3,510 research outputs found
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
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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
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Globalización y competitividad económica en las ciudades de la región Centro Occidente de México en la última década del siglo XX
Peer Reviewe
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