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Research Paper

To study the effect of tool pin profile on mechanical properties and micro structure of friction stir welding magnesium alloy

Friction stir welding (FSW) is a solid-state joining process that uses a non-consumable tool to join two facing workpieces without melting the workpiece material. This is performed by using a milling machine. Heat is generated by friction between the rotating tool and the workpiece material, which leads to a softened region near the FSW tool. Magnesium alloy is the most widely used due to its excellent corrosion resistance, high ductility and reflective finish, lightweight material used in industries and aerospace, the selected material was welded with Friction Stir Welding (FSW) process, by using a combination of different tool rotation speed (1500 rpm, 2500 rpm, 3500 rpm) and welding speed (10 mm/min, 30 mm/min, 50 mm/min) as welding parameters. The weldments are welded by changing the tool length, the material of tool, depth of indentation, by changing tilt angle and the welded joints were tested using the universal testing machine, Ultimate Tensile Strength and hardness test. By using the above testing methods various parameters and grain structure of welded joints are studied.

Published by: Sai Krishna Praneeth Duggirala

Author: Sai Krishna Praneeth Duggirala

Paper ID: V7I1-1264

Paper Status: published

Published: February 23, 2021

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Research Paper

Stock market price prediction using Neural Networks

In this research analysis, in addition to the conventional ARIMA model, specific long short-term memory (LSTM), stacked-LSTM, and concept-based LSTM were used to calculate next day expenses. Furthermore, using our expectation, we developed two modes of transmission, different and important identity. Our database information not only includes the usual end-of-day expense and transfer modules, but also includes corporate bookkeeping insights, which are effortlessly selected and used in samples. With the regular ARIMA model, learning the next model in anticipation of the next day's stock costs, especially long short-term memory model (LSTM), stacked-LSTM, and concept-based LSTM. In addition, using our forecast, we developed two exchange procedures and developed differential and scale. Our database information not only includes regular end-of-day cost and transfer modules, but also includes corporate bookkeeping metrics, which are deliberately selected and used in samples. Bookkeeping information is considered information and cost plans for a company that no longer relies on expanding the pioneering power of the model. The effect indicates that the LSTM beats any remaining model in relation to the forecast error and shows a lot better yield in our transfer practice on different models. Besides, we found that the stacked-LSTM model does not improve the advance control over the LSTM.

Published by: Deebak S., Dr.P.Sindhuja

Author: Deebak S.

Paper ID: V7I1-1274

Paper Status: published

Published: February 23, 2021

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Review Paper

Introduction to charging technology in E-vehicles

With the growing need for mobility, the percentage of fossil fuel consumption is increasing day by day. Fuel like petrol and diesel are depleting and also causing pollution. So, there is an emergent need to switch to a more environmentally friendly mode of mobility. Considering this E-Vehicle has become the best substitute for IC engine cars. This Paper lightens Techniques of Charging of Electric Vehicles, Levels of Charging, Recent Technology in Charging and Batteries used in of Electric Vehicles

Published by: Chaitanya Arun Patil

Author: Chaitanya Arun Patil

Paper ID: V7I1-1270

Paper Status: published

Published: February 23, 2021

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Review Paper

Review paper on scope of Atmanirbhar Bharat

“Necessity is the mother of invention”. Like all the other countries India is also fighting with the Covid-19 Pandemic. The pandemic creates huge inflation, economic depression all over the world. However, it also turns out an opportunity for India to be stand out as global manufacture and self-reliant under the AtmaNirbhar Bharat program. This Abhiyan is started to mitigate the negative effects of the COVID-19 pandemic. We have to take steps to ensure that products which we import from elsewhere are manufactured in India. Our whole paper highlights the practical implementation areas with detailed reviews. It will also showcase how the Indian Youth should participate and shape the AtmaNirbhar Module for the betterment of the motherland. It tries to analyze the limitations and bring out various suggestions to utilize the existing capacity for becoming a global supplier. Our paper delivers the extended arm towards the five significant pillars of the AtmaNirbhar Bharat mission named Economy, Infrastructure, System, Demography, and Demand. It also highlights the four prime sectors like Rural Tourism, Electronic, Information Technology, and Modern Agriculture which are competent to give a quantum scale growth in this initiative. Our paper's sole aim is to converge the differential building blocks of the AtmaNirbhar Bharat mission.

Published by: Shritish Shete, Siddhi Dave

Author: Shritish Shete

Paper ID: V7I1-1271

Paper Status: published

Published: February 22, 2021

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Research Paper

Optimism at workplace

Optimism is a management strategy that gives tremendous energy to face any challenges. Optimism is a state of mind. Optimistic employees never succumb to any negativity, instead, they stay determined to reach their goals and enjoy the work. If you want to succeed in your career you have to overcome all the odds. This article focuses on workplace optimism, its challenges, and opportunities.

Published by: S. Ramesh, Annie Valsan

Author: S. Ramesh

Paper ID: V7I1-1273

Paper Status: published

Published: February 19, 2021

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Research Paper

Profanity detection in social media text using a hybrid approach of NLP and machine learning

Profanity is socially offensive language, which may also be called cursing, cussing, swearing, or expletives. Nowadays where everything is digitally managed, there are lots of online platforms and forums which people use. If we take an example of any social media platform like Twitter, their privacy policy suggests that users cannot share or write any obscene/vulgar language on a public platform. Several corporate and research organizations discuss how such content is found and controlled, such as computer vision research has developed to detect illegal practices in public spaces, NLP has progressed to detect profanity in social media texts. However, existing profanity detection systems still remain flawed because of various factors. In this paper, we define and analyze the system which will use NLP and Machine learning approach to solve this. It is usually framed as a supervised learning problem. Generic features such as Bag-Of-Words or embeddings systematically deliver fair success in classification. Lexical resources in combination with models such as Linear Support Vector Machine (SVM); feature modeling specific linguistic constructs making it more effective in classification.

Published by: Raktim Chatterjee, Sukanya Bhattacharya, Soumyajeet Kabi

Author: Raktim Chatterjee

Paper ID: V7I1-1269

Paper Status: published

Published: February 17, 2021

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