Mirian Fernandes Carvalho Araújo

Multiattribute Response of Maize Genotypes Tested in Different Coastal Regions of Brazil

This work applies the three mode principal components analysis to analyze simultaneously the multiple attributes; to fit of models with additive main effects and multiplicative interaction effects (AMMI models) and the regressions models on sites (SREG models); to evaluate, respectively, the multivariate response of the genotype × environment interaction and the mean response of 36 genotypes of corn tested in 4 locations in Brazil. The results were presented by joint plots to identify the best genotypes for their adaptability and performance in the set of attributes.

Quality monitoring of network traffic forecasts using statistical process control

The literature of network traffic analysis has investigated different forecasting methods applied to traffic engineering in computer and communication networks. Several sophisticated models have been proposed, evaluated and compared, showing very good results in many empirical or controlled studies. In general, network traffic forecasting can be conducted in an offline or online manner. An important aspect in both approaches is the quality control of the obtained predictions. This paper is focused on the quality control of online network traffic forecasts. We present a statistical process control based approach in order to keep in control online predictions of different network traffics. Our proposal is based on a combination of CUSUM and Shewhart control charts. We evaluate the proposed method using four different traffic samples collected from real LAN, MAN e WAN network environments.

Gráficos biplot e joint plot para o estudo da interação tripla

The present research had the following objectives: to propose a systematics for the study and the interpretation of the phenotypic stability and adaptability, through Tucker3 models; assess the use of the joint plot; comparing the results obtained by tucker3 model with the results obtained by biplot analysis and AMMI models. The data used are related to the experiments with 13 genotypes of beans that had been lead in 9 distinct experiments. The results indicated that the joint plot graph facilitates the understanding of triple interaction and bring to the researcher more real information about triple interaction, than AMMI modeling of two entries. The genotype 6 was the one which least contributed for the triple interaction and genotypes 12, 9 and 5 were those e which had contributed more for the interaction.