Large batch size training of Neural Networks has been shown to incur accuracy loss when trained with the current methods. The precise underlying reasons for this are still not completely understood. Here, we study large batch size training through the lens of the Hessian operator and robust optimization. In particular, we perform a Hessian based study to analyze how the landscape of the loss fu...

Anaerobic treatment system was used for determination of colour removal under batch conditions. Azo-dye (Reactive Black 5, RB 5) with glucose as a carbon source was used as a synthetic wastewater. The decolourization process follows first order kinetics with respect to RB 5 azo-dye concentration in batch conditions. Decolourization rate constant (k1) value for dye concentration of 150 mgL was 0...

The issues of waste generation in batch process plants differ in many aspects from those in continuous plants. Despite the smaller-scale of processing, complexities from discontinuities and run-to-run variations make waste minimization in batch plants more challenging. In this paper, we introduce an integrated qualitative-quantitative methodology and decision support system, called Batch-ENVOPE...

This paper focuses on batch environment of an enterprise. We use various data sources such as dependency data, alert and ticket data, and run history data of the jobs in batch systems to build a model of batch operations. We enrich the model with various attributes derived by graph analysis of dependency data, time-series analysis of execution history of jobs, and text and statistical analysis ...

MOTIVATION Batch effects are due to probe-specific systematic variation between groups of samples (batches) resulting from experimental features that are not of biological interest. Principal component analysis (PCA) is commonly used as a visual tool to determine whether batch effects exist after applying a global normalization method. However, PCA yields linear combinations of the variables th...