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Research Paper

Improvised approach to Deepfake detection

Deepfakes are realistic, human-synthesized videos that are incredibly simple to produce thanks to the advent of sophisticated algorithms fueled by advances in the field of deep learning. Deepfakes are being used to create fictitious news stories about terrorism, politics, and retaliation in order to incite societal unrest. The development of efficient techniques for identifying deepfakes is imperative, given the mounting concerns surrounding them. Our work in this field offers a brand-new deep learning-based method that effectively distinguishes between authentic videos and artificial intelligence-generated phony ones. Our technique can identify deepfakes that are both reenactments and replacements. To counter the threat posed by artificial intelligence (AI), we suggest a system that makes use of AI. In order to train an InceptionV3 model to categorize films as either real or manipulated, depending on whether they have undergone any kind of alteration, this method uses an MTCNN neural network to extract frame-level information. We assess our method on a large-scale balanced and mixed data set in order to mimic real-time scenarios and improve the model’s performance on real-time data. This dataset was painstakingly created by combining multiple available datasets.

Published by: Lipika Chadha, Hiya Kulasrestha, Vishesh Bhargava, Varun Jindal

Author: Lipika Chadha

Paper ID: V9I6-1183

Paper Status: published

Published: November 25, 2023

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Research Paper

Efficient establishment of foreign manufacturing units in India: utilizing operation research approaches amidst changing import regulations

With increasing regulatory policies from countries, companies have to find an efficient way to set up their manufacturing units in other countries as well. Currently majority of the companies set up their manufacturing units in China as they are able to manufacture products at a cheaper price, however this will not work for the long term, as if the companies intend to sell their products in countries with restrictive import policies, they will have to diversify and set up their manufacturing units in that/those countries as well. To select the right location for setting up a manufacturing unit, a company must look into what we classified as Internal and External factors which we will be going in-depth further into the research paper. This research paper sets out to provide a framework to those companies that are looking to set up their own manufacturing units in a country using operation research tools such as Linear programming which includes visualizing the “Internal” factors as a transportation problem. One probable limitation of this research paper is assuming that the current demand for the products in the economy will remain equal to the forecasted demand or demand in the coming years after setting up the manufacturing units, demand will be used in the linear programming problems later in this research paper.

Published by: Bhuvan Mahesh, Ashray Kamath, Bharath Ram, Diya Jindal, Aditya Maurya, Atharva Kasat

Author: Bhuvan Mahesh

Paper ID: V9I6-1158

Paper Status: published

Published: November 16, 2023

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Research Paper

Optimizing waste recycling through data science: a deep learning approach with Tensorflow

The intricate relationship between recycling practices and the generation of solid waste emphasizes the multifaceted character of sustainable waste management. A comprehensive comprehension of these dynamics is crucial for formulating specific interventions and policies that optimize the positive effects of recycling on our environment. This research explores the application of deep learning, specifically utilizing TensorFlow, in the domain of waste classification for enhanced waste recycling. The study focuses on the efficient categorization of diverse waste materials, including cardboard, glass, trash, metal, and plastic, through the implementation of advanced neural networks. By leveraging TensorFlow's capabilities, our research demonstrates the successful development and deployment of deep learning models that exhibit accurate and reliable waste classification. The utilization of deep learning model was able to select accurately the most important types of garbage worthy for recycling processes. And not only streamlines recycling processes but also addresses the environmental challenges associated with inefficient waste management. The findings finally highlight the transformative potential of integrating cutting-edge technologies into waste sorting systems, paving the way for a more sustainable and eco-friendly approach to waste disposal. This research contributes to the ongoing efforts in environmental conservation by presenting a viable solution to enhance waste recycling practices through the power of deep learning.

Published by: Oghenetega Adogbeji

Author: Oghenetega Adogbeji

Paper ID: V9I6-1167

Paper Status: published

Published: November 16, 2023

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Review Paper

Cloud Migration Challenges for IP PBX in Critical Hospital Environments

Migrating to the cloud for IP PBX systems in critical environments like hospitals is a transformative endeavor offering significant benefits, but it also introduces a unique set of challenges. This article delves into the complexities associated with this migration, addressing key concerns such as data security and privacy, reliability, network connectivity, cost management, legacy system integration, compliance with healthcare regulations, and user training and adoption. By proactively recognizing and effectively tackling these challenges, hospitals can harness the potential of cloud-based IP PBX systems to enhance patient care, streamline operations, and maintain the highest standards of security and reliability.

Published by: Saju Thanislas

Author: Saju Thanislas

Paper ID: V9I6-1153

Paper Status: published

Published: November 16, 2023

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Review Paper

Assessing the effects of social isolation on elderly individuals

Loneliness and social isolation, prevalent among older adults, have profound and often interconnected effects on physical and mental health, leading to increased mortality, depression, and cognitive decline. This paper reviews the literature on social isolation and loneliness in seniors. Key factors contributing to social isolation include the death of a spouse, physical relocation, retirement, changes in family structures, changes in mobility, chronic health problems, household income, race, ethnicity, gender, and sexual orientation. These factors have varying impacts on the social well-being of older adults. Research suggests that subjective social isolation has a stronger link to mental health, while objective social isolation is more strongly related to physical health. Both social isolation and loneliness are associated with higher rates of depression and psychological distress among seniors. Understanding social isolation and loneliness in seniors is crucial for developing targeted interventions and support systems to enhance the well-being of this growing demographic.

Published by: Lakshita Popli

Author: Lakshita Popli

Paper ID: V9I6-1136

Paper Status: published

Published: November 13, 2023

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Survey Report

Impact of marketing mix on the retailers’ preference towards cookies

In this research, the researchers try to find the retailer preference towards the biscuits industry in Chennai. The main objective is, to find the retailer's satisfaction, measuring the effect of promotional mix and retailers’ perception towards biscuits and cookies. The data have been collected using a structured Questionnaire from the 125 retailers and a convenience sampling technique method is being used. The research design used in this study is Descriptive in nature. In this research, the SPSS software is used to analyze Data. The brand is the influence factor in purchasing biscuits and cookies. Retailers are satisfied with the cookie's quality and brand name of the biscuits, majority of the retailers have maintained a smooth relationship with their dealers.

Published by: Ivan Kenny Raj L., Ramesh Babu S., S.M. Atchaya Eswari.

Author: Ivan Kenny Raj L.

Paper ID: V9I6-1145

Paper Status: published

Published: November 8, 2023

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