RESUMEN
This paper introduces the application of a genetic programming (GP)-based method for the automated design and tuning of process controllers, representing a noteworthy advancement in artificial intelligence (AI) within the realm of control engineering. In contrast to already existing work, our GP-based approach operates exclusively in the time domain, incorporating differential operations such as derivatives and integrals without necessitating intermediate inverse Laplace transformations. This unique feature not only simplifies the design process but also ensures the practical implementability of the generated controllers within physical systems. Notably, the GP's functional set extends beyond basic arithmetic operators to include a rich repertoire of mathematical operations, encompassing trigonometric, exponential, and logarithmic functions. This broad set of operations enhances the flexibility and adaptability of the GP-based approach in controller design. To rigorously assess the efficacy of our GP-based approach, we conducted an extensive series of tests to determine its limits and capabilities. In summary, our research establishes the GP-based approach as a promising solution for automating the controller design process, offering a transformative tool to address a spectrum of control problems across various engineering applications.
RESUMEN
The aim of this study was to examine the validity and reliability of the Maslach Burnout Inventory-Human Services Survey (MBI-HSS) as a tool for assessing the prevalence and level of burnout in dental students in Spanish universities. The survey was adapted from English to Spanish. A sample of 533 dental students from 15 Spanish universities and a control group of 188 medical students self-administered the survey online, using the Google Drive service. The test-retest reliability or reproducibility showed an Intraclass Correlation Coefficient of 0.95. The internal consistency of the survey was 0.922. Testing the construct validity showed two components with an eigenvalue greater than 1.5, which explained 51.2% of the total variance. Factor I (36.6% of the variance) comprised the items that estimated emotional exhaustion and depersonalization. Factor II (14.6% of the variance) contained the items that estimated personal accomplishment. The cut-off point for the existence of burnout achieved a sensitivity of 92.2%, a specificity of 92.1%, and an area under the curve of 0.96. Comparison of the total dental students sample and the control group of medical students showed significantly higher burnout levels for the dental students (50.3% vs. 40.4%). In this study, the MBI-HSS was found to be viable, valid, and reliable for measuring burnout in dental students. Since the study also found that the dental students suffered from high levels of this syndrome, these results suggest the need for preventive burnout control programs.
