This page contains a Flash digital edition of a book.

Abbott, A. D. (2004). Methods of discovery: Heuristics for the social sciences. WW Norton & Company New York.

Alonso-Almeida, M., Llach, J., and Marimon, F. (2014). A closer look at the global reporting initiative sustainability reporting as a tool to implement environmental and social policies: a worldwide sector analysis. Corporate Social Responsibility and Environmental Management, 21(6):318–335. Amit, D. J. (1992). Modeling brain function: The world of attractor neural networks. Cambridge University Press.

Bohland, J. and Minai, A. (2001). Efficient associative memory using small-world architecture. Neurocomputing, 38-40:489–496. Carpenter, G. A., Grossberg, S., Markuzon, N., Reynolds, J. H., and Rosen, D. B. (1992). Fuzzy artmap: A neural network architecture for incremental supervised learning of analog multidimensional maps. Neural Networks, IEEE Transactions on, 3(5):698–713.

Hopfield, J. J. (1982). Neural networks and physical systems with emergent collective computational abilities. Proceedings of the National Academy of Sciences of the United States of America, 79(8):2554–2558.

Jones, S., Frost, G., Loftus, J., and Laan, S. (2007). An empirical examination of the market returns and financial performance of entities engaged in sustainability reporting. Australian Accounting Review, 17(41):78–87.

Kim, K.-j. (2006). Artificial neural networks with evolutionary instance selection for financial forecasting. Expert Systems with Applications, 30(3):519–526. Lamberton, G. (2005). Sustainability accounting—a brief history and conceptual framework. In Accounting Forum, volume 29, pages 7–26. Elsevier. Marimon, F., del Mar Alonso-Almeida, M., del Pilar Rodríguez, M., and Alejandro, K. A. C. (2012). The worldwide diffusion of the global reporting initiative: what is the point? Journal of Cleaner Production, 33:132–144.

Davis, L. et al. (1991). Handbook of genetic algorithms, volume 115. Van Nostrand Reinhold New York. Dominguez, D., González, M., Rodríguez, F. B., Serrano, E., Jr., R. E., and Theumann, W. (2012). Structured information in sparse-code metric neural networks. Physica A: Statistical Mechanics and its Applications, 391(3):799 – 808. Dominguez, D., González, M., Serrano, E., and Rodríguez, F. B. (2009). Structured information in small-world neural networks. Phys. Rev. E, 79(2):021909. Etzion, D. and Ferraro, F. (2010). The role of analogy in the institutionalization of sustainability reporting. Organization Science, 21(5):1092–1107. González, M., del Mar, A.-A. M., Avila, C., and Dominguez, D. (2015). Modeling sustainability report scoring sequences using an attractor network. Neurocomputing, In Review. González, M., Dominguez, D., and Ángel Sánchez (2011). Learning sequences of sparse correlated patterns using small-world attractor neural networks: An application to traffic videos. Neurocomputing, 74(14-15):2361 – 2367. González, M., Dominguez, D., and Rodríguez, F. B. (2009). Block attractor in spatially organized neural networks. Neurocomputing, 72(16):3795–3801.

González, M., Dominguez, D., Rodríguez, F. B., and Sanchez, A. (2014). Retrieval of noisy fingerprint patterns using metric attractor networks. International journal of neural systems, 24(07).

Ruppin, E. and Yeshurun, Y. (1991). Recall and Recognition in an Attractor Neural Network Model of Memory Retrieval. Connection Science, 3:381 – 400. Saad, E. W., Prokhorov, D. V., and Wunsch, D. C. (1998). Comparative study of stock trend prediction using time delay, recurrent and probabilistic neural networks. Neural Networks, IEEE Transactions on, 9(6):1456–1470. Shahi, A., Issac, B., and Modapothala, J. (2012). Intelligent corporate sustainability report scoring solution using machine learning approach to text categorization. In Sustainable Utilization and Development in Engineering and Technology (STUDENT), 2012 IEEE Conference on, pages 227–232. IEEE.

Stringer, S. M., Rolls, E. T., Trappenberg, T. P., and de Araujo, I. E. T. (2003). Self-organizing continuous attractor networks and motor function. Neural Networks, 16:161–182. Watts, D. J. and Strogatz, S. H. (1998). Collective dynamics of ’small-world’ networks. Nature, 393:440–422. Willis, A. (2003). The role of the global reporting initiative’s sustainability reporting guidelines in the social screening of investments. Journal of Business Ethics, 43(3):233–237. Wong, C. and Versace, M. (2011). Context sensitivity with neural networks in financial decision processes. Global Journal of Business Research, 5(5):27–43.

La seguridad y salud en el trabajo en la Escuela Politécnica Nacional

Kléber Mejía Guzmán, Valentina Ramos Ramos. 1

1 Escuela Politécnica Nacional, Facultad de Ciencias Administrativas, Av. Ladrón de Guevara E11-253, CP170413, Quito,

2 Escuela Politécnica Nacional, Facultad de Ciencias Administrativas, Av. Ladrón de Guevara E11-253, CP170413, Quito

El presente artículo recoge algunas ideas de la tesis: “Propuesta de organización del servicio de seguridad y salud en el trabajo, para una Universidad Pública Ecuatoriana: caso Escuela Politécnica Nacional, de la ciudad de Quito, Enero a Mayo del 2013”, presentada para la Facultad de Jurisprudencia, Ciencias Políticas y Sociales de la Universidad Central del Ecuador, en junio del 2013, previo a la obtención del título de Magister en Prevención de Riesgos Laborales, y elaborada por Kléber Hernán Mejía Guzmán

Algunas generalidades

El tema de la salud es una realidad compleja, que abarca desde la problemática estrictamente técnica hasta efectos humanos, organizacionales y sociales. Además es un derecho fundamental que significa no solamente la ausencia de enfermedad, sino que toma en cuenta a los elementos y factores que afectan negativamente el estado físico, mental y ambiental

sobre la calidad y afectación de la imagen institucional.

La gestión de la seguridad y salud en el trabajo, es un conjunto de elementos interrelacionados e interdependientes que tienen por objeto establecer políticas, objetivos y estrategias de seguridad y salud en los ambientes laborables; así como, los

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