An unconventional modelling methodology based on artificial neural networks is proposed to rapidly develop a model from data obtained during different batch experiments. The objective of the global predict time evolution concentrations all species present in reaction medium. For this, recurrent are elaborated estimate particular as function operating parameters and then assembled complex model....

The batch-to-batch model-based iterative optimal control strategy for batch processes is realized based on multilayer recurrent fuzzy neural network (MRFNN) and chaotic search. MRFNNs are used to model batch processes. Modeling and optimization problems are mainly solved by chaotic search. Due to model-plant mismatches and disturbances, the calculated optimal control profile may not be optimal ...

In a batch processing network, multiple jobs can be formed into a batch to be processed in a single service operation. The network is multiclass in that several job classes may be processed at a server. Jobs in different classes cannot be mixed into a single batch. A batch policy specifies which class of jobs is to be served next. Throughput of a batch processing network depends on the batch po...

Introduction: Note taking while attending a PPT requires highactivity of memory and writing process which ultimately leadsto what is called “death by power point” referring to boredomand fatigue. To overcome this we planned to evaluate the impactof utilisation of uncompleted handouts given prior to PPTpresentations.Methods: Final year MBBS students were divided in 2 batches,batch A and batch B....

The goal of metabolomics data pre-processing is to eliminate systematic variation, such that biologically-related metabolite signatures are detected by statistical pattern recognition. Although several methods have been developed to tackle the issue of batch-to-batch variation, each method has its advantages and disadvantages. In this study, we used a reference sample as a normalization standar...