Hamiltonian theory for collective longitudinally polarized gluon excitations (plasmons) interacting with classical high-energy test color-charged particle propagating through a high-temperature gluon plasma is develop...
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The necessary and sufficient conditions of internal stability for the formations, whose dynamics is defined by linear differential equations, have been obtained. In this case, programmed controls have been chosen in t...
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A confining extension of the quark model with nonlocal currents is proposed. The quark propagator is modified by introducing a cut in α-space, which in momentum space corresponds to the subtraction of pole singularit...
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Bottom-up segmentation approaches, where words are combined into lines, lines into paragraphs, etc., are well-known nowadays. In this work, we use this principle for classification of segments. The features of the blo...
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ISBN:
(数字)9798331504663
ISBN:
(纸本)9798331504670
Bottom-up segmentation approaches, where words are combined into lines, lines into paragraphs, etc., are well-known nowadays. In this work, we use this principle for classification of segments. The features of the blocks that make up a segment and their relationships can be sufficient for classification. Our approach combines a specific choice of features that increases explainability by employing the generalizing ability of neural networks. This work presents an intermediate result, but, nevertheless, the 0.793 classification accuracy on the part of PubLayNet indicates the competitive potential of the approach. It is expected that, similar to the transition from MLP to CNN for MNIST, the transition from vector representation at our stage to GCN at the planned stage will allow us to achieve good results in document classification.
The paper presents algorithms for constructing nonlinear integral models based on the Volterra series tool. Modeling of dynamic processes means assessing the response to possible external changes in real time. The vec...
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ISBN:
(数字)9798350349818
ISBN:
(纸本)9798350349825
The paper presents algorithms for constructing nonlinear integral models based on the Volterra series tool. Modeling of dynamic processes means assessing the response to possible external changes in real time. The vector of input signals may include measured influences and control actions to be identified based on an analysis of the current state. We use identification algorithms based on the theory of Volterra polynomial equations of the first kind. An approach to the approximate solution to selected types of nonlinear systems of Volterra integral equations using the Newton-Kantorovich method is presented. We use the numerical solution to the corresponding linear system of equations as a trial solution. Calculation schemes obtained with help the standard quadrature methods are given.
Water quality affects many human activities. Remote sensing is efficient and economical instrument for water monitoring. The paper investigates the problem of choosing an algorithm for Chl-a concentration determinatio...
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Clustering is traditionally one of the basic tools of data analysis widely applied in diverse fields. By now, one of the most common clustering models is the Euclidean minimum-sum-of-squares clustering problem (MSSC)....
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The paper describes the principles of the implementation of supervisors for discrete event systems, designed with the help of automatic theorem proving in the calculus of positively constructed formulas. The main adva...
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Differential equations describing the motion of a rigid body with a fixed point under the influence of both a magnetic field generated by the Barnett–London effect and potential forces are analyzed. We seek first int...
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This paper addresses a nonconvex optimization problem where the cost function and inequality constraints are d.c. functions. Two special local search methods based on the idea of the consecutive solution of partially ...
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