ABSTRACT For several years, farmers in India have had little liberty in choosing markets and purchasers for their produce. All states in the country, except three, degree that marketing and selling of farm produce must be directed through state-owned mandis, retail markets where mediators (middlemen) crush farmers to increase margins. According to research, mediators have become dominating buyers of the agricultural market, resulting them to take control over the plight of the farmers and gulping all the profits. The farmers work day and night expecting a good yield. They use a lot of financial resources lending money and buying fertilizers, seeds etc. So, they have the right to enjoy every rupee gained on their corp. In this context, we propose a system which brings farmers close to the retailers cutting the middlemen. The middlemen usually take up to 70% of the profits of farmers leaving them helpless. Our system consists of a mobile or web application which will serve as a platform for farmer the growers and retailers or customers to sell and buy their farm products. This system aims at giving a profitable price to farmers to their farm products cutting the middlemen. This allows the retailers or the customers to buy products from the farmers at a lower than the normal price. This system is used to farmer and user. Farmer uploads their product with details and buyers view these details and book that product with in a time.

Most of the people in this world like to travel from one place to another no matter whether it is a small or large distance. The need for a tourism management system that can manage tourism information with ease is sought after by every tour management company. Tour Management system is a dynamic website for tourism business. This travel and tourism application is designed for travel agencies by which they can manage different tour packages based on the destinations. The main purpose is to help tourism companies to manage tour packages .To provide user friendly environment to overcome the drawbacks of exiting system. This project �TOURISM MANAGEMENT SYSTEM� is used to automate all process of the travel and tourism, which deals with creation, booking and confirmation and user details. The project is designed HTML-PHP as front end and Microsoft SQL Server 2008 as backend which works in any browsers.

The purpose of �IFSC Code Finder Portal� is to automate existing manual system by the help of computerized equipments and full-fledge computer software, fulfilling their requirements, so that their valuable data/information can be stored for a long period with easy accessing and manipulation of the same. The required software and hardware are easily available and easy to work with. �IFSC Code Finder Portal� can lead to error free, secure, reliable and fast management system. It assist the user to concentrate on their other activities rather concentrate on the record keeping. Thus it will help organization in better utilization of resources. The organization can maintain computerized records without redundant entries. That means that one need not be distracted by information that not relevant, while being able to reach the information. The aim to automate its existing manual system by the help of computerized equipments and full-fledge computer software, fulfilling their requirements, so that their valuable data/information can be stored for a long period with easy accessing and manipulation of the same. Basically the project describes how to manage for good performance and better services for the clients.

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Online bus reservation system is a web based application that works within a centralized network. This project presents a review on the software program online bus reservation system as should be used in a bus transportation system, a facility which is used to reserve seats, cancellation of reservation and different types of route enquiries used on securing quick reservations

This paper present the Automated Visitors Management System A visitor management system tracks the usage of a public building or site. By gathering increasing amounts of information, a visitor management system can record the usage of the facilities by specific visitors and provide documentation of visitor�s whereabouts. Because a visitor management system provides a record of building use, these systems are frequently used to complement building security systems and access control systems. As electronic visitor management systems become more common and more powerful, these systems are taking over many of the functions of building security and access control.

�Online Examination System� is a software solution, which allows a particular company or institute to arrange, conduct and manage examinations via an online environment. This can be done through the Internet, Intranet and or Local Area Network environments. Some of the problems faced by manual examination systems are delays in result processing, filing poses a problem, filtering of records is not easy, The chance of loss of records is high and also record searching is difficult. Maintenance of the system is also very difficult and takes lot of time and effort. I intend to use the systems development life cycle (SDLC) which is a conceptual model used in project management that describes the stages involved in an information system development project.

This project helps us parking now a days vehicle parking has become major problem in many areas like malls, theatres, public places. It even effects traffic in major areas. Due to increasing population in urban areas, there is an exponential rise in the number of vehicles which is leading to major problems leading to poor traffic management and congestion. Another major problem faced by the vehicle owners is the availability of parking space. The idea of parking system is used to decrease the parking issues.

This is a web based application that provides an online platform for the grocery store/shop's customers or possible customers to order their desired product. The main purpose of the simple project is to let the customers buy their groceries without going to the shop or store. The system will list all products with available stock and customer can save their desired product to their shopping cart and checkout when they are done. The system is easy to use and has a simple user-interface.

ABSTRACT Online event management system is a software project that serves the functionality of an event manager. The system allows only registered users to login and new users are allowed to register on the application.. The project provides most of the basic functionality required for an event. It allows the user to select from a list of event types. Once the user enters an event type eg(Marriage, Dance Show etc), the system then allows the user to select the date and time of event, place , event equipment, parking details and the food details(menu). All this data is logged and stored in the database and the user is given a receipt number for his booking if the time and place of the function hall was acceptable which means that both the organizer and the admin were accepts the user request. This data is then sent to the administrator (website owner) and they may interact with the client as per his requirements and his contact data stored in the database. And the user can also give feedback about the event. It improve your workflow processes and customer engagement simultaneously with connected data, automatic updates, tasks, rule assignments, and much more. Keywords:Functionality, equipment, receipt, administrator, requirements, database, feedback, engagement, automatic, assignment

This application is specifically developed to help hotel staff. The project hotel management manages and maintains the records of customers and room in the hotel. This rooms have different categories such as delux, semi delux etc... So their charges nd records will be maintained accordingly..

ABSTRACT The Project is developed for the threat free and user oriented Online Voting System. The Online Voting system is made for the people of the country residing around the world and wants to vote for their representative. The election can be conducted in two ways the paper ballot election and the automated ballot elections. The proposed online voting system with biometric authentication is an electronic voting system which seeks to make use of the uniqueness of the minutiae of the human fingerprint to further enhance the level of trust and confidentiality of the voters in the system as well as making the actual process as universally accessible as possible which would be achieved through the deployment on the Internet. It is expected to solve the two critical issues facing staff elections conducted within the University of Ibadan community which serves as the project case study. For the voter registration and authentication processes which are performed on the desktop module, the voter is expected to have his or her fingerprints captured and the minutiae extracted that is stored on the database. This is done to prevent the occurrence of multiple registrations or identity. The project was able to achieve a high success rate in the use for conducting elections as it was able to stamp multiple registrations by voters through the combined use of both the unique voter identification number and their unique fingerprints. This effectively solved all questions that may arise on eligibility of voters and accreditation hiccups. Voters can thus proceed to the online module of the project to cast their votes through any internet � connected device using the voter identification number, security answer keyed in during the registration process as well as a token key that was generated automatically for each voter per election on the online module.

This paper is focused on Blood Bank Management System which is a web application with supporting mobile application aimed to serve as a communication tool between patients (who need blood) and blood donor. To become members of the system, donors need to create their profiles by providing fundamental information like name, blood group, email address, password, and exact location from �Google Map�. In order to find out the exact location of a donor, Google Map is integrated with this application. Blood donors can also be searched from the mobile application, but this is only accessible for registered members. The goal of this paper is to reduce the complexity of the system to find blood donors in an emergency situation

Nowadays we cohabit with technology in an inseparable way. With the aim to facilitate and automate application have brought improvement in many different fields and disciplines. A particular field that requires technology�s intervention is vaccination in Albania, which is the most important and crucial component of populations� health. The e-Vacc is a web application which is used for managing and organizing the vaccination process data. This application will be used by every individual in Albania that receives vaccination, and by the vaccination service providers which are the employees.

Criminal record generally contains personal information about particular person along with photograph. To identify any Criminal we need some identification regarding person, which are given by eyewitness. In most cases the quality and resolution of the recorded image segments is poor and hard to identify a face. To overcome this sort of problem we are developing software. Identification can be done in many ways like finger print, eyes, DNA etc. One of the applications is face identification. The face is our primary focus of attention in social inters course playing a major role in conveying identify and emotion. Although the ability to infer intelligence or character from facial appearance is suspect, the human ability to recognize face is remarkable.

ABSTRACT In this competitive era, the education among the people is so increasing that the jobs for them are now decreasing. The companies even want the people who are best in their fields. At that time, it becomes difficult to find the people who are intelligent enough to be hired. The work for the companies also increases to find the people who can fulfill their requirements. Thinking about these problems, one can think about the process which can handle this process and make the work less complex. This project is about the recruitment process which is done online. The recruitment process here is handled by the system. This project will allow the person to apply for a job in the company for the interested vacancy which would be available at the company. The person will be having the account after registration and will be then called the applied user. If he would be qualified, he would be interacting with the system for the updates. The project is created for fulfilling the requests of the company managers so that the recruitment module can be placed in the company�s website and the users who visit the website can view the vacancies in the company and will be able to apply directly from remote place even. The vacancies will be posted by the administrator on the basis of needs of the manpower in the company. T

This project deals with the design of "Online Electricity Billing System", in which it is possible pay amount electronically. This approach is implemented via virtual bank in which the process of money transfer can be implemented. In the project " Online Electricity Billing System"is an application to automate the process of ordering and calculating the electricity bill with all the charges and penalty for a consumer who has been given connection of electricity. Paper bills are now the primary channel of communication between companies and their customers.However, their potential for personalization is limited, and they are not interactive. An electric bill is a bill for the consumption of electric energy.The user is incapable of paying the bill before month end, it would calculate fine for each subsequent day.

The purpose of this project to create an online leave management program which is essential to somthing like an organization or college.The employee leave information Mangement system was designed to automate the employee administration and management and strategic planning of leavs for employees.This program manages all of the employee records.

This project is aimed at developing an Online Banking for customer. The system is an online application that can be accessed throughout the organization and outside as well with proper login provided.The project has been planned to be having the view of distributed architecture, with centralized storage of the database. The application for the storage of the data has been planned. Using the constructs of MYSQL and all the user interfaces have been designed using the HTML with Javascript. The database connectivity is planned using the �Database� methodology. The main aim of Online Banking System is to manage customers, and their transactions, and it is specifically developed for balance enquiry, Fund transfer to another account in the same bank, and changing the address , getting the last transcations (viewing month wise) and also update their profile through online and also provide the comfort to both bank and customers.The entire project has been developed keeping in view of the distributed client server computing technology, in mind. The specification has been normalized up to 3NF to eliminate all the anomalies that may arise due to the database transaction that are executed by the general users and the organizational administration. The user interfaces are browser specific to give distributed accessibility for the overall system. The internal database has been selected as MYSQL.The basic constructs of table spaces, clusters and indexes have been exploited to provide higher consistency and reliability for the data storage. The MYSQL was a choice as it provides the constructs of high-level reliability and security. The total front end was dominated using the HTML 5. At all proper levels high care was taken to check that the system manages the data consistency with proper business rules or validations. The database connectivity was planned using the latest � Database connection� technology provided by MYSQL. The authentication and authorization was crosschecked at all the relevant stages.

This Car Rental System project is designed to aid the car rental company to enable renting of cars through an online system. It helps the users to search for a available cars view profile and book the cars for the time period it has a user friendly interface which helps the user to check for cars and rent them for the period specified. They could also make payment online the rental cars shall be categorized into economy, premium etc. Based on the type of car required by the customer, the user shall be able to make bookings. The use of internet technology has made it easy for the customers to rent a car any time. This Car Rental System makes the bookings easy. Its saves time and labor. The tool shall ask the user for information such as the date and time of journey, type of car etc. Also, it will need an information number Using these details, the tool shall help the customer to book a car for the journey.

ABSTRACT The project titled Online Food Ordering System is designed with visual studio as from and SQL server as back end. There will be different items available in restaurant, many customers will be coming at different time for having food, they will be eating different items available in the restaurant. Restaurant owner has to maintain records of each sales and purchase to keep track of the availability of stock of any materials which is used for cooking. This system will save time and will be easy to use when compared to manual work which will be done in papers. Modern handheld devices such as smart as smart phones and PDAs have become increasingly powerful in recent years. Dramatic breakthroughs in processing power along with the number of extra feature included in these device have opened the doors to a wide range of commercial possibilities. In particular, most cell phones regular include cameras, processor comparable to PCs from only a few years ago, and internet access. However, even with all these added abilities, there are few applications that allow much passing of the environmental information and location based services.

�Sanitization Management System� is a web based application which is developed in PHP and MySQL server. Nowadays it is very important to sanitize and disinfect each every thing. The main purpose of this system is to provide sanitization services to clean and disinfect of envoronment. The main purpose of �Sanitization Management System� is to systematically record, store and update recorded data.

Employee Payroll Application has been designed to for the purpose of maintaining details of various allowances and deductions that need to be given to the employees of the organization. Also, it generates the salary Sheet of the employees of the organization that assists the accounts department in many ways. Employee Payroll is a web application which is used to maintain the Employee details of the organization or concern in different places; this provides each employee details with unique information. Admin plays the main roll to maintain the activities of the employees, this system is user friendly GUI based application that will automate the day to day activities of the employees who are working in the concern. An application for completely automating the different activities of the various departments or sections of the employees is processed.

The packers and movers company uses the brst quality packing materials to pack goods in such away that all goods remain in safesafe condition during transist&moving services assure the safe delivary of goods at destination.

One of the most important responsibilities of pharmacy management is to supervise and manage the pharmacy employees in order to ensure healthy working relationships and outcomes. Each of these functions is critical to the pharmacy�s operation and should be explained by the management. However, most pharmacies faced problems such as insufficient service promotions, lack of coherence of pharmacy services in hospitals, poor drug information systems and the inconsistency of the pharmacy information management due to its manual processes. Now these are the problems that must be solved with this Pharmacy Management System Project Proposal.

ABSTRACT The main objective of the online crime reporting system is to manage the details of crime, criminal, public, solutions, department. It manages all the information about crime complaint, department, crime. The project is totally built at administrative end and thus only the administrator is guaranteed the access. The purpose of the project is to build and application program to reduce the manual work for managing the crime, criminal, complaint, public. It tracks all the details about the public, solutions, department. The aim is to automate its existing manual system by the help of computerized equipments and full-fledged computer software, fulfilling their requirements, so that their valuable data/information can be stored for a longer period with easy accessing and manipulation of the same. Basically the project describes how to manage for good performance and better services for the clients.

The challenge of maintaining proper diet can be facilitated by the use of mobile phones.Mobile phones provide a fair infrastructure, which can be used to provide cost effective, high quality aids to behaviour monitoring and modiication. The nature of mobile phonesallows the user for customization and personalization, retrieval of nutrition informationon demand, as well as the ability to truly monitor the user�s consumption trends. Thisandroid application is a one stop solution for all health related issues and question. It hasvarious functions like diet tracking, nutritional information about food�s, Bmi calculator, information about some basic�medicines.

ABSTRACT Now-a-days there is a huge demand in �storing the information available in the paper documents in to a computer storage disk and then later reusing this information by searching process�. One simple way to store information in these paper documents in to computer system is to first scan the documents. Whenever we scan the documents through the scanner, the documents are stored as images format in the computer system. These images containing text cannot be edited by the user. But to reuse this information it is very difficult to read the individual contents and searching the contents form these documents line-by-line and word?by-word. Thus there is a need of character recognition mechanisms to perform Document Image Analysis (DIA) where the text from these documents in image format is recognized and transformed into machine readable text-data. Language is the only way to communicate with people of different regions. If you are planning to expand your business in different regions, you need to communicate with staff, partners and also with the clients. At that time, language translation is the best way to understand people about your business and services. This project displays a menu where the user tend to choose requirement of his own. It facilitates extraction of text from images, writing text to images, translation of text to speech or text of specified language

The main objective of this project (DMS) is to store the data of the desired persons in a database and to automate the complete operation of the directory which meets all the requirements. It is a easy to use interface developed in PHP with MySQL as the backend to store the details. This application stores all the details like name, telephone number, address, email id in a database. This software also allows editing, updating and searching various contact details. It is secure, easy to use and reliable software system. It also provides a good level of security as there is an admin who can only edit and update details.

The project definition name describes many ways, Student attendance management system, Attendance portal, Online attendance System, School attendance system, College attendance system etc.

This Project "HOSTEL MANAGEMENT INFORMATION SYSTEM" targeted for the College Hostel integrates the transaction management of the Hostel for better control and timely response. This eliminates time delay and paper transactions being marked. The warden is provided with a better control over the transactions like adding the details of new students in the hostel, modifying the details of the students, deleting the students, viewing the students details in the Hostel. This project's main motto is to reduce the effort of Wardens and provide better service to the students. The goal of this project is to develop a system for the computerization of the Hostel. The common transactions of the hostel Includes the maintenance of mess bills, information about students in the hostel, enrolling of new students and their payments and dues etc are stored into the databases and reports are generated according to the user requirements.

The interview is an important data gathering technique involving verbal communication between the researcher and the subject. Interviews are commonly used in survey designs and in exploratory and descriptive studies.

The objective and scope of my Project Pizza Ordering System is to record the details various activities of user. It will simplifies the task and reduce the paper work. During implementation every user will be given appropriate training to suit their specific needs. Specific support will also be provided at key points within the academic calendar. Training will be provided on a timely basis, and you will be trained as the new is Pizza Ordering System rolled out to your area of responsibility

Computer become away of life for today's high society.many aspects modern life that we have to accept as common place Would not be possible if there were no computers Today computers are used extensively in many areas of business The project title was "cyber cafe management system" of software package By using LAN connection in cyber cafe automatic these process very easily These are two modules . Server module . Cilent module

ABSTRACT The goal of the project "CURFEW E-PASS MANAGEMENT SYSTEM" is to develop a system that can be utilized during curfew to efficiently manage people's passes during Covid-19. A computer's internal memory can store data and instructions in an electronic form that may be retrieved at any moment. It makes the task easier to complete and decreases the amount of documentation required. Lockdown is intended to prevent the spread of infection, and it entails not leaving the house unless absolutely essential. However, under unusual circumstances, people may need to go from one town to another, and this e-pass generating mechanism will aid in people's contact-less transportation. The electronic version of the paper gate pass is available. Keywords: E-Pass, Curfew, End-To-End Application, Lockdown.

It is a software developed for managing complaints

Life style is fast changing in the modern era, and the women have become more conscious abou their makeup. More women are seen frequenting the beauty parlours for availing themselves of some kind of service to enhance their appearance to look good. The status of women has improved a lot and is improving further. This has resulted in their life style changing. Also their economic independence encourages them to resort to this type of service.

The main objective of �Student Result Management System� is to be developed software which manages student result activities in the college makes an interactive GUI where result admin can manage details of all student results. Although such project as very wide scope, this project contains the most important parts i.e. class_student, class_subject allocation and information relating to students for each subject has to be maintained separately.

The Online Shopping is a web application intended for online retailers. The main objective of this application is to make it interactive and its ease of use. It would make searching, viewing and selection of a product easier. It contains a sophisticated search engine for user to search for products specific to their needs. The search engine provides an easy and convenient way to search for products where a user can Search for a product interactively and the search engine would refine the products available based on the user�s input. The user can then view the complete specification of each product

OurprojectHospitalManagement system includes registration of patients, storing their details into the system, and also computerized billing in the pharmacy. Our software has the facility to give a unique id for every patient and stores the details of every patient and the staff automatically. It includes a search facility to know the current status of each room. User can search availability of a doctor and the details of a patient using the id. The Hospital Management system can be entered using username and password. It is accessible either by an administrator or receptionist. Only they can add data into the database. The data can be retrieved easily. The interface is very user-friendly. The data are well protected for personal use and makes the data processing very fast.

Teacher ManagementDr. Radhika KapurAbstractProgressions can be brought about in the overall System of education, when the concept of teacher management is identified in an appropriate Manner. Teachers are the ones, who are impart knowledge and information to the students in such a Manner and ensure that their growth and development takes place in an operative manner and they are able to achievetheir academic goals and objectives.

This website Milk Dairy Management System is built such a way that it should suits for all type of Milk Distributors in future. So every effort is taken to implement this project in this Milk Distributing Office, on successful implementation in this Dairy Distributors Office, we can target other Milk Distributors in the city. This project is developed using PHP and MySQL. This website helps in controlling all the dairies in and around the area to prevent from extra dairy production. And the admin can easily control over all the dairies. The main objective of this website is to automate the complete operations of the Dairy Distributors office and bring ease between each dairy managers and the system admin. They need to maintain hundreds of thousands of records. Also searching should be very faster so they can find required details instantly

Abstract The online course registration system is the central part of the educational administration system, which consists of registration guidance, registration controlling, undergraduate course registration, graduate course registration, retaking and retesting, dropping the course in the middle phase and information exchange, etc. By registering the course voluntarily, the new system improved registration mechanism, implemented course registration of common course for undergraduate and graduate students, and also supported the teaching activities across spring, summer and fall semesters. This article introduces the design and implementation of the new online course registration system, including registration mechanism, technical architecture, and system design, etc. There are a number of online registration systems that have been made in different context and to suit the need arising. Researched on the online course registration for the faculty of engineering and in their research they generated a solution named Online Registration. The project was divided into three namely, Online Registration which is the start-up project of their system, and depending on data Access and web security. data Access would actuate the data transaction between the client and the server and Web Security would configure the database and handle the authentication and authorization. The research described their experience in designing, developing and deploying an online course registrati0n. The system has not only reduced the burden of all parties involved in the course registration process, but also improved the process by reducing errors. Though their system managed to reduce the errors significantly it lacked the continued interaction with the student in the updates of the student�s registration status updates. It also lacked accountability as some stakeholders in the registration process do not have access to the system.

Client management system is an established concept. Which is used to manage client life cycle through various technologies and process oriented tools. This study identifies how web application can be utilized for improved client management and to understand the potential of web application in the business environment.

It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.

Employee Management System is a distributed application, developed to maintain the details of employees working in any organization. It maintains the information about the personal details of their employees, also the details about the payroll system which enable to generate the payslip. The application is actually a suite of applications developed using php. It is simple to understand and can be used by anyone who is not even familiar with simple employees system. It is user friendly and just asks the user to follow step by step operations by giving him few options. It is fast and can perform many operations of a company

Online Art gallery project in php exhibits the work s of many artist. Each artist is given a specified space on the online webpage. Any user can register and login to the website and can buy those art works.

Nowadays covid-19 testing management system is one of the most essential tools that are mostly used in testing lab; it is mostly used to manage covid-10 medical lab related activities.

Car Washing Management System is fully automated with different stages of foaming, washing, drying and brushing. In Car Washing System, we performed all the operations needed to clean the car successfully by using highly expert and experience worker

This project deals with reserving tickets for the trains which reserve date.So in order to make is convenient to travel we can book tickets priority.This makes the travel smooth and convenient.This also helps in checking the details afterwards.

A college library management is a project that manages and stores books information electronically according to students needs. The system helps both students and library manager to keep a constant track of all the books available in the library. It allows both the admin and the student to search for the desired book. It becomes necessary for colleges to keep a continuous check on the books issued and returned and even calculate fine. This task if carried out manually will be tedious and includes chances of mistakes. These errors are avoided by allowing the system to keep track of information such as issue date, last date to return the book and even fine information and thus there is no need to keep manual track of this information which thereby avoids chances of mistakes. Thus this system reduces manual work to a great extent allows smooth flow of library activities by removing chances of errors in the details.

Today the world totally relays upon the electronic media to its every day venture. People have no time to be updated through newspaper or watching or listening the news on television or radios. People today need to be updated on daily basis in this competitive world. Most of the people get the information about the world around through the internet which is fast, accessible, and reliable. The WWW (World Wide Web) is huge, widely distributed, global information service centre for Information services news, advertisements, consumer information, financial management, education, government, e-commerce etc, hyper-link information, acces and usage information. �24 Hours News Portal� is

This project manages people, animals details and provides ticket to the person who comes to visits in zoo with his/her family. With this project admin is able to see how many people is visiting in zoo and also see how many ticket is generating in particular period.

Student management systems serve academic institutions in a variety of ways, the most important of which is centralized data administration and accessibility. Teachers will be able to input, maintain, and access student data more simply. Parents and guardians have a better understanding of how their children perform in class. Teacher and other school or college professionals must enhance their student management skills over time. It is defined as a collection of skills that every teacher develops through time in order to properly manage their students. Getting into the student�s heart is one of the most important aspects of management.

A saloon management system is a website that manages the appointment scheduling functionality. This system connects users and Salon in an online platform where user can browse salon and their services. Users can also write and read reviews of the salon and its management. Salon management system helps the industry to fill this void in such a way that is on-demand, easy to use, and effective. The final product will be a functioning web application that can handle use cases like appointment scheduling, writing, and reading review for specific salon.

A Disk Jockey (DJ) plays musical recordings in parties or events. Roles of these professionals vary depending on the purpose or the setting of the music. They may work for radio stations where they play musical selections from playlists. The Online DJ Booking System makes a DJ more profitable as they can be reached in the web. This system is programmed using php and mysql is the database used.

Online Birth Certificate System maintains a good record of date of birth of people. This system helps admin to view data of date of birth of people who reside in country. The main objective of �Online Birth Certificate System� project is to providing easier registration of date of birth and gets certificate of birth online which save lots of time

Local Services Search Engine Management System (LSSEMS) is a web based application which helps user to find serviceman in a local area such as maid, tuition teacher, plumber etc. LSSEMS contain data of serviceman (maid, tuition teacher, plumber etc.). The main purpose of LSSEMS is to systematically record, store and update the serviceman records.

The main agenda of the paper is to lessen the mammoth task of manually allocating seats during an examination. The tool provides an effective measure to dynamically allocate students in a classroom. This research can be further extended to seating planning in conferences, weddings, movie theaters etc. It is an organized system which enables us to automatically allocate students to their desired location. For people handling institutions, the work load is very high and the need for faster work is a need of an hour. There is a general complaint that government offices have surplus work load but the speed of efficiency is very low. It is a type of software which can decrease our work time. Those Institutions which uses this software can save a sample amount of time during the examination time. Some of the few benefits of this model are that it is very fast, reliable and robust. In today�s world, it is the tool for event management which is extremely useful of various occasions. This much needed feature of user friendliness is present in this model and can be used for all types of user whether Agile, Na�ve or expert.

The detection of various types of flowers based on their characteristics, is very useful in many fields of agriculture and medical research. Random Forest, Decision Tree and CNN algorithms are applied in this project to the identification of flowers on the basis of their characteristics. This algorithms are applied in a data set of flowers and their precision is calculated. Algorithms are implemented on a data collection in the Python programming language. It is found that the performance of CNN algorithm is best in detection of flowers.

Nowadays, heart disease is a common and frequently present disease in the human body and it�s also hunted lots of humans from this world. Doctor and clinical research said that heart disease is not a suddenly happen disease it�s the cause of continuing irregular lifestyle and different body�s activity for a long period after then it�s appeared in sudden with symptoms. After appearing those symptoms people seek for a treat in hospital for taken different test and therapy but these are a little expensive. So, I developed a machine learning model to predict weather a patient has heart disease or not.

Under the limitation of modern science, Anatomy is not able to discover the extremely complicated organ - brain�s working activities. Along with the development of machine learning and its subset - neural network, named by nearly implementing neurons connection, scientists found an efficient way to represent brain as a visible approach. Therefore, a new discipline has been created under biology, named as computational neuroscience. Most scientists focus on finding computational models that are closed to fit the specific or general areas of the cortex. Convolutional neural network (CNN) and Recurrent neural network (RNN) are two of them.

During the pandemic, there has been a strong upward momentum in the supply of online jobs posted on various trading portals. Therefore, a fictitious assignment to a job posting can be a huge problem for everyone. Thus, these fake jobs can be detected and properly distinguished from the pool of real and fake job hobby advertisements using advanced deep mastering algorithms and automated field type. This model proposed using several statistical mining strategies and algorithms along with KNN, preference tree, naive Bayes classifier, random forest classifier, SVM and deep neural society to wait for the submitted project to decide whether it is real or Fake. They experimented with EMSCAD with 18, 000 employee samples. We've used 3 dense layers for this Deep Neural network. An expert classifier suggests up to 98% accuracy for predicting a fraudulent e-book assignment.

Image Caption is a concept of gathering the right description of the given image on the internet use Computer Vision and natural language processing. We modeled automatic image caption using convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) to provide a series of text that best describes the image.

Data mining is the development of instinctive discovery of valuable information from a huge repository. In educational record mining, prediction of a student's overall educational performance is a well-known study. The purpose of study boards is to show class algorithms as a hybrid type. We used feature network algorithms based on Radial, Layered Perceptron, C4Five, and Class Random Forest Areas. At first, grace accuracy was calculated by yourself using nice algorithms. The combination of the radial basis function, multi-layer realization, C4.5, and the odd- numberedness of the Random Forest algorithm gave an accuracy of 72, 9167%, 75, 4167%, 75%, and 73%. . One hundred twenty-five percent, and vice versa. To increase the accuracy of the type rule set, the ray-based feature grid is carefully layered. This set of instructions provides a type accuracy of 75.625%. We then combine the C4.Five ruleset with the Random Forest ruleset, to give an accuracy of type 76, 4583%. In this test, we found that a mixed class rule set provides more accuracy than a single class rule set.

This study analyzes activities to create a model that can help college students choose topranked institutions based on their scores and profiles. We can test applicants in all disciplines, including Master of Science (International), Master of Technology (India) and Master of Business Administration (India and worldwide). We plan to build a device study model to provide results that can help students choose the right college. The dataset contains records about the university and academic profiles and a field indicating successful admission. Key performance indicators are used to evaluate predictions made with Ensemble Machine Learning using algorithm diffusion. Thissuggestedsystem uses linear regression (LR), random forest (RF), CatBoostClassifier algorithms but CatBoostClassifieralgorithm is giving highest accuracy

In this system, we used five different machine learning algorithms. Those are Decision Tree, Random Forest, Gradient Boosted Trees, Support Vector Machine and Linear Regression.These algorithms were applied on the BSE index data from 1st January 2015 to 31st March 2020. Amongst all the models applied, Linear Regression is chosen to be the efficient one, as it has least relative error and standard deviation. Further Linear Regression is used to forecast the BSE SENSEX Closing prices.The Indian Stock Market is expected to experience significant growth over the next few years.

We aim to implement an intelligent processing system that can reduce road accidents drastically. The major challenges faced by these methods are robustness to handle variation in human face and lightning conditions This approach enables us to identify driver's face characteristics like eye closure percentage, eye-mouth aspect ratios, blink rate, yawning, head movement, etc. This system will helps the driver to come out from the drowsy state by alarm sound.

A recurring problem in the area of public health is the high rate of patients who do not attend scheduled medical examinations and consultations. Absenteeism from previously scheduled appointments compromises the effectiveness of medical care and generates a series of problems in the public health system, such as long waiting lines for care, lack of resources to meet demand and high financial loss, by paying a professional who will be idle due to the absence of patients. This predictive approach may help in optimizing resource allocation, reducing no-show rates, and enhancing overall healthcare efficiency and patient satisfaction. Thus, this study aims to explore different models of machine learning in order to help predict whether the patient will attend the scheduled appointment or not

Our country, India is the largest democratic country in the world. So it is essential to make sure that the governing body is elected through a fair election. India has only offline voting system which is not effective and upto the mark as it requires large man force and it also requires more time to process and publish the results. Therefore, to be made effective, the system needs a change, which overcomes these disadvantages. The new method does not force the person's physical appearance to vote, which makes the things easier. This project focusses on a system where the user can vote remotely from anywhere using his/her computer or mobile phone and doesn�t require the voter to go to the polling station through two step authentication of face recognition and OTP system.

The rainfall rate is one of the essential phenomena in the weather system, which has a direct influence on the agriculture and biological sectors. This project aims to develop a linear regression model in order to predict the rate of precipitation (PRCP), i.e., rainfall rate, for Khartoum state. It is based on some weather parameters, such as temperature, wind speed, and dew point.

The status of Inflammatory Bowel Disease from vitamin D in children and adolescents. IBD is a phrase used to refer to gastrointestinal system swelling that is recurrent. It is observed that low vitamin D levels are linked with higher risk, particularly colon cancer in people with IBD.

Crop recommendation systems for agriculture are based on various input parameters. It proposes a hybrid model recommending plants for South Indian states by considering multiple attributes, including soil type, rainfall, groundwater level, temperature, fertilizers, pesticides and weather.

This project predicts student grade on the basis of various parameters which plays an important role in an education system. Some of the parameters are taken into consideration like learner factor, learner engagement, learning strategies use, teacher experience and motivational beliefs etc. With the help of examination and evaluation of these parameters we can measure student learning outcome. Classification Algorithms like Decision Tree, Random Forest and Support Vector Machine can help us to classify student�s performance.

Navigation with the Indian Constellation is now progressing through the Indian Space Research Organization (ISRO). The satellite constellation consists of four geosynchronous satellites and three geostationary satellites. There are many elements that affect the navigation device. Doppler collimation is one such addition that ends up being detected by geostationary satellites. It occurs between a mix of IRNSS 1C-1G, 1C-1F, 1F-1G geostationary satellites. When the relative Doppler frequency of the satellites is much less than the bandwidth of the tracking code loop, the Doppler collision length (DC) is determined. The positional accuracy of the NavIC is low with the most direct modern accuracy.Due to the CC, the most influential geostationary satellite television of the computer pair is 1C-1G. For DC mitigation, DC prediction using system recognition algorithms can be very useful to improve positional accuracy. The parameters taken into account for the prediction are the relative Doppler, the duration of the computer, the satellite TV, the speed of the computer, the satellite TV, the repetition duration and the relative Doppler. For the prediction, 3 supervised system control algorithms are used, together with linear regression, Random Forest repressor and K-Nearest Neighbors (KNN). Among these three algorithms, the random regression predicted the Doppler collision in the forest area as it should.

Abstract�Nowadays, the MOBA game is the game type with the most audiences and players around the world. Recently, the League of Legends has become an official sport as an e-sport among 37 events in the 2022 Asia Games held in Hangzhou. As the development in the e-sport, analytical skills are also involved in this field. The topic of this research is to use the machine learning approach to analyze the data of the League of Legends and make a prediction about the result of the game. In this research, the method of machine learning is applied to the dataset which records the first 10 minutes in diamond-ranked games. Several popular machine learning (AdaBoost, GradientBoost, RandomForest, ExtraTree, SVM, Na�ve Bayes, KNN, LogisticRegression, and DecisionTree) are applied to test the performance by cross-validation. Then several algorithms that outperform others are selected to make a voting classifier to predict the game result. The accuracy of the voting classifier is

The main motive of our project is to detect stress in the IT professionals using vivid Machine learning and Image processing techniques. Our system is an upgraded version of the old stress detection systems which excluded the live detection and the personal counseling but this system comprises of live detection and periodic analysis of employees and detecting physical as well as mental stress levels in his/her by providing them with proper remedies for managing stress by providing survey form periodically. Our system mainly focuses on managing stress and making the working environment healthy and spontaneous for the employees and to get the best out of them during working hours.

Communicating with everyone through hand gestures is, of course, called sign language. It is the ideal language of communication among the deaf-mutes in this society. The Deaf-Mute Network recognizes positive everyday barriers to communicating with the people they meet. The World Health Organization's most up-to-date test report shows that a very large percentage of the world (about 360 million parents) have hearing problems, i.e., 5.3% of the world's population. This makes us want to invent an automated system that converts hand gestures into meaningful phrases and sentences. A convolutional neural network (CNN) is used on 24 American Sign Language hand gestures to simulate the comfort of verbal communication. Text mining algorithms is proposed and vice versa in this document.

Thyroid disease is one of the most common diseases among the female mass in Bangladesh. Hypothyroid is a common variation of thyroid disease. It is clearly visible that hypothyroid disease is mostly seen in female patients. Most people are not aware of that disease as a result of which, it is rapidly turning into a critical disease. There are two types of thyroid diseases namely 1. Hyperthyroid and 2.Hypothyroid. Here in this project, we have attempted to predict hypothyroid in the primary stage. Feature selection techniques used by us are Recursive Feature Selection(RFE)along with classification algorithms named Support Vector Machine(SVM), Decision Tree(DT), Random Forest(RF), Logistic Regression(LR) and Naive Bayes(NB). By observing the results, we could extrapolate that the RFE feature selection technique helps us to provide constant 99.35% accuracy.

A sedentary lifestyle, bad diet, stress from work causes diabetes, which can also cause many fatal health problems like heart attack, stroke, kidney failure, nerve damage, etc. Automated scanning (ML) strategies are highly effective for early detection and prediction of diabetes. The aim of this report is to provide a comprehensive review of diabetes analysis using supervised and unsupervised system knowledge algorithms. This survey consists of articles about the 2018-2020 Diabetes Assessment. The algorithms are entirely based on decision trees, AdaBoost, XGBoost, etc., and predict diabetes with extraordinary accuracy. Unsupervised knowledge techniques along with PCA and K-Mean are also useful for feature selection and external detection from large datasets. This analysis shows that K-Mean and SVM also diagnosed and assessed diabetes mellitus with excellent accuracy as a combination of supervised and unsupervised device monitoring techniques.

Chronic Kidney Disease (CKD) is a type of chronic disease which means it happens slowly over a period of time and persists for a long time thereafter. It is deadly at its end stage and will only be cured by kidney replacement or regular dialysis which is an artificial filtering mechanism. It is important to identify CKD at an early stage so that necessary treatments can be provided to prevent or cure the disease. The main focus of this project is on the classification techniques, that is, tree-based decision trees, random forest, and logistic regression have been analyzed. Different measure has been used for comparison between algorithms for the dataset collected the from standard UCI repository.

The project is to develop a model for human actions such as running, jogging, walking, clapping, handwaving and boxing etc. A series of videos is given for the layout, where an individual executes an event in each video. The action performed on that particular video will be the label of a video. This relationship must be learned by the model, and the label of an input (video) which he never saw can then be predicted. Technically, despite descriptions of these acts, the model would need to learn to distinguish between various human behaviors. There may be many content identification programs which can work on following jobs like Active object tracking for identifying an item such as a vehicle or a human from a CCTV picture and learning the patterns in the movement of humans when we are able to create a pattern that will guide us (humans) to perform a variety of activities.

Stroke is the leading cause of life loss in many countries .This project aims to classify stroke patients into ischemic and hemorrhagic subgroups using optimized CT scan images and eight different machine learning algorithms. We pre-processed data with advanced image optimization techniques to improve image quality and minimize noise. Evaluation metrics such as accuracy, precision, recall, and F1-score were employed to assess algorithm performance. Results indicate success rates for stroke classification. The combination of optimized imaging and machine learning algorithms offers promising insights for enhancing stroke diagnosis and treatment outcomes, potentially reducing stroke-related mortality.

To address security issues caused by network vulnerabilities, tools, and area-based Internet utility vulnerability detection technique has been proposed to effectively prevent programmatic website script attacks. Reduce the spread of network and community security incidents. An indepth look at the latest exploit detection technology, exploit detection test with machine development techniques, exploit detection version requirements, and website scripts. The security vulnerability detection model is designed for .NET applications and is fully based on popular and advanced network vulnerability detection tools, an authentication code detection

Interpersonal interaction correspondence has acquired an everyday public way of addressing the network. Informal correspondence refers to the use of live packets and destinations on the Internet. Twitter is one of the main web-based media in use today. People share their inclinations with the post in many activities in our daily life. What if valuation becomes a huge addiction. In any case, Twitter's strong example of representation of ideas is compromised by a few problems: the particularly unbalanced beauty of calculating different patterns, the problems of explanatory extravagance of emotional labels, and the use of different everyday semantic paradigms. These problems are extreme given the fact that different forms of evaluating online presence are based on subtle insights spread from Twitter. There also appears to be a need for a form of book selection recommended for Twitter cognition research. Twitter data usage estimates are widely attributed to this record. Words and phrases express people's views on things, groups, governments and activities through the method of electronic management structures. Depolarizing the coolest, terrible, or non-partisan content in digital life is called the NLP Skepticism Assessment Project. The remarkable development of association requests from industrial companies and governments, influences specialists to take their exams within the so-called exam. This exploration uses three top-rated ML SVMs, logistic regression, random forests, and a Naive Bayes classifier to increase the overall product score. The scans are completed using datasets from Twitter Yelp. This statistic is on the Internet on the net. Discussion, verbal exchange, fashion objections, and placements are all part of evaluating valuable resources where commentary or published articles are closest to your general inclinations or causes of the problem.

The aim of this project is to perform a grayscale normalization of a selected image and thereafter to reduce the effect of illumination differences. Normalization is considered so that CNN works in a faster manner. The Image Data Generator group in Keras provides a matching set of techniques for scaling pixel standards in the image dataset subsequent to modeling. The Keras functional API provides an additional flexible approach for significant models.

The leading intention of the project is to provide a new approach for image recognition using Python and its library in which we extensively use python libraries like numpy, Bing image downloader, matplotlib, sklearn and several others as well for the use of machine learning and its properties like support vector machine (SVM). An image recognition technique utilizing aa info of image characteristics is introduced.

Pneumonia is an infection of the lower part of the respiratory tract in which the airways and lungs are affected. The risk of pneumonia is critical for many, particularly in developing countries where billions of people facing the air pollution problems. The World Health Organization estimates that more than 4 million premature deaths occur yearly from household air pollution-related illnesses, including pneumonia. The X-ray is very important for detecting the pneumonia. This project is very use full for doctors. This is not a time consuming process and no need of high Quality machines and specialists. Here in my project i used deep learning algorithms to process chest X-ray images in order to support the decision making process in determining the correct diagnosis. This algorithm predicts the whether the pneumonia is present or not.

the technological advancement in the field of medical science for the detection, classification and identification of several diseases is making the diagnosis process easier and efficient at the same time, provides a helping hand for medical practitioners in saving life. Health experts are making use of these most advanced technological practices for reaching at conclusions in the area of health care. Brain tumor detection is one of the key major challenges in medical field. Early detection of tumor plays the most important role in fixing the most efficient treatment techniques for increasing the survival rate of patients. Manual detection of tumors for diagnosing cancer from data generated from clinical instruments is a time consuming task and the efficiency depends upon the radiologist. So through this paper, we are proposing methods for automating the detection process which can help the radiologist reaching at a faster conclusion in an efficient manner.

With the continued expansion in employer size, a single offline revenue model cannot meet the demand. To keep up with the current trends of the Internet age, companies want to expand their e-commerce platform. Many e-commerce websites introduce the record mining era. Based on customer�s purchase records and past browsing statistics, they can discover products they like and recommend them to customers to improve the level of dealers and the competitiveness of the internet business market.

The success of machine learning algorithms in medical imaging has increased the need for artificially trained models to make them work in the medical field more quickly and efficiently. This paper gives a technique to identify bone fracture using machine learning algorithms, by which workload for orthopedics can be reduced. The significant use of machine learning in this era of big medical data would help gather information from the available x-ray images rather than spending hours in the radiology departments. This paper presents imaging technologies used to identify bone fracture in the human body and give quick results once the x-ray has been taken.

The COVID-19 pandemic has created a major disaster that affects most people's health in most towns in the region, taking a toll on human health. The comparative model is developed with unique differences: 20, 50, 100, 300, and 500. Our main goal is to decide whether a person in a photo/video broadcast is wearing a face mask with the help of deep learning and deep understanding."Deep learning based face mask detection using yolov5 algorithm for real-time streaming and image detection" is a comprehensive project designed to deploy a robust and efficient face mask detection system.The model is trained on a diverse dataset to ensure high accuracy and adaptability to various environmental conditions.

The life of humans living without liver disease is one of the fundamental care of every human. Therefore, for better care detection of liver disease at a primary phase is necessary. For medical experts, predicting the early stage of liver disease is a very difficult task. So, our current work aims to solve the liver disease problem by using machine learning methods.

Today, it is normal for humans to experience mild depression in various situations. A stress capacity is sufficient for a function. However, too much stress affects a person's mental well- being, and if it is neglected for too long, it is a definite risk of suicide. Long-term stress is associated with health problems. With an increasing number of people facing technological stress, it is crucial to address it as soon as possible and help humans understand and control it before it causes further harm. Traditional techniques for assessing stress levels include interviewing the individual and observing facial expressions. This study represents an in-depth investigation of human stress detection using support vector machine (SVM) algorithm. Accurately detecting stress can prevent psychological and physical problems.

Currently, obesity has become one of the major international threats. Obesity refers to an abnormal or unnatural amount of fat in our body. People live bad lives, eat too much junk food, sleep too late and sit too long. Young people are especially vulnerable to their unconscious behaviors. It is a systemic problem known as a fully complex disease. It promotes the spread of complex diseases, stroke, coronary heart disease, liver cancer and many types of cancer. The objective of this paper is to develop an approach based primarily on device handling to estimate the probability of weight problems using machine handling algorithms. The aim of the article is to recognize the outcome of obesity on ANS utilizing by HRV parameters. Originally, 16 older adults and 16 heavy subjects among the ages of 20 and 50 participated in the trial. At the same time, a SMOTE approach was utilized to extend the control sample period. Overweight subjects ranged from 16 to 48

In developing countries like India, agriculture is excess, but food security remains a major problem. Most flowers are lost due to garage installations, transportation and plant diseases. More than 15% of crops in India are lost due to disease. So, fixing it becomes the first issue. There is a need for an automated machine that can detect these diseases and help farmers take appropriate measures to delay crop failure. Farmers have followed the traditional method of visual detection of plant diseases, and now it is not possible for all farmers to detect even these diseases. With the advancement of artificial intelligence, he wants to add centres of imagination and clairvoyance to agriculture. Deep expertise libraries and a human- and developer-friendly environment to work with � those types of features make deep learning a good way to tackle this problem. This document uses deep learning as it offers instant paint for fast results, especially on images. This method involves taking leaves from infected plants and labelling them according to the disease pattern. Images of swollen leaves are processed simultaneously on a pixel basis, and operations are performed to improve image registration. As a next step, feature extraction is performed, followed by image segmentation, and in the remaining crop disease categories, it is mainly based on samples taken from diseased leaves.

Traffic sign Recognizer (TSR) and visibility are important to aid engine pressure and protect drivers, pedestrians, and vehicles. To find ways to push, drivers sometimes forget road signs and signals, and alerts on the road or extreme weather conditions (e.g., fog, rain, and many others) make things difficult for drivers and pedestrians. Our software will help the device to detect and understand the signs and symptoms of visitors without losing the focal point of the driving force while driving .The TSR framework makes it easy for drivers to use road signs and symbols to provide sufficient data about the road. The auto industry has become a big business, and some groups are trying to collect autonomous vehicles that site visitors sign because popularity is important to remember. One version is built using a cnn, and this version will recognize the signs and symptoms of website visitors to understand their signs and symptoms. This version can also be done on common engines to report visitor signs and symptoms and the driving force of symptoms through content recognition.

Farmer suicides have become an urgent social problem which governments around the world are trying hard to solve.Most farmers are driven to suicide due to an inability to sell their produce at desired profit levels, which is caused by the widespread uncertainty/fluctuation in produce prices resulting from varying market conditions. To prevent farmer suicides, this paper takes the first step towards resolving the issue of produce price uncertainty by presenting PECAD, a deep learning algorithm for accurate prediction of future produce prices based on past pricing and volume pattern.

During the diagnostic process, the dentist must interpret salient patterns of dental problems, such as the number of teeth and associated diseases. Segmentation of dental X-ray images is useful to help clinicians monitor dental conditions and detect dental disease. This paper aims to discuss the in-depth knowledge and lightweight techniques of dental X-ray image segmentation

Now a days, employee health and well-being is the most important consideration in the work place. Because it will affect the productivity of an individual employee and team contribution. the automatic facial expression analysis using machine learning has become an interesting and active research area from past few decades. Real time Employee Emotion Detection System (RtEED) has been proposed to automatically detect employee emotions in real time using machine learning. RtEED system helps the employer can check well-being of employees and identified emotion will be intimated to respective employee through messages.

Security is always a main concern in every domain, due to a rise in crime rate in a crowded event or suspicious lonely areas. Abnormal detection and monitoring have major applications of computer vision to tackle various problems. Due to growing demand in the protection of safety, security and personal properties, needs and deployment of video surveillance systems can recognize and interpret the scene and anomaly events play a vital role in intelligence monitoring. This paper implements automatic gun (or) weapon detection using a convolution neural network (CNN) based SS D and Faster RCNN algorithms. Proposed implementation uses two types of datasets. One dataset, which had pre-labelled images and the other one is a set of images, which were labelled manually. Results are tabulated, both algorithms achieve good accuracy, but their application in real situations can be based on the trade-off between speed and accuracy.

In this project, Object Detection and Tracking System (ODTS) in combination with a well-known deep learning network, Faster Regional Convolution Neural Network (Faster R-CNN), for Object Detection and Conventional Object Tracking algorithm will be introduced and applied for automatic detection and monitoring of unexpected events on CCTVs in tunnels, which are likely to (1) Wrong-Way Driving (WWD), (2) Stop, (3) Person out of vehicle in tunnel (4) Fire. This system makes it possible to track a moving object in time, which is not usual to be achieved in conventional object detection frameworks.

To achieve safe driving of vehicles, it is necessary to perceive information about the vehicle's surroundings, and computer vision is one of the key technologies to solve this problem. The YOLO series and SSD, RetinaNet algorithm are representative of one-stage target detection algorithms, which have high accuracy and high speed. YOLOv4 is the latest algorithm of YOLO series, which has improved the speed and accuracy of vehicle target detection than before, but there is still a distance from the real real-time in vehicle detection. This paper proposes an improved YOLOv4-based video stream vehicle target detection algorithm to solve the problem in the detection speed which is not fast enough. This paper first introduces the YOLOv4 algorithm theoretically, then proposes an algorithmic process to speed up the detection speed, and finally conducts practical road experiments. From the experimental results, the algorithm of this paper can improve the detection speed of the algorithm without losing accuracy, which can provide a basis for decision making for safe vehicle driving.

Malefic Cancer will create pleasant effect on people. Much of the research on this topic has been done to judge benign and malignant images and to classify unique types of skin lesions. Therefore, within the approach of skin and porous lesions, beauty, segmentation, feature extraction, and type of dermoscopic images will play an important role. In this record, we are focusing on the class description. We are using the MNIST HAM 10000 dataset. This document contains gadgets. In the first step, we argued that, during mode, a balanced data set would provide greater accuracy than an unbalanced set of data. Therefore, to balance the data set, we use a sampling method called Synthetic Minority Oversampling Technique (SMOTE), which significantly improves the accuracy of most device knowledge models. We then evaluated the accuracy of several device learning algorithms that we ran. As a result, we conclude that the support vector system concept provides higher accuracy than other systems that derive knowledge from algorithms based on polynomial kernels, such as selection tree, Gini, and entropy index. Use of A set of regression laws. We chose precision, do not forget, and F1-rank as valid evaluation metrics. On our device, at best, we got 96.825% accuracy with Support Vector Machine using Polynomial Kernel. Since XGBoost is a gradient. When iterating through a set of rules, the final result provided using the algorithm may vary. To validate the accuracy obtained from the XGBoost ruleset, we used the OK-fold cross-validation method on the XGBoost approach. On our device, we used ok = 10 within the exact fold-omit validation algorithm and obtained an accuracy of 95.984% and concluded that the SVM with polynomial kernel gave higher accuracy than all other algorithms.

Nowadays, more individuals are being diagnosed with diseases that are becoming chronic due to not following the proper diet, not doing proper exercise regularly, or not giving proper attention to the diseases because of busy schedules. Hence, we propose a system that aims at improving the health of the patients suffering from various diseases by recommending them healthier diet. Our System can be essentially useful for the doctors to recommend diet based on the reports and personal health details.For the Diet and Exercise Recommendation module, the algorithm that is used is a Decision tree for classification. To be precise, C4.5 is used to give recommendations of diet. A C4.5 Decision tree will help recommend and determine if a particular food item should be given to a particular individual or not with respect to our customized�datasets.

Agricultural experts have done important work on rice plant Parallel Random Forest (CPRF) algorithm to evaluate the applicable information within the last period. Confronting problems of protection. However, the problem of plant diseases has not been investigated in depth until now. In this text, we have explored a sample of rice diseases using the Continuously large size and asymmetry within the statistical distribution of agricultural facts. The proposed technique reduces the scale and potential impact of skewed logs with the help of multiple random forest configurations. For the empirical evaluation, we used the Spark platform to investigate the vegetation records of several provinces in China for twenty years. Results for CPRF transcripts for plant diseases affecting rice yield are presented, as well as results using random forests, CRF, and Spark-MLRF. The accuracy of CPRF is 96.253%, which is better than other algorithms. These results indicate that CPRF and mass data assessment are useful in solving vegetation degradation problems.

The novel coronavirus disease 2019 (COVID-19) has been an extreme health problem that affects the respiratory system and has spread rapidly from humans to other parts of the world. The limited diagnostic strategies are applied to detect patients with Covid-19, which are not effective in overcoming this issue. In this text, deep neighborhood awareness techniques are used to detect the inflammatory regions of the corona virus in the lung. A deep convolutional neural network for large-scale segmentation of the infected community, identifying the specific affected region and evaluating it in a fully deterministic convolutional network in COVID-19 and non-COVID-19 cases. CNN was used to end up labeling it collectively. The proposed model is primarily tested based on detection, segmentation, and sophistication using a validated, qualified dataset of humans infected with COVID-19.

Customer churn is one of the biggest issues within the telecommunications industry. In the telecom industry, attracting new customers to your network costs more than retaining existing customers. Therefore, it is very important to develop customer churn and techniques to prevent customers from switching to their current issuer. Various sophisticated customer forecasting models and techniques developed by specialized researchers are largely successful. Data mining strategies have proven useful in predicting which customers will switch between their telecommunications businesses. With this forecast, the telecommunication company can implement various customer retention plans. This article reviews several statistical mining strategies for churn prediction.

Generally, wheat grows well in moderate temperatures. By predicting wheat yield accurately, farmers can make decisions about their farming practices. They can plan their planting, irrigation, fertilization, and pest control strategies more effectively. Without accurate yield predictions, resources like water and fertilizers could be used inefficiently, leading to waste and increased costs. To overcome this problem I developed this Project. When we are knowing the production of a crop, it may help the farmers can know the yield of wheat.

Parkinson�s disease is a neurodegenerative disease which worsens over time. People have trouble vocally, writing, strolling, or completing other simple tasks when dopaminegenerating neurons in parts of the brain become impaired or expire. These symptoms worsen over time, increasing the severity of the condition in patients. We have suggested a methodology in this article for the prediction of Parkinson�s disease severity using deep neural networks on UCI�s Parkinson�s Telemonitoring Vocal Data Set of patients. We have created a neural network to predict the severity of the disease and a machine learning model to detect the disorder. Classification of Parkinson�s Disease is done by Neural network, Random Forest Classifier.

Food image classification is an emerging research field due to its increasing benefits in the health and medical sectors. For sure, in the future automated food recognition tools will help in developing diet monitoring systems, calories estimation and so on. In this paper, automated methods of food classification using deep learning approaches are presented. SqueezeNet and VGG-16 Convolutional Neural Networks are used for food image classification.

The main aim of this project to develop a classification system for agricultural articles using CNN algorithm. It is used to solve the time -consuming and labuor intensive problem of classifying agricultural articles . The rapid growth of agricultural information on the internet has made it challenging for researchers , farmers to efficiently locate relevant literature. This system is used for solving this issues and classifies the agricultural articles into different categories like planting , processing , cultivation , Reproduction .

The automobile industry is one of the prominent industries for the national economy. Day by day car is getting popular for the private transport system. The customer needs review when he wants to buy the right vehicle, especially the car. Because it is a very costly vehicle. There are many conditions and factors matter before buying a new car like spare parts, cylinder volume, headlight and especially price. So deciding everything, it is important for the customer to make the right choice of purchase which can satisfy all the criteria. Our goal is to help the customer to make the right decision whether he will buy a car or not. Therefore we wanted to build a technique for decision making in-car buy system. That�s why we propose some wellknown algorithms to get better accuracy for a car purchase in our project. We applied those algorithms in our dataset which contains 50 data. Among them, Support Vector Machine(SVM) gives the best result with 86.7% accuracy of prediction.

Recommendation systems are the most important intelligent systems that plays in giving the information to the users. Previously approaches in recommendation systems (RS) include Content-based-filtering and collaborative filtering. Thus, these approaches had certain limitations as like the necessity of the user history as they visit. So as to make back the effect of such dependencies, this research paper provides a hybrid RS are those which mixes both Collaborative filtering, Content based filtering with sentiment analysis of movies. In this research paper, we developed a recommender system based on the sentiment of the user to suggest the movie to the user based on their view history

Understanding the buying behavior of a pair of consumers (specific variables) using their demographic characteristics (IS characteristics, most of which are self-explanatory) to approximate an exceptional product. This collection of facts includes values, redundant information and device experience. Encapsulation of the retail industry within a location � This idea helps scale expectations that have great business value for store owners because it allows stock Controlling, financial planning, advertising and marketing, and advertising and marketing, advertising and marketing will help. We are developing a model consisting of processing, modeling, schooling, control and evaluation so that managers can automate and complicate part of it. Our proposed algorithm is transformed into a random forest area with the Accuracy of 83.6% and minimum RMSE (root squared errors) of 2829 on Black Friday tire sales data.

Hepatitis is a life-threatening condition caused by inflammation of the liver. It can result from infection of the liver by hepatitis viruses (hepatitis B, hepatitis C, and viral hepatitis). Manual tests can greatly overload evaluation, which has a great impact on men's and women's fitness software. Automated hepatitis prediction, using machine learning strategies such as Naive Bayes , Support Vector Machine (SVM), K-NN, perceptron, and Random Forest, promises to serve as an effective diagnostic tool. Based on this comment, a decision tree is built to predict hepatitis, and another algorithm, K-NN and perception, is executed to predict the same disease. The three learning algorithms are compared with each of them with respect to the volume in which their hepatocytes are located. Comparisons are made using the RAND index and the confusion matrix. By postponing observations that do not contain missing values beyond the reality location feature selection system, we have helped improve the accuracy of our prediction models.

With the development of natural language processing(NLP) technology and machine learning, the research task of automatic English scoring(AES) is becoming clearer and clearer, and the research difficulties arise due to the mutual constraints of research methods and annotation data. How to build a perfect and reliable scoring system has become a great challenge under today's research. In this paper, we designed an English AES system, and verified the effectiveness of RF on English scoring model by analyzing the prediction effect of RF on non-text features and text features, and then compared the Pearson correlation coefficients(PCC) of RF(RF), GBDT, and XGBoost, and the study showed that the performance of RF algorithm is higher than the other two composition scoring methods.

The most qualified applicant for a position must be found through careful consideration of job applications, which is done during the Automated Resume Screening Using Natural Language processing. Automated resume screening is now a practical alternative to the manual screening procedure because to developments in natural language processing .To increase the precision and effectiveness of the screening process, these approaches employ a variety of method for screening automated resumes . The results of this study can help human resource managers and recruiters automate the hiring process and efficiently and impartially identify viable applicants.

As e-commerce has grown in recent years, so online shopping has increased with the number of product reviews posted online. The consumer�s recommendations or complaints influence significantly customers and their decision to purchase. Sentiment polarity analysis is the interpretation and classification of text-based data. The main goal of our work is to categorize each customer�s review into a class that represents its quality (positive or negative). Our sentiment polarity detection consists of the following steps: preprocessing, feature extraction, training, classification and generalization. First, the reviews were transformed into vector representation using different techniques of Tf-Idf and Tokenizer. Then, we trained with a machine learning model of SVM Linear, RBF, Sigmoid kernel and a deep learning model LSTM. After that, we evaluated the models using accuracy, f1-score, precision, recall. Our LSTM model predicts an accuracy of 86% for Amazon-based customer reviews and an accuracy of 85% for Yelp customer reviews

This project aims to predict the prices of sneakers using machine learning techniques. The sneaker market is known for its volatile nature, with prices fluctuating rapidly due to various factors such as brand popularity, limited edition releases, and celebrity endorsements. To tackle this problem, we gathered data from Stock X, a leading sneaker marketplace, and utilized four linear regression models for prediction. Through our analysis, we found that the Ordinary Least Squares (OLS) regression model exhibited the highest accuracy in predicting sneaker prices. Our study demonstrates the potential of machine learning in forecasting sneaker prices, providing valuable insights for both consumers and sellers in this dynamic market.

In the modern era, everyone tries to be aware of their health, but because of their workload and hectic schedules, they only pay attention to it when certain symptoms appear. However, because CKD (Chronic Kidney disease) is a disease with no symptoms or, in some cases, no symptoms at all, it is difficult to predict, detect, and prevent such a disease, which could result in long-term health damage. However, machine learning (ML) offers hope in this situation because it excels at prediction and analysis. In this paper, we proposed nine ML approaches, such as K-nearest neighbors (KNN), support vector machines (SVM), logistic regression (LR), Na�ve Bayes, Extra tree classifiers, AdaBoost, Xgboost, and LightGBM. These predictive models are built using a dataset on chronic kidney disease with 14 attributes and 400 records to choose the best classifier for predicting chronic kidney illness. The dataset was gathered via Kaggle.com. Additionally, this study has compared how well these model�s function. With the LightGBM model, we could predict kidney illness more accurately than ever before, with a 96.00% accuracy level.

In current situation, we come across various problems in traffic regulations in India which can be solved with different ideas. Riding motorcycle without wearing helmet is a traffic violation which has resulted in increase in number of accidents and deaths in India. Existing system monitors the traffic violations primarily through CCTV recordings, where the traffic police have to look into the frame where the traffic violation is happening, zoom into the license plate in case rider is not wearing helmet. But this requires lot of manpower and time as the traffic violations frequently and the number of people using motorcycles is increasing day-by-day. What if there is a system, which would automatically look for traffic violation of not wearing helmet while riding motorcycle and if so, would automatically extract the vehicles' license plate number. Recent research have successfully done this work based on CNN, R-CNN. But these works are limited with respect to efficiency, accuracy or the speed with which object detection and classification is done. In this research work, a Non-Helmet Rider detection system is built which attempts to satisfy the automation of detecting the traffic violation of not wearing helmet and extracting the vehicles' license plate number. The main principle involved is Object Detection using Deep Learning. Then the license plate registration number is extracted using OCR . All these techniques are subjected to predefined conditions and constraints, especially the license plate number extraction part. Since, this work takes video as its input, the speed of execution is crucial.

This paper deals with the prediction of Diabetes Disease by performing an analysis of five supervised machine learning algorithms, i.e. K-Nearest Neighbors, Na�?ve Baye, Decision Tree Classifier, Random Forest and Support Vector Machine. Further, by incorporating all the present risk factors of the dataset, we have observed a stable accuracy after classifying and performing cross-validation. We managed to achieve a stable and highest accuracy of 76% with KNN classifier and remaining all other classifiers also give a stable accuracy of above 70%. We analyzed why specific Machine Learning classifiers do not yield stable and good accuracy by visualizing the training and testing accuracy and examining model overfitting and model underfitting. The main goal of this paper is to find the most optimal results in terms of accuracy and computational time for Diabetes disease prediction.

controlling and defensive the higher air greatness has gotten one in everything about first imperative occasions in different creating and metropolitan districts at the present. The greatness of air is adversely contacting collectible to the different styles of tainting influenced through the transportation, power, powers consumptions, and so forth. In our country population is a big problem as day by day population is increasing, so the rapid increasing in population and economic upswing is leading environment problems in city like air pollution, water pollution etc. In some of air pollution and air pollution is direct impact on human body. As we know that major pollutants are arising from Nitrogen Oxide, Carbon Monoxide & Particulate matter (PM), SO2 etc. Carbon Monoxide is arising due to the deficient Oxidization of propellant like as petroleum, gas, etc. nitrogen oxide (NO) is arising due to the ignition of thermal fuel; Sulphur Dioxide(So2) is major spread in air, So2 is a gas which is present more pollutants in air, it�s affect more in human body. the predominance of air is overstated by multidimensional impacts containing spot, time and vague boundaries. The goal of this improvement is to take a gander at the AI basically based ways for air quality expectation. In this paper we will predict of air pollution by using machine learning algorithm.

The current paper presents a fine-grained image recognition problem, one of multi-class classification, namely determining the breed of a dog in a given image. The presented system employs innovative methods in deep learning, including convolutional neural networks. Two different network are trained and evaluated on the Stanford Dogs dataset. The usage/evaluation of convolutional neural networks is presented through a software system. It contains a central server and a mobile client, which includes components and libraries for evaluating on a neural network in both online and offline environments.

Progression and evolution of technology has super- seeded mechanical human workload in almost every domain with the operation of machines. The currency paper recognition is applicable in various domains of automatic selling goods systems and in banking systems. In the modern transition world for the automatic current recurring systems, the precise identi?cation of paper currency notes is indeed an essential need. Machines often ?nd it dif?cult in identifying and recognising the currencies in the market when the currency notes have turned bleary and damaged. It is hard for visually disabled people without any technological support or assistance to predict and analyse genuine currency notes. The accuracy of currency notes analysis identi?cation have been re?ned and boosted throughout with the assistance of these models.

Text-based passwords are currently the most widely used form of authentication and are expected to remain so. However, since these passwords are typically made up of meaningful strings, machine learning and deep learning algorithms can help developers assess their strengths and predict their vulnerability to brute-force attacks. Advanced techniques such as Long Short-Term Memory (LSTM) and Generative Adversarial Networks (GAN) can generate lists of similar and expected text passwords by learning the patterns of how users create and select their passwords. This paper explores using machine learning algorithms to categorize passwords into three levels: strong, moderate, and weak. We also evaluate whether machine learning or deep learning techniques can learn the patterns used in hashing techniques. Furthermore, we have developed a password generation model using Gated Recurrent Unit (GRU) to create new passwords based on learned patterns. With this approach, we aim to improve password security and enhance the user experience of creating and managing passwords.

Depression has become a serious problem in this current generation and the number of people affected by depression is increasing day by day. However, some of them manage to acknowledge that they are facing depression while some of them do not know it. On the other hand, the vast progress of social media is becoming their �diary� to share their state of mind. Several kinds of research had been conducted to detect depression through the user post on social media using machine learning algorithms

The integration of artificial intelligence (AI) into healthcare systems has significantly transformed patient care and management. This abstract presents an overview of an AI-enabled healthcare management system designed to optimize healthcare delivery, enhance patient outcomes, and streamline administrative processes. The AI-enabled healthcare management system leverages advanced machine learning algorithms and natural language processing techniques to analyze vast amounts of medical data efficiently. By harnessing the power of AI, healthcare providers can make data-driven decisions, personalize treatment plans, and improve diagnostic accuracy.

Popularity prediction using social media is an important task because of its wide range of real-world applications such as advertisements, recommendation systems, and trend analysis. However, this task is challenging because social media is affected by multiple factors that cannot be easily modeled (e.g.quality of content, relevance to viewers, real-life events). Usually, other methods adopt the greedy approach to include as many modalities and factors as possible into their model but treat these features equally.To solve this phenomenon, our proposed method leverages the self-attention mechanism to effectively and automatically fuse different features to achieve better performance for the popularity prediction of a post, where the features used in our model can be mainly categorized into two modalities, semantic (text) and numeric features.

Placement of students is one of the most important objective of an educational institution. Reputation and yearly admissions of an institution invariably depend on the placements it provides it students with. That is why all the institutions, arduously, strive to strengthen their placement department so as to improve their institution on a whole. Any assistance in this particular area will have a positive impact on an institution�s ability to place its students. This will always be helpful to both the students, as well as the institution. In this study, the objective is to analyse previous year's student's data and use it to predict the placement chance of the current students. This model is proposed with an algorithm to predict the same. Data pertaining to the study were collected form the same institution for which the placement prediction is done and also suitable data pre-processing methods were applied. This proposed model is also compared with other traditional classification algorithms such as Decision tree and Random forest with respect to accuracy, precision and recall. From the results obtained it is found that the proposed algorithm performs significantly better in comparison with the other algorithms mentioned.

In this paper, we present a resource allocation mechanism for the problem of incentivizing filtering among a finite number of strategic social media platforms. We consider the presence of a strategic government and private knowledge of how misinformation affects the users of the social media platforms. Our proposed mechanism incentivizes social media platforms to filter misleading information efficiently, and thus indirectly prevents the spread of fake news. In particular, we design an economically inspired mechanism that strongly implements all generalized Nash equilibria for efficient filtering of misleading information in the induced game. We show that our mechanism is individually rational, budget balanced, while it has at least one equilibrium. Finally, we show that for quasi-concave utilities and constraints, our mechanism admits a generalized Nash equilibrium and implements a Pareto efficient solution.