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The aim with this study was, in contrast, to perform and evaluate a landscape-based monitoring method for butterflies in diverse habitats and more specifically to: (i) evaluate the impact of environmental variables on butterfly abundance; (ii) compare the distribution of butterflies in different habitats; and (iii) analyse data from the study with the aim of improving the method.
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The comparative score values against different variables of salience, reliability and legitimacy for Community based monitoring (CM) and Remote Sensing + Community based Monitoring RSS + CM) methods are presented in Table 4.
A nonlinear kernel Gaussian mixture model (NKGMM) based inferential monitoring method is proposed in this article for chemical process fault detection and diagnosis.
This method is seen as a great enhancement of existing satellite based air temperature monitoring methods especially for urban applications.
In this paper, we present a parity relation based integrated method for battery SOH monitoring.
Currently, most piezoelectric transducers based non-destructive monitoring method lays basis on wave-based method.
A monitoring method based on a sensor network and ANFIS as estimation method for non-linear systems is presented.
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