Velagapudi Ramakrishna Siddhartha Engineering College

About: Velagapudi Ramakrishna Siddhartha Engineering College is a based out in . It is known for research contribution in the topics: Computer science & Antenna (radio). The organization has 1307 authors who have published 1155 publications receiving 6163 citations.

Enhancement of Efficiency and Performance Gain of Massive MIMO System Using Trial-Based Rider Optimization Algorithm

Abstract: Massive multiple-input multiple output (mMIMO) is considered as one of the most in demand and innovative technologies for the fifth-generation wireless communication systems. This paper attempts to frame a mMIMO system model, intends to improve the spectral efficiency, energy efficiency and performance gain. Here, the system performance achievements are premeditated in a multi-cell downlink mMIMO system under the core considerations such as “imperfect channel estimation, perfect channel estimation and the effect of interference among cells due to pilot sequences contamination”. The performance gains such as “spatial multiplexing gain, array gain and spatial diversity gain” are considered to maximize in this paper. For attaining this multi-objective function, an improved meta-heuristic algorithm called rider optimization algorithm (ROA) known as trial-based ROA adopted, and analyse the performance of the proposed model by comparing over existing models.

Privacy and protection of medical images ROI using SPLSB and bit-plane based watermarking

Abstract: In the current digital world, health departments and telemedicine systems are one among the sensitive data management systems of the users. Currently, at the time of managing the information by the authorities, the attackers have to tamper the medical data. It should happen while transmitting, storing and computing the data. In this paper, we propose a methodology for protecting the ROI of medical images data using Squint-Penultimate-Least Significant bits and Bit-planes of the covered image based watermarking technique. In this method, initially, the sensitive data of the medical image such as ROI segment can be detected using edge contour extraction method. Extracted ROI can act as a watermark which has required protection from the attackers. Later this watermark has protected by embedding into the chosen bit-plane of the source or cover image with SPLSB method. Thus generates a watermarked image which holds the watermark. Experiments have done on various medical images and the results were analyzed by considering performance evaluation factors. Thus, the proposed scheme is the robustness and effective method to protect the ROI of a medical image.

Comparative study of theoretical ultrasonic velocities of binary liquid mixtures containing quinoline and mesitylene at temperatures T = (303.15,308.15,313.15 and 318.15) K

Abstract: Ultrasonic velocities and densities of binary liquid mixtures containing quinoline and mesitylene have been measured at temperatures T = (303.15,308.15,313.15 and 318.15) K over the entire molefraction range of quinoline under frequency of 3 MHz. Theoretical velocities have been evaluated by using Nomoto (U NOM ), Impedance (U IMP ), Van-Dael and Vangeel (U VDV ), Junjie (U JUN ) and Rao's specific velocity (U RAO ) models. A good agreement has been found between experimental and theoretical values. U 2 EXP /U 2 IMX has also been evaluated for non-ideality in the liquid mixtures. The results are discussed in terms of intermolecular interactions between the component molecules of the binary liquid mixtures.

A comparative study on techniques used for prediction of stock market

Abstract: The most significant issue in the recent times in finance is finding the systematic ways to abridge and envision the stock market data. Stock market analysis gives useful information to Entrepreneurs, Individuals and Institutions about the etiquette of the market helping with speculation decisions. Many prediction models have been developed during the last decade. As a comparative study, we will be analyzing the ARIMA model, Neural Nets, Holt winters and the TSLM linear model. These models are outlined to assist the investors, bankers and capitalists to find out the concealed patterns that are present in the historical data. For the analysis purpose, we will be using five different companies' data procured through the Yahoo Finance. As the prediction of stock market is always considered as a provocative job and the precision of the predictions done has become an important part a comparative study is even done while removing the seasonal trends in the data too. We have observed that the Holt Winters model while removing the seasonal trends outperformed when compared to the rest models with a higher prediction accuracy.