Child Labor in Colombia: Physical and Psychological Discomfort at Work in Children Who Work and Attend School

This study examined the health consequences of child labor in Colombian through the use of a dataset on the economic and non-economic activities engaged in by children and adolescents during 2011. The data collection was a collective effort between the Colombian government and the International Labor Organization (ILO). The data was collected on 48,876 children between the ages of 4 and 17 (mean=11.13, SD=3.7). This particular study focused on a subset of the population of children that either worked and attended school (n=3989) or only worked (n=2,118). Univariate Analysis of Variance (ANOVA) was used to determine whether there was a statistically significant difference between these two groups on the basis of physical and psychological discomfort at work. The group of children who worked and attended school was associated with statistically significant lower mean physical (M=.043) and psychological discomfort (M=.023) than the group of children who only worked (M=.044; M=.066, respectively). The higher mean discomfort in children who only worked showed that attending school mitigates children\u27s discomfort at work. By promoting protective factors to deter child labor, the Colombian government could safeguard children’s health and development. Education should be at the forefront of these. Keywords: Child labor, Colombia, Health, Mental Healt

Harnessing synthetic gauge fields for maximally entangled state generation

We study the generation of entanglement between two species of neutral cold atoms living on an optical ring lattice, where each group of particles can be described by a $d$-dimensional Hilbert space (qu$d$it). Synthetic magnetic fields are exploited to create an entangled state between the pair of qu$d$its. Maximally entangled eigenstates are found for well defined values of the Aharonov-Bohm phase, which are zero energy eigenstates of both the kinetic and interacting parts of the Bose-Hubbard Hamiltonian, making them quite exceptional and robust against certain non-perturbative fluctuations of the Hamiltonian. We propose a protocol to reach the maximally entangled state (MES) by starting from an initially prepared ground state. Also, an indirect method to detect the MES by measuring the current of the particles is proposed.Comment: 10 pages, 3 figure

A systems thinking approach to business intelligence solutions based on cloud computing

Thesis (S.M. in System Design and Management)--Massachusetts Institute of Technology, Engineering Systems Division, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 73-74).Business intelligence is the set of tools, processes, practices and people that are used to take advantage of information to support decision making in the organizations. Cloud computing is a new paradigm for offering computing resources that work on demand, are scalable and are charged by the time they are used. Organizations can save large amounts of money and effort using this approach. This document identifies the main challenges companies encounter while working on business intelligence applications in the cloud, such as security, availability, performance, integration, regulatory issues, and constraints on network bandwidth. All these challenges are addressed with a systems thinking approach, and several solutions are offered that can be applied according to the organization's needs. An evaluations of the main vendors of cloud computing technology is presented, so that business intelligence developers identify the available tools and companies they can depend on to migrate or build applications in the cloud. It is demonstrated how business intelligence applications can increase their availability with a cloud computing approach, by decreasing the mean time to recovery (handled by the cloud service provider) and increasing the mean time to failure (achieved by the introduction of more redundancy on the hardware). Innovative mechanisms are discussed in order to improve cloud applications, such as private, public and hybrid clouds, column-oriented databases, in-memory databases and the Data Warehouse 2.0 architecture. Finally, it is shown how the project management for a business intelligence application can be facilitated with a cloud computing approach. Design structure matrices are dramatically simplified by avoiding unnecessary iterations while sizing, validating, and testing hardware and software resources.by Eumir P. Reyes.S.M.in System Design and Managemen

Current and entanglement in a Bose-Hubbard lattice

We study the generation of entanglement for interacting cold atoms in an optical lattice. The entanglement is generated by managing the interaction between two distinct atomic species. It is found that the current of one of the species can be used as a good indicator of entanglement generation. The thermalization process between the species is also shown to be closely related to the evolution of the current.Comment: 10 pages, 5 figure

Análisis de los contenidos de los dosieres de las asignaturas elaborados por los docentes de la carrera de Educación Comercial, entregada a los alumnos de tercer año, primer semestre 2016

Este documento está basado en los contenidos de los dosieres de las asignaturas elaborados por los docentes, que entregan a los alumnos de tercer año en el primer semestre 2016. Durante la investigación se analizaron algunas dificultades encontradas al respecto a la reproducción de dosieres que son entregados a los alumnos. De acuerdo al tipo de investigación tanto maestros como estudiantes se les hizo una entrevista. Los instrumentos antes mencionados nos brindan pautas para determinar probables causas de problemas identificados y así los alumnos podrán tener mejor rendimiento académico. Al final esta tesis propone que esto dosieres deben ser ejecutivos con el enfoque metodológico con alto contenido científico y alto nivel de actualizació

DETECCIÓN DE FALLAS OPERACIONALES CON REDES NEURONALES ARTIFICIALES: APLICACIÓN DEL PROCESO TENNESSEE EASTMAN

The purpose of this article is to compare results of fault detection for the Tennessee Eastman (TE) process with the application of artificial neural networks (ANN). The Neuralnet library of the open-source program R, as well as the Keras library of the open-source program Python were used for the training of ANN. The TE process simulation data were down loaded from Harvard University’s server, and subsequently analyzed, defining the trends in the operational variables during the appearance of failures. With the database, the training and validation of different ANN structures were developed, considering the parameters number of hidden neurons, activation function, and number of hidden layers. According to the results, the training and validation of the ANNs with the Neuralnet library yielded a lower performance in fault detection than that obtained with the Keras library. The ANN with the best performance in detecting failures in the TE process was obtained by the application of the Keras library. This ANN considered 52 input variables, 11 neurons in the hidden layer, and one neuron in the output layer, using a logistic function (ANN represented as 52:11:1 logistic) and reporting a prediction efficiency of 92% for the detection of faults with an external test set, which is convenient for future implementation in industrial processes.Este artículo tiene como finalidad la comparación de resultados de detección de fallas en el proceso Tennessee Eastman (TE) con redes neu ronales artificiales (RNA), utilizando las librerías neuralnet del programa de código abierto R y Keras del programa de código abierto Python. Para esto, los datos de la simulación de proceso TE fueron descargados del servidor de la universidad de Harvard, y posteriormente analizados, definiendo las tendencias en las variables operacionales ante las res pectivas fallas. Con la base de datos, el entrenamiento y la validación de diferentes estructuras de RNA fue desarrollado considerando los parámetros: número de neuronas ocultas, función de activación y número de capas ocultas. Según los resultados, el entrenamiento y la validación de las RNA con la librería neuralnet reportó menores desempeños de detección de fallas, que las obtenidas con la librería Keras. La RNA de mejor desempeño en la detección de fallas del proceso TE correspondió a la estructura 52 variables de entrada, 11 neuronas en la capa oculta y una neurona en la capa de salida, con función logística y entrenada con la librería Keras (RNA representada como 52:11:1 logistic). Esta RNA presenta una eficiencia en la predicción del 92% para la detección de fallas en un conjunto externo de prueba, lo que resulta conveniente en una futura implementación en procesos industriales