The paper proposes a version of realization for a fiber optic vibration sensor. The sensor possesses a wide range of operation frequencies with such interrogation devices as optical power meters. In comparison to spectral measuring complexes, the sensor imposes lower requirements on operating conditions. The authors investigated a sensing head based on a fiber SMF-MMF-SMF structure and a fiber Bragg grating inscribed in this structure. The external vibration frequency applied to the tested sensor structure is obtained using the Fourier transform of the signal received from the photodetector. The structure designed in this study with a fiber Bragg grating inscribed in it can be used as a sensing head of a fiber optic vibration sensor. It is demonstrated that the sensor based on the developed sensitive structure is able to obtain the external vibration frequency in the range of 20-9000 Hz with accuracy up to 1%. The research results are essential for monitoring systems for the state of structural elements of buildings and structures. The implementation of the vibration sensor in the format of a fiber optic device allows overcoming the limitations of piezoelectric sensors, providing high noise immunity and resistance to harsh environmental effects.

The paper considers the optical systems of virtual reality, which use an optical wedge to eliminate or reduce the conflict of convergence and accommodation (vergence-accommodation conflict, VAC). The inclined surfaces of the optical wedge introduce specific aberrations into the optical system that can critically affect image quality. The authors analyzed wedge aberrations using relationships derived from the third-order aberration theory. In contrast to existing approaches, the relationships were obtained without the assumption of a small refractive angle or wedge thickness. The results demonstrate that in the scheme with an optical wedge, with characteristics typical for virtual reality systems, the dependence of astigmatism on the angular field is linear and significantly exceeds the other types of aberrations. It is shown that to obtain a high-quality image, the most successful compensation for such aberration can be achieved by using diffractive optical elements (kinoforms) or a Fresnel lens. The paper gives examples of optical systems with a wedge, developed taking into account the requirements for the overall dimensions of virtual reality systems and image quality. The obtained ratios for the aberrations of the optical wedge and the inclined surface make it possible to evaluate the correction capabilities of schemes where such elements are used with arbitrary characteristics. The proposed solutions can be used in virtual reality systems with a reduced value of vergence-accommodation conflict.

The use of algorithmic temperature compensation requires that the external temperature sensor data and the thermal response of the fiber optic sensor should be synchronized. The paper considers an approach to estimate the temperature detection delay for the external temperature sensor in a sensing coil assembly of a fiber-optic gyroscope. The delay estimation is based on a cross-correlation of temperature data from an external temperature sensor and temperature data of an optical fiber segment obtained by distributed temperature measurement based on optical frequency reflectometry. The results include the estimation of temperature detection delay between the sensing coil and the temperature sensor. The described approach allows evaluating temperature detection delay in a sensing coil assembly of a fiber-optic gyroscope. In case of using multiple temperature sensors, the delay for each temperature sensor can be estimated and taken into account to improve the efficiency of the thermal drift compensation of the fiber optic gyroscope.

The research deals with the topical problem of stabilizing the optical parameters of a single-mode vertical-cavity surface-emitting laser. A solution to the problem is proposed by forming an external cavity based on a Bragg grating induced into an optical polarization-maintaining fiber. In this experimental research, the authors estimated the contribution of an external cavity to the relative intensity noise of a vertical-cavity surface-emitting laser. The stability of the laser generation with a varying phase of back reflections at various pump currents is investigated. The relative intensity noise of laser radiation in the pump current range of 1.1–6.3 mA is estimated using a photodetector with a bandwidth of 8.5 MHz. The phase change of the back reflections was carried out by shifting the optical fiber end with a 100 nm step. As a result of the research, it was obtained that the vertical-cavity surface-emitting laser with such an external cavity shows a stable emission in the current range of 1.8–3.2 mA. However, one can observe instability with constant switching between adjacent longitudinal modes outside this range. The most stable laser operation mode with an external cavity against a change in the phase of back reflections is registered at a pump current of 2.78 mA. Utilizing an external cavity with the fiber Bragg grating made it possible to reduce the relative intensity noise from 7.2∙10–10 1/Hz to 1.5∙10–11 1/Hz in the currents range 1.86–3.2 mA. The study can be useful in applications that require an optical radiation coherent source with a low relative intensity noise level (such as coherent optical communication or fiber-optic sensors).

The paper investigates the frequency characteristics of the spectra of a human eye and a faceted diamond (brilliant). The relevance of the research deals with a large number of modern studies on the use of diamond as a lens of the eye. The results obtained were compared with the averaged data (described in the literature) on the visibility curve of day, evening and night vision of the human eye. The research method is based on the representation of the optical environment of the human eye and diamond in the form of a dynamic link with an input and output. The Gaussian function is used to approximate the spectral curves. The study of the inertial properties of such a link in the time domain is performed by feeding signals to its input in the form of a δ-function or a unit function. The steady-state forced oscillations at the output of the investigated dynamic link are found when a harmonic action is applied to the input. Frequency characteristics discover a relationship between the spectra of the input and output signals, representing the direct Fourier transform of the function of time. It was found that the spectra of the visibility of the human eye and the luminescent radiation of diamond have the properties of ultra-wideband signals. It is shown that the amplification of light takes place in the time domain when the width of the spectrum at its half-maximum does not exceed a certain critical value. This phenomenon also manifests itself in the frequency domain. It was revealed that the dynamic links of diamond and human eyes for day and night vision exhibit amplifying properties. Their comparison in terms of the light amplification factor showed their insignificant difference. The results obtained can find application in the creation of matrix photodetectors and as a standard in identifying a faceted diamond (brilliant) of unknown origin and producing a lens from a diamond.

Quantum communication protocols are considered secure provided that all devices included in the system are fully characterized, and side channels are closed. However, as a result of laser radiation exposure, it is possible to change quantum communication systems components’ characteristics. This leads to vulnerabilities appearing in the quantum key distribution system. In this paper, we consider the effect of pulsed laser radiation on fiber-optic isolators used in quantum communication systems. Isolators protect the source of the system from attacking optical radiation coming from the “eavesdropping” side via the quantum channel. Lowering the isolation factor can bring the entire system out of a secure state. This gives an eavesdropper access to information about the secret key. The scenario of the most probable attack to the source of the quantum key distribution system via a pulsed laser was simulated. The experimental setup provided exposure of fiber isolators with pulsed laser radiation at a wavelength of 1064 nm (within the transparency window of the isolators) with a mean power up to 840 mW in four different pulse generation modes. The isolation factor and throughput of tested samples were monitored using a laser diode with a wavelength of 1550 nm and average power of 10.5 mW. Spectrally selective splitters were used to separate the lasers. It is shown that the isolation factor (isolator attenuation in the direction from the quantum channel to the system) at a wavelength of 1550 nm decreases from the initial value of 59.1 dB to 24.5 dB. The throughput (in the direction from the system to the quantum channel) at the same wavelength decreases from 0.6 dB to 1.2–12.3 dB or remains the same, depending on the acting pulsed laser radiation parameters. Temperature monitoring showed that the temperature of the isolator body changes insignificantly when exposed to pulsed radiation. The obtained effects of changing the isolation coefficient and throughput can be explained by the presence of nonlinear effects in the magneto-optical crystal of the isolator. The results of the work can be applicable in the practical evaluation of quantum communication systems security, in particular, the security evaluation of quantum key distribution systems. The results can be used to prepare the standards for certification procedures for assessing the security of quantum communication systems. The work gives recommendations for enhancing signal source unit security in quantum communication systems. Namely, as countermeasures to protect against the effects of pulsed laser radiation, it is proposed to set optical fuses with a limited threshold power, detectors for monitoring input optical radiation power, and narrow-band optical filters at the entrance of the quantum communication system.

The article considers issues of increasing the target performance of the spatial monitoring system expressed in the maximization of the number of detected search objects under the influence of destabilizing factors. It is shown that such a task can be solved by integrating simulation modeling and artificial intelligence in the modeling and forecasting module of the proactive management subsystem of the spatial monitoring system. Within the framework of the proposed approach, the simulation model allows generating many variants of the course of an antagonistic conflict and is used as a training ground for the neural network module, which is responsible for the structure of the spatial monitoring system. The interaction between the neural network module and the simulation model is realized by integrating a mental agent into the simulation model with reinforcement learning. It is revealed that the proposed integration is possible by applying an agent-based approach. Based on this approach, the paper presents a structural and functional description of the simulation model for the spatial monitoring system that functions under the influence of destabilizing factors. The results of simulation modeling, which confirm the effectiveness of recommendations to manage the elements of the system using the neural network module trained during the simulation, are also presented. The comparison with the basic strategy of the object search is executed. The authors outline the prospects of applying the neural network technology and reinforcement machine learning in the proactive control subsystem of the spatial monitoring system and ways to achieve them.

The paper considers the problem of controlling the movement of a mobile robot along a given smooth trajectory without measuring its position coordinates. To solve the problem, an adaptive observer of the local coordinates of a moving object is used by measuring the linear speed, yaw angle, and range to a beacon with known coordinates. Then the minimum distance from the robot to the given smooth trajectory is determined. Based on the estimates for the coordinates of the robot and the distance to the curve, we synthesized the control law of the movement along the trajectory with the desired speed under the conditions of uncertainty of the mathematical model. The motion control algorithm is based on the robust sequential compensator method, which ensures that the deviations of the robot from a given trajectory are limited. The proposed coordinate observer ensures asymptotic convergence of the estimation errors to zero. In this paper, we propose two algorithms for determining the minimum distance from the robot to the trajectory: an exact analytical calculation and a nonlinear observer that guarantees the convergence of the estimate to the true value in an arbitrarily short time. The trajectory regulator ensures the movement of the robot along a given trajectory with a limited error. The application of the proposed approach allows one to solve the issues of controlling the movement of a mobile robot without measuring the position coordinates. The approach can be widely applied for controlling self-driving vehicles when they run in tunnels or under a bridge, where it is not possible to measure their coordinates using the satellite navigation systems (GLONASS or GPS).

Recently, III-V semiconductor nanostructures of reduced dimension attract more and more interest of researchers for the new generation devices creation. Combinations of nanostructures with different dimensions are of special interest, among them, for example, quantum dots in the body of nanowires. Such quantum dotsʼ size and location control is strictly determined by the growth parameters. As a result of effective relaxation of mechanical stresses on the lateral faces of nanowires, the integration of hybrid nanostructures with silicon technology is possible. In this work, we have demonstrated the possibility of GaP nanowires with GaAs quantum dots and AlGaP nanowires with InGaP quantum dots growth on silicon by molecular-beam epitaxy. The physical properties of the selected nanowires have been investigated. Growth experiments were performed using Riber Compact 21 setup, which is equipped, in addition to the growth chamber, with a vacuum-aligned chamber for gold deposition (metallization chamber). The morphological properties of the obtained nanostructures were studied by scanning electron microscopy. The optical properties of the nanostructures were investigated by the photoluminescence method. The analyses of morphological properties showed that GaP nanowires with GaAs quantum dots were formed predominantly in the <111> direction, in contrast to AlGaP nanowires with InGaP quantum dots, which in some cases changed the growth direction. The reason for the change in the direction of growth of nanowires may be the participation of indium in the growth process. With a sufficient content of indium in the gold catalyst droplet, such mixed droplet can etch the facets at the top of the nanowires, thereby descending to the side of the nanowires and changing the direction of nanowires growth. The studies of the optical properties of the grown nanostructures showed that the photoluminescence signal from InGaP quantum dots in AlGaP nanowires is observed at a temperature of –263 °C with a peak maximum of around 550 nm. Thus, the synthesized nanostructures are promising for optoelectronic applications, in particular, for creating sources of single-photons.

The paper investigates the effect of the magnesium oxide concentration on the ceramics’ microstructure and optical transmittance under conditions of excess Al3+ (4.8 mol.%) and Y3+ (2.9 mol.%) cations in the garnet structure, as well as the stoichiometric ratio Y3+/Al3+ = 3/5. Samples of optical ceramics were fabricated by vacuum sintering of compacts obtained from ceramic powders. Precursor powders with different ratios of Y3+/Al3+ cations were synthesized by the method of two-stage coprecipitation. Magnesium oxide was used as a sintering additive in concentrations from 0 to 0.2 wt.%. The microstructure and optical properties of the obtained samples were studied using scanning electron microscopy, energy dispersive X-ray spectroscopy and spectrophotometry techniques. It is shown that with the addition of magnesium oxide in a concentration of 0–0.2 wt.%, the stoichiometry of yttrium-aluminum garnet significantly affects ceramics’ optical transmittance and microstructure. Samples of optical ceramics of yttrium-aluminum garnet with a light transmission coefficient of more than 70 % in the visible and near-infrared range were obtained.

One of the application fields of bulk gallium oxide crystals is the manufacture of substrates for epitaxial growth of device structures for power electronics and optoelectronics in the Ga2O3/(AlxGa1–x)2O3 system. For most instrument designs, the substrate serves as a channel for heat removal from the device to an external heat sink. This property stresses the importance of information about the thermal characteristics of bulk crystals of gallium oxide and a solid solution of gallium and aluminum oxide, particularly about the heat capacity and thermal conductivity. In this work, we measured the heat capacity of bulk crystals of the β-modification of pure gallium oxide (β-Ga2O3) obtained by the Czochralski method, as well as of a double solid solution of gallium and alumina oxide β-(AlxGa1–x)2O3 in the range of temperatures from 25 °C to 480 °C and for various values of the Al concentration. Samples of bulk crystals were grown in an industrial installation “Nika-3” by pulling from the melt (Czochralski method). Further, the specific heat was measured on samples specially prepared from bulk crystals by differential scanning calorimetry. The thermal conductivity in the [010] crystallographic direction was measured by the method using a flat heat source (hot disk method). The dependence of the specific heat capacity of β-(AlxGa1–x)2O3 crystals on Al concentration was obtained for the atomic concentration of aluminum ranging from 0 (pure gallium oxide) to 9.11 at.%. The influence of the Al content on the heat capacity of the material is analyzed. The temperature dependence of the thermal conductivity of β-Ga2O3 in the [010] direction (direction of growth) in the temperature range from 43 °С to 120 °С was also obtained. The results of the study can be used to investigate the thermal properties of gallium oxide, as well as to solve the problem of heat removal for electronic devices based on gallium oxide.

The close integration of modern cyber-physical systems with production and technological ones as well as with critical information infrastructure requires improving the monitoring process. The monitoring process is necessary with a constant increase in the possible points of entry into the system. The processing of a large amount of data coming from monitoring systems requires significant computing power. In this regard, it is relevant to reduce the dimension of the feature space while maintaining an acceptable monitoring accuracy. The proposed solution should be invariant to the dimension and orders of magnitude from which the time series supplied to the input of the monitoring system are composed. To obtain the most informative features in the formation of their set, it is proposed to use principal component analysis, and a method based on decision trees for their classification. A computational experiment was performed to confirm the applicability of the developed approach. The data of the network traffic for the research stand of the cyber-physical system water treatment were used in the experiment. The accuracy of the set of methods on the analyzed data was 98.74 %. The comparison with known studies showed an increase in the F-measure up to 0.925, which is 4.8 % higher than the most effective method used to date, namely the Isolation Forest method. The developed approach allows one to significantly increase the speed of identification and to detect anomalies of information security and functional safety of cyber-physical systems with high accuracy by reducing the dimension of the original feature space. The proposed approach can be used in event monitoring systems that deal with information security. The presented theoretical results can be useful for researchers of information security and functional safety of cyber-physical systems.

Stochastic testing by fuzzing tools is one of the approaches to software vulnerability analysis. A testing process usually generates random input data for a tested program and takes a significant period of time. Reducing testing time is an important task. One of the areas of research for improving testing is to define only those sets of data sequences, which have an impact on the execution path of the tested program. Thus, a new approach of input data generation that reduces total testing time allows finding more program vulnerabilities. The paper suggests a modification of a genetic algorithm, which is used by fuzzer afl (American Fuzzy Lop). The promising positions model is introduced to improve the efficiency of input data generation. With this model, the most promising position in input data is chosen by the fuzzer genetic algorithm from the viewpoint of vulnerability analysis for next mutation steps. Compared to existing solutions, the suggested model pays attention to the perspective position of a data element to increase code coverage and directs the genetic algorithm to change it. The model was evaluated with the popular fuzzer afl and its modifications (aflfast, symfuzz, afl-rb). During the evaluation study, the suggested model reached 21 % more code coverage than existing solutions. Edge coverage between base program blocks is increased from 20897.3 up to 17267.4. The developed model can be used during software testing, which implies an input and processing of user data. The model can be integrated into stochastic testing tools. The modification should be done only, in the random generator component and does not require redesigning the whole testing tool.

The development of the medical imaging field is becoming a significant challenge due to the growing need for automated, fast, and efficient diagnostics. Traditionally, blood cells are counted by using a hemocytometer along with other laboratory equipment and chemicals, which is a laborious task. The paper investigates the application of machine learning methods to the identification and classification of blood cells, which allow increasing the recognition rate without deteriorating quality. A comparative analysis of methods for solving the problem of recognizing blood cells based on artificial intelligence approaches is carried out. The paper uses support vector machine, k-nearest neighbors’ algorithm, deep learning (convolutional neural network), and forward propagation neural network. A set of images with cell samples was selected as the initial data for comparison. A comparative analysis of the quality of the considered algorithms was performed on a set of training data with more than 3000 images. It is shown that a program that implements artificial intelligence methods provides a cell recognition time within 4-6 seconds when using an office personal computer, which is significantly less than the time spent by medical workers on one study of a biomaterial. The implementation of the presented results makes it possible to automate the process of studying a biomaterial, reduce the time for conducting and obtaining the result of the analysis of whole blood cells (identification and counting), lessen the influence of operator errors on the result, unload computing resources, thereby increases the efficiency of digital medicine.

Optimization problems in the Cloud Intrusion Detection System (CIDS) contain numerous conflicting objectives, uni-modal and multi-modal functions and the difficulty level varying between linear to non-linear limits. The Grey Wolf Optimizer (GWO) is a meta-heuristic technique that is implemented based on social behavior of wolves and their hunting behavior. Significant improvement in exploration and exploitation of the search space in GWO can be obtained by modifying the control parameter a. Works have already been carried out by many researchers by modifying the control parameter a in different manner to achieve better results. In a similar content, the authors of this study also modified the control parameter a and added a weight factor to the position of each wolf to attain the best possible results. Due to high demand for the cloud computing environment, intrusion detection in a cloud network plays a big role in maintaining the faith of the clients. Hence, CIDS is required to inspect the network packets to identify the abnormal behavior. For developing a system for cloud based IDS, the researchers created fuzzy rules to represent the relationship between the attributes and the nature of activity (normal or abnormal). The Modified Grey Wolf Optimizer (MGWO) algorithm is applied on eleven benchmark test functions and obtained good performance metrics. The results presented in this paper are promising; MGWO is used to reduce the fuzzy rules in developing fuzzy based CIDS. The performance of the proposed algorithm is compared with classical GWO, Particle Swarm Optimization (PSO), Cuckoo Search (CS) and variant of MGWO. The experimental results reveal that there is significant improvement in its performance.

The Flying Adhoc (FANET) network is focused on the use of mobile airborne objects and makes it possible to form self-organizing networks, which can provide channels of information interaction between these objects and not be limited. A specific property of airborne objects (FANET agents) is a high speed of movement and a limited communication range, which leads to frequent topology changes in a changing noise environment. This entails a data availability violation and may lead to the impossibility of performing the task by the group. One of the ways to improve the quality of information interaction between agents in the FANET network is to optimize the routing of information interaction channels in the dynamic topology of mobile agents. The paper proposes a model for routing communication channels in the FANET network using a fuzzy logic approach for grouping unmanned aerial vehicles (UAVs) with limited performance. The proposed model provides higher stability of the communication system for mobile objects when there are potential threats to the UAV grouping. The productivity of the described solutions is confirmed by the study of the developed Fuzzy protocol implemented in the NS3 environment: an analysis of quality indices is carried out in comparison with the well-known routing protocols AODV, OLSR.

Node authentication and key management are the two significant security services employed in Wireless Sensor Networks (WSN). Since the growth of the devices in WSN is rapidly increasing, strong security policies should be employed to save the network from outside invaders. There is a wide range of smart applications developed in various fields such as military, health, agriculture, smart city, and many others. Since most of the applications consist of sensitive data, they should be protected to save the users’ privacy. Conventional protocols are more prone to security attacks and therefore the authors propose a secure and reliable protocol named Polynomial Authentication and Mapping Verification based Mannequin Routing (PAMVMR). This scheme involves two main processes such as Bi-level authentication and Information Processing. Bi-level authentication includes node-to-gateway authentication using polynomial key shares and node-to-node verification using mapping function that is processed through a context free grammar. Information processing includes creation of mannequin routes by applying Pascal’s triangle method and transmission of data. This makes the network more secure and reliable for data transmission from sensor nodes to a gateway node and from a gateway to users.

The paper examines the application and properties of bent functions of various degrees to construct R-robust codes with a spline wavelet grid for the protection against side-channel attacks. The use of the bent function of various degrees in coding algorithms allows changes the robust parameters and the information coding time. Higher degrees of bent functions in robust coding algorithms increase the likelihood of detecting errors in the transmission or storage of data. In comparison, smaller degrees reduce the time for coding information but at the expense of robust properties. As part of the coding algorithm, it is possible to change the degree of the bent function through the use of the spline-wavelet decomposition; for this, it is necessary to change the process of generating the spline-wavelet grid. In this work, bent functions were compiled from nonlinear functions and elements of the spline-wavelet composition. Based on the results obtained, a new construction of a spline-wavelet robust bent code was proposed. The use of spline wavelets allows one to change the designs and parameters of codes during execution, which increases the security of the system against attacker’s actions. The distinction between the given code constructions lies in the use of different grids for the spline-wavelet transform and in the choice of bent functions of various degrees. The developed design of a robust code has a lower probability of error concealment in the case of using a high-degree bent function, while a lesser degree entails a faster coding time compared to existing robust codes. These code constructions can be used to protect against side-channel attacks when storing and transmitting information in communication systems.

The article proposes a new approach to comparing accounts of the social media “VKontakte” and “Instagram” to determine those accounts which belong to the same user. The approach is based on the comparison of graphic content; the novelty of the approach consists in combining several methods for matching graphic content, also for the first time a method is proposed for matching accounts of the mentioned social media. The proposed method combines three methods of matching graphic content: by extracting the faces of the account users from the photos in the account and matching them, by matching all faces in both accounts, and by pairwise comparison of images to determine the same images in both accounts using the perceptual pHash method. The described method was tested on a dataset of more than 8,000 pairs of accounts. According to the results of the experiment, the value of the F1-score metric reached 0.87. The practical significance lies in automating the comparison of user accounts in various social networks by implementing of the developed algorithm in the prototype of the software package. A further direction for research lies in expanding the set of data and attributes of profiles considered for comparison. The results can be introduced into a software package for the analysis of the security of a user of information systems against social engineering attacks. It seems promising to combine the obtained findings with account matching methods based on the structural similarity of social graphs.

The paper presents the results of a new method for training the NASNet neural network called Monte Carlo Concrete DropPath for epistemic uncertainty estimation to classify pollen images. The developed method is compared with existing methods for epistemic uncertainty estimation. The method turns an arbitrary multipath neural network into a Bayesian one by sampling from the predictive distribution. The Monte Carlo method samples different masks of DropPath to estimate uncertainty. Moreover, the probability of DropPath is optimized using continuous relaxation. The proposed method was tested for the classification task on the state-of-the-art NASNet architecture. The method demonstrated advantages on the task of classifying pollen images. The classification accuracy increased for 13 pollen species of allergen plants by 0.73 % on average compared to the baseline NASNet, reaching 98.34 % by F1 measure. Furthermore, the method increased calibration and reduced the epistemic uncertainty of the model by two times compared to the NASNets ensemble. It is shown that continuous relaxation of the DropPath probability parameter increases the accuracy of problem solving and reduces the epistemic uncertainty of the model. These results contribute to the automation of aeropalinological monitoring to reduce the time of informing patients who suffer from pollinosis and hence to prevent allergy symptoms. The developed method can be applied to train a neural network for other computer vision tasks on any image dataset.

The paper investigates the results of random number generation with arrays of coupled quantum-dot micropillar lasers. The micropillars array laser generation is modeled based on the rate equations for quantum dot lasers. The numerical simulation of the dynamics for the arrays of coupled quantum-dot micropillar lasers is carried out utilizing the semi-implicit Euler method, implemented in Julia programming language. The algorithm of random bit sequence generation consists of the following steps: sampling the values of the total field intensity for coupled micropillar lasers; normalizing and discretizing the obtained values per resolution of the 8-bit analog-to-digital converter; extracting the four least significant bits from the bit representation of the sampled values; concatenating the bit values in a single sequence. The possibility of the bit sequences generation having an equiprobable distribution of zeros and ones with a performance of up to 400 Gbit/s was shown utilizing a random number generator based on an array of coupled quantum-dot micropillar lasers for sequences with a length of 14285716 bits at a sampling rate of 100 gigasamples per second and four least significant bits extraction. The resulting bit sequences successfully passed 14 NIST 800-22 statistical tests for the p-value equal to 0.01. The proposed method can be applied to develop random number generators based on larger arrays of coupled quantum-dot micropillar lasers. The results can be utilized in the experimental implementation of random number generators based on arrays of coupled quantum-dot micropillar lasers.

The integration of automated systems in enterprises provides information support for the stages of the product life cycle and electronic interaction between employees in performing their work. Typically, this integration is carried out on a specific enterprise and is based on an ontological approach. This generates many similar results in the form of digital product passports. The proposed work is aimed at implementing a new approach to the integration of automated systems. It is based on the formulation of generalized design and production procedures and types of product data generated through control systems. The sequence of these procedures determines the activities of the enterprise at the stages of the life cycle. This results in an ontological model of a product for the instrument-making industry. The application of the model at each specific enterprise is possible if the requirements for the content of the passport and design solutions are provided verbally. The proposed method is implemented in several stages. At the first stage, the elements of the basic ontology are marked up. The content of its elements depends on the problem that is being solved. At the same time, ontology elements are formed that determine the content of a digital passport or a generated design solution. This is due to the automation of the management dealing with design and production procedures, and product data, which are considered appropriate in a particular enterprise. Consequently, design solutions based on a digital passport must be generated considering the requirements of specific enterprises. To form the content of a digital passport of an enterprise, subontology is extracted from the basic ontology at the second stage. At the final stage, subontology is extracted to generate the desired design solution. The study proposes the sequences of actions to mark up the basic ontology, as well as to extract subontology to form the content of a digital passport or generate a design solution. The described solution can be implemented at enterprises of the instrument-making industry, which include automated design systems. The presented method allows the development of signatures and semantics of unified services for the use of a digital passport.

Obtaining accurate phase values of the output signals for the receiving elements of a phased array antenna is one of the crucial issues relating to radio-photon technologies in radar and radio communication. The paper considers measuring the phase difference of the output signals for the receiving elements of a phased array antenna using electro-optical Mach–Zehnder modulators as part of a radio-photonic device. The dependences of the output signals of the optical signal receivers and the phase difference of the output signals for the receiving elements of the phased antenna array in the radio-photonic scheme are formalized for different variants of the connection of electro-optical Mach–Zehnder modulators. The authors propose the methods for determining the phase difference of the output signals for the receiving elements of a phased array antenna based on parallel and series connection of electro-optical Mach–Zehnder modulators into radio-photonic devices. A comparative assessment of the proposed methods is carried out. It is shown that the method based on the determination of the phase difference with the parallel connection of electro-optical modulators produces 1.58 times less error than the method with the series connection. The description of the radio-photonic scheme of the phase direction finder is presented. The proposed scheme provides high accuracy in measuring the phase difference of the output signals for individual receiving elements of a phased array antenna. The results of the work can be applied by specialists in the field of advanced radar and radio communication systems.

Autonomous underwater vehicles have a wide range of applications, but their limited capabilities make it difficult to perform some time critical functions. To coordinate joint actions between agents, it is proposed to use a multi-agent approach with information exchange. For networks of autonomous underwater vehicles, information interaction is carried out with sound underwater communication equipment, which shows non-directional radiation and imposes limitations on speed (kilobits per second) and on the radius of information exchange. This results in the need for planning an exchange route using nodes as repeaters. The paper considers issues of routing exchanges for such networks. The research focuses on the problem of ordering the sequence of messages in each of the devices at the stage of the transmission session. The issue of ordering messages is reduced to the well-known problem of flow shop planning according to the total optimization criterion that is minimizing the average time spent by job in the system. The authors present an algorithm for scheduling communication sessions based on the concept of a resolvable class of systems. Based on information interaction between subscribers, it is proposed to correlate the state of the network with one of the resolvable classes of systems with the subsequent application of the scheduling algorithm. The main results involve the analysis of an algorithm for scheduling exchanges and present a model of its operation. Assertions are formulated and proved for four known decidable classes of systems. The developed algorithm makes it possible to reduce the total time of information exchange in the network of autonomous underwater vehicles and can be used by specialists in the design of equipment for sound underwater communications.