The aim of this paper was to examine whether the COVID-19 epidemic has slowed the fulfilment of one of the core tasks of the energy sector “Ensure Access to Affordable, Reliable, Sustainable and Modern Energy for All” (SDG7) taking into account corporate social responsibility. Four research questions and hypotheses were posed, relating to the perspectives of local authorities, the activities of large energy companies, the impact of the epidemic on the implementation of the SDG7 and, in addition, to the understanding of CSR principles from the point of view of ordinary entrepreneurs. A qualitative descriptive analysis based on two reliable databases and a survey procedure (Question 4) was used to answer the research questions posed. The goal was achieved by positively confirming three hypotheses and testing one negatively, relating to COVID-19’s slowing role in SDG7 implementation. The analysis showed that the 2020–2021 epidemic in Poland has led to more initiatives in this area, contrary to expectations. However, they were linked to the simultaneous implementation of other SDGs, which distorted their importance for achieving Goal 7. In summary, although energy companies were more active than expected during the epidemic, they had a low contribution to SDG 7. This also applies to local authorities. An analysis of the knowledge about CSR in a group of entrepreneurs from the Lublin district (case study) confirmed the opinion appearing in the literature about the lack of understanding of the concept and the need for its application.
This paper describes the method developed using the Extreme Gradient Boosting (Xgboost) algorithm that allows high-resolution imaging using the ultrasound tomography (UST) signal. More precisely, we can locate, isolate, and use the reflective peaks from the UST signal to achieve high-resolution images with low noise, which are far more useful for the location of points where the reflection occurred inside the experimental tank. Each reconstruction is divided into two parts, estimation of starting points of wave packets of raw signal (SAT—starting arrival time) and image reconstruction via XGBoost algorithm based on SAT matrix. This technology is the basis of a project to design non-invasive monitoring and diagnostics of technological processes. In this paper, we present a method of the complete solution for monitoring industrial processes. The measurements used in the study were obtained with the author’s solution of ultrasound tomography.
carried studies in Southern Anatolia. Kowalski, at that time already an outstanding oriental linguist, was studying the dialects of this part of Turkey, while the accompanying young geographer Leszczycki prepared anthropogeographical observations of the villages focusing on the impact of geographical environment on rural settlements. In fact this was not the first Polish geographical study in Anatolia. Nearly 10 years earlier another social geographer, Professor Ludomir Rozycki, investigated mountain areas in Turkey and encouraged younger scholars to perform direct observations and analyses in the areas unknown in Poland. Leszczycki was carrying out his field studies in Southern Anatolia during 6 weeks from August 1st till September 13th, 1936. He prepared questionnaire which was filled out in the total of 30 villages, seasonal settlements and towns. The settlements were chosen along two profiles cutting the Taurus mountains from North to the South and along the motorways, i.e. from Karaman to Silifke and from Dinar to Antalya. In our reports we will name the former "the Eastern Route" and the latter "the Western Route". The results of Leszczycki's studies were published only in 1987, to celebrate His 80th birthday, by the Polish Academy of Sciences-the Institute of Geography 1. In the mid-1980s Professor Leszczycki, an already internationally known scientist (the President of International Geographical Union
The work covers the development of intelligent sensors, as well as intelligent mechanisms for the assembly and control of industrial processes using modern measurement techniques, process tomography, vision systems, motion and temperature sensors. Design/Methodology/Approach: Tomographic techniques and new analytical algorithms were used. Special algorithms have been developed to combine data from different types of measurements in real time to identify potential hazards or undesirable effects. Findings: The use of various types of data in a single decision-making process, starting with the availability of resources, availability of staff and ending with the maintenance schedules of machines, will allow for the analysis and optimisation of the process. The use of the socalled uncertain data and data that do not have an unambiguous impact on the production process requires the use of solutions based on artificial intelligence algorithms in the decision-making process, which are able to draw conclusions relatively quickly based on such data, and then quickly affect the optimisation of the production process. The results of the conducted research indicate that a platform with an open architecture can be a useful tool in the control and steering of industrial processes. Practical Implications: A measurement module that allows to unify the signal coming out of particular measurement sub-assemblies to a coherent form, thanks to which the acquisition, storage and processing of any quantity can be carried out in a similar way for each case. Originality/Value: The novelty and innovation of the system is a unique technological solution (types of measurements and data processing), new algorithms for optimisation, reconstruction and data analysis, a unique multi-module device based on tomographic technologies. The project as a whole as well as each of its components is innovative on a global scale. The use of tomography for analysis, control and monitoring of technological processes is an innovative solution.
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