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The application of different multivariate statistical approaches for the interpretation of a complex data matrix obtained during the period 2004-2005 from Uluabat Lake surface water is presented in this study. The dataset consists of the analytical results of a 1 year-survey conducted in 12 sampling stations in the Lake. Twelve parameters (T, pH, DO, [Formula: see text], NH(4)-N, NO(2)-N, NO(3)-N, [Formula: see text], BOD, COD, TC, FC) were monitored in the sampling sites on a monthly basis (except December 2004, January and February 2005, a total of 1,296 observations). The dataset was treated using cluster analysis, principle component analysis and factor analysis on principle components. Cluster analysis revealed two different groups of similarities between the sampling sites, reflecting different physicochemical properties and pollution levels in the studied water system. Three latent factors were identified as responsible for the data structure, explaining 77.35% of total variance in the dataset. The first factor called the microbiological factor explained 32.34% of the total variance. The second factor named the organic-nutrient factors explained 25.46% and the third factor called physicochemical factors explained 19.54% of the variances, respectively.  相似文献   
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This article presents a new thermoelectric generator power analysis system (TEG-PAS) for the examination of all parameters of the thermoelectric generators (TEGs) operated by geothermal or any liquid heat. As a sample application, the developed TEG-PAS has been tried on a TEG of 100 W. During electrical energy generation, the values of the electrical, the thermo-electrical and the thermal variables of the TEG have been transmitted to the TEG-PAS by the employed sensors. Thus, the using of several devices simultaneously has been eliminated while the power performance analyses are being carried out.  相似文献   
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