http://localhost:8080/xmlui/handle/123456789/413 2026-06-23T06:19:24Z 2026-06-23T06:19:24Z http://localhost:8080/xmlui/handle/123456789/2098 2019-06-20T06:10:18Z 2018-12-01T00:00:00Z

Title: Encrypted graph based Keyword searching Technique Abstract: In this era cloud computing is widely used by many users, so the computing and storage services are moving from cloud to edges. In edge computing, data is processed by the device itself or by a local computer or server, rather than being transmitted to a data centre. To deal with this problem the proposed system provides solutions of data encryption at data owner side before outsourcing. If data owner is valid then cloud service provider will send the tokens to data owner and data owner will be able to outsource the data. Also, user can find appropriate file by using keyword search rather than searching by file name. The proposed system provides a searching technique called K-Nearest Keyword searching algorithm to search the file keyword instead of file name. If any user wants to read or access the data, the user will send request to data owner. At the time of registration user will be authenticated by service provider using K-Map method. After the confirmation of valid user, service provider sends request to data owner for accessing data and approval will be given by data owner.Then user will be able to download the original data by using K-Map secret key. Index term: Keyword searching, edge computing, K-Map

2018-12-01T00:00:00Z http://localhost:8080/xmlui/handle/123456789/2097 2019-06-20T05:59:54Z 2018-11-15T00:00:00Z

Title: Classification and Notification of Road Incidents Using Ensemble Approach Abstract: Normally many vehicle travels on road and number of traffic incidents occur which influences people journeying on that direction. The task of manual classification of these incidents takes more time which may be minimized the use of the system which classifies these incidents using machine learning algorithms. When the incident takes place administrator fills the information of it for dataset generation. This dataset is used for prediction of incident severity. The incidents are categorized for finding out severity using Naïve Bayes and k- Nearest Neighbour classifiers in an effort to discover and visualize frequent patterns in ancient incidents. The classification model accuracy will be progressed using k-fold cross validation. The ensemble approach of machine learning allows to apply different model which yields better results and reduce problem of overfitting by the combination of model. The system has an android software for consumer who's visiting. Even as traveling at the route, person gets notification concerning incidents like accident prone sector, slippery road beforehand and so on. In order that consumer can take suitable choices and saves time throughout touring.

2018-11-15T00:00:00Z