Performance of the Corresponding States Model of Dual-Reference on the Determination of Viscosity According to the Pressure of Hydrocarbon Mixtures in the Modeling Domain | Chapter 7 | New Ideas Concerning Science and Technology Vol. 10

 The model of K.A. Petersen [1] was used to predict viscosimetric activity in this study. The main idea behind this approach is to determine a fluid's viscosity using two models as a guide when going through a reduced pressure. The process is a two-reference corresponding state. This study demonstrates that the approach is based on the reference chosen, as well as any of the possible C10/C6H6 and C1/C10 references. For four different weight ratios, the findings were examined. It shows that adding a modified coefficient has no noticeable impact on the results when compared to the results without the adjustment factor, which appears to be the best option. In terms of the effect of the references chosen, the two couples tend to be a good match in general, but we should point out that this is not a prerequisite. The results are right in the case of mixtures containing at least one aromatic, particularly when comparing the ratio of adjustment and our ratio without adjustment to that of K. A. PETERSEN. The viscosity experimental findings are in good agreement with the measured values. We can predict that the implementation of the second body of reference (C10) from the model states corresponding to the authors' reference (C1) would result in a relative change.

Author (s) Details

Aziz Et-tahir
Materials, Energy, Acoustics Team (Meat), University Mohammed V of Rabat, Morocco.

View Book :- https://stm.bookpi.org/NICST-V10/article/view/589

Representation of the Predictive Analytics based Financial Assistance Model for Chronic Care Patients in India | Chapter 9 | Recent Developments in Engineering Research Vol. 3

 

Indian pharmaceutical industry (IPI) has traversed through many phases and it is in emerging phase
now (2019). IPI is looking for innovation, creativity, newness in patient connect to perform different
activities to achieve their stated goals. According to a recent World Health Organization report,
approximately 50% of the people with chronic illness do not take their medication as prescribed [1].
Medication Non-Adherence is a huge problem across the world. Pharmaceutical companies across
the world manufacture medicines with set of standard operating procedures, guidelines, quality
execution systems, inspection and verification from quality control and quality assurance activities.
The very intention of producing medicines is to sell them to the patients who are in need. The last
thing Pharmaceutical companies expects from Health Care Professional (HCP) is to write the
prescription and patient carrying it to Pharmacy to buy the medicine. Despite having the prescriptions
for medicines, there are plethora of reasons for Patient not to buy them. If the medicines are not taken
in case of the chronic illness, the patient’s quality of life degrades over a period of time, eventually
resulting to fatality. This paper made an attempt to introduce predictive analytics based financial
assistance model for chronic care patients in India.

Author (s) Details

Ramakumar Kommajosyula
Department of IT, VFSTR Deemed to be University, Guntur, Andhra Pradesh, India.

Prof. Nirupama Bhat
Department of Computer Science, VFSTR deemed to be University, Guntur, Andhra Pradesh, India.

Dr. P. L. S. Rao
India Research Lab, T J Watson Research Lab, New York, USA.

View Book :- http://bp.bookpi.org/index.php/bpi/catalog/book/261