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Research Paper

Black hole attack detection and prevention by Grey Wolf Optimization

In this work, a detailed description of attacks in wireless sensor networks is presented and after this detailed literature review on the related approaches is resented. The review of different approaches and their methodology helps to improve the methodology of the work and helps to enhance the knowledge related to different types of attacks and their solution on WSN. This work presented the work on the optimization of energy and reduction in delay and packet loss during the communication on network. The optimization performed by using the grey wolf optimization algorithm which is a global optimizer that optimizes the results for effective and efficient outcomes. It improves the packet delivery rate, throughput, and reduces energy consumption and delay.

Published by: Gbazoe Kelezonga Daniel, Anuj Gupta

Author: Gbazoe Kelezonga Daniel

Paper ID: V6I4-1313

Paper Status: published

Published: July 30, 2020

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Thesis

Use of cotton, curcumin smoke as a potential treatment of COVID-19

COVID-19 pandemic is rapidly spreading at an increased rate. Various medicines are at various stages of testing or live usage, but none is proven to effectively reduce either the recovery time or the fatality rate. Current treatments focus on treating the symptoms or the complications which arise from the virus. Curcumin as traditionally used in India and as per various researches conducted is proven to act as antiviral, anti-inflammatory, antibacterial, anti-fibrotic, antioxidant, anti-fungal, antithrombotic agent when consumed orally. Studies have also suggested curcumin to be explored as cure or remedy for COVID-19. In this thesis, we suggest why and how Cotton, Curcumin smoke inhalation may help to cure or remedy COVID-19 so that this may be used as an effective treatment to reduce recovery time and fatality rate.

Published by: Praveen Adiga N. K., Subrahmanya Madhyastha

Author: Praveen Adiga N. K.

Paper ID: V6I4-1307

Paper Status: published

Published: July 30, 2020

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Research Paper

Rupayinvest

The numbers of smart phone users have increased exponentially irrespective of the platform within no time. Hence there arose several opportunities for both users and developers. User would be sure of downloading an application which provides more features, easier to use, responsive etc. Keeping these circumstances in the mind the developer has to work accordingly and provide an attractive interface which attracts the user and obtain a better feedback, which motivates the developer in making the application better every day by launching updates and by adding more features to it. In today’s world there arises multiple scenarios where a person is in an emergency and would require funds to overcome, and at the same time he would be running short of money. Our project or this application will provide loan via a digital platform through which he could achieve or accomplish their needs. Money is lent based on their occupation and other credentials.

Published by: Satish, H. K. Vedamurthy, D. V. Nishanth, Vishwajeet Kumar

Author: Satish

Paper ID: V6I4-1281

Paper Status: published

Published: July 30, 2020

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Research Paper

A Study on the behaviour of IT Employees during the COVID 19 Pandemic with special reference to Bangalore.

COVID 19 an issue which the whole world is talking about and the world is looking out for a solution to come out of this pandemic situation. During this pandemic situation, a lot of industries and individuals are effected by means of mental and financial pressure. One such industry that got effected is the IT industry. The paper deals with the issues faced by IT employees during this pandemic situation. The researcher highlights the issues and challenges faced by the IT employees and suggestions are given on how to overcome the issues and the researcher has collected the sample from 50 respondents. The paper is empirical in nature and depends on the primary data. The respondents were administered a questionnaire comprising the statements addressing the challenges and issues. Various statistical tools like correlation and regression analysis have been carried on to test the relation between the COVID effect and the reduction in salary. From the statistical results, it becomes evident that IT employees are undergoing tremendous pressure.

Published by: Glady Agnes L., Amritha Ashok, Kalyani V.

Author: Glady Agnes L.

Paper ID: V6I4-1288

Paper Status: published

Published: July 29, 2020

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Research Paper

Combined emission economic load dispatch problem using hybrid combination of flower pollination algorithm and moderate random search particle swarm optimization

The total cost of electricity generation is minimized while fulfilling the total load demand and considering all constraints in the Combined Economic Emission Dispatch (CEELD) problem. Electricity generation from fossil fuel negatively impacts the environment. Therefore, various optimization techniques have been deployed for the CEELD problem. In the literature, the Modified Random Search Particle Swarm Optimization (MRSPSO) and Flower pollination algorithm (FPA) are used as a solution for CEELD known as Combined Economic Emission Load dispatch problem. However, MRSPSO is easy to settle into local optima in high-dimensional space and delivers a low convergence rate in the iterative process, whereas in the FPA, the diverse population make it prone to being limited to the local optima. Thus, in order to overcome these limitations, in this paper, we have hybrid the FPA and MRSPSO algorithm that improves the convergence rate to meet the optimal solution. Initially, we have implemented MRSPSO and FPA algorithm; after that, combined it for CEELD. The experimental results were performed in MATLAB. The experimental results show that the hybrid approach gives better results as compared to the MRSPSO and FPA. Thus, the proposed technique is efficient and can be deployed for real-time CEELD problem.

Published by: Jaspreet Singh, Puneet Jain

Author: Jaspreet Singh

Paper ID: V6I4-1286

Paper Status: published

Published: July 29, 2020

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Research Paper

Lightweight privacy-preserving scheme for the smart grid data using ANU and Perturbation Algorithm

Smart Grid collects the data of smart meter and communicates the data to electricity generation, pricing, and billing departments. The departments used this information for electricity forecasting, real-time pricing, and generate electricity bills. The smart grid data contains customer personal information as well as electricity consumption details. Thus, sharing all information with the departments violates customer privacy. In addition, if no security mechanism provided for the data makes it prone to the attacks. In this paper, we have proposed a privacy-preserving algorithm for smart grid data security. The algorithm has two-phase. In the first phase, customer personal information and electricity consumption details separated. In the second phase, the customer's personal information is secured using a lightweight algorithm ANU and electricity consumption details are secured using noise addition on the data by applying the perturbation algorithm. The algorithm is coded and simulated in the MATLAB 2013a. The experimental results show that the proposed technique consumes less memory and provides better security as compared to the existing algorithms.

Published by: Ravinderpal Singh, Puneet Jain

Author: Ravinderpal Singh

Paper ID: V6I4-1285

Paper Status: published

Published: July 29, 2020

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