Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Department of Communication Engineering

Department of Information Security

School of Computer Science and Engineering

Vellore Campus

School of Electronics Engineering

Department of Sensor and Biomedical Technology

Electronics

Chennai Campus

Journal of Information and Knowledge Management

Preface

In this work, an ultra-wideband multiple-input multiple-output antenna on a low-cost frame retardant (Fr-4) substrate is proposed. A complex task in designing a MIMO antenna is accomplished by using the genetic algorithm. This paper develops an improved method of converting a novel compact two-element multi-band MIMO antenna into a UWB antenna using a genetic algorithm optimizer of HFSS. The length of a typical rectangular finger-like protrusion is optimized using a genetic optimizer to resonate with the proposed MIMO in UWB frequencies. To validate the outcomes of simulation, the proposed antenna model was developed on a flame retardant 4 substrate, a decent match between the measurement and simulation is observed. These designed antennas have advantages of low cost, ease of fabrication, low profile with compact design, and operating in UWB, which covers all major commercial bands. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

World University root node

Advances in Intelligent Systems and Computing

Genetic Algorithm-Based Optimization in the Improvement of Wideband Characteristics of MIMO Antenna

Digital communication has emerged as an important aspect in today’s world. Due to which we need to secure the data to a great extent otherwise there will be data loss. Various methods have been developing day by day to ensure data protection high level. This paper is based on the application of recurrence relation namely, Ackermann’s function, and using concept of Moore machine in Cryptography. Encryption and Decryption can be done by the aforesaid methods in order to pass the message from sender to receiver securely. © 2021, Springer Nature Singapore Pte Ltd.

Lecture Notes in Electrical Engineering

Application of Ackermann’s Recurrence Relation and Moore Machine on Cryptography

In this paper, an antenna design has been proposed for sub-6 GHZ fifth generation (5G) applications, which can cover several popular frequency bands of consumer interest that ranges from 0.5 to 7.1 GHz. Antenna design is based on modified meander line design, which is used for multiband generation. The proposed antenna design covers frequency bands that includes L1 GNSS, Wi-Fi 2.4 and 5 GHz, and LTE 41/42/43/46. The design is proposed in such a way that the frequency bands have good isolation and the good return loss is less than −10 dB. Antenna is designed on FR4 substrate with dielectric constant as 4.4 and substrate height of 1.57 mm. Furthermore, the single port antenna design is extended for two-port with reduced mutual coupling among the two antenna elements. © 2021, Springer Nature Singapore Pte Ltd.

Design of Dual-Port Multiband Antenna for Sub-6 GHz 5G Applications

AEU-International Journal of Electronics and Communications

A compact wide-bandwidth Antipodal Vivaldi Antenna array with suppressed mutual coupling for 5G mm-wave applications

As the communication technology advanced rapidly in recent times, the need for confidential data communication also arose. Here, a computationally feasible encryption/decryption algorithm is proposed to secure data using DNA sequences. The principal objective of DNA algorithm is to reduce big image encryption time. In this algorithm, natural DNA sequences are used as main keys. The image in which secret data is hidden using reversible data hiding (RDH) technique is encrypted twice before transmission. RDH is an information security technology which is extremely helpful in telemedicine. Authentication is necessary for images captured by robots. This can be used for authentication of data. This technique also enables us to embed electronic patient records (EPR) data into medical image before transmission, which can be later recovered on transmission side. The images are divided block-wise before encryption in the proposed scheme. Machine learning helps us to design a support vector machine (SVM), based on which a classification scheme is obtained to group encrypted and original images separately and to recover original image from encrypted image. Copyright © 2021 Inderscience Enterprises Ltd.

International Journal of Cloud Computing

DNA coding and RDH scheme hybrid encryption algorithm using SVM

In this research article, a multi-layered convolutional neural network (MLCNN) based auto-CODEC for audio signal enhancement which is utilizing the Mel-frequency cepstral coefficients (MFCC) has been proposed. The proposed MLCNN takes the input as MFCC with different frames from the noise contaminated audio signal for training and testing. The proposed MLCNN models has been trained and tested as 80:20 and 70:30 ratios from the available database. The proposed method has been verified and validated MNIST database. From the validation it has been found that the proposed MLCNN model provides an accuracy of 93.25%. The performance of MLCNN has been evaluated using short-time objective intelligibility, perceptual evaluation of speech quality and Cosine similarities. The proposed MLCNN model has been compared with the reported models. Form the comparisons; it has been observed that the proposed MLCNN model outperforms other models. From the cosine similarity, it has been proved that MLCNN provides high security level which can be used for many secure applications. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.

International Journal of Speech Technology

Audio signal quality enhancement using multi-layered convolutional neural network based auto encoder–decoder

Localization or positioning of wireless sensor nodes is an essential task for a wide range of applications in wireless sensor networks-based fifth generation (5G) networks. Node localization using mobile aerial beacon nodes (MABNs) provides high localization accuracy and less deployment cost compared to the localization using fixed ground beacon nodes because MABN deployed in unmanned aerial vehicles sends signals to unknown nodes (UNs) through reliable air to ground (AG) channel link. The classical received signal strength indicator (RSSI)-based multilateration and optimization-based least square localization (OLSL) schemes result high localization error because of the nonlinear distortions induced in the wireless channel. So, the highly nonlinear artificial neural network (ANN) models such as multilayer perceptron (MLP) and radial basis function (RBF) are used effectively for nonlinear node localization problems. ANN-based localization techniques are also capable of localizing mobile UNs. Further, the RBF with Gaussian activation has a little edge over the MLP with sigmoid activation because the wireless channel usually modelled with a Gaussian random variable. The simulation results included in this article also justify the efficacy of the proposed RBF localization with performance gain of about (7–70) % over MLP, OLSL and RSSI localization techniques. © 2021, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.

Neural Computing and Applications

Radial basis function-based node localization for unmanned aerial vehicle-assisted 5G wireless sensor networks

Survivability is the predominant major criteria for any fibre optical link during failure condition since it occurs frequently to disconnect several wavelength channels in the NG-PON2 system. The article proposes resilience in the protection mechanism for NG-PON2 network recommended by ITU-T G. 983.1 using Markov chain model. We analysed average downstream data loss for a 7:1 stacked NG-PON2 architecture where seven working lines can be protected by one protection line. The protection scheme allows protection to an architecture capable of a network throughput of 80 Gbps. Further, there is a comparison between the performance of 3:1 and 7:1 architecture for 40 and 80 Gbps data rate. © 2021, Springer Nature Singapore Pte Ltd.

Lecture Notes in Mechanical Engineering

Survivability Technique Using Markov Chain Model in NG-PON2 for Stacked Wavelength

The aim of this work is to study the suitability of two newly introduced bio-inspired algorithms, namely the dragonfly algorithm (DA) and the salp swarm algorithm (SSA) for thinning a linear antenna array. In array thinning, a fully populated array is chosen as a starting point, and a thinned array is obtained through careful deactivation of select sensors such that the residual active sensors enable the array to achieve a desired side-lobe performance. In this paper, we apply the binary versions of DA and SSA, namely the binary dragonfly algorithm (BDA), and the binary salp swarm algorithm (BSSA) to thin a symmetric linear array with uniform inter-element spacing of half wavelength. Extensive simulations were performed in MATLAB by considering arrays of different sizes. The results obtained from BDA and BSSA were compared against those obtained from the binary versions of two benchmark algorithms, namely the genetic algorithm (GA) and the gray wolf optimizer (GWO). Relative side-lobe level (RSLL) and filling percentage were used as performance comparison metrics. It has been observed that both BDA and BSSA offer promising results in line with BGA and BGWO. More specifically, BDA was found to be faster than BSSA. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.