The article is devoted to the issues of optimizing the process of technical inspection of buildings and structures damaged as a result of emergency situations, using the most modern information systems and technologies. The difficulty in carrying out work on the inspection of buildings damaged as a result of natural and man-made emergencies necessitates the search for effective organizational and technological solutions in order to reduce the time required to carry out work on the inspection of buildings and structures without losing the quality and accuracy of the studies, as well as to create safe working conditions for specialists during work.

Keywords: technical inspection, emergency situation, digital building model, ground penetrating radar sensing, information technology, geographic information technology

The article views the process of preparing territories damaged by the war for housing stock restoration and it describes the main measures that need to be carried out in the damaged neighborhoods, depending on their degree of damage. These activities in the article are divided into two groups: the first for moderately damaged quarters, and the second for severely damaged quarters. The works from the first group are somewhat different from the ones in the second. For example, the decision to restore moderately damaged quarters requires temporary strenghtning and temporary protection of damaged buildings, while in severely damaged quarters, demolition of all buildings is required. In addition, the quantity of work in the second group is larger compared to the quantity in the first due to the need to demolish all buildings, dismantle all outdoor networks and lay new ones. However, the advantages of constructing works in these quarters are that it is possible to speed up the work due to the variety of implementation methods and the equipment that can be used.

Keywords: post-conflict reconstruction, demining of territories, preparatory works, technical condition of damaged buildings

The paper presents the results of a study, the purpose of which was to automate the process of designing ventilation for a residential construction project. The ventilation system is one of the most complex life support systems of a building, which has a significant impact on the level of comfort of residents. Automation of the design of such a system will reduce the number of errors, reduce the time and labor required for design. During the study, the design process was considered as a business process consisting of individual works. When modeling this process in the “As Is” notation, the connection of the ventilation system with other engineering systems and a number of other important factors were taken into account. In the process model, the most time-consuming and, at the same time, algorithmizable works were identified. Subsequently, these works were automated using code created in the Visual Studio environment in C#. This made it possible to reduce the number of errors and reduce the time spent on creating a ventilation system project.

Keywords: automation, design, ventilation system, business process, Visual Studio

The article considers the problem of cryptanalysis of an information security system based on a difficult-to-solve problem of Diophantine equations. A mathematical model of such a protection system is described in the article and a solution to the cryptanalysis problem using an artificial immune system adapted for solving Diophantine equations is proposed. The paper discusses the basic principles of building artificial immune systems and presents the results of experiments on evaluating the effectiveness of the proposed system of Diophantine equations of a degree not exceeding six. The results obtained demonstrate the possibility of using artificial immune systems to solve the problem of cryptanalysis of information security systems based on Diophantine equations.

Keywords: cryptanalysis, information security system, diophantine equations, artificial immune system, adaptive algorithm, efficiency assessment

The article explores the interaction of Tello EDU, a small-sized educational drone, with Turtlebot3, an unmanned ground vehicle, in rooms with a weak signal. The article examines how, using a local network and the robot operating system (ROS), it is possible to achieve effective collaboration between these two devices. It analyzes how a local network can be used to broadcast data and monitor devices in conditions of a weak external signal. The role of ROS as the main tool for managing and interacting with devices is being investigated. In addition, the article examines specific use cases, including interaction and coordination between Tello EDU and Turtlebot3. A diagram of the interaction of two unmanned vehicles is also presented, a detailed description of their operation is described, and Python code is presented using various libraries based on the ROS robotic operating system.

Keywords: Tello Edu, operating system (ROS), UAV, local area network, Wi-fi, nodes, SLAM, weak signal, route planning, autonomous robot, Turtlebot3

The article describes a technique for constructing a non-fuzzy model for selecting contour points on an image. The technique includes the following steps: the formation of linguistic variables “pixel brightness difference” and “a sign that a pixel belongs to a contour”, the formation of a knowledge base of a neuro-fuzzy model using a binary image, the formation of a training set using both grayscale and contour images, training a neuro-fuzzy model using genetic algorithm. A feature of the presented genetic algorithm is - checking the conditions for the correctness of the values of the parameters of the membership functions obtained during the generation of chromosomes. Described the structure of a neuro-fuzzy model for making a decision about whether a pixel belongs to a contour. Presented the result of applying a neuro-fuzzy model for constructing image contours.

Keywords: neuro-fuzzy model, contour image, contour extraction, contour pixel, linguistic variable, fuzzy set, membership function, genetic algorithm, Tsukamoto inference, neuro-fuzzy model learning

Determining human emotions from speech is a pressing task at the moment, because it can be applied in various industries, such as economics, medicine, marketing, security and education. This work examines the recognition of human emotions specifically from speech, because speech is an informative indicator that is quite difficult to fake. The paper discusses a neural network approach to solving the problem. A recurrent neural network with LSTM memory was implemented, and our own dataset was collected on which the model was trained. The dataset includes the speech of Russian-speaking actors, which will improve the quality of the model for Russian-speaking users.

Keywords: neural network, emotion detection, speech, classification, deep learning, recurrent model, LSTM

This article discusses the theoretical and practical aspects of remotely connecting a user to an automation system controller, as well as analyzes the main methods and technologies used in this process.

Keywords: industrial controllers, remote connection to the controller, Modbus TCP

The article presents a mathematical model for assessing the applicability of intelligent chatbots in the context of studying dialects of foreign languages. The model is based on the analysis of key parameters and characteristics of chatbots, as well as their ability to adapt to various dialects. The model's parameters include questions, answers, evaluation criteria, types, and costs of errors. The quality of the chatbot's responses is evaluated both according to individual criteria and overall. To test the effectiveness of the proposed method, an experimental study was conducted using the dialects of the German language as examples. During the research, such intelligent chatbots as ChatGPT-3.5, GPT-4, YouChat, Bard, DeepSeek, and Chatsonic were evaluated. The analysis of the results of applying the developed mathematical model showed that at present, the models by OpenAI (ChatGPT-3.5 and GPT-4) offer the broadest range of possibilities. ChatGPT-3.5 demonstrated the best results in communication in Bavarian and Austrian dialects, while YouChat excelled in the Swiss dialect. The obtained results allow for important practical recommendations to be made for selecting intelligent chatbots in the field of studying dialects of foreign languages and serve as a basis for further research in the area of evaluating the effectiveness of educational technologies based on artificial intelligence.

Keywords: large language model, chatbot, quality assessment, foreign language learning, artificial intelligence technology in education

The dynamic system of the grinding machine is simulated, taking into account tool wear. The purpose of the simulation is to improve the algorithmic support of an active control microprocessor device. The vibration characteristics of the SIW-5 machine ring support have been studied at idle and during processing to determine the vibration level at the moment when the grinding wheel touches the workpiece. An algorithm for maintaining the cutting speed with a decrease in the diameter of the circle due to wear has been developed and modeled. characteristics of the ring support of the SIW-5 machine at idle and during processing for the development of algorithms for controlling the grinding process.

Keywords: grinding, bearing rings, active control, mathematical model of grinding, algorithmic support

Fuel efficiency of dump trucks is affected by real world variables such as vehicle parameters, road conditions, weather parameters, and driver behavior. Predicting fuel consumption per trip using dynamic road condition data can effectively reduce the cost and time associated with on-road testing. This paper proposes new models for predicting fuel consumption of dump trucks in surface mining operations. The models combine locally collected data from dump truck sensors and analyze it to enhance their capabilities. The architectural design consists of two distinct parts, initially based on dual Long-term Short-Term Memories (LSTMs) and dual dense layers of Deep Neural Networks (DNNs). The new hybrid architecture improves the performance of the proposed model compared to other models, especially in terms of accuracy measurement. The MAE, RMSE, MSE and R2 scores indicate high prediction accuracy.

Keywords: LSTM algorithm, DNN, density, prediction, fuel consumption, quarries

The article describes a way to optimize the trajectory optimization process by replacing the edges of the trajectory with spatial Bezier curves with a Pythagorean hodograph.

Keywords: Algorithms for generating trajectories, methods for constructing the formation of UAV groups, mathematical models of UAVs, multi-agent systems, Bezier curves, Pythagorean hodograph

This paper examines the impact of regulations on cultural heritage protection zones on the cost of land plots intended for hotel accommodation. The application of the theory of fuzzy sets to assess the influence of cultural heritage objects on the value of commercial land plots is substantiated. The result of the study is a methodology for estimating the share of the value of a commercial land plot attributable to the presence of a cultural heritage protection zone, based on the methodology for determining easement fees and the theory of fuzzy sets.

Keywords: hotel, historical and cultural monument, phasification, market value, cadastral value, type of permitted use, term-set, restrictions of use, adaptation, sustainable development

The paper considers the opportunities and obstacles to the integration of renewable energy sources (RES) in megacities on the example of Moscow. The paper analyzes the applied RES-based generation technologies, taking into account their applicability in large cities. Special attention was paid to the conversion of unused historical dams into small hydroelectric power plants (SHPP) as an integration of RES in megacities. Based on the results of the technical and economic analysis, it was found that the conversion of an unused dam on the Yauza River into a SHPP is justified.

Keywords: small hydropower, unused dam, megacity, renewable energy integration

One of the actual problems in the field of analysing loads and impacts on bearing structures is their identification. It means the point of application, the type of action and its intensity in cases where there is an impact result, but the parameters that caused this result are not determined. For example, it is an accident action, as a result of which the structure is deformed and collapsed. The solution of such problems arises when analysing accidents on load-bearing structures in construction, as well as when monitoring the deformed state of structures in time. The paper proposes to use the principles of neural network modelling to solve the problem of identifying the impact in the form of a concentrated force on the example of beam systems. The values of linear and angular nodal displacements at some action are considered as input data to neurons. As an example, the linearly deformable beam of constant stiffness is considered, the material of which is a continuous isotropic medium.

Keywords: neural network, deflections, load-bearing structure, displacement, deformation, identification