Abstract: One of the most important factors for the timely provision of medical care is to quickly and accurately obtain information about the state of health of the patient. Electrocardiography (ECG) is a non-invasive process of interpreting the electrical activity of the heart, allowing to evaluate the speed and regularity of heart contractions. This data is used to determine the damage and pathologies of the heart. Automatic ECG analysis is a challenging theoretical and practical task. The goal of the work is to use neural networks to detect the characteristic ECG signals that determine heart rhythm abnormalities and identify the corresponding heart disease. In the design, the Neural Network Toolbox of MATLAB 8.6 (R2015b) was used to simulate an artificial neural network apparatus. The effectiveness of the developed neural network model for ECG analysis was investigated using the MIT-BIH database. The accuracy of detection and extraction of the components of the ECG signal shows that the developed neural network model can be used to detect heart disease in patients. The sensitivity of the model was 71%, the specificity of 89%.

Abstract: Due to the low power consumption, CMOS structures are preferred for creating large and ultra-large integrated circuits. However, the reliability of the circuits is largely limited by the latch phenomenon that occurs in CMOS structures. The electrical characteristic of the latch up phenomenon in a CMOS integrated circuit is characterized by the presence of a number of anomalous phenomena. These effects distort and make ambiguous the results of measuring the electrical sensitivity of the circuits to the latch. The development of microelectronics is constantly striving to reduce the size of the elements of integrated circuits, in particular transistors. Reducing the size of integrated circuits leads to the amplification of short-channel effects in MOS transistors. When reducing the size of integral elements, various options for scaling devices with a metal-oxide-semiconductor structure are considered. The mechanisms that cause the appearance of the snap-in do not depend on the conductivity type of the semiconductor region of the pocket.

Abstract: The greatest success of ion implantation has been achieved in the field of planar technology of semiconductor devices and integrated circuits. The development of devices with elements of nanoparticles, including the active region of which are metal nanoparticles in a dielectric matrix, has been greatly developed. The aim of the work is to simulate the process of ion implantation of a structure consisting of gold nanoparticles in a silicon dioxide matrix and calculations of the distribution of doping ions, cascades of displaced matrix ions and nanoparticles, as well as the distribution of ions reflected from the nanoparticles. The implantation conditions vary depending on the position of the projection of a point on the surface of the structure on the horizontal radius of the nanoparticle from the center to the periphery. A physical model of the process of ion implantation of gold nanoparticles located in a silicon dioxide matrix has been compiled. The process of ionic doping of the structure with boron and arsenic ions was simulated for different cross sections, and graphs of the distribution of doping ions, recoil atoms, reflected and sputtered ions were obtained depending on the coordinate from the center of the nanoparticle.

Abstract: The processes of formation of radiation-resistant heterostructures with required set of structural and electrophysical parameters, taking into account the influence of ionizing radiation effects, allowing to expand the field of their application and improve the reliability of electronic equipment are described. The influence of irradiation on the parameters of hetero- and semiconductor structures made according to various design-technological variants is studied. It is shown that the charge density in the dielectric increases with increasing dose of ionizing particles, reaches saturation at a dose of 108- 109 rad, and the value of the built-in charge and mechanical stresses in multilayer dielectric systems decrease due to the formation of an intermediate charge at the dielectric interface and the presence of a potential barrier between them. By adjusting the rate of introduction and characteristics of radiation centers during irradiation type, method of growing and the level of doping material, and the integrated flux density of the irradiation, the sample temperature during irradiation may purposefully alter the electrical properties of heterostructures and electrical parameters of devices and integrated circuits. Developed methods, for radiation resistant heterostructures forming, reduces charge formation at silicon-oxide interface. SOI technology on optimized structure, shows good results, even at high radiation doses. The resistance to the total dose of radiation rises by three orders of magnitude.

Abstract: Aluminum and its alloys are the main metallization materials. With an increase in degree of integration the role of interconnections rises: they occupy a growing area of the crystal, the density of the package increases, which leads to a decrease in the thickness and width of the conductive tracks. In nanodimensional structures the value of the current density sufficient for the development of electromigration effects occurs at currents of 50-100 mA. The article explores the factors affecting the mechanism of destruction of the integrated circuits' metallization due to electromigration. The author studies metallization lines at different stages of their destruction by electromigration with the help of raster scanning and transmission electron microscopes. In general, the main problem associated with high-temperature application of aluminum metallization is the large grain size and surface roughness, which makes alignment on such a metal layer difficult. The results of the experiments lead to the conclusion that geometric factors play a dominant role in the mechanism of destruction of metallization of integrated circuits due to electromigration.

Abstract: Aluminium with its alloys is the basic material of integrated circuits metallization. Use of VLSIC toughens the requirements to the parameters of metallization, which determine its reliability, such as surface resistance, step coating quality, number and sizes of tension-caused voids, and electromigration tolerance. Poor quality of metallization is one of the most dangerous defects in semiconductor technology of integrated circuits. Electromigration can cause failure when passing high-density current through metallization. The materials have been tested in order to estimate the intensity of metal resistance variation caused by electromigration. Based on the results of these tests, the authors conclude that geometrical factors play a dominant role in the mechanism of erosion of integrated circuits metallization caused by electromigration. With regard to the tests, the authors formulate recommendations about the transition from the sputtering technique to evaporation deposition. 

Abstract: Silicon-on-sapphire structures serve as a base for the production of radiation-resistant integration circuits, which are very important for space industry, nuclear energetics, and the military sphere. The authors study the silicon-on-sapphire hetero-epitaxial mechanism for the subsequent creation of low-defectiveness transistor structures. Using the Rutherford backscattering, the authors study epitaxial layers of silicon, grown on sapphire substrate. Using the Auger analysis, the authors define the composition and the depth of the transitional layer of silicon-sapphire. The authors ascertain that silicon-to-sapphire bond is performed through tetrahedral sited oxygen. Defectiveness growth can be observed in the regions of spectrum of epitaxial layers, corresponding to the transitional region between the silicon layer and the sapphire substrate, and contributing to ion channeling. Account of an irregular character of the silicon-sapphire transition allows establishing causal link between the charge on the silicon-on-sapphire structure border and leakage current of field emission transistor. The authors develop the method of creation of a semiconductor device with improved parameters both in leakage currents and in structure defects density. 

Abstract: Diabetus melitus is a metabolic disorder caused by an absolute deficiency of insulin secretion and characterized by the inability of the body to maintain an adequate blood glucose level. Optimal doses and types of artificial insulin depend on many factors. In this paper the author proposes a neural network model of blood glucose prediction allowing to predict impending critical condition of patients suffering from diabetes. Implementation of the prediction system combined with an insulin pump creates a range of opportunitities for constructing a system of automatic blood glucose level control. The simulation was performed by using The Neural Network Toolbox of the Matlab 2015b environment due to a wide range of opportunities offered by the system, convenience of developing compex applications, advanced imaging study results. The results of the training process and verification of the proposed prediction model performance show that artificial neural networks of direct distribution can help to sustain a satisfactory blood glucose level at all stages of prediction. The average quadratic prediction error did not exceed 3 in the process of the research.  

Abstract: Diabetes is a chronic disease, in the pathogenesis of which is a lack of insulin in the human body causing a metabolic disorder and pathological changes in various organs and tissues, often leading to a high risk of heart attack and kidney failure. The author makes an attempt to create a system for early diagnosis of diabetes patients using the device of artificial neural networks. The article presents a model of neural network based on multilayer perceptron trained by back-propagation algorithm. For the design of the neural network the author used Neural Network Toolbox èç MATLAB 8.6 (R2015b) which is a powerful and flexible tool for working with neural networks. The results of training and performance tests of the neural network designed show its successful application for the task and the ability to find patterns and complex relationships between the different characteristics of the object. The sensitivity of the developed neural network model is 89.5%, specificity of 87.2%. Once the network is trained it becomes a reliable and inexpensive diagnostic tool.

Abstract: One of the problems hampering the development of the active use of renewable energy is to determine the optimal placement of wind and solar power plants on the earth's surface. The paper presents a model for predicting the level of solar energy in the region allowing choosing the most effective location for solar power location. The forecast of the level of solar energy is given using an artificial neural network of direct distribution educated on the basis of meteorological stations data using the back-propagation algorithm. Designing a neural network was carried out with the Neural Network Toolbox package of MATLAB 8.6 (R2015b). Comparison of results of forecasting solar energy performed by artificial neural network level with the current values shows a good correlation. This confirms the possibility of using artificial neural networks for modeling and forecasting in regions where there are no data on the level of solar energy, but some other data of meteorological stations is present.

Abstract: The author considers the methods of network attacks on a computer system detecting and reveals their advantages and drawbacks. The development of new methods and means of protection of computing systems from network attacks is urgent. The author considers the possibility of using artificial neural networks for traffic analysis. The author offers the neural network model of the incoming traffic filtration. The research is aimed at the creation of an adaptive neural network system serving as a cyber-attacks detection complex helping to take the peculiarities of the network traffic into consideration. To design the artificial neural network the author applies the Neural Network Toolbox pack from MATLAB 8.6 (R2015b). The author develops and offers the method of analysis of incoming traffic on the base of a three-layered neural network. The results of its teaching and testing demonstrate the possibility of its successful application for network cyber-attacks detection. The best results can be acquired in computing systems using the limited software suite allowing forming the traits of normal behavior for attacks detection more effectively. 

Abstract: The research is devoted to one of the physical nanoelectronic effect – resonant tunneling. The authors provide numerical calculations for constructing the MIS-structure based diod and modeling its characteristics. The metal-oxide-silicon semiconductor in the severe depletion mode next to the doped semiconductor has a similar structure. The authors establish the MIS-structure energy band diagram, define energy levels and wave functions of an electron in the quantum well and during tunneling and calcuate the probability of tunneling based on the amounnt of the voltage applied. In the course of calculations the authors use the PTC Mathcad Prime 3.1 visual environment for mathematical modeling and technical computing. The results of the computer modeling allow to define external limit voltage including the amount of voltage that leads to the dielectric breakdown. In addition, the authors define the qualitative dependency between the MIS-structure voltage and the height and width of the energy barrier. The model developed by the authors takes into account the joint influence of several factors which is proved by the coordination of recorded current voltrage characteristic with the experimental characteristics.