A Study on Capital Asset Pricing Model (CAPM) with reference to selected Banking Stocks traded at BSE

Project synopsis

RATIONALE OF THE STUDY:

The Study on the capital asset pricing model in equity shares of banking companies will be undertaken with the objective of getting an insight into the concept of investments, market risk, security market line, undervalued and overvalued stocks, the risks, and the returns. The study aims to determine the market risk involved in the investments and the factors affecting the market risk and to determine the required rate of returns. The other objectives of the study are to observe the security market line and the degree of volatility of the Banking industry and undervalued and overvalued stocks.

OBJECTIVES OF THE STUDY:

To observe the risk-free rate and evaluate the relationship between risk and return involved in equity share prices of the banking industry.
To observe the significant risk of shares (market risk or systematic risk).
To observe the relationship between the security market line and the capital market line
To develop the inputs required for applying the capital asset pricing model.
To produce a benchmark for evaluating various investments and finding out whether the stocks are under or overvalued.

RESEARCH METHODOLOGY

Method of data collection:

The Historical data of share prices for the period of one year will be collected from the BSE index for the study.

Source of data

Secondary data will be collected from respective websites like Bseindia.com, Moneycontrol.com, and other financial Journals.

Period of the study

The study will be done for a period of 30-40 days.

Data analysis tools:

Appropriate data tools like Beta, Mean, and Standard deviation will be used.

LIMITATIONS OF THE STUDY

The study will be based on secondary data only.
The study will be limited to banking stocks only
The time for the project is limited to 30-40 days

SCOPE FOR FURTHER RESEARCH:

The study covers information related to the equities share of the banking sector. It also covers the systematic risk and unsystematic risks of banking companies. The study is confined to only one Sector i.e., the banking industry, and the entire study is based on their Stock prices for a period of the last two years. The present study gives an insight into this issue by analyzing the capital asset pricing model Analysis in Equity share prices of the Banking industry.

March 14, 2022February 9, 2023

A Study on Consumer buying behaviour with reference to Amazon.in

RATIONALE OF THE STUDY:

To study the consumer buying experience at Amazon.in in Hyderabad.
To identify opportunities and the interest of the buyers towards online retailing transactions at Amazon.in
To understand the offers and discounts provided by Amazon.in
To study the problems and dissatisfaction that may be experienced by the customers Amazon.in.

OBJECTIVES OF THE STUDY:

1. To study the consumer buying behaviour towards Amazon.in in Hyderabad

2. To know the factors that influences the Consumers to do purchasing from Amazon.in.

3. To find out the problems faced by young consumers in buying online retail products from Amazon.in.

4. To come out with suitable suggestions towards making online purchases at Amazon.in.

SCOPE OF THE STUDY:

The scope of the study is limited to the buying behaviour of consumers at Hyderabad who do online shopping from Amazon.in. The Main reason of the present study is to find out the online retailing experience of the consumers and their attitude and satisfaction levels. The study also focuses on factors that influence in doing online shopping at Amazon.in and the problems faced by them during placing the order and receiving the product.

RESEARCH METHODOLOGY:

a) RESEARCH DESIGN:

Both Descriptive and exploratory research will be used for this project study. The research of this study involves in both field survey& literature survey, to identify the scope & potential marketing challenges of purchasing from Amazon.in.

Nature of the Data: Primary & secondary data will be used in this project study

Primary data: The descriptive research will be conducted by using primary data which will be collected through the personal interviews using questionnaire as a data collection tool, to identify the scope of retail ecommerce business in India. The primary data is accurate & highly reliable in nature.

Field Study: Field study will be used to collect the primary data from the sample trough the interviews by using questionnaire as data collection tool.

Secondary data: The exploratory research will be conducted by using secondary data which will be collected from various published sources such as retail and e-commerce Journals such as International journal of electronic commerce, Indian Journal of retailing, Indian Journal of Marketing, E commerce magazines, Business Magazines Text books on Retail Management, E-commerce and websites on online retailing and Amazon.in.

b) SAMPLING DESIGN:

Sampling Frame: The Sampling frame will be taken from the population residing in urban Areas in Hyderabad.

Sample Size: The study will be conducted on a sample of 100 Consumers who are frequent buyers from Amazon.in from Hyderabad city.

Sample units: The sample units will be taken from among the 100 consumers residing in selected areas in Hyderabad. The Consumers who are making their online purchases from Amazon.in may be considered for the study.

Sampling Method: This study will be undertaken by using Convenience and Area sampling.

Data Analysis: Charts, tables and percentage analysis will be used for the study.

LIMITATIONS OF THE STUDY:

The primary data will be collected only from online buyers.
The survey will be conducted in only in Hyderabad city only.
The data will be collected only from the urban consumers, who might be aware of the process of online transactions & have their own bank accounts.
The views and opinions of the respondents may change over the period of time.

DIRECTION FOR FURTHER RESEARCH: At present there is a lot of demand for online purchasing. The present study will focus on the purchasing behaviour towards Amazon.in and finding out suitable solutions to make purchasing more interesting and will be a torch bearer for future researchers and online retailing companies can benefit from such survey.

Focusing on the post-purchase experience is the next frontier for online retailers. Now, retailers are extending the customer hand-holding postpurchase with beautiful branded interfaces, delivery visibility, and personalized content. By streamlining customers’ paths to purchase and bringing them back directly into the loyalty loop, brands can convert one-time shoppers into lifelong brand advocates.

March 8, 2022February 9, 2023

Latest CSE Python Projects on ML & AI – 2022

These are the Latest CSE Python Projects on Machine Learning, Deep Learning, Artificial Intelligence, Big Data, Blockchain Technology, Cloud Computing, Data Mining, Networking, Network Security, and Cyber Security domains.

Download the Projects List Here – Python Projects on ML & AI – 2022

Python Projects List – 2022

These are the latest Python Machine Learning & Deep Learning projects for the year 2022.

Characterizing And Predicting Early Reviewers For Effective Product Marketing On Ecommerce Websites
Semi-Supervised Machine Learning Approach For DDoS Detection
5g-Smart Diabetes Toward Personalized Diabetes Diagnosis With Healthcare Big Data Clouds
Credit Card Fraud Detection Using Random Forest & Cart Algorithm
Driver Drowsiness Monitoring System Using Visual Behaviour And Machine Learning
E-Assessment Using Image Processing In ∞Exams
Automating E-Government Using Ai
Eye Ball Cursor Movement Using OpenCV
Filtering Instagram Hashtags Through Crowdtagging And The Hits Algorithm
Converging Blockchain and Machine Learning for Healthcare
Suspicious Activity Detection
Use Of Artificial Neural Networks To Identify Fake profiles
Video-Based Abnormal Driving Behaviourdetection Via Deep Learning Fusions
Crop Yield Prediction And Efficient Use Of Fertilizers
Fake Images Detection
Opinion Mining For Social Networking Sites
Image Classification Using Cnn (Convolution Neural Networks) Algorithm
Cyber Threat Detection Based On Artificial Neural Networks Using Event Profiles
Analysis Of Women’s Safety In Indian Cities Using Machine Learning On Tweets
Construction Site Accident Analysis Using Text Mining And Natural Language Processing Techniques
Performance Comparison Of SVM ,Random Forest, And Extreme Learning Machine For Intrusion Detection
Accident Detection System
A Data Mining-Based Model For Detection Of Fraudulent Behaviour In Water Consumption(Standalone)
Detection Of Lung Cancer From Ct Image Using Svm Classification And Compare The Survival Rate Of Patients Using 3d Convolutional Neural Network(3d Cnn)On Lung Nodules Data Set
Automatic Facial Expression Recognition Using Features Extraction Based On Spatial & Temporal Sequences Using Cnn & Rnn Algorithm
Facial Expression Recognition And Their Temporal Segments From Face Profile Image Sequences Using Yolo Object Detection Algorithm
Cartoon Of An Image
Bird Species Identification Using Deep Learning
A Deep Learning Facial Expression Recognition Based Scoring System For Restaurants
Seer Cancer Incidence Using Machine Learning With Data Analysis
Loan Prediction Dataset Using Machine Learning With Data Analysis
User-Centric Machine Learning Framework For Cyber Security Operations Center
Recolored Image Detection
Robust Malware Detection For IoT Devices Using Deep Eigenspace Learning
Modeling And Predicting Cyber Hacking Breaches
Image-Based Appraisal Of Real Estate Properties
Heart Disease Prediction
Crop prediction using machine learning
Face mask detection using artificial intelligence
Facial attendance system using artificial intelligence
Skin disease prediction using deep learning
Fruit disease prediction using deep learning
Malaria disease prediction using deep learning
Phishing email detection using convolutional neural network
Type 2 diabetes prediction using machine learning
Suicidal tweets detection using machine learning
web community questions and answering
currency recognize system using artificial intelligence
Fake news Detection using machine learning
Detection of fake online reviews using semi-supervised and supervised learning
mobile price prediction using machine learning
Vigorous malware detection for the internet of things devices using machine learning
Estimating the price of houses using machine learning
Predicting the strength of the concrete pillars used in industrial infrastructure
Passive Aggressive Classifier for Detection of Encrypted VPN
speech emotion recognition using mlp algorithm
face emotion recognition system using artificial intelligence
Data Analysis by Web Scraping using Python
A Decision Tree-based Recommendation System for Tourists
A Machine Learning Model for Average fuel consumption in Heavy Vehicles
Density-Based Smart Traffic Control System UsingCanny Edge Detection Algorithm for CongregatingTraffic Information
Image Classification Using CNN (Convolution Neural Networks) Algorithm
Prudent Fraud Detection in Internet Banking
Twitter sentimental analysis
Android malware detection using Machine learning techniques
Missing Child Identification System using DeepLearning and Multiclass SVM
Emotion-Based Music recommendation system
Stress Detection in IT Professionals
Cryptocurrency Price Analysis with Artificial Intelligence
Object detection using artificial intelligence
Using Deep Learning to Predict Plant Growth and Yield in Greenhouse Environments
Human Activity Recognition
Deep Learning Model for Detecting COVID-19 on Chest X-Ray Using Convolutional Neural Networks
Encryption And Decryption Algorithm Based On Neural Network
FAMD: A Fast Multi-feature Android Malware Detection Framework, Design, and Implementation
Image Super-Resolution using Convolution Neural Networks and Auto-encoders
Lip Reading using Neural Networks and Deep learning
Image Segmentation with Mask R-CNN
Open Pose: Real-time Multi-Person 2D Pose Estimation using Part Affinity Fields
Tuning Malconv: Malware Detection With Not Just Raw Bytes
A Hybrid Fuzzy Logic-based Deep Learning Approach for Fake Review Detection and Sentiment Classification of Amazon Food Reviews
News Text Summarization Based on Multi-Feature and Fuzzy Logic
An Android Malware Detection Approach Based on SIMGRU
Access Control and Authorization in Smart Homes: A Survey
Spam Detection for Youtube Comments
Animal Classification using Facial Images with Score-Level Fusion
An Enhanced Anomaly Detection in Web Traffic Using a Stack of Classifier Ensemble
Automatic Corpus Creation and Annotation for Natural Language Processing of Telugu
Blockchain for Secure EHRs Sharing of Mobile Cloud-Based E-Health Systems
CaptionBot for Assistive Vision
A joint multi-task CNN for cross-age face recognition
Cyber security Tools for IS Auditing
Cyber Threat Detection Based on Artificial Neural Networks Using Event Profiles
A Deep Learning Approach for Effective Intrusion Detection in Wireless Networks using CNN
Digital Image Encryption Algorithm Based on Elliptic Curve Public Cryptosystem
Toward Universal, Word Sense Disambiguation Using Deep Neural Networks
An Expert System for Insulin Dosage Prediction
An Efficient Gait Recognition Method for Known and Unknown Covariate Conditions
Self-Diagnosing Health Care Chatbot using Machine Learning
Machine learning Models for diagnosis of the diabetic patient and prediction insulin dosage
An Improved Approach to Movie Recommendation System
Efficient Privacy-Preserving Machine Learning for Blockchain Network
Sentiment Analysis to Classify Amazon Product Reviews Using Supervised Classification Algorithms
A Deep Learning Approach for Effective Intrusion Detection in Wireless Networks using CNN
SE-Enc: A Secure and Efficient Encoding Scheme Using Elliptic Curve Cryptography
Secure Image Transmission Using Chaotic-Enhanced Elliptic Curve Cryptography(JAVA)
Predicting Stock Market Trends Using Machine Learning and Deep Learning Algorithms Via Continuous and Binary Data a Comparative Analysis
Multimedia summarization
Quality Risk Analysis for Sustainable Smart Water Supply Using Data Perception
Android Permission Control App(ANDROID)
Increasing the Performance of Machine Learning-Based IDSs on an Imbalanced and Up-to-Date Dataset
Fake Image Identification
Non-Binary Image Classification using Convolution Neural Networks
Robust Intelligent Malware Detection Using Deep Learning
Construction site accident analysis using text mining and natural language processing techniques
Cyber Threat Detection Based on Artificial Neural Networks Using Event Profiles
Data Recovery
Context-Based Image Processing Using Machine Learning Approaches
A Knowledge-Based Recommendation System That Includes Sentiment Analysis and Deep Learning
Robust Intelligent Malware Detection Using Deep Learning
Rossman Stores Sales Prediction
A Driving Decision Strategy (DDS) Based on Machine learning for an autonomous Vehicle
A Machine Learning-Based Lightweight Intrusion Detection System for the Internet of Things
A Model for prediction of consumer conduct using a machine learning algorithm
An automatic garbage classification system based on deep learning
Detection of fake online reviews using semi-supervised and supervised learning
Forensic Scanner Identification Using Machine Learning
Use of Artificial Neural Networks to Identify Fake Profiles
Analysis and Prediction of Industrial Accidents Using Machine Learning
Credit Card Fraud Detection Using Random Forest & Cart Algorithm
Identification of covid-19 spreaders using multiplex networks approach
Object Tracking Using Python from Video
Software Defect Estimation Using Machine Learning Algorithms
MamaBot: A System Based on ML and NLP for Supporting Women and Families during Pregnancy
Deep Texture Features for Robust Face Spoofing Detection
Prediction of loan eligibility of the customer
Using Deep Learning to Predict Plant Growth and Yield in Greenhouse Environments
A Malware Detection Method for Health Sensor Data Based on Machine Learning
Blood Cell Types Classification Using CNN
Feature extraction for classifying students based on their academic performance
Hazard Identification and Detection using Machine Learning Approach
Effective Heart Disease Prediction using Hybrid ML Algorithms
Noise Reduction in Web Data A Learning Approach Based on Dynamic User Interests
Online Book Recommendation System by using Collaborative filtering and Association Mining
Sentiment Analysis Using Telugu SentiWordNet
Soil Moisture Retrieval using Groundwater Dataset using Machine Learning
A Time-Series prediction model using long-short-term memory networks for the prediction of Covid – 19 data
Detection of Cyber Attacks in Network using Machine Learning Techniques
Duplicate Question Detection with Deep Learning in Stack Overflow
Machine Learning Techniques Applied To Detect Cyber Attacks On Web Applications
Performance Analysis and Evaluation of Machine Learning Algorithms in Rainfall Prediction
A Machine Learning Model for Average Fuel Consumption in Heavy Vehicles
Accident Detection
BAT Deep Learning Methods on Network Intrusion Detection Using NSL-KDD Dataset
Online Book store
Data Poison Detection Schemes for Distributed Machine Learning
Detecting At-Risk Students With Early Interventions Using Machine Learning Techniques
Detection of Possible Illicit Messages Using Natural Language Processing and
Machine Learning-Based Approaches for Detecting COVID-19 using Clinical Text Data
Personalized effective feedback to address students’ frustration in an intelligent tutoring system
Research on Recognition Model of Crop Diseases and Insect Pests Based on Deep Learning in Harsh Environments
Smart contract-based access control for health care data vehicle Pattern Recognition using Machine & Deep Learning to Predict Car Model
Analysis of Women’s Safety in Indian Cities Using Machine Learning on Tweets
Analyzing and estimating the IPL winner using machine learning
Characterizing and predicting early reviewers for effective product marketing on eCommerce websites
Crime Data Analysis Using Machine Learning Models
Detection of fake online reviews using semi-supervised and supervised learning
Detection of Malicious Code Variants Based on Deep Learning
Detection and classification of fruit diseases using image processing & cloud computing
Grape Leaf Disease Identification using Machine Learning Techniques
Effective Heart Disease Prediction Using Hybrid Machine Learning Techniques
Missing Child Identification System using Deep Learning and Multiclass SVM
Music & Movie Recommendation
Network Intrusion Detection using Supervised Machine Learning Technique with Feature Selection
Prediction of Hepatitis Disease Using Machine Learning Technique
Skin Disease Detection and Classification Using Deep Learning Algorithms
Spammer Detection and Fake User Identification on Social Networks
Using Deep Learning to Predict Plant Growth and Yield in Greenhouse Environments
Using Data Mining Techniques to Predict Student Performance to Support Decision
Making in University Admission Systems

Latest CSE Python Projects on ML & AI – 2022

An automated system to limit COVID-19 using facial mask detection in a smart city network
Analysis and Prediction of COVID-19 using Time Series Forecasting
Analysis and prediction of occupational accidents
Analysis of Women’s Safety in Indian Cities Using Twitter Data
Artist Recommendation System using Collaborative Filtering
A-Secure-Searchable-Encryption-Framework-for-Privacy-Critical-Cloud-Storage-Services
Authorship Identification Using Text Mining
Automated word prediction in Telugu language using a Statistical approach
Biometric Steganography Using Mid Position Value Technique
Classification of COVID-19 Using Chest X-ray
Covid-19 future forecasting
Covid19 Social Distance Monitoring System Using YOLO
Credit Card Fraud Detection
Detection and Classification of Fruit Diseases
Diabetic Retinopathy Detection
Early prediction of Diabetes Mellitus using intensive care data to improve clinical decisions
E-Certificates Issue Services Using Blockchain
Face to Emoji using OpenCV and haar cascade classifier
Facial Emotion Recognition using ML Algorithms
Fake Job Recruitment Detection
Fusion Approach to Infrared and Visible Images
High-value customers identification for an E-Commerce company
Image Caption And Speech Generation Using LSTM and GTTS API
Image Deblurring
IoT based Attendance System using Blockchain
Malicious Application Detection Using Machine Learning
Money Laundering Detection Using Machine Learning Methods
Music Genre Classification using ML algorithms
Object Detection and Alert System for Visually Impaired People
Object detection and localization
Offline Signature Forgery Detection
People count on Surveillance Video
Politeness Transfer A Tag and Generate Approach
Prediction Analysis Using Support Vector Machine In Cardiovascular Ailments
Product Recommendation System Using ML Technique
Rice Crop Disease Detection
Sign Language Translator for Speech Impaired
Skin Lesion Classification
StellarStudent Social Web Application for Colleges
Survival of Heart Failure Prediction Using Feature Scaling
Text Summarization Method
Text to Image Generator using GAN
Vessel detection from spaceborne images
HR Analysis of Employee Attrition & Performance
Analysis of Forest Fire Area Prediction
Prediction of Chronic Kidney Disease Using Machine Learning
Predicting the Resale Price of a Car
Prediction Of Diabetes Mellitus
Prediction of Exact Niche using Bank Data
Prediction of Insurance Claims using Health Analysis
Sales Prophesy in Business using ML
Prediction Of Taxi Fare Using Exploratory Analysis
Prediction of customer churn in the telecom industry
Estimation Of Wine Quality Using Chemical Analysis Data
The Simpsons Character Recognition
IMDB Movie Review Analysis Using Bidirectional LSTM
Pattern Recognition of IRIS Flower based on Artificial Intelligence
Recommendation System
Zomato Review System
Drug Review Prediction
Web Traffic Prediction
Building a Model for MNIST Dataset using Convolutional
Toxic Comment Detection
Sonar Prediction
Accuracy analysis using Fashion MNIST dataset
Survival Analysis Of Diabetes
Wine Quality Prediction
Bank Churn Model
Survival Analysis (Human Breast Cancer Prediction)
Black Friday Sales Data Analysis Prediction
Bank Marketing
Breast Cancer Classification
Company Turnover Predictor
Pneumonia Prediction
Employee Attrition Prediction
Intelligent Album Creator
Predicting The Readmission To Hospitals For Diabetic Patients
Communication Through Gesture
Twitter Sentiment Analysis
Smart Security System Using Image Recognition
Text Generation
Crop Health Assistant using Artificial intelligence
Air Quality Prediction
Suspicious activity Detector
Watch Bot
Pneumonia Detection Using CNN
Sentiment analysis of Twitter comments
Motor Health Prediction
Real or fake face Detection
predicting simpson Characteristics
The Sorting Hat
Analysis of Airline reviews using NLP
Heart Disease Prediction
Cereal Analysis
Fertilizer Prediction
Turbine power prediction
Kidney Disease Analysis
Analysis of Accidents in 2017
A Machine Learning Approach to Predict Crime Rate Analysis
Advertising Based on Usage
Life Expectancy
Abalone Age Prediction
Exploring the Bitcoin Cryptocurrency
Predicting High Potential Employees and Employees at Risk
Insurance Purchase Prediction
MNIST Classification using CNN
Vehicle resale value Prediction
University Admission Prediction
Automatic Challan Generation
Smart investment Prediction
Smart Security using Artificial Intelligence
Bike Buyer Prediction
Best Crop Prediction
Taxi Fare Prediction
Resale Values of Predicting Cars
Power Consumption Prediction
Health Insurance Prediction
Health Monitoring System
Crime Rate Prediction
Assert Failure Prediction
Adult Census Income Prediction Using Random Forest
Smart Predictors
Nutrition Analysis Using Image Classification
Liver Patient Analysis
Flood Prediction
Customer Recommendation System
Crop Protection Using Deep Learning Techniques
Communication Using Gestures
Car Performance Prediction
Avalanche Prediction
3D Printer Material Prediction
Income Prediction Using Random Forest
Term Deposit Subscription Prediction
Advertisement popularity Prediction
Google Review of Places Certificates
Blood Cell Image Prediction

March 8, 2022February 9, 2023

Restaurant Management System Database Project using PHP, MySQL/MS Access

The aim of this project is to create a Restaurant Management Database (RMD) is an online application for restaurant management. This system wakes to provide service facilities to restaurants and to the customer. The services which are provided are food ordering, reservation of the table by the customer through the system online, menu information management, and report.

The main goal of this project is to make the customers satisfied to get the food from anywhere

To develop the online ordering and reservation system in restaurants.
To develop a user interface for an online restaurant management system to provide online menu information for customers to order

Project requirement

The basic requirement is to make the customers log in and order their favorite food online. To do so they need to look at the menu. Thus, there must be a menu with quantity and price options. Thus, these basic requirements are addressed for now.

Mission statement

The objective is to help the customer to order food online and get them delivered through an interactive application.

Objectives

The application should support customer registration
Registered customers should gain access through username and password
There must be an interactive menu with all details
Customers should be allowed to browse the menu
Customers can place an order by adding the menu item to the cart.

Interview Questions

What tables are needed for the system?
How will we ensure that there are no duplicate records in the database?
How will the customer know whether the item is available or not?
What navigational options are good for customers?
How do secure customer payment information and personal information?

ER Diagram

Tables

Product ID	Product name	Details	Status	Price
Int	char	char	char	Currency

user_id	username	password	address	mobileno	email id
int	char	varchar	varchar	number	varchar

cart_id	user_id	product details	product_id	quantity	price
int	int	char	int	int	currency

delivery_id	user_id	delviery status	duedate & time
int	int	varchar	date time

Reservation_id	User_id	Name	date	table choice	time
int	int	Varchar	date	int	time

Output Results:

Admin Dashboard:

All Orders Details Page:

Restaurant Management Table booking Admin Page:

Popular Dishes Page:

Here you can freely download the complete Restaurant Management System project Source code with both MySQL and MSAccess database code, User Manual Report.

March 7, 2022March 29, 2022

Library Management System Database Project using PHP & MySQL/MS Access

EXECUTIVE SUMMARY

Libraries are popular places where there are numerous books to keep track of. Not only books but the librarian is also required to keep track of users, books that were taken, due dates, etc. Making manual entries and keeping track of due dates is not easy when the user’s size is more. It becomes complex when there are numerous books and when the members of the library are increasing. Tracking members and books details become time-consuming and are prone to error. Thus, the objective of the project is to come up with easy to use and user-friendly database management application that helps the librarian with all the tasks related to efficient library management.

The application is expected to be a secure, user-friendly, and easy-to-use database application for library management, that is capable of performing library tasks like adding books, searching books, issuing books, returning books, and generating fines and reports. The application is expected to simplify the librarian tasks, reduce errors in bookkeeping, and make the task interactive and interesting.

The project management and development shall be iterative and shall employ the RAD application development methodology. The rapid Application Development methodology is a fast way of completing a project prototype with more emphasis on the design phase and application development. With RAD in use, the application development shall be broken down into smaller tasks that are easily manageable and monitored.

At the end of the project, there shall be a live web-based application with an easy-to-use and rich navigational front end designed with JavaScript and PHP and a back end with My SQL. Both platforms are open-free and thus making applications cost-effective.

PROJECT PROPOSAL

1. Statement of Work

1.1 Project Background

Database management systems have become vital for organizations to manage large databases and to perform transactions upon such large data. These database applications not only store data, but also manage them, synchronize them, and help in information retrieval without errors. They reduce manual efforts and enhance the quality of information retrieval services. Due to this reason, they are widely used in almost all sectors. Libraries are popular places where there are numerous books to keep track of. Not only books but the librarian is also required to keep track of users, books that were taken, due dates, etc. Making manual entries and keeping track of due dates is not easy when the user’s size is more. Thus, this work implements a library management system database application that helps the librarian manage all tasks in an efficient and user-friendly manner.

1.2 Vision

The project vision is to come up with a library management system database application that does the jobs of the librarian like maintaining book records, maintaining user records, due dates, fines, etc. efficiently and in a quick time without errors.

1.3 Project Objective

The objective of the project is to come up with easy to use and user-friendly database management application that helps the librarian with all the tasks related to efficient library management.

1.4 Project Scope

The project scope is:

To have a user-friendly and easy-to-use database application for library management.
To have an application that secures data records.
To have an application that generates reports on books, due reports, fine reports, etc. easily.
To have an application that can track the user activities and their records easily.
To have an application that reduces the errors and efforts of the librarian.
The application shall have a login and password for allowing only authorized users to access the application.

1.5 Value proposition

This application shall reduce the manual errors and efforts of the librarian. It shall provide the end-user with the abstraction of all the database details and thus simplify the task as a set of small activities. It shall enhance the quality of the services of the library. It shall keep better track of book availability, dues, fines, etc., and enhance the quality of response to the user by the librarian.

1.6 Technical details

Existing system:

Currently, the library system in use is a mixture of both file-based and manual-based work. Excel files are used to keep records of books, library users, and library user transactions. With such a system the key challenges are

More duplicate records as there is no control on duplicity.
inconsistent records are more as there is no referential integrity control
Time-consuming tasks as a simple tasks may require extensive search and a lot of entries.
such a system is prone to errors due to inconsistencies in data
Lack of user-friendly GUI: the system lacks a GUI that facilitates the end-user by providing an abstraction of the back end. This abstraction of the backend makes the end-user efficiently do his or her job without worrying about other details.
Data loss risk: if the data is lost it becomes impossible to recover the data from excel files.
Generating reports of books or users with fines becomes difficult and time-consuming as it requires multiple worksheets to be navigated and used. Due to the cumbersome job, the accuracy of the reports is low.

Thus, it is proposed to come up with an efficient, user-friendly, library management system that makes end-user tasks easy, error-free, and fast. The system shall follow the norms of a database management system ensuring integrity, consistency, and no duplicates of data.

Thus, the system shall have a simple to use GUI as the front end. Database application shall be developed using My SQL. The front-end JavaScript & PHP. The operating system is Microsoft Windows 7 and above with either 32 or 63 bits configuration.

1.7 Challenges

The Key challenges the project development may face are as follows:

The existing data from excel can be imported to MY SQL database. But to ensure referential integrity of the data it is essential that the database follows norms of having the primary key, removing duplicates ensuring consistency, etc. Thus, it may require the excel data to pre-process, convert and then migrate it to MY SQL.
The end-user may be new to GUI and API usage. Thus, there may be a need to train the end-user with the application.
Issues may arise from front-end and back-end connectivity. This can be managed through proper coding.
The system development may face hurdles if its development process is not managed and monitored properly. It is essential to have a Gantt chart with proper milestones to monitor the activities.

1.8 Organization of the proposal

This project proposal is divided into sections. The first section was a background of the project giving details on its vision, value proposition, objectives, and scope.

Sections 2 to 6 details are as follows:

Section 2: This section gives in detail the project methodology and the implementation plan. In this section the database design principles and methodology employed is elaborated, the way the application is developed is defined and the key areas of the application along with key features and functionalities are explained through various diagrams. It shall also contain the test plans for the application.
Section 3: This section defines the key deliverables from this project. It thus gives details on what the project shall give for a specified set of inputs and how the result is used.
Section 4: This section defines how the application project management shall be carried out. It shall give details of the milestones to be achieved and details on project monitoring and evaluation.
Section 5:This section gives details on the project team and their roles
Section 6: This section is about the tools and the supporting platforms that make the application implementation possible.

2. Methodology and Implementation Plan

The database design and implementation process shall be done on the MySQL database management platform. The project management and development shall be iterative and shall employ the RAD application development methodology. The rapid Application Development methodology is a fast way of completing a project prototype with more emphasis on the design phase and application development. With RAD in use, the application development shall be broken down into smaller tasks that are easily manageable and monitored. With regular communication and feedback among the team, the application development becomes faster and more efficient with RAD. The key phases of application development thus are as follows:

Requirement analysis
Application Design
Rapid construction & Testing
Going live

2.1 Requirements Analysis

This is the first phase of the application development lifecycle. The objective of this phase is to gather the end-user requirements and the expectations of the stakeholders from the library management system. These are listed in the form of functional and non-functional requirements.

Functional requirements

Login/logout: The application should provide user-based login and logout mechanism. Thus authorized users can login into the system.
Add book: This shall allow the librarian to add the book record into the database.
Manage book: This shall allow the librarian to edit or delete any book record in the database.
Search book: This shall allow the user to search for a book through book name, author name, or both.
View book: This shall allow viewing all the books, new books, old books, damaged books, lost books.
Issue Book: This shall make an entry of the member with the books browed and the due to return.
Accept Return book: This shall enter the return date and ensure that the book is successfully returned.
View issued books: This shall list the books that have been borrowed with their member name and due date.
View returned books: This shall consist of lists of returned books.
Add member: This shall help the librarian to add a new member and categorize them.
Manage members: This shall make changes in the member record like deactivating them, deleting them, and editing their information.
Search member: this shall help in searching the library member record
View fine details: This shall generate a fine for those borrowed books with member details that skipped their due dates.
Generate report: this shall allow the system admin to generate user reports, book reports, borrower reports, fine list reports, etc., and download them.

Non-functional requirements

Security: the application should endure data security and user access security.
Navigational requirement: The navigational options of the system should be user-friendly and easy to use.
Database requirements: The database should be accessed by only secure and authorized users. The database should be available, consistent, have no duplicate entries, and should give error-free output.
Performance requirement: the system should be responding with a proper message thus giving an idea to the user of the interactions.

Use case diagram

Following is the use case diagram of the system

Figure 1: Use case diagram

Activity diagram: Consider the process of adding a book record

The steps of adding the book record to the database are as follows:

Figure 2: Activity diagram

1.1 Conceptual Design

ER diagram for the Library Management System

Figure 4: ER Diagram

1.2 DBMS cost/benefit analysis

The technology that shall be used for the proposed system is the MySQL database management system. It is used because it is simple to use, supports a large database system, and has compatibility with various programming languages that can support the front-end design.

The front-end technology relies on JavaScript and PHP. These are selected as they offer good design options, navigational options, making the user interface interactive and more appealing. Thus, with consideration to having a good and user-friendly interface, these technologies are selected.

The other options were to use the Oracle database management system and MS Access database management system. But MS access system was ruled out due to its failure to support large databases and its difficulty in providing front-end connection to programing and scripting languages like PHP. Oracle was ruled out as it is tough to use and is costly when compared to MY SQL which is free and open source.

Product	Cost
Option 1 Oracle	Standard Edition One – $5,800 per unit (sockets)
Option 2 MS Access	$109.99 per license
Option 3 My SQL	Free
Front end option 1 Java and swings	Free but requires programming expertise
Front end option 2 PHP and Javascript	Free requires scripting expertise
Front end option 3 ASP.NET	Free requires scripting expertise

Based on the above and the available expertise, the project is built using MY SQL, PHP ad Java Scripts is selected.

1.3 Logical Design

The main tables proposed for the system are as follows:

User table:

User_id	Username	password	firstname	Lastname
Primary key int	Varchar(100)	Varchar(100)	Varchar(100)	Varchar(100)

Book table

book_id	Book_title	Author	Book_copies	Book_pub	Publisher_name	Isbn	Copyright_year	status	Category_id
Primary key int	Varchar(100)	Varchar(100)	int	Varchar(100)	Varchar(100)	Varchar(50)	int	Varchar(30)

Borrow

borrow_id	Date_borrow	Due_date	Member_id
Primary key int	Date	date	Int

Member

member_id	Firstname	lastname	Gender	contact	address	type	Status
Primary key int	Varchar(100)	Varchar(100)	Varchar(100)	Varchar(100)	Varchar(100)	Varchar(100)	Varchar(100)

Return

Return_id	Book-id	Borrow_id	Borrow_status	Date_return	Fine
Primary key int	int	Int	Varchar(100)	Date	int

1.4 Physical Design

The proposed system shall have a user interface form designed and developed using JavaScript and PHP scripting languages. The key issue in this design is the special emphasis on navigational options, proper usage of arrows and icons so that the user can operate the system without any hurdles. The user navigation should give control freedom to the user. It should not be complex and should be user-friendly.

The database backend is designed and developed using MySQL. It can be problematic to establish front and back-end connectivity while using the application. Thus, in such a case proper commands for the connection must be established.

1.5 Prototype

A sample prototype is as follows:

Front end admin login screen

Back end book table

Adding books

Adding members

1.6 Performance Evaluation

The Project is successful only if it is capable of giving expected results. Thus, the application is to be tested to ensure that it is executing as per expected objectives. The proposed application shall be using black-box testing wherein test cases shall be built and executed. The test cases shall test the user interfaces and each use case. If the expected results are achieved the application shall be assumed to be error-free and ready for launch. Otherwise, the test result recommendations shall be implemented.

2. Expected Result

At the end of the project completion following things shall be expected:

A back end designed and developed in MySQL with tables for users, members, books, return records, borrowing records, searching capabilities, and report generation.
A front end that is user-friendly, rich with icons, and is appealing to use. The front end shall be designed so that the user can perform the actions without any issues.
A fully functional application with both front end and back end connectivity capable of doing all the said tasks of use cases.
An application manual describing the ways to use the application
A cost-benefit analysis describing the feasibility of the product in economic terms.
A requirement analysis documents and work breakdown structure.
A complete coding and scripting file
A test project report giving details of project implementation and test results.
Final project document

3. Project Management Approaches & Milestones

The objective of project management is to ensure that the project development is planned well and executed properly to ensure quality and timely delivery. For proper management of the application development, the project development process is broken down into small tasks. Each task is grouped as milestones. For each milestone, a deadline is assigned and an expected outcome checklist is prepared.

Once a milestone is reached, the checklist is evaluated and the reviews are done with the team members. The outcome of the checklist evaluations and the review are recommended and implemented to ensure that the project is meeting its quality standards.

To ensure the tasks are executed on time a Gantt chart is used. The Gantt chart for the project is as follows:

Figure 4: Gantt Chart

Here you can download the entire project source code, User Manual Report.

March 6, 2022February 9, 2023

Student School Record Keeping System Application Database Project

Project Background

Efficient management of student-related information becomes challenging for any educational organization when the volume of data and operations over that data increases. Information systems and database systems are the needed tools that help in the efficient management of such large volumes of data. These systems not only manage the data but even help in the easy retrieval and processing of useful information.

Vision

This project work vision is thus to come up with an efficient database management system that is capable of maintaining student records for an educational organization.

Project Objective

The objective of designing and implementing such a database management system is to manage the student records in a proper and organized manner, enable data flow and information flow among various activities related to student information processing, and secure the student data.

The project scope is as follows:

To come up with an efficient database management application for student record management.
The application shall help to add student records like their personal information, fees-related information, scholarship-related information, course-related information, and marks-related information.
the application shall allow to edit or delete any student record based on authorized permission
The application shall allow generating reports like marks statistics, feed duellist of students, etc.
The application shall have access based on authorization and role-based authorization shall be enabled for read and write processes.
The key information like payment, and a password shall be stored in encrypted form for security purposes.

Value proposition

This database application shall help the educational organization to keep track of all the student records and manage them in a more efficient manner. It shall reduce the number of manual errors, do the student record processing task in quick time and thus reduce human effort. It shall enhance the student and teacher experience in generating reports and getting key notifications.

Technical development plan

The existing system makes use of excel based records. These are file-based systems. The biggest challenge in this system is that there are more duplicate records due to the lack of any control mechanisms that control duplicates. Database management system makes use of a primary key that is unique and it is capable of identifying any unique record. Thus, it is a way of eliminating duplicates.

The existing system is not user-friendly to use as they lack user-friendly APIs. With supporting scripting languages like PHP, CSS, and Java Script it is possible to come up with an interactive GUI. Such GUI helps the user to do the tasks in a more efficient manner.

Thus, the proposed system shall make use of the following:

Front end: PHP

Back end: MySQL

Web Server: Wamp server

Operating system: Windows 7 and above.

Development Methodology

The application development shall adopt the Rapid application development methodology and develop the application in a small set of tasks. The objective shall be to come up with a rapid prototype and iterate it as per the testing results. The development process shall begin from starting from system requirements, system design, coding, testing & debugging implementation & maintenance. It shall be an iterative process.

The development tasks shall be small manageable tasks. This shall make project monitoring and management easier.

Requirements Analysis

The first functional requirement of the project is to have an application capable of adding and managing student records.

Thus, the application should allow Admin to do the following

Add student: to should allow the admin to add student details like name, enrolment id, contact address, course enrolled, subjects, date of birth, address, gender, and other details.

Figure 1: Activity diagram depicting adding or deleting student

Manage student: to allow the admin to view student records, delete existing student records, and edit or update any existing student records.
The application should allow the admin to add marks, manage marks and generate a result
The admin can add subject or course details.
The application should allow the admin to generate lists of students who have not paid fees and those who have availed of scholarships.
Manage user records and change passwords

Students can do the following:

The application should allow students to register,
view result and download result

Conceptual diagram

Figure 2: Student record system overall architectural diagram

Tasks of Students and Admin are explained in the figure below:

Figure 3: Task in detail

Interview Questions

With front-end designer:

What entries are needed for a student form wherein details can be entered?
What entries are needed for the resulting form so that admin can add marks for the students?
What entries are needed for the course and subject form?

With back-end designer:

What columns should be used for a student table, result-in table, course table, user table, and fees table?
Which column should be the primary key to help in unique row identification?
How to connect the front end and back end?

Tables

Student table:

Student_id	first name	last name	gender	age	Date of birth	Contact no	address	City	CourseId	email	Password
Primary Key Varchar (10) Unique	Varchar (30)	Varchar (30)	Varchar (30)	int	date	int	Varchar (100)	Varchar (30)	Varchar (30)	Varchar (30)	Varchar (30)

Course table:

Course_id	Course name	Subjects
Primary Key Varchar (10) Unique	Varchar (30)	Varchar (30)

Subject table:

Subject_id	Subject name	Course_id
Primary Key Varchar (10) Unique	Varchar (30)	Varchar (30)

User table:

User_id	username	password	role
Primary Key Varchar (10) Unique	Varchar (30)	Varchar (30)	Varchar (30)

Result table:

Result_id	Student_id	first name	last name	Course_id	Subject_id	Marks obtained	Total marks	Grade
Primary Key Varchar (10) Unique	Varchar (30)	Varchar (30)		Varchar (30)	Varchar (30)	Int	int	Int

Student Record System Application Manual

Software required: Wamp Server, MS Access, ODBC driver, and Windows 7 or above operating system

Extract the Zip file as an SRS folder.
Install Wamp server
In the www folder of the Wamp server Copy and paste SRS complete folder
Open the Wamp server and start all the services
The SRS folder has a database file named srms.mdb file.
Open odbc driver by clicking on data sources.
Click Add and select Microsoft Access Driver .mdb and accdb.
Enter the Data source name as srms and select the folder path where the srms.mdb file is i.e. C:wamp/www/SRA/srms.mdb
Click finish and see that the srms.mdb is listed as the new database.
Now open a web browser and type URL localhost/SRS

This shall open the home page

The admin can enter the application through username and password as admin and admin

From the dashboard the admin can navigate to any sections like course, fees, subjects, students, results, etc.

For example Admin wants to add a student

The student form opens wherein the student details can be entered.

In this way results, courses, subjects, etc can be added and updated.

On the student end, the student can enter the application through the Roll number as a password and select the class from the dropdown list.

On entering details if the results are not ready you get

Otherwise

From where the result file can be downloaded.

ER DIAGRAM

Download Student School Record Keeping System Application Database PHP, MySQL, and MSAccess Project Code and Database.

March 10, 2021February 9, 2023

Teachers Tracking system using Android APP

Nowadays there are many cases of teachers leaving school by signing in registers. Faking attendance is becoming common practice for teachers all over the country. Officials are not provided with a proper solution to solve this problem. This project explains an android application that is used to track the teachers working in schools and colleges. This application works on android mobile. The android application is based on GPS and SMS services in Android mobile.

The GPS service is used for tracking the exact location of the teacher. The GPS-based systems are used to track the location of teachers where GPS services are taken from google maps API. This application is divided into two modules admin and teacher, each module will have an android app with different features.

Admin can set location details for each teacher which are the location of school boundaries longitude and latitude values. When the teacher reaches that location admin will receive a notification on the android app. In this method, the admin can track each teacher’s position and improve efficiency in managing teachers in the govt education system.

Project objective:

Developing an android application that can help govt education department to manage teachers in colleges and schools more effectively by tracking and getting notifications of each teacher when they leave school or college and improve education standards.

Existing system:

Colleges and schools use attendance books as proof knowing if teachers are attending schools or colleges regularly based on this data employee’s salaries and other factors are calculated. But most of the teachers are manipulating attendance by signing records and leaving schools and colleges.

Disadvantages:

Attendance books with signature data are only considered as proof for teachers which can be manipulated in various ways.
Employee tracking data is not managed in a database for further reference.
There is no proof for teachers tracking information.
Existing applications are developed for tracking family members or tracking children and finding the destination of the user based on longitude and latitude values.

Proposed System:

In the proposed system, two applications are designed one for admin and one for teachers. Both of these modules will use Google GPS services from Google Maps. Live locations are always tracked in the teacher’s module where a notification system is available for admin. Admin sets locations for each teacher (school or college boundary locations) based on these values every time teachers’ longitude and latitude values are tracked and compared with existing values in the database. If longitude values are matched then the notification is sent to admin.

Advantages:

Easy to track with proof of each teacher who is leaving school or college.
Teachers’ attendance can be increased.

SOFTWARE REQUIREMENTS:

Operating system: Windows 7.
Coding Language: JAVA
Tool: Android Studio
Database: SQLite

February 27, 2021February 9, 2023

Detecting Impersonators in Examination Centres using AI

Detecting impersonators in examination halls is important to provide a better way of examination handling system which can help in reducing malpractices happening in examination centers. According to the latest news reports, 56 JEE candidates who are potential impersonators were detected by a national testing agency. In order to solve this problem, an effective method is required with less manpower.

With the advancement of machine learning and AI technology, it is easy to solve this problem. In this project we are developing an AI system where images of students are collected with names and hall ticket numbers are pre-trained using the KDTree algorithm and the model is saved. Whenever a student enters the classroom, the student should look at the camera and enter class, after the given time or class is filled the student’s information will store in a video file with the student’s name and hall ticket no. The video will have a user with a hall ticket no and name on each face. If the admin finds any unknown user tag on the face admin can recheck and trace impersonators.

Problem statement:

Existing system:

Information given in the hall ticket is used as verification to check if the student is the impersonator or not. Manual security checks performed are not perfect and sometimes students can even change images from the hall ticket.

Advantages:

Manual verification methods are used for checking personally for each student which is not possible to check each student personally.

Chances of changing images from hall tickets are possible which doesn’t have a verification method.

Proposed system:

In the proposed system initially, images of each student are collected and each dataset consists of 50 images of each student. These images are trained using kdtree algorithm using the image processing technique and the model is saved in the system this model can be used for automatic prediction of students in exam halls from live video or images.

Advantages:

The student verification process is fast and accurate with the least effort. Reduces impersonator’s issue with live verification.
The time taken for prediction and processing is less and prediction is done automatically using a trained model.
A trained model can be used to track live video and automates the process of detecting students at exam centers and display them in the video.

SOFTWARE REQUIREMENT:

Operating system: Windows XP/7/10
Coding Language: python
Development Kit anaconda
Library: Keras, OpenCV
Dataset: any student’s dataset

February 24, 2021February 9, 2023

Movie Character Recognition From Video And Images Project

Live tracking of characters from movies is important for automating the process of classification for user-friendly information management systems like online platforms where characters in a movie can be seen before watching the movie. At present manual method is used which can be automated using this movie character classification method. The objective of this work is to collect a dataset of any movie characters and train a model which captures the facial features of all characters and the model is saved for prediction.

For testing purposes, a real-time live video can be used to track characters. This application also works for images where users can give input as images of trained movie characters and get results with character names on the image as output. In this project for training dataset KDTree, the algorithm is used which takes images from a given folder and trains each image and saves the model into a dump file in the system. In the second stage using this trained model input image or input video is predicted with the model and the result is shown as a video or image.

Problem statement:

Classification of characters for each movie manually is a time taking process and the database should be managed.

Objective:

The objective of this project is to develop an automatic classification of characters after training from the dataset. If the one-time model is created it can be used for prediction at any time from images or video

Existing system:

In the existing system movie characters are managed in the database and which are used for displaying when required in this process database is the important to the time taken for processing is more.

Disadvantages:

The time taken for processing is more and the database should be managed and integrated with the required system whenever required.
This method includes the manual process of data collection and updating and deleting data.

Proposed system:

In the proposed system initially, a dataset of respected move characters is collected and each dataset consists of 50 images. These images are trained using the KDDTree algorithm using the image processing technique and the model is saved in the system this model can be used for the automatic prediction of characters from live video or images.

Advantages:

The time taken for prediction and processing is less and prediction is done automatically using a trained model.
A trained model can be used to track live video and automates the process of detecting characters and displays on screens.

SOFTWARE REQUIREMENTS:

Operating system: Windows XP/7/10

Coding Language: Python
Development Kit: Anaconda
Library: TensorFlow, Keras, OpenCV
Dataset: Any movie dataset

February 23, 2021February 9, 2023

Canteen Automation System using NLTK and Machine Learning

The canteen automation system project is designed to select the food items from a web application with cost, time of cooking, and give rating for products. This application is designed to help students to order food items without giving orders to waiters or going to the counter and giving orders. Most of the colleges don’t have order-taking system students should directly reach the counter and give an order which is time taking process in order to solve this problem this online order-booking system is designed.

As there will be many students who will be giving orders from different departments as a web application is designed with multiple admins, each department will have one admin who will take request and process request. Another problem is best food from today’s canteen menu can be known by checking ratings given by other users based on that students can give orders. Students can also give reviews for each food item along with ratings. NLT is used to calculate the sentiment of each review by taking the yelp dataset and applying machine learning and NLTK to calculate sentiment and store it in the database.

Proposed system:

In the proposed system food ordering is done online and each department has its own admin who handles requests on daily basis, users can give a rating of food items which will help other students to select the food item from the list. Sentiment analysis using Yelp data set and NLTK and Machine learning are used to store the sentiment of each review given by the student.

Advantages:

Helps students to give orders from any location inside the campus and save time by reaching the canteen based on the given cooking time from the application.
Sentiment analysis is done for reviews using NLTK and Machine Learning. Sentiment and Rating are useful for students to select food items.

SOFTWARE REQUIREMENTS:

Operating system: Windows XP/7/10

Coding Language: Html, JavaScript,
Development Kit: Flask Framework
Database: MySQL
Dataset: YELP
IDE: Anaconda prompt