La Encuesta Nacional de Salud como herramienta de medición de la doble carga y sobrecarga de trabajo en España: comparación con la Encuesta de Población Activa

Objetivo: Determinar si la ENS y la EPA de 2006 producen la misma información sobre labores del hogar y doble carga de trabajo en la población de 25 a 64 años, en ambos sexos. Métodos: Comparación entre las ENS y EPA sobre la forma de recoger información de la doble carga de trabajo. Fuente: Preguntas ENS: actividad económica (C.1.2:categorías 1,2,6), dedicación labores del hogar (A.11:categorías 1,2,3). EPA: actividad económica (H.1:categorías 1,5). Descripción por sexo en España y Comunidades Autónomas (CC.AA). Resultados: El 43,4% de las mujeres según la EPA tienen doble carga de trabajo, pero solo un 0,7% según la ENS. En los hombres el 31,5% (EPA) y el 0,02% (ENS). Alternativamente, cruzando a quienes afirman trabajar (C.1.2:categorías 1,2) con quienes realizan labores del hogar (A.11:categorías 1,2,3), la doble carga de ambas encuestas se aproxima (Hombres: ENS:31,7%; EPA:31,5%; Mujeres: ENS:46,3%; EPA:43,4%). Ambas encuestas ordenan de forma similar a las CC.AA según la doble carga de trabajo (ρmujeres:0,770 (p=0,001); ρhombres:0,647 (p=0,003)). Conclusión: La pregunta de actividad económica de la ENS subestima la frecuencia de la doble carga de trabajo. Esta es parecida en ambas encuestas, si se cruzan los datos de quienes afirman trabajar con quienes realizan labores del hogar de la ENS. En este caso, ambas encuestas ordenan de igual forma a las CC.AA. La exclusión del adverbio «principalmente» de la categoría sobre dedicación a las labores del hogar de la ENS 2011 normalizará la pregunta sobre actividad económica respecto a las utilizadas en encuestas de salud internacionales y de CC.AA.

Random exams using Sweave

The adaptation of the Spanish University to the European Higher Education Area (EEES in Spanish) demands the integration of new tools and skills that would make the teaching- learning process easier. This adaptation involves a change in the evaluation methods, which goes from a system where the student was evaluated with a final exam, to a new system where we include a continuous evaluation in which the final exam may represent at most 50% in the vast majority of the Universities. Devising a new and fair continuous evaluation system is not an easy task to do. That would mean a student’s’ learning process follow-up by the teachers, and as a consequence an additional workload on existing staff resources. Traditionally, the continuous evaluation is associated with the daily work of the student and a collection of the different marks partly or entirely based on the work they do during the academic year. Now, small groups of students and an attendance control are important aspects to take into account in order to get an adequate assessment of the students. However, most of the university degrees have groups with more than 70 students, and the attendance control is a complicated task to perform, mostly because it consumes significant amounts of staff time. Another problem found is that the attendance control would encourage not-interested students to be present at class, which might cause some troubles to their classmates. After a two year experience in the development of a continuous assessment in Statistics subjects in Social Science degrees, we think that individual and periodical tasks are the best way to assess results. These tasks or examinations must be done in classroom during regular lessons, so we need an efficient system to put together different and personal questions in order to prevent students from cheating. In this paper we provide an efficient and effective way to elaborate random examination papers by using Sweave, a tool that generates data, graphics and statistical calculus from the software R and shows results in PDF documents created by Latex. In this way, we will be able to design an exam template which could be compiled in order to generate as many PDF documents as it is required, and at the same time, solutions are provided to easily correct them.

Flexible Framework for Real-Time Embedded Systems Based on Mobile Cloud Computing Paradigm

The development of applications as well as the services for mobile systems faces a varied range of devices with very heterogeneous capabilities whose response times are difficult to predict. The research described in this work aims to respond to this issue by developing a computational model that formalizes the problem and that defines adjusting computing methods. The described proposal combines imprecise computing strategies with cloud computing paradigms in order to provide flexible implementation frameworks for embedded or mobile devices. As a result, the imprecise computation scheduling method on the workload of the embedded system is the solution to move computing to the cloud according to the priority and response time of the tasks to be executed and hereby be able to meet productivity and quality of desired services. A technique to estimate network delays and to schedule more accurately tasks is illustrated in this paper. An application example in which this technique is experimented in running contexts with heterogeneous work loading for checking the validity of the proposed model is described.