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.

Effect of Crack Angle on Stress Shielding in Bone and Orthopedic Fixing Plate Implant: Design and Simulation

Abstract: In the present study, laminated composites of polymethyl methacrylate (PMMA)—titanium (Ti) with different ply orientation were designed and three different crack angles (20°, 40° and 50°) were considered in femur bone to investigate the effect of crack angle on the stress distribution in the bone. PMMA was selected as matrix and titanium was selected as fiber from 0.2 to 0.5 volume fraction (Vf). 3D model of bone implant assembly was designed by using computer-aided drafting (CAD) and simulation was carried out with the help of ANSYS Workbench® software. Laminated composites with different ply orientations with different volume fractions of fiber were analyzed, and optimum combination was abstracted with an objective to attain higher and uniform stress distribution throughout the bone. From the results, it is observed that the crack angle effects the stress distribution in the bone even though the same laminated composite is used as implant.

The Omic Insights on Unfolding Saga of COVID-19.

Abstract: The year 2019 has seen an emergence of the novel coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing coronavirus disease of 2019 (COVID-19). Since the onset of the pandemic, biological and interdisciplinary research is being carried out across the world at a rapid pace to beat the pandemic. There is an increased need to comprehensively understand various aspects of the virus from detection to treatment options including drugs and vaccines for effective global management of the disease. In this review, we summarize the salient findings pertaining to SARS-CoV-2 biology, including symptoms, hosts, epidemiology, SARS-CoV-2 genome, and its emerging variants, viral diagnostics, host-pathogen interactions, alternative antiviral strategies and application of machine learning heuristics and artificial intelligence for effective management of COVID-19 and future pandemics.

An Unsupervised Drift Detector for Online Imbalanced Evolving Streams

Abstract: Detecting concept drift from an imbalanced evolving stream is challenging task. At high degree of imbalance ratios, the poor or nil performance estimates of the learner from minority class tends to drift detection failures. To ameliorate this problem, we propose a new drift detection and adaption framework. Proposed drift detection mechanism is carried out in two phases includes unsupervised and supervised drift detection with queried labels. The adaption framework is based on the batch wise active learning. Comparative results on four synthetic and one real world balanced and imbalanced evolving streams with other prominent drift detection methods indicates that our approach is better in detecting the drift with low false positive rates.

Hybrid PSOGSA Method of Solving ORPD Problem with Voltage Stability Constraint

Abstract: This paper presents a new hybrid evolutionary based algorithm based on PSO and GSA for solving optimal reactive power dispatch problem in power system. The problem was designed as a Multi-Objective case with loss minimization and voltage stability as objectives. Generator terminal voltages, tap setting of transformers and reactive power generation of capacitor banks were taken as optimization variables. Modal analysis method is adopted to assess the voltage stability of system. The above presented problem was solved on basis of efficient and reliable technique which takes the advantages of both PSO and GSA. The proposed method has been tested on IEEE 30 bus system where obtained results were found satisfactorily to a large extent that of reported earlier.