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Filtration

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Modelling of transmembrane pressure using slot/pore blocking model, response surface and artificial intelligence approach.

Chemosphere
This work investigates the application of empirical, statistical and machine learning methods to appraise the prediction of transmembrane pressure (TMP) by oscillating slotted pore membrane for the treatment of two kinds of deformable oil drops. Here...

Improvement of DBR routing protocol in underwater wireless sensor networks using fuzzy logic and bloom filter.

PloS one
Routing protocols for underwater wireless sensor networks (UWSN) and underwater Internet of Things (IoT_UWSN) networks have expanded significantly. DBR routing protocol is one of the most critical routing protocols in UWSNs. In this routing protocol,...

Optimization of dewatering process of concentrate pressure filtering by support vector regression.

Scientific reports
This work studies the mechanism and optimization methods of the filter press dehydration process to better improve the efficiency of the concentrate filter press dehydration operation. Machine learning (ML) models of radial basis function (RBF)-OLS, ...

Modelling and optimization study to improve the filtration performance of fibrous filter.

Chemosphere
Fibrous filter made up of non-woven material was utilized in many industrial applications for increasing the collection efficiency and the quality factor. But there exists a competing effect among the fibre diameter, filtration efficiency, pressure d...

A Denoising and Fourier Transformation-Based Spectrograms in ECG Classification Using Convolutional Neural Network.

Sensors (Basel, Switzerland)
The non-invasive electrocardiogram (ECG) signals are useful in heart condition assessment and are found helpful in diagnosing cardiac diseases. However, traditional ways, i.e., a medical consultation required effort, knowledge, and time to interpret ...

The intelligent prediction of membrane fouling during membrane filtration by mathematical models and artificial intelligence models.

Chemosphere
Recently, membrane separation technology has been widely utilized in filtration process intensification due to its efficient performance and unique advantages, but membrane fouling limits its development and application. Therefore, the research on me...

Applications of artificial intelligence (AI) in drinking water treatment processes: Possibilities.

Chemosphere
In water treatment processes (WTPs), artificial intelligence (AI) based techniques, particularly machine learning (ML) models have been increasingly applied in decision-making activities, process control and optimization, and cost management. At leas...

Loss of micropollutants on syringe filters during sample filtration: Machine learning approach for selecting appropriate filters.

Chemosphere
Prefiltration before chromatographic analysis is critical in the monitoring of environmental micropollutants (MPs). However, in an aqueous matrix, such monitoring often leads to out-of-specification results owing to the loss of MPs on syringe filters...

Spectral fusion-based machine learning classifiers for discriminating membrane breakage in multiple scenarios.

Water research
Membrane breakage can lead to filtration failure, which allows harmful substances to enter the effluent, posing potential hazards to human health and the environment. This study is an innovative combination of fluorescence and ultraviolet-visible (UV...

A machine learning based framework to tailor properties of nanofiltration and reverse osmosis membranes for targeted removal of organic micropollutants.

Water research
Nanofiltration (NF) and reverse osmosis (RO) membranes play an increasingly important role in the removal of organic micropollutants (OMPs), which puts higher demands on the customization of membranes suitable for OMPs removal based on the rejection ...