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Research Paper

Automated leaf disease prediction and suggested remedies using Convolutional Neural Network (CNN) algorithm

The proposed system uses in identification of plant disease and provides remedies which will be used as a defence reaction against the disease. The data obtained from the Internet is correctly segregated and therefore the totally different plant species are identified and are renamed to form a proper database then obtain a test-database that consists of varied plant diseases that are used for checking the accuracy and confidence level of the project. By using training data we will train our image classifier and then output will be predicted with more accuracy. We use Convolution Neural Network(CNN) which comprises different layers which are used for prediction. A image drone model is additionally designed which might be used for live coverage of huge agricultural fields so that a high-resolution camera is connected and can capture images of the plants which will act as input for the software, based on which the software will tell us whether the plant is healthy or not. With our code and training model we have achieved an accuracy level of 78% .Our software gives us the name of the plant species with its confidence level and also the remedy that can be taken as a cure. Deep learning has become prominent with big data technologies and high-performance computing to create new opportunities for data-intensive science. In this paper, we tend to give a comprehensive review of analysis applications of deep learning in agricultural systems. The prediction and diagnosis in this project demonstrate how agriculture will benefit from deep learning technologies. The deep learning techniques used for farm management systems are entering into real-time artificial intelligence.

Published by: S. Ashwin kumar, Dr. S. Rajagopal

Author: S. Ashwin kumar

Paper ID: V7I1-1288

Paper Status: published

Published: February 27, 2021

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Review Paper

IoT based traffic and street light control management for smart cities

All metropolis cities suffer from traffic obstruction issues, particularly within the central downtown. traditional cities will be remodeled into good cities by exploiting data and communication technologies. The signal temporal arrangement changes with the density of the traffic and delay are given the assistance of a microcontroller. The web of Things (IoT) will play an important role in the accomplishment of good cities. The aim of this project is to style a density-based stoplight system interfaced with a barrier gate. This project proposes a microcontroller for temporal arrangement modification of the signal and buzzer action. before the barrier gate, a stop line is created and with the assistance of another IR device, the vehicle is caterpillar-tracked whenever it approaches the stop line If the vehicle crosses the stop line the hint is given to the close room. Node MCU microcontroller is employed for signal temporal arrangement modification supported the density of traffic.

Published by: Monika J. Raut, Vrushali D. Jaywar, Sonali Bhoyar, Ashwini kumbhare

Author: Monika J. Raut

Paper ID: V7I1-1167

Paper Status: published

Published: February 27, 2021

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Research Paper

Online portal for study and book donation

The point and object of this task are to set up an online gateway for the assortment of reading books so they can be given to the students who are out of luck. What this task will do is, gather the trade-in book from the understudy who has totally perused the book and completes his course effectively from the understudies and doesn't need the books any longer. After the assortment of these books, they would be given over to the NGOs which would check the books, and afterward whenever affirmed will be given to individuals straightforwardly or to the Government schools who will be giving out these books free of charge. Will the aggregate endeavors of the public authority, NGOs, and common society associations help in acquainting computerized activities with address the underlying difficulties and help in making learning seriously captivating and intriguing and simple to gather your books and In this project, we are also trying to cover the mode of online learning and preparation for higher study in village areas as well as city’s

Published by: Nishant Kumar Singh

Author: Nishant Kumar Singh

Paper ID: V7I1-1272

Paper Status: published

Published: February 27, 2021

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Research Paper

Comparative study of the prevalence of thyroid disorders

Thyroid hormone disorders are the commonest endocrine disorder in India and also the commonest preventable cause of mental retardation. The male and female ratio of the disease ranges from 4:1 to 7:1 Untreated hypothyroidism during pregnancy can lead to delays in growth and intellectual development in the baby. The present study focused on the comparison of prevalence of thyroid disorders on various aspects like Comparison of prevalence of thyroid disorder on the basis of age, on the basis of gender, and on the basis of religion. The clinic-based study was conducted in the clinic Ranchi, in this study 305 patients are taken as samples who visited the clinic for treatment of thyroid disorder (Hypothyroidism, Hyperthyroidism) from year Sept 2015 to Dec 2017. Patients of all ages are included in the study. Out of the 305 patients with a thyroid disorder, 298 patients found to have hypothyroidism (98%) and 7 patients with hyperthyroidism (2%). The comparison of disorders found that hypothyroidism is more prevalent than hyperthyroidism. Thyroid disorder is more prevalent in females than males. There is a high prevalence of thyroid dysfunction in female in Ranchi and need for similar studies from different regions of the country covering larger population are well appreciated.

Published by: Rose Rani Minz, Dr. Manju Kumari

Author: Rose Rani Minz

Paper ID: V7I1-1277

Paper Status: published

Published: February 27, 2021

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Research Paper

Load Flow and Transient simulation of power system using PSSE software. A case study of interconnection for new run of river hydro power plant at Machai with national grid.

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Published by: Nageen Jalal, Muhammad Iftikhar, Mujtaba Hassan, Anjum Khalid

Author: Nageen Jalal

Paper ID: V7I1-1266

Paper Status: published

Published: February 27, 2021

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Research Paper

Foraging efficiency of APIs spp. in Syzygium cumini (Myrtaceae)

The foraging behavior of honey bees (Apis spp.) on blackberry (Syzgium cumini) was studied in Bengaluru. During fully flower blooming period of March to April in 2019 and 2020. twenty days in each period of the year. It was noticed that honey bee intensely and preferably forage pollen first and then nectar almost thought the day from 6 am to 6 pm with a peak between 9 am to 11 am. And noticed that percentage of foraging Apis florea (51.18%), Apis dorsata(19.75%), Apis mellifera(14.76%), and Apis cerana(14.31%). Apis florea spent more time to forage per flower and at least one is Apis dorsata than the other.

Published by: Amaravathi D., Dr. M. Shankar Reddy

Author: Amaravathi D.

Paper ID: V7I1-1234

Paper Status: published

Published: February 26, 2021

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