The article discusses the problems of introducing digital technologies into the decision-making process in the energy sector. For this purpose, two types of digital decision-making technologies are analyzed. The first technology - direct, which today is the main (traditional), is that the decision is made by a person - a decision maker, and a computer program acts as an “advisor” - a decision support system. The development of this technology is associated with the development of “active advisers”, when, after the implementation of the decision, a comparison is made of the decision made by the decision maker and the decision proposed by the “adviser” on the basis of so-called “recalculating models”. In the second technology (let's call it inverse), the decision is made by a computer program, and the person only observes and analyzes, without interfering in the decision-making process (with the exception of force majeure situations). In this technology, a decision support system is transformed into a decision-making system, and a decision maker becomes a decision analyst. However, the decision-making mechanism is developed by the head and other stakeholders who are responsible for the results of the operation. The necessary conditions for the effective functioning of both technologies are, firstly, the interest of participants in the presentation of reliable information required for decision-making, and secondly, interest in the implementation of decisions made (conditions of L.V. Kantorovich - V.M. Glushkov). The article provides a comparative analysis of these technologies and provides examples of their practical implementation.

In this article, an original method is proposed for address and covalent immobilization of anti-E. coli antibodies on a screen-printed electrode (SPE). The method is based on a copper-catalyzed “click” reaction between a polyvinylbenzylazide (PVBA) film electrochemically deposited on the electrode surface and acetylene fragments of propargyl-N-hydroxysuccinimide ester. The products of electrochemical oxidation of copper particles incorporated in the polymer film on the electrode were first used for catalysis of the click reaction. This approach allowed us to reduce the immobilization time from a few hours for conventional methods to just 30 min, and to prevent denaturation of the immunoreceptor. The modified electrodes were characterized by scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS), and cyclic voltammetry (CV). Based on the results obtained, a label-free impedimetric immunosensor for E. coli detection was developed. The detection limit of the immunosensor was estimated as 6.3 CFU/ml, with a linear range of 103–106 CFU/ml. The immunosensor demonstrated good stability during 30 days of storage in phosphate buffer solution (PBS, pH 7) and selectivity toward excess Staphylococcus aureus bacteria.

Distributed automatic weather stations networks (AWSN) play an important role in modern weather forecasting and digitalization of agriculture. These networks allow to monitor various environment parameters and transmit actual data in real time to data centers, which makes possible to dramatically increase the efficiency of technical processes controlling farming. Since these networks may cover large areas, weather stations may use other stations to connect to gateways via multihop routes. The nodes are deployed outdoors and they are subject to failures due to harsh environment, deterioration of equipment, battery discharge, etc. If a station is used as a relay for other nodes, after its failure other stations may also become unavailable. To study the network reliability in this paper we propose a general methodology, consisting of six consolidated procedures, and apply the apparatus of the multidimensional alternating stochastic processes. We demonstrate the application of this analytical method for a special case of the minimal topology AWSN. General topology cases are studied with the use of the simulation approach. To study the numerical results, a discrete-event simulation model in Python language was developed. The paper presents numerical reliability analysis for three types of topologies: a simple network with three stations, a forest of ternary trees and random multihop networks with one or more gateways. In all scenarios we estimate reliability for the cases of static and dynamic routing. Different ways to enhance the distributed network reliability are discussed.

The paper briefly describes a mathematical model of multiservice traffic processing in a data network. Methods for the model’s quality indicator assessment based on working out a system of equilibrium equations and its subsequent solving by means of the iterative Gauss-Seidel method are proposed. The work presents numerical results and their usage for planning the values of the model’s structural parameters such as evaluation results of the rate in the cell providing the service of specified request flows of real time and non-real time traffic with the predetermined amount of maximum losses as well as results of the rate estimation in the cell, which provides the service of the specified requests flows of elastic traffic and real time services traffic, with the specified values of the maximum losses and the average elastic traffic transfer time.

Taking account for the graph randomness, our purpose is a node classification by their extremal indexes (EI) as the local dependence measure of node influence characteristics. The EI was calculated by node PageRanks of the local tree related to the node, which is a kind of Thorny Branching Tree (TBT). The blocks estimator was used for the EI estimation by sliding and disjoint block definitions. The classification by the node EI value and the average block size for the local node TBT was introduced for simulated graphs by the Forest Fire and Erdős-Rényi Models and the Berkeley-Stanford dataset as a real example. The new classification methodology is proposed irrespective on the graph structure.