The green energy transition is associated with the use of a wide range of metals and minerals that are exhaustible. Most of these minerals are limited in access due to small resource fields, their concentration in several locations and a broader scale of industry usage which is not limited exclusively to energy and environmental sectors. This article classifies 17 minerals that are critical in the green energy transition concerning the 10 main technologies. The following classification signs of metal resources were used: (1) the absolute amount of metals used in the current period for energy; (2) projected annual demand in 2050 from energy technologies as a percentage of the current rate; (3) the number of technologies where there is a need for an individual metal; (4) cumulative emissions of CO₂, which are associated with metal production; (5) period of reserves availability; (6) the number of countries that produced more than 1% of global production; (7) countries with the maximum annual metal productivity. The ranking of metals according to these characteristics was carried out using two scenarios, and the index of the availability of each mineral was determined. The lowest availability index values (up to 0.15) were calculated for cobalt, graphite and lithium, which are key battery minerals for energy storage. Low indices (up to 0.20) were also obtained for iron, nickel and chromium. The calculation of the availability index for each mineral was enhanced with linear trend modelling and the fuzzy logic technique. There are two scenarios of demand–supply commodity systems with a pre-developed forecast up to 2050: basic independent parameter probability and balanced fuzzy sum. Both scenarios showed comparable results, but the second one highlighted supply chain importance. Generally, the lowest availability index values (up to 0.15) were calculated for cobalt, graphite and lithium, which are key battery minerals for energy storage. Low indices (up to 0.20) were also obtained for iron, nickel and chromium. The fuzzy logic model helped to reveal two scenarios up to 2050. The two scenarios presented in the current research expose a high level of uncertainty of the projected 2050 forecast.

Contemporary office building standards require the installation of advanced HVAC systems, which, alongside industrial processes, are significantly responsible for energy consumption. While the literature describes numerous multi-parameter, deep artificial neural networks that are highly complex but poorly explainable (black box), commercial control systems must be based on simple-to-implement, easily adaptable intelligent predictive models whose reliability stems from their monitorability and explainability. The study verified several edge-oriented approaches using machine learning techniques for short- and medium-term predictions (1 day) with relatively high granularity (15 minutes). High granularity of time intervals, combined with high prediction reliability, not only provide a practical opportunity to optimize energy consumption, but also to increase the efficiency of renewable energy sources exploitation. Operational, high granularity predictions can also be used to detect anomalies and attacks, as required by modern cybersecurity rules.

The aim of this paper is to present methods to calculate pupil size based on various parameters, such as: luminance, age, corneal flux density or monocular/binocular effect. These models allow to distinguish pupil dilation caused by the influence of light and other factors such as psychological state of participants.The developed methods were presented based on empirical data. Various researchers estimate their equations based on oculographic data obtained in the course of experiments. The presented plots are based on those equations. Different approaches can be compared to show the difference between particular models.The methods presented in this paper enable a more detailed investigation of the influence of various parameters on the pupil. It can be used to better estimate the influence of light on pupil size. The main changes occurring in pupil size, i.e. contractions and dilation, are caused by light. Other criteria such emotional arousal, cognitive processes or even memory operations can also alter the pupil, among which the decoupling of light is important. The presented approach is distinct from other similar studies because it decouples the pupillary light reflex.

Purpose: Technological innovation has made it possible to review how a film cues particular reactions on the part of the viewers. The purpose of this paper is to capture and interpret visual perception and attention by the simultaneous use of eye tracking and electroencephalography (EEG) technologies. Design/methodology/approach: The authors have developed a method for joint analysis of EEG and eye tracking. To achieve this goal, an algorithm was implemented to capture and interpret visual perception and attention by the simultaneous use of eye tracking and EEG technologies. All parameters have been measured as a function of the relationship between the tested signals, which, in turn, allowed for a more accurate validation of hypotheses by appropriately selected calculations. Findings: The results of this study revealed a coherence between EEG and eye tracking that are of particular relevance for human perception. Practical implications: This paper endeavors both to capture and interpret visual perception and attention by the simultaneous use of eye tracking and EEG technologies. Eye tracking provides a powerful real-time measure of viewer region of interest. EEG technologies provides data regarding the viewer’s emotional states while watching the movie. Originality/value: The approach in this paper is distinct from similar studies because it takes into account the integration of the eye tracking and EEG technologies. This paper provides a method for determining a fully functional video introspection system.

A new approach is proposed for designing coils free of partial discharges (PDs) for compact machines operating at high altitudes. The proposed method consists in using an enameled wire made with a thin additional resistive layer on the outer surface, which reduces strongly the electrical field in the voids between the wires of random coils. With such a wire, PDs occur only in specific zones situated near the wire connections and a local reinforcement of the insulation can increase strongly the partial discharge inception voltage (PDIV). The paper proposes a theoretical method for determining the properties of the resistive layer. The local reinforcement of the insulation is analysed with an electrostatic simulation and Paschen's law. Measurements confirm the effectiveness of the proposed method.