With the fast growth of software-defined networking (SDN) and Internet of Things (IoT) ecosystems, the risk of getting major cyber-attacks has become a serious concern. As such, robust real-time intrusion prevention is drastically needed. In this paper, we present HashBoost-IPS, a novel intrusion prevention system that merges XGBoost-based attack detection with multi-hash cryptographic verification. The system detects malicious traffic in real-time, blocks it immediately, and ensures secure handling through cryptographic hash-based validation. The NSL-KDD dataset was used to test the system. The model works extremely well with efficient handling of features and almost no extra computing power needed. Findings show that HashBoost-IPS is an efficient and versatile solution for real-time intrusion prevention in SDN, IoT networks. Maintaining a low computational overhead, the proposed model was able to achieve accuracy of around 99.8 % . Besides, the model demonstrated high precision, recall, and F1-score.
The article describes the development and implementation of a microservice architecture upon which the functionality of an Intelligent Digital Twin of Plants (IDTP) is built. This system is designed for planning and simulation plant growth stages and forecasting yields, synchronized with the states of actual crops, based on ontologies and multiagent technologies. The functional capabilities of the Manager, Ontology Constructor and Knowledge Base (OC and KB), planning (multiagent planner) services are examined, as well as the organization of interfaces for the interaction of the IDTP with external services and users. Examples are provided to represent the results of modeling the comprehensive state of a crop, based on real-time environmental data and forecasting the crop’s condition at all stages of plant development up to harvest. The developed microservice architecture is open for integrating the IDTP with external services, such as environmental data collection, as well as recommendation systems and Agro-IoT platforms. The results of the IDTP prototype development have been passed on to several farms for experimental testing in different climatic conditions. The article discusses directions for improving the accuracy of IDTP forecasts and the potential for creating a decision support system for agronomic applications in precision agriculture based on the IDTP.
The development of a neural network for predicting the aerodynamic coefficients of airfoil sections for subsequent application in the blade element method to calculate the characteristics of aircraft engine propeller blades is described. A specific feature of this neural network is the ability to predict the dependences of the lift and drag coefficients on the angle of attack and Reynolds number of flows in the form of two-dimensional images of pixel color distributions. An airfoil parametrization method and the development of a database are presented, and the architecture of the proposed neural network is described. The results of training the neural network are reported, and its capability of predicting the aerodynamic characteristics is demonstrated.
The paper presents the results of developing a photocatalytic generator of chemically active oxygen species intended for air disinfection and purification in fruit and vegetable storage systems. A Cu/ZnO-ZnAl _2 O _4 composite oxide photocatalyst synthesized by the polymer-salt method was used as the active material; under excitation by 365 nm radiation, it provides efficient generation of singlet oxygen. The design of the generator is described; it includes preliminary mechanical air cleaning, a photocatalytic unit, carbon and paper filters, and a forced-air supply system. It is shown that the use of the device reduces weight loss in raspberries and improves the preservation of mango and avocado fruits during storage, which confirms the prospects of photocatalytic air purification for maintaining fruit freshness.
We consider the issues of creating algorithmic support for supervised classification problem, which is one of the central tasks of machine learning. Original procedures of logical analysis and classification of integer data represented as a set of elements of Cartesian product of finite partially ordered sets (product of partial orders) are constructed and investigated. At the training stage of the proposed procedures, the search for so-called regular representative elementary classifiers (special fragments in feature descriptions of precedents that distinguish objects belonging to different classes) is performed. An asymptotically optimal algorithm for enumerating the required elementary classifiers over a product of antichains is constructed and the results of its testing on real-world tasks are presented. Theoretical and experimental justifications for the efficiency of the new classification procedures are provided for the case when linear orders on sets of feature values are defined. The theoretical conclusions are based on the study of the metric (quantitative) properties of the set of regular representative elementary classifiers.
A software module for calculating the productivity and efficiency of discrete manufacturing is developed. The module’s business logic is implemented in the AnyLogic package, which was used to create a simulation model and export it to a set of JAR files. The model was built for a production cell located in the Institute of Production Innovation Technologies (IPIT-216) of Samara University. The simulation error was less than 15
This paper considers the problems of estimating the state of charge (SoC) of lithium-ion batteries. A second-order Thevenin equivalent circuit model is utilized as the battery’s mathematical model. An extended information Kalman filter (EIKF) is applied to estimate the battery state of charge. The algorithm efficacy is demonstrated through numerical examples, which show acceptable estimation errors across various charge and discharge modes, including discharge by pulsed current and a cycle similar to the Worldwide Harmonized Light Vehicles Test Cycle (WLTC). The information form of the extended Kalman filter outperforms its covariance form, ensuring lower numerical instability and better results at a low noise level in measurements. Furthermore, the information form of the Kalman filter allows effectively combining data from several sensors. This is particularly crucial for situations, where sensors vary in accuracy and noise level, ensuring accurate estimates for battery systems, in which individual energy cells may differ in the battery state of health and have different indicators of the maximum battery capacity and, correspondingly, different discharge curves.
This paper presents a method for designing support structures for 3D printing based on the topological optimization and the method of equivalent static loads. Information exchange between the optimization and numerical simulation modules of the SLM process is organized for the computational process. The proposed support synthesis method effectively reduces the maximum shrinkage deflection from 0.731 to 0.630 mm, which corresponds to a reduction of 13.8 % .
This paper examines the dispersion coefficient of low-frequency electromagnetic waves known as whistling atmospherics or whistlers. A mathematical model describing the law of whistler frequency variation over time is proposed. An algorithm for calculating the whistler dispersion coefficient based on the spectrogram analysis is also developed. This algorithm involves identifying the whistler trace using threshold filtering and clustering. The whistler trail is then straightened by transforming the coordinates, and a linear regression equation is constructed, where the cotangent of the slope provides an estimate of the dispersion. The algorithms are implemented in the ADWRK 1.0 software package using the Python programming language. The results obtained using this software package are compared with those obtained using the proposed mathematical model. It is shown that the calculation of the whistler dispersion coefficient can be more accurate when using a combined method for extracting the whistler trail.
Methods for compressing information about the boundaries of regions generated by superpixel segmentation of images are considered. A representation of superpixel boundaries as a quaternary image is proposed. A new compression method for this image has been developed on the basis of statistical encoded trajectories of boundary elements. An experimental study of the new method demonstrates its advantages over existing statistical and predictive coding methods, especially for a small number of boundaries between superpixels.
Efficient use of domain-specific knowledge based on representative statistics is an important problem from different points of view. The methods used to utilize reliable a priori information are diverse and often specialized for each specific problem of data analysis. This paper describes an approach that solves the problem from a unified perspective based on the use of a multivariate analogue of the Hough transform. This approach offers new possibilities for solving two important problems: a unified method is proposed for constructing models of the interaction between known particular patterns, and the minima of the discrepancy measure found in the Hough space are used as a tool for model optimization.
A technique for constructing the trajectory of an unmanned aerial vehicle (UAV) has been developed by analyzing the video stream from a camera mounted on it, without the use of global navigation system data. The trajectory is constructed using the parameters of an affine model of mutual spatial misalignment of adjacent video frames. Methods for finding Shi–Tomasi keypoints, a Lucas–Kanade optical flow, and a Kalman filter are used. The technique was implemented on single-board computers and tested under limited computing resources on real video sequences.
This paper describes the results of comparative analysis between conventional and modified genetic algorithms of search for the optimal gate location in a mold during the injection molding of thermoplastic materials. Based on this comparison, it is established that the modified genetic algorithm converges 25 % faster than the conventional one and finds a minimum at a 55 % lower number of objective function calls as compared to the conventional genetic optimization algorithm. The issue of selecting the best criterion for solving the problem of gate location optimization on a discrete finite element mesh is studied.
A method using conformal meshes to solve bimaterial topological optimization problems in linear and nonlinear formulations is proposed. The specific features of using conformal meshes to solve the contact problems in isotropic and anisotropic formulation are considered. The solution speed and the results of bimaterial topological optimization on uniform and conformal meshes are compared. The results show that the use of conformal meshes increases the speed of solving the topological optimization problem by more than 12 times.
This work is devoted to studying the formation and decoding of interference patterns to reconstruct the reference wave phase. The phase reconstruction algorithms are considered using the plane and conical beams. The methods for enhancing the quality of the reconstructed image in the case of using a plane wave as a reference wave are presented.
In this paper, the formation of perfect optical vortex beams is investigated based on numerical simulation for different parameters of the optical system, such as the axicon angle and the vortex beam order. The formation of beams during their propagation in free space and in the focal plane is considered, which can be useful for optical trapping and movement of microparticles.
The problem of assessing the heterogeneity of infrared photosensitive photodetectors (IRPDs) is considered. A statistical method for estimating and correcting for nonuniformity in IRPD parameters based on observed data is proposed. Experimental results illustrating the effectiveness of the method are presented.
The complex spatial flow of a freon jet flowing out of a long channel with a triangular cross section in a laminar–turbulent transition mode was studied. To obtain a detailed picture for the flow, a multiangle measuring complex of Hilbert diagnostics on the basis of an IAB-463M device was implemented. It was shown that channel geometry has a weak effect on the scenario of laminar–turbulent transition in a channel with the formation of puff-structures. It was established that, when entering a jet flowing from a channel with a triangular cross section, a puff-structure induces its turbulization and generates secondary disturbances in the mixing layer. The results may be of practical importance in combustion an chemical vapor deposition (CVD) processes.
The interaction of the radiation of the THz spectral range with indium tin oxide (ITO) films with a thickness of less than 300 nm on fused quartz substrates has been investigated. The dependence of their complex refraction index within the range 0.2–1.2 THz on their thickness has been determined. The properties of the films in this range are well described by the Drude model, whose parameters are determined from approximation of data in a wide spectral range. The model demonstrates a linear increase in the specific conductance with growing thickness and can be useful to calculate antireflection coatings for the radiation of the THz spectral range. The results of the investigation of the interaction of intensive THz radiation with the peak and medium intensity of up to 2 MW/cm ^2 and 1.2 kW/cm ^2 , respectively, have shown the absence of laser damage to the films and have made it possible to outline the scope of application of ITO films as dichroic mirrors of the transport channels of intensive THz beams.
Some experimental data on the energy efficiency (EE) of radiation input/output throughout the entire path of its propagation in a medium of photopolymer holographic gratings and a planar waveguide were obtained and analyzed. It was established that the major contribution to radiation power losses is made by absorption in the photopolymer medium due to incomplete decoloration of the dye during the postprocessing of holograms and a relatively low diffraction efficiency (DE). Due to incomplete matching between the spectral characteristics of reflection holograms and LED displays, the power of their radiation is only partially used as a useful signal. Taking into account the experimental data, the final EE estimate is ∼10% relative to the LED emission power at the input of the entire input/output gratings–waveguide structure. To increase this parameter, it is necessary to apply recording media with a small thickness (less than 10 μ m) and, at the same time, with a high amplitude of photoinduced change in the refractive index to provide the necessary DE and degree of matching between the mentioned diffraction characteristics and to decrease absorption in the photopolymer medium. In this case, the desired EE value may attain ∼40% .
