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]

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]

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]

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 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 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]

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 propose a method for solving diagnosis and estimation problems based on the Jordan canonical form. The problems of constructing diagnostic observers, virtual sensors, and interval and sliding-mode observers are considered. Algorithms for solving these problems are designed for both linear and nonlinear systems in the presence of exogenous disturbances and measurement noise. It is shown that in some cases, the use of the Jordan canonical form reduces the complexity of the observers and sensors and simplifies the procedure for their synthesis compared with the identification canonical form. This is illustrated by a practical example. [ABSTRACT FROM AUTHOR]

We consider the problem of fault identification in nonlinear technical systems described by dynamic models and in their sensors in the presence of disturbances. A method based on sliding mode observers is used to solve the problem. A modification of this method is proposed which permits one to expand the family of systems for which the identification problem can be solved by weakening the constraints imposed on the original system. This modification has made it possible to reduce the complexity of diagnostic tools. The results are illustrated by practical examples. [ABSTRACT FROM AUTHOR]

We consider the problem of optimal control of a linear time-invariant discrete-time system by inaccurate measurements of its output signals subject to guaranteed satisfaction of geometric constraints on the output signals. We study the case in which a minimal realization of the system in the state space is known and the case where the parametric model of the system is not known. A novel method is proposed for solving the problem in the case of an unknown model. The method is based on a single observed trajectory of the input and output signals of the system and allows omitting the stage of parametric identification of the system. [ABSTRACT FROM AUTHOR]

A bimatrix game with deterministic payoffs and mixed strategies is considered. The probability and quantile functions of the players' losses (payoffs taken with the opposite sign) are defined. The problem of search for a Nash equilibrium is considered for these functions. It is shown that the game with probability criteria is reduced to a bimatrix game with expectation payoff functions. Necessary and sufficient conditions for the existence of an equilibrium in a game with a quantile criterion are obtained. A theorem on the relation between equilibria in games with quantile and probability criteria is proved. An algorithm for searching equilibria in the game with a quantile criterion is proposed. The algorithm is based on successively solving problems of searching for points belonging to sets described by quadratic nonconvex constraints. Approaches to finding these points are proposed. Results of calculating equilibrium pairs of strategies are given. [ABSTRACT FROM AUTHOR]

The synthesis of a control law for tracking a target informative path as a new approach to solving the problem of planning a flight experiment for identifying the aerodynamic characteristics of automatically controlled aircraft is proposed. The mathematical statement and the method for solving the synthesis problem are obtained. In the numerical experiment, it is shown that the identification accuracy on the synthesized control can be significantly improved compared to the identification accuracy on the optimal program test signal. [ABSTRACT FROM AUTHOR]

An original analytical method is developed to design the selectively invariant control systems for nonlinear plants with differentiable nonlinearities. To solve the design problem, the method of designing nonlinear control systems is applied on the base of a quasilinear model of nonlinear plants and the internal models principle of external impacts is used, taking into account the requirements for the relative order of the control device and the fast response of the designed system. The system of linear algebraic equations is solved to determine the parameters of the nonlinear control device. The suggested method can be applied to design the control systems for nonlinear plants of various purposes, operating under conditions of regular external impacts of the known form. [ABSTRACT FROM AUTHOR]

Сontrolling the docking of noncooperative spacecraft requires information about the relative position of the active and passive spacecraft. This problem is solved by relative optical navigation systems that analyze visible images, identify (recognize) the observed spacecraft, and measure relative linear and angular coordinates. Since the aspect at which the passive spacecraft is observed can vary over a wide range (up to a full sphere), the image of the passive spacecraft itself changes accordingly over a wide range. Therefore, to solve the identification and measurement problems, a sufficiently large number of reference images is required. The article proposes a way to considerably reduce the number of reference images used to form a cover of the uncertainty area. [ABSTRACT FROM AUTHOR]

We consider the problem of decoding a two-valued monotone function defined on a -valued -dimensional cube. The traditional approach to solving this problem is to construct a Shannon-optimal algorithm. The Shannon-optimal decoding algorithm has minimal "worst-case" complexity (efficient for the most difficult case). The authors propose and study an approach to the decoding problem based on the application of an asymptotically optimal dualization algorithm over the product of -valued chains. The asymptotically optimal decoding of the function is aimed at the "typical case" (typical version of the problem). The conditions for the applicability of the traditional and new approaches are experimentally revealed. [ABSTRACT FROM AUTHOR]

We consider the problem of synthesizing simple structured relay controllers as part of a self-oscillatory system with a linear plant. The controller structure is said to be simple if it cannot be simplified since any further simplification that consists in excluding any element from it leads to the impossibility of satisfying all the requirements for the system. It is necessary to ensure the presence of self-oscillations with a given frequency and amplitude in the system and bring its behavior closer to the desired one. A method for solving the problem under consideration is proposed. [ABSTRACT FROM AUTHOR]

The least upper bound for the probability that a random vector with fixed mean and covariance will be outside the ball is found. This probability bound is determined by solving a scalar equation and, in the case of identity covariance matrix, is given by an analytical expression, which is a multivariate generalization of the Selberg bound. It is shown that at low probability levels, it is more typical when the bound is given by the new expression if compared with the case when it coincides with the right-hand side of the well-known Markov inequality. The obtained result is applied to solving the problem of hypothesis testing by using an alternative with uncertain distribution. [ABSTRACT FROM AUTHOR]

We consider a new algorithm for estimating the time-varying parameter of a noiseless sinusoidal signal . It is assumed that the unknown parameters and of the sinusoidal signal are functions of time that are solutions of linear time-invariant differential equations with known coefficients but unknown initial conditions. The problem is solved using gradient tuning algorithms based on a linear regression equation obtained by parametrizing the original parameter-nonlinear sinusoidal signal. An example and results of computer simulation illustrate the efficiency of the proposed algorithm and also explain the procedure for its synthesis. [ABSTRACT FROM AUTHOR]

A rationality-bounding condition is formulated: when jointly solving control, communication, and computing problems (С ), an optimal solution (control action) can be impossible to find due to real-time requirements, and almost optimal solutions have to be used instead (the best ones found under the existing constraints on the search procedure). This condition interconnects common concepts in control and optimization such as requisite variety, bounded rationality, analytical complexity, heuristics, and records in real-time optimization, demonstrating their unity and deep relationship. For the institutional control of organizational and technical systems, several applications-relevant problems are solved: minimizing the error or complexity, finding a critical capacity of a communication channel and a critical rate of computing, and determining the maximum number of controlled subsystems. [ABSTRACT FROM AUTHOR]

An analysis of the currently used methodology for selecting the composition of the included generating equipment is carried out in relation to a CHPP with a complex composition of equipment based on traditional heating units and combined-cycle plants (CCGT). It is revealed that the specified problem is solved on the basis of an economic criterion without taking into account the reliability factor. The features of CCGT operating modes and the problems of taking them into account when choosing options for the composition of CHPP equipment are given by the example of CCGT-450. A technique for taking into account the reliability factor when choosing and reducing the number of acceptable options according to the criterion of minimal generalized risk is proposed. It is shown that its application makes it possible to determine the priority procedure for considering acceptable options in order to select the optimal one, which will ensure reliable operation in the electricity market and maximize profits. With regard to CHPPs with PT-80 and CCGT-450 heating units, an algorithm for selecting possible CCGT operating modes during the passage of a load dip in the winter period of the plant operation is considered. The general approaches to solving the problem taking into account the proposed approach to allowing for the reliability factor are considered. [ABSTRACT FROM AUTHOR]

A number of methods and examples are considered that substantiate the possibility and expediency of using the actional approach to solving applied problems of analyzing information processes in active network structures. [ABSTRACT FROM AUTHOR]

We propose a method for test signal planning for identifying the aerodynamic characteristics of automatically controlled aircraft taking into account possible errors in a priori estimates of aerodynamic characteristics and the uncertainty in the initial conditions of the test maneuver. This method can be used in test signal planning problems with constraints on the admissible disturbances of the state vector of the aircraft in the test maneuver. [ABSTRACT FROM AUTHOR]

We consider the NP-hard problem of optimizing the sequence and times of aircraft landings under necessary constraints. It is impossible to obtain an exact solution of the problem online owing to the large amount of calculations. An integrated approach is proposed to produce an approximate solution: a genetic algorithm is applied at the first stage to obtain an initial solution; this algorithm is then improved based on a heuristic algorithm. The approach proposed permits obtaining optimal or nearly optimal solutions in reasonable time. To study the algorithms developed, a simulation software tool was used. Extensive computational experiments have confirmed the efficiency of the approach. [ABSTRACT FROM AUTHOR]

The most important unsolved problem of control theory is the problem of optimizing a multiplicative stochastic system in the class of noisy output signal controllers. The controller in the feedback loop must be feasible; i.e., it must ensure the stability of the closed-loop system and guarantee the required level of suppression of exogenous disturbances acting on the plant. In this article, within the framework of the stochastic -control theory in the presence of noise, we solve the problem of analysis, i.e. finding conditions for the existence of feasible controllers. The results obtained can be used further in the synthesis problem for conditional optimization of a multiplicative stochastic system in the class of feasible dynamic controllers. [ABSTRACT FROM AUTHOR]

A new approach is proposed for solving the problem of suppressing nonrandom bounded exogenous disturbances in linear control systems using dynamic output feedback. The approach is based on reducing the problem to a matrix optimization problem with the feedback matrix and the observer matrix as the variables. A gradient method for finding dynamic output feedback is written out and justified. A number of examples are considered. [ABSTRACT FROM AUTHOR]

It is proposed to expand the capabilities of the metric approach for solving special problems, for example, in scheduling theory, by weakening the requirements for the metric axioms or by introducing probability proximity measures. The author's results are considered at the junction of the theory of means and the research area dealing with expert error indicators set axiomatically. The result obtained by Academician A.N. Kolmogorov when he considered a system of axioms for deriving an analytical formula for the associative mean is strengthened. [ABSTRACT FROM AUTHOR]

An efficient method for solving the classical NP-hard problem of scheduling theory for one device—the problem of minimizing the total delay —is presented. An algorithm for solving the problem is proposed based on the decomposition of the original problem into subproblems of timely servicing each of the requests and placing those of them for which the increase in the delay is most compensated for by the reduction in the delay of the previous requests at the end of the schedules. The complexity of the algorithm does not exceed operations, where is the number of requests. [ABSTRACT FROM AUTHOR]

We consider the problem of estimating the queuing system structure and parameters when implementing the system of optimal switching of the main service channels at control times separated from each other by a fixed time step. Expert classification analysis, structural forecasting, and expert statistical data processing procedures are proposed to solve the problem of assessing the model structure and parameters. [ABSTRACT FROM AUTHOR]

We consider knowledge-oriented models, problems, and algorithms for routing traveling salesmen in complex networks. The formalization leads to models of pseudo-Boolean discrete optimization with constraints that take into account the specifics of the multiple traveling salesmen problem. We consider a class of problems that can be represented in the form of pseudo-Boolean optimization models with separable objective functions (monotone, linear) and constraints in the form of disjunctive normal forms (DNFs). We demonstrate the possibility of an approximate synthesis of DNF constraints based on precedent information. The methodology, theoretical principles, and algorithms for solving problems of this class are presented. It is shown that the solution of routing problems can be based on the application of a multiagent approach in combination with clustering of the original problem, pseudo-Boolean optimization algorithms with disjunctive constraints, and metaheuristics. [ABSTRACT FROM AUTHOR]

The article deals with some approaches to solving convex problems of the min-min type with smoothness and strong convexity in only one of the two groups of variables. It is shown that the proposed approaches based on Vaidya's method, the fast gradient method, and the accelerated gradient method with variance reduction have linear convergence. It is proposed to use Vaidya's method to solve the exterior problem and the fast gradient method to solve the interior (smooth and strongly convex) one. Due to its importance for applications in machine learning, the case where the objective function is the sum of a large number of functions is considered separately. In this case, the accelerated gradient method with variance reduction is used instead of the fast gradient method. The results of numerical experiments are presented that illustrate the advantages of the proposed procedures for a logistic regression problem in which the a priori distribution for one of the two groups of variables is available. [ABSTRACT FROM AUTHOR]

We consider a system of nonlinear discrete-time equations subject to the influence of a discrete random process of the "white" noise type. It is assumed that the system admits a "partial" (with respect to some part of state variables) zero equilibrium. The problem of partial stability in probability is posed—the stability of a given equilibrium is not with respect to all but only to part of the variables determining it. To solve the problem, a discrete-stochastic version of the Lyapunov function method is used with the appropriate refinement of the requirements for the Lyapunov function. To expand the capabilities of the method used, it is proposed to correct the domain in which the auxiliary Lyapunov function is constructed; this is achieved by introducing an additional (vector, generally speaking) auxiliary function. Conditions of partial and asymptotic stability in probability in the indicated form are obtained. An example is given showing the specific features of the proposed approach. [ABSTRACT FROM AUTHOR]

As part of the synthesis of a tracking system for an unmanned aerial vehicle (UAV) exposed to uncontrolled external disturbances under the conditions of incomplete measurements of the state vector, we develop procedures for synthesizing novel low-order state and disturbance observers that do not require constructing dynamic models of external inputs. The observation subsystem includes two state observers. One of them estimates the velocities based on measurements of the UAV center of mass coordinates. The other observer uses the measurements of tracking errors to give estimates of mixed variables (state functions, external inputs, and their derivatives) from which the feedback is directly formed. It is noted that implementing the developed algorithms, which do not involve readjustment when external inputs change, will increase the UAV control system functionality and its reliability in the event of failure of measuring devices. The efficiency of our approach to tracking system synthesis is confirmed by numerical simulation results. We present the results of comparative analysis of closed-loop systems with static (under the assumption that all internal and external variables are measured) and dynamic feedback that uses two approaches to solving the problem of estimation under external disturbances—high-gain observers and observers with piecewise linear bounded corrective inputs. It is shown that, despite the simpler setup, it is expedient to use observers of the second type in linear feedback systems, while high-gain observers will be in demand in systems with a priori bounded controls. [ABSTRACT FROM AUTHOR]

We survey the progress in data mining methods for spacecraft health monitoring. The main emphasis is placed on the analysis of telemetry data enabling the identification of spacecraft states that are atypical during normal operation and the prediction of possible failures in the operation of the spacecraft or its components. The main stages required for the creation of general-purpose spacecraft state monitoring systems are considered; methods for detecting anomalies in telemetry data taking into account the specific features of the spacecraft are presented in detail; and publications on this topic known to the authors are analyzed. Examples of the implementation of such systems in flight control centers of various countries are given. The promising areas of development of methods for analyzing the technical state of complex systems relevant for solving problems in space technology are discussed, and the main factors that hinder the development of machine learning methods for analyzing telemetry data are noted. [ABSTRACT FROM AUTHOR]