Automated real-time detection and reporting accidents using IoT based helmet
In recent days, road accidents are occurred as regular habits by mainly using motorbikes. The goal of this project is proposed to prevent, detect and report the accidents to the respective authorities. This may reduce severe accidents and as well as may save the lives of people. We propose the solution, where the helmet itself initiates communication to report the accident using a person’s phone. Our design consists of Arduino Microcontroller, transmitter and receivers, and sensors. By using RF transmitter and indicator, indicates that the person is wearing a helmet, if it doesn’t indicate which means the person doesn’t wear a helmet. Only then does the bike get started. So, this will be the initial prevention in this design. If a severe accident occurs, the pressure sensor in the helmet detects the pressure limit, then python code executes and triggers the alert message using cloud authentication. Mobile application catches the trigger and obtain the device’s location and sends the alert message to nearby hospitals, relations. There will also be a buzzer sound to alert the nearby people to draw attention, even if it is unable to send an alert message. If there is a mild accident and no injury, there will be a reset button to cancel the sending of the alert messages using a secret PIN.
Published by: Karthik B.
Author: Karthik B.
Paper ID: V7I5-1151
Paper Status: published
Published: September 4, 2021
Supercharge the dopamine naturally for a good feel
“Happiness depends on ourselves.” More than anybody else. Yes when an exogenic force shakes our mental equilibrium to drop down, we must be aware to reboot with our God’s pharmacy app that is inbuilt in our body. Dopamine also plays a big role in our ability to think, plan, focus, and engage in activities; it drives motivation. If dopamine levels are low, we may struggle with motivation or feel a little down. Thankfully, there are some incredible ways to increase dopamine levels naturally. So, let us dive into the natural mood-boosting hacks that will drive us to positivity and success. This article scribes down to unveil the ways to boost our hanging android that is sad and sorrows, weary and worn out by just activating the hormone app that is inbuilt as God’s Pharmacy.
Published by: Dr. Esther John, Priscilla Prabu
Author: Dr. Esther John
Paper ID: V7I5-1136
Paper Status: published
Published: September 4, 2021
Pareto-optimal phylogenetic tree reconciliation considering duplications, transfers, losses, and incomplete lineage sorting
A phylogenetic tree is a representation of the evolutionary histories of different species from which the gene tree is constructed from some specific sequence of copies of genes that are sampled from a group of species. For some biological events like gene Duplication (D), Horizontal Gene Transfer (T), Loss (L), and Incomplete Lineage Sorting (ILS), with the passage of time, the history of gene evolution and species evolution might show discord in most cases. Though many researchers do not account ILS event as discordance between a gene tree and species tree because, in theory, ILS is not a true “gene event” such as duplication or a transfer, since nothing “happens” to the gene during incomplete lineage sorting. But still, this phenomenon can lead to a gene tree differing from the species tree just like speciation acts on populations. Reconciliation is a process of resolving a disagreement between gene and species tree with the least possible evolutionary event costs. Addressing this problem (not accounting ILS event), we propose an efficient Pareto-optimal algorithm to reconcile a binary gene tree with binary species tree under Duplication, Transfer, Loss and Incomplete Lineage Sorting parsimony criterion, which is the extension of the previous Pareto-optimal algorithm developed by Libeskind-Hadas et al., 2014[12]. Through this research, it has been shown that how to properly cost DTL events considering ILS event and then give a fixed-parameter tractable (FPT) algorithm which calculates the most parsimonious Duplication (D), Horizontal Gene Transfer (T), Loss (L), and Incomplete Lineage Sorting (ILS) reconciliations. Comparing with the previous Pareto-optimal algorithm, the space complexity will remain the same after considering the ILS events. This is the first Pareto-optimal reconciliation algorithm to consider all of the four evolutionary processes driving tree incongruence.
Published by: Rahnuma Tasmin, Dr. Md. Abul Kashem Mia
Author: Rahnuma Tasmin
Paper ID: V7I4-1862
Paper Status: published
Published: September 4, 2021
Rake- A cross-platform digital product
Rake is a cross-platform release-ready digital product that is a production-level app, making use of all the latest Firebase technologies. This app uses Firebase MLKit, Firebase Firestore & Firebase Authentication for its core functionality. It also uses libraries like Retrofit, Glide, GSON, and more third-party libraries for other functionalities. Firebase MLKit is used to recognize handwriting and text in images, objects in images, and also scan barcodes. This contributes to the main purpose of our app, which labels images and provides the user with context-aware actions of what the user can do next. Firebase Authentication is used to authenticate and help users log in & signup into the app. This uses OAuth 2.0 under the hood, so it is a very secure mechanism for login. Firebase Firestore is used as a database to store the user’s scanned data so that he can refer to it for later use. We’re also using our own custom TensorFlow Lite model, named ‘mobilenet’, to detect images. The app can be accessed via the web portal as well. Firebase Authentication lets the user login on to the web portal, which can be found at the rake.now.sh, and give the user access to his data on Firebase Firestore. This extended functionality where the user can access his data enhances the ease of use and makes sure that the user doesn’t always need a mobile device to see his previously scanned data.
Published by: Ganavi J., Amith S. Bharadwaj
Author: Ganavi J.
Paper ID: V7I5-1164
Paper Status: published
Published: September 4, 2021
Effectiveness of Doula care on anxiety and labor outcome among parturients
Pregnancy is a natural event, speculated to be of celebration and joy. But anxiety and fear about childbirth often inhibit most women from enjoying this childbirth experience. Supportive measures involve continuous support during labor by doula and doula care is effective in these situations to reduce anxiety. This study was conducted to assess the effectiveness of doula care on anxiety and labor outcome among parturients in Kanyakumari, India. Methods: This was a quasi-experimental study, conducted among 30 primi parturients who were selected using consecutive sampling techniques, in 2021 in Kanyakumari, India. The tools used for data collection was interview schedule composed of demographic and obstetrical variables, anxiety scale, and labor outcome checklist. Collected data is entered in Excel and analyzed in SPSS 20 using appropriate descriptive (f,%) and inferential statistics (Independent ‘t’ test). Results: Regarding anxiety pretest anxiety scores did not differ significantly between the experimental and control group (p=1.000). After doula care, in the post-test, there was a significantly low anxiety level in the experimental group as compared to the control group (P & lt; 0.001). Conclusion: Doula care is effective in the reduction of anxiety and promotes labor outcomes during childbirth.
Published by: Joylet Paulian, Dr. Arzta Sophia R., Dr. Santhi Appavu
Author: Joylet Paulian
Paper ID: V7I5-1163
Paper Status: published
Published: September 4, 2021
Building an Intelligent Agent to play Flappy Bird using NEAT
Games are an efficient way to measure the progress of AI. Artificial intelligence has been making rapid advances in recent years, and one way to see how it is progressing is by playing games. Go, Atari2600 and Chess are some AI agents which even defeated human players. These AI agents require or have a training stage involved. In this paper, we propose a training strategy to develop an Artificial Intelligence agent using the NeuroEvolution of Augmenting Topologies (NEAT) algorithm to play the Flappy Bird Game. NEAT basically implements a genetic algorithm that generates ANNs. Our agent learns to safely dodge all the barriers and flap its way through them, optimally playing the famous “Flappy Bird” game.
Published by: Pratik Manoj Desai, Rhugaved Rajendra Narmade
Author: Pratik Manoj Desai
Paper ID: V7I5-1155
Paper Status: published
Published: September 4, 2021
