Search

In this paper, we solve the problem of detecting anomalies in X-ray images obtained by full-body scanners (FBSs). The paper describes the sequence and description of image preprocessing methods used to convert the original images obtained with an FBS to images with visually distinguishable anomalies. Examples of processed images are given. The first (preliminary) results of using a neural network for anomaly detection are shown. [ABSTRACT FROM AUTHOR]

The paper proposes a predictive approach to assessing special classes of dangerous states in the development of technological processes in order to make proactive decisions. The developed approach is based on a hybrid model based on the combination of an evidence-based classifier, fuzzy logic, and a Dempster–Shafer probabilistic scheme for evidence combination. The article presents a formal description of the predictor of critical states of the technological process. The resulting approach is universal and applicable in the automation of any complex technical systems. As an example, this article considers the application of the developed approach to solve the problem for assessing the safety of the technological process of shunting trains on a hump yard. The presented example shows the high efficiency and practical usefulness of the developed approach. [ABSTRACT FROM AUTHOR]

This paper considers the multi-depot vehicle routing problem with object alternation. We propose a formal statement of the problem with two types of objects and a mathematical model with two blocks of Boolean variables. First, the model is studied without gathering vehicles (mobile objects). Then, a special object (a single collection point) is introduced in the model. We show additional constraints of the mathematical model with this object. Special attention is paid to the condition of no subcycles. This condition is considered based on the adjacency matrix. Five greedy algorithms are proposed for solving the problem, two of which are iterative. One of the greedy algorithms is given a probabilistic modification based on the randomization of variables (an adaptive algorithm). Finally, the proposed algorithms are compared in terms of the average value of the objective function and the running time in a computational experiment. Also, the results of another experiment—the parametric tuning of the adaptive algorithm—are presented. [ABSTRACT FROM AUTHOR]

The paper deals with the construction of interpretable machine learning models. The approximation problem is solved for a set of shapes on a contour image. Assumptions that the shapes are second-order curves are introduced. When approximating the shapes, information about the type, location, and shape of curves as well as about the set of their possible transformations is used. Such information is called expert information, and the machine learning method based on expert information is called expert-augmented learning. It is assumed that the set of shapes is approximated by the set of local models. Each local model based on expert information approximates one shape on the contour image. To construct the models, it is proposed to map second-order curves into a feature space in which each local model is linear. Thus, second-order curves are approximated by a set of linear models. In a computational experiment, the problem of approximating an iris on a contour image is considered. [ABSTRACT FROM AUTHOR]

The paper considers the problem of visual odometry based on a sequence of video frames formed using a camera perpendicularly downward facing the reference surface. The problem is solved under the assumption that the shooting frequency is high, so that the interframe rotation and shift parameters are small. The technology is implemented in the form of a sequence of the following steps: determining the shift and rotation with an accuracy of an integer number of pixels using the correlation method, clarifying the shift and rotation parameters using the optical flow method, and correcting estimation errors associated with uneven motion and fluctuations in the distance of the camera to the reference surface by estimating deviations of local calibration characteristics from their mean values. The results of experimental studies of the technology on test trajectories obtained by simulating the motion of a vehicle along the reference surface are presented. [ABSTRACT FROM AUTHOR]

We study the implementation of the optimal control strategy obtained in [1] and supplemented in [2]. The algorithm for optimal stabilization of a linear stochastic differential system in a position determined by a piecewise constant Markov drift has been tested in a substantial number of model experiments. The drift value is observed indirectly; i.e., the control problem is solved in the statement with incomplete information. Practical implementation is complicated by the instability of Euler–Maruyama numerical schemes that implement the Wonham filter, which is a key element of the optimal control strategy. To perform calculations, the Wonham filter is approximated by stable schemes based on the optimal filtering of Markov chains by discretized observations [3]. These schemes have different implementation complexity and orders of accuracy. The paper presents a comparative analysis of the control performance for various stable approximations to the Wonham filter and its typical implementation using the Euler–Maruyama scheme. In addition, three versions of discretized filters are compared and final recommendations are given for their application in the problem of stabilizing a system with hopping drift. [ABSTRACT FROM AUTHOR]

The paper deals with the problem of triclustering in multivalued triadic contexts in terms of one multidimensional extension of formal concept analysis; triclustering can be viewed as a search for dense subtensors in three-dimensional tensors over the field of real numbers. Two methods are proposed for solving this problem, namely, NOAC—a version of the OAC triclustering method for numerical data based on delta operators—and a triadic version of the -means method with an improved metric based on Manhattan distance and proximity predicates in each of the three dimensions. Numerical experiments are carried out both on real and synthetic data and confirm the superiority of the NOAC method in terms of the performance criteria for the resulting triclusters. [ABSTRACT FROM AUTHOR]

We consider the problem of stabilizing a cart moving along a straight line with an inverted pendulum installed on it. The control objective is to stabilize the cart at a given target point so that the pendulum is in the upper vertical position. The main difficulty associated with solving this problem is that the two subsystems (the cart and the pendulum) must be stabilized simultaneously using one control. A new control law is proposed based on the introduction of a second-order reference system, the trajectory of which is taken as the target one for the cart with the pendulum. By extending the reference system to the fourth order and introducing an algebraic condition coupling the two systems, the target trajectory is found in the four-dimensional phase space of the original system and a control law is constructed that ensures the trajectory of the closed-loop system asymptotically approaching the target one. The control law obtained in this paper is applicable to systems with an arbitrary ratio of pendulum and cart masses, since the closed-loop system does not depend on the mass characteristics of the system. The range of the system parameters is found for which the linearized system is stable. The presentation is illustrated with numerical examples that demonstrate the efficiency of the proposed control. [ABSTRACT FROM AUTHOR]

The paper is based on using methods of continuous mathematics in discrete problems. Three new approaches to solving scheduling theory problems are considered, namely, a metric approach, an interpolation approach, and a combined one (metric interpolation). Metric interpolation is a mix of the other two approaches and combines their advantages. Each of these approaches permits one to reduce the time required for solving the corresponding problems and calculate the values of the guaranteed absolute error of the objective function. [ABSTRACT FROM AUTHOR]

We propose a dead-end control algorithm for the exact solution of NP-hard combinatorial optimization problems. The efficiency of the algorithm is demonstrated by examples of solving the set-partition and 0-1 knapsack problems. The paper also shows that the use of the idea of dead-end controls when implementing the dynamic programming method can considerably reduce the number of problem state variables at each optimization step. A comparative analysis of the proposed method with known algorithms for solving these problems is carried out. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of determining politico-ideological preferences of users of online social networks. We propose a (DLS) model that allows assessing politico-ideological preferences of VKontakte users using information from their accounts (digital footprints). The model meets the main ideological directions in modern-day Russia. Our approach is based on the supervised learning methodology whereby one solves a classification problem by calculating posterior probabilities of class membership. We compile an anonymized labeled dataset and develop appropriate software. Then we formulate and solve the problem of the politician's choice of an ideological positioning strategy that will potentially receive the most support from the considered set of users. We exemplify our methodology by finding "ideal" political positioning for some popular online communities in VKontakte. [ABSTRACT FROM AUTHOR]

We consider a class of hyperbolic systems of linear inhomogeneous partial differential equations with one spatial variable. As a rule, in the case of systems of partial differential equations, when solving particular problems, additional conditions are immediately used to ensure the uniqueness of the solution. However, this greatly complicates the construction of a solution in the case of additional conditions of nonstandard form. For a similar situation in the case of ordinary differential equations, one tries to find a general solution, for which one can then try to use the given additional conditions. However, for systems of partial differential equations, this approach is difficult, since, as a rule, in this case it is not possible to construct the general solution. For the class of systems of linear inhomogeneous partial differential equations considered in the present paper, it was possible to find an algorithm for constructing a general solution. A distinctive feature of the considered systems of equations is the multiplicity of the corresponding characteristics. As an application of the proposed algorithm, a general solution of the Kolmogorov system of equations for the probabilities of the states of a process is obtained, which describes the behavior of a popular model of a stochastic system of the type -out-of- with a general distribution of the repair time for failing components. The indicated system of Kolmogorov equations is a system of partial differential equations of the mentioned class. Therefore, it is possible to construct a general solution for this system. [ABSTRACT FROM AUTHOR]