All issues

This paper presents an experimental study of the application of automatic annotation of text data in the question – answer format (QA pairs) under conditions of limited computing resources and data protection requirements. Unlike traditional approaches based on rigid rules or the use of external APIs, we propose using small language models with a small number of parameters that can function locally without a GPU on standard CPU systems. Two models were selected for testing — Gemma-3-4b and Qwen-2.5-3b (quantized 4-bit versions) — and a corpus of documents with a clear structure and a formally rigorous style of presentation was used as source material. An automatic annotation system was developed that implements the full cycle of QA dataset generation: automatic division of the source document into logically connected fragments, formation of “question – answer” pairs using the Gemma-3-4b model, preliminary verification of their correctness using Qwen-2.5-3b based on evidence span from the context and expert quality assessment. The results are exported in JSONL format. Performance evaluation covers the entire QA pair generation system, including fragment processing by the local language model, text preprocessing and postprocessing modules. Performance is measured by the time it takes to generate a single QA pair, the total throughput of the system, RAM usage, and CPU load, which allows for an objective assessment of the computational efficiency of the proposed approach when running on a CPU. An experiment on an extended sample of 12 documents showed that automatic annotation demonstrates stable performance when processing different types of documents, while manual annotation is characterized by significantly higher time costs and high variability. Depending on the type of document, the acceleration of annotation compared to the manual process ranges from 8 to 14 times. Quality analysis showed that most of the generated QA pairs have high semantic consistency with the original context, with only a limited proportion of data requiring expert correction or exception. Although full manual validation of the corpus (the “gold standard”) was not performed as part of this work, the combination of automatic evaluation and selective expert review allows us to consider the resulting quality level acceptable for preliminary automated annotation tasks. Overall, the results confirm the practical applicability of small language models for building autonomous and reproducible automatic text annotation systems under limited computational resources and provide a basis for further research in the field of effective training corpus preparation for natural language processing tasks.

This paper presents a non-iterative method for solving an inverse problem for a parabolictype equation with an unknown time-dependent coefficient at the first spatial derivative. The overdetermination condition is specified as a definite integral of the unknown function with a weighting factor over the spatial domain or its subdomain. The study is motivated by the need to identify dynamic parameters in applied problems, particularly in modeling transport processes in biological fluids, where the flow velocity may vary over time. In contrast to conventional iterative methods that require substantial computational effort and careful selection of regularization parameters, an original approach based on solution decomposition is proposed. At each time layer, the solution is represented as a linear combination of solutions to two auxiliary systems with the same matrix and different right-hand sides, followed by the determination of the unknown coefficient from a discrete analogue of the overdetermination condition. This approach eliminates the need for an iterative procedure. In the presence of inexact overdetermination data, the highest reconstruction accuracy is achieved using a quasi-solution. Numerical experiments on test problems demonstrate high accuracy in reconstructing the unknown functions under small perturbations of the overdetermination condition. The results indicate strong potential for applications in medical diagnostics and other fields requiring rapid processing of experimental data.

This paper covers deployable systems assembled from a set of trapezium plates. The middles lines of the plates represent a plane curve in the original position of the package. It is proved that when the package of thin plates is unwrapped, a surface approximating a shell of nearly any curvature is formed. Kinematics of the continual model is analyzed by the method of Cartan moving hedron, extending the results the authors published earlier. Various applications of rotating shells are shown. Experimental models of deployable latticed systems are demonstrated.

The models of liquid heptane and cyclohexane has been developed. The properties of model liquids appear to be in a good agreement with a properties of real liquids. X-Ray diffraction spectra of model liquids were also in a good agreement with experimental ones. Radial distribution functions analysis allows us to reveal a crucial molecular feature of cyclohexane. Isometric molecules of cyclohexane are packed more tightly and regular. Tight packing lead to the free volume deficiency, which could explain increased viscosity and melting temperature of cyclohexane.

A new method is described for finding parameters of univariate regression model: the greatest cosine method. Implementation of the method involves division of regression model parameters into two groups. The first group of parameters responsible for the angle between the experimental data vector and the regression model vector are defined by the maximum of the cosine of the angle between these vectors. The second group includes the scale factor. It is determined by means of “straightening” the relationship between the experimental data vector and the regression model vector. The interrelation of the greatest cosine method with the method of least squares is examined. Efficiency of the method is illustrated by examples.

The paper presents results of experimental, computational and analytical study of the effect of nonequilibrium chemical activation of air-fuel mixture on effectiveness of Diesel process. The generation of a high-voltage multi-streamer discharge in combustion chamber at the compression phase is considered as the method of the activation. The description of electrical discharge system, results of measurement and visualization are presented. The plasma-chemical kinetics of nonequilibrium ignition is analyzed to establish a passway for a proper reduction of chemical kinetics scheme. The results of numerical simulation of gas dynamic processes at presence of plasma-assisted combustion in a geometrical configuration close to the experimental one are described.

А discrete element model is applied to the problem of a spherical projectile penetration into a massive obstacle. According to the model both indenter and obstacle are described by a set of densely packed particles. To model the interaction between the particles the two-parameter Lennard–Jones potential is used. Computer implementation of the model has been carried out using parallelism on GPUs, which resulted in high spatial — temporal resolution. Based on the comparison of the results of numerical simulation with experimental data the binding energy has been identified as a function of the dynamic hardness of materials. It is shown that the use of this approach allows to accurately describe the penetration process in the range of projectile velocities 500–2500 m/c.

Use of algorithms based on neural networks can be inefficient for small amounts of experimental data. Authors consider a solution of this problem in the context of modelling of properties of ceramic composite materials reinforced with carbon nanotubes using perceptron complex. This approach allowed us to obtain a mathematical description of the object of study with a minimal amount of input data (the amount of necessary experimental samples decreased 2–3.3 times). Authors considered different versions of perceptron complex structures. They found that the most appropriate structure has perceptron complex with breakthrough of two input variables. The relative error was only 6%. The selected perceptron complex was shown to be effective for predicting the properties of ceramic composites. The relative errors for output components were 0.3%, 4.2%, 0.4%, 2.9%, and 11.8%.

The goal of this work is to generalize second order mathematical models for automotive flow using algorithm for building state equation — the dependency of pressure on traffic density — which is adequate with regard to real world data. The form of state equation, which closes the system of model equations, is obtained from experimental form of fundamental diagram — the dependency of traffic flow intensity on its density, and completely defines all properties of any phenomenological model. The proposed approach was verified using numerical experiments on typical traffic data, obtained from PeMS system (http://pems.dot.ca.gov/), using segment of I-507 highway in California, USA as model system.

The results of verification carried out for investigations of hydrodynamic effect on reentry conicalsegmental space vehicle are presented in the paper. The program complex Flow Vision is used for this analysis. The purpose of the study is verification of using Flow Vision program complex for problem solving mentioned above on the base of comparison between calculated and experimental data, obtained on the Apollo landing models and new development reentry spacecraft of manned transporting spaceship designed by RSC Energia. The comparison was carried out through the data of pressure values on spacecraft model surfaces during its water landing and inertia center motion parameters.

The results of study show good agreement between experimental and calculated data of force effects on vehicle construction during water landing and its motion parameters in the water medium. Computer simulation sufficiently well reproduces influence of initial velocities & water entry angles variations on water landing process.

Using of computer simulation provides simultaneous acquisition of all data information needed for investigation of water landing peculiarities during construction design, notably, hydrodynamic effects for structural strength calculations, parameters and dynamics of center mass motion and vehicle revolution around center mass for estimation water landing conditions, as well as vehicle stability after landing.

Obtained results confirm suitability of using Flow Vision program complex for water landing vehicle investigations and investigations of influence of different landing regimes through wide initial condition change range, that permits considerably decrease extent of expensive experimental tests and realize landing conditions which are sufficiently complicated for realizing in model physical experiments.