This article presents a comparative analysis of two prominent machine learning techniques for predicting electricity consumption in workplace lighting systems: polynomial regression analysis and artificial neural networks. The primary objective is to assess their suitability and applicability for developing an accurate predictive model. After a brief overview of the current state of energy-saving techniques, the article examines several established models for predicting energy consumption in buildings and systems. These models include artificial neural networks, regression analysis and support vector machines. It then focuses on a practical comparison between polynomial regression analysis and an artificial neural network-based model. The article then looks at the data preparation process, outlining how the data is used within each model to establish appropriate prediction functions. Finally, it describes the methods used to evaluate the accuracy of the developed prediction functions. These functions allow the prediction of lighting consumption based on external lighting intensity. The article evaluates the accuracy of the developed prediction functions using the root mean square error, correlation coefficient and coefficient of determination values. The article compares these values obtained for both models, allowing a conclusive assessment of which model provides superior accuracy in predicting lighting consumption based on external lighting intensity.

In order to increase the corrosion resistance of magnesium alloy AZ91 in corrosion environments containing chlorides, the alloy surface has been modified by plasma electrolytic oxidation (PEO). The chemical composition of electrolyte in the PEO process consisted of 12 g/L Na₃PO₄·12 H₂O and 1 g/L KOH, and a direct current was applied to the sample. The corrosion resistance of PEO coating and as-cast AZ91 (sample without PEO coating) was assessed using two different electrochemical methods: electrochemical impedance spectroscopy (EIS) and potentiodynamic polarisation (PDP) in 0.1 M NaCl at laboratory temperature. In addition to the electrochemical methods, the morphology of the oxidic coating was observed in the cross-sectional and top surface view by using the SEM technique. For better determination of the microstructure and PEO coating, chemical composition EDX analysis was used. The results of the experiments show that the formation of the PEO coating on AZ91 alloy has a more positive effect on the corrosion resistance in 0.1 M NaCl based on electrochemical methods than in the case of the formed coating on AZ31 alloy from the previous study. Based on electrochemical measurements in the selected environment, the formation of PEO coating on AZ91 was accompanied by a significant increase in polarisation resistance after short-term exposure compared to the as-cast surface. The EIS results showed a 73 times higher R_p value for PEO coated AZ91 when compared to the as-cast AZ91. Correspondingly, a 27 times lower i_corr value was observed for PEO coated AZ91 than in the case of substrate AZ91 in 0.1 M NaCl. At the same time, the typically porous and inhomogeneous structure of the formed PEO coating on the magnesium alloy AZ91 was demonstrated.

Wrought AZ31 magnesium alloy was used as the experimental material for fluoride conversion coating preparation in Na[BF₄] molten salt. Two coating temperatures, 430 °C and 450 °C, and three coating times, 0.5, 2, and 8 h, were used for the coating preparation. A scanning electron microscope and energy-dispersive X-ray spectroscopy were used for an investigation of the surface morphology and the cross-sections of the prepared coatings including chemical composition determination. The corrosion resistance of the prepared specimens was investigated in terms of the potentiodynamic tests, electrochemical impedance spectroscopy and immersion tests in the environment of simulated body fluids at 37 ± 2 °C. The increase in the coating temperature and coating time resulted in higher coatings thicknesses and better corrosion resistance. Higher coating temperature was accompanied by smaller defects uniformly distributed on the coating surface. The defects were most probably created due to the reaction of the Al_xMn_y intermetallic phase with Na[BF₄] molten salt and/or with the product of its decomposition, BF₃ compound, resulting in the creation of soluble Na₃[AlF₆] and AlF₃ compounds, which were removed from the coating during the removal of the secondary Na[MgF₃] layer. The negative influence of the Al_xMn_y intermetallic phase was correlated to the particle size and thus the size of created defects.

A progressive type of tungsten-doped DLC coating was applied to a quenched and tempered 100Cr6 steel with the aim to improve the wear and corrosion properties in simulated seawater conditions and to compare the performance to conventional DLC coating. Tungsten doping caused a shift of the corrosion potential (E_corr) to a lower negative value of −172 mV, while the conventional DLC exhibited an E_corr of −477 mV. In dry conditions, the W-DLC coefficient of friction is slightly higher than that of the conventional DLC (0.187 for the W-DLC vs. 0.137 for the DLC), but in cases of a saltwater environment, this difference becomes almost negligible (0.105 for the W-DLC vs. 0.076 for the DLC). The conventional DLC coating also started to show marks of deterioration when exposed to a combination of wear in a corrosive environment, while the W-DLC layer still maintained its integrity.

A surface treatment process, composed of plasma electrolytic oxidation (PEO) and sealing by temporary oil preservation system containing corrosion inhibitors, was performed on AZ31 magnesium alloy in order to improve its corrosion resistance i...