AI Medical Compendium Journal:
Bioprocess and biosystems engineering

Showing 1 to 9 of 9 articles

Genetic algorithm-optimized artificial neural network for multi-objective optimization of biomass and exopolysaccharide production by Haloferax mediterranei.

Bioprocess and biosystems engineering
Microbial production of industrially important exopolysaccharide (EPS) from extremophiles has several advantages. In this study, key media components (i.e., sucrose, yeast extract, and urea) were optimized for biomass growth and extracellular EPS pro...

High-content imaging and deep learning-driven detection of infectious bacteria in wounds.

Bioprocess and biosystems engineering
Fast and accurate detection of infectious bacteria in wounds is crucial for effective clinical treatment. However, traditional methods take over 24 h to yield results, which is inadequate for urgent clinical needs. Here, we introduce a deep learning-...

Neuro-fuzzy modelling of a continuous stirred tank bioreactor with ceramic membrane technology for treating petroleum refinery effluent: a case study from Assam, India.

Bioprocess and biosystems engineering
A continuous stirred tank bioreactor (CSTB) with cell recycling combined with ceramic membrane technology and inoculated with Rhodococcus opacus PD630 was employed to treat petroleum refinery wastewater for simultaneous chemical oxygen demand (COD) r...

Design of experiment (DOE) applied to artificial neural network architecture enables rapid bioprocess improvement.

Bioprocess and biosystems engineering
Modern bioprocess development employs statistically optimized design of experiments (DOE) and regression modeling to find optimal bioprocess set points. Using modeling software, such as JMP Pro, it is possible to leverage artificial neural networks (...

Hybrid neural network modeling and particle swarm optimization for improved ethanol production from cashew apple juice.

Bioprocess and biosystems engineering
A hybrid neural model (HNM) and particle swarm optimization (PSO) was used to optimize ethanol production by a flocculating yeast, grown on cashew apple juice. HNM was obtained by combining artificial neural network (ANN), which predicted reaction sp...

Comparative efficacy of machine-learning models in prediction of reducing uncertainties in biosurfactant production.

Bioprocess and biosystems engineering
An accurate and reliable forecast of biosurfactant production with minimum error is useful in any bioprocess engineering. Bacterial isolate FKOD36 capable of producing biosurfactant was isolated in this study and pre-inoculums was prepared from the a...

Incorporation of negative rules and evolution of a fuzzy controller for yeast fermentation process.

Bioprocess and biosystems engineering
The control of bioprocesses can be very challenging due to the fact that these kinds of processes are highly affected by various sources of uncertainty like the intrinsic behavior of the used microorganisms. Due to the reason that these kinds of proc...

Fuzzy logic feedback control for fed-batch enzymatic hydrolysis of lignocellulosic biomass.

Bioprocess and biosystems engineering
A fuzzy logic feedback control system was developed for process monitoring and feeding control in fed-batch enzymatic hydrolysis of a lignocellulosic biomass, dilute acid-pretreated corn stover. Digested glucose from hydrolysis reaction was assigned ...

Artificial neural network associated to UV/Vis spectroscopy for monitoring bioreactions in biopharmaceutical processes.

Bioprocess and biosystems engineering
Currently, mammalian cells are the most utilized hosts for biopharmaceutical production. The culture media for these cell lines include commonly in their composition a pH indicator. Spectroscopic techniques are used for biopharmaceutical process moni...