Response surface methodology and machine learning optimisations comparisons of recycled AA6061-BC-ZrO hybrid metal matrix composites via hot forging forming process.

The optimal conditions of applied factors to reuse Aluminium AA6061 scraps are (450, 500, and 550) ⁰C preheating temperature, (1-15) % Boron Carbide (BC), and Zirconium (ZrO) hybrid reinforced particles at 120 min forging time via Hot Forging (HF) process. The response surface methodology (RSM) and machine learning (ML) were established for the optimisations and comparisons towards materials strength structure. The Ultimate Tensile Strength (UTS) strength and Microhardness (MH) were significantly increased by increasing the processed temperature and reinforced particles because of the material dispersion strengthening.

Validity of zinc oxide nanoparticles biosynthesized in food wastes extract in treating real samples of printing ink wastewater; prediction models using feed-forward neural network (FFNN).

In the present study, biosynthesized ZnO nanoparticles in food wastewater extract (FWEZnO NPs) was used in the photocatalytic degradation of real samples of printing ink wastewater. FWEZnO NPs were prepared using green synthesis methods using a composite food waste sample (2 kg) consisted of rice 30%, bread 20 %, fruits 10 %, chicken 10 %, lamb 10%, and vegetable 20%. The photocatalysis process was optimized using response surface methodology (RSM) as a function of time (15-180 min), pH 2-10 and FWEZnO NP (20-120 mg/100 mL), while the print ink effluent after each treatment process was evaluated using UV-Vis-spectrophotometer.

Amazon Employees Resources Access Data Extraction via Clonal Selection Algorithm and Logic Mining Approach.

Amazon.com Inc. seeks alternative ways to improve manual transactions system of granting employees resources access in the field of data science.