Jaypee Institute of Information Technology

About: Jaypee Institute of Information Technology is a education organization based out in Noida, Uttar Pradesh, India. It is known for research contribution in the topics: Cluster analysis & Wireless sensor network. The organization has 2136 authors who have published 3435 publications receiving 31458 citations. The organization is also known as: JIIT Noida.

Realization of Novel Cascadable Current-Mode All-pass Sections

Abstract: This paper introduces four new resistorless circuits of first-order current-mode all-pass filter (CMAPF) based on dual-X current conveyor transconductance amplifier (DXCCTA). All the four circuits use a single DXCCTA and a capacitor for their realization. The main features of the proposed CMAPFs are: use of minimum active and passive components, resistorless realization, electronically adjustable pole frequency, easily cascadable, good sensitivity performance with respect to active and passive elements, low total harmonic distortion of output current (0.74%) and good operating frequency range (39.2 MHz). The non-ideal analysis of the proposed circuits has also been explored. Moreover, two applications of the proposed first-order CMAPF in terms of second order CMAPF and current-mode quadrature oscillator are also presented. HSPICE simulations have been carried out with 0.18 μm CMOS process parameters to validate the proposed circuits.

A Blockchain-based Framework for Drone-Mounted Base Stations in Tactile Internet Environment

Abstract: 5G, blockchain, and drones are potentially revolutionizing future technologies. 5G promises to provide a tactile internet environment to the users. Tactile internet is characterized by ultra-low latency, with high reliability, security, and availability. Few attempts have been made in academia and industry to use drones-mounted small cell base stations. Such flying base stations can be used in disaster areas, emergencies, or in rural areas. The major challenge in deploying such flying base stations is data security. Drones being resource-constrained devices cannot be overloaded with heavy security algorithms. Moreover, the decision of user association, drone movement, and bandwidth allocation are major bottlenecks in deploying such networks. In this paper, we propose a blockchain-based security framework for drone mounted base stations in the tactile internet environment. Furthermore, a game-theoretic model is proposed as a smart contract to decide on the dynamic bandwidth allocation to different users based on bandwidth availability and cost. Numerical results show that the proposed model helps in better user experience in terms of bandwidth allocation in low network areas.

Applications of MFCC and Vector Quantization in speaker recognition

Abstract: In speaker recognition, most of the computation originates from the likelihood computations between feature vectors of the unknown speaker and the models in the database. In this paper, we concentrate on optimizing Mel Frequency Cepstral Coefficient (MFCC) for feature extraction and Vector Quantization (VQ) for feature modeling. We reduce the number of feature vectors by pre-quantizing the test sequence prior to matching, and number of speakers by ruling out unlikely speakers during recognition process. The two important parameters, Recognition rate and minimized Average Distance between the samples, depends on the codebook size and the number of cepstral coefficients. We find, that this approach yields significant performance when the changes are made in the number of mfcc's and the codebook size. Recognition rate is found to reach upto 89% and the distortion reduced upto 69%.

Proposed lead molecules against Hemagglutinin of avian influenza virus (H5N1).

Abstract: Human infection with avian influenza H5N1 is an emerging infectious disease characterized by respiratory symptoms and a high fatality rate Hemagglutinin and neuraminidase are the two surface proteins responsible for infection by influenza virus Till date, neuraminidase has been the major target for antiviral drugs In the present study we chose hemagglutinin protein as it mediates the binding of the virus to target cells through sialic acid residues on the host cell-surface Hemagglutinin of H5 avian influenza (PDB ID: 1JSN) was used as the receptor protein Ligands were generated by structure-based de novo approach and virtual screening of ZINC database A total of 11,104 conformers were generated and docked into the receptor binding site using 'High Throughput Virtual Screening' We proposed potential lead molecules against the receptor binding site of hemagglutinin based on the results obtained from in silico docking and hydrogen bond interaction between the ligand and the 1JSN protein molecule We found sialic acid derivative 1 to be the lead molecules amongst the ligands generated by structure based de novo approach However the molecules obtained from ZINC database were showing better docking scores as well as conserved hydrogen bond interactions Thus we proposed ZINC00487720 and ZINC00046810 as potential lead molecules that could be used as an inhibitor to the receptor binding site of hemagglutinin They could now be studied in vivo to validate the in silico results