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This paper proposes a methodology for concurrently optimizing station locations and the rail transit alignment connecting those stations, by accommodating multiple system objectives, satisfying various design constraints, and integrating the analysis models with a geographical information system database.
This paper proposes a methodology for concurrently optimizing station locations and the rail transit alignment connecting these stations, by accommodating multiple system objectives, formulating various design constraints, and integrating the analysis models with a geographical information system (GIS) database.
Integrating the analysis of the cistrome of a transcription factor by ChIP-Seq with the study of its transcriptional output by microarray or RNA-Seq analysis is a powerful approach to elucidate the genomic functions of a transcription factor.
Integrating the analysis of physical and symbolic space, the toponymic-material approach provides a valuable perspective on the past and present of place on the local level and beyond.
Integrating the analysis of high-throughput SNP data with knowledge-based SNP functional annotation offers a promising way to reversely engineer the underlying genetic networks for complex human diseases.
Interestingly, integrating the analysis of the miRNAs with cytology offered a higher sensitivity than did any single approach used alone (71.8% vs. 61.5%; 71.8% vs. 35.9%, all P < 0.05), while having 93.0% specificity (Figure 3). Figure 3 Comparison of miRNA biomarkers and sputum cytology for lung cancer diagnosis in 39 patients diagnosed with stage I NSCLC and 42 cancer-free individuals.
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The approach integrates the analysis of the clustering mechanism into the MAC layer model.
In contrast to existing approaches, our approach integrates the analysis of user management data as well as contextual data.
Finally the paper tries to integrate the analysis based on macroeconomic variables with the approach based on risky market instruments.
Firstly, they allow us to seamlessly integrate the analysis during subsequent software lifecycle stages in critical scenarios.
A multi-objective stochastic optimization method is used to integrate the analysis so that the overall process economic and environmental footprint is optimized.
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