Preferred Language
Articles
/
jmracpc-250
GEOMETRY OPTIMIZATION OF COUPLING ALLIN -METFORMIN USING DFT/B3LYP MOLECULAR MODELLING TECHNIQUE: GEOMETRY OPTIMIZATION OF COUPLING ALLIN -METFORMIN USING DFT/B3LYP MOLECULAR MODELLING TECHNIQUE
...Show More Authors

This researchpaper includes the incorporation of Alliin at various energy levels and angles 

With Metformin using Gaussian 09 and Gaussian view 06. Two computers were used in this work. Samples were generated to draw, integrate, simulate and measure the value of the potential energy surface by means of which the lowest energy value was (-1227.408au). The best correlation compound was achieved between Alliin and Metformin through the low energy values where the best place for metformin to bind was through (CH2-).  This is considered to be very useful for the industrial application of drugs.

This level of calculation was used for physical and quantum properties such as total energy, HOMO and LUMO orbitals energies, and power gap. Besides, the calculation of FT-IR spectra in the range 400-4000 cm-1 was calculated in addition to the essential vibrational frequencies and the intensity of the vibrational bands. Moreover, the chemical displacement of the 1H and 13C NMR of the compound in the ground state was studied.

View Publication Preview PDF
Quick Preview PDF
Publication Date
Tue Jun 24 2025
Journal Name
Baghdad Science Journal
Accelerating Face Mask Detection Training Model Based on Multi-GPUs and Multi-core CPU
...Show More Authors

Modern machine-learning applications require GPUs, and modern platforms can leverage numerous GPUs on one or more machines to increase performance. Contemporary deep-learning models are too huge for CPU or GPU training. Training these models with many GPUs without performance degradation is necessary to train them rapidly and maximize GPU consumption. Thus, training deep convolutional neural networks (DCNN) with multiple GPUs has become necessary for improving training. Therefore, we presented a parallel design and development of an efficient model for enhancing face mask CNN performance and improving resource efficiency. This DCNN model is a parallel training system over multiple GPUs, a multi-core CPU, and a multi-process GPU platform wit

... Show More
View Publication Preview PDF
Scopus Crossref