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: Computer science & Control theory. The organization has 1138 authors who have published 1381 publications receiving 7798 citations.

An Introduction to Neural Networks in SCMA

Abstract: Sparse Code Multiple Access (SCMA) has proved to be a fascinating research in order to curtail the complications faced by the wireless communication networks. SCMA being a Non-Orthogonal Multiple Access technique evinces to be an outstanding candidate, to cater the complications faced by 5G communication networks to improve the bit error rate and reduce the complexity of decoding the transmitted signal from received signal. This paper explains the concept of SCMA by explaining the basic structure of encoder, decoder and codebook design with the help of neural networks. It explains the concept of reducing the complexity of the traditional decoder of the SCMA by implementing Neural Networks. Further sections explain the use of Convolutional Neural Networks for blind decoding, that outperforms the complexity of decoding carried by conventional SCMA using Message Passing Algorithm. This further explains the use of Deep Neural Networks for designing the codebook and decoding it, by adopting an autoencoder structure.

Porous Hybrid Materials with POSS

Abstract: Massive applications and advantages of porous hybrid materials based on polyhedral oligomeric silsesquioxane (POSS) have generated enormous research interest in the development of porous POSS hybrid materials in both the industries and the academics. POSS, a well-known nanoporous inorganic building block materials with the formula (RSiO1.5)n, (n ≥ 6) including definite cage-shaped three-dimensional structures is surrounded by organic functional groups, which were utilized to produce porous hybrid materials with organic molecules via copolymerization, grafting, and blending and also with metals by coordination. This chapter reviews the properties and importance of porosity of POSS and POSS hybrid materials.

Real Time Face Authentication Using Convolutional Neural Network

Abstract: Face analysis is the recent and challenging technology for authentication and recognition. Researchers have been developing new techniques for face analysis for the past decades. This paper deals with the real time face authentication using Deep learning based Convolutional Neural Network (CNN) for high True Acceptance Rate (TAR). Face authentication is done by training the images of the persons to be claimed, thus it provides the confidence value with test images; if the score is above 0.7 then the person is authenticated. This paper has employed Constrained Local Model (CLM) for 3D alignment of Face Recognition Grand Challenge (FRGC) dataset thus achieving highest TAR of 91.5%.

Huntington's chorea, a neurological disorder of all ages - Bioinformatics approach for its precise diagnosis.

Abstract: Background: The disease that obstructs social movements of people is Huntington’s disease (HD). Hence, the expedition of its molecular aspects and bioinformatics tools relating to precise confirmation of the disease is warranted. Due to social stigma, the care and attention to safeguard these patients had increased at community level. Objective: The objective of the study was to explore bioinformatics tools to trace the defects in Huntington’s gene and design its small-guided RNA (sgRNA). Methodology: The HTT gene sequence was retrieved, CRISPR sites were identified, and gRNA sequence was determined using the University of California Santa Cruz (UCSC) Genome Browser. HTT protein molecular structure elucidation was retrieved through PDB and Swiss Model. Ramachandran plot displayed the cluster of poly-Q at the Phi (−60–−36) and Psi (−60–−65) regions. The pattern of residues in the plot displayed that the HTT protein is alpha-helical predominant. Results: The CRISPR sites on HTT gene are viewed and sgRNA sequences are obtained through the UCSC Genome Browser. This sgRNA sequence along with Cas9 would be planned for genome editing in future experimental models. The Ramachandran plot for HTT protein derived through online Rampage revealed the recurrent appearance of polyglutamine (Q) at the Phi (−55–−65) and Psi (120–135) regions. Conclusion: Online bioinformatic tools such as UCSC Genome Browser, Swiss-Model, and Rampage help in exploring molecular basis of HD and disease-causing protein HTT, and the same invariably assists in creating awareness among health workers.