The KIAM Astrodynamics Toolbox, a new software library for designing spacecraft orbital motion, is introduced. The toolbox is developed at the Keldysh Institute of Applied Mathematics of the Russian Academy of Sciences in Fortran and Python languages and, therefore, combines computational speed and program design flexibility. The library can be useful for space flight mechanics specialists, as well as for students in relevant educational programs.
A review of software dynamic analysis methods is presented, mainly focusing on the methods supported by tools targeted on software security verification and applicable to system software. Fuzzing, runtime verification and dynamic symbolic execution techniques are considered in detail. Dynamic taint data analysis methods and tools are excluded since gathering technical details on them is complicated. The review of fuzzing and dynamic symbolic execution is focused mostly on the techniques to solve various problems that arise during operation of the tools rather than the particular tools that amount to a number greater than 100. In addition, the fuzzing counteraction techniques are considered.
This paper discusses the use of a fully connected neural network to classify images of firing pin impressions. The purpose of this work is to investigate the effectiveness of clone images of firing pin impressions in improving the quality of training of fully connected neural networks. Another purpose of the work is to estimate the accuracy of multigroup classification of firing pin impressions left by different firearms by using a neural network. The scientific novelty of this work is in the use of augmentation for creating images of firing pin impressions to increase the number of objects in the training dataset and to artificially improve the feature diversity of objects of each class. The conducted investigation shows that the accuracy of classification of the analyzed objects reaches approximately 84% for a fixed value of the classification criterion and 94–98% when the classification is carried out based on three maximum signals on output neurons. The work is of interest to developers of automated ballistic identification systems.
In this work, a symbolic-numerical solution of Maxwell’s equations is constructed, describing the guided modes of a two-dimensional smoothly irregular waveguide in the zeroth approximation of the model of adiabatic waveguide modes. The system of linear algebraic equations obtained in this approximation is solved symbolically. The dispersion relation is solved numerically using the parameter continuation method.
The representation of elements of free non-associative algebras as a set of multidimensional tables of coefficients is defined. An operation for finding partial derivatives for elements of free non-associative algebras in the same form is considered. Using this representation, a criterion of primitivity for elements of lengths 2 and 3 in terms of matrix ranks, as well as a primitivity test for elements of arbitrary length, is derived. This test makes it possible to estimate the number of primitive elements in free non-associative algebras with two generators over a finite field. The proposed representation allows us to optimize algorithms for symbolic computations with primitive elements. Using these algorithms, we find the number of primitive elements of length 4 in a free non-associative algebra of rank 2 over a finite field.
Modern graphics accelerators (GPUs) can significantly speed up the execution of numerical problems. However, porting programs to graphics accelerators is not an easy task, sometimes requiring their almost complete rewriting. CUDA graphics accelerators, thanks to technology developed by NVIDIA, allow one to have a single source code for both conventional processors (CPUs) and CUDA. However, parallelization on shared memory is still done differently and should be specified explicitly. The use of a functional programming library developed by the authors makes it possible to hide the use of one or another parallelization mechanism on shared memory within the library and make the user’s source code completely independent of the computing device used (CPU or CUDA). This article shows how this can be done.
First differential approximation has been used to analyze various numerical methods for solving systems of ordinary differential equations. This has made it possible to estimate the stiffness of the ODE system that models the oscillations of the Van der Pol oscillator and the error of the method as well as to propose simple criteria for choosing a calculation step. The presented methods allow one to perform efficient calculations using computer algebra systems.
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