Volume 10, Special Issue
Vighnaharata Trust's Shivajirao S. Jondhale College of Engineering & Technology
April 2024

  • A Survey On Data Integrity Checking and Enhancing Security for Cloud to Fog Computing Dr. Shital Agrawal, Mr. Digvijay Devare, Mr. Shubham Gotarne, Miss. Priti Patil

    In accordance with its ability to supply services to users via the internet at a lower cost, cloud computing is becoming more and more essential in the computer world. Cloud service providers (CSPs) relieve clients of the hassle of managing their data and provide massive amounts of storage space at very low costs. The lack of transparency in the operational details may make the CSPs untrustworthy

    A Survey On Data Integrity Checking and Enhancing Security for Cloud to Fog Computing

    Dr. Shital Agrawal, Mr. Digvijay Devare, Mr. Shubham Gotarne, Miss. Priti Patil

    A Survey On Data Integrity Checking

  • A COMPARATIVE ANALYSIS OF DEEP NEURAL NETWORK FOR BRAIN TUMOR DETECTION Dr.Sneha Jondhle, Mr.Harsh Jondhle, Mr. Pratik Ashtikar, Mr. Ruturaj Chatuphale, Mr. Prathamesh Mayekar

    The rise of powerful technologies in medicine has revolutionized disease detection, classification, and identification. This has significantly streamlined diagnosis, providing healthcare professionals with invaluable tools to improve patient outcomes. Identifying brain’ tumors’ poses a substantial challenge in the medical realm, as early detection is crucial for selecting optimal treatment

    A COMPARATIVE ANALYSIS OF DEEP NEURAL NETWORK FOR BRAIN TUMOR DETECTION

    Dr.Sneha Jondhle, Mr.Harsh Jondhle, Mr. Pratik Ashtikar, Mr. Ruturaj Chatuphale, Mr. Prathamesh Mayekar

    A COMPARATIVE ANALYSIS OF DEEP

  • Predicting Patient Data Like Heart Problems, Diabetes, Brain Tumor, And NLP Based for Drugs Suggestion Based On Cloud Prof. Vishal Shinde, Mr. Prathamesh Sunil Sonawane, Mr. Santosh Laxman Narvekar, Mr. Ajinkya Ashok Redekar

    Early diagnosis of the disease is important for effective treatment and betterpatient outcomes. This work offers cloud-based multiple predictions using machine learning algorithms. The system aims to predict three diseases: heart disease, diabetes, andbrain disease. Supervised machine learning has been developed to predict heart disease and diabetes. This model was studied on a large database of patients

    Predicting Patient Data Like Heart Problems, Diabetes, Brain Tumor, And NLP Based for Drugs Suggestion Based On Cloud

    Prof. Vishal Shinde, Mr. Prathamesh Sunil Sonawane, Mr. Santosh Laxman Narvekar, Mr. Ajinkya Ashok Redekar

    Predicting Patient Data Like Heart

  • Drug Recommendation System Based On Sentiment Analysis of Drug Reviews Using Machine Learning Dr. Sneha Jondhle, Mr. Harsh Jondhle, Miss. Bhavika Borade, Miss. Sakshi Bachhav, Miss. Urmila Bokad

    The absence of appropriate tools and medications, as well as the scarcity of professionals and other healthcare workers,is at an all-time high since the coronavirus first appeared. There are many deaths as a result of the medical community as a whole being in crisis. Individuals started to take treatment on themselves without an appropriate counselling since it was unobtainable, leading

    Drug Recommendation System Based On Sentiment Analysis of Drug Reviews Using Machine Learning

    Dr. Sneha Jondhle, Mr. Harsh Jondhle, Miss. Bhavika Borade, Miss. Sakshi Bachhav, Miss. Urmila Bokad

    Drug Recommendation System

  • E-Commerce Recommendation System Model Based On Cloud Computing Dr. Shital Agrawal, Mr. Chandan Mali, Mr. Nilesh Pawar, Mr. Suyash Vishwasrao

    As the company grows, the traditional offline sales model is no longer sufficient. Adapting to the digital era, companies need to create their online e-commerce platforms. The complex nature of e-commerce information is constantly increasing, overwhelming users with vast amounts of product data. Establishing effective customer relationships amidst this data overload proves challenging for merchants

    E-Commerce Recommendation System Model Based On Cloud Computing

    Dr. Shital Agrawal, Mr. Chandan Mali, Mr. Nilesh Pawar, Mr. Suyash Vishwasrao

    E-Commerce Recommendation System

  • Whatsapp Chat Analysis Based On NLP Using ML Dr.Sneha Jondhle, Mr.Harsh Jondhle, Miss.Insha Mulla, Mr.Ibad Nachan, Mr.Prashik Tayde

    WhatsApp has an extremely user-friendly user interface, which is one of its main features. WhatsApp is the first messaging app that springs to mind when you want to connect or interact with someone. Everyone finds it convenient to communicate via WhatsApp. To send a message, just open the app, choose Contact, and start typing. You're done there. The user can utilize WhatsApp chats to examine

    Whatsapp Chat Analysis Based On NLP Using ML

    Dr.Sneha Jondhle, Mr.Harsh Jondhle, Miss.Insha Mulla, Mr.Ibad Nachan, Mr.Prashik Tayde

    Whatsapp Chat Analysis Based On NLP

  • An Analytical Survey for Improving Authentication Level in Cloud Computing Prof. Dr. Shital Agrawal, Mr. Sahil Avinash Wagh, Mr. Shreyas Kiran Badgujar, Mr. Tanay Subhash Chhabhaiya

    Cloud computing is a on-demand network. Cloud computing is very affordable and rapidly developing technology. In this type of network, you can approach your data anytime, anywhere as long you are a true cloud computing user. Data storage in a cloud computing environment is secure. In the cloud computing environment, there are no time and location restrictions on data usage so long as you have

    An Analytical Survey for Improving Authentication Level in Cloud Computing

    Prof. Dr. Shital Agrawal, Mr. Sahil Avinash Wagh, Mr. Shreyas Kiran Badgujar, Mr. Tanay Subhash Chhabhaiya

    An Analytical Survey for Improving

  • A Secure G Cloud Based Framework for Government Healthcare Services Prof.Kanchan Umavane, Mr. Sachin Alam, Mr. Manish Bhoir, Mr. Aniket Dhasade

    The healthcare industry witnesses a rising need for and acceptance of cloud-based software development to address and meet the present and forthcoming requirements in healthcare provision. This initiative presents attributes including a versatile, safeguarded, cost-efficient, and privacy-conscious cloud-based framework tailored for healthcare settings. It introduces a resilient and efficient framework

    A Secure G Cloud Based Framework for Government Healthcare Services

    Prof.Kanchan Umavane, Mr. Sachin Alam, Mr. Manish Bhoir, Mr. Aniket Dhasade

    A Secure G Cloud Based Framework

  • Drone Detection in Long-Range Surveillance Videos Dr.Sneha Jondhle, Mr.Harsh Jondhle, Mr. Raj Chauhan, Mr. Omkar Kalvitkar, Mr. Pankaj Mandal

    The use of drones is increasingly apparent.in contemporary society is evident the In recent years, significant progress in drone technology has enabled drones to execute increasingly complex tasks. The escalating proliferation of drones within the national airspace,encompassing both recreational and commercial applications, has spurred concerns regarding potential misuse. Instances such as smuggling

    Drone Detection in Long-Range Surveillance Videos

    Dr.Sneha Jondhle, Mr.Harsh Jondhle, Mr. Raj Chauhan, Mr. Omkar Kalvitkar, Mr. Pankaj Mandal

    Drone Detection in Long-Range

  • Development of React Component Library Prof. Kanchan Umavane, Emaaz Khot, Naufil Shemle, Vivek Varkute

    Using contemporary JavaScript libraries such as REACT, it is crucial to divide our user interface into more small, more manageable components that are readily reusable and distributable while dealing with vast codebases. In front-end Development mostly each project require similar component created over and over. Then iterate the projects very quickly then make a lot of components to satisfy

    Development of React Component Library

    Prof. Kanchan Umavane, Emaaz Khot, Naufil Shemle, Vivek Varkute

    Development of React Component Library

  • A Framework to Make Voting System Transparent Using Blockchain Technology Prof. Satish Manje, Mr. Gaurav V. Jadhav, Mr. Aakash L. Desale, Mr. Nitesh N. Sawardekar

    The Indian voting system is now inefficient and open to outside interference. Voter ID cards are the only thing that are subject to security checks, and these days, many people can fake them. It is sluggish and can take a time to hand count the votes. Polling booths are taken and most ballots are frequently destroyed in certain remote regions with no security. The main goal is to address issues

    A Framework to Make Voting System Transparent Using Blockchain Technology

    Prof. Satish Manje, Mr. Gaurav V. Jadhav, Mr. Aakash L. Desale, Mr. Nitesh N. Sawardekar

    A Framework to Make Voting System

  • Car Traffic Sign Recognition Using Convolutional Neural Network CNN Prof.Vishal Shinde, Mr. Pratham Vishwakarma, Miss.Ankita Vishe

    In this paper recognition of traffic signs (TSR) is a crucial part of driving. assistance systems (DAS) and autonomous vehicles (AVs), as they provide essential information about road conditions and regulations. However, identifying traffic signals in various environments and scenarios is a difficult task that requires robust and efficient methods. This paper proposes a car roadsign identification

    Car Traffic Sign Recognition Using Convolutional Neural Network CNN

    Prof.Vishal Shinde, Mr. Pratham Vishwakarma, Miss.Ankita Vishe

    Car Traffic Sign Recognition

  • Spammer Detection and Fake User Identification On Social Media Prof. Satish Manje, Mr. Shubham Ramchandra Vishe, Mr. Nitesh Sainath Vishe, Mr. Amol Shivaji Birari

    Social media platforms have millions of users worldwide. Users interactions on social media network such as Facebook and Twitter have a significant influence on daily life, often with unintended consequences. The popular social platforms have become a objective for spammers that distribute a great deal of harmful and irrelevant content. For instance, Twitter has grown to be among the most

    Spammer Detection and Fake User Identification On Social Media

    Prof. Satish Manje, Mr. Shubham Ramchandra Vishe, Mr. Nitesh Sainath Vishe, Mr. Amol Shivaji Birari

    Spammer Detection and Fake

  • Detection of Cyberbullying On Social Media Using Machine Learning Prof.Vishal Shinde, Ms. Renuka Vikas Hase, Ms. Priti Pandharinath Chaudhari, Ms. Nayna Dattaram Vashiwale

    Cyberbullying is one of the biggest problems on the internet, affecting adults and teens alike. It has led to suicide and sadness. The need for content regulation on social media platforms is growing. research that follows makes use of natural language processing (NLP) and machine learning (ML) to create a model to detect cyberbullying within text data. The data comes from two different categories

    Detection of Cyberbullying On Social Media Using Machine Learning

    Prof.Vishal Shinde, Ms. Renuka Vikas Hase, Ms. Priti Pandharinath Chaudhari, Ms. Nayna Dattaram Vashiwale

    Detection of Cyberbullying On Social

  • Machine Learned Classifiers for Trustworthiness Assessment of Web Information Contents Prof. Satish Manje, Mr. Pranjal Harishchandra Gadge, Mr. Abhishek Laxman Kannam, Mr. Mayur Sanjay Mote

    Human society has always included social networking, information sharing, knowledge transfer, conversations about current events, etc. People are depending more and more searching for information online due to the rapid advancements in technology as well as the fast-paced nature of life; thus, digital platforms have assumed an important part for social interactions. This has caused the spreading of fake

    Machine Learned Classifiers for Trustworthiness Assessment of Web Information Contents

    Prof. Satish Manje, Mr. Pranjal Harishchandra Gadge, Mr. Abhishek Laxman Kannam, Mr. Mayur Sanjay Mote

    Machine Learned Classifiers

  • Implementation of Greyscale Normalization Using ML for Biometrics in CNN Dr. Sneha Jondhle, Mr. Harsh Jondhle, Mr.Yogesh Shete, Ms.Tanushree Adhikari, Mr. Suraj Tiwari

    These days, machine learning is a popular field and is widely recognized as an application of artificial intelligence (AI). Secure mathematical algorithms are used in machine learning to build computers in a constructive manner. The algorithms use specific arithmetical techniques to obtain the freedom of a participated value and estimate the outputfor this. The field of AI has achieved

    Implementation of Greyscale Normalization Using ML for Biometrics in CNN

    Dr. Sneha Jondhle, Mr. Harsh Jondhle, Mr.Yogesh Shete, Ms.Tanushree Adhikari, Mr. Suraj Tiwari

    Implementation of Greyscale Normalization

  • Bone Deformity Identification Using Machine Learning Dr.Sneha Jondhle, Mr.Harsh Jondhle, Mr. Sufiyan Surve, Mr.Tausif Ansari

    The effectiveness of machine learning algorithms in medical imaging has underscored the necessity for proficiently trained models to expedite and optimize their application within the medical domain. This project proposes a methodology for identifying bone fractures using machine learning algorithms, aiming to alleviate the workload for orthopedic professionals. Leveraging machine learning

    Bone Deformity Identification Using Machine Learning

    Dr.Sneha Jondhle, Mr.Harsh Jondhle, Mr. Sufiyan Surve, Mr.Tausif Ansari

    Bone Deformity Identification

  • An Efficient Approach For Interpretation Of Indian Sign Language Using Machine Learning Dr.Sneha Jondhle, Mr.Harsh Jondhle, Ms. Laxmi Ramkrishna Sahu, Ms. Swati Suhas Rodge, Mr.Parth Kirti Panchal

    One way to communicate nonverbally is via sign language. Individuals with hearing impairments utilizing sign language as a means of communicating their emotions. However, because they are not familiar with the meaning of the sign language movements, individuals typically have trouble understanding the hand signals used by those with unique challenges. When a person with speech or hearing impairments

    An Efficient Approach For Interpretation Of Indian Sign Language Using Machine Learning

    Dr.Sneha Jondhle, Mr.Harsh Jondhle, Ms. Laxmi Ramkrishna Sahu, Ms. Swati Suhas Rodge, Mr.Parth Kirti Panchal

    An Efficient Approach For Interpretation

  • Multilingual Neural Machine Translation System for Indic Languages Prof. Vishal R. Shinde, Mr. Pratham Agawane, Miss. Nisha Sonawane, Mr. Sanket Waghmare

    This research presents an LSTM-based language translation model utilizing the pre-trained Google/MT-small model within the transformer’s architecture. The model is designed for bidirectional translations between various foreign languages and Indian languages. Three key features enhance its functionality: Text Translation, Image Translation, and Video Translation. To enhance user interaction

    Multilingual Neural Machine Translation System for Indic Languages

    Prof. Vishal R. Shinde, Mr. Pratham Agawane, Miss. Nisha Sonawane, Mr. Sanket Waghmare

    Multilingual Neural Machine Translation

  • Evaluation Based Approaches Liver Diseases Prediction Using Machine Learning Algorithm Dr.Sneha Jondhle, Mr.Harsh Jondhle, Mr. Devesh Pandurang Patil, Mr. Ajay Shivaji Bangar, Mr. Subodh Manik Gawali

    One of the most important aspects of human existence is the well-being of those free of liver tumors. Consequently, early diagnosis of liver illness is essential for improved therapy. It is extremely challenging for medical professionals to diagnose an ailment in its early stages based on minor symptoms. For many, the indicators become apparent only after it is too late. In order to combat this epidemic

    Evaluation Based Approaches Liver Diseases Prediction Using Machine Learning Algorithm

    Dr.Sneha Jondhle, Mr.Harsh Jondhle, Mr. Devesh Pandurang Patil, Mr. Ajay Shivaji Bangar, Mr. Subodh Manik Gawali

    Evaluation Based Approaches Liver Diseases

  • International Stock Index Prediction Using Artificial Intelligence Prof. KANCHAN UMAVANE, Ms. Kalyani Patil, Mr. Eknath Vishe

    The stock exchange is one of the best channels for financial development requires a high accuracy prediction of the trades. This subject needs some technical skills and experience in order to accomplish best result. This project is a tailored Python console software that uses Networks of neural sensors and artificial intelligence (AI) to predict future prices in a qualified and quantized manner

    International Stock Index Prediction Using Artificial Intelligence

    Prof. KANCHAN UMAVANE, Ms. Kalyani Patil, Mr. Eknath Vishe

    International Stock Index Prediction

  • Analysing Cyber Hacking Violations Using RPM for Risk Mitigation Prof. Vishal R. Shinde, Mr. Vaibhav Keni, Ms. Anushka Sapale, Ms. Khushi Bhavsar

    In this paper, one key technique for improving our comprehension of the evolution of the threat scenario is the analysis of cyber event data sets. Numerous investigations need to be conducted because this is a relatively new research issue. this research presents a statistical examination of a data collection of breach incidents including cyber hacking activities spanning 12 years (2005–2017)

    Analysing Cyber Hacking Violations Using RPM for Risk Mitigation

    Prof. Vishal R. Shinde, Mr. Vaibhav Keni, Ms. Anushka Sapale, Ms. Khushi Bhavsar

    Analysing Cyber Hacking Violations

  • Research On Railroad Turnout Fault Diagnosis Based On Support Vector Machine Prof. Satish Manje, Mr. Akshay Bhau Paradhi, Mr. Pratik Kailas Bhere, Mr. Bhargav Deepak Taware

    The dependability of turn-out is essential to the efficiency and safety of railroad transportation, as it serves as a vital signaling device for the secure functioning of train traffic. Turnout maintenance is mostly dependent on experience and pertinent information for recurring maintenance. This approach has numerous drawbacks, including imprecise fault location, sluggish fault investigation

    Research On Railroad Turnout Fault Diagnosis Based On Support Vector Machine

    Prof. Satish Manje, Mr. Akshay Bhau Paradhi, Mr. Pratik Kailas Bhere, Mr. Bhargav Deepak Taware

    Research On Railroad Turnout Fault

  • Weapon Detection Using Artificial Intelligence & Deep Learning for Security Applications Prof. Kanchan Umavane, Mr. Anil Waghmare, Miss. Tejaswini Rathod, Miss. Damini Lad

    Within this project, Due to the fact that crime tends to increase at major events or in isolated, unsettling areas, security is always the first priority in every industry involved in this project. Computer vision addresses a variety of problems and is widely utilized in anomaly detection and monitoring. Video surveillance systems that can recognize and analyse situations and unexpected actions

    Weapon Detection Using Artificial Intelligence & Deep Learning for Security Applications

    Prof. Kanchan Umavane, Mr. Anil Waghmare, Miss. Tejaswini Rathod, Miss. Damini Lad

    Weapon Detection Using Artificial