L D College of Engineering activities as per MHRD guideline during Covid-19 pandemic

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Covid-19 General Guidelines

Covid-19 Related Projects by Institute

Project Title : Health City

Department : IT Department

Team Members : Bhumi Sharma,Aman Shaikh,Arpan Prajapati,Meet Prajapati,Ravi Patel,Istiyak Shaikh

Guide Name : Prof. Madhuri Patel

Project Title : Food Drive

Department : IT Department

Team Members : Coder’s Club

Guide Name : Dr. Hiteishi Diwanji

Project Title : Covid Stats

Department : IT Department

Team Members : Smit Rami,Smit Mistry

Guide Name : Prof. Madhuri Patel

Project Title : EduLane

Department : IT Department

Team Members : Drashti Darji,Vaibhavi Ghelani,Krima Patel,Trushali Satasiya

Guide Name : Dr. Hiteishi Diwanji

Project Title : Fake News Detection

Department : IT Department

Team Members : Priyanka Dobariya,Heena Katariya,Mashirabanu,Neil Saxena,Pansuriya Ravi,Parmar Hardik,Dubendu Singh,Vishal Sakariya

Guide Name : Dr. Hiteishi Diwanji

Project Title : SOIC2021_001236

Department : EC Department

Team Members : Domadiya yash kamleshbhai

Project Details : During recent years, due to advancement of technology many sophisticated techniques are used in healthcare. In the glucose bottle it is responsibility of nurse to observe the status of bottle. But now it based on electrolyte monitoring and any nurse can observe the status of bottle in monitor. But then after some time the observer can forgot to change the bottle. So some issue may generate some big problem. Today in medical sector automation takes part and it is very easy to operate and do work on that system. We have used some advance technique in our project that is used valve to stop the reverse liquid or blood from body to bottle. We have to put one valve between the bottle and node while is in our body. So when the liquid of bottle is low then that liquid reverse to the body and then blood also reverse with that liquid. So we require to stop that reverse liquid. We have used valve which stops the reverse liquid. The benefits of this project is that cost is low. We make a device which have very low cost because we have make a cost control using a many way. Other is device size is small. We make a device as possible as small and it is compact and very flexible with glucose bottle. The important things is that power consumption is low because our project is used only 5V dc. And also we have used a rechargeable battery with more life time.

Project Title : SOIC2021_001256

Department : EC Department

Team Members : takwani yash jayeshkumar

Project Details : Our project Manav Rakshak is basically an application that can be installed in any smart devices. This software will track the movement of each and every person. Then, if any patient is diagnose with covid-19, then we can track the past history of a person. People who were close to the person in past fifteen days will be given red zone which will be displayed on our application. So the person having red zone should make himself home quarantine and person who were not close to any of the covid-19 patient in last 15 days will be given green zone. Our application works in both way that is if a normal person who is in green zone comes in contact with a person in red zone than our application will give continuous push notifications until a person is away enough from a person of red zone. This application will help to secure each and every person from getting infected by virus. This application only needs the user's location always remains on. This will be most important part that it does not affect the privacy of any person.

Project Title : SOIC2021_001296

Department : EC Department

Team Members : vadi krutik jayntibhai

Project Details : This Project comes up with the applications of NLP (Natural Language Processing) techniques for detecting the 'fake news', that is, misleading news stories that comes from the non-reputable sources. Only by building a model based on a count vectorizer (using word tallies) or a (Term Frequency Inverse Document Frequency) tfidf matrix, (word tallies relative to how often they’re used in other articles in your dataset) can only get you so far. But these models do not consider the important qualities like word ordering and context. It is very possible that two articles that are similar in their word count will be completely different in their meaning. The data science community has responded by taking actions against the problem. There is a Kaggle competition called as the “Fake News Challenge” and Facebook is employing AI to filter fake news stories out of users’ feeds. Combatting the fake news is a classic text classification project with a straight forward proposition. Is it possible for you to build a model that can differentiate between “Real “news and “Fake” news? So a proposed work on assembling a dataset of both fake and real news and employ a Naive Bayes classifier in order to create a model to classify an article into fake or real based on its words and phrases.

Video Prepared by Students for awareness