Desarrollo de una práctica de Estadística Descriptiva con GeoGebra

El presente trabajo pretende dar una pauta para emplear el potencial de las herramientas TIC con el propósito de facilitar en el aula y fuera de ella, el aprendizaje de conceptos propios de la estadística a un nivel universitario. Existen diversos programas computacionales capaces de realizar análisis estadísticos de alto nivel: SPSS, Minitab, Matlab, por mencionar algunos; estos programas funcionan muy bien cuando se trata de encontrar respuestas a planteamientos complicados o cuando se tiene un enorme banco de datos. Para emplear de la forma correcta este tipo de software y no malinterpretar sus resultados, es necesario en primer lugar, que el usuario entienda perfectamente los conceptos básicos de la estadística descriptiva, como son el análisis para datos agrupados y no agrupados, medidas de tendencia central y de dispersión, así como los diversos gráficos y tablas de datos que describen la frecuencia con la cual sucede un evento; para lo cual es necesario el uso de un software dinámico y en este caso diseñado específicamente para el aprendizaje didáctico de las matemáticas como lo es GeoGebra

Uso del Internet como TIC en las MIPYMES de Celaya, Guanajuato

Se aplicó un instrumento sobre el uso de las TIC en empresas a nivel Micro, Pequeño y Mediano de la ciudad de Celaya, Guanajuato, dirigida principalmente hacia el uso de computadora y del Internet como herramienta de trabajo. De los resultados obtenidos se realizó un análisis estadístico de la  información del grado de implementación y uso del internet en la dinámica de trabajo de las empresas,  conformando una muestra de 91 establecimientos en total. El instrumento aplicado está basado en los indicadores para la Sociedad de la Información desarrollados por la Organización de las Naciones Unidas y el Grupo de Trabajo de la Organización de Cooperación y Desarrollo Económico.Los indicadores sobre el uso del internet como TIC obtenidos, señalan que existen actividades económicas abiertas al uso de tecnología, encontrando que dos de cada tres empresas disponen de página web y ésta se convierte en un canal prioritario para la comercialización de sus productos y/o servicios.Palabra(s) Clave(s): TIC, MIPYMES, Internet

PROPUESTA PARA REDUCIR LA DESERCIÓN EN EL NIVEL SUPERIOR (PROPOSAL TO REDUCE DROPOUT AT THE HIGHER LEVEL)

Resumen La problemática de los altos índices de reprobación y deserción en el nivel profesional, especialmente en los programas de ingeniería, ocasiona el abandono de los estudios ante el riesgo de baja definitiva del programa profesional que cursa. Esta situación ocasiona que el estudiante no cuente con documentación oficial que le permita su incorporación inmediata al sector productivo y de servicios, con la posibilidad de ejercer sus competencias y contar con condiciones laborales satisfactorias. En este contexto, ofertar programas de Profesional Asociado es un área de oportunidad tanto para las instituciones educativas para reducir los índices de deserción como para aquellos estudiantes que están en riesgo de quedar fuera de sus programas de nivel profesional. El programa de Profesional Asociado habilita la posibilidad para el estudiante en riesgo de baja definitiva, de su transición a un programa educativo que le ofrecerá una salida lateral o una alternativa de egreso diferenciado. En este trabajo, se presentan los resultados de una encuesta aplicada a 42 estudiantes para conocer su nivel de aceptación para la opción educativa de profesional asociado. Los estudiantes encuestados manifiestan interés en esta opción educativa, pues les parece atrae la posibilidad de incorporarse rápidamente al mercado laboral. Palabras Clave: deserción, egreso diferenciado, formación profesional, profesional asociado. Abstract The problem of high failure and dropout rates at the professional level, especially in engineering programs, causes students to drop out of studies due to the risk of permanent withdrawal from the professional program they are studying. This situation means that the student does not have official documentation that allows his immediate incorporation to the productive and services sector, with the possibility of exercising his skills and having satisfactory working conditions. In this context, offering associate professional programs is an area of opportunity both for educational institutions to reduce dropout rates and for those students who are at risk of being left out of their professional level programs. The associate professional program enables the possibility for the student at risk of permanent withdrawal, of their transition to an educational program that will offer them a lateral exit or a differentiated exit alternative. In this work, the results of a survey applied to 42 students are presented to know their level of acceptance for the educational option of associate professional. The surveyed students express interest in this educational option, as they find the possibility of quickly entering the labor market attractive. Keywords: desertion, differentiated graduation, professional training, associated professional

APLICACIÓN DE LA PERCEPTRÓN EN EL GRÁFICO DE CONTROL DE MEDICIONES INDIVIDUALES // IMPLEMENTATION OF THE PERCEPTRON IN THE CONTROL CHART FOR INDIVIDUAL

In this article the Perceptron artificial neural network is applied as a classifier system of out of control points, in the field of contrlol chart for individual measurements. The use of geometric properties of the Perceptron as a training method is introduced, replacing in consequence to the known training methods. Some experiments with numerical databases contaminated with altered data in global average was performed, and the ability of the detection of \out of control points" of the control chart with the implementation of the Perceptron trained by geometry was compared. The results reveal greater capacity in the Perceptron. This approach can be generalized to other types of control charts and patterns of natural and special variation, not considered in this research. // RESUMEN: En este artículo se aplica la red neuronal artificial Perceptrón como sistema clasificador de puntos fuera de control en el ámbito de la carta de control de mediciones individuales. Se introduce el uso de las propiedades geométricas de la Perceptrón como método de entrenamiento para sustituir, en consecuencia, a los métodos de entrenamiento conocidos. Se experimentó con bases de datos numéricas contaminadas con datos alterados en su media global y se comparó la capacidad de la detección de puntos fuera de control de la carta de control con la aplicación de la Perceptrón entrenada por geometría. Los resultados revelan mayor capacidad en la Perceptrón en diferentes porcentajes de contaminación. Esta propuesta puede ser generalizada a otros tipos de gráficos de control y a patrones de variación especial y natural no considerados en esta investigación

Generación de la formulación de color en un producto textil mediante redes neuronales artificiales

Color is an essential characteristic in quality for many products; to obtain the appropriate color is necessary to determine the colorants proportions required to get an exact coincidence of the color desired. In the textile industry, the development of an appropriate coloration is an essential quality standard, since it generates a direct impact in a product’s level of attraction. Currently in the textile industry, the color’s formulation development depends on a colorist master. That is why this process is highly subjective, since it depends from the colorist’s experience to get a coincidence of color in function of his appreciation. At the same time, the color’s visual evaluation depends on environmental factors such as: kind of illumination, light incidence, and the background color applied. Due to the subjectiveness and the low standardization of the color’s formulation in the textile industry, it is necessary the development of new techniques that allow to generate more exact color formulations. Artificial neural networks (ANN) are intelligent tools, which can be trained to imitate the colorists’ way of work, allowing the error minimization between the color to develop and a targeted color. With an ANN is possible to create efficient color recipes, in a faster and continuous way within a manufacturing process. To eliminate the color’s visual subjectivity evaluation, the ANN can be fed with precise colorimetric data from the object under study. In the present work the use of a 3-layer back propagation of an ANN is presented, which generates color formulations for textiles products from color coordinates L, a*, b* delivered from a colorimeter. The total measurement coefficient R obtained by the proposed ANN was 0.99776 having an error margin of 0.0016 and 0.0019 in milliliters for the applied colorants. Introduction Color evaluation is a quality standard of great importance, which influences the level of acceptance or rejection of many products in the industrial sector (Li, Wang, & Jing, 2015). In the textile industry, one of the most important processes is the appropriate coloring to dye certain type of fabric through the creation of adequate color recipes (Furferi & Carfagni, 2010). Color valuation in the textile industry depends highly in the product’s visual valuation, which is highly subjective, due to the fact that many environmental factors as well as the evaluator training affect the color’s perception. Currently, many methods have been developed for the color perception analysis. Artificial intelligence techniques and tools have been applied currently in them, such as the ANN (Li, Wang, & Jing, 2015). This article proposes the development of a system to obtain the color recipes, in which a back propagation ANN was applied to generate color formulations that have a small variation based on a stablished color pattern, applying a colorimeter as a measurement instrument, this due to its low cost regarding the spectrophotometer to obtain the color evaluation colorimetric coordinates that allowed the ANN training applied, reducing the subjectivity of color evaluation and formulation, when applying instrumental techniques within the process. Method For the present article, having cotton fabric as a base and 2 pigment vats (blue and yellow), 4 colorimetric samples were generated corresponding to 5 proposed formulations, which were replicated 4 times, thus obtaining a total of 20 experimental units, from which a total of 840 colorimetric data (corresponding to the vectors L, a*, b* in the color space CIELAB); this data was analyzed to determine if significant differences were present that could influence in the network’s performance in the color formulation, with this analysis done the data was applied to train a back propagation ANN. The ANN was analyzed with 5, 10, 15, and 20 neurons in the hidden layer, to determine the best structure that allows for error minimization in the formulation in a fast and adequate way. The choice of network depended on the correlation coefficient value (R-value) which was pretended to be closet to 1. With this process concluded, a proposal for a color formulation was obtained by the outcome from the ANN, which was analyzed to get the mean squared error (MSE); and to verify the ANN performance built according to the accuracy obtained in the color equalization from the formulation created. Results Then ANOVA analysis performed showed that there is a significant difference for the sample variable, but this difference didn’t affect the performance from the ANN training on obtaining the precise and adequate color formulations. The back propagation ANN designed showed a good performance for each analyzed case; having as a base the value R obtained in the training, the best ANN was selected for the purpose of the research; thus, obtaining the adequate color formulations; which were analyzed to get the mean squared error (MSE) value for each colorant applied and verify the selected ANN performance. Discussion or Conclusion A back propagation ANN is able to reduce the errors in the formulation of textiles products, in the present article, with the objective to minimize such errors, a back propagation ANN was trained; which has a 3-5-2 structure and showed a good performance for solving this kind of problems, with the ANN training an adequate color formulation was obtained, which showed a mean squared error of 0.0016628 for the blue colorant and 0.0019724 for the yellow colorant, the total correlation coefficient R obtained by the ANN was 0.99776, this value indicates that the created network is able to explain 99.77% of the variation observed in the data applied for its training