ACO-based feature selection and neural network modeling for accurate gamma-radiation based pipeline monitoring in the oil industry.

This work presents a novel technique to improve oil pipeline monitoring capabilities, a vital activity in the oil and gas sector. Using Monte Carlo simulations, the work meticulously records data from a pipeline testing environment with various petroleum products and volume ratios. We apply the presented technique to mix four petroleum products-ethylene glycol, gasoline, crude oil, and gasoil-in different volumetric fractions to precisely determine their volume ratios.

Measuring volume fractions of a three-phase flow without separation utilizing an approach based on artificial intelligence and capacitive sensors.

Many different kind of fluids in a wide variety of industries exist, such as two-phase and three-phase. Various combinations of them can be expected and gas-oil-water is one of the most common flows. Measuring the volume fraction of phases without separation is vital in many aspects, one of which is financial issues.

Contribution of neural networks in the diagnosis and treatment of cardiac arrhythmia.

Arrhythmia is a dangerous disease in which the heart rhythm varies and it may be very fast or very slow. Rapid heartbeats can lead to shortness of breath, chest pain, and sudden weakness, whereas slow heartbeats can lead to dizziness, problems with concentration, and constant stress. Finding an effective treatment for arrhythmia has become a very important endeavor for researchers and clinicians.

Qualitative theoretical modeling to study the possibility of detecting multi-virus in blood flow using Nano-quartz crystal microbalance.

Methods for testing the presence of a virus in the blood are of interest to researchers and doctors because they determine how rapidly a virus is detected. In general, virus detection is a major scientific problem due to the serious effects of viruses on the human body. At present, only one virus can be detected in a single test.

Validation of Nanoparticle Response to the Sound Pressure Effect during the Drug-Delivery Process.

Intravenous delivery is the fastest conventional method of delivering drugs to their targets in seconds, whereas intramuscular and subcutaneous injections provide a slower continuous delivery of drugs. In recent years, nanoparticle-based drug-delivery systems have gained considerable attention. During the progression of nanoparticles into the blood, the sound waves generated by the particles create acoustic pressure that affects the movement of nanoparticles.