Online Donation Based Crowdfunding

ABSTRACT
Charity is an organization set up to provide help and raise money for those in need.
It is generosity and helpfulness, especially toward the needy or suffering.
Crowdfunding works through individuals or organizations who invest in (or donate
to). Crowdfunding projects in return for a potential profit or reward. Investing this
way can be risky, so make sure you know what you're doing. So, we are providing
trustworthy crowdfunding through government which is the funding of a project by a
large number of supporters who contribute a small amount. Only authenticated
recipients and the donor can request and donate money here. This system uses the
K-means clustering algorithm to cluster the similar data from a large scale of
datasets. After the completion of transaction process it will generate a certificate on
the name of donor. This system helps in automatically notifying the donors
according to their interest in a donation on any particular day, for example, on their
birthday, and appreciate the donors to further improve their sequence of donation.
iv
LIST OF FIGURES
FIGURE NO. FIGURE NAME PAGE NO.
3.1 Architecture Diagram 19
3.2 Sequence Diagram 20
3.3 Use Case Diagram 21
3.4 Activity Diagram 22
3.5 Collaboration Diagram 22
3.6 Data Flow Diagram 24
3.7 Class Diagram 24
4.1 Tomcat Web Application Manager 34
4.2 Registration page for user 35
4.3 Admin Page 35
4.4 Authentication Mail 36
4.5 Grouping of Categories 36
4.6 Notification 37
4.7 Bank Application 37
4.8 Certification 38
v
LIST OF ABBREVATIONS
JDK Java Development Toolkit
DEX Dalvik Executables
TCP Transmission Control Protocol
IP Internet Protocol
HTTP Hyper Text Transfer Protocol
ADT Android Development Tool
OCR Optical Character Recognition
vi
TABLE OF CONTENTS
CHAPTER NO. CHAPTER NAME PAGE NO.
ABSTRACT V
LIST OF FIGURES VI
LIST OF ABBERVATIONS VII
1 INTRODUCTION 1-3
1.1 SYNOPSIS 1
1.2 AIM OF THE PROJECT 2
1.3 EXISTING SYSTEM 2
1.4 PROBLEM DEFINITION 2
1.5 PROPOSED SYSTEM 2
1.6 ADVANTAGES 3
2 LITERATURE SURVEY 4-7
3 METHODOLOGY 8-37
3.1 PURPOSE AND SCOPE OF THE PROJECT 8
3.1.1 PRODUCT PERSPECTIVE 8
3.1.2 SYSTEM FEATURES 9
3.2 HARDWARE AND SOFTWARE 9

SPECIFICATION
HARDWARE REQUIREMENTS 9
SOFTWARE REQUIREMENTS 9
3.2.3 TECHNOLOGIES USED 9
3.3 ALGOROTHM DESCRIPTION 13
3.3.1 K-MEANS CLUSTERING 13
vii
3.3.2. OPTICAL CHARACTER 14
RECOGNITION
3.4 TESTING TECHNIQUES / TESTING 14

STRATEGIES
3.4.1 TESTING 14
3.4.2 SOFTWARE TESTING 15

STRATEGIES
3.5 SYSTEM DESIGN 17
3.5.1 ARCHITECTURE DIAGRAM 19
3.5.2 : SEQUENCE DIAGRAM 19
3.5.3 USE CASE DIAGRAM 20
3.5.4 ACTIVITY DIAGRAM 21
3.5.5 COLLABORATION DIAGRAM 22
3.5.6 DATA FLOW DIAGRAM 23
3.5.7 CLASS DIAGRAM 24
3.6 IMPLEMENTATION CONSTRAINTS AND 25

NONFUNCTIONAL REQUIREMENTS
3.6.1 CONSTRAINTS IN ANALYSIS 25
3.6.2 CONSTRAINTS IN DESIGN 25
3.6.3 CONSTRAINTS IN IMPLEMENTATION 25
3.6.4 PERFORMANCE REQUIREMENTS 25
3.6.5 SAFETY REQUIREMENTS 26
3.7 MODULES 26
3.7.1 MODULE DESCRIPTION 26
3.8 CODING AND TESTING 27
viii
3.8.1 CODING 27
3.8.2 CODING STANDARDS 27
3.8.2.1 NAMING CONVENTIONS 28
3.8.2.2 VALUE CONVENTIONS 28
3.8.2.3 SCRIPT WRITING AND 29

COMMENTING STANDARD
3.8.2.4 MESSAGE BOX FORMAT 29
3.8.3 TEST PROCEDURE 29
3.8.3.1 SYSTEM TESTING 29.
3.8.4 TEST DATA AND OUTPUT 30
3.8.4.1 UNIT TESTING 30
3.8.4.2 FUNCTIONAL TESTS 30
3.8.4.3 PERFORMANCE TEST 30
3.8.4.4 STRESS TEST 30
3.8.4.5 STRUCTURED TEST 30
3.8.4.6 INTEGRATION TESTING 31
3.9 SOFTWARE DEVELOPMENT PROCESS 31
3.9.1 LIFE CYCLE USED TO DEVELOP THIS 31

PROJECT
3.9.1.1 OVERVIEW OF SDLC 32
3.9.2 SYSTEMS DEVELOPMENT PHASES 32
4 RESULTS AND DISCUSSION 34-38
4.1 TOMCAT WEB APPLICATION MANAGER 34
4.2 REGISTRATION PAGE 34
ix
4.3 ADMIN PAGE 35
4.4 AUTHENTICATION MAIL 35
4.5 GROUPING OF CATEGORIES 36
4.6 NOTIFICATION 37
4.7 Bank Application 37
4.8 CERTIFICATE 38
5 CONCLUSION AND FUTURE WORK 39
5.1 CONCLUSION 39
5.2 FUTURE WORK 39
REFERENCES 40-41
APPENDIX 42-50
A.SAMPLE CODE 42
B. SCREEN SHOTS 48
C. PUBLICATION WITH PLAGARISM REPORT
52
x
CHAPTER 1
INTRODUCTION
Crowdfunding is a practice of raising funds from people to support this project

which has bought new life to charity, i.e., making it easy to donate any amount of
money to help across the globe. Donation-based crowdfunding is the most preferred
mode of fundraising. Crowdfunding through online platforms knows no boundaries,
and has the potential to go viral. The problem of high donor attrition i.e., many
donors donate only once or very few times within a rather short lifecycle and then
leave. Thus, it is an urgent task to analyze the factors and then further predict donor
behavior. In this process, presenting a focused study on the analysis of donation
recurrence and donor retention to predict the donor’s interest in a donation.
Specifically, it proposes a model, which has the details of the recipient, actual donor,
and the verifying person. After the donation process, every donor will get a proper
donation certificate approved by the government. The experimental results will
demonstrate the individual’s interest in the donation and appreciate them to donate
more in their future with a properly secured transaction with the support of the
government.
SYNOPSIS
The emergence of mobile cloud computing enables mobile users to offload

applications to nearby mobile resources to reduce energy consumption and improve
performance. However, due to mobility and cloudlet capacity, the connections
between a mobile user and mobile cloudlets can be mobile services. As a result,
offloading actions taken by the mobile user may fail (e.g., the user moves out of the
communication range of cloudlets). The mobile user has an application to be
executed. In the intermediate mobile act as a mobile provider to perform user tasks
with neighbors offload node. As the application is divided into code sections during
the execution the mobile user can dynamically decide to execute application phases
locally on the mobile device or offload to nearby cloudlet mobiles.
The incentive scheme uses a virtual currency, named FlopCoin, to
compensate devices whenever they execute an off loadable task. The amount of
2
the Flop Coins that are exchanged in each application offloading is determined by
individually rational and incentive method
AIM OF THE PROJECT
The main aim of this project is to demonstrate the effectiveness of analyzing and
predicting donation recurrence and donor retention in crowdfunding and providing a
proper trustworthy donation from the donors to the clients.
EXISTING SYSTEM
In the existing system, donation recurrence and donor retention were

predicted with the help of large-scale behavioral data collected from crowdfunding.
It uses the Joint Deep Survival model to integrate the heterogeneous since they are
highly relevant. This system demonstrates the effectiveness of analyzing and
predicting the donation recurrence and donor retention in crowdfunding and further
predicts the donors for future donation.
PROBLEM DEFINITION
 The retention of the donor is not known because they have not observed the
occurrence of donor attrition.
 The models may lose the abilities to capture the sequence dependence for such a
long time.
 The security for donors and recipients for requesting and donating money is not
mentioned.
PROPOSED SYSTEM
In this work, the client and the donor have to fill their details which will be
verified by the third party, the verifying agent appointed by the government. The
verifying agent will accept the details by verifying their details using Optical
character Recognition and proceeds the secured transaction from the donors to the
clients. This system uses the clustering algorithm to filter the data from a large scale
of datasets and uses the K-means Clustering algorithm for clustering similar data
from a large dataset. This system will automatically notify the donors on any
3
particular day, for example, on their birthday, and appreciate the donors to further
improve their sequence of donation.
ADVANTAGES
 By analyzing and predicting the donation recurrence and donor retention, the donors
can be predicted easily and are contacted for any need of money from the recipient.
 We are giving trustworthy security for recipients and donors to donate and request
money through this government charity.
 This system improves the interest in donations among donors. It appreciates and
notifies the donor to donate based on their interests.
4
 We designed optimal result vector selection algorithms and two respective efficient
online assignment algorithms for Accuracy and F-score.
Disadvantages:
We further investigate online assignment strategies, which enables optimal
task assignments.
TITLE: Net Cycle: Collective Evolution Inference in Heterogeneous Information

Networks
AUTHOR: Yizhou Zhang1,2 Yun Xiong1,2 Xiangnan Kong3 Yangyong Zhu1
Advantages:
 There are also approaches on time series prediction, which mainly exploits the
autocorrelation within an instance different time points during the inference
process.
 Empirical studies on real-world tasks demonstrate the effectiveness of the method.
Disadvantages:
 The Net Cycle method can not only predict the values of node response variables
for collective inference problems.
 The response variables of related instances can co-evolve over time and their
evolutions are not following a static correlation across

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ABSTRACT

3.1 Architecture Diagram 19

3.2 Sequence Diagram 20

3.3 Use Case Diagram 21

3.4 Activity Diagram 22

3.5 Collaboration Diagram 22

3.6 Data Flow Diagram 24

3.7 Class Diagram 24

4.1 Tomcat Web Application Manager 34

4.2 Registration page for user 35

4.3 Admin Page 35

4.4 Authentication Mail 36

4.5 Grouping of Categories 36

4.7 Bank Application 37

JDK Java Development Toolkit

DEX Dalvik Executables

TCP Transmission Control Protocol

HTTP Hyper Text Transfer Protocol

ADT Android Development Tool

OCR Optical Character Recognition

LIST OF ABBERVATIONS VII

1.2 AIM OF THE PROJECT 2

1.3 EXISTING SYSTEM 2

1.4 PROBLEM DEFINITION 2

1.5 PROPOSED SYSTEM 2

2 LITERATURE SURVEY 4-7

3.1 PURPOSE AND SCOPE OF THE PROJECT 8

3.1.1 PRODUCT PERSPECTIVE 8

3.1.2 SYSTEM FEATURES 9

3.2 HARDWARE AND SOFTWARE 9

3.2.3 TECHNOLOGIES USED 9

3.3 ALGOROTHM DESCRIPTION 13

3.3.1 K-MEANS CLUSTERING 13

3.4 TESTING TECHNIQUES / TESTING 14

3.4.2 SOFTWARE TESTING 15

3.5 SYSTEM DESIGN 17

3.5.1 ARCHITECTURE DIAGRAM 19

3.5.2 : SEQUENCE DIAGRAM 19

3.5.3 USE CASE DIAGRAM 20

3.5.4 ACTIVITY DIAGRAM 21

3.5.5 COLLABORATION DIAGRAM 22

3.5.6 DATA FLOW DIAGRAM 23

3.5.7 CLASS DIAGRAM 24

3.6 IMPLEMENTATION CONSTRAINTS AND 25

3.6.2 CONSTRAINTS IN DESIGN 25

3.6.3 CONSTRAINTS IN IMPLEMENTATION 25

3.6.4 PERFORMANCE REQUIREMENTS 25

3.6.5 SAFETY REQUIREMENTS 26

3.7.1 MODULE DESCRIPTION 26

3.8 CODING AND TESTING 27

3.8.2 CODING STANDARDS 27

3.8.2.1 NAMING CONVENTIONS 28

3.8.2.2 VALUE CONVENTIONS 28

3.8.2.3 SCRIPT WRITING AND 29

3.8.2.4 MESSAGE BOX FORMAT 29

3.8.3 TEST PROCEDURE 29

3.8.3.1 SYSTEM TESTING 29.

3.8.4 TEST DATA AND OUTPUT 30

3.8.4.1 UNIT TESTING 30

3.8.4.2 FUNCTIONAL TESTS 30

3.8.4.3 PERFORMANCE TEST 30

3.8.4.4 STRESS TEST 30

3.8.4.5 STRUCTURED TEST 30

3.8.4.6 INTEGRATION TESTING 31