Optimal random sampling designs in random field sampling

A Horvitz-Thompson predictor is proposed for spatial sampling when the characteristic of interest is modeled as a random field. Optimal sampling designs are deduced under this context. Fixed and variable sample size are considered

OPTIMAL RANDOM SAMPLING DESIGNS IN RANDOM FIELD SAMPLING

A Horvitz-Thompson predictor is proposed for spatial sampling when the characteristic of interest is modeled as a random field. Optimal sampling designs are deduced under this context. Fixed and variable sample size are considered.

Los significados de función y función derivada desarrollados por los estudiantes al estudiar la variación en el contexto de los problemas de ingeniería

Este es un reporte parcial de un proyecto diseñado para investigar el papel del contexto de la enseñanza en la formación y desarrollo de los significados de los objetos matemáticos que construyen los estudiantes. En este proyecto específicamente se está investigando sobre los significados de los objetos matemáticos función y función derivada que adquieren los estudiantes de ingeniería al estudiar la variación en el contexto de los problemas de optimización y se desarrolla con alumnos de los cursos de Cálculo Diferencial de la carrera de ingeniería civil de una universidad del norte de la República Mexicana. En este trabajo se reporta el proceso de diseño de las actividades que se utilizaron en la investigación y un avance de los resultados obtenidos

MISIÓN, VISIÓN Y VALORES DE LA FACULTAD DE ODONTOLOGÍA UAEM

El inicio de cursos para los estudiantes de nuevo ingreso de la Facultad de Odontología provoca inquietud y ansiedad por conocer los espacios físicos como las aulas, laboratorios, clínicas, centro de investigación, áreas de esparcimiento y cafetería. Algo de misterio por conocer nuevos compañeros, maestros, personal administrativo. Pero sobre todo por ser parte de una comunidad que a lo largo de su estancia en la universidad, nos lleve a considerarse como “universitarios todos”, como se manifiesta constantemente en todas las ceremonias

SMS Advertising in India: Is TAM a Robust Model for Explaining Intention?

This study examined mobile users’ intentions to receive SMS advertising in India using Technology Acceptance Model (TAM) as research framework. 242 respondents completed a structured questionnaire; measuring their responses for the TAM’s five constructs viz. perceived utility, perceived ease of use, perceived trust, attitude and intention. Using Structural Equation Modeling (SEM) both measurement model and structural model testing was done to analyze the data. Findings indicated that specified TAM model contributed to 81.8% of variance in the intention to receive SMS advertising and was a valid model in explaining the intention to receive SMS advertising. Study further indicated that perceived utility was much better predictor of attitude towards SMS advertising than perceived ease of use and perceived trust. Study suggested marketers that to increase acceptance of SMS advertising they should focus more on increasing utility of SMS ads, so that users would develop positive attitudes towards SMS advertising

Bridging the Gap Between the Least and the Most Influential Twitter Users

Social networks play an increasingly important role in shaping the behaviour of users of the Web. Conceivably Twitter stands out from the others, not only for the platform's simplicity but also for the great influence that the messages sent over the network can have. The impact of such messages determines the influence of a Twitter user and is what tools such as Klout, PeerIndex or TwitterGrader aim to calculate. Reducing all the factors that make a person influential into a single number is not an easy task, and the effort involved could become useless if the Twitter users do not know how to improve it. In this paper we identify what specific actions should be carried out for a Twitterer to increase their influence in each of above-mentioned tools applying, for this purpose, data mining techniques based on classification and regression algorithms to the information collected from a set of Twitter users.This work has been partially founded by the European Commission Project ”SiSOB: An Observatorium for Science in Society based in Social Models” (http://sisob.lcc.uma.es) (Contract no.: FP7 266588), ”Sistemas Inalámbricos de Gestión de Información Crítica” (with code number TIN2011-23795 and granted by the MEC, Spain) and ”3DTUTOR: Sistema Interoperable de Asistencia y Tutoría Virtual e Inteligente 3D” (with code number IPT-2011-0889- 900000 and granted by the MINECO, Spain