In the paper the use of the artificial neural network to the control of the work of heat treating equipment for the long axisymmetric steel

elements with variable diameters is presented. It is assumed that the velocity of the heat source is modified in the process and is in real

time updated according to the current diameter. The measurement of the diameter is performed at a constant distance from the heat source

(∆z = 0). The main task of the model is control the assumed values of temperature at constant parameters of the heat source such as radius

and power. Therefore the parameter of the process controlled by the artificial neural network is the velocity of the heat source. The input

data of the network are the values of temperature and the radius of the heated element. The learning, testing and validation sets were

determined by using the equation of steady heat transfer process with a convective term. To verify the possibilities of the presented

algorithm, based on the solve of the unsteady heat conduction with finite element method, a numerical simulation is performed. The

calculations confirm the effectiveness of use of the presented solution, in order to obtain for example the constant depth of the heat

affected zone for the geometrically variable hardened axisymmetric objects.

In this work synthesis, sintering processes and properties of three groups of perovskite-type ceramics utilized in chosen electronic applications are briefly described. The first group includes high permittivity dielectrics based on relaxor ferroelectrics and new leadfree ceramics, destined for bulk and thick film capacitors. The second group comprises ceramics for low and high temperature thermistors and the third one nonstoichiometric conducting compounds containing doped SrMnO3 and SrCoO3, tested as electrode materials for solid state cells.

Replacing mathematical models with artificial intelligence tools can play an important role in numerical models. This paper analyses the modeling of the hardening process in terms of temperature, phase transformations in the solid state and stresses in the elastic-plastic range. Currently, the use of artificial intelligence tools is increasing, both to make greater generalizations and to reduce possible errors in the numerical simulation process. It is possible to replace the mathematical model of phase transformations in the solid state with an artificial neural network (ANN). Such a substitution requires an ANN network that converts time series (temperature curves) into shares of phase transformations with a small training error. With an insufficient training level of the network, significant differences in stress values will occur due to the existing couplings. Long-Short-Term Memory (LSTM) networks were chosen for the analysis. The paper compares the differences in stress levels with two coupled models using a macroscopic model based on CCT diagram analysis and using the Johnson-Mehl-Avrami-Kolmogorov (JMAK) and Koistinen-Marburger (KM) equations, against the model memorized by the LSTM network. In addition, two levels of network training accuracy were also compared. Considering the results obtained from the model based on LSTM networks, it can be concluded that it is possible to effectively replace the classical model in modeling the phenomena of the heat treatment process.

Millimeter-wave (mm-wave) transmitters are often fabricated using advanced technology and require a sophisticated manufacturing facility. Access to such technologies is often very limited and difficult to gain particularly at the initial stage of research. Therefore, to increase the accessibility of mm-wave transmitters, this study proposes a design that can be assembled in a standard microwave laboratory from commercially available or externally ordered components. The transmitter demonstrated in this paper operates above 100 GHz and is based on a lowtemperature co-fired ceramic board in which the antenna array, microstrip lines, and power-supply lines are fabricated in a single process. Different technologies are used to assemble the module, e.g., wire-bonding, soldering, and wax adhesion. Advantages and disadvantages of the proposed design are given based on experimental evaluation of the prototype. Although the performance of the developed transmitter is not as good as that of the similar modules available in the recent literature, the results confirm the feasibility of a mm-wave transmitter that is assembled without employing advanced technologies and superior machinery.