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Analysis of business process automation: RPA

This research is a study to explore the features available in the leading RPA software for business. Robotic process automation (RPA) is a leading software technology that helps in building, deploying, and managing software robots that surpass human actions interacting with digital system. The software bot can perform task as of human do like identifying what’s there on the screen, extracting & identifying data, navigating system etc. But RPA robots are more consistent than human. The main highlights of this study discussed the Pros and Cons of RPA.

Published by: Namrata Manohar Dhuri, Dr. Abhijit N. Banubakode

Author: Namrata Manohar Dhuri

Paper ID: V7I4-1396

Paper Status: published

Published: July 16, 2021

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Research Paper

Association of social networking addiction and anorexia nervosa (desire for thinness)

The present research was conducted to study the association between Social Networking addiction and Anorexia Nervosa( desire for thinness) among adolescents. A sample of 913 junior college students were selected as a sample for the present study.The findings suggest that there is no significant association between Social networking addiction and Anorexia nervosa.

Published by: Dr. Khan Zeenat Muzaffar

Author: Dr. Khan Zeenat Muzaffar

Paper ID: V7I4-1287

Paper Status: published

Published: July 16, 2021

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Research Paper

Recognition of Handwritten digits using Machine Learning and Deep Learning algorithms

Digitalization has become very prominent in today’s world. The need for storing information in computers is rapidly increasing. Converting handwritten documents into digital form by humans is often difficult and time-consuming. With the rapid development of technology, human’s reliance on machines to do time-consuming and monotonic tasks also greatly increased. Machine learning and deep learning are the major fields in Computer Science that have developed intelligent algorithms to train machines to do a set of repetitive tasks. Handwritten digit recognition is one of the significant areas of research and development with an increasingly large number of possibilities that could be attained. Handwritten Digit Recognition is the ability of a computer to receive and interpret handwritten input from various sources such as paper documents, photographs, touch screens, and other devices. This paper illustrates handwritten digit recognition with the help of MNIST datasets using Support Vector Machines (SVM) and Convolution Neural Network (CNN) models. The main objective of this paper is to compare the accuracy of the models stated above and develop a Graphical User Interface (GUI) application with the most accurate model.

Published by: Sahithi Akundi, B. Prajna, Bathina Lakshmi Rishitha, Balaka Supraja, Arugula Gayathri

Author: Sahithi Akundi

Paper ID: V7I4-1381

Paper Status: published

Published: July 15, 2021

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Research Paper

A study on Quality of Life in Indian adults – Outcomes and role of nutrition

Understanding factors influencing the Quality of Life (QoL) of people has been a subject of growing interest, as measurement of QoL includes subjective dimensions of general well-being of individuals. The present study is aimed at assessing the QoL as perceived by Indian adults and arriving at a cutoff for categorizing QoL. A cross-sectional survey was conducted on a stratified sample of 2762 adults in 8 cities representing 4 geographical zones of India - North, South, East and West. WHOQoL-BREF was self-administered to measure QoL while a structured questionnaire and an app-based 24-hr diet recall were used to assess perceptions and practices about health and nutrition that affect QoL. The QoL scores were computed in accordance with WHO manual and cutoff value was arrived based on percentage mean score to categorize respondents as having poor and good QoL. Descriptive statistics were reported as mean, standard deviation, percentage for the scores and other variables, while a two-sample t-test was performed to compare the QoL scores for independent variables. The QoL percentage mean score of 68.5 for the sample population was obtained which was considered as a cutoff for categorizing QoL. It was observed that nearly half of the respondents (46.2%) had poor QoL. Men had a better QoL score than women while older adults had lower scores than younger adults (P<0.01). Being employed and higher socio-economic status positively impacted the QoL. From the 8 cities, Mumbai had the highest percentage of respondents with good QoL. Almost all respondents agreed that nutrition plays an important role in having good QoL, however, protein and micronutrient intake showed a huge gap. In conclusion, QoL assessment could be an important tool towards holistic approach to health and can assist individuals and healthcare professionals to take impactful steps towards improving QoL of the population.

Published by: Dr. Madhavi Marathe, Dr. Pushkala Padmanabh

Author: Dr. Madhavi Marathe

Paper ID: V7I4-1370

Paper Status: published

Published: July 15, 2021

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Research Paper

Fetal birth weight estimation in high-risk pregnancies through Machine Learning Techniques

Low birth weight of the fetus is considered one of the most critical problems in pregnancy care, which will affect the health of the newborn and in more severe cases will lead to its death. This situation is the reason for the high infant mortality rate throughout the world. In terms of health, artificial intelligence technologies, especially those based on machine learning (ML), can early predict problems related to the health of the fetus throughout pregnancy (even at birth). Therefore, the project proposes an analysis of several ML techniques that can predict whether the fetus will lose weight at birth in its gestational age. The importance of early diagnosis of problems related to fetal development depends on the possibility of increasing the number of days of pregnancy through timely intervention. This intervention will help to improve the weight of the fetus at birth, thus reducing neonatal morbidity and mortality.

Published by: Meghana S., Y. Sree Rushitha, Susan Syeda, Priyanka M., Dr. Shantakumar B. Patil

Author: Meghana S.

Paper ID: V7I4-1342

Paper Status: published

Published: July 15, 2021

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Research Paper

A study on effect of emotional attitude on emotional purchase intention

The study emphasis on emotional attitude and emotional purchase intention, where the study focused on six major items under Emotional Attitude and Emotional purchase Intention. The main purpose of the study is to find the direct effect of Emotional Attitude on Emotional Purchase Intention. It also emphasizes how these impacts the customer’s attitude regarding age, gender, and qualification. This study is applicable in terms of objective and various hypotheses are implemented. To collect the data self-administered questionnaire was designed and the data is collected from the region of Hyderabad, Using a convenient sample of 97 respondents. The data is analyzed with assorted methods like frequency calculation and the Chi-squared test. It was found that gender, age, and education qualification had a very significant role to play. Amos was used to finding the direct effect of Emotional Attitude on Emotional Purchase Intention.

Published by: Namratha, P. Purushotham Rao, Dr. A. Patrick

Author: Namratha

Paper ID: V7I4-1352

Paper Status: published

Published: July 14, 2021

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