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Review Paper

Credit card fraud detection using random forest and isolation forest algorithms

The project is mainly focussed on credit card fraud detection in the real world. The phenomenal growth in the number of credit card transactions has recently led to a considerable rise in fraudulent activities. The purpose is to obtain goods without paying or to obtain unauthorized funds from an account. As the usage of credit cards is increasing more, the chances of credit card frauds are also increasing dramatically. The credit card system is most vulnerable to fraud. These credit card frauds cost financial companies and consumers a very huge amount of money annually, fraudsters always try to find new methods and tricks to commit these illegal and outlaw actions. Online transaction fraud detection is the most challenging issue for banks and financial companies. So it is essential for banks and financial companies to have efficient fraud detection systems to reduce their losses due to these credit card fraud transactions. Various approaches have been found by many researchers to date to detect these frauds and to reduce them. Comparison of Local Outlier Factor and Isolation Factor algorithms using python and their detailed experimental results are proposed in this paper. After the analysis of the dataset we got the accuracy of 99% by random forest and 76% by Isolation Forest.

Published by: Modekurthi Susmitha, Kamala Beena Mukiri, Muraharirao Harshita, Potnuru Rishita, M. Sion Kumari

Author: Modekurthi Susmitha

Paper ID: V6I3-1333

Paper Status: published

Published: May 29, 2020

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Research Paper

Detection of Diabetic Retinopathy

Diabetic Retinopathy (DR) is an eye ailment that influences eighty to eighty-five percent of the patients having diabetes for more than ten years. The common process for analysis and detection of diabetic retinopathy is through retinal fundus images. The raw retinal fundus images are very hard to process by machine learning algorithms. The pre-processing of raw retinal fundus images is performed through the extraction of the green channel, image enhancement, and resizing techniques. These features are also extracted from pre-processed images for quantitative analysis. The experiments was performed using Kaggle Diabetic Retinopathy dataset, and the results were evaluated by considering the mean value and standard deviation for extracted features. The result yielded an exudate area as the best-ranked feature with a mean difference of 1029.7. The result attributed due to its complete absence in normal diabetic images and its simultaneous presence in the four classes of diabetic retinopathy images namely mild, normal, and severe and Proliferative.

Published by: Balvanth Verma, Fahad Ahmed K., Tanari Sai Surya Teja, Dr. Aditya Kishore Saxena

Author: Balvanth Verma

Paper ID: V6I3-1343

Paper Status: published

Published: May 29, 2020

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Research Paper

Use of Discrete Sumudu Transform in cryptography

Cryptography is a method of protecting information and communications through the use of codes so that only those for whom the information is intended can read and process it. Modern cryptography uses sophisticated mathematical equations (algorithms) and secret keys to encrypt and decrypt data. Today, cryptography is used to provide secrecy and integrity to our data, and both authentication and anonymity to our communications. In this paper we have to encrypt and decrypt secret data using discrete Sumudu transformation and congruence modulo operator relation.

Published by: Sarada Mahesh Madhukar, Mundhe Ganesh Ashruji, Shaikh Jamir Salim

Author: Sarada Mahesh Madhukar

Paper ID: V6I3-1339

Paper Status: published

Published: May 28, 2020

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Research Paper

IoT based advance driverless seed sowing

Agriculture in India has a significant history. Today, India ranks second worldwide in far output. Still, agriculture is demographically the broadest economic sector and plays a significant role in the overall socio-economic fabric of India. In farming process, more labours are required to sow the seeds. The seed feed rate is more but the time required for the total operation is more and the total cost is increased due to labour. The conventional seed sowing machine is less efficient, time consuming. Today’s era is marching towards the rapid growth of all sectors including the agricultural sector. To meet the future food demands, the farmers have to implement the new techniques which will not affect the soil texture but will increase the overall crop production. The main aim of our project is to sow the seeds automatically so that the time required will be reduced and efficiency will be increased. All the components will be manufactured and then assembled together. After making the assembly, the testing will be carried out and then the result & conclusion will be drawn.6

Published by: Ajay Ramdas Kulkarni, Indrajeet Nikam, Yogesh Gudewar, Ajay Suryavanshi, Jasmine Bagban

Author: Ajay Ramdas Kulkarni

Paper ID: V6I3-1336

Paper Status: published

Published: May 28, 2020

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Research Paper

Real-time tracking of water tanker using GPS, GSM, and Arduino

Vehicle tracking system is a well-established technology in this era which is used by fleet system and owner of vehicle all over the world. It is a very safe and reliable technology. In this paper a real time tracking system is proposed. It is going to design a system which is used for tracking and positioning of any vehicle by using Global Positioning System (GPS) and Global System for Mobile Communication (GSM). The design is an embedded application, which will continuously monitor a moving vehicle and report the status of vehicle on demand. Tracking device used in real time vehicle location tracking is made up with Arduino Mega, SIM800A module and GPS module. For doing so the Arduino Mega is interfaced serially to a GSM module and GPS module. The GSM module is used to continuously send the position of the vehicle from remote place. The GPS module that uses satellite technology for its navigation system will continuously give data like longitude, latitude, time, direction of travel etc. Google map is used to view the position of vehicle on a digital mapping. This proposal has significant application for vehicle security, salesman tracking and private drivers.

Published by: Tanmay Srivastava, Deepak Shingote, Aashish Patil, Abhijit Mhatre, Upendra Patil

Author: Tanmay Srivastava

Paper ID: V6I3-1337

Paper Status: published

Published: May 28, 2020

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Research Paper

Face recognition based attendance system

In modern times, Automatic Face recognition (AFR) technologies have seen dramatic improvements in performance over the last few years. There are two reasons for this trend; the first is for saving the time in the classroom and accuracy in attendance will be maintained, and the second is availability of advanced technology it is more useful for the future generation. In simple words, it was a computer implementation for recognizing automatically whether the student is present in the classroom or not with the help of still image or video frame. We proposed an automatic attendance management system. It was completely based on face recognition and the face detection. This both detection and recognition will automatically detect the students in the classroom and mark the attendance by recognizing the person. This research includes for Face Detection of Students and system is based on CNN algorithms.

Published by: Raj Mhatre, Shashank Angane, Pallavi Vartak

Author: Raj Mhatre

Paper ID: V6I3-1334

Paper Status: published

Published: May 27, 2020

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