Emerging Trends in Films in Creating Eco awareness among People
Movies have become an integral part of human life, from telling stories to emphasizing rituals, culture, and history, having mentioned that cinemas are milestones when an awareness quotient comes into the picture. Films are the most impactful channel to spread the news as they have both audio and video content which would help to bring a massive response from a larger audience. A film is therefore a wonderful and most effective medium to create an eco-awareness among all walks of people in society. As we are already facing depletion in the ozone layer, global warming and environmental problems like acid rain, air pollution, water pollution, etc. can affect every human, animal, and nation on this planet. The researchers strongly believe that cinemas, web series, documentaries, etc. play a vital role in awareness creation among people. The current comprehensive research study says that the impact is more when it comes to cinema as compared to other mediums. The present research work is focusing on the following objectives like (i) analyze the impact of movies in creating eco-awareness, (ii) doing a comparative analysis of the impact of the movies created, (iii) suggesting policies that can enhance the effects of movies on the respective theme. Three movies from the International and three movies from the Indian Film Industry are chosen for the study. The research is conducted on the basis of reviews from IMDB (Internet movie database). The study shows that the movies under review had a positive effect on society in creating eco-awareness. According to current research, it can be said that movies play a crucial role in creating eco-awareness.
Published by: Niji Nelson, Dr. Jaya Patil
Author: Niji Nelson
Paper ID: V7I3-2093
Paper Status: published
Published: June 24, 2021
GEVAS: GPS based emergency vehicle detection system
Emergency vehicles being stuck in traffic jams and various kinds of accidents caused due to speeding first response vehicles has become a very common scene in our country lately. The increased traffic congestion and underdeveloped roads along with the poor traffic regulation system have resulted in emergency vehicles like ambulances not reaching their required destination in time. So, the idea emphasizes mainly enabling emergency vehicles to reach their required destination safe and smooth within the least possible time on any road traffic conditions. This could be implemented by developing a GPS based device which notifies all other vehicles so that they can move out of the way in advance avoiding accidents and unnecessary traffic jams and clearing path for the emergency vehicle. The notification is either visual/sound based and the system is placed inside every vehicle so that the alert precedes the conventional siren alert system.
Published by: Laxman Krishnan, Pankaj Madhu, C. Nirupama, Devi Saranya R. S., Evankumar G.
Author: Laxman Krishnan
Paper ID: V7I3-2101
Paper Status: published
Published: June 24, 2021
Design and Analysis of selective components of the roving machine
There are numbers of parts in Roving Machine some of them are Aprons (top and bottom), Spacer, Condenser, Flyer. In this report, we have analyzed the functions of this component and designing of a roving machine. The effect of process variables like:-lap hank, card draft, draft/doublings, and drafts at speed frame, ring frame, rotor, and air-jet spinning machine on packing density parameters of respective technology yarn was Analyzed The effect of noise variables were also accounted for. The trends of change in packing density with process variables are opposite to those of yarn diameter and helix angle of the ring, rotor, and air-jet yarns studied. The packing density is found to be the highest in air-jet yarn and the lowest in rotor yarn. An increase in the draft in air-jet spinner and decrease in rotor spinner increase packing density of the respective yarns. The change in noise variables does affect the packing density parameters of yarns.
Published by: Adnan Shaikh, Kedar Kulkarni, Gajanan Khadse, Aniket Gurav, Siddharth Chilvery
Author: Adnan Shaikh
Paper ID: V7I3-2062
Paper Status: published
Published: June 24, 2021
The injustice and oppression in Mulk Raj Anand’s Novel- Untouchable
Problem of untouchabilty is still prevalent in the society and Mulk Raj Anand through his novel Untouchable brings to light the sorrows and sufferings that high caste Hindus inflicted on the untouchables. Mulk Raj Anand's Untouchable, is more compact than his other novels. Mulk Raj Anand has a special place in Indian literature in English. He is a committed writer, a novelist with the purpose. His purpose is to throw light on the sufferings, misery, despair, wretchedness of the poor, which result from the exploitation of the downtrodden by the caste Hindus and capitalists. Through his art, he has rendered valuable service by highlighting the plight of the underprivileged class of the Indian society, by enlisting our sympathy for them and thereby paving the way for social reform. His themes and linguistic experiments have carved out a special niche for himself in the Indian social and cultural field. They are unique in their depiction of the exploitation of the poor and the downtrodden in the Indian society. The central characters in the novels are socially segregated, humiliated, physically and psychologically exploited by the caste and class ridden society. Anand's focus on the untouchables, coolies, plantation labourers, workers in the factories, destitute, and the neglected show his humanitarian nature, true love and compassion leading to social justice and freedom. The novel Untouchable, published in 1935, centres around a sweeper boy, Bakha. The eighteen year boy Bakha, son of Lakha, the jamadar of sweepers is a child of the twentieth century, and the impact of new influences reverberates within him. Keywords: Mulk Raj Anand, Untouchable, underprivileged, humanitarian, downtrodden, exploited, justice
Published by: Nafsa Ajmi
Author: Nafsa Ajmi
Paper ID: V7I3-2002
Paper Status: published
Published: June 24, 2021
Credit card fraud identification using machine learning
Today technology is increasing at a very rapid pace, which can be used for good as well as for bad purposes. So with this growing technology e-commerce and online transactions grew up which mostly contain transactions through credit cards. Credit cards help People to enjoy buy now and pay later for both online and offline purchases. It provides cashless shopping at every shop in all countries. As the usage of credit cards is increasing more, the chances of credit card frauds are also increasing dramatically. The credit card system is most vulnerable to frauds. These credit card frauds cost financial companies and consumers a very huge amount of money annually, fraudsters always try to find new methods and tricks to commit these illegal and outlaw actions. Online transaction fraud detection is the most challenging issue for banks and financial companies. So it is much essential for banks and financial companies to have efficient fraud detection systems to reduce their losses due to these credit card fraud transactions. Various approaches have been found by many researchers to date to detect these frauds and to reduce them. Comparison of Local Outlier Factor and Isolation Factor algorithms using python and their detailed experimental results are proposed in this paper. After the analysis of the dataset, we got an accuracy of 97% by the Local Outlier Factor and 76% by Isolation Forest.
Published by: Aishwarya Shirole, Riya Thakur, Yash Singh, Harsh Singh
Author: Aishwarya Shirole
Paper ID: V7I3-2083
Paper Status: published
Published: June 24, 2021
An efficient optimized multi-kernel support vector machine-based brain tumor classification and segmentation in MRI
Magnetic resonance (MR) imaging has been playing a vital role in neuroscience research to examine brain conditions related to normal and abnormal brain structures and functions in vivo. In previous years, MRI is observed to play an important role in brain abnormalities research in determining the size and location of affected tissues. MRI Image segmentation and classification refers to a process of assigning labels to a set of pixels or multiple regions. It plays a major role in the field of biomedical applications as it is widely used by radiologists to segment the medical images input into meaningful regions. Thus, various segmentation techniques in medical imaging depending on the region of interest had been proposed. Medical image segmentation problems have been approached with several solution methods by different ranges of applicability such as Region Growing, Self-Organizing Map (SOM), and Fuzzy c-Means (FCM). Some recent progress has been made to create semi-supervised (based on user interaction) or supervised variational methods. In the last decades, many methods have been proposed to segment the brain tumor of MR images, such as neural networks, finite Gaussian mixture model, knowledge-based methods, atlas-based method, active contour model, level set methods, and outlier detection. However, the segmentation of medical imagery remains a challenging problem due to the complexity of the images. Brain tissue is a particularly complex structure and its segmentation is an important step for studies in temporal change detection of morphology. The success of MRI in the detection of brain pathologies is very encouraging. However, diagnosis and locations of abnormality are made manually by radiologists. It consumes valuable human resources, is error sensitive, and makes it prone to error.
Published by: P. Harshavardhan, M. Rishika Reddy
Author: P. Harshavardhan
Paper ID: V7I3-2103
Paper Status: published
Published: June 24, 2021
