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Review Paper

Non-performing assets and their effect on the Indian economy

Non-performing assets have negatively affected the Indian Economy for several years now. While NPAs have been present for a long time, they sky-rocketed in India during the mid-2000s. The objective of this paper is to explain what NPAs are and show the causes as well as the impact of NPAs in India.

Published by: Ayush Bhatia

Author: Ayush Bhatia

Paper ID: V7I1-1192

Paper Status: published

Published: January 23, 2021

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Research Paper

Psychological Impact of Covid-19 in India

The Covid-19 Pandemic has caused the world to go into lockdown. This lockdown and isolation from others have had a negative impact on the psychological and emotional health of many people. The objective of this study is to study the effect the Covid-19 pandemic has had on people of 16-36 years of age. This study has been conducted with a help of a survey completed by 160 participants of various backgrounds. The study suggests that more than 40% of the participants are experiencing anxiety and depression symptoms.

Published by: Ayush Bhatia

Author: Ayush Bhatia

Paper ID: V7I1-1176

Paper Status: published

Published: January 23, 2021

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Research Paper

In Vitro Toxicity of Bavistin (Carbendazim 50% Wp) On Sclerotium Rolfsii Sacc.

When the hosts are susceptible and the environment is feasible the viable fungal pathogens cause many plant diseases. The diseased plant fails to produce a healthy yield and also declines its viability. To inhibit the effect of fungal pathogens either natural or synthetic fungicides are applied. The present investigation deals with In vitro antifungal activity of the synthetic fungicide Bavistin (50% WP) on Sclerotium rolfsii Sacc. using poisoned food technique. Mainly 0.2mg, 0.4mg, 0.6mg, and 0.8mg of fungicide were incorporated into four different 100ml PDA media and obtained specific concentrations such as 10ppm, 20ppm, 30ppm, and 40ppm respectively, and then poured into four different Petri plates. It was found very toxic at 40ppm and the growth was completely inhibited whereas the lower concentrations such as 30ppm, 20ppm, and 10ppm showed various degrees of inhibition on soil-borne fungus Sclerotium rolfsii Sacc.

Published by: Dr. Prashant Kumar, Dr. C. Narayana Reddy

Author: Dr. Prashant Kumar

Paper ID: V7I1-1172

Paper Status: published

Published: January 23, 2021

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Research Paper

Analysis of concrete with using human hair as fiber-reinforced

Human hair is a waste material that is found in the bountiful sum in the day by day life. It is a typical constituent in city squander streams and causes ecological issues as it is a non-degradable waste. Fiber strengthened cement gives great flexure strength less brake improvement. Since concrete is frail in strain thus a few estimates should be embraced to defeat this insufficiency. Human hair is by and large solid in strain; henceforth it very well may be utilized as a fiber fortification material. Human hair Fiber is a choice non-degradable issue available in riches and at unassuming cost. Hair additionally diminishes ecological issues. Likewise, expansion of human hair strands upgrades the coupling properties, miniature breaking control, Imparts ductility, strength and furthermore builds expanding opposition. The exploratory discoveries in our investigations would support future examination toward the path for long haul execution to expanding this expense of powerful kind of strands for use in primary applications. The examination was led on solid 3D shapes, chambers, and light emissions size with expansion of different rates of human hair fiber i.e., 0%,0.5% 1%,1.25%,1.5%, and 2% by weight of concrete, fine and coarse aggregate, and results were contrasted and those of plain concrete cement of mid-range grade. For every level of human hair included solid, we make a different cubes sample that was tried for their individual mechanical properties at relieving times of 7days, 14days, and 28days. The ideal amount of human hair was gotten as 2% by the weight of concrete. That investigation encourages the fresher to comprehend the human hair fiber fortified execution in concrete cement.

Published by: Akshay Patel, Abhay srivastava

Author: Akshay Patel

Paper ID: V7I1-1188

Paper Status: published

Published: January 23, 2021

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Research Paper

A lightweight encryption authentication scheme using rectangle and chaotic logistic map algorithm for smart grid

Smart Grid is the advanced power grid system that combines renewable energy resources like wind, solar, biogas with the existing power system. Besides that, it provides two-way communication using a large number of electronic devices between the customer and providers which is also known as Advanced Metering Infrastructure (AMI). The devices are resource constraint devices and sensitive information is communicating through them. Therefore, in this paper, these constraints are taken under consideration and designed a lightweight encryption authentication scheme for AMI. The lightweight RECTANGLE and chaotic Logistic map algorithms are taken under consideration. These algorithms encrypt the information along with generating authentication tags. These tags are used on the receiver side to verify the authenticity of the data. The algorithm is simulated in MATLAB and various performance parameters calculated for it. After that, it is compared with the existing algorithms.

Published by: Arun Kumar, Puneet Jain

Author: Arun Kumar

Paper ID: V7I1-1178

Paper Status: published

Published: January 23, 2021

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Research Paper

Hybrid the artificial intelligence and swarm-based optimization algorithm for load forecasting in the smart grid

Electricity load forecasting algorithms are used in the smart grid to predict the electricity demand in the future. Besides that, it helps in reducing the electricity generation cost. In the literature, three types of load forecasting are done such as short-term, medium-term, and long-term. In this paper, the short term forecasting is done. The short-term forecasting algorithm predicts the electricity demand from a few hours to several weeks ahead. Due to the nonlinear, nonstationary, and non-seasonal nature of the electric load time series, accurate forecasting is challenging. In this paper, Artificial Intelligence (AI) and the swarm optimization algorithm is hybrid in order to improve the prediction of load forecasting. We have considered Artificial Neural Network (ANN) and Binary Particle Swarm Optimization (BPSO) algorithms in our work. The BPSO algorithm used to improve the learning rate in the ANN network. The experimental results were simulated in MATLAB and various performance metrics such as RMSE, MAPE, minimum and maximum error determined. The results show that the proposed algorithms provide better results as compared to the existing algorithms.

Published by: Kuljeet Singh Sandhu, Puneet Jain

Author: Kuljeet Singh Sandhu

Paper ID: V7I1-1179

Paper Status: published

Published: January 23, 2021

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