Data Analyze and Prediction Using Data Science Technique in Bank Loan Approval
Authors: Bhava Dharani. P, Dr. V. Ramesh Babu
Abstract
Anomaly detection relies on individuals’ behavior profiling and works by detecting any deviation from the norm. When used for online banking fraud detection, however, it mainly suffers from three disadvantages. The historical behavior data are often too limited to profile his/her behavior pattern. Due to the heterogeneous nature of transaction data, there lacks a uniform treatment of different kinds of attribute values, which becomes a potential barrier for model development and further usage. The transaction data are highly skewed, and it becomes a challenge to utilize the label information effectively. The three disadvantages result in both poor generalization and high false positive rate of anomaly detection, and we propose a ranking metric embedding based multi-contextual behavior profiling (ReMEMBeR) model to battle them effectively. With the idea of collaborative filtering, for an individual, information from other similar individuals can be used to establish his/her behavior profile. The proposed model can, thus, integrate the multi- contextual behavior patterns and allow transactions to be examined under the different contexts. Extensive experiments on a real-world online banking transaction dataset demonstrate that our model not only outperforms benchmarks on all metrics but also can be combined with them to achieve even better performance.
Disaster Management System using Smart Phones
Authors: Kethineni Keerthi, Appisetty Pavan Kumar, Narni Siva Srinivas, Katta Venkata Sai Tharun, Jajula Bhuvaneswara Rao
Abstract
Recently, the world is facing more risk of natural disasters as a result of ongoing climate changes. One of the most critical obstacles in disaster mitigation (especially rescue operation) is lack of communication and localization of survivors in disaster sites. This paper develops a disaster rescue platform for quick and accurate rescue operation with utilizing direct communication on smart hand-held devices such as Bluetooth and Wi-Fi. Specifically, we attempt to design an application-layer ad hoc network over smart devices without relying on centralized cellular networks or wireless access points. This study also incorporates a mobile localization algorithm to effectively perform disaster rescue objectives. Specifically, it aims (1) to accurately locate survivors, (2) to help rescuers to find victims quickly, and (3) to minimize calculation overheads for power saving on smart devices. This article verifies the proposed approach with presenting simulation and implementation results compared to other studies.
Addressing the Solid Waste Management Challenge in India
Author: Dr. Anjali Gaidhane
Abstract
Solid waste management is the most significant challenge that we as human society are facing in the 21st century as urbanization, industrialization and economic growth have resulted in generation of huge solid waste which is growing at an unprecedented scale on daily basis. Solid waste management has emerged as one of the greatest crises as there is a sharp contrast between the waste generated and safe and sustainable ways to dispose it off. The problem is further compounded by the fact that there is a huge gap between the increasing population generating waste and inadequate means and services available to dispose it. The inefficiency of current solid waste management mechanisms is posing a serious threat to public health, environment and quality of life of the citizens. The per capita waste generation rate is increasing on an everyday basis due to changing lifestyles and increased purchasing power of people in general, adding a huge stress on available natural, infrastructural and financial resources. Almost 21 months of COVID 19 pandemic has added bio-medical waste to the already existing grave situation of waste management.The present research paper looks into the various challenges posed by waste management, success stories and issues associated with the same.
QR Code Generator and Detector using Python
Authors: Mr. B. Naga Raju, N.Venkatesh, G. Dhana Lakshmi, N. Sai Chand, D. Haritha
Abstract
QR codes were developed in the 1990s as a way to provide more information than a standard barcode. QR code was invented by a Japanese engineer Masahiro Hara from automobile manufacturer Denso Wave in the year 1994 to track the movement of car parts. QR codes consist of black squares arranged in a grid (matrix) on a white background and are read by specialized software that is able to extract data from the patterns that are present in the matrix. These codes are capable of containing more information than traditional barcodes, and primarily handle four modes of data: alphanumeric, numeric, binary, and Kanji. QR code means Quick Response Code. Now a days it is used widely in many organizations. QR codes are frequently used to track information about products in a supply chain. QR Code has increased in popularity in the later 2010s with improvement in optical capabilities of mobile phones and their wide adoption.Nowadays, QR codes are being used for wide variety of applications like, make online payments, check hotel menu, share wifi password, obtain price and other details of products etc. QR Codes have become so popular that now every new smartphone comes within built QR code reader. Keywords— Android Operating System, Mobile Network Operators, Mobile Application Scanner, Quick Response Code (QR), Python Flask Framework, Recharge Vouchers, Smart Phone