Using multiple evaluation methods and systems give a comprehensive assessment. A computer-based multiple-choice assessment system was designed, implemented, posted online, and used to assess students as part of their final evaluation marks for a discipline. The online system of evaluation was intended to be used multiple times for evaluating the assimilation degree of a specific course at the end of the course. The data recorded for the period 2017–2023 with about 1400 distinct users were used to analyze the performance of the evaluation system. The system worked fine and a slight modification of it served well on remote evaluation during COVID-19 period. However, the upturn of mobile phone applications requires the creation of a system adapted to the new virtual reality.

The relationship between new-quality productivity and educational equity is characterized by close mutual influence and co-evolution. Driven by technological innovation, new-quality productivity is profoundly transforming the economic and social landscape. Educational equity, a crucial component of social justice, is vital for ensuring equal development opportunities for all individuals. The robust growth of new-quality productivity not only optimizes the distribution of educational resources and enhances educational quality but also poses new challenges and demands for equity in education. In turn, the continuous advancement of educational equity provides a solid talent foundation and a conducive environment for innovation to new-quality productivity. These two aspects intertwine and progress together in various domains, including policy systems, cultural values, and educational practices. This interplay highlights the central role of new-quality productivity and educational equity in societal development, while also demonstrating their dynamic and complementary relationship.

The cost of diagnostic errors has been high in the developed world economics according to a number of recent studies and continues to rise. Up till now, a common process of performing image diagnostics for a growing number of conditions has been examination by a single human specialist (i.e., single-channel recognition and classification decision system). Such a system has natural limitations of unmitigated error that can be detected only much later in the treatment cycle, as well as resource intensity and poor ability to scale to the rising demand. At the same time Machine Intelligence (ML, AI) systems, specifically those including deep neural network and large visual domain models have made significant progress in the field of general image recognition, in many instances achieving the level of an average human and in a growing number of cases, a human specialist in the effectiveness of image recognition tasks. The objectives of the AI in Medicine (AIM) program were set to leverage the opportunities and advantages of the rapidly evolving Artificial Intelligence technology to achieve real and measurable gains in public healthcare, in quality, access, public confidence and cost efficiency. The proposal for a collaborative AI-human image diagnostics system falls directly into the scope of this program.

The cross wire projection welding of wires (Al 5182, = 4 mm) performed using the conventional (i.e. pneumatic) electrode force system was subjected to thorough numerical analysis. Calculations were performed until one of adopted boundary conditions, i.e., maximum welding time, maximum penetration of wires, the occurrence of expulsion or the exceeding of the temperature limit in the contact between the electrode and the welded material was obtained. It was observed that the ring weld was formed within the entire range of welding parameters. The process of welding was subjected to optimisation through the application of a new electromechanical electrode force system and the use of a special hybrid algorithm of electrode force and/or displacement control. Comparative numerical calculations were performed (using SORPAS software) for both electrode force systems. Technological welding tests were performed using inverter welding machines (1 kHz) provided with various electrode force systems. The research also involved the performance of metallographic and strength (peeling) tests as well as measurements of welding process characteristic parameters (welding current and voltage).
The welding process optimisation involving the use of the electromechanical force system and the application of the hybrid algorithm of force control resulted in i) more favourable space distribution of welding power, ii) energy concentration in the central zone of the weld, iii) favourable (desired) melting of the material within the entire weld transcrystallisation zone and iv) obtainment of a full weld nugget.