Volume 08, Issue 01, APR 2022 Special Issue

  • An Application of Deep Learning Algorithm for Automatic Detection of Unexpected Accidents Under Bad CCTV Prof.Vishal Shinde, Miss.Sneha Shet, Miss.Sneha Chauhan, Miss.Suryanjali Verma

    Object Detection & Tracking System (ODTS) is combined with a popular deep learning network which is known as Faster RCNN (Faster Regional Convolution Neural Network), for Detecting the Object and Conventional Tracking of objects an algorithm is introduced and is applied for detecting and monitoring unexpected events automatically on CCTVs, the unexpected events can be Wrong-Way Driving or Stopping, Person getting out of the vehicle or Fire

    An Application of Deep Learning Algorithm for Automatic Detection of Unexpected Accidents Under Bad CCTV

    Prof.Vishal Shinde, Miss.Sneha Shet, Miss.Sneha Chauhan, Miss.Suryanjali Verma

    An Application of Deep Learning Algorithm

  • Applications of Machine Learning in The Field of Medical Care Prof. Swapnil Wani, Mr.Dipak Bochkari, Mr.Vivek Alaspure, Mr.Tushar Thube

    These years, with ML and AI becoming the hotspot of research, several applications have come forth in each of these areas. It exists as a kind of academic frontier as well as something close to our life. In this trend, the combination of both medical field and machine learning become more emerging. This research paper proposes the idea which remarkably reduced the existing situation of unbalanced medical distribution and resources strain

    Applications of Machine Learning in The Field of Medical Care

    Prof. Swapnil Wani, Mr.Dipak Bochkari, Mr.Vivek Alaspure, Mr.Tushar Thube

    Applications of Machine Learning in The Field

  • Alzeimer Disease Prediction Using Machine Learning Algorithms Prof. Satish Manje, Miss.Chetana Vishe, Miss.Niharika Dhanik, Miss.Namita Sonavane

    Alzheimer's complaint is the one amongst neurodegenerative diseases. This complaint is a grueling bone because there's no treatment for the complaint. Opinion of the complaint is done but that too at the after stage only. Therefore if the complaint is prognosticated before, the progression of the symptoms of the complaint can be braked down. This paper uses machine literacy algorithms to prognosticate Alzheimer's complaints using cerebral parameters

    Alzeimer Disease Prediction Using Machine Learning Algorithms

    Prof. Satish Manje, Miss.Chetana Vishe, Miss.Niharika Dhanik, Miss.Namita Sonavane

    Alzeimer Disease Prediction Using Machine Learning

  • Design of a restaurant billing system and data billing synchronization between branches Prof. Swapnil Wani, Mr,Shubham Vekhande, Mr.Sudhir Guntha, Mr.Saurabh Jain

    In recent years, the restaurant industry has been one of the most well-known and in-demand industries. E-Bill Resto is a restaurant billing system that was created by collaborating with a number of selling locations/restaurants under the same brand name, all of which are linked to the main firm via a database server. All revenue from restaurant sales may be tracked in real time with an integrated system

    Design of a restaurant billing system and data billing synchronization between branches

    Prof. Swapnil Wani, Mr,Shubham Vekhande, Mr.Sudhir Guntha, Mr.Saurabh Jain

    Design of a restaurant billing system

  • Location Prediction On Twitter Using Machine Learning Techniques Prof.Swapnil Wani, Mr.Shashank Barve, Mr.Prathamesh Khedekar, Mr.Ankit Yadav

    This project predicts the position of a user from the text content of a tweet by applying machine learning methods like Support Vector Machine, Naive Bayes, & Decision Tree. These days, predicting location of a user from various social media sites requires extensive research. For decades, researchers have been researching the automatic detection of places associated with or most relevant to records. As a most visited social networking site

    Location Prediction On Twitter Using Machine Learning Techniques

    Prof.Swapnil Wani, Mr.Shashank Barve, Mr.Prathamesh Khedekar, Mr.Ankit Yadav

    Location Prediction On Twitter Using Machine

  • Provably Secure and Light Weight Identification Based Data Sharing Protocol in Cloud Environment Prof.Vishal Shinde, Mr. Rushabh Baranwal, Mr. Vignesh Elagandula, Mr. Shubham Tripathi

    In a cyber-physical cloud context, Share and store files that is both secure and efficient via authorized physical devices remains a challenge, especially given the variety of devices to obtain access to the service and data. As a result, we describe a lightweight identity-based authenticated data sharing protocol in this work, which allows for safe data exchange among geographically separated objects and clients

    Provably Secure and Light Weight Identification Based Data Sharing Protocol in Cloud Environment

    Prof.Vishal Shinde, Mr. Rushabh Baranwal, Mr. Vignesh Elagandula, Mr. Shubham Tripathi

    Provably Secure and Light Weight Identification

  • Arduino Based Voice Control Robot with Lazer Security Prof. Satish Manje, Mr.Atul Yadav, Mr.Abhishek Shinde, Mr.Bipin Yadav

    This study present how a robot responds to voice input. This paper illustrates how a robot interacts with a human by responding to voice commands. This system is quite quick. The first portion of this system is a voice recognition system, followed by a central controller system, and finally a robot. The employment of robots in today's world has spread from industries to everyday life. A healthy interface between people and robotics is critical

    Arduino Based Voice Control Robot with Lazer Security

    Prof. Satish Manje, Mr.Atul Yadav, Mr.Abhishek Shinde, Mr.Bipin Yadav

    Arduino Based Voice Control Robot

  • Analysis of Machine Learning Classifiers for Breast Cancer Diagnosis Prof. Satish Manje, Mr.Sainathreddy Bonthu, Mr.Arun Elavarasan, Mr.Aniket Gupta

    Breast cancer is a form of cancer which originates in breasts of women. Cancer is caused by uncontrolled cell division or expansion. Breast cancer cells usually form a tumor that can be seen on an X-ray. Breast cancer has become one of the most well-known illnesses among women, resulting in the death of the most prevalent malignancies in women. Early treatment helps to cure malignant growth and prevent its recurrence

    Analysis of Machine Learning Classifiers for Breast Cancer Diagnosis

    Prof. Satish Manje, Mr.Sainathreddy Bonthu, Mr.Arun Elavarasan, Mr.Aniket Gupta

    Analysis of Machine Learning Classifiers

  • Implementation of Machine Learning Algorithm on Factors Effecting Divorce Rate Prof. Swapnil Wani, Mr.Soham Patil, Miss.Viral Jangale, Miss.Mayuri Baviskar

    As the number of marriages are growing, so does the amount of detachment and separation. The major factors that prompt separation can be numerous, and machine performed different computations to determine how to characterize the variables. The amount of separation can be reduced by this project as this will consists of possible factors leading to divorce. A sample data set has some main features that cause divorce

    Implementation of Machine Learning Algorithm on Factors Effecting Divorce Rate

    Prof. Swapnil Wani, Mr.Soham Patil, Miss.Viral Jangale, Miss.Mayuri Baviskar

    Implementation of Machine Learning Algorithm

  • House Price Prediction System Using Machine Learning Prof. Gayatri Naik, Master.Dhruv Patil, Master.Rohit Kore, Miss.Priti Ingale

    With the help of Python modules, this paper gives an overview of how to predict house expenses using various regression models. The proposed technique took into accountthe more refined components of the property price calculation and offered a more accurate projection. It also goes over the many graphical and numerical techniques that will be used to predict the price of a home. This paper explains what a machine learning-based house

    House Price Prediction System Using Machine Learning

    Prof. Gayatri Naik, Master.Dhruv Patil, Master.Rohit Kore, Miss.Priti Ingale

    House Price Prediction System Using Machine Learning

  • Tourist Place Reviews Sentiment Classification Using Machine Learning Techniques Prof. Gayatri Naik, Mr. Sushant Wani, Mr. Rushikesh Pawar, Mr. Rohan Randhir

    Social networking is getting increasingly popular these days. On tourism websites, millions of users evaluate and rate tourist attractions every day. These reviews may be subjected to sentiment analysis, which will aid in determining the popularity of tourism destinations. A ML approach was used to implement sentiment analysis in this research The information came from a number of different travel review websites. The feature extraction techniques

    Tourist Place Reviews Sentiment Classification Using Machine Learning Techniques

    Prof. Gayatri Naik, Mr. Sushant Wani, Mr. Rushikesh Pawar, Mr. Rohan Randhir

    Tourist Place Reviews Sentiment Classification

  • Machine Learning for Web Vulnerability Detection:The Case of Cross-Site Request Forgery Prof.Kanchan Umavane, Mr. Kunal Jain, Prathamesh Vishwakarma, Manoj Verma

    In this research, author present an approach for detecting web application vulnerabilities using Machine Learning (ML). Due to their diversity and broad use of bespoke programming approaches, web applications are particularly difficult to analyses. As a result, machine learning highly valuable in web security: It might blend human understanding of web app semantics into mechanized analysis techniques using manually explained data

    Machine Learning for Web Vulnerability Detection:The Case of Cross-Site Request Forgery

    Prof.Kanchan Umavane, Mr. Kunal Jain, Prathamesh Vishwakarma, Manoj Verma

    Machine Learning for Web Vulnerability

  • A Lightweight Secure Data Sharing Scheme for Mobile Cloud Computing Prof. Kanchan Umavane, Miss. Nidhi Sharma, Miss. Vrushali Gadhari, Miss.Vedangi Pawar, Mr. S Mohd Huzaifa

    the widespread cloud computing technology, smart phones may now store and access personal information from any location at any time. Consequently, the database security issue in mobile cloud is becoming increasingly serious, impeding the mobile phone usage is increasing cloud. There have been numerous studies undertaken to increase cloud security. However, because mobile devices have very limited processing abilities and power

    A Lightweight Secure Data Sharing Scheme for Mobile Cloud Computing

    Prof. Kanchan Umavane, Miss. Nidhi Sharma, Miss. Vrushali Gadhari, Miss.Vedangi Pawar, Mr. S Mohd Huzaifa

    A Lightweight Secure Data Sharing Scheme

  • Search Rank Fraud and Malware Detection in Google Play Prof. Vishal Shinde, Miss.Sheetal Shilwant, Miss.Akshata Potale, Mr.Prathamesh Sawant

    Fake methods of behaving in Google Play, the brilliant widely known Android software market, gasoline seek rank maltreatment and malware has been elevated in massive number. In this paper, we use framework that serves to unearths and use follows left behind, to differentiate each malware and packages uncovered to appearance rank extortion. FairPlay accomplishes greater than 95% precision in arranging great pleasant stage datasets of fake and legit apps

    Search Rank Fraud and Malware Detection in Google Play

    Prof. Vishal Shinde, Miss.Sheetal Shilwant, Miss.Akshata Potale, Mr.Prathamesh Sawant

    Search Rank Fraud and Malware Detection in Google Play

  • A Study of Blockchain Technology in Farmer's Portal Prof. Namrata Shinde, Miss.Pratima Yadav, Miss.Pranali Pashte, Miss.Ruchita Patil, Miss.Komal Awar

    Blockchain may be a methodology within which a authentication of a transaction is unbroken by betokens that of a crypto-currency. The record is maintained transversally, linking many computers during a peer to look network. Agreement, transactions, and therefore the documentation of them outline the economic system of a rustic. They set boundaries and supply security to the assets. Considering the options of blockchain

    A Study of Blockchain Technology in Farmer's Portal

    Prof. Namrata Shinde, Miss.Pratima Yadav, Miss.Pranali Pashte, Miss.Ruchita Patil, Miss.Komal Awar

    A Study of Blockchain Technology in Farmer's Portal

  • Connecting Social Media To E-Commerce Cold-Start Product Recommendation Using Microblogging Information Prof. Namrata Shinde, Miss. Pradnya Panmand, Miss. Pranjali Kapate, Miss. Aditi Hedau

    In last few years, the bounds in the middle of e-commerce and social media have become increasingly dim. Many e-commerce websites support a public login system where buyer can sign up for websites using their social website. network identity such as their Facebook or Instagram accounts. this paper prefer a new solution for a product that starts in the cold recommendation, which aims to recommend products from electronic commerce web pages

    Connecting Social Media To E-Commerce Cold-Start Product Recommendation Using Microblogging Information

    Prof. Namrata Shinde, Miss. Pradnya Panmand, Miss. Pranjali Kapate, Miss. Aditi Hedau

    Connecting Social Media To E-Commerce Cold-Start

  • Blockchain as a Platform for Secure Cloud Computing Services Prof. Vishal Shinde, Mr. Jas Verma, Miss. Mayuri Pawar, Miss. Ruchita Gaikwad

    In recent years problems associated with cyber-attacks and privacy of data have increased which is resulting in the speedy growth of Cloud Computing. Secure cloud computing services gets connected on a blockchain platform with the support of this work, which is called cloud@blockchain, which enjoy the notoriety and unchangeable side of blockchain. Cloud@blockchain designs two functions- unidentified file sharing and evaluation

    Blockchain as a Platform for Secure Cloud Computing Services

    Prof. Vishal Shinde, Mr. Jas Verma, Miss. Mayuri Pawar, Miss. Ruchita Gaikwad

    Blockchain as a Platform for Secure Cloud

  • Predicting CO2 Emission Using Machine Learning Prof. Swapnil Wani, Mr. Akash Akhilesh Yadav, Mr.Mihir Mukesh Panchal, Mr. Prashant Vinod Pandey

    The Random Forest & SVM are put forward to estimate the outlay of CO2 outpouring. Energy expenditure, such as power and coal energy, is the cause of the aggressive growth in CO2 emissions. The aim is to track co2 emissions gleaned from electrical energy and coal utilized in the manufacturing process. In setup to train and test the model, the statistics on electrical and energy were obtained

    Predicting CO2 Emission Using Machine Learning

    Prof. Swapnil Wani, Mr. Akash Akhilesh Yadav, Mr.Mihir Mukesh Panchal, Mr. Prashant Vinod Pandey

    Predicting CO2 Emission Using Machine Learning

  • Tomato Leaves Diseases Detection Using Image Processing and Deep Learning Prof.Satish Manje, Mr. Trusharth Pawar, Mr. Khan M. Waseem, Miss.Sneha Sapale

    Tomato is a very popular crop, this paper tries to solve the disease-causing problems that farmers face. This research paper attempts to eliminate the harmful side effects of chemicals and pesticides with the help of the Image Processing system. In this study, 10 different types of tomato leaf disease were diagnosed including one healthy class. Farmers can use pictures of affected tomato leaves and it will predict disease

    Tomato Leaves Diseases Detection Using Image Processing and Deep Learning

    Prof.Satish Manje, Mr. Trusharth Pawar, Mr. Khan M. Waseem, Miss.Sneha Sapale

    Tomato Leaves Diseases Detection

  • Machine Learning Algorithm for Stroke Disease Classification Prof. Vishal Shinde, Mr.Nikhil Patil, Mr.Omkar Sonar, Mr.Nishant Shedage

    Stroke is the most significant element of death as well as obesity in various countries. This study analyzes CT scan image enhancement data for stroke patients by improving image quality to improve image effects and noise reduction, and using ML algorithms to separate patient images into two subtypes of stroke i.e. ischemic stroke and stroke haemorrhage. Eight ML algorithms are operated in this study to classify stroke i.e., Naive Bayes

    Machine Learning Algorithm for Stroke Disease Classification

    Prof. Vishal Shinde, Mr.Nikhil Patil, Mr.Omkar Sonar, Mr.Nishant Shedage

    Machine Learning Algorithm for Stroke Disease Classification

  • Analysis and Prediction of Cardiovascular Disease using Machine Learning Classifiers Prof. Vishal Shinde, Mr. Hrithik Kedare, Mr. Rahul Gupta, Mr. Vinit Mahajan

    Cardiovascular disorder refers to a variety of issues that encompass narrowed or blocked veins, which can result in a heart assault, chest pain (angina), or stroke. The condition is anticipated via the gadget gaining knowledge of classifier based at the nation of the patient's facet impact. This research is used to look at the presentation of system mastering Tree Classifiers inside the prediction of Cardiovascular disorder (CVD)

    Analysis and Prediction of Cardiovascular Disease using Machine Learning Classifiers

    Prof. Vishal Shinde, Mr. Hrithik Kedare, Mr. Rahul Gupta, Mr. Vinit Mahajan

    Analysis and Prediction of Cardiovascular

  • Performance Analysis of Machine Learning Classifier for Predicting Chronic Kidney Disease Prof. Vishal Shinde, Mr. Shubham Narayan Bhoir, Mr.Zaid Irfan Khan, Mr. Mrunal Umakant Nagmoti

    In today’s life everyone has been trying to be conscious about health due to workload and busy schedule this gives attention to the health when a it shows symptoms but chronic kidney disease does not shows particular symptoms it is difficult detect and predict, to prevent this best solution prediction and analysis this problem Chronic Kidney Disease (CKD) has the type of chronic disease which means that a it happened calmly over period of specific time

    Performance Analysis of Machine Learning Classifier for Predicting Chronic Kidney Disease

    Prof. Vishal Shinde, Mr. Shubham Narayan Bhoir, Mr.Zaid Irfan Khan, Mr. Mrunal Umakant Nagmoti

    Performance Analysis of Machine Learning

  • Content Analysis of Messages in Social Networks, Identification of Suicidal Types Prof.Satish Manje, Mr.Shubham Dhawale, Mr.Acchutam Kulthe, Mr.Rohit Ghoshtekar

    This project describes a content analysis of text to spot suicidal tendencies and kinds. This article describes the way to make a sentence classifier that uses a neural network created using various libraries created for machine learning within the Python programing language. Attention is paid to the matter of teenage suicide and «groups of death in social networks, the look for ways to prevent the propaganda of suicide among minors

    Content Analysis of Messages in Social Networks, Identification of Suicidal Types

    Prof.Satish Manje, Mr.Shubham Dhawale, Mr.Acchutam Kulthe, Mr.Rohit Ghoshtekar

    Content Analysis of Messages in Social

  • Survey on Machine Learning Techniques for The Diagnosis of Liver Disease Prof. Satish Manje, Miss.Tannaz Inamdar, Miss.Shivani Kamalekar, Miss. Akanksha Shaha

    Machine Learning Algorithm focuses on building the model using sample data which is known as training of the data for making decisions or predictions. The project focuses to give a survey and providing a comparative survey of the entire ML techniques for diagnosing and predicting liver disease in Medical Areas, which are been already used for predicting liver disease by several authors, and analyses are based on Sensitivity

    Survey on Machine Learning Techniques for The Diagnosis of Liver Disease

    Prof. Satish Manje, Miss.Tannaz Inamdar, Miss.Shivani Kamalekar, Miss. Akanksha Shaha

    Survey on Machine Learning Techniques

  • Federated Data Management Aggregation Framework by using NLP Prof. Swapnil Wani, Miss.Jyoti Gupta, Miss.Namrata Kasturi, Mr.Suraj Yadav

    Given the increasing range of heterogeneous information hold on in relative databases, file systems or cloud environments, it has to be simply accessed and semantically connected for any information analysis. The potential of information federation is essentially unrealized, this paper provides associate interactive information federation system by applying large-scale techniques as well as heterogeneous information federation

    Federated Data Management Aggregation Framework by using NLP

    Prof. Swapnil Wani, Miss.Jyoti Gupta, Miss.Namrata Kasturi, Mr.Suraj Yadav

    Federated Data Management Aggregation