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The dynamic system analysis performed by using parametric identification procedures and non-linear fit routines has demonstrated that data obtained under a wide variety of experimental conditions can be interpreted by taking into account the participation of various Sn II Sn(IV -containing surface specIV -containing
Hence, this work has demonstrated that data fusion strategy used to combine e-Nose and e-Tongue signals led to a system of complementary and comprehensive information of the fruit juices which outperformed the performance of each instrument when applied separately.
Previous research has demonstrated that data obtained using respondent-driven techniques yield representative samples of drug-users [ 16, 17].
While the current study did not address the issues of normalization, it has demonstrated that data from the two different technologies, if properly filtered, will yield comparable results.
It has demonstrated that data from STEPS survey which were used to perform risk assessment at individual level could present results of the CVD risk at population levels.
A cross-platform comparison between cDNA and oligonucleotide microarrays has demonstrated that data generated by different platforms may have poor correlation [ 10].
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Empirical studies have demonstrated that data representations obtained from stacking up non-linear feature extractors (as in Deep Learning) often yield better machine learning results, e.g., improved classification modeling [9], better quality of generated samples by generative probabilistic models [10], and the invariant property of data representations [11].
A recent data quality inspection report has demonstrated that the data are of decent quality, especially in the eastern regions of China, with reporting completeness of 99.84% and accuracy of the information reported of 92.76% [ 17].
While the WHO recommends considering the inclusion of disease register data in the burden of disease studies, previous experience with RHD registers in South Africa has demonstrated that such data collection is unreliable and not representative of the general population.
12 Previous work has demonstrated that call data are sensitive to increases in community transmission of a range of pathogens, including influenza.
This study has demonstrated that EMS data can be successfully linked to other health related datasets using deterministic and probabilistic matching with varying levels of success.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com