SEGURIDAD E HIGIENE EN LAS EMPRESAS DE MANUFACTURA “LA RESISTENCIA DE LOS TRABAJADORES AL USO DE IMPLEMENTOS DE TRABAJO”

Las empresas de manufactura tienen como característica principal la transformación de la materia prima, en este sentido los empleados forman parte fundamental en el proceso mencionado.En el presente ensayo se abordaran temas relacionados con la seguridad e higiene en las empresas de manufactura, como seguridad, accidentes de trabajo, higiene, enfermedades laborales entre otro temas de interés, con el fin de conocer la resistencia de los trabajadores al uso de los implementos de trabajo, describiendo la función de cada uno de esos, y cada una de sus principales funciones, con el fin de conocer cada una de las causas del porque se resisten a su uso de los mismos

Development of an Automated Multiple Material Stereolithography Machine

An automated Multiple Material Stereolithography (MMSL) machine was developed by integrating components of a 3D Systems 250/50 stereolithography (SL) machine in a separate stand-alone system and adapting them to function with additional components required for MMSL operation. We previously reported retrofitting a 250/50 SL machine with multiple vats to accommodate multiple material fabrication for building a wide variety of multi-material models (Wicker et al., 2004). In the MMSL retrofit, spatial constraints limited the multiple vats located circumferentially on a vertical rotating vat carousel to cross-sectional areas of approximately 4.5-inches by 4.5-inches. The limited build size of the retrofitted 250/50 motivated the full development of a new system with multiple material build capabilities comparable to the build envelope of the original 250/50 machine. The new MMSL machine required fabrication of a large system frame, incorporating various 250/50 components and software, and adding a variety of new components and software. By using many existing components and software, the previous engineering development of 3D Systems could be directly applied to this new technology. Components that were transferred from an existing 250/50 to the MMSL machine included the complete optical system (including the optics plate with laser, mirrors, beam expander, scanning mirrors, and focusing lens), the rim assembly (including the laser beam profilers), the associated controllers (computer system, scanning mirror controller, power supply-vat controller) and the wiring harness. In addition to the new frame, the MMSL machine required the development of a new rotating vat carousel system, platform assembly, multi-pump filling/leveling system, and a custom LabVIEW® control system to provide automated control over the MMSL process. The overall operation of the MMSL system was managed using the LabVIEW® program, which also included controlling a new vat leveling system and new linear and rotational stages, while the 3D Systems software (Buildstation 4.0) was retained for controlling the laser scanning process. As a demonstration of MMSL technology, simple multi material parts were fabricated with vertically and horizontally oriented interfaces. The fully functional MMSL system offers enormous potential for fabricating a wide variety of multiple material functional devices.Mechanical Engineerin

Privacy-preserving parametric inference: a case for robust statistics

Differential privacy is a cryptographically-motivated approach to privacy that has become a very active field of research over the last decade in theoretical computer science and machine learning. In this paradigm one assumes there is a trusted curator who holds the data of individuals in a database and the goal of privacy is to simultaneously protect individual data while allowing the release of global characteristics of the database. In this setting we introduce a general framework for parametric inference with differential privacy guarantees. We first obtain differentially private estimators based on bounded influence M-estimators by leveraging their gross-error sensitivity in the calibration of a noise term added to them in order to ensure privacy. We then show how a similar construction can also be applied to construct differentially private test statistics analogous to the Wald, score and likelihood ratio tests. We provide statistical guarantees for all our proposals via an asymptotic analysis. An interesting consequence of our results is to further clarify the connection between differential privacy and robust statistics. In particular, we demonstrate that differential privacy is a weaker stability requirement than infinitesimal robustness, and show that robust M-estimators can be easily randomized in order to guarantee both differential privacy and robustness towards the presence of contaminated data. We illustrate our results both on simulated and real data

Centrality measures for graphons: Accounting for uncertainty in networks

As relational datasets modeled as graphs keep increasing in size and their data-acquisition is permeated by uncertainty, graph-based analysis techniques can become computationally and conceptually challenging. In particular, node centrality measures rely on the assumption that the graph is perfectly known -- a premise not necessarily fulfilled for large, uncertain networks. Accordingly, centrality measures may fail to faithfully extract the importance of nodes in the presence of uncertainty. To mitigate these problems, we suggest a statistical approach based on graphon theory: we introduce formal definitions of centrality measures for graphons and establish their connections to classical graph centrality measures. A key advantage of this approach is that centrality measures defined at the modeling level of graphons are inherently robust to stochastic variations of specific graph realizations. Using the theory of linear integral operators, we define degree, eigenvector, Katz and PageRank centrality functions for graphons and establish concentration inequalities demonstrating that graphon centrality functions arise naturally as limits of their counterparts defined on sequences of graphs of increasing size. The same concentration inequalities also provide high-probability bounds between the graphon centrality functions and the centrality measures on any sampled graph, thereby establishing a measure of uncertainty of the measured centrality score. The same concentration inequalities also provide high-probability bounds between the graphon centrality functions and the centrality measures on any sampled graph, thereby establishing a measure of uncertainty of the measured centrality score.Comment: Authors ordered alphabetically, all authors contributed equally. 21 pages, 7 figure

Imputación de datos: teoría y práctica

Incluye BibliografíaDocumento preparado por Fernando Medina y Marco Galván, Asesor Regional y Asistente de Investigación, respectivamente, de la Unidad de Estadísticas Sociales de la División de Estadística y Proyecciones Económicas de la CEPAL.Las opiniones expresadas en este documento, que no ha sido sometido a revisión editorial, son de exclusiva responsabilidad de los autores y pueden no coincidir con las de la Organización. RESUMEN La presencia de datos faltantes, es la situación a la que permanentemente se enfrentan investigadores y tomadores de decisiones. Disponer de un archivo de datos completos es ideal, pero aplicar métodos de imputación inapropiados para lograrlo, puede generar más problemas de los que resuelve. Durante las últimas décadas se han desarrollado procedimientos que tienen mejores propiedades estadísticas que las opciones tradicionales como la eliminación de datos (listwise), el pareo de observaciones (pairwise), el método de medias y el hot-deck. Los algoritmos de imputación múltiple (IM) se pueden aplicar utilizando paquetes comerciales y de acceso gratuito, pero imputar información no debe entenderse como un fin en sí mismo. Sus implicaciones en el análisis secundario de datos deben evaluarse con cautela, y este trabajo concluye que no existe el método de imputación ideal. Cada situación es diferente, y la tasa de no respuesta y su distribución espacial cambia entre encuestas, por lo que no es conveniente adoptar —a priori— el mismo procedimiento de imputación para todas las variables, en todas las encuestas. En la primera parte se analiza la teoría en la que se sustentan los procedimientos de imputación utilizados, y en la segunda se aplican ocho métodos alternativos para imputar distintos conceptos de ingreso para datos provenientes de una encuesta de hogares, y se evalúa la sensibilidad de los índices de pobreza y desigualdad (Gini, Theil y Atkinson (ε = 2), a las técnicas de imputación utilizadas. Se demuestra que los índices de pobreza son sensibles a los métodos de imputación, en tanto el procedimiento de sustitución de información tiene menor impacto en los indicadores de desigualdad

Jerarquía funcional y urbana entre las zonas metropolitanas de la región Centro Occidente de México en el contexto de la globalización

Peer Reviewe

Globalización y competitividad económica en las ciudades de la región Centro Occidente de México en la última década del siglo XX

Peer Reviewe