Программные системы: теория и приложения @programmnye-sistemy
Статьи журнала - Программные системы: теория и приложения
Все статьи: 449
A note on migration perturbation and convergence rates to a steady state
Статья научная
Using tools developed in the Markov chains literature, we study convergence times in the Leslie population model in the short and middle run. Assuming that the population is in a steady state and reproduces itself period after period, we address the following question: how long will it take to get back to the steady state if the population distribution vector was affected by some shock as, for instance, the “brain drain”? We provide lower and upper bounds for the time required to reach a given distance from the steady state.
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A picture of common subsequence length for two random strings over an alphabet of 4 symbols
Статья научная
The maximal length of longest common subsequence (LCS) for a couple of random finite sequences over an alphabet of 4 characters was considered as a random function of the sequences lengths and 𝑛; Exact probability distributions tables are presented for all couples of length in a range 2
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An FPGA packet communication protocol
Статья научная
When creating computer boards with FPGA or application-specific chips, it is often needed to connect several chips. Existing available buses do not have all the properties required by the authors' task at hand: packet transmission, using a small number of GPIO pins, sufficient bandwidth.We describe a packet communication protocol that uses GPIO pins and has bandwidth up to 10 MB/s at a frequency of 20 MHz.
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Analytical design of controllers for discrete-continuous systems with linear control
Статья научная
The study focuses on a certain kind of discrete-continuous systems (DCS): the linear hybrid DCS with state-dependent coefficients. The authors proposed a problem similar to the analytical design of optimal controllers (ADOC). For this study, we generalized the Krotov sufficient optimality conditions. The paper includes several examples.
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Approximate optimal control synthesis for nonuniform discrete systems with linear-quadratic state
Статья научная
Nonuniform discrete systems linear-quadratic over its state are the subject of intense study in optimal control theory. This work presents an approximate optimal control synthesis method in this class based on Krotov’s sufficient optimality conditions and illustrates it with a simple example.
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Статья научная
Malware detection is essential in cybersecurity, yet its accuracy is often compromised by class imbalance and limited labeled data. This study leverages conditional Generative Adversarial Networks (cGANs) to generate synthetic malware samples, addressing these challenges by augmenting the minority class. The cGAN model generates realistic malware samples conditioned on class labels, balancing the dataset without altering the benign class. Applied to the CICMalDroid2020 dataset, the augmented data is used to train a LightGBM model, leading to improved detection accuracy, particularly for underrepresented malware classes. The results demonstrate the efficacy of cGANs as a robust data augmentation tool, enhancing the performance and reliability of machine learning-based malware detection systems.
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Статья научная
This paper is devoted to the study of interrelated thermal processes in a submersible electric motor of a pumping unit located in an oil-producing well and flowed around by a water-oil-gas reservoir mixture, taking into account the heat exchange of the flow with the rocks surrounding the well. To describe these processes, mathematical and numerical models are developed. The numerical model and algorithms are implemented in a software that allows to study temperature fields and various thermal effects using computational experiments with simultaneous visualization of the results of computations. It is shown, in particular, that the transient thermal processes in the system “motor - three-phase flow - rocks”, when the motor is turned off due to its heating to the maximum permissible temperature depend on the physical and geometrical characteristics of each element of the system and are characterized by a non-trivial temperature profiles in rocks. Calculated estimates of the duration (on the order of tens of minutes) of the cooling stage of the motor after it is turned off and its heating stage when it is turned on again correspond to the real times of these processes in producing oil wells.
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Clustering of handwritten digits by Kohonen neural network
Статья научная
Clustering of handwritten digits is carried out for sixty thousand images contained in the training sample of the MNIST database. For clustering, the Kohonen neural network is used. For each handwritten digit, the optimal number of clusters (no more than 50) is determined. When determining the distance between objects (images of handwritten digits), the Euclidean norm is used. Checking the correctness of building clusters is carried out using data from the test sample of the MNIST database. The test sample contains ten thousand images. It is concluded that the images from the test sample belong to the "correct digit" cluster with a probability of more than 90{\%}. For each digit, an F-measure is calculated to evaluate the clusters. The best F-measures are obtained for digits 0 and 1 (F-mean is 0.974). The worst values are obtained for the number 9 (F-mean is 0.903). A cluster analysis is also carried out, which allows drawing conclusions about possible errors in recognition by the Kohonen neural network. Intersections of clusters for images of handwritten digits are constructed. Examples of intersections of clusters are given, as well as examples of images that are incorrectly recognized by the neural network.
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Complexity of Computations with Time Travel
Статья научная
This paper explores a mathematical model of computation that can be interpreted as a computer capable of receiving data from future states of its own computational process. Under certain combinations of input data and programs, such computations may become infeasible due to emerging contradictions or lead to ambiguous outcomes. We investigate programs for which this process is always feasible and yields a unique result. It is demonstrated that, in the absence of computational complexity constraints, such machines can output the value of any recursively decidable predicate within a fixed time after the computation begins—referred to as the response delay time—while the computation process must continue even after the result is produced. When the total runtime of these machines is bounded by a polynomial function of the input size, they precisely recognize languages belonging to the intersection of the NP and co-NP complexity classes, with the same constant response delay time in the aforementioned sense. Possible practical implementations of such a computer are examined, including an analysis of operational protocols leveraging quantum annealing to select the appropriate computational process. It is shown that, with parallelization of the computational process, the class of problems solvable by these machines in polynomial time corresponds to the PSPACE complexity class. Additionally, a mode of operation is studied in which these machines have direct access to input data. In this case, if the runtime is limited to a logarithmic function of the input size, the class of problems solvable by such a parallelized computer encompasses LOGSPACE The findings of this study can be applied to develop new programming principles for nondeterministic computational machines, where data transmission from the future is employed instead of nondeterministic choices.
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Desktop Grid корпоративного уровня
Статья научная
В работе рассказывается о системах Desktop Grid корпоративного уровня, их возможностях, отличительных особенностях и приложениях. Даны примеры реализации систем промежуточного программного обеспечения, предназначенных для организации корпоративных Desktop Grid.
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Detecting states of ion channels on the cell membrane using neural networks
Статья научная
The problem of automating the process of analyzing the open states of channels on the membrane of a neuron of a living organism is considered. Taking into account that the registration of the electrical activity of the cell was made by the patch clamp method at various values of the applied potential, a division into intervals with a constant potential is carried out. Further, to eliminate noise, a notch filter, low-frequency and high-frequency Chebyshev filters are applied to the data. A neural network is applied to the normalized data, based on the results of which the data is changed and re-processed by the same neural network. As a result of the algorithm, the dynamics of channel states was obtained, which makes it possible to register up to several open channels simultaneously.
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Etherbox: протокол для управления модульной сенсорной сетью
Ред. заметка
Протокол прикладного уровня Etherbox предназначен для взаимодействия управляющего компьютера с узлами сенсорной сети в форме исполняемых программ виртуальной машины, что позволяет обеспечить гибкость в управлении, необходимую для сенсорных сетях с модульной конструкцией узлов. В статье описаны принципы функционирования сенсорной сети, использующей протокол Etherbox, в сравнении с сетями, использующими протоколы MQTT-SN и CoAP. Рассматривается архитектура программного обеспечения снесорных узлов и управляющего компьютера.
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Existence of global fundamental solution to a class of Fokker-Planck equations
Ред. заметка
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Статья научная
A hybrid method of global optimization NNAICM-PSO is presented. It uses neural network approximation of inverse mappings of objective function values to coordinates combined with particle swarm optimization to find the global minimum of a continuous objective function of multiple variables with bound constraints. The objective function is viewed as a black box.The method employs groups of moving probe points attracted by goals like in particle swarm optimization. One of the possible goals is determined via mapping of decreased objective function values to coordinates by modified Dual Generalized Regression Neural Networks constructed from probe points.The parameters of the search are controlled by an evolutionary algorithm. The algorithm forms a population of evolving rules each containing a tuple of parameter values. There are two measures of fitness: short-term (charm) and long-term (merit). Charm is used to select rules for reproduction and application. Merit determines survival of an individual. This two-fold system preserves potentially useful individuals from extinction due to short-term situation changes.Test problems of 100 variables were solved. The results indicate that evolutionary control is better than random variation of parameters for NNAICM-PSO. With some problems, when rule bases are reused, error progressively decreases in subsequent runs, which means that the method adapts to the problem.
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Improving the accuracy of segmentation masks using a generative-adversarial network model
Статья научная
Masks obtained using the deep learning model Mask R-CNN may in some cases contain fragmented contours, uneven boundaries, false fusions of adjacent objects, and areas with missed segmentation. The more detection objects in the image and the smaller their size, the more often various types of defects in their masks are encountered. Examples of such images include aerial photographs of cottage and garden associations and cooperatives characterized by high building density. To correct these defects, it is proposed to use a generative adversarial network model that performs post-processing of the predicted Mask R-CNN masks. A qualitative assessment of the model formed in the work demonstrated that it is capable of restoring the integrity of contours at an acceptable level, filling in missing areas, and separating erroneously merged objects. Quantitative analysis using the IoU, precision, recall, and F1-score metrics showed a statistically significant improvement in the segmentation quality compared to the original Mask R-CNN masks. The obtained results confirmed that the proposed approach allows to increase the accuracy of the formation of object masks to a level that satisfies the requirements of their practical application in automated aerial photograph analysis systems.
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Local competing in interpolation problems
Статья научная
A simple example illustrates the insufficiency of the known approaches to interpolation in the problem of recovering a function from a few given specific values that clearly convey the form. A local choice between polynomial and rational local interpolants, which minimizes the local interpolant's errors at the nearest external nodes from one or different sides, complements the known approaches. It combines the extreme computational simplicity of local interpolants with the thorought selection of them. The principles of constructing the algorithm are formulated in general terms for mappings of metric spaces. They provide accurate (with rare exceptions) reconstruction of mappings that locally coincide with some of the given possible interpolants. In the one-dimensional case, the two-stage algorithm guarantees the continuity of the interpolant and accurately reconstructs {[itemindent=1cm] polynomials of small degree, simple rational functions with a linear denominator, broken lines of long links with knots at the ends } when these requirements do not contradict each other. An additional parameter allows you to replace the exact restoration of polylines with the required smoothness of interpolation.
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Memory-efficient sensor data compression
Статья научная
We treat scalar data compression in sensor network nodes in streaming mode (compressing data points as they arrive, no pre-compression buffering). Several experimental algorithms based on linear predictive coding (LPC) combined with run length encoding (RLE) are considered. In entropy coding stage we evaluated (a) variable-length coding with dynamic prefixes generated with MTF-transform, (b) adaptive width binary coding, and (c) adaptive Golomb-Rice coding. We provide a comparison of known and experimental compression algorithms on 75 sensor data sources. Compression ratios achieved in the tests are about 1.5/4/1000000 (min/med/max), with compression context size about 10 bytes.
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Methods for anchoring boundary nodes when smoothing a triangular surface mesh
Статья научная
In numerical modeling tasks that use surface meshes, remeshing is often required. However, while remeshing, distortion can occur. The accumulation of distortions can lead to the collapse of the solution. Smoothing algorithms are used to maintain the quality of the mesh during the calculation. When performing smoothing using methods that shift the mesh nodes, the border nodes are usually fixed to avoid distortion. However, simply fixing the nodes can lead to more severe distortion. This paper presents methods for working with boundary nodes to control such nodes during the smoothing process. Algorithms for working with pseudo-3D surface meshes, which are of particular interest, are also considered
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