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Modeling and optimization of pectin extraction from banana peel using artificial neural networks (ANNs) and response surface methodology (RSM)
In the present study, the extraction of pectin from banana peel ( Musa sp.) was optimized using artificial neural network and response surface...
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Design artificial intelligence-based optimization and swelling behavior of novel crosslinked polymeric network hydrogels based on acrylamide-2-hydroxyethyl methacrylate and acrylamide-N-isopropylacrylamide
With the development of three-dimensional crosslinked hydrogel networks, various applications with excellent hydrophilicity and swelling ability have...
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Neural virtual sensor for determination of high-density polyethylene melt flow index and solids concentration in a loop slurry reactor
The high-density polyethylene (HDPE) production requires a precise control of process variables which are controlled by various instruments...
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Improved laccase production from Pleurotus floridanus using deoiled microalgal biomass: statistical and hybrid swarm-based neural networks modeling approach
Fungal laccases are versatile biocatalyst and occupy a prominent place in various industrial applications due to its broad substrate specificity. The...
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Optimal Enzyme-Assisted Extraction of Phenolics from Leaves of Pongamia pinnata via Response Surface Methodology and Artificial Neural Networking
This research work seeks to evaluate the impact of selected enzyme complexes on the optimised release of phenolics from leaves of Pongamia pinnata ....
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Insights into brewed tea waste as a green and low-priced adsorbent for solid-phase extraction of Cd(II) ions: isotherm, kinetic, and artificial neural network approach
In the present research, brewed tea waste (BTW) was utilized as a green, low-priced, and abundant adsorbent for separation/preconcentration of Cd(II)...
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Feature extraction for artificial intelligence enabled food supply chain failure mode prediction
The Farm to Fork Strategy of the European Commission is a contingency plan aimed at always ensuring a sufficient and varied supply of safe,...
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Forecasting the thermal conductivity of a nanofluid using artificial neural networks
In this study, the influence of incorporating MWCNT on the thermal conductivity of paraffin was evaluated numerically. Input variables including mass...
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Artificial neural network for cytocompatibility and antibacterial enhancement induced by femtosecond laser micro/nano structures
The failure of orthopedic and dental implants is mainly caused by biomaterial-associated infections and poor osseointegration. Surface modification...
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The influence of the functionalization of polystyrene and graphene oxide composites on the flammability characteristics: modeling with artificial intelligence tools
This paper tackles the influence of the functionalization of polystyrene and graphene oxide (GO) composites on the flammability characteristics. A...
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Monitoring and warning for ammonia nitrogen pollution of urban river based on neural network algorithms
Ammonia nitrogen (AN) pollution frequently occurs in urban rivers with the continuous acceleration of industrialization. Monitoring AN pollution...
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Artificial neural networks for quantitative online NMR spectroscopy
Industry 4.0 is all about interconnectivity, sensor-enhanced process control, and data-driven systems. Process analytical technology (PAT) such as...
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Rapid quantitative elemental analysis using artificial neural network for case study of Isfahan Miniature Neutron Source Reactor
In this study, new method for NAA purposes at 30 kW Isfahan MNSR is suggested. An algorithm based on ANN is proposed to quantitatively predict the...
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ABT-MPNN: an atom-bond transformer-based message-passing neural network for molecular property prediction
Graph convolutional neural networks (GCNs) have been repeatedly shown to have robust capacities for modeling graph data such as small molecules....
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Artificial Neural Network-Based Study Predicts GS-441524 as a Potential Inhibitor of SARS-CoV-2 Activator Protein Furin: a Polypharmacology Approach
Furin, a pro-protein convertase, plays a significant role as a biological scissor in bacterial, viral, and even mammalian substrates which in turn...
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Artificial Neural Network Modeling of Thermo-catalytic Methane Decomposition for Hydrogen Production
Thermo-catalytic methane decomposition is a prospective route for producing CO x free hydrogen. In this study, Bayesian regularization and...
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Convolution Neural Network Approaches for Cancer Cell Image Classification
Recently, research incorporating the benefits of deep learning in the application of cancer cell classification and analysis has been actively...
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Prospects of Applying the Neural-Network Modeling for Estimating the Structure and Properties of Polymer-Composite Materials with Hybrid Matrices
AbstractArtificial neural networks are used in various fields, ranging from economics and sociological research to medicine and robotics. Neural...
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Computation of photovoltaic and stability properties of hybrid organic–inorganic perovskites via convolutional neural networks
Hybrid organic–inorganic perovskites (HOIPs) have gained considerable interest due to their potential applications as photovoltaic materials....
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Modeling, Sensitivity Analysis, and Optimization of the Methanol-to-Gasoline Process using Artificial Intelligence Methods
AbstractIn this study, the gasoline yield in the methanol-to-gasoline (MTG) process was modeled using artificial neural network (ANN) and...
