The author presents a development of computational model of design of ball screws thread. This model is the basis for computer program, which calculates the geometrical features of the thread for precisely given backlashes and contact angles. The program makes it possible to create a data base of a new generation ball screw of quality competitive to foreign ball screws. The modeling allows one to better select the ball screw and to predict its quality in the early stage of design.

In this paper, we have researched implementing convolutional neural network (CNN) models for devices with limited resources, such as smartphones and embedded computers. To optimize the number of parameters of these models, we studied various popular methods that would allow them to operate more efficiently. Specifically, our research focused on the ResNet-101 and VGG-19 architectures, which we modified using techniques specific to model optimization. We aimed to determine which approach would work best for particular requirements for a maximum accepted accuracy drop. Our contribution lies in the comprehensive ablation study, which presents the impact of different approaches on the final results, specifically in terms of reducing model parameters, FLOPS, and the potential decline in accuracy. We explored the feasibility of implementing architecture compression methods that can influence the model’s structure. Additionally, we delved into post-training methods, such as pruning and quantization, at various model sparsity levels. This study builds upon our prior research [1] to provide a more comprehensive understanding of the subject matter at hand.

The paper presents the problem of position control of DC motor with rated voltage 24 V loaded by flywheel. The fractional order PD controller implemented in National Instruments NI ELVIS II programmed in LabView is used for controlling. The simple method for determining stability regions in the controller parameters space is given. Knowledge of these regions permits tuning of the controller and ensures required the phase margin of the system.

The article presents results of the influence of the GMDH (Group Method of Data Handling) neural network input data preparation method on the results of predicting corrections for the Polish timescale UTC(PL). Prediction of corrections was carried out using two methods, time series analysis and regression. As appropriate to these methods, the input data was prepared based on two time series, ts1 and ts2. The implemented research concerned the designation of the prediction errors on certain days of the forecast and the influence of the quantity of data on the prediction error. The obtained results indicate that in the case of the GMDH neural network the best quality of forecasting for UTC(PL) can be obtained using the time-series analysis method. The prediction errors obtained did not exceed the value of ± 8 ns, which confirms the possibility of maintaining the Polish timescale at a high level of compliance with the UTC.

The construction of transmission infrastructure and its functioning imposes the obligation on transmission companies to have a legal title to land. Both in Poland and in Canada, the title particularly results from the established easements subject to registration in public information systems. Due to different historical, social, and economic conditions, the specificity of legal regulations and technical solutions related to the registration of rights to land property is different in both countries. This results from the functioning and the substantive scope of particular systems of information on land property. Such systems are regulated by independent, internal rules of each of the countries. In Poland, easement is subject to registration in the land and mortgage register. In Canada, a federation country, it depends on legal regulations of particular provinces. The research objective of the article is the analysis of the way of registration of easements established for transmission companies in Poland and in Canada in the Ontario and Quebec provinces. The analysis covers the scope of registration of the said right in systems of information on land property. The evaluation of the applied solutions particularly involves pointing out those which to the greatest extent guarantee the safety of land property turnover. The best result is obtained in Canada in the Ontario province.

In this paper an artificial neural network, which realizes a nonlinear adaptive control algorithm, has been applied in a control system of variable speed generating system. The speed is adjusted automatically as a function of load power demand. The controller employs a single layer neural network to estimate the unknown plant nonlinearities online. Optimization of the controller is difficult because the plant is nonlinear and no stationary. Furthermore, it deals with the situation where the plant becomes uncontrollable without any restrictive assumptions. In contrast to previous work [1] on the same subject, the number of neural networks has been reduced to only one network. The number of the neurons in a network structure as well as choosing certain design parameters was specified a priori. The computer test results have been presented to show performance of proposed neural controller.

The aim of the considerations presented in the article was a stand-alone groundbased photovoltaic power plant. The article is devoted to the qualitative analysis of some lightning protection configurations. These types of constructions often require an individual look at the design and execution of lightning protection installations, which causes problems with the selection of optimal solutions. These problems relate primarily to the way the lightning rods are arranged to create protection zones, but also to the way they are attached: to the supporting structure for PV modules or as free-standing. Another problem raised in the article is the way how lightning current is discharged from rods to the ground and how it is dispersed there. Due to the vast area of such facilities and the requirements for electrical safety, it is necessary to consider and design a ground system with optimal electrical parameters, but also technical and economic ones. All these elements have their impact on the value of voltages induced in the electrical installation, which is also presented in the content of the article as the magnetic field distribution and calculation of induced voltages in an exemplary configuration. Finally, this article will compare described technical solutions encountered in selecting the best protection method for this type of photovoltaic installation.

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.

The economic downturn in Europe and in the world, has affected the traditional branches of industry in a particular way. Development plans of domestic coke plants in terms of main production assets for the next years have been presented. Taking into account the current market situation, the coke plants strategy should aim at risk minimization through application of already known technologies. On the other hand, investments in scope of new and innovative technologies which are connected with a high level of variability, should be seen as an opportunity. Thus, evaluation of investment projects should be done in a different way than so far. The traditional discount analysis, because of its static nature, does not take into account variability and options included in projects with many decision moments - it can prove to be not sufficient. A tool which helps the decision makers in such situations, is the real options analysis. The article presents the findings of the research-development project on coal blend pre-drying implementation, realized by Zdzieszowice Coke Plant and ICHPW in Zabrze. The results achieved so far, as well as the concerns resulting from the project, have been discussed in this article. Further project development plans, aiming at the construction of a semi industrial research installation for analysing the impact of pre-drying on the coke making process have been presented. The article describes premises for the application of real options analysis as a tool to evaluate projects, the results of which are uncertain. The origin and structure of real options as well as the conditions of their application compared to traditional, discount based project evaluation methods, have been presented. The origin and characteristic parameters of real options have been discussed. In the next part, by applying the NPV and real options method, the research-development undertaking of coal blend pre-drying implementation on two coke batteries, has been evaluated. In order to assess the real option's value of the project, which is a classic European call option, the Black-Scholes formula has been used. The achieved results have been compared as well as the flexibility rate of the analyzed research-development project has been defined.