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Research Paper

Size-specific variation in the rate of oxygen consumption, ammonia excretion, and O: N ratio of freshwater bivalve lamellicorns marginalis during the season of monsoon

Malacology means the study of molluscan animals and also conchology means the study of the molluscan shell. Body mass is one of the best known and most studied characteristics of aquatic animals on scaling of metabolic rates. We studied here how size-specific variation in the rate of oxygen consumption, ammonia excretion, and O: N ratio in Freshwater Bivalve Mollusc Lamellidens marginalis species in an attempt to know how size-specific variation affects their metabolism. The freshwater bivalve molluscs were chosen for experimental work from Bhima River at Siddhatek in August and September for the period of monsoon season with body size i.e. small (75-79 mm in shell-length) and large (90-93 mm in shell-length). In current work reported that the rate of oxygen consumption and O: N ratio was high in the small body-sized bivalve mollusc but the rate of ammonia excretion was low in small body-sized bivalves compared to large ones. The results are discussed in the flush of metabolic processes in fresh-water bivalve molluscs.

Published by: Pritesh Ramanlal Gugale

Author: Pritesh Ramanlal Gugale

Paper ID: V7I4-1320

Paper Status: published

Published: July 12, 2021

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Research Paper

Helping business owners to find potential competitors

Opening a business in any place is not an easy task as it needs lots of things to be considered. One should consider its competitors before opening a business. This project is one attempt to help those business people to find their competitors. In this project, a taco palace is planned to open in the city of Monterrey, Mexico. Here the attempt is to find a neighborhood with not too many competitors with enough customers. To find the neighborhood, considering the latitude and longitude values of the city of Monterrey, Mexico, and can be able to locate the best place to open the restaurant. In this project Foursquare API is used to explore the neighborhoods and get the most common restaurants near that place and using this function clusters can be grouped. For clustering, a K-means clustering algorithm is used. Clusters are used to know the similar business in that areas. Clusters group the similar business and list out all its names. To visualize the neighborhoods Folium library is used.

Published by: Suraksha S. S., Darunya B. C., Priya D., Anisha B. S.

Author: Suraksha S. S.

Paper ID: V7I4-1279

Paper Status: published

Published: July 12, 2021

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Research Paper

Social Cause Marketing (Pink Capitalism) and its impact on consumers’ brand preferences

As its name implies, cause-based marketing is the process of marketing a specific idea, cause, or goal, rather than a specific business, product, or service. These initiatives are often partnerships between a nonprofit organization – typically the driving force behind the” “messaging of the campaign itself – and either an ad agency or corporate partner, which typically handles the execution of the campaign. Although cause-based marketing campaigns can focus predominantly on PPC or social advertising, these campaigns can and often do incorporate” elements of guerilla marketing in their execution. Trying to grab people’s attention is no easy feat these days, and as such many organizations adopt more creative ways of getting their message out, as we’ll see later on. Many cause-based marketing campaigns are organic offshoots of grassroots marketing efforts, which also tend to focus on causes. This paper will discuss thoroughly cause-related marketing through the lenses of Pink Capitalism. It will also discuss how pink capitalism is not entirely an ethically incorrect concept and focus on the silver lining of the same, which would benefit both the NGO as well as the corporations.

Published by: Saniya Savant

Author: Saniya Savant

Paper ID: V7I4-1276

Paper Status: published

Published: July 12, 2021

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Research Paper

Development of a home security Robot using Deep Learning and IoT

The major problem in every urban city is the lack of security to residential areas. The number of thefts, electricity and food wastage at homes in urban areas increase every year due to human error. As per the National Crime Records Bureau (NCRB), 2,44,119 cases of robbery, theft, and burglary took place in residential premises in 2019. Also, electricity consumption in Indian homes has tripled since 2010. In 2019, an urban Indian household consumed about 90 units (kWh) of electricity as a monthly average which is one-third of the monthly world average. To solve these issues, we have proposed an idea of a “Home Security Robot” for a smart city using AI. The Home Security Robot will help in eliminating the reliance on security guards and will effectively monitor everything in the house (if there are any gas leakage, fridge malfunctions, unnecessary electricity wastage, indoor air quality and any unknown movements inside the house). If the owner is under attack, he/she can shout out “HELP” or “SAVE ME "so that the robot can take in the voice command to automatically call the police. The navigation part is done by Arduino and Bluetooth RC Controller App. There are 2 parts (Face Detection & Recognition using Raspberry Pi and IoT system using BOLT module with sensors). The first part has three python programs used for facial detection and recognition using OpenCV with Haar Cascade Classifier and LBPH algorithm. The first program (Face Dataset) is used for collecting images of known users and storing it in a database using Haar Cascade Classifier. The second program (Face Training) is used to train the stored images using LBPH algorithm so the model can distinguish between the users whose faces are stored in database and then these trained images are stored in the trainer.yml file. The third program (Face Recognition) is used to read the trained images stored in the trainer.yml file and then uses Haar Cascade Classifier to recognize the detected face and identifies whether the face belongs to a user or an intruder. The IoT system with the help of BOLT module helps in checking the temperature in the room and checking if any unnecessary lights are on in the room. If the room temperature is outside the safe range specified or if any lights are on, owner will get an alert via SMS.

Published by: Shravan Aruljothi, Sharad Dewanand Parate, Harshit S., Nehal Dinesh Andani

Author: Shravan Aruljothi

Paper ID: V7I4-1269

Paper Status: published

Published: July 12, 2021

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Survey Report

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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