Digital fundus image quality assessment

Diabetic retinopathy (DR) is a disease caused by complications of diabetes. It starts asymptomatically and can end in blindness. To detect it, doctors use special fundus cameras that allow them to register images of the retina in the visible range of the spectrum. On these images one can see features, which determine the presence of DR and its grade. Researchers around the world are developing systems for the automated analysis of fundus images. At present, the level of accuracy of classification of diseases caused by DR by systems based on machine learning is comparable to the level of qualified medical doctors.The article shows variants for representation of the retina in digital images by different cameras. We define the task to develop a universal approach for the image quality assessment of a retinal image obtained by an arbitrary fundus camera. It is solved in the first block of any automated retinal image analysis system. The quality assessment procedure is carried out in several stages. At the first stage, it is necessary to perform binarization of the original image and build a retinal mask. Such a mask is individual for each image, even among the images recorded by one camera. For this, a new universal retinal image binarization algorithm is proposed. By analyzing result of the binarization, it is possible to identify and remove imagesoutliers, which show not the retina, but other objects. Further, the problem of no-reference image quality assessment is solved and images are classified into two classes: satisfactory and unsatisfactory for analysis. Contrast, sharpness and possibility of segmentation of the vascular system on the retinal image are evaluated step by step. It is shown that the problem of no-reference image quality assessment of an arbitrary fundus image can be solved.Experiments were performed on a variety of images from the available retinal image databases.

Feasibility of creation and use of specialized search systems for scientific and technical information

The efficiency of using global Internet search systems versus specialized systems, including the State System of Scientific and Technical Information of the Republic of Belarus, for searching the scientific and technical information is compared in this article. Potential advantages and disadvantages of STI search systems are considered. The experience of individual states in creating and maintaining the functioning of state resources of scientific and technical information is analyzed.

Evaluation of metal objects surface parameters informativity using 2D­ and 3D­data For classification of fractures

This article describes evaluation the information content of metal objects surfaces for classification of fractures using 2D and 3D data. As parameters, the textural characteristics of Haralick, local binary patterns of pixels for 2D images, macrogeometric descriptors of metal objects digitized by a 3D scanner are considered. The analysis carried out on basis of information content estimation to select the features that are most suitable for solving the problem of metals fractures classification. The results will be used for development of methods for complex forensic examination of complex polygonal surfaces of solid objects for automated system for analyzing digital images.

Formation of unmanned aircraft trajectory when flying around prohibited areas

Considered the problem of flying over restricted areas by an unmanned aerial vehicle (UAV), which have various shapes and restrictions, set on the basis of the international airspace classification system for aviation in accordance with the Chicago Convention and the recommended principles for the formation of forbidden zones, rules for creating a flight route along forbidden zones and actions in case of border violations of restricted areas. The problem of analytical synthesis of the control acceleration of an unmanned aerial vehicle (UAV) is solved during its flight along a route passing along the boundaries of the forbidden zone of a given shape, along a given trajectory, which consists of subsequent segments located at the same height relative to the earth’s surface, in a given coordinate system. The optimal control synthesis problem is solved as an analytical definition of the optimal control of a linear non-stationary system based on the quadratic quality functional. A mathematical model of UAV motion in the horizontal plane is proposed, in the form of a system of ordinary differential equations in the Cauchy form. A law for measuring the control acceleration of the UAV’s center of mass is obtained on the basis of specifying the minimized quality functional and the corresponding constraints, which is a feature of the considered method of solving the problem. The proposed quality functional takes into account the parameters of coordinates and speed of the UAV, which correspond to the given points in the airspace, which characterize the necessary trajectory for flying around the restricted area. The derived mathematical dependences make it possible to implement them on board a UAV and minimize energy costs when guiding a UAV moving through specified points in space. Computer modeling of the derived analytical results, mathematical dependencies representing the optimal trajectory of the UAV flight along the boundaries of the forbidden zone, as well as the corresponding processes of changing the control acceleration and speed of the UAV movement was carried out, which made it possible to draw conclusions about the efficiency of the proposed method and the feasibility of its further use as a basis. for the initial stage of the synthesis of the UAV control system.

Method for determining of the distance to the object in the hyperbolic navigation system via doppler frequency offsets

In this paper, a method for estimating the distance to the object guided along a hyperbola to a target using a bistatic hyperbolic navigation system on a plane is given. At the same time, to solve the guidance problem, the number of required navigation positions is reduced by one in comparison with the classical method of hyperbolic navigation. However, in the guidance algorithms, it is still required to estimate the distance of the targeted object from the center of the base, the methods of obtaining which are considered in the work.

Neuroevolutionary reinforcing learning of neural networks

The article presents the results of combining 4 different types of neural network learning: evolutionary, reinforcing, deep and extrapolating. The last two are used as the primary method for reducing the dimension of the input signal of the system and simplifying the process of its training in terms of computational complexity.In the presented work, the neural network structure of the control device of the modeled system is formed in the course of the evolutionary process, taking into account the currently known structural and developmental features of self-learning systems that take place in living nature. This method of constructing it makes it possible to bypass the specific limitations of models created on the basis of recombination of already known topologies of neural networks.

Approbation of the stochastic group virus protection model

The article discusses the implementation in Java of the stochastic collaborative virus defense model developed within the framework of the Distributed Object-Based Stochastic Hybrid Systems (DOBSHS) model and its analysis. The goal of the work is to test the model in conditions close to the real world on the way to introducing its use in the practical environment. We propose a method of translating a system specification in the SHYMaude language, intended for the specification and analysis of DOBSHS models in the rewriting logic framework, into the corresponding Java implementation. The resulting Java system is deployed on virtual machines, the virus and the group virus alert system are modeled stochastically. To analyze the system we use several metrics, such as the saturation time of the virus propagation, the proportion of infected nodes upon reaching saturation and the maximal virus propagation speed. We use Monte Carlo method with the computation of confidence intervals to obtain estimates of the selected metrics. We perform analysis on the basis of the sigmoid virus propagation graph over time in the presence of the defense system. We implemented two versions of the system using two protocols for transmitting messages between nodes, TCP/IP and UDP. We measured the influence of the protocol type and the associated costs on the defense system effectiveness. To assess the potential of cost reduction associated with the use of different message transmission protocols, we performed analysis of the original DOBSHS model modified to model message transmission delays. We measured the influence of other model parameters important for the next steps towards the practical use of the model. To address the system scalability, we propose a hierarchical approach to the system design to make possible its use with a large number of nodes.

Image quality assessment

Quality assessment is an integral stage in the processing and analysis of digital images in various automated systems. With the increase in the number and variety of devices that allow receiving data in various digital formats, as well as the expansion of human activities in which information technology (IT) is used, the need to assess the quality of the data obtained is growing. As well as the bar grows for the requirements for their quality.The article describes the factors that deteriorate the quality of digital images, areas of application of image quality assessment functions, a method for normalizing proximity measures, classes of digital images and their possible distortions, image databases available on the Internet for conducting experiments on assessing image quality with visual assessments of experts.

Authenticated encryption mode with blocks skipping

Block symmetric ciphers are one of the most important components of modern information security systems. At the same time, in addition to the structure of the applied block symmetric cipher, the cryptographic strength and performance of the information protection system is largely determined by the applied encryption mode. In addition to high performance and high-quality destruction of block statistics, modern encryption modes should also protect encrypted information from occurred or intentionally introduced errors. In this paper, we have developed an encryption mode with blocks skipping and using a pseudo-random key sequence generator, which allows checking the integrity of encrypted information with accurate detection of the place where an error was introduced. In this case, the error detection accuracy is determined by the adjustable parameter of the macroblock size and can be set depending on the level of importance of the protected information. The developed encryption mode is characterized by the following key advantages: reducing the number of required encryption operations by half, while providing a high level of cryptographic quality; more effective destruction of macroblock statistics due to the use of an additional generator of pseudo-random key sequences, the impossibility of propagation of the occurred (intentionally introduced) error outside the macroblock, as well as higher values of the number of protection levels due to the possibility of classifying the initial states of the applied generators of pseudo-random key sequences. As proposed in this paper, the mode of authenticated encryption with blocks skipping can be recommended for use on mobile platforms that are demanding both in terms of the quality and reliability of the protected information and are limited in terms of computing and power resources.

Automated CATS system for distance learning

This paper discusses a new automated training system called CATS. The proposed system covers all the main components of the educational process, including the simple and convenient formation of educational material, tasks for laboratory works, tests to check knowledge, allows you to monitor the progress of students, the process of studying educational content, check completed work for plagiarism, send incorrectly completed tasks to correction, keep an electronic journal and much more. The automated CATS system has been introduced into the educational process at the Belarusian National Technical University and is actively used, especially in the context of the COVID-19 pandemic. In the spring of 2020 alone, more than a thousand users have registered in the CATS system. The intellectual component in the CATS system allows you to implement a unique training program, which is based on the existing knowledge and the level of perception of the educational material by the students. As mathematical methods, it is proposed to use the analysis of expert systems, as well as artificial neural networks. These mathematical methods made it possible to develop adaptability algorithms, their software implementation and testing in the educational process. Users are provided with a web application and its mobile clients for iOS and Android operating systems. Mobile applications are localized in Russian, Belarusian, English and German. By formalizing the intellectual processes that are carried out by both the teacher and the student, it is possible to automate a certain part of their functions, reduce the cost of manual labor, which will make it easier to control the educational process, and make the training itself more effective.