Multivariate Analyses to Improve Understanding of NAPL Pollutant Sources

Inverse Identification of Multiple Pollutant Sources

In case of an accidental release of indoor airborne pollutants, it is critical to know information of the pollutant sources. Current inverse modeling concentrates on identifying a single pollutant source or multiple pollutant sources in simplified puff or constant release forms. This investigation proposes an inverse model to precisely identify the multiple pollutant source number, locations an...

Eigenimages and multivariate analyses

P-93: Understanding The Different KindsFactors of Infertility in Men and Womenin order to Improve The Treatment of Infertility

Background: Infertility in couples who fail to get pregnant after one year of sexual intercourse without contraception is called. approximately 40% of infertility problems in men, 40% women and 10% of androgynous, 10% is unknown. Therefore, the awareness of the different kinds of infertility treatment is effective. Materials and Methods: Study overview, the present Internet search at timescales...

Multivariate analyses in microbial ecology

Environmental microbiology is undergoing a dramatic revolution due to the increasing accumulation of biological information and contextual environmental parameters. This will not only enable a better identification of diversity patterns, but will also shed more light on the associated environmental conditions, spatial locations, and seasonal fluctuations, which could explain such patterns. Comp...

Multivariate Statistical Analyses and Applications

I. Introduction: Multivariate Statistical Analyses comprise a number of statistical methods/tools that may be applied to several fields of empirical investigations. Most of these methods have three characteristics in common: (i) they presume availability of data set, say Z(nxk) (in n observations and k variables; k ≥ 2, n>k), collected from the field (observationally or experimentally); (ii) th...