Experimental verification of the stefan-boltzmann law in the physics iii course of the engineering department of La Plata university

Facultad de Ingeniera de la Universidad Nacional de La Plata abarca dos módulos bimestrales. En el segundo de ellos se abordan temas de Física Moderna y entre las actividades de laboratorio establecidas, los alumnos realizan un experimento donde comprueban la ley de Stefan-Bolztmann determinando la dependencia funcional de la irradiancia emitida por un cuerpo negro con su temperatura absoluta utilizando un cubo de Leslie. En el presente trabajo se describe el instrumental utilizado en el laboratorio, la metodología experimental realizada por los alumnos, se presentan las mediciones realizadas y se analiza la relación funcional entre la irradiancia emitida por el cubo de Leslie y su temperatura comprobando la Ley de Steffan-Boltzmann. Además, se determina el valor de la constante de Stefan-Boltzmann (V) analizando la relación de la radiación electromagnética emitida por la cara negra del cubo con su temperatura. Palabras Claves: Stefan-Boltzmann, cuerpo negro, temperatura, Ingeniería, laboratorio. (hasta 6)The Physics IIIA course of the Electronic, Electric and Chemical Engineering degrees of La Plata University includes two modules of two months each. The second teaching module includes Modern Physics topics and laboratory activities where students perform an experiment to verify the Stefan-Boltzmann law where they get the dependency of the radiation of the black body with the absolute temperature of the Leslie cube. In the present work, we describe the experimental methodology, the experimental equipment and we analyze the temperature dependence of the radiation emitted by the Leslie cube. Finally, we verified the Stefan-Boltzmann law and determine the Stefan-Bolzmann constant (V) from the temperature dependence of the radiation emitted by the black face of the Leslie cube.Fil: Muñoz, Emiliano Luis. Universidad Nacional de La Plata. Facultad de Ingenieria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Instituto de Física La Plata; ArgentinaFil: Creus, M.. Universidad Nacional de La Plata. Facultad de Ingenieria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); ArgentinaFil: Sanjuan, F.. Universidad Nacional de La Plata. Facultad de Ingenieria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); ArgentinaFil: Rabal, Hector Jorge. Universidad Nacional de La Plata. Facultad de Ingenieria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); ArgentinaFil: Gallego, J.. Universidad Nacional de La Plata. Facultad de Ingenieria; Argentin

Evaluation of negentropy-based cluster validation techniques in problems with increasing dimensionality

The aim of a crisp cluster validity index is to quantify the quality of a given data partition. It allows to select the best partition out of a set of potential ones, and to determine the number of clusters. Recently, negentropy-based cluster validation has been introduced. This new approach seems to perform better than other state of the art techniques, and its computation is quite simple. However, like many other cluster validation approaches, it presents problems when some partition regions have a small number of points. Different heuristics have been proposed to cope with this problem. In this article we systematically analyze the performance of different negentropy-based validation approaches, including a new heuristic, in clustering problems of increasing dimensionality, and compare them to reference criteria such as AIC and BIC. Our results on synthetic data suggest that the newly proposed negentropy-based validation strategy can outperform AIC and BIC when the ratio of the number of points to the dimension is not high, which is a very common situation in most real applications.The authors thank the financial support from DGUI-CAM/UAM (Project CCG10-UAM/TIC-5864

XP/Architecture: An Agile Model for Scaling XP

XP es uno de los métodos ágiles más usados por la industria del software y la comunidad científica. Sin embargo, la literatura reporta problemas para escalarlo cuando el equipo crece y el producto es complejo. El SEI propone prácticas de arquitectura como mecanismos para resolver asuntos de complejidad y organización de las soluciones para alcanzar los atributos de calidad más relevantes. Aprovechando la capacidad de los métodos de arquitecturas y para separar preocupaciones a gran escala, en este artículo se propone un método de desarrollo de software en que varios equipos de desarrollo XP trabajan coordinadamente alrededor de un equipo que incorpora en forma ágil prácticas arquitectónicas. El método ha sido aplicado en un estudio de caso en dos proyectos académicos, mostrando la capacidad del modelo para escalar grupos trabajo, organizados en equipos XP en proyectos de mediana complejidad.XP is one of the most used agile methods by the software industry and the scientific community. However, the literature reports problems scale it when the team grows and the product is complex. The SEI proposes architectural practices as mechanisms for resolving issues of complexity and organization of solutions to achieve the attributes of most relevant quality. Taking advantage of the capacity of the methods of architectures and to separate large-scale concerns, this article will proposes a method of software development in which several teams of XP development work in coordination around a team that incorporates in an agile architectural practices. The method has been applied in a study of case in two academic projects, showing the capacity of the model to scale work groups, organized in XP teams in medium-sized projects complexity

EDUMAT: gamified web tool for teaching elementary operations

Esta investigación propone un método para la enseñanza de operaciones elementales basadas en la gamificación y las tecnologías de la información y la comunicación con el objetivo de promover las mejores prácticas en el contexto de la educación y mejorar el rendimiento de los estudiantes de de educación básica en el área de matemáticas, centrado la división con sustracción sucesiva, que incluye las cuatro operaciones elementales (suma, resta, multiplicación y división) en un solo procedimiento. El método se implantó en una aplicación web con un entorno interactivo y didáctico donde a través del juego se puso a prueba las destrezas y el conocimiento que los estudiantes adquirían en el aula. La intención, fue verificar mediante una prueba de implantación en un entorno educativo si el método es realmente efectivo y si fomenta el interés de incluir estrategias didácticas de aprendizaje en las aulas de claseThis research proposes a method for teaching elementary operations based on gamification and information and communication technologies with the aim of promoting best practices in the context of education and improving the performance of basic education students in the area of mathematics, centered the division with successive subtraction, which includes the four elementary operations (addition, subtraction, multiplication and division) in a single procedure. The method was implemented in a web application with an interactive and didactic environment where through the game the skills and knowledge that students acquired in the classroom were tested. The intention was to verify by means of an implantation test in an educational environment if the method is really effective and if it fosters the interest of including didactic learning strategies in the classroo

Exploring deep learning for complex trait genomic prediction in polyploid outcrossing species

Genomic prediction (GP) is the procedure whereby the genetic merits of untested candidates are predicted using genome wide marker information. Although numerous examples of GP exist in plants and animals, applications to polyploid organisms are still scarce, partly due to limited genome resources and the complexity of this system. Deep learning (DL) techniques comprise a heterogeneous collection of machine learning algorithms that have excelled at many prediction tasks. A potential advantage of DL for GP over standard linear model methods is that DL can potentially take into account all genetic interactions, including dominance and epistasis, which are expected to be of special relevance in most polyploids. In this study, we evaluated the predictive accuracy of linear and DL techniques in two important small fruits or berries: strawberry and blueberry. The two datasets contained a total of 1,358 allopolyploid strawberry (2n=8x=112) and 1,802 autopolyploid blueberry (2n=4x=48) individuals, genotyped for 9,908 and 73,045 single nucleotide polymorphism (SNP) markers, respectively, and phenotyped for five agronomic traits each. DL depends on numerous parameters that influence performance and optimizing hyperparameter values can be a critical step. Here we show that interactions between hyperparameter combinations should be expected and that the number of convolutional filters and regularization in the first layers can have an important effect on model performance. In terms of genomic prediction, we did not find an advantage of DL over linear model methods, except when the epistasis component was important. Linear Bayesian models were better than convolutional neural networks for the full additive architecture, whereas the opposite was observed under strong epistasis. However, by using a parameterization capable of taking into account these non-linear effects, Bayesian linear models can match or exceed the predictive accuracy of DL. A semiautomatic implementation of the DL pipeline is available at https://github.com/lauzingaretti/deepGP/

Exploring deep learning for complex trait genomic prediction in polyploid outcrossing species

Genomic prediction (GP) is the procedure whereby the genetic merits of untested candidates are predicted using genome wide marker information. Although numerous examples of GP exist in plants and animals, applications to polyploid organisms are still scarce, partly due to limited genome resources and the complexity of this system. Deep learning (DL) techniques comprise a heterogeneous collection of machine learning algorithms that have excelled at many prediction tasks. A potential advantage of DL for GP over standard linear model methods is that DL can potentially take into account all genetic interactions, including dominance and epistasis, which are expected to be of special relevance in most polyploids. In this study, we evaluated the predictive accuracy of linear and DL techniques in two important small fruits or berries: strawberry and blueberry. The two datasets contained a total of 1,358 allopolyploid strawberry (2n=8x=112) and 1,802 autopolyploid blueberry (2n=4x=48) individuals, genotyped for 9,908 and 73,045 single nucleotide polymorphism (SNP) markers, respectively, and phenotyped for five agronomic traits each. DL depends on numerous parameters that influence performance and optimizing hyperparameter values can be a critical step. Here we show that interactions between hyperparameter combinations should be expected and that the number of convolutional filters and regularization in the first layers can have an important effect on model performance. In terms of genomic prediction, we did not find an advantage of DL over linear model methods, except when the epistasis component was important. Linear Bayesian models were better than convolutional neural networks for the full additive architecture, whereas the opposite was observed under strong epistasis. However, by using a parameterization capable of taking into account these non-linear effects, Bayesian linear models can match or exceed the predictive accuracy of DL. A semiautomatic implementation of the DL pipeline is available at https://github.com/lauzingaretti/deepGP/.info:eu-repo/semantics/publishedVersio

Cambios del patrón de radiación en arreglos lineales de dipolos de microcinta a 2,4 GHz en presencia de elementos parásitos

This paper presents one of the results of research conducted to study the changes in the impedance input and radiation pattern parameters of the antenna systems, specifically linear arrays of microstrip dipoles are used; it is chosen as a parameter study the radiation pattern, the input impedance parameter will be presented in another publication. For their study, the system is modeled using numerical techniques with the help of the method of moments, in the conformation of the mesh array is used basis function given by Rao-Wilton and Glisson. The model is simulated with the Matlab® tool, the radiation pattern is determined for a dipole type patch and an array of these; the parasitic elements (dipoles) are located at different distances from the original array dipole and calculates the radiation pattern again, which are compared to those originally found. Finally, the results are presented and the advantage of these studies for handling radiation pattern in radiant systems is evident. Additionally, the presence of an element of symmetry is evident, this situation allows a considerable decrease the number of simulations, since the effect of the parasitic elements located on one side of the array of dipoles is similar to the effect that occurs when the parasitic elements are located on the opposite side.En este artículo se presenta uno de los resultados de la investigación realizada para estudiar los cambios producidos en los parámetros de impedancia de entrada y patrón de radiación de los sistemas radiantes cuando son sometidos a la presencia de elementos parásitos. Específicamente, se utilizan arreglos lineales de dipolos de microcinta y se escoge como parámetro de estudio el patrón de radiación; el parámetro de impedancia de entrada será presentado en otra publicación. Para su estudio, el sistema es modelado mediante técnicas numéricas con la ayuda del método de los momentos, en la conformación de la malla del arreglo se utiliza la función base propuesta por Rao-Wilton y Glisson. El modelo es simulado con la herramienta Matlab®, se determina el patrón de radiación para un dipolo tipo parche y para un arreglo de estos elementos; se ubican elementos parásitos (dipolos) a diferentes distancias del dipolo y del arreglo original y se calculan nuevamente los patrones de radiación, los cuales son comparado con los inicialmente encontrados. Finalmente, se presentan los resultados y se evidencia la ventaja que tienen estos estudios para la manipulación del patrón de radiación en sistemas radiantes. Adicionalmente, se evidencia en el presente estudio la presencia de un elemento de simetría, lo cual permite disminuir en un alto porcentaje las simulaciones, ya que el efecto producido por los elementos parásitos ubicados a un lado del arreglo de dipolos es similar al efecto que se produce cuando se ubican los elementos parásitos al lado opuesto