SECURITY SURVEY AND STORAGE IMPROVEMENT IN MOBILE CLOUD COMPUTING
Abstract
We know now we are ready to go with new technology over currently used technology that is computer cloud computing (personal computer wi-fi network). In this paper implementing the heart of any technology i.e. for storage & security purpose we must define the client side and server side framework. This framework is must to form any cloud. At the time of implementation considering the power consumption and database availability terms, also we will check status of mobile application about its usage in device and manage storage by interfacing with server .I would like to express the technique implemented in this paper i.e. current technology, Mobile threats, security, storage, Data privacy.
Predictive Analysis of Air Pollution using Collaborative Filtering Prediction Algorithm
Samieksha Sharma1,Akanksha Gupta 2Mrs. Monia Digra3 ,MBS, College.
Abstract
Growing trends in Air pollution is possessing threat to environment. Various Researchers have extended their work in predicting air pollution using various predictive analytics. In this paper, we are implementing a predictive model for monitoring air pollution level in different cities of India and publishing it as a web service .The algorithm being used is Collaborative Filtering Prediction Algorithm. A comparison has also been carried out in different predictive analytics mainly using Machine Learning techniques such as regression and Deep Learning Technique and Collaborative filtering technique Index Terms — Collaborative filtering, Pearson Coefficient, Heuristics, Deep learning.
Machine learning based digitization of data in banking enviornment
Miss. Shruti Kadukar BE, Information technology Rajiv Gandhi Institute of technology Affiliated to Mumbai University Mumbai,India
Abstract
Digitization of handwritten and printed documents used in financial institutions, using optical character recognition (OCR) and artificial neural networks (ANN). Image scanner is used to scan the documents which store the document into an image format. In this paper OCR in combination with ANN is used to recognize the characters from the documents, the output in stored in .xml file format. This file is first converted and stored in excel file format, second the banking management system integrates the obtained excel data. This translated data is stored in database, which further performs various procedures on database with help of SQL operations. The output obtained is linked to an android platform, which can be further used for different applications using machine learning code. The current banking system is tedious and error prone. This paper aims to create a system which provides higher accuracy and efficiency. The proposed approach will revolutionize the current approach of banking system. .