Wavelet introscopy of human organism bionets

In domestic and foreign practice, a great deal of experience has been accumulated in the creation of means for monitoring the functional state of the human body. The existing complexes mainly analyze the electrocardiogram, blood pressure and a number of other physiological parameters. Diagnostics is often based on formal statistical data which are not always correct due to the nonstationarity of bioprocesses and without taking into account their physical nature. An urgent task of monitoring the state of the cardiovascular system is the creation of effective algorithms for computer technologies to process biosignals based on nonlinear dynamic models of body systems since biosystems and bioprocesses have a nonlinear nature and fractal structure. The nervous and muscular systems of the heart, the vascular and bronchial systems of the human body are examples of such structures. The connection of body systems with their organization in the form of self-similar fractal structures with scaling close to the “golden ratio” makes it possible to diagnose them topically. It is possible to obtain detailed information about the state of the human body’s bio-networks for topical diagnostics on the basis of the wavelet analysis of biosignals (the so-called wavelet-introscopy). With the help of wavelet transform, it is possible to reveal the structure of biosystems and bioprocesses, as a picture of the lines of local extrema of wavelet diagrams of biosignals. Mathematical models and software for wavelet introscopy make it possible to extract additional information from biosignals about the state of biosystems. Early detection of latent forms of diseases using wavelet introscopy can shorten the cure time and reduce the consequences of disorders of the functional state of the body (FSO), and reduce the risk of disability. Taking into account the factors of organizing the body’s biosystems in the form of self-similar fractal structures with a scaling close to the “golden ratio” makes it possible to create a technique for topical diagnostics of the most important biosystems of the human body.

Information processing using the Kalman filter in Matlab Simulink

In this paper, we investigate the problem of improving data quality using the Kalman filter in Matlab Simulink. Recently, this filter has become one of the most common algorithms for filtering and processing data in the implementation of control systems (including automated control systems) and the creation of software systems for digital filtering from noise and interference, for example, speech signals. It is also widely used in many fields of science and technology. Due to its simplicity and efficiency, it can be found in GPS receivers, in devices for processing sensor readings for various purposes, etc. It is known that one of the important tasks that should be solved in systems for processing sensor readings is the ability to detect and filter noise. Sensor noise leads to unstable measurement data. This, of course, ultimately leads to a decrease in the accuracy and performance of the control device. One of the methods that can be used to solve the problem of optimal filtering is the development of cybernetic algorithms based on the Kalman and Wiener filters. The filtering process can be carried out in two forms, namely: hardware and software algorithms. Hardware filtering can be built electronically. However, it is less efficient as it requires additional circuitry in the system. To overcome this obstacle, you can use filtering in the form of programming algorithms in a single method. In addition to the fact that it does not require electronic hardware circuitry, the filtering performed is even more accurate because it uses a computational process. The paper analyzes the results of applying the Kalman filter to eliminate errors when measuring the coordinates of the tracked target, to obtain a "smoothed" trajectory and shows the results of the filter development process when processing an electrocardiogram. The development of the Kalman filter algorithm is based on the procedure of recursive assessment of the measured state of the research object.

A method of searching and marking artifacts in images applying detection and segmentation algorithms

The paper explores the possibility of using neural networks to single out target artifacts on different types of documents. Numerous types of neural networks are often used for document processing, from text analysis to the allocation of certain areas where the desired information may be contained. However, to date, there are no perfect document processing systems that can work autonomously, compensating for human errors that may appear in the process of work due to stress, fatigue and many other reasons. In this work, the emphasis is on the search and selection of target artifacts in drawings, in conditions of a small amount of initial data. The proposed method of searching and highlighting artifacts in the image consists of two main parts, detection and semantic segmentation of the detected area. The method is based on training with a teacher on marked-up data for two convolutional neural networks. The first convolutional network is used to detect an area with an artifact, in this example YoloV4 was taken as the basis. For semantic segmentation, the U-Net architecture is used, where the basis is the pre-trained Efficientnetb0. By combining these neural networks, good results were achieved, even for the selection of certain handwritten texts, without using the specifics of building neural network models for text recognition. This method can be used to search for and highlight artifacts in large datasets, while the artifacts themselves may be different in shape, color and type, and they may be located in different places of the image, have or not have intersection with other objects.

A risk-based approach to solving the problem of airline schedule operational management

The paper discusses the problem of optimal regulation of aircraft assignments for airline flights. Due to the fact that the activities of the airline are subject to changes caused by both external and internal environment, the planned schedule needs continuous management and control. In the event when the actual flight schedule deviates from the planned one, it is necessary to promptly make a decision on adjusting (restoring) the schedule and reassigning aircraft. Operational schedule management involves making adjustments to the current schedule from a depth of several hours to several days. The solution to the problem is to determine the unambiguous correspondence of flights and specific aircraft subject to maximizing the likelihood of meeting production targets and observing a number of restrictions. The task of managing airline schedules belongs to the class of scheduling optimization problems for parallel-sequential systems studied within the scheduling theory. It is NP-hard and requires the development of computationally efficient solution algorithms. However, the issue of choosing criteria for the optimization problem deserves special attention, since the correct choice plays an essential role in terms of assessing the effectiveness of decision-making. In the theory of decision-making, no general method for choosing the optimality criteria has been found. The definition of the target criterion depends on the expectations of the production. Within the framework of this paper, an original criterion is proposed for constructing an optimal solution to the discrete problem of managing aircraft assignments, the main idea of which is to find a balance between the duration of the schedule and the number of flights with a negative deviation from the planned schedule by assessing the level of punctuality violation risk. The paper gives a detailed concept of punctuality, describes an approach to assessing the level of risk, and also proposes an original formal formulation of the task of operational management of aircraft assignments based on the criterion of minimizing the risk of violation of flight punctuality.

A computational scheme for calculating the temperature field when oil production problems

The paper presents an approach to coupled modeling of hydrodynamic and thermal processes occurring in the oil reservoir during field development using thermal methods of enhanced oil recovery. To simulate the processes of non-isothermal multiphase flow, an approach based on implicit calculation of pressure using the finite element method and an explicit calculation of phase saturations is used. A computational scheme for calculating the temperature field is considered. This scheme makes it possible to take into account both heat transfer between phases and heat transfer of a fluid mixture and matrix-rock. In order to take into account the effect of thermal conductivity, a coefficient characterizing the rate of heat transfer between the fluid mixture and the rock is used. The proposed scheme also takes into account the effect of the temperature field on the phases flow in the field reservoir and provides for the possibility of heat sources and sinks occured due to chemical reactions or thermodynamic processes in gaseous phases. Numerical experiments were carried out on a model of a real oil field obtained as a result of history matching of well data. The model contains a large number of wells and is characterized by a high heterogeneity of the porous medium. The applicability of the considered computational scheme is demonstrated on the example of modeling hot water injection into wells crossing a formation with super-viscous oil. The efficiency of thermal methods for the development of super-viscous oil fields is shown. When hot water was injected into the reservoir, the increase in oil production was about 25 % due to a significant decrease in oil viscosity. The time spent for calculating the temperature field while simulating a multiphase flow did not exceed 6 % of the total computational time.

On the application of estimation and correction algorithms in the system for measuring vibration parameters of aircraft structural elements

Nowadays, high-precision measurement of aircraft vibration parameters during its main operations modes, including in-flight operation mode, is still considered an important scientific and technical field of study and research. These kinds of measurements are usually conducted in order to analyze the airplane vibration properties and characteristics, which serves in diagnosing the state of its structure, predicting the appearance and development of defects and deformations, as well as to prevent or avoid the influence of dangerous phenomena such as flutter, buffeting, etc. In this article, the authors present the primary results of their work to build a system designed to measure such airplane vibration parameters. In comparison with the existing analogous systems, the new proposed system makes use of traditional vibrometric measurement methods in combination with approaches typical for solving orientation and navigation problems. So, the article discusses the principles of constructing a measurement system of vibration parameters of aircraft structural elements using the example of a system for measuring aircraft wing vibrations using MEMS IMU units and data fusion technology. A brief review of the main existing solutions in this research field is carried out, and the relevance and expediency of the proposed version of the system is substantiated. The basic components and structure of the proposed system are presented, including MEMS IMU units, a displacement sensor, and an onboard navigation system. The basic principles of the system operation are described based on the use of data from the displacement sensor, inertial measurements and optimal Kalman estimation. The main algorithms for the system operation are presented, including algorithms for inertial measurements, estimation and correction, as well as the actual algorithm for calculating vibration parameters. In addition, the mathematical errors models of the main measurements units of the system are presented. The article also presents simulation results, which are encouraging, and they demonstrate the performance of the system and its expected relatively high accuracy characteristics, which in turns confirms the expected efficiency of its application and the prospects of the chosen direction of research and development.

Analysis of current research in the field of detecting driver fatigue in the vehicle cab

The article analyzes the methods of detecting driver fatigue which are described in modern literature. There are a great variety of methods for assessing the functional state of a person. A functional state is an integral set of characteristics of those functions and qualities of a person that directly or indirectly determine the performance of any activity. The physical and mental state of a person, the success of his work, training, creativity depends on the functional state of the organism. The assessment of dynamic driver behavior has become an increasingly popular area of research in recent years. Dynamic assessment of driver behavior includes continuous monitoring that allows you to determine functional states, in contrast to modern driver monitoring systems, which assess conditions such as drowsiness and impaired attention for a short (1-10 s) time interval. Such systems allow us to talk about physiological, but not neurophysiological monitoring, which allows monitoring the functional state of fatigue. Therefore, it makes sense to monitor the driver’s state of fatigue of, as well as to warn them in a timely manner to avoid collisions with other vehicles. In the article, a study was carried out and an analysis of the ways to obtain the appropriate characteristics from a person, with the help of which it is possible to determine his functional state of fatigue. As a result of the analysis of the sources, the most common methods for determining the functional state of the driver were selected. Further, the sources found were classified according to the most common methods for obtaining significant characteristics of the functional state of the driver. As a result, a comparative analysis was made, demonstrating the capabilities of modern systems of this class.

Comparison of numbers and analysis of overflow in modular arithmetic

The method of modular arithmetic consists in operating not with a number, but with its remainders after division by some integers. In the modular number system or the number system in the residual classes, a multi-bit integer in the positional number system is represented as a sequence of several positional numbers. These numbers are the remainders (residues) of dividing the original number into some modules that are mutually prime integers. The advantage of the modular representation is that it is very simple to perform addition, subtraction and multiplication operations. In parallel execution of operations, the use of modular arithmetic can significantly reduce the computation time. However, there are drawbacks to modular representation that limit its use. These include a slow conversion of numbers from modular to positional representation; the complexity of comparing numbers in modular representation; the difficulty in performing the division operation; and the difficulty of determining the presence of an overflow. The use of modular arithmetic is justified if there are fast algorithms for calculating a number from a set of remainders. This article describes a fast algorithm for converting numbers from modular representation to positional representation based on a geometric approach. The review is carried out for the case of a comparison system with two modules. It is also shown that as a result of increasing numbers in positional calculus, they successively change in a spiral on the surface of a two-dimensional torus. Based on this approach, a fast algorithm for comparing numbers and an algorithm for detecting an overflow during addition and multiplication of numbers in modular representation were developed. Consideration for the multidimensional case is possible when analyzing a multidimensional torus and studying the behavior of the turns on its surface.

Method for encryption of cartographic images on the basis of internal reorganization of the digital filter structure

The paper presents a method for encrypting geo-images based on the reorganization of the internal structure of the filter. Methods for digital image filtering in the MATLAB environment are taken as a basis. The essence of encryption is to control the aliasing of noise and the kernel of smearing. Knowing these values will allow the addressee to recover the transmitted cards with minimal interference, which will be unattainable for the data interceptor. Under conditions of unfavorable factors, conditions sometimes arise that lead to the loss of information content of images and, as a consequence, damage to information. Therefore, the development of methods to minimize their influence is an urgent task of the study. Thus, one of the approaches to the construction of spatial filters with a controlled structure is proposed for the selection of contrasting images in noises of different intensities. The procedure for converting any spatial filter from an initial display to a form that allows you to control its internal state is described. The obtained results of the original and transformed images make it possible to draw conclusions about the possibility of practical application of the proposed invariant spatial filter in the blocks for analyzing the original image. The method can be used to transfer photo, video messages and text information between consumers using data transmission systems for any purpose. Due to the factorial dependence, it is very problematic for information interceptors to find the required resulting position of all image encryption parameters (sizes, type of the distortion function, regularization parameters α and σ) for information interceptors, since the computational costs are not commensurate with the capabilities of modern computers. This can be used to transfer photo, video messages and text information between consumers using data transmission systems for any purpose, especially when transferring cartographic information.

Recognition of Russian and Indian Sign Languages Based on Machine Learning

In the paper, we consider recognition of sign languages (SL) with a particular focus on Russian and Indian SLs. The proposed recognition system includes five components: configuration, orientation, localization, movement and non-manual markers. The analysis uses methods of recognition of individual gestures and continuous sign speech for Indian and Russian sign languages (RSL). To recognize individual gestures, the RSL Dataset was developed, which includes more than 35,000 files for over 1000 signs. Each sign was performed with 5 repetitions and at least by 5 deaf native speakers of the Russian Sign Language from Siberia. To isolate epenthesis for continuous RSL, 312 sentences with 5 repetitions were selected and recorded on video. Five types of movements were distinguished, namely, "No gesture", "There is a gesture", "Initial movement", "Transitional movement", "Final movement". The markup of sentences for highlighting epenthesis was carried out on the Supervisely.ly platform. A recurrent network architecture (LSTM) was built, implemented using the TensorFlow Keras machine learning library. The accuracy of correct recognition of epenthesis was 95 %. The work on a similar dataset for the recognition of both individual gestures and continuous Indian sign language (ISL) is continuing. To recognize hand gestures, the mediapipe holistic library module was used. It contains a group of trained neural network algorithms that allow obtaining the coordinates of the key points of the body, palms and face of a person in the image. The accuracy of 85 % was achieved for the verification data. In the future, it is necessary to significantly increase the amount of labeled data. To recognize non-manual components, a number of rules have been developed for certain movements in the face. These rules include positions for the eyes, eyelids, mouth, tongue, and head tilt.