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Medicines for underprivileged patients using android application

Gift of medication is one of the most huge commitments that an individual can make towards the general public. Drugs for health care(DFHC) framework is a mix of site application and android application made for such respectable and incredible reason. The rising innovation in android improvement has made this conceivable. The emergency clinics, patients and clients can enroll through site. Furthermore, on other hand, the android application gives an approach to searcher to look for givers were calling and informing to companions through application on android. This application can likewise be utilized by medication benefactor and searcher where individual can enlist for keen on medication gift .User can get giver area through GPS and calling to them will be available. In DFHC there will be use GPS innovation that will be utilized to follow the route to the medication giver. The client will get the course to arrive at the ideal area and he doesn't need to ask physically, in this manner time can be spared.

Published by: Vishnu R.

Author: Vishnu R.

Paper ID: V7I4-1277

Paper Status: published

Published: July 12, 2021

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Research Paper

Sentiment and thematic analysis on E-commerce application for user reviews using Machine Learning

Over the year's we have experienced tremendous growth in the use of ECommerce Applications. Since the pandemic, there has been an escalation in the use of these applications. Hence, we must understand the factors that are affecting the effectiveness of the services. In this paper, we will be analyzing different eCommerce applications on Google Play and App Store by performing sentiment analysis on user reviews by machine learning and then perform thematic analysis to identify the themes of reviews. Sentiment analysis is the process of identifying and categorizing opinions expressed in the text, especially when we want to determine whether the attitude of the customer concerning the services provided is positive, negative ,or neutral. Performing Sentiment analysis manually is a humongous task as there are millions of users. Hence we will be implementing different classifiers using supervised ML algorithms. These Classifiers will be trained and compared, then the classifier with the highest accuracy will be used to predict the sentiment polarity. Later on, we will be performing thematic analysis on positive and negative reviews to determine themes representing various factors affecting the effectiveness of e- commerce apps both positively and negatively. In the end, we will be proposing how to tackle the negative issues that are hampering the services

Published by: Rutuja Sanjay Mane, Aarti Sanjay Sahib, Prachi Sunil Mulay, Sumesh Santosh Mapara, Sulochana Sonkamble

Author: Rutuja Sanjay Mane

Paper ID: V7I4-1275

Paper Status: published

Published: July 12, 2021

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Research Paper

Calmify: Novel Way to Monitor the Mental Health using IoT

Emotional and mental health is important as it encompasses our psychological, emotional and social wellbeing. It plays a vital role in the health of our relationships, allowing us to adapt to changes in life and deal with adversity. The Covid-19 pandemic has had a major impact on our lives. Many of us are facing challenges that can be stressful, overwhelming and cause strong emotions in adults and children. One in four people in the world will be affected by mental or neurological disorders at some point in their lives. Around 450 million people currently suffer from such conditions, placing mental disorders among the leading causes of ill-health and disability worldwide. Considering this as quintessential and need of the hour, I have developed Calmify a full mental wellness Tech package to help and discover ways to take a healthy approach to your emotional wellness. It includes a mobile application along with a novel and innovative Mental Wellness Smart Glove, which will surely help people to cope with stress in a healthy way. IoT technologies have a great potential in mental health for diagnoses, treatment, and care due to the increased ability to collect real-time data indicating patterns of activity and behaviour of people. On that note, I developed Calmify as an IoT-based BioMedical Embedded System that aims to provide a mental health solution that is efficient, cost-effective, feasible, easy to use and most importantly affordable for everyone. The smart glove is a wearable device that can monitor the mental wellbeing of the patient and provide ML predictions on the onset of serious mental health issues using psychophysiological signals obtained from unobtrusive smart sensors embedded in the glove which can be carried during daily life routines of individuals. Overall, it will be helpful in providing proactive healthcare to the patients.

Published by: Harmanjot Singh

Author: Harmanjot Singh

Paper ID: V7I4-1267

Paper Status: published

Published: July 12, 2021

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Research Paper

Comparison of readiness for the practice among Bacculerate and Diplomate Pregraduate Nurses – Are there any differences?

Nursing Education in India is undergoing a major transition in inorder to improve the standards across. Graduate Nurses' transition from educational program to clinical practice is a global concern. They often feel insecure, inadequately prepared and it’s a time of reality shock. Diplomate and Bacculerate programs are the two entry-level courses in Nursing in India. There is documented evidence on the differences between diploma and degree nurses in terms of professional competence. However, readiness for the practice among pregraduate nursing students is less explored in the Indian context. This article will reveal the differences in readiness for the practice among Bacculerate and Pregraduate nurses in the South Indian setting.

Published by: Dinesh Kumar Suganandam, Vinitha Ravindran, Vathsala Sadan

Author: Dinesh Kumar Suganandam

Paper ID: V7I4-1266

Paper Status: published

Published: July 12, 2021

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Research Paper

Performance evaluation of GMM super-pixel model-based technique with various bleeding detection techniques in WCE images

Wireless Capsule Endoscopy (WCE) is a non-invasive medical process that permits the assessment of the whole gastrointestinal tract that includes small intestine parts ahead of the conventional endoscope scope. This in turn needs the approach of a computer-aided scheme to assess the video frames for reducing the time of diagnosis. In this approach, the performance comparison on various existing techniques like color-based feature extraction, histogram-based approach, Discrete Wavelet Transform (DWT), K-nearest neighbor (KNN), K-means, and Support Vector Machine (SVM) techniques employed in the detection of bleeding to that of the proposed Gaussian Mixture Model (GMM) super-pixel model has been carried out. The study is carried out in terms of feature extraction models used so far and the classification approaches employed so far. Then the experimental study is carried out in terms of existing techniques and the performance is compared with GMM super-pixel feature extraction model and linear SVM to prove the effectiveness of the super-pixel-based model for bleeding detection. From the experimental analysis, the GMM super-pixel model is concluded better for automated bleeding detection.

Published by: Rathnamala S., Dr. S. Jenicka

Author: Rathnamala S.

Paper ID: V7I4-1256

Paper Status: published

Published: July 12, 2021

Full Details
Research Paper

Weed detection using Machine Learning

Agriculture is one of the world's oldest sources of human nourishment. To satisfy the strain of an ever-increasing population, agricultural output must be greatly enhanced. People employed natural techniques to enhance production within the past, like utilising garbage as a fertiliser within the fields, which increased output sufficiently to fulfil the population's needs. Following this epoch, the utilization of lethal chemicals like herbicides skyrocketed. As a result, we've got made extra money while also causing greater environmental damage. the most important goal of this research is to use image processing to detect and take away weeds.So, in this project, we've created a way to decrease herbicide consumption by only spraying them where weeds are present. Using image processing, we were able to locate weeds in the site photos and classify them based on their area and aspect ratio.

Published by: Anupuri Sai Priya, Nadimpalli Lavanya, Pallavi K., G. Nithyasree, Santhosh Reddy P.

Author: Anupuri Sai Priya

Paper ID: V7I4-1255

Paper Status: published

Published: July 12, 2021

Full Details
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