis of a molecular multi-qubit model system with three individually addressable, weakly interacting, spin centres of differing g-values. We use pulsed Electron Paramagnetic Resonance (EPR) techniques to characterise and separately address the individual electron spin qubits; CuII , Cr7 Ni ring and a nitroxide, to determine the strength of the inter-qubit dipolar interaction. Orientation selective Relaxation-Induced Dipolar Modulation Enhancement (os-RIDME) detecting across the CuII spectrum revealed a strongly correlated CuII -Cr7 Ni ring relationship; detecting on the nitroxide resonance measured both the nitroxide and CuII or nitroxide and Cr7 Ni ring correlations, with switchability of the interaction based on differing relaxation dynamics, indicating a handle for implementing EPR-based quantum information processing (QIP) algorithms.

Office of Naval Research Undersea Signal Processing, Contributions of Dr. Lisa Zurk

The Undersea Signal Processing team at the Office of Naval Research (ONR 321US) is tasked with developing advanced active/passive sonar signal and information processing technologies that improve the anti-submarine warfare (ASW) performance of US Navy sonar systems. Pursuant to this goal ONR supports academics whose research, being on the cutting edge, lead to high-risk technologies with potential for the greatest advancement of fleet capability. Dr. Lisa Zurk was such an academic, first supported by ONR 321US in 2005. Dr. Zurk’s research focused on developing signal and information processing algorithms which exploited the physics of the underwater operating environment. She believed the path to significant gains in sonar system performance would be obtained through exploitation of environmental knowledge. This belief is now a realization within the Naval Research Enterprise (NRE) and was a primary motivation for initiation of the ONR Task Force Ocean (TFO) Program in 2017. From establishment of the NEAR-Lab at Portland State University in 2005 until her transition to a Program Manager at the Defense Advanced Research Projects Agency in 2016, Dr. Zurk made significant contributions to the NRE. This presentation looks to highlight these past contributions and to consider their present impact.