Dynamo is a full-stack software solution for scientific data management. Dynamo's architecture modular, extensible, and customizable, making the suitable managing in wide range of installation scales, from few terabytes stored at single location to hundreds petabytes distributed across worldwide computing grid. This article documents core system design describes applications that implement vari...

Abstract A significant advancement that occurs during the data cleaning stage is estimating missing data. Studies have shown improper handling leads to inaccurate analysis. Furthermore, most studies indicate occurrence of irrespective correlation between attributes. However, an adaptive search procedure helps determine estimates when correlations attributes are considered in process. Firefly Al...

Graph neural networks (GNNs) are popular weapons for modeling relational data. Existing GNNs not specified attribute-incomplete graphs, making missing attribute imputation a burning issue. Until recently, many works notice that coupled with spectral concentration, which means the spectrum obtained by concentrates on local part in domain, e.g., low-frequency due to oversmoothing As consequence, ...

In past years, cloud storage systems saw an enormous rise in usage. However, despite their popularity and importance as underlying infrastructure for more complex services, today's do not account compliance with regulatory, organizational, or contractual data handling requirements by design. Since legislation increasingly responds to rising protection privacy concerns, complying becomes a cruci...