Surgery scheduling based on large language models

Artificial Intelligence in Medicine, Год журнала: 2025, Номер 166, С. 103151 - 103151

Опубликована: Май 7, 2025

Язык: Английский

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Optimization of the flocculating capacity of a new micro-atomization extract from a Nostoc cyanobacterium species from the High Andes

Chemical Engineering Journal Advances, Год журнала: 2025, Номер unknown, С. 100777 - 100777

Опубликована: Май 1, 2025

Язык: Английский

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Forecasting of wastewater quality parameters in solar still desalination using R language

Urban Water Journal, Год журнала: 2025, Номер unknown, С. 1 - 12

Опубликована: Май 29, 2025

Язык: Английский

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Experimental and artificial intelligence optimization of paint wastewater (PWW) coagulation using novel Phaseolus vulgaris seed extract (PVSE)

Heliyon, Год журнала: 2024, Номер 10(14), С. e34229 - e34229

Опубликована: Июль 1, 2024

This study investigated the application of artificial intelligence algorithms (AIA) in coagulation treatment paint wastewater anchored by novel Phaseolus vulgaris seed extract (PVSE). Untreated discharge harms ecosystem, and therefore harmful industrial effluent, such as wastewater, must be brought to safe levels before being released into environment. In addition AIA, comprehensive characterization tests, kinetics, process optimization were also executed. Characterization results revealed that total solid PWW was above allowable standard, justifying need for effective particle decontamination. The XRD FTIR indicated PVSE structure is amorphous with abundant amine groups. Results analysis variance (ANOVA) obtained from modeling coagulation-flocculation a nonlinear quadratic system (F-value = 45.51) which mostly influenced coagulant dosage 222.48; standardized effect 14.85). Artificial neural network training effectively captured nature ANN (RMSE 0.00040194; R 0.98497), ANFIS 0.003961) algorithms. Regression coefficient highlighted suitability RSM (0.9662), (0.9739), (0.9718) forecasting process, while comparative statistical appraisal authenticated superiority model over models. kinetics experiment, used kinetic model, constant flocculation (Kf-value) all jar test batches strong association between Menkonu (Km) Kf values. Best removal efficiency 97.01 % using coupled genetic algorithm (ANN-GA) at 4 g/L, time 29 min temperature 25.1oC.

Язык: Английский

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High-efficiency removal of Rhodamine B using modified biochar from agricultural waste pine nut shell: investigation of kinetics, isotherms, and artificial neural network modeling

Biomass Conversion and Biorefinery, Год журнала: 2024, Номер unknown

Опубликована: Авг. 26, 2024

Язык: Английский

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