Christ University

About: Christ University is a education organization based out in Bengaluru, India. It is known for research contribution in the topics: Computer science & Convection. The organization has 2267 authors who have published 2715 publications receiving 14575 citations. The organization is also known as: Christ College & Christ University.

A Voltage Balancing Scheme for Modular Multilevel Converter Based on Charge Variation in Each Cycle

Abstract: This article presents a voltage balancing scheme for a modular multilevel converter (MMC) based on capacitor charge variation in each fundamental cycle. An in-depth theoretical analysis of stored charge variation for the concept is described. A new hybrid pulsewidth modulation (PWM) sequence is proposed based on a rotation strategy to achieve capacitor voltage balancing without sensing the capacitor voltages or arm currents. The rotation strategy provides the freedom of finding the best possible sequence to achieve capacitor voltage balancing. This reduces hardware, software burden and overall cost of the design implementation. The functionality and performance of the balancing strategy with new hybrid PWM sequence are carried out over wide range of modulation index (M) for three-phase five-level MMC in MATLAB/Simulink. A hardware prototype of single-phase five-level MMC is designed for experimental validation. The proposed hybrid PWM sequence is implemented on an Altera/Cyclone I series (EP1C12Q240C8N) field-programmable gate array using alternate phase opposition disposition PWM method. Simulation and experimental results are presented.

Hyperspectral multi-level image thresholding using qutrit genetic algorithm

Abstract: Hyperspectral images contain rich spectral information about the captured area. Exploiting the vast and redundant information, makes segmentation a difficult task. In this paper, a Qutrit Genetic Algorithm is proposed which exploits qutrit based chromosomes for optimization. Ternary quantum logic based selection and crossover operators are introduced in this paper. A new qutrit based mutation operator is also introduced to bring diversity in the off-springs. In the preprocessing stage two methods, called Interactive Information method and Band Selection Convolutional Neural Network are used for band selection. The modified Otsu Criterion and Masi entropy are employed as the fitness functions to obtain optimum thresholds. A quantum based disaster operation is applied to prevent the quantum population from getting stuck in local optima. The proposed algorithm is applied on the Salinas Dataset, the Pavia Centre Dataset and the Indian Pines dataset for experimental purpose. It is compared with classical Genetic Algorithm, Particle Swarm Optimization, Ant Colony Optimization, Gray Wolf Optimizer, Harris Hawk Optimization, Qubit Genetic Algorithm and Qubit Particle Swarm Optimization to establish its effectiveness. The peak signal-to-noise ratio and S o rensen-Dice Similarity Index are applied to the thresholded images to determine the segmentation accuracy. The segmented images obtained from the proposed method are also compared with those obtained by two supervised methods, viz., U-Net and Hybrid Spectral Convolutional Neural Network. In addition to this, a statistical superiority test, called the one-way ANOVA test, is also conducted to judge the efficacy of the proposed algorithm. Finally, the proposed algorithm is also tested on various real life images to establish its diversity and efficiency.

Stock Market Sensitivity to Macroeconomic Factors: Evidence from China and India

Abstract: The purpose of this study is to analyse the impact of Chinese macroeconomic factors on Shanghai Stock Exchange (SSE) Composite returns and Indian macroeconomic factors on Nifty returns based on monthly data from January 1998 to December 2018. This study adopts quantile regression approach. The QR allows examining the conditional dependence of specific quantile of SSE and Nifty returns with respect to the conditioning factors. The authors present results for two sample periods that are pre-recession and recession period from 1998 to 2008 and the post-recession period from 2009 to 2018. This paper also documents quite interesting and useful results for the entire period. From the results, It is concluded that Chinese consumer price index significantly affects the SSE returns only for lower quantiles. However, Indian consumer price index has a significant and positive impact on the Nifty returns for the upper quantiles. Further, Chinese interest rates and Indian interest rates have no impact on the SSE and Nifty returns respectively across the different quantiles. Moreover, the Chinese exchange rate influence the SSE returns at the extreme dataset. However, the Indian exchange rate is insignificant. It is important to note that the dependence structure of China shows a negligible change during the post-recession period. Conversely, the dependence structure has changed significantly for India post-recession. The implication of this paper would guide stock market participants.

Perceived stress among information technology professionals in India during the COVID-19 pandemic

Abstract: The Information Technology (IT) industry in India is an integral part of the nation’s economy. The COVID-19 pandemic is a cause of disquietude and is probably the gravest challenge encountered by t...