Talento humano y trabajo en equipo del personal directivo de las universidades del municipio Maracaibo

The intention of this research was to determine the relation between human talent and teamwork among directive personnel at universities in the Maracaibo Municipality, based on the theoretical approaches of Alles (2005), Dolan et al. (2003), Gubman (2000), Hayes (2002), Jericó (2001), among others. Research was of the correlational, non-experimental, transversal type, using a population of 31 subjects pertaining to the administrative directors at the aforementioned public and private universities. Data was collected through observation using a survey, for which two (2) data collection instruments were designed, structured with five alternative answers on a Likert-type attitude scale; content was validated by the criteria of 10 experts, using furthermore, discriminating analysis of items, which allowed greater certainty in their designs. Reliability was calculated using the Cronbach Alpha coefficient, which produced a value of 0.99 for human talent and 0.91 for teamwork, showing high consistency. Results were analyzed using descriptive statistics with absolute and percentage frequencies, supported with central tendency measurements, also using inferential statistics with non-parametric tests. In conclusion, a correlation with a positive direction and strong magnitude between the variables with a Spearman rho index of 0.88 suggests a strong correspondence between the variables under the present conditions of this study.El propósito de esta investigación fue determinar la relación entre talento humano y trabajo en equipo del personal directivo de las universidades del Municipio Maracaibo, sobre la base de los enfoques teóricos de Alles (2005), Dolan et al. (2003), Gubman (2000), Hayes (2002), Jericó (2001), entre otros. La investigación se tipificó como correlacional, no experimental y transversal, utilizando una población de 31 sujetos pertenecientes a la planta directiva de administración de las referidas universidades públicas y privadas. La técnica de recolección de datos fue la observación mediante encuesta, para lo cual se diseñaron dos (2) instrumentos de recolección de datos, estructurados con cinco alternativas de respuestas bajo una escala de actitud tipo Likert, utilizando una validez de contenido por el criterio de 10 expertos, utilizando además el análisis discriminante de ítems, lo cual permitió mayor certeza en sus diseños. La confiabilidad fue calculada por el coeficiente Alfa de Cronbach, el cual arrojó un valor de 0.99 para talento humano y 0.91 para trabajo en equipo, siendo altamente consistentes. Los resultados se analizaron mediante estadística descriptiva con frecuencias absolutas y porcentuales, soportadas con medidas de tendencia central, haciendo uso además de la estadística inferencial con pruebas no paramétricas. Como conclusión, se observó una correlación con dirección positiva y magnitud fuerte entre las variables con un índice rho de Spearman de 0.88, lo que sugiere que bajo las actuales condiciones de este estudio existe una fuerte concomitancia entre las variables

Intelligent electronic tongue system for the classification of genuine and false honeys

ABSTRACTHoney quality is a global concern since this product is highly susceptible to adulteration, given its competitive price. As a reliable strategy for honey authenticity determination, this work introduces an intelligent classification system that considers the pattern recognition point of view to develop an economical and quick analytical method to identify and differentiate genuine from adulterated honey. This work used an electronic tongue composed of three working electrodes of carbon, platinum, and gold. The system used Cyclic voltammetry to obtain data from 50 genuine and 50 adulterated honey samples. Subsequently, the system used multivariate data analysis using a pattern recognition methodology composed of three big stages, including data organization and normalization, dimensionality reduction, and k-Nearest Neighbors (k-NN) as a classification method. The process was validated with the Leave One Out Cross Validation technique (LOOCV), reaching a classification accuracy performance of 100%. The results show that it was possible the development of a combined methodology between analytical tools and chemometrics for an in-situ, quick and efficient authenticity honey evaluation