Online based Aadhar notification system
The Indian voter ID card is an Identity document is issued by the Election Commission of India to adult domiciles of India, who have reached the age of 18, which primarily serves as an identity proof for Indian citizen while casting their ballot in the country’s municipal, state and national elections. So, voter id is an important need for everyone. Our paper is going to represent the notification of a Voter id and will give the link for registration based on an aadhar card. Moreover, such notification will be sent for applying for Employment registration, License for Vehicle, Passport, and Pan Card like each and everything will be notified to apply to every citizen through their email id. Every important document and identification card need to be with every citizen so that every person can get all the needs.
Published by: Bharathi R., Bharathi N., Jeevan Kumar R., Dr. Saravanan S
Author: Bharathi R.
Paper ID: V7I2-1218
Paper Status: published
Published: March 30, 2021
Delineating the psychological impact of COVID-19 on small businesses in India
The covid-19 pandemic has caused large-scale loss of life and economy across all sectors. It has psychologically and socially impacted the general population ranging from their health and well-being to their education, career, and businesses. It has impacted the global economy drastically. India saw its worst recorded decline in economic growth since 1996 during the pandemic. In India, most of more than 100 million people engaged in small businesses were laid off and about one-third of the small businesses went beyond the scope of rescuing during the pandemic. In such a scenario, this paper intends to delineate the psychological impact of the pandemic on small businesses in India which faced a significant economic blow. At the same time, the resilience of some small businesses that managed to cope and thrive during these difficult times have been briefly discussed.
Published by: Neha Jain, Inayaa Gulati, Ananay Rajput
Author: Neha Jain
Paper ID: V7I2-1269
Paper Status: published
Published: March 30, 2021
Improved plant leaf disease classification by optimizing weight with convolution neural network learning approach
Agricultural productivity is something on which the economy highly depends. This is one of the reasons that disease detection in plants plays a vital role in the agriculture field, as having the disease in plants is quite natural. If proper care is not taken in this area, then it causes severe effects on plants and due to which respective product quality, quantity, or productivity is affected. In synopsis proposed approach optimized segmentation to find an active area for features and reduce noise, then extract texture base features and learning by ensemble classifier approach. In the Proposed framework main emphasis on getting sufficient features from disease and learning a combination of Convolution and nonlinear classification function.
Published by: Nisha Sharma, Dr. Sukhvinder Kaur, Dr. Rahul Malhotra
Author: Nisha Sharma
Paper ID: V7I2-1265
Paper Status: published
Published: March 30, 2021
Analysis of operations research applications in agricultural research: A literature review
Agriculture is a productive process requiring the transformation of a set of productive inputs into output with the aim of satisfying wants. These inputs are limited and as such place a constraint in the transformational process. It, therefore, implies that decision-making on the allocation of these limited agricultural resources is a major area of concern in attaining the objectives of agricultural production. Operations research, an analytical method used in problem-solving and decision-making in organizations, have been applied for over 70 decades in decision-making in agriculture. A review of applications of Operations research by some researchers in agriculture problems at farm level, regional sector level, environment protection, risks, and uncertainty analysis, formulating livestock rations and feedstuffs, forestry management, etc., shows that its application in agriculture is extensive and its potential for development is limitless. The application is constrained by complex interacting drivers existing in productivity, markets, the environment, and the people. These drivers include accuracy of data, quantifiability of data. natural disasters, instability of prices, demand for products, changes in government subsidies and policies, and dependence on an electronic computer. In conclusion, the decision to implement the results from Operations research lies with human beings and so this human element is still the most significant part of the decision-making process. The changes and adjustments in the natural and economic environment, and new improved information in the subject area, must be incorporated in the mathematical models and their parameters to account for the change.
Published by: Abasilim Chinwe Frances
Author: Abasilim Chinwe Frances
Paper ID: V7I2-1219
Paper Status: published
Published: March 25, 2021
Plant leaf disease detection by Features Selection and Learning Approaches Review
Agricultural productivity is something on which the economy highly depends. This is one of the reasons that disease detection in plants plays a vital role in the agriculture field, as having disease in plants is quite natural. If proper care is not taken in this area, then it causes severe effects on plants and due to which respective product quality, quantity, or productivity is affected. In this proposed approach optimized segmentation to find active area for features and reduce noise, then extract texture base features and learning by ensemble classifier approach. In Proposed framework main emphasis on getting sufficient features from disease and learning combination of classifier use linear and nonlinear classification function.
Published by: Nisha Sharma, Dr. Sukhvinder Kaur, Dr. Rahul Malhotra
Author: Nisha Sharma
Paper ID: V7I2-1255
Paper Status: published
Published: March 25, 2021
Detecting autism from facial image
Autism is a serious developmental spectrum disorder that puts constraints on the ability to communicate linguistic, cognitive, and social interaction skills. Autism spectrum disorder screening is the process of detecting potential autistic traits in an individual where the early diagnose shortens the process and has more accurate results. The methods used to predict the presence of autism by doctors involve physical identification of facial features and questioners, this conventional method of diagnosis needs more time, cost and in the case of pervasive developmental disorders, the parents feel inferior to come out in open. Therefore, a time-efficient and accessible ASD screening are imminent to help health professionals and inform individuals whether they should pursue formal clinical diagnosis or not. A screening tool that could identify ASD risk during infancy offers the opportunity for intervention before the full set of symptoms is present. The proposed model by using a convolution neural network classifier helps in predicting the early autistic traits in children through facial features in images, with the least cost, less time, and a greater amount of accuracy when compared to the traditional type of diagnosis.
Published by: Shaik Jahanara, Shobana Padmanabhan
Author: Shaik Jahanara
Paper ID: V7I2-1181
Paper Status: published
Published: March 25, 2021
