Vignan University

About: Vignan University is a education organization based out in Guntur, Andhra Pradesh, India. It is known for research contribution in the topics: Control theory & CMOS. The organization has 1138 authors who have published 1381 publications receiving 7798 citations.

Variations in Denitrification and Ventilation Within the Arabian Sea Oxygen Minimum Zone During the Holocene

Abstract: The continental slope of India is exposed to an intense perennial oxygen minimum zone (OMZ) supporting pelagic denitrification. Sediments that are presently in contact with the lower boundary of the denitrification zone indicate marked changes in the intermediate and bottom waters ventilation of OMZ during the past 9,500 years. The δ15N of sediment suggests that the OMZ waters were less ventilated during the early Holocene (between 9.5 and 8.5 ka BP) resulting in intensified denitrifying conditions with an average δ15N value of 7.8‰, while at the same time stable Mo isotope composition (average δ98Mo of -0.02‰) indicates that the bottom waters that were in contact with the sediments were better oxygenated. By the mid-Holocene OMZ became more oxygenated suppressing denitrification (average δ15N of 6.2‰), while bottom waters gradually became less oxygenated (average δ98Mo of 1.7‰). The mid-Holocene reduction in denitrification coincided with a global decrease in atmospheric N2O as inferred from ice core records, which is consistent with a decreased contribution from the Arabian Sea. Since ~5.5 ka BP OMZ waters have again been undergoing progressive deoxygenation accompanied by increasing denitrification.

Optimal Power Flow by Newton Method for Reduction of Operating Cost with SVC Models

Abstract: The optimal power flow is a power flow problem in which certain variables are adjusted to minimize an objective function such as cost of the active power generation or the losses,while satisfying physical operating limits on various controls, dependent variables and function of control variables. Current interest in OPF covers around its ability to solve for the optimal solution that takes account of security of the system. Practical solutions for OPF problems with separable objective functions have been obtained with special linear programming methods,but the classical OPF has defined practical solutions, the Newton approach is a flexible formulation that can be used to develop different OPF algorithms suited to the requirements of different applications. In other words, the optimal power problem seeks to find an optimal profile of active and reactive power generations along with voltage magnitudes in such a manner as to minimize the total operating costs of a thermal electric power system, while satisfying network security constraints. The OPF method is based on load flow solution by the Newton’s method, a first order gradient adjustment algorithm for minimizing the objective function and use of penalty functions to account for inequality constraints on dependent variables.

Data-driven modelling and prediction of COVID-19 infection in India and correlation analysis of the virus transmission with socio-economic factors.

Abstract: Aims The current study attempts to model the COVID-19 outbreak in India, USA, China, Japan, Italy, Iran, Canada and Germany. The interactions of coronavirus transmission with socio-economic factors in India using the multivariate approach were also investigated. Methods Actual cumulative infected population data from 15 February to May 15, 2020 was used for determination of parameters of a nested exponential statistical model, which were further employed for the prediction of infection. Correlation and Principal component analysis provided the relationships of coronavirus spread with socio-economic factors of different states of India using the Rstudio software. Results Cumulative infection and spreadability rate predicted by the model was in good agreement with the actual observed data for all countries (R2 = 0.985121 to 0.999635, and MD = 1.2–7.76%) except Iran (R2 = 0.996316, and MD = 18.38%). Currently, the infection rate in India follows an upward trajectory, while other countries show a downward trend. The model claims that India is likely to witness an increased spreading rate of COVID-19 in June and July. Moreover, the flattening of the cumulative infected population is expected to be obtained in October infecting more than 12 lakhs people. Indian states with higher population were more susceptible to virus infection. Conclusions A long-term prediction of cumulative cases, spreadability rate, pandemic peak of COVID-19 was made for India. Prediction provided by the model considering most recent data is useful for making appropriate interventions to deal with the rapidly emerging pandemic.